Analysis of short tandem repeat allele frequencies in theUnited Arab Emirates populationJones, R. J. (2016). Analysis of short tandem repeat allele frequencies in the United Arab Emiratespopulation DOI: 10.4225/23/593f5758257be
DOI:10.4225/23/593f5758257be
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Analysis of Short Tandem Repeat Allele Frequencies in the United Arab
Emirates population
By Rebecca Jayne Jones (21524658)
Bachelor of Forensic Investigation (ECU), Graduate Diploma in Forensic Science
(UWA)
This thesis is presented for the degree of MASTER OF FORENSIC SCIENCE -
RESEARCH at The University of Western Australia
School of Anatomy, Physiology and Human Biology
2016
2
Thesis Declaration
I, Rebecca Jones, certify that:
This thesis has been substantially accomplished during enrolment in the degree.
This thesis does not contain material that has been accepted for the award of any other
degree or diploma in my name, in any university or other tertiary institution.
No part of this work will, in the future, be used in a submission in my name, for any
other degree or diploma in any university or other tertiary institute without the prior
approval of the University of Western Australia and where applicable, any partner
institution responsible for the joint-award of this degree.
This thesis does not contain any material previously published or written by another
person, except where due reference has been made in the text.
The work(s) are not in any way a violation or infringement of any copyright,
trademark, patent, or other rights whatsoever of any person. The research involving
human data reported in this thesis was assessed and approved by The University of
Western Australia Human Research Ethics Committee (RA/4/1/7778).
This thesis contains published work and/or work prepared for publication, some of
which has been co-authored.
Signature,
Rebecca Jones
03-11-2016
3
Abstract
Population-specific genetic research continues to progress with modern day
advancements in technology leading to the expansion in applications in forensic
identification, paternity testing and mapping of disease susceptibility genes. The
Middle East populations have been poorly studied but this region is significant as a
destination and route in early human migration out of Africa. The objective of the
research described in this thesis is to add to the existing knowledge in the region by
describing the genetic diversity that exists between ethnic groups of the United Arab
Emirates (UAE).
The UAE was chosen to study as it is situated in the Arabian Peninsula and located at
the crossroads of human migration out of the Horn of Africa as well as across the land
bridge that is now Egypt into Asia and Europe. The aims of the research were to
characterise allele frequencies and calculate forensic parameters for the UAE
populations and to improve our understanding of the genetic relationships between
different populations from the Middle East, North Africa and South Asia. In order to
address these aims, analyses of variable autosomal and Y-chromosome Short Tandem
Repeats (Y-STRs) were performed. A total of 996 UAE individuals were analysed
using 21 autosomal STR loci with the GlobalFiler® PCR Amplification Kit (Life
Technologies). The allele frequencies and statistical parameters were calculated and
results highlighted the genetic diversity of the UAE population. The combined power
of discrimination, exclusion and match probability were 0.999999999, 0.999999996
and 4.38 x 10-27 respectively. Locus-by-locus analysis of the autosomal STR allele
frequencies in the UAE population studied were then compared with published
autosomal data from the surrounding regions of North Africa, Middle East and South
4
Asia. The UAE population showed close genetic relationships with other Middle
Eastern populations and South Asian populations. Increasing the number of loci from
six up to 15 loci was found to provide more accuracy and better delineated the
observed genetic relationships.
The comparison of Y-STR haplotypes in the UAE population was subsequently
carried-out with the Y-Filer PLUS Amplification Kit (Life Technologies). Twenty-
seven Y-STR loci were analysed in 217 UAE individuals. Statistical parameters were
calculated using haplotype frequencies. Haplotype data was compared to populations
in the public Y-chromosome Haplotype Reference Database (YHRD) using MDS and
AMOVA (www.yhrd.org). This study is the first to highlight the use of data from 27
Y-STR loci on a UAE population. A high degree of genetic diversity was observed
in the UAE population based on typing from the 27 Y-STR loci with a Discrimination
Capacity of 95.40%. However, the number of populations with haplotypes comprising
27 Y-STR loci was limited and as such only haplotypes based on 17 Y-STR loci were
available for comparison from other populations in the regions immediately
surrounding the UAE. The reduction in the number of Y-STR loci used for haplotype
construction resulted in decreased discrimination capacity to 83.40%. Based on the
Y-haplotype distribution, the UAE population clustered with other Middle Eastern
populations. South Asian populations clustered closer to the UAE than the North
African populations. Variable results of some population genetic relationships were
observed when comparing the results between autosomal STR and Y-STR analyses.
The analyses described in this thesis provides insight into the relationship between the
Arab population of the UAE and others in the region surrounding the Middle East,
which goes partly to explaining human migration, historical events, trade and socio-
5
cultural relationships. The present research also establishes the importance of ongoing
research into Middle Eastern populations such as the UAE and the utility of increasing
sample size and number of sampled STR loci in population-based genetic applications.
6
Table of Contents
Acknowledgements………………………………………………………………...11
Statement of Candidate Contribution………………………………………….....13
Chapter One
1. General Introduction……………………………………………………………...16
1.1 Introduction……………………………………………………………..17
1.2 Aims and Hypothesis…………………………………………………....17
1.3 Thesis Structure…………………………………………………………18
1.4 References……………………………………………………………….20
Chapter Two
2. Literature Review: Genetic Analysis of People of the Middle East and the Use of
Short Tandem Repeats for Population Genetic Analyses…..………………………22
2.1 Introduction……………………………………………………………..23
2.2 Human Migration……………………………………………………….24
2.3 Impact of Bidirectional Migration through the Middle East…………....26
2.4 Historical and Trade Migration in the Middle East Region…………….28
2.5 Geographical Differentiation Determined by Different Genetic
Components…………………………………………………………………32
2.6 Distinguishing Closely Related Groups using Autosomal STRs………..34
2.7 Middle East Region and Worldwide Research…………………………..36
2.8 Conclusion………………………………………………………………38
7
2.9 References……………………………………………………………….39
Chapter Three
3. Population Genetics Data for 21 Autosomal STR loci for United Arab Emirates
(UAE) Population using a Next Generation Multiplex STR Kit……………………47
3.1 Introduction……………………………………………………………..49
3.2 Materials and Methods…………………………………………………..50
3.2.1 Sample Description……………………………………………50
3.2.2 DNA Extraction…………………………………………….....50
3.2.3 PCR Multiplex Amplification…………………………………50
3.2.4 STR Typing……………………………………………………51
3.2.5 Statistical Analysis……………………………………….........51
3.3 Results and Discussion…………………………………………………..52
3.4 Conclusion………………………………………………………………53
3.5 References……………………………………………………………….62
Chapter Four
4. Allele Frequencies of Short Tandem Repeat markers used for Forensic
Applications in the Arab Population of the United Arab Emirates.………………...63
4.1 Introduction……………………………………………………………..65
4.2 Materials and Methods…………………………………………………..66
4.2.1 Sample Description……………………………………………66
4.2.2 DNA Extraction……………………………………….............67
8
4.2.3 PCR Multiplex Amplifications………………………………..67
4.2.4 STR Typing……………………………………………………67
4.2.5 Statistical Analysis………………………………………….....68
4.3 Results and Discussion…………………………………………………..68
4.4 Conclusion………………………………………………………………71
4.5 References……………………………………………………………….79
Chapter 5
5. A Comparative Analysis of Autosomal Short Tandem Repeat (STR) Allele
Frequencies of Populations in the United Arab Emirates and Surrounding Regions...81
5.1 Introduction……………………………………………………………..82
5.2 Methods…………………………………………………………………84
5.3 Results…………………………………………………………………..85
5.3.1 Within-population Genetic Variability Measures……………..85
5.3.2 Regional population Genetic Comparisons of the Middle East..87
5.3.3 Inter-population Genetic Comparison…………………………90
5.3.4 Effect of Increased Number of STR Markers………………….90
5.4 Discussion……………………………………………………………….93
5.4.1 Significance of Inter-population Genetic Comparisons……….93
5.4.2 Heterozygosity Analysis………………………………………93
5.4.3 Inter-population Genetic Comparison using Six Autosomal STR
Loci………………………………………………………………….94
9
5.4.3.1 Regional Genetic Comparisons with the Present UAE
Study………………………………………………………...94
5.4.3.2 Broader Population Genetic Comparison with the
Present UAE Study………………………………………….95
5.4.4 Significance of Increasing Number of Autosomal STR Loci in
Analyses…………………………………………………………….97
5.5 Conclusion………………………………………………………………98
5.6 References…………………………………………………………….....99
Chapter Six
6. Y-Chromosome STR haplotypes can be used to differentiate lineages in the United
Arab Emirates Population………………………………………………………….104
6.1 Introduction……………………………………………………………106
6.2 Materials and Methods…………………………………………………108
6.2.1 Study Population……………………………………………..108
6.2.2 Genotyping…………………………………………………..109
6.2.3 Statistical Analysis…………………………………………...110
6.3 Results and Discussion…………………………………………………110
6.4 Conclusion……………………………………………………………..121
6.5 References……………………………………………………………...123
Chapter Seven
7. General Discussion and Conclusion……………………………………………..127
7.1 Discussion……………………………………………………………...128
10
7.2 Conclusion……………………………………………………………..134
7.3 References……………………………………………………………...136
Bibliography………………………………………………………………………140
Appendices………………………………………………………………………..152
Appendix 1………………………………………………………………...153
Appendix 2………………………………………………………………...155
Appendix 3………………………………………………………………...157
Appendix 4………………………………………………………………...159
11
Acknowledgements
I acknowledge the support and assistance from Khalifa University Biotechnology
Center for providing de-identified DNA samples from the Emirates Family Registry
for the following studies. I further acknowledge the travel grant from the Graduate
Research School at the University of Western Australia, which facilitated the
collaborative link with colleagues at Khalifa University. I would like to also
acknowledge the Abu Dhabi Police General Head Quarter for sponsoring the studies
of collaborators Osamah Ali Alhmoudi and Wafa Al Tayyare.
I would like to thank my supervisor Dr Guan Tay for providing me with great
opportunities, dedication and support towards the completion of the thesis.
Furthermore, I would like to thank Dr Habiba Alsafar for her efforts whilst travelling
to Khalifa University, providing a wonderful experience. Also I would like to thank
the ongoing assistance from my supervisors Dr Silvana Gaudieri and Dr Daniel
Franklin and the School of Anatomy, Physiology and Human Biology at the
University of Western Australia.
12
I would like to dedicate this thesis to my parents Kylie and Brett Jones, my partner
Anthony Carameli and my family for their ongoing support throughout my many years
of study. I would not have achieved this without their positive influences impacting
my determination in the completion of this thesis.
13
Statement of Candidate Contribution
In accordance with the University of Western Australia’s regulations regarding
Research Higher Degrees, this thesis includes published and formatted journal papers.
The contribution of the candidate and co-author(s) for the appropriate chapters are
hereby set forth:
Chapter Three: Population genetics data for 21 autosomal STR loci for the United
Arab Emirates (UAE) population using a next generation multiplex STR kit.
The manuscript presented is first authored by Osamah Ali Alhmoudi and published
with co-authors. The publication details are as follows:
Ali Alhmoudi O, Jones R, Tay G, Alsafar H, Sibte H. Population genetics data
for 21 autosomal STR loci for United Arab Emirates (UAE) population using
next generation multiplex STR kit. Forensic Science International: Genetics.
2015;19:190-1.
The candidate completed a thorough interpretation of the autosomal STR data under
the supervision of Drs Tay and Alsafar. The laboratory processes were carried out by
first author Osamah Ali Alhmoudi under the supervision of Drs Sibte and Alsafar.
The project was designed by Mr Alhmoudi in collaboration with the co-authors of the
paper. Mr Alhmoudi prepared the first draft of the paper and the candidate contributed
substantially to the editing and proof-reading processes of the manuscript. The
candidate was responsible for formatting and responding to comments from the editors
of the Journal.
14
Chapter Four: Allele frequencies of Short Tandem Repeat markers used for forensic
applications in the Arab population of the United Arab Emirates.
The manuscript has been accepted and in Press of the Journal Forensic Science
International: Genetics. The details of the submission are:
Jones R, Al Tayyare W, Tay G, Alsafar H, Goodwin W. Description of Short
Tandem Repeat markers used for Forensic applications in the Arab population
of the United Arab Emirates. Forensic Science International: Genetics (In Press).
The candidate developed the project and outlined the justification for the study under
the supervision of Drs Tay and Alsafar. The laboratory processes were carried-out by
Wafa Al Tayyare under the supervision of Drs Alsafar and Goodwin with technical
assistance from the candidate. The writing, planning and preparation of the
manuscript, statistical calculations and formatting for the journal were carried-out by
the candidate; with guidance from Drs Tay, Alsafar and Goodwin.
Chapter Six: Y-Chromosome STR haplotypes can be used to differentiate lineages in
the United Arab Emirates population.
The manuscript has been presented in the appropriate format and submitted for
publication to the Annals of Human Biology. The details of the manuscript are:
Jones R, Tay G, Mawart A, Alsafar H. Y-Chromosome haplotypes can be used
to differentiate lineages in the population of the United Arab Emirates. Annals
of Human Biology (submitted).
The candidate developed the project outline and objectives of the work described in
this manuscript. The laboratory tasks were carried-out by Dr Mawart; with technical
assistance from the candidate under the supervision of Dr Alsafar. The writing,
15
statistical calculations and formatting of the manuscript were carried-out by the
candidate under the guidance of Dr Tay.
Student signature:
Date: 03-11-2016
I, Dr Daniel Franklin certify that the student statements regarding their contribution to
each of the works listed above are correct.
Coordinating Supervisor signature:
Date:
16
Chapter 1
GENERAL INTRODUCTION
17
1.1 Introduction
Increasing and improving research into population-specific genetic data allows for the
establishment of quality standards within the field of Forensic Science (1). Short
Tandem Repeats (STRs) are commonly used in the generation of genetic data (1-4)
allowing the development of databases to advance knowledge in worldwide patterns
of genetic diversity (5). Importantly, the variability of the autosomal STRs provides
distinction between closely situated and related groups. Additionally Y-chromosome
STRs (Y-STRs) and mitochondrial (mtDNA) genetic information analyses establish
the paternal and maternal component of genetic history and geographic dispersal of
populations, respectively.
The importance of genetic research on the populations in the Middle East is
increasingly being highlighted in the literature (6,7) with a number of recent
population-specific genetic studies (8-10). The United Arab Emirates (UAE) is
situated within the Arabian Peninsula, located within the ancient human migration
route out from the Horn of Africa and into South Asia (11). In contrast to other genetic
studies on Middle East populations within the literature, there is a paucity of data on
UAE populations and minimal genetic comparisons to surrounding populations (2, 6,
12). Given the importance of genetic research in applications such as human identity,
paternity testing and in identifying disease susceptibility genes there is a need to
expand genetic research into this important region within the Middle East.
1.2 Aims and Hypothesis
The overall objective of this thesis was to improve the understanding of human genetic
diversity within the Middle East. The specific aims of this project are listed below:
18
1. Characterise allele frequencies and calculate forensic parameters for UAE
populations.
2. Examine genetic relationships and distances between different populations
from the Middle East, North Africa and South Asia.
3. Establish findings provided from two different STR analyses (autosome and
Y-chromosome).
4. Recognize factors such as human migration that impact population genetic
diversity.
The hypothesis of this research is that autosomal STR and Y-STR analyses of UAE
populations will provide a better understanding of the region. This study will advance
the existing literature on the topic (2, 8, 13, 14) by increasing sample size, number of
loci tested and comparing data from the UAE population to other populations in the
Middle East and surrounding regions relevant to known human migration patterns.
1.3 Thesis Structure
Each chapter within the thesis presents a new study enhancing the results established
in the chapters before and building on previous knowledge noted within the literature.
Research collaborations were initially established with the completion of the first
studies of autosomal STR data allowing for the statistical calculations of the UAE
allele frequencies to be obtained (Chapter 3). In the effort to maintain improved
standards in genetic research, the validation and replication of the autosomal STR
report on the UAE allele frequencies was then carried-out with additional samples and
described in the subsequent chapter (Chapter 4). This study improved the confidence
level of the results and increased the population sample size for addition to genetic
19
databases. Furthermore, the autosomal STR data of the UAE population was then
compared to populations from the Middle East, North Africa and South Asia (Chapter
5). The combination of all the populations used for comparison within this thesis is
novel as previous publications have omitted important populations in comparisons (2,
6, 12). To further enhance the knowledge in population genetics, Y-STR analyses
using up-to-date technologies for increased number of STR loci was carried-out
(Chapter 6). A meta-analysis of the UAE population using Y-STR haplogroups was
carried-out to compare findings established from the use of autosomal STR analyses
towards understanding how factors such as initial human migration, historic and trade
relationships impact genetic diversity.
20
1.4 References
1. Schneider PM. Scientific standards for studies in forensic genetics. Forensic
Sci Int. 2007;165(2-3):238-43.
2. Garcia-Bertrand R, Simms TM, Cadenas AM, Herrera RJ. United Arab
Emirates: phylogenetic relationships and ancestral populations. Gene.
2014;533(1):411-9.
3. Carracedo A, Butler JM, Gusmao L, Linacre A, Parson W, Roewer L, et al.
Update of the guidelines for the publication of genetic population data.
Forensic Sci Int Genet. 2014;10:1-2.
4. Osman AE, Alsafar H, Tay GK, Theyab J, Mubasher M, Sheikh N, et al.
Autosomal short tandem repeat (STR) variation based on 15 loci in a
population from the Central Region (Riyadh Province) of Saudi Arabia. J
Forensic Res. 2015;6(1):1-5.
5. Silva NM, Pereira L, Poloni ES, Currat M. Human neutral genetic variation
and forensic STR data. PLOS One. 2012;7(11).
6. Petraglia MD, Rose JI. The evolution of human populations in Arabia:
Paleoenvironments, prehistory and genetics. Netherlands: Springer 2009.
7. Shetty P. Lihadh Al-Gazali: a leading clinical geneticist in the Middle East.
The Lancet. 2006;367(9515):979.
8. Alshamali F, Alkhayat AQ, Budowle B, Watson ND. STR population diversity
in nine ethnic populations living in Dubai. Forensic Sci Int. 2005;152(2-
3):267-79.
9. Barni F, Berti A, Pianese A, Boccellino A, Miller MP, Caperna A, et al. Allele
frequencies of 15 autosomal STR loci in the Iraq population with comparisons
21
to other populations from the middle-eastern region. Forensic Sci Int.
2007;167(1):87-92.
10. Perez-Miranda AM, Alfonso-Sanchez MA, Pena JA, Herrera RJ. Qatari DNA
variation at a crossroad of human migrations. Hum Hered. 2006;61(2):67-79.
11. Kundu S, Ghosh SK. Trend of different molecular markers in the last decades
for studying human migrations. Gene. 2015;556(2):81-90.
12. Cadenas AM, Zhivotovsky LA, Cavalli-Sforza LL, Underhill PA, Herrera RJ.
Y-chromosome diversity characterizes the Gulf of Oman. Eur J Hum Genet.
2008;16(3):374-86.
13. Alshamali F, Pereira L, iacute, sa, Budowle B, Poloni ES, et al. Local
population structure in Arabian Peninsula revealed by Y-STR diversity. Hum
Hered. 2009;68(1):45-54.
14. Nazir M, Alhaddad H, Alenizi M, Alenizi H, Taqi Z, Sanqoor S, et al. A
genetic overview of 23Y-STR markers in UAE population. Forensic Sci Int
Genet. 2016;23:150-2.
22
Chapter 2
LITERATURE REVIEW: GENETIC ANALYSIS OF PEOPLE OF THE
MIDDLE EAST AND THE USE OF SHORT TANDEM REPEATS FOR
POPULATION GENETIC ANALYSES
23
2.1 Introduction
Highly variable regions within the DNA termed Short Tandem Repeats (STRs) are
widely used for characterising population structure and estimating human genetic
diversity (1-4). Such DNA-based data also provide leads in disease susceptibility
studies, paternity and individual identification. Population genetic analyses utilising
such variable markers have identified bidirectional human migration through the
Middle East, linking movement through Africa, Asia and Europe (2, 5, 6).
Accordingly, the Middle East is at the crossroads of human migration and the degree
of genetic variation within the region is of interest particularly in improving the
understanding of the impact of human migration on genetic diversity. However,
making sense of how human dispersal affects the patterns of genetic diversity remains
a complicated task (7, 8). Furthermore, there is minimal research on the genetic
diversity of Middle Eastern populations compared to other populations around the
world (9). Importantly, inconsistencies in genetic relationships have been noted due
to the geographical location of the Middle East in addition to the variety of cultural
and religious relationships throughout the region (8).
The Middle East region includes the Arabian Peninsula, which comprises Saudi
Arabia, Yemen, Oman, the United Arab Emirates (UAE), Bahrain, Qatar, Kuwait and
parts of Iraq and Jordan. The Levant region is an extension of the Middle East and
comprises Iraq, Jordan, Syria and Lebanon. Interactions between populations or
groups within the region and with surrounding areas are likely given known historical
events and the continuous trade throughout the Middle East, North Africa and South
Asia since the initial migration in early human history. Furthermore, there has been
the spread of cultural and religious lifestyles such as today the Muslim faith is
24
prevalent within the Middle East and collectively throughout North Africa, Horn of
Africa and parts of South Asia.
The numerous dispersal routes have influenced the degree of genetic variation
throughout the region, which requires greater understanding to provide significant
insights into genetic variations associated with disease susceptibility and in individual
identification applications.
2.2 Human Migration
Changes in the frequency of genetic variations within and between populations over-
time can be caused by demographic events such as human dispersal, population
expansion and admixture or gene flow due to the establishment of trade routes or with
the spread of a particular technology. These events leave genetic imprints altering
allele frequencies that are passed down through generations (10, 11). It has been
suggested that human dispersal since the out of Africa migration and agricultural
transitions have exerted some of the strongest evolutionary pressures on human
populations (12). Additionally, selection events can impact upon allelic diversity,
including disease-associated genetic variation (13).
DNA analyses have provided insight into human migration routes (Figure 2.1). The
specific nature of human genetic variations for a particular population has been
associated with certain migration routes and the resulting ethnic admixtures (14). It is
known that migration routes were bidirectional with humans migrating back through
Asia, the Middle East and back into Africa (5). Factors causing migration such as war,
food and climatic conditions likely resulted in the occurrence of bidirectional
25
migration. Furthermore, trade has become a more recent factor for many bidirectional
migration routes seen today (15, 16).
Figure 2.1: Estimated human migration routes using mitochondrial DNA
analyses. Map generated based on published data (2, 5, 6, 17-19).
Early human migration out of Africa has been predominantly studied using methods
inferring the evolutionary history of mitochondrial DNA (mtDNA) haplogroups
(Figure 2.1). One of the earliest discovered mtDNA lineages (L1 type) has been
suggested to have originated within East Africa approximately 130,000 years ago and
found to be restricted to African populations. This restriction of the L1 lineage in
African populations suggests ancient migration first began with the spread across
Africa with the discovery of the L2 and L3 lineages deriving from the L1 type also
within Africa (17). The first waves of the out of Africa migration are suggested to
have occurred approximately 85,000 years ago with two different proposed routes into
the Middle East (2, 3, 17, 18). These waves out of Africa from the L3 lineage gave
rise to the M and N type lineages observed within the Middle East. The proposed
routes of migration out of Africa are through the Horn of Africa (M type) and through
the Levantine region (N type) into the Middle East (Figure 2.1). The literature agrees
26
that both of these routes would have occurred, however it is unclear as to which
migration route occurred first (17, 18).
Kundu & Ghosh (2015) used mtDNA analyses to suggest that following the initial
migration from Africa, humans travelled from the Middle East through Southern Asia
and later on through Sri Lanka into Indonesia and then Australia approximately 60,000
years ago (2). Furthermore, the analyses of mtDNA haplogroups led to the discovery
of the N1e splitting from haplogroup I into three variable sequences approximately
40,000-30,000 years ago (17, 19). Haplogroup I is overall frequent in most of Europe
and then within the Gulf region. The three N1e sequences were further observed in
Arabia and Russia (17, 19). This analysis is indicative that human migration from the
Middle East travelled north into Russia and expanded west into Europe within the
estimated 40,000-30,000 timeframe. Genetic analysis of mtDNA has dated the
beginning of the migration across America approximately 25,000 years ago. During
that timeframe, the ‘Bering Land Bridge’ is proposed to have formed from the freezing
climate between Asia and Alaska allowing humans to cross into America (2). Analysis
of mtDNA haplogroup variations suggests the route into South America to have
initially occurred approximately 20,000-15,000 years ago (17).
2.3 Impact of Bidirectional Migration through the Middle East
Evidence of bidirectional migration between the Middle East and Africa is provided
by mtDNA analysis that identifies the presence of the U6 lineage (of Middle East
origin) within North Africa. The presence of the U6 lineage in these regions suggests
migration from the Middle East back into Africa occurring approximately 50,000-
40,000 years ago (5). Such instances of bidirectional migrations are not unique as
27
bidirectional routes within the Middle East are common (6). Accordingly, as seen in
Figure 2.1, the Middle East represents the multidirectional region between Africa,
Asia and Europe.
As mentioned earlier, the initial human migration out of Africa comprised the M and
N type mtDNA haplogroups, signifying separate genetic lineages between the Levant
and coast of the Arabian Peninsula. With the use of mtDNA analyses, Iraqi
populations (Levant Region) were found to not only have the N type lineage, but
additional haplogroups sharing relationships with populations within the M type
dispersal routes (e.g. India) (20). This example using mtDNA analysis highlights the
importance of considering the historical dispersal of humans after the initial out of
Africa migration to describe genetic relationships. Although there may have been two
different mtDNA haplogroups dispersed from the L3 type out of Africa, the dispersals
of humans within and through the Middle East region has involved multiple waves.
Furthermore, more recent human dispersals have resulted in genetic inferences that
have in some cases contradicted the assumed genetic relationships from the initial out
of Africa migration (18), signifying the importance of continuous genetic research.
Using mtDNA analyses to understand the dispersal of humans out of Africa indicates
how there is still much more to learn from population-specific analyses (18). For
example, in contrast to the observed heterogeneity within the Middle East, the Arabian
Gulf populations such as Saudi Arabia and Yemen have shown distinct genetic
homogeneous structures possibly due to the occurrence of isolated desert groups (18).
Further analyses of human dispersal throughout the Middle East and surrounding
regions will provide a better understanding of how the Middle East can exhibit a large
degree of heterogeneity with some areas of homogeneity.
28
The analysis of the Y-chromosome will further add towards understanding the degree
of heterozygosity within the Middle East and the likely impact of sociocultural
impacts, such as polygyny that will affect the male contribution towards the Y-
chromosome genetic pool. Historically polygyny was common, which would give rise
to homogeneous populations (identified via Y-chromosome haplotypes) being traced
through genetic analyses with a shift to monogamy; increasing genetic diversity (21).
As polygynous marriages occur throughout the Middle East, North Africa and South
Asia (22), it is important to address this factor when examining the degree of observed
homozygosity and heterozygosity at genetic traits amongst populations in the region.
2.4 Historical and Trade Migration in the Middle East Region
As indicated by archaeological data, mtDNA and Y-chromosome analyses, trade
between the Horn of Africa and the Arabian Peninsula has been occurring since 6000
BCE (Figure 2.2) (23). This migration would have been a key beginning to simple
maritime dispersals around the Middle East (9). The bidirectional trade involved
exchanging plants and animals (e.g. cattle), resulting in international migration (23).
The earliest archaeological data indicating trade routes between South Asia,
Mesopotamia and the Arabian Peninsula was the Mature Harappan Period (2600
BCE). This period involved maritime trade and transportation.
Supported by DNA analyses, this trade period is indicative of migration from South
Asia (India) to areas along the coasts of the UAE, Iran and within the Levant (24).
More recent maritime trade (20th Century) has seen an increase in trade across the Gulf
between the geographical locations of Iran, Qatar and the UAE, resulting in
bidirectional human migration across the sea (25).
29
Figure 2.2: Estimated historical and trade migration routes through the Middle
East. Map generated based on published data (9, 16, 19, 23-27).
Since the 6th Century, during suitable climatic conditions, the Red Sea coasts of Africa
and the Arabian Peninsula was a region of trade migrations (e.g for cotton) and
successive population expansions (16). The spread of Islam in the 7th and 11th Century
included the migration of populations throughout the Middle East and North Africa
(16). During the 7th Century, Islamic culture extended from Mecca and Jeddah into
Pakistan and west into the Iberian Peninsula. The extension of Islamic culture within
North Africa during the 11th Century, with evidence to have spread through to
Morocco (16, 26). Furthermore, the Ottoman Empire was the longest dynasty from
the 13th Century to the 20th Century (27). The migration routes of particular ethnic
groups are reflective of the spread of the dynasty, involving refugee routes and trade
(27). Furthermore, bidirectional migration between Oman and Zanzibar occurred
from the 19th Century (27). Cultural influences and genetic diversity can be seen to
30
have resulted from the trade and various historical events such as the Zanzibar
colonization.
Overall human dispersal, together with subsequent sub-population endogamy and
consanguinity throughout the Middle East has resulted in ethnic population diversity
(Figure 2.3). Furthermore, in more recent family generations, the increase in
population sizes in addition to the large-scale urbanisation throughout the region has
impacted genetic structures. This rise in ethnic diversity has been observed from the
variety of social and cultural influences throughout the Middle East. There are at least
19 different ethnic groups within the Middle East with the largest pan-ethnic group
within and around the Arabian Peninsula referred to as ‘Arabs’. The next largest
ethnic groups within the Middle East region (and extending into Iran) are Persians and
then the Baluch. In addition to the diversity of different populations within the Middle
East, different Arab populations are geographically distributed throughout the Middle
East and North Africa (Bedouin, Egyptian, Jordanian, Yemenite, etc). The influence
of human migration on the resulting different Arab and other ethnic populations within
the Middle East is important to establish to determine its effect on genetic diversity
and the extent of ethnic geographical distributions.
31
Figure 2.3: Qualitative analysis of different ethnicity and cultural groups residing
within and surrounding the Middle East. Map generated using published data (15,
26, 28-43).
Many populations within the Middle East practise consanguineous marriage (21).
Higher rates of consanguineous marriages have been seen within Arabic populations
(e.g. Bedouin), and to some extent increasing homozygosity rates (44, 45).
Homozygosity rates observed within populations such as the Bedouins are also
affected by the isolation of these cultures in the desert as reflected in the mtDNA
haplogroup analyses. Accordingly, it is important to consider consanguinity and
endogamy in population genetic research when examining the effect of historical
human migration factors on levels of genetic diversity observed in consanguineous
families (21, 22). However, recent bidirectional migration and cultural influences
from surrounding regions have been observed to increase gene flow from surrounding
32
Asian, African and some European areas, resulting in observable genetic diversity
within the region (45). This highlights the importance of studying specific populations
within the Middle East region to understand the influences of observable
consanguinity, human migration and socio-cultural factors on genetic variation.
2.5 Geographical Differentiation Determined by Different Genetic Components
Analysis of genetic variation across the Y-chromosome (resulting in haplotypes)
allows for the investigation of male lineage contributions to gene flow. The genetic
variation along the Y-chromosome has been shown to be affected by rapid genetic
drift resulting in high levels of geographical differentiation of Y-haplotypes (46).
Furthermore, the Y chromosome contains the largest non-recombining section within
the human genome, providing significant informative haplotypes for application in
population genetic analyses (7). Worldwide population data have been collected for
Y-chromosome STR (Y-STR) haplotypes. Results have shown Y-STR haplotypes are
region-specific, increasing their utility in population genetic studies, forensics and
paternity testing (47).
Due to the geographical location of the Middle East and bidirectional dispersals, the
degree of ethnic diversity in the region has complicated population genetic analyses.
Discrepancies between genetic analyses of the Middle East have been observed. For
example, Triki-Fendri et al (2010) used Y-STR data to support the relationship
between the degree of genetic diversity and geographical location (47). Genetic
relatedness was seen between the Kuwaiti population and Arabian Peninsula
populations (Yemen, Saudi Arabia and the UAE) reflecting the close geographical
location of the groups (27). However, Roewer et al (2009) highlighted the importance
33
of studying individual populations or minority groups in close-proximity in the same
region and country (48) as this study found genetic differences between linguistic
groups residing within Iran. This latter study highlights the importance in genetic
analyses of considering not only the geographical location of countries but also factors
such as cultural and religious isolation of populations within the same region.
The level of human dispersal throughout the Middle East has been diverse from
variable locations but the region also contains isolated populations. Not surprisingly,
Y-STR analysis of the genetic structure of the Middle East has been described as
reflecting a “mosaic pattern” (18). Accordingly, it is important to increase the number
of analyses between different identifiable populations and subpopulations within the
Middle East to attempt to understand the “mosaic pattern” of the genetic diversity.
Additional comparison to other regions in North Africa and South Asia due to
dispersal patterns needs to be considered to further understand genetic diversity in
close-proximity subpopulations.
The use of mtDNA analyses is thought to have advantages over Y-STR analyses in
genetic studies due to the abundance of mtDNA in the cell, faster mutation rate and
increased number of polymorphisms (2). However, the use of Y-chromosome
analyses supports mtDNA analyses of human migration such as the ancient African
origin for all modern humans and bidirectional dispersals (2, 5, 49-50). But
differences in observed genetic outcomes can result between mtDNA and Y-
chromosome analyses due to the different gene flow patterns of male and females (51).
As may be expected, males and females may not always accompany each other
through dispersal routes (51, 52) and the continued analysis of Y-chromosome
variation in different populations is necessary to fill in the gaps in human history not
reflected in mtDNA analyses.
34
2.6 Distinguishing Closely Related Groups using Autosomal STRs
The use of autosomal DNA for population genetic analyses has advanced studies on
migration, parentage and ability to infer genetic diversity (53). Both mtDNA and Y-
chromosome results only represent single loci reflecting maternal or paternal history,
respectively. By analysing autosomal STRs, the overall population genetic structure
can be represented. Studies in the literature have shown autosomal STR markers
provide useful information on our evolutionary and migratory history (1, 53-55). The
enhanced understanding of the degree of genetic variation within and between
populations can then be associated with improving analyses of disease patterns and
susceptibility.
Due to the hyper-variability and ubiquity of autosomal STRs throughout the genome,
extensive sets of autosomal STRs can be used for population genetic applications (1).
Single nucleotide polymorphisms (SNPs) have been highlighted in the literature to be
superior to STRs for genetic analyses, especially with the advent of next generation
sequencing technologies (2, 4). There are a large number of SNPs along the genome
and these loci exhibit lower mutation rates than for STRs (56). The mutation rate of
these markers is important to consider as the high mutation rate of STRs have been
associated with a decrease in reliability in allele frequency estimations (1, 55, 57).
However, Gaiber et al (2012) found using 51 worldwide populations that 88.9% of the
genetic variation could be assessed by using 650,000 SNPs, whereas typing only 783
autosomal STRs resulted in considerably higher population genetic variation at 94%
with the same samples (55). Furthermore, due to the number of STR markers available
for large population sample sizes, the advantages of using STRs over SNPs include
the higher analytical power, higher allelic abundance and lower ascertainment bias
35
(58-60). A worthy suggestion within the literature is to combine the analysis of STRs
and SNPs to improve population genetic inferences (53, 61).
As mtDNA and Y-chromosome analyses have identified the importance of studying
closely located and related groups, the hyper-variability of autosomal STRs has the
ability to advance knowledge on this topic. Shepard et al (2006) found a strong
correlation between the degree of genetic variation and both geography and language
using autosomal STRs (6). For example, Bentayebi et al (2014) found minimal
genetic variance with shared ancestry between North African populations (Morocco
and Egypt) and populations within the Middle East (Iraq and Oman respectively) (60).
Even though there is geographical distance between these populations, autosomal
STRs can indicate which cultural and religious similarities may have impacted genetic
relationships. The use of autosomal STRs has also shown that close geographical
populations have genetic relationships that reflect known historical events, trade and
sociocultural relationships (54, 62, 63). The fact autosomal STRs show both close
geographical relationship and distant relationships, highlights the need for
continuation of research to understand the degree of genetic influences.
Variable degrees of genetic relationships were observed within the literature between
Saudi Arabia and other Arabian Peninsula populations including Qatar (62). Perez-
Miranda et al (2006) found significant genetic distance between Qatar and Saudi
Arabia even though they share common borders (62). Additionally, the genetic
isolation of Saudi Arabian populations has been highlighted when compared with
other neighbouring populations such as the UAE (64). Furthermore, the UAE share
greater genetic similarities with South Asian populations such as Iran reflecting trade
and cultural relationships (54).
36
The degree of genetic variation observed in the Middle East fluctuates from low levels
of diversity in isolated populations (Saudi Arabia) to high levels of heterogeneity
(UAE) within the region, complicating the task of understanding the degree of genetic
diversity in the Middle East. Clearly, the degree of genetic variation within the Middle
East and in North African and South Asian populations do not show a smooth pattern
of genetic diversity affected only by geographical distance. Additional factors
impacting genetic diversity, as seen using autosomal STRs, consist of historic and
trade relationships throughout the years that require consideration in addition to
geographical distance and initial human migration.
2.7 Middle East Region and Worldwide Research
There have been numerous global projects analysing the degree of genetic variations
in populations. The International HapMap Project was developed to characterise
DNA sequences, allele frequencies and genetic relationships across different
populations (65). The population samples were collected over three phases (Figure
2.4). Despite the widespread nature of this genetic research, no population data was
collected from the Middle East region. Furthermore, the 1000 Genomes Project only
characterised allele frequency variants from West Africa, Europe, North America and
South and East Asia (66). Although the Middle East region has been established as
the crossroads of migration, showing fluctuated degrees of genetic variation, there
remains a lack of information from this region, especially seen within global genetic
projects. As mentioned previously, the Middle East is significantly located
geographically, contributing to the flow of genes through bidirectional human
migration.
37
Figure 2.4: Populations chosen for the International HapMap Project. Note there
is no described ethnic population from the Middle East region. Map generated using
published data (65, 67, 68). Note that the map shows the location from which the
ethnic groups came from and the location where participants were recruited is also
described.
Furthermore, the residing diverse ethnic populations and different cultural lifestyles
have impacted gene flow and in turn the genetic diversity in the Middle East and
surrounding North African and South Asian populations. These facts prove how the
Middle East region is important to be included in global genetic projects to compare
the diverse genetic imprint in the Middle East from a global perspective (69).
However, there is minimal genetic research in the literature on the Middle East in
comparison to other global regions (66). Although there are publications describing
genetic data from Middle Eastern populations, as mentioned above with the use of
mtDNA, Y-chromosome and autosomal STRs (70-73), not every country within the
region has been analysed and compared to each other. Furthermore, due to the
advancements in DNA analyses, more STR markers and sample size increases are
38
required than what is provided within previous publications (74). Such research would
also impact on our understanding of the genetics of disease susceptibility in the region
(44).
2.8 Conclusion
Strategically located, the Middle East region is important in population genetic
analyses to understand the waves of migration and back-migrations intersecting
Europe, Asia and Africa (6). The advancements in genetic analyses have proven the
importance of migratory studies of the Middle East. However, the complexity of
genetic relationships amongst the Middle East populations may be understood with
further genetic studies into the significance of the major dispersal routes and the
impact of other factors on genetic diversity.
The literature has shown how STRs are still powerful tools for population genetic
analyses. From the amount of information STR analyses can provide, population allele
frequency standards can be obtained and population structures can be inferred. This
review highlights how genetic analyses using mtDNA, Y-chromosome and autosomal
STRs have the ability to better understand the genetic diversity of the Middle East.
However, due to the Middle East showing isolated population structures but overall
significant heterogeneity amongst the region and surrounding areas, further genetic
comparisons using modern advancements in technology and more populations for
comparisons in meta-analyses needs to take place. This information will allow for a
greater understanding of the Middle East region and the impact of historic and recent
human dispersal on genetic variation.
39
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47
Chapter 3
POPULATION GENETICS DATA FOR 21 AUTOSOMAL STR LOCI FOR
THE UNITED ARAB EMIRATES POPULATION USING A NEXT
GENERATION MULTIPLEX STR KIT
Following the literature review in the preceding chapters, the remainder of this
thesis describes the data collected and analysed. This specific chapter is the first
of four chapters describing the data collected. It contains the script for a
manuscript that has been published in 2015 in the Journal of Forensic Science
International (FSI): Genetics. The published manuscript is in the form of a Letter
to the Editor of FSI Genetics and is included in the appendices (Appendix 1) of the
thesis. The candidate contributed towards the interpretation of data, statistical
calculations and analyses, proof-reading and editing as well as formatting of the
manuscript for FSI Genetics.
48
Forensic Science International: Genetics. 2015;19:190-1
Population genetics data for 21 autosomal STR loci for the United Arab Emirates
(UAE) population using a next generation multiplex STR kit.
Osamah Ali Alhmoudi1,2, Rebecca J Jones3, Guan K Tay3, Habiba Alsafar4, Sibte
Hadi1.
1 University of Central Lancashire, School of Forensic and Investigative
Sciences, Preston, UK.
2 Forensic Evidence Department, Abu Dhabi Police General Head Quarter, Abu
Dhabi, The United Arab Emirates.
3 Centre for Forensic Sciences, University of Western Australia, Crawley,
Western Australia.
4 Facility of Biomedical Engineering, Khalifa University of Science,
Technology and Research, Abu Dhabi, The United Arab Emirates.
49
3.1 Introduction
The United Arab Emirates (UAE) is one of the Middle East countries located on the
Arabian Gulf. It shares a border with Iran, Saudi Arabia and Oman. The UAE was
founded in 1971, and consists of seven Emirates: Abu Dhabi, Dubai, Sharjah, Ajman,
Ra’s Al-Khaymah, Al-Fujairah and Umm Al-Quwain (1). According to the 2015
Census data (2015), the total UAE population was reported to be approximately 9.6
million in 2015. The data showed native Arabs to be 11.3% of the total population
with the majority of the population being of Indian and Pakistani ethnicities. In the
early part of the twentieth century, the different tribes started migrating in different
directions in search of a better life. Some moved into coastal regions, while others
inhabited the desert. Despite the modernization throughout the union, the basic family
structure and pattern of a native UAE Arab population has remained unchanged.
Culturally, the preference for consanguineous marriages remains embedded in the
society (2). However, as the awareness of the social and medical impact of
consanguinity increases and with diversification, non-consanguineous marriages
appear to be on the increase, which has possibly resulted in greater genetic diversity
throughout the population (3). The increase in genetic diversity in the population is
of interest to assess whether Short Tandem Repeat (STR) loci can be used for forensic
and paternity purposes. This study expands on previous publications in regards to the
analysis of UAE populations with the genotyping of additional STR loci and a larger
population sample size (4).
50
3.2 Materials and Methods
3.2.1 Sample Description
DNA samples from 519 randomly chosen healthy, unrelated individuals who reside in
Abu Dhabi, UAE were used in this study. The DNA samples utilised in this current
study were previously obtained from individuals at Khalifa University in Abu Dhabi
and in accordance with approval from the Ethics committee of the Ministry of Health
in the UAE (2011). Informed consent was received from every volunteer during this
collection process and de-identified data is presented.
3.2.2 DNA Extraction
The DNA samples provided for this study were collected and extracted from buccal
swabs using the Oragene-DNA kit (Genotek, Ottawa, Canada) in accordance with
manufacturer’s guidelines. The quantity and quality of extracted DNA was
determined using a NanoDrop spectrophotometer (Thermo Scientific, Wilmington
DE, USA).
3.2.3 PCR Multiplex Amplification
Using half volume (7.5µl) reactions, samples were amplified using the GlobalFiler®
PCR amplification kit (Life Technologies, Foster City CA, USA) in addition to the
amplification of the provided allelic ladder in accordance with manufacturer’s
guidelines. The PCR was performed in the GeneAmp® PCR System 9700 (Life
Technologies). The GlobalFiler® PCR amplification kit (Life Technologies)
amplifies 24 STR loci. The 21 autosomal loci within this amplification kit are of
interest in this study for the analysis of the UAE population. The 21 autosomal loci
amplified and analysed in this study were D3S1358, vWA, D16S539, CSF1PO,
51
TPOX, D8S1179, D21S11, D18S51, D2S441, D19S433, TH01, FGA, D22S1045,
D5S818, D13S317, D7S820, SE33, D10S1248, D1S1656, D12S391 and D2S1338.
3.2.4 STR Typing
The PCR products with the additional LIZ-internal Standard (Life Technologies) were
analysed using an ABI 3500 DNA Genetic Analyser with POP-4TM polymer (Life
Technologies). GeneMapper® Software version 4.0 (Life Technologies) was then
used for analysis. The alleles from all loci reported here were designated according
to the published nomenclature and the guidelines of the International Society for
Forensic Genetics (ISFG) for performing STR analyses (5).
3.2.5 Statistical Analysis
The STR allele frequencies along with parameters of population genetics: Observed
and Expected Heterozygosity (Ho and He, respectively), Power of Discrimination
(PD), Power of Exclusion (PE), and Polymorphic Information Content (PIC) were
estimated using PowerStats version 1.2 (Promega, Madison, USA). Version 3.11 of
the Arlequin software was used to perform an exact test to investigate any departures
from the Hardy-Weinberg equilibrium (HWE) (6). The Bonferroni correction was
carried-out by dividing the critical P value (α) by the number of comparisons being
made (n) to adjust for the multiple STR loci being tested using the following
calculation α ÷ n = 0.05 ÷ 21. The theoretical profile frequency range was estimated
and was used to identify the rarest and most common genotypes. Furthermore, the
number of possible genotypes was also calculated using 0.03 and 0.05 FST values to
gain a better understanding.
The data generated from this study was compared to five published population data
sets for the 15 overlapping STR loci (7). The locus-by-locus exact test (using 30,000
52
Markov steps) comparisons were made between this current study of the UAE
population and data from Kuwait, India, Saudi Arabia, Egypt and Iran using Arlequin
v3.11 (6).
3.3 Results and Discussion
Through the analysis of allele frequency data (Table 3.1), allele 8 of TPOX was found
to exhibit the highest allele frequency with 49.4% in the total sample. During analysis,
two off-ladder allelic variants were observed at locus SE33. These variants were allele
7.3 (in three samples) and allele 17.3 (in one sample). Both of these variants have
been previously reported on STRBase (8). A tri-allelic pattern (allele 6, 8, 10) was
observed for TPOX during analysis, which has also been previously reported on
STRBase (8). The SE33 locus showed the largest number of alleles (50 alleles) and
the D13S1358, D16S539 and CSF1PO loci showed the smallest number of alleles (8
alleles). The Ho values of the 21 autosomal STR loci ranged from 65% (TPOX) to
92% (SE33). The PD values for all tested loci were above 85%; the highest observed
for SE33 with 99.3% and the lowest for TPOX with 85%. The combined PE (CPE),
combined PD (CPD) and combined matching probability (CMP) for all 21 STR loci
were 0.9999992, 0.9999999 and 6.2468x10-27, respectively. When HWE was tested,
there was no statistical significance observed for 19 out of 21 autosomal STR loci.
Bonferroni correction was calculated (0.002) and applied to the two loci (D8S1179
and D22S1045) that showed deviation from HWE after which no significant departure
was observed.
The data for the most common STR profile from the UAE population (Table 3.2)
showed that even using a conservative 0.05 FST value leads to a PD value in the order
53
of 1015, which translates into a value higher than 1 in a billion. These estimates
indicate that the match probability estimates reported on UAE populations in
laboratories (in the case of a full match) can be based on statistics generated using its
own population allele frequency data. Further work is required as more STRs are
added to the standard panel in order to develop guidelines and standards for UAE
population genetic data to be used in the form of databases.
Some significant differences were identified between the obtained UAE population
data and other published data (Table 3.3). The populations from Iran and Saudi Arabia
showed significant differences at fewer loci when compared with populations from
Kuwait, Egypt and India (P > 0.05). This is also supported by low FST values for the
Iranian and Saudi Arabian populations. These results support the development of
population and/or location specific databases even when considering populations that
are geographically close such as within the Middle East.
3.4 Conclusion
This current dataset establishes the characteristics of the 21 STR loci panel for the
identification of individuals in paternity testing and for crime scene analysis in the
UAE with the use of an amplification kit.
54
Table 3.1: Allele frequency data for 519 individuals from UAE Population for 21 autosomal STR loci.
Allele D3S1358 vWA D16S539 CSF1PO TPOX D21S11 D8S1179 D18S51 D2S441 D19S433 TH01
4 0.001
5 0.001
6 0.004 0.299
7 0.005 0.217
8 0.03 0.003 0.494 0.01 0.113
9 0.16 0.036 0.136 0.007 0.002 0.238
9.3 0.116
10 0.002 0.096 0.278 0.107 0.073 0.008 0.122 0.003 0.013
11 0.002 0.357 0.303 0.23 0.102 0.021 0.402 0.015 0.003
11.3 0.076
12 0.233 0.316 0.023 0.154 0.114 0.106 0.1
12.2 0.006
12.3 0.008
13 0.004 0.002 0.111 0.049 0.004 0.241 0.183 0.021 0.215
13.2 0.038
14 0.063 0.066 0.01 0.011 0.001 0.164 0.158 0.232 0.245
14.2 0.059
15 0.255 0.13 0.001 0.168 0.136 0.03 0.143
15.2 0.001 0.073
16 0.301 0.247 0.069 0.126 0.001 0.05
16.1 0.049
16.3 0.001
17 0.234 0.272 0.012 0.104 0.003
17.2 0.001
18 0.131 0.211 0.001 0.076 0.001
19 0.011 0.058 0.003 0.041
20 0.012 0.017
21 0.002 0.006
21.2 0.003
22 0.005
55
26 0.001
27 0.03
28 0.155
29 0.219
30 0.234
30.2 0.031
31 0.039
31.2 0.102
32 0.007
32.2 0.119
33 0.001
33.2 0.045
34 0.002
34.2 0.005
35 0.007
35.2 0.001
36 0.002
N 519 519 519 519 518 519 519 519 519 519 519
Ho 0.768 0.799 0.732 0.716 0.657 0.797 0.811 0.838 0.743 0.793 0.764
He 0.769 0.796 0.77 0.727 0.673 0.843 0.843 0.875 0.752 0.848 0.782
HWE 0.110 0.577 0.156 0.641 0.274 0.060 0.037 0.347 0.340 0.367 0.069
PD 0.907 0.925 0.915 0.875 0.846 0.957 0.955 0.971 0.902 0.961 0.918
PE 0.542 0.598 0.48 0.455 0.367 0.62 0.595 0.672 0.499 0.588 0.536
MP 0.093 0.075 0.085 0.125 0.154 0.043 0.045 0.029 0.098 0.039 0.082
PIC 0.73 0.77 0.74 0.68 0.63 0.82 0.82 0.86 0.72 0.83 0.75
TPI 2.12 2.5 1.87 1.77 1.46 2.65 2.47 3.09 1.95 2.43 2.13
N: Number of Samples, Ho: Observed Heterozygosity, He: Expected Heterozygosity, HWE: Hardy Weinberg p-value, PD: Power of Discrimination,
PE: Power of Exclusion, MP: Match Probability, PIC: Polymorphic Information Content, TPI: Typical Paternity Index. Where no alleles were
identified, this allele number was deleted from the table.
56
Continuation of Table 3.1
Allele FGA D22S1045 D5S818 D13S317 D7S820 SE33 D10S1248 D1S1656 D12S391 D2S1338
6 0.001
6.3 0.003
7 0.001 0.001 0.025
8 0.001 0.013 0.145 0.176 0.006 0.012
9 0.046 0.042 0.096 0.003 0.011
10 0.016 0.121 0.068 0.283 0.007
11 0.169 0.264 0.255 0.264 0.002 0.011 0.093
12 0.01 0.342 0.329 0.137 0.002 0.03 0.127
12.2 0.002
13 0.004 0.198 0.121 0.016 0.019 0.187 0.107
13.2 0.003
14 0.066 0.014 0.037 0.001 0.025 0.328 0.118 0.001 0.002
14.2 0.001
14.3 0.003 0.007
15 0.406 0.001 0.032 0.276 0.151 0.023
15.2 0.002
15.3 0.005 0.03
16 0.248 0.001 0.067 0.117 0.191 0.018 0.042
16.1 0.003
16.2 0.001
16.3 0.079 0.002 0.045
17 0.004 0.084 0.039 0.047 0.132 0.205
17.3 0.039 0.009
18 0.003 0.003 0.094 0.002 0.004 0.174 0.107
18.3 0.015 0.015
19 0.061 0.086 0.001 0.122 0.148
19.1 0.001
19.2 0.002 0.001
19.3 0.006 0.003
20 0.095 0.037 0.114 0.149
57
20.2 0.003
20.3 0.001
21 0.115 0.018 0.133 0.052
21.1 0.002
21.2 0.005 0.015
22 0.158 0.007 0.086 0.042
22.2 0.008 0.017
23 0.162 0.003 0.086 0.104
23.2 0.001 0.027
24 0.208 0.001 0.054 0.078
24.2 0.004 0.034
25 0.115 0.022 0.057
25.2 0.042
26 0.041 0.006 0.011
26.2 0.049
27 0.01 0.002
27.2 0.061
28 0.003
28.2 0.059
29 0.002
29.2 0.053
30.2 0.039
31.2 0.002 0.034
32 0.002
32.2 0.021
33 0.002
33.2 0.004
34 0.01
34.2 0.004
35 0.005
35.2 0.001
36 0.004
36.2 0.001
37 0.002
58
N 519 519 519 519 519 515 519 519 519 519
Ho 0.834 0.666 0.764 0.788 0.789 0.928 0.737 0.872 0.882 0.865
He 0.865 0.735 0.757 0.783 0.89 0.949 0.765 0.884 0.888 0.876
HWE 0.062 0.003 0.643 0.856 0.051 0.183 0.232 0.165 0.129 0.133
PD 0.966 0.893 0.896 0.92 0.919 0.993 0.907 0.974 0.975 0.97
PE 0.664 0.379 0.536 0.577 0.581 0.853 0.489 0.74 0.76 0.725
MP 0.034 0.107 0.104 0.08 0.081 0.007 0.093 0.026 0.025 0.03
PIC 0.85 0.7 0.72 0.75 0.76 0.95 0.73 0.87 0.88 0.86
TPI 3.02 1.5 2.13 2.36 2.38 6.96 1.91 3.93 4.25 3.71
CPD 0.9999999
CPE 0.9999992
CMP 6.2468x10-27
N: Number of Samples, Ho: Observed Heterozygosity, He: Expected Heterozygosity, HWE: Hardy Weinberg p-value, PD: Power of Discrimination,
PE: Power of Exclusion, MP: Match Probability, PIC: Polymorphic Information Content, TPI: Typical Paternity Index, CPD: Combined Match
Probability, CPE: Combined Power of Exclusion, CMP: Combined Match Probability. Where no alleles were identified, this allele number was deleted
from the table.
59
Table 3.2: Calculations for theoretical most common and rarest genotype frequencies.
Locus Allele1
Allele
Frequency
HW2
Genotype
Proportion
BN3
Heterozygote
Genotype
proportion
at 0.03 FST
BN3
Heterozygote
Genotype
proportion
at 0.05 FST
D3S1358 15 0.255 0.15351 0.203679472 0.240908145
16 0.301
VWA 16 0.247 0.134368 0.163047194 0.216241269
17 0.272
D16S539 11 0.357 0.166362 0.198279695 0.249675596
12 0.233
CSF1PO 11 0.303 0.191496 0.224354029 0.284585861
12 0.316
TPOX 8 0.494 0.134368 0.169695556 0.213753173
9 0.136
D21S11 29 0.219 0.102492 0.128228429 0.175752793
30 0.234
D8S1179 13 0.241 0.080976 0.104758996 0.144462309
15 0.168
D18S51 13 0.183 0.057828 0.078271805 0.114813569
14 0.158
D2S441 11 0.402 0.186528 0.220441917 0.273021592
14 0.232
D19S433 13 0.215 0.10535 0.131415111 0.180246393
14 0.245
TH01 6 0.299 0.142324 0.17182914 0.222171096
9 0.238
60
1 Calculations based on two heterozygote alleles found in UAE allele frequency database
2 Hardy Weinberg calculations
3 Balding Nichols formulae at two different FST Value
FGA 23 0.162 0.067392 0.089269632 0.131718484
24 0.208
D22S1045 15 0.406 0.201376 0.236017211 0.29064288
16 0.248
D5S818 11 0.264 0.180576 0.213001503 0.27555507
12 0.342
D13S317 11 0.255 0.16779 0.199303064 0.259982879
12 0.329
D7S820 10 0.283 0.149424 0.179303056 0.232466834
11 0.264
SE33 18 0.094 0.016168 0.028289106 0.052235983
19 0.086
D10S1248 14 0.328 0.181056 0.213346499 0.26924128
15 0.276
D1S1656 15 0.151 0.057682 0.078190328 0.118059339
16 0.191
D12S391 18 0.174 0.046284 0.065057259 0.098027087
21 0.133
D2S1338 17 0.205 0.06109 0.082209052 0.118295807
20 0.149
Most Common Profile
Frequency 3.48E-21 5.31E-19 3.10E-16
Discrimination Power For
Most Common Profile 2.88E+20 1.88E+18 3.23E+15
Rarest profile frequency
(2pq)21
9.955 x
10E-92
61
Table 3.3: Population differentiation (locus-by-locus exact test p-value) between UAE and five regional populations for 15
Identifiler STR Loci.
Locus/ Population Kuwaiti (8) India (8) Saudi (8) Egypt (8) Iran (8)
D8S1179 0.00043 0 0.06934 0.00577 0
D21S11 0.18961 0.00021 0.03273 0.01611 0.3034
D7S820 0 0.00105 0 0.14422 0.11488
CSF1PO 0.00771 0 0.00199 0.28927 0.19687
D3S1358 0.13193 0.01863 0.17805 0.10996 0.32399
TH01 0.64225 0.00374 0.93339 0 0.38819
D13S317 0.45192 0 0.00781 0.01139 0.19152
D16S539 0.47292 0 0.68441 0.09367 0.58645
D2S1338 0.01664 0 0.00405 0.40457 0.01023
D19S433 0 0 0 0 0
vWA 0.0187 0 0.16488 0.22881 0.39942
TPOX 0.023 0 0.53425 0.03548 0.04426
D18S51 0.02238 0 0.11677 0 0.20286
D5S818 0.19789 0.00021 0.32408 0.05 0.03438
FGA 0.00218 0.14595 0.00435 0 0.00512
Note: Statistically significant P-value (P<0.05) are indicated in bold
(30,000 Markov steps done).
62
3.5 References
1. Miles SB. The countries and tribes of the Persian Gulf. London: Harrison and
Sons 1919.
2. Tadmouri GO, Nair P, Obeid Y, Al-Ali MT, Al-Khaja N, Hamamy HA,
Consanguinity and reproductive health among Arabs. Reprod Health.
2009;6:17.
3. Abed I, Hellyer P. United Arab Emirates: A new perspective. London: Trident
Press 2001.
4. Garcia-Bertrand R, Simms TM, Cadenas AM, Herrera RJ. United Arab
Emirates: Phylogenetic relationships and ancestral populations. Gene.
2014;533:411-419.
5. Schneider PM, Scientific standards for studies in forensic genetics. Forensic
Sci Int. 2007;165:238-243.
6. Excoffier L, Laval G, Scnheider S. Arlequin ver. 3.0: An integrated software
package for population genetics data analysis. Evol Bioinform. 2005;1:47-50.
7. Al-Enizi M, Ge J, Ismael I, Al-Enezi H, Al-Awadhi A, Al-Duaij W et al.
Population genetic analyses of 15 STR loci from seven forensically-relevant
populations residing in the state of Kuwait. Forensic Sci Int Gen.
2013;7(4):e106-e107.
8. Ruitberg CM, Reeder DJ, Butler JM. STRBase: A short tandem repeat DNA
database for the human identity testing community. Nucl Acids Res.
2001;29(1):320-322.
63
Chapter 4
ALLELE FREQUENCIES OF SHORT TANDEM REPEAT MARKERS
USED FOR FORENSIC APPLICATIONS IN THE ARAB POPULATION OF
THE UNITED ARAB EMIRATES
The data in this chapter augments the study in the previous chapter by inclusion of
other ethnic groups not studied previously. The following chapter has been
accepted by Forensic Science International (FSI): Genetics and currently in the
Press (Appendix 2). The candidate was involved in developing the research
question, providing technical assistance in the laboratory, compiling the data,
drafting the manuscript and undertaking the statistical calculations. She prepared
the manuscript in the format for FSI Genetics and was responsible for assisting in
its submission.
64
Forensic Science International: Genetics. 2017 (In Press)
Allele frequencies of Short Tandem Repeat markers used for Forensic
applications in the Arab population of the United Arab Emirates.
Rebecca J Jones1, Wafa Al Tayyare2,3, , Guan K Tay1,4,5, Habiba Alsafar6,7, William
H Goodwin2.
1 School of Anatomy, Physiology and Human Biology, University of Western
Australia, Crawley, Western Australia.
2 School of Forensic and Applied Sciences, University of Central Lancashire,
Lancashire, United Kingdom.
3 Forensic Evidence Department, Abu Dhabi Police General Head Quarter, Abu
Dhabi, United Arab Emirates.
4 School of Psychiatry and Clinical Neurosciences, University of Western Australia,
Crawley, Western Australia
5 School of Medical and Health Sciences, Edith Cowan University, Joondalup,
Western Australia.
6 Center for Biotechnology, Khalifa University, Abu Dhabi, United Arab Emirates.
7 Faculty of Biomedical Engineering, Khalifa University of Science, Technology
and Research, Abu Dhabi, United Arab Emirates
65
4.1 Introduction
The United Arab Emirates (UAE) lies on the east coast of the Arabian Peninsula with
a coastline at the Arabian Gulf and is neighbours with Saudi Arabia to the west and
Oman to the south. The residents of the country are predominantly expatriates with
only about 11.3% (2015 census data) of approximately 9.6 million residents
comprising UAE nationals. This specific subset are predominantly people of Arab
descent (1).
Throughout history, nomadic Arabian tribes have traversed this region of the Middle
East and this region is also located at a junction where there was constant and regular
human migration between the African, European and Asian continents (2, 3) through
the land bridge around modern Egypt. The human dispersal from Africa across the
land bridge into the Middle East was one of the two initial out of Africa migration
routes. The general region around contemporary UAE, Qatar, Bahrain and Oman,
with borders only defined in the early 1970s, was an alternative migration route from
the initial out of Africa dispersal involving migration from the Horn of Africa across
the Red Sea and into Yemen (4).
Consanguineous marriages are common in societies throughout this region, potentially
limiting the genetic pool. However, a recent report in 2014 cited an increase in genetic
diversity within the Middle East region arising from an increase in non-
consanguineous marriages (5). To appreciate the impact of cultural norms in a region
that represents the hub through which humans dispersed from Africa, it is essential
that studies related to genetic markers are continuously undertaken.
The genome era has and continues to reveal a rich vein of knowledge in disease-
susceptibility genes and in overall genetic diversity of different populations. Given
66
the paradox that exists in a population shaped by extensive migration patterns and
constrained by cultural practices, this study was conceived in an attempt to replicate
the previous data on a set of highly polymorphic Short Tandem Repeat (STR) loci on
the UAE population. The focus of this study, in part, was to make observations
relating to the genetic diversity within the UAE population. It adds to the knowledge
base arising from previous studies, which have also presented autosomal STR allelic
data on UAE populations (2, 6, 7). With the addition of new studies, such as this
present study, the confidence in the information for applications in forensics and
medicine improves with the iterative process and with increases in the population
sample size being interrogated.
4.2 Materials and Methods
4.2.1 Sample Description
This study involved STR analysis of DNA samples from 477 unrelated individuals
from the UAE. These individuals were Emirati Arabs of mixed ethnic origin
predominantly from Abu Dhabi. The results from these samples were then combined
to the previous STR data described in Chapter 3, which used 519 DNA samples from
unrelated Emirati subjects who were largely Emirati Bedouins (6). DNA samples of
individuals who provided consent to have their de-identified DNA samples stored for
research purposes were obtained from the Emirates Family Registry (EFR). The EFR
was established as a resource to collect DNA for genetic association studies (8).
Assistance from EFR staff for this study involved sample collection and storage, and
provision of de-identified samples such that the researchers working on the study did
not have access to any linked personal information. Prior to commencement of this
67
study, approval to undertake the work was obtained from the Ethics committee of the
Ministry of Health of the UAE (2011). The study was also submitted to and approved
by the Human Research Ethics Committee of the University of Western Australia
(RA/4/1/7778).
4.2.2 DNA Extraction
Buccal cells were collected from saliva using the Oragene-DNA kit (Genotek, Ottawa,
Canada) and DNA extracted from buccal cells using the prepIT-L2P system (Genotek)
in accordance with manufacturer’s instructions. The NanoDrop spectrophotometer
(Thermo Scientific, Wilmington DE, USA) was used to determine the quantity and
quality of the extracted DNA.
4.2.3 PCR Multiplex Amplification
The GlobalFiler® PCR Express Amplification Kit (Life Technologies, Carlsbad, CA,
USA) was used to amplify 24 STR markers using half volume (total 7.5 µl) reactions.
There were 21 autosomal STR presented in this analysis: D3S1358, vWA, D16S539,
CSF1PO, TPOX, D8S1179, D21S11, D18S51, D2S441, D19S433, TH01, FGA,
D22S1045, D5S818, D13S317, D7S820, SE33, D10S1248, D1S1656, D12S291 and
D2S1338. The PCR was performed using the GeneAmp® PCR System 9700 using
the manufacturer’s instructions for the PCR cycle program (Life Technologies).
4.2.4 STR Typing
The PCR products were added to a 500 LIZ-Internal Standard (Life Technologies) and
analysed using an ABI 3500 DNA Genetic Analyser with POP-4™ polymer (Life
Technologies). GeneMapper® Software ID-X version 4.0 (Life Technologies) was
used for analysis.
68
The alleles from all 21 autosomal loci reported within this present study were labelled
according to the published nomenclatures and the guidelines for performing STR
analyses of the International Society for Forensic Genetics (ISFG) (9).
4.2.5 Statistical Analysis
The data from this present study was initially compared to population data from the
previous published STR data (6) to identify if there were differences between the two
datasets using locus-by-locus exact tests (with 20,000 Markov steps) with the Arlequin
v3.5.2.1 software (10). Allele frequencies for the 21 autosomal STR markers were
calculated using GeneALEx v6.5 (11, 12). Genetic parameters such as the Power of
Discrimination (PD), Power of Exclusion (PE), Match Probability (MP), typical
Paternity Index (TPI) and Polymorphism Information Content (PIC), were also
calculated using GeneAlEx v6.5 (11, 12) with the appropriate formulas for each of the
parameters (13). The observed and expected heterozygosity values (Ho and He,
respectively) and Hardy-Weinberg equilibrium (HWE) were calculated using an exact
test with the Arlequin v3.5.2.1 software (10). The Bonferroni correction was carried-
out by dividing the critical P value (α) by the number of comparisons being made (n)
to adjust for the multiple STR loci being tested using the following calculation α ÷ n
= 0.05 ÷ 21.
4.3 Results and Discussion
Before the two separate datasets from the UAE population were combined for allele
frequency analysis, a locus-by-locus exact test was carried-out to determine whether
there were any significant variations between them (Table 4.1). Three out of the 21
autosomal STRs (TPOX, FGA and D22S1045) showed significant differences
69
between the two UAE population datasets (p-value < 0.05). However, after applying
the Bonferroni correction (0.002) no significant differences were observed.
Furthermore, when the overall locus-by-locus AMOVA test was carried-out using
Arlequin v3.5.2.1, the resulting fixation index (FST) of 0.00005 showed no significant
variation between the two separate datasets. Consequently, the two datasets were
combined for subsequent analyses totalling 996 samples.
Table 4.1: Population differentiation locus-by-locus exact test between the two
UAE population datasets for each locus
Locus P-Value
D3S1358 0.27590+-0.07084
vWA 0.51635+-0.05404
D16S539 0.46340+-0.05499
CSF1PO 0.27370+-0.6450
TPOX 0.02595+-0.01628*
D8S1179 0.31850+-0.04799
D21S11 0.50080+-0.04294
D18S51 0.05430+-0.01989
D2S441 0.09855+-0.04905
D19S443 0.44905+-0.06866
TH01 0.99075+-0.00272
FGA 0.00945+-0.00366*
D22S1045 0.0560+-0.0057*
D5S818 0.10040+-0.03256
D13S317 0.52585+-0.08496
D7S820 0.20525+-0.05905
SE33 0.44045+-0.08680
D10S1248 0.77245+-0.04410
D1S1656 0.22980+-0.05511
D12S391 0.36060+-0.06192
D2S1338 0.14675+-0.04035
Note: Statistically significant p-value (P<0.05) indicated in bold (20,000 Markov steps done).
*Before the Bonferroni Correction
70
The calculated allele frequencies and genetic parameters for the 21 autosomal STR
markers are presented in Table 4.2. The STR locus with the largest number of alleles
was SE33 (59 alleles), as seen within the first UAE STR dataset described in Chapter
3. The least number of alleles was observed for the locus D16S539 (8 alleles). Eight
of the STR markers deviated from the HWE (D21S11, D18S51, D19S433, TH01,
D22S1045, SE33, D10S1248 and D2S1338). After applying the Bonferroni
correction, only three markers deviated from this HWE (D19S433, SE33 and
D2S1338). The Ho values ranged from 0.687 (TPOX) to 0.917 (SE33). High Ho
values for the UAE population have been reported in previous studies (2, 6, 7).
The PD range was 0.832 (TPOX) to 0.994 (SE33) with a combined PD value of
0.9999999999. The present study has shown a larger range of PD values than seen in
the previous STR dataset from Chapter 3 with only 519 samples (6), which could be
due to the increase in sample size (7). The PD in correlation with MP supports the
high degree of polymorphism between UAE individuals. The combined MP of
2.62515x10-26 is greatly reduced with the increase of sample size compared to when
only 519 samples were tested as described in Chapter 3 (6). The PE range was 0.408
(TPOX) to 0.830 (SE33) with a combined power of exclusion of 0.9999999964.
Allele TPOX has previously been observed to have the lower PD, PE and
Heterozygosity values out of the loci in the previous STR dataset in Chapter 3 and in
the literature (2, 6, 7). The wide range for the PE can be expected as these values do
vary across individual cases (14). The high value for the combined PE indicates that
there is a higher fraction of the individuals with allele variations, highlighting genetic
diversity of UAE individuals. The PIC range was 0.653 (TPOX) to 0.945 (SE33).
These high informative values support the heterozygosity values indicating the high
71
degree of genetic polymorphism. The typical PI value for every marker was larger
than 1.0 making it useful for paternity testing applications (14).
4.4 Conclusion
The data presented here indicates that the 21 autosomal STR markers from the
GlobalFiler® Express amplification kits have forensic applications for individual
identification and paternity testing in the local population of the UAE. The similarity
between the two datasets provides a degree of reassurance that potential errors and
biases have been reduced or eliminated. Furthermore, consolidation of the data
provides representation of the distribution of various ethnic groups that make-up
nationals in the UAE. As further studies of Arab populations in the region become
available, it may be possible to develop a greater understanding of the relationships
between the different jurisdictions on the Arabian Peninsula.
72
Table 4.2: Allele frequency data for 996 individuals from UAE Population for 21 autosomal STR loci.
Allele D3S1358 vWA D16S539 CSF1PO TPOX D21S11 D8S1179 D18S51 D2S441 D19S433 TH01
4 0.001
5 0.001
5.3 0.001
6 0.001 0.006 0.298
6.2 0.001
7 0.003 0.004 0.211
8 0.031 0.006 0.461 0.007 0.109
8.3 0.001
9 0.151 0.030 0.142 0.006 0.001 0.002 0.242
9.3 0.119
10 0.001 0.096 0.282 0.117 0.070 0.005 0.133 0.002 0.014
10.2 0.001
11 0.001 0.359 0.310 0.238 0.096 0.019 0.401 0.018 0.003
11.2 0.001
11.3 0.082
12 0.001 0.229 0.311 0.029 0.148 0.119 0.089 0.093
12.2 0.006
12.3 0.001 0.005
13 0.004 0.001 0.123 0.048 0.003 0.240 0.179 0.023 0.215
13.2 0.001 0.036
14 0.052 0.065 0.010 0.010 0.001 0.170 0.148 0.233 0.238 0.001
14.2 0.057
15 0.257 0.132 0.001 0.001 0.186 0.137 0.031 0.140
15.2 0.001 0.085 0.001
16 0.297 0.244 0.063 0.116 0.002 0.051 0.001
16.2 0.002 0.049
17 0.246 0.268 0.011 0.117 0.003
73
17.2 0.001 0.005
18 0.130 0.210 0.002 0.077 0.001
18.2 0.001
19 0.014 0.068 0.002 0.049
20 0.009 0.019
21 0.002 0.005
21.2 0.002
22 0.005
24 0.001
26 0.001
27 0.024
28 0.165
29 0.219
29.2 0.001
30 0.239
30.2 0.027
31 0.044
31.2 0.096
31.3 0.001
32 0.007
32.2 0.123
33 0.002
33.2 0.038
34 0.002
34.2 0.006
35 0.006
35.2 0.001
36 0.002
n 996 996 996 996 995 996 996 996 996 996 996
Ho 0.750 0.801 0.738 0.715 0.687 0.827 0.798 0.858 0.732 0.819 0.766
He 0.766 0.799 0.771 0.725 0.697 0.839 0.839 0.878 0.752 0.852 0.782
74
P-value 0.399 0.537 0.383 0.196 0.195 0.020 0.202 0.012 0.056 0.000 0.031
PD 0.908 0.928 0.916 0.872 0.863 0.953 0.955 0.972 0.900 0.962 0.920
MP 0.092 0.072 0.084 0.129 0.137 0.047 0.045 0.028 0.100 0.038 0.081
PE 0.510 0.601 0.489 0.452 0.408 0.650 0.601 0.711 0.479 0.635 0.538
TPI 2.000 2.513 1.908 1.754 1.597 2.890 2.475 3.521 1.866 2.762 2.137
PIC 0.726 0.768 0.738 0.673 0.653 0.819 0.819 0.864 0.718 0.836 0.748 N: Number of Samples, Ho: Observed Heterozygosity, He: Expected Heterozygosity, HWE: Hardy Weinberg p-value, PD: Power of Discrimination,
PE: Power of Exclusion, MP: Match Probability, PIC: Polymorphic Information Content, TPI: Typical Paternity Index, CPD. Where no alleles were
identified, this allele number was deleted from the table.
75
Table 4.2 continued
Allele FGA D22S1045 D5S818 D13S317 D7S820 SE33 D10S1248 D1S1656 D12S391 D2S1338
4
4.2 0.001
5
5.3 0.001
6 0.001
6.2
6.3 0.005
7 0.001 0.001 0.021
7.3 0.001 0.001
8 0.001 0.012 0.136 0.174 0.005 0.009
8.3
9 0.041 0.044 0.088 0.002 0.010 0.002
9.3 0.001
10 0.009 0.110 0.078 0.297 0.001 0.002 0.007
10.2
11 0.165 0.287 0.251 0.255 0.002 0.010 0.100
11.2
11.3
12 0.015 0.355 0.338 0.144 0.004 0.033 0.114
12.2 0.002
12.3
13 0.003 0.180 0.117 0.021 0.016 0.186 0.109
13.2 0.003
13.3 0.001
14 0.071 0.014 0.035 0.001 0.033 0.328 0.117 0.001 0.002
14.2 0.001
14.3 0.002 0.005
15 0.413 0.001 0.001 0.029 0.284 0.145 0.023 0.001
76
15.2 0.001 0.001
15.3 0.005 0.030
16 0.243 0.001 0.067 0.112 0.200 0.024 0.047
16.1 0.002
16.2 0.001
16.3 0.003 0.050
17 0.004 0.077 0.001 0.087 0.034 0.055 0.127 0.197
17.2
17.3 0.001 0.032 0.007
18 0.005 0.004 0.101 0.002 0.006 0.177 0.099
18.2 0.001
18.3 0.016 0.012
19 0.063 0.082 0.001 0.123 0.140
19.1 0.001
19.2 0.005 0.001 0.001
19.3 0.005 0.002
20 0.087 0.042 0.128 0.164
20.2 0.003 0.004
20.3 0.001
21 0.117 0.018 0.125 0.064
21.1 0.001
21.2 0.004 0.015
22 0.152 0.006 0.088 0.043
22.2 0.006 0.020
23 0.167 0.003 0.089 0.109
23.2 0.002 0.021
24 0.217 0.002 0.049 0.076
24.2 0.002 0.030
25 0.109 0.001 0.019 0.048
25.2 0.001 0.034
25.3 0.001
77
26 0.040 0.005 0.009
26.2 0.043
27 0.007 0.002
27.2 0.054
28 0.005
28.2 0.066
28.3 0.001
29 0.002 0.002
29.2 0.059
30 0.001
30.2 0.038
31 0.001 0.001
31.2 0.001 0.036
31.3
32 0.001
32.2 0.022
33 0.002
33.2 0.006
34 0.010
34.2 0.004
35 0.004
35.2 0.001
36 0.002
36.2 0.001
37 0.002
n 991 996 996 996 996 991 996 996 996 996
Ho 0.850 0.689 0.749 0.785 0.783 0.917 0.730 0.859 0.878 0.850
He 0.863 0.732 0.746 0.782 0.788 0.948 0.763 0.883 0.886 0.877
P-value 0.294 0.024 0.629 0.648 0.230 0.000 0.009 0.305 0.376 0.000
PD 0.967 0.832 0.888 0.922 0.922 0.994 0.907 0.975 0.975 0.972
MP 0.034 0.108 0.112 0.078 0.078 0.006 0.093 0.025 0.025 0.028
78
PE 0.695 0.411 0.508 0.572 0.568 0.830 0.476 0.713 0.751 0.695
PI 3.333 1.608 1.992 2.326 2.304 6.024 1.852 3.546 4.098 3.333
PIC 0.848 0.693 0.704 0.751 0.755 0.945 0.725 0.871 0.875 0.864
CPD 0.999999999999999
CMP 4.38E-27
CPE 0.999999996 N: Number of Samples, Ho: Observed Heterozygosity, He: Expected Heterozygosity, HWE: Hardy Weinberg p-value, PD: Power of Discrimination,
PE: Power of Exclusion, MP: Match Probability, PIC: Polymorphic Information Content, TPI: Typical Paternity Index, CPD: Combined Match
Probability, CPE: Combined Power of Exclusion, CMP: Combined Match Probability. Where no alleles were identified, this allele number was deleted
from the table.
79
4.5 References
1. Osman AE, Alsafar H, Tay GK, Theyab J, Mubasher M, Sheikh N, et al.
Autosomal short tandem repeat (STR) variation based on 15 loci in a
population from the Central Region (Riyadh Province) of Saudi Arabia. J
Forensic Res. 2015;6(1):1-5.
2. Garcia-Bertrand R, Simms TM, Cadenas AM, Herrera RJ. United Arab
Emirates: phylogenetic relationships and ancestral populations. Gene.
2014;533(1):411-9.
3. Kundu S, Ghosh SK. Trend of different molecular markers in the last decades
for studying human migrations. Gene. 2015;556(2):81-90.
4. Beyin A. The Bab al Mandab vs the Nile-Levant: An appraisal of the two
dispersal routes for early modern humans out of Africa. African Archaeol Rev.
2006;23(1-2):5-30.
5. Tadmouri GO, Sastry KS, Chouchane L. Arab gene geography: From
population diversities to personalized medical genomics. Glob Cardiol Sci
Pract. 2014;2014(4):394-408.
6. Ali Alhmoudi O, Jones RJ, Tay GK, Alsafar H, Hadi S. Population genetics
data for 21 autosomal STR loci for United Arab Emirates (UAE) population
using next generation multiplex STR kit. Forensic Sci Int. 2015;19:190-1.
7. Alshamali F, Alkhayat AQ, Budowle B, Watson ND. STR population diversity
in nine ethnic populations living in Dubai. Forensic Sci Int. 2005;152(2-
3):267-79.
8. Alsafar H, Jama-Alol KA, Hassoun AAK, Tay GK. The prevalence of Type 2
Diabetes Mellitus in the United Arab Emirates: Justification for the
80
establishment of the Emirates Family Registry. International Journal of
Diabetes in Developing Countries. 2012;32(1):25-32.
9. Schneider PM. Scientific standards for studies in forensic genetics. Forensic
Sci Int. 2007;165(2-3):238-43.
10. Excoffier L, Laval G, Schneider S. Arlequin (version 3.0): An integrated
software package for population genetics data analysis. Evol Bioinform
Online. 2005;1:47-50.
11. Peakall R, Smouse PE. GenAlEx 6.5: Genetic analysis in Excel. Population
genetic software for teaching and research-an update. Bioinformatics.
2012;28(19):2537-9.
12. Peakall ROD, Smouse PE. Genalex 6: Genetic analysis in Excel. Population
genetic software for teaching and research. Mol Ecol Notes. 2006;6(1):288-95.
13. Huston KA. Statistical Analysis of STR Data. Profiles in DNA. 1998;1(3):14-
5.
14. Bentayebi K, Abada F, Ihzmad H, Amzazi S. Genetic ancestry of a Moroccan
population as inferred from autosomal STRs. Meta gene. 2014;2:427-38.
81
Chapter 5
A COMPARATIVE ANALYSIS OF AUTOSOMAL SHORT TANDEM
REPEAT (STR) ALLELE FREQUENCIES OF POPULATIONS IN THE
UNITED ARAB EMIRATES AND SURROUNDING REGIONS
The previous chapters describe autosomal STR data from 996 unrelated UAE
individuals. This chapter compares the data collected in this project with the
autosomal STR data published for populations of the Middle East, North Africa
and South Asia to examine the relationship between these populations. The
analysis further increases our knowledge of diversity in these regions.
82
5.1 Introduction
Population genetic analyses provide important advancements in studying human
genetic diversity for applications in forensic studies, paternity identification and
medical research. Such DNA-based analyses have also provided the foundation to
examine the impact of human migration routes on the degree of genetic variation
amongst populations. Specifically, the use of the highly variable autosomal Short
Tandem Repeats (STRs) allow for population-specific DNA analyses that can provide
an understanding of the extent of human genetic variation amongst neighbouring and
geographically distant populations.
The Middle East is located amongst some of the earliest known bidirectional human
migration routes, linking dispersal through Africa, Asia and Europe (1-3). However,
there is a paucity of genetic analyses that have included Middle Eastern populations
relative to populations from other parts of the world (4). The migration out of Africa
is postulated to have involved at least two proposed routes through the Horn of Africa
(into the Arabian Peninsula) and through the Levant region, both into the Middle East
(see Figure 5.1). It is important to understand the impact of the two separate migration
routes and the ongoing human dispersal that is continuously taking place throughout
the Middle East region on the genetic diversity of the populations in the region.
The United Arab Emirates (UAE) plays a significant role in these ancient migration
routes as the proposed route from the Horn of Africa through the UAE and into South
Asia has been highlighted in the literature with the use of DNA analyses (5).
Archaeological discoveries have also indicated the climatic conditions in the UAE
(and the Hajar Mountains of Oman) at this time would have been conducive to
settlement and migration (4).
83
Figure 5.1: Ancient human migration routes involving the Middle East. Map
generated using published data (1-8).
The UAE consists of the seven Emirates Abu Dhabi, Dubai, Sharjah, Ajman, Ra’s Al-
Khaymah, Al-Fujairah and Umm Al-Quwain. The country is known for its trade
expansions over several decades with countries in surrounding regions such as Iran
and other South Asian populations (9) and Dubai has been identified as the major
maritime trading centre of the lower Arabian Peninsula. Additionally during the 1960s
and 1970s oil-revenue-financed development boom, Western relationships (such as
with the United Kingdom) were also established (9). In more recent times, the
residents of the UAE have been observed to be predominantly expatriates with other
UAE nationals of mixed ethnic backgrounds. The noted subset residing within the
UAE are primarily of Arab descent with additional native populations and tribal
groups such as the Bedouins. Even with the increase of expatriates due to trading
relationships, the Arabic populations remain traditional within the Arabic cultures.
The UAE is an important population to consider in the region at the genetic-level due
to the ethnically diverse residents of the country resulting from historic tribal group
migrations and advancements in trade relationships. However, the UAE population
has been minimally examined at the genetic level and compared to other populations
from surrounding regions. Accordingly, the aim of this study was to advance
84
knowledge from previous genetic-based studies (10-12) about the UAE by increasing
sample size and the range of selected populations for comparison to examine the
impact of human dispersal through the Middle East, North Africa and South Asia and
the resulting genetic relationships.
5.2 Methods
The allele frequency data used for this study were previously presented in Chapter 4
and describes the autosomal STR loci polymorphisms for 996 Arabic nationals from
the UAE. To complete the analysis, published population data from the Middle East
and North Africa (MENA region) and select South Asian countries were collected.
The Middle East populations included the UAE (11), Saudi Arabia (13), Yemen (10),
Oman (10), Qatar (14), Kuwait (15), Iraq (16), Jordan (17), Syria (18), and Lebanon
(19). North African and South Asian population data were from Egypt (20), Libya
(21), Malta (22), Tunisia (23), Algeria (24), Morocco (25), Iran (7), Pakistan (26),
India (27), and Bangladesh (28) (Figure 5.2).
The statistical analyses for the inter-population comparisons involved the six common
loci used in all the published data (namely vWA, CSF1PO, TPOX, TH01, D13S317
and D7S820). Initially, the combined statistical parameters and heterozygosity values
for the six common loci for each population were calculated using the data from
publications. The combined statistical parameters calculated for each population was
the Combined Power of Discrimination (CPD), Combined Power of Exclusion (CPE)
and Combined Match Probability (CMP) using the appropriate statistical equations to
determine the relevance of the six loci in the analysis (29).
85
ALGERIA LIBYA EGYPT
MOROCCO TUNISIA
MALTA
SAUDI ARABIA
YEMEN
OMAN
U.A.E. QATAR
JORDAN
LEBANON
SYRIA
IRAQ IRAN
PAKISTAN
INDIA BANGLADESH
North Africa Middle East South Asia
KUWAIT
Figure 5.2: Geographical location of the countries with published population data
used for the meta-analysis in this study. Map generated using published data (7, 10,
11, 13-28).
The FST values of the shared six loci were calculated using Fisher’s locus-by-locus
Exact Test (using 20,000 Markov steps) using the Arlequin v3.5.2.1 software (30).
For each of the FST values from the locus-by-locus exact test calculated, the number
of significant differences (P-value < 0.05) between any two populations was counted
for all six loci. Additionally, an extended set of 15 of the most commonly published
STR loci (namely D3S1358, vWA, D16S539, CSF1PO, TPOX, D21S11, D8S1179,
D18S51, D19S433, TH01, FGA, D5S818, D13S317, D7S820 and D2S1338) was
compared and the percentage of significant differences using the FST values were
calculated where data was available between any two populations.
5.3 Results
5.3.1 Within-population Genetic Variability Measures
By using the published statistical parameters of the six common loci for the
populations (Tunisia and Bangladesh parameters not available), the combined
86
parameters were calculated. The CPD was similar in all populations with the range of
0.99999913 (Libya) to 0.999999871 (Yemen) and the CPE were high overall with a
range of 0.950134 (Qatar) to 0.999432 (Jordan). The CMP varied between
populations but all with low probabilities below 5.00 x 10-5 (Table 5.1).
Table 5.1: The calculated combined parameters for the six common loci for each
population.
The observed heterozygosity values for the common six loci are shown in Figure 5.3.
The heterozygosity values for the majority of populations, except for Jordan, were
high for the loci representing substantial genetic diversity. The heterozygosity values
for the six loci for the Jordanian population ranged from a low of 0.220 (vWA) to
POPULATION COMBINED
POWER OF
DISCRIMINATION
COMBINED
POWER OF
EXCLUSION
COMBINED
MATCH
PROBABILITY
UAE (PRESENT
STUDY)
0.999999386 0.988943 6.27E-07
SAUDI ARABIA (13) 0.999998839 0.975964 1.16052E-06
QATAR (14) 0.999999381 0.950134 6.19446E-07
UAE (11) 0.999999076 0.979605 9.24449E-07
OMAN (10) 0.999998055 0.990594 1.94513E-06
YEMEN (10) 0.999999871 0.988433 1.40457E-06
LEBANON (19) 0.99999922 0.983311 7.79662E-07
SYRIA (18) 0.999999139 0.988335 8.6078E-07
JORDAN (17) 0.999999446 0.999432 5.5442E-07
IRAQ (16) 0.999998422 0.962225 1.57809E-06
KUWAIT (15) 0.999998194 0.978309 1.80627E-06
EGYPT (20) 0.999998697 0.982859 1.30333E-06
LIBYA (21) 0.99999913 0.986345 8.70071E-07
ALGERIA (24) 0.999998533 0.994072 1.46701E-06
MOROCCO (25) 0.999999545 0.987986 4.59474E-06
MALTA (22) 0.999999472 0.9894 5.2786E-07
IRAN (7) 0.999999034 0.986423 9.65997E-07
PAKISTAN (26) 0.999999398 0.981284 6.01986E-07
INDIA (27) 0.99999616 0.998577 3.8403E-06
87
0.390 (TPOX), reflecting a more homogeneous population. The remaining
populations, including the present UAE study, varied in the range of values with vWA
heterozygosity values between 0.542 (Qatar) and 0.889 (Tunisia), CSF1PO between
0.568 (Tunisia) and 0.889 (India), TPOX between 0.563 (Kuwait) and 0.790
(Morocco), TH01 between 0.713 (Yemen) and 0.825 (Syria and Iraq), D13S317
between 0.618 (Qatar) and 0.812 (Yemen), and D7S820 between 0.713 (Yemen) and
0.907 (India).
5.3.2 Regional Population Genetic Comparison of the Middle East
The locus-by-locus exact test was carried-out between each of the 21 populations and
compared for the common six loci. Table 5.2 summarises the number of significant
differences (p-value < 0.05) found between the FST values compared. Initially, the
Middle East regional populations were compared to each other. The highest number
of significant differences between populations (6/6 loci) was observed for Saudi
Arabia, Jordan and Lebanon with other Middle East countries.
When data from the present UAE study was compared to the other Middle East
populations, Saudi Arabia was found to have the greatest number of significant
differences (6/6 loci) with Kuwait, Jordan and Lebanon also having a high number of
significant differences with the UAE (5/6 loci). The least number of significant
differences with the present UAE study was found with Syria and the previously
published UAE dataset (2/6 loci), then Iraq, Qatar and Yemen (1/6 loci), with Oman
and the present UAE study showing no significant differences between the loci.
88
Figure 5.3: Observed heterozygosity values for the common six loci for each of the 21 populations in the analysis.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Pre
sen
t St
ud
y
Mo
rocc
o
Alg
eria
Tun
isia
Mal
ta
Lib
ya
Egyp
t
Leb
ano
n
Jord
an
Syri
a
Iraq
Ku
wai
t
Sau
di
Qat
ar
UA
E
Om
an
Yem
en
Iran
Pak
ista
n
Ind
ia
Ban
glad
esh
Het
ero
zygo
sity
Fre
qu
ency
Populations
Observed Heterozygosity
vWA
CSF1PO
TPOX
TH01
D13S317
D7S820
Autosomal Loci
89
Table 5.2: Number of significant differences (p-value<0.05) between two populations for the common six loci in the analysis.
90
5.3.3 Inter-population Genetic Comparison
When comparing the North African populations, the least significant differences were
observed between Libya, Algeria and Egypt (2/6 loci) but others had a high number
of significantly different loci. The South Asian countries shared less significant
differences between each other, with the greatest number of significant differences
between Pakistan and India (4/6 loci).
When the present UAE study was compared to the data from the South Asian
populations the number of significant differences ranged from 6/6 loci with India to
1/6 loci with Iran. Furthermore, when the present UAE study was compared to the
North African populations, the greatest number of significant differences was seen
with Morocco (6/6 loci), Tunisia (4/6 loci), then with Malta, Algeria and Egypt (3/6
loci), with the least number of significant differences with Libya (2/6 loci).
5.3.4 Effect of Increased Number of STR Markers
When 15 of the most commonly used STR markers in publications were compared
between the present UAE study and the other 20 populations, a better delineation of
the genetic relationships was obtained than observed with the examination of the
common six STR loci (see Appendix 3). Table 5.3 summarises the number of
significant differences between any two populations. Table 5.3 shows how the present
UAE study exhibited numerous significant differences (P-value ≤ 0.05) with
populations from Morocco, Saudi Arabia, Lebanon, Kuwait, Jordan and India (more
than 80% significant differences overall). The populations compared to the present
UAE study, which had the least number of significant differences when using a greater
number of markers, were the published UAE dataset, Oman, Yemen and Iraq (less
than 20% significant differences overall).
91
Between the present UAE study and Oman only 1 out of 13 loci (8%) was significantly
different indicating a genetic relationship with more confidence than with the use of
only six loci. The improved confidence of genetic relationships was also observed
between populations with greater significant differences. When the common six STR
loci were compared, India and Morocco both exhibited 100% significant difference
with the present UAE study. However, the extent of genetic difference between
Morocco and India compared to the present UAE study was refined using 15 STR loci,
with only 80% significant difference between India and the present UAE study
compared to 100% significant difference between the present UAE study and
Morocco, providing a greater understanding of the degree of genetic relationships
between the populations.
92
Table 5.3: Number of significant differences (p-value<0.05) between two populations for the common loci in the analysis (up to
15 loci).
93
5.4 Discussion
5.4.1 Significance of Inter-population Genetic Comparisons
By comparing genetic relationships between the populations from the MENA and
South Asian regions, we can gain a greater understanding of the extent of ethnic
admixture with respect to human migration using autosomal STR analysis.
Unfortunately, publications utilised in this analysis did not contain the same set of loci
with allele frequency descriptions and hence limited the number of loci able to be
compared between populations. The reduced number of STR loci analysed still
produced high discriminatory and exclusionary values in all populations from North
Africa, the Middle East and South Asia, and highlighted how polymorphic the shared
six loci were for human identification, paternity testing and disease susceptibility
applications. However, when compared to the original datasets for all populations the
resulting PD, PE and MP values improved with the increase of STR loci studied in the
individual populations (7, 11, 15, 18, 20, 21, 25). An increase in autosomal STR loci
in the literature will provide access to an increased number of STR loci to be compared
between different populations in the future.
5.4.2 Heterozygosity Analysis
Analysing observed heterozygosity values in populations provide information on
genetic structure and potential genetic history of the particular population. Of the
common six loci tested in the different populations, the heterozygosity range is
considerably high ranging from 0.542 (Qatar; vWA) to 0.907 (India; D7S820) in
support of North Africa, the Middle East and South Asia having observable ethnic
admixture and genetic diversity. The Jordanian population however has the lowest
heterozygosity values. The known historical background and significant geographical
94
location of Jordan as a “major transit zone” would provide the expectation of larger
observed heterozygosity values from the residing populations. However, the literature
describes outlier populations residing in Jordan amongst groups such as the Bedouin
(17, 31). Furthermore, the observed low heterozygosity values seen in this analysis
could also, in part, be due to common consanguineous marriages amongst Jordanian
populations and the data being retrieved from a relatively isolated population within
the region (17).
5.4.3 Inter-population Genetic Comparison using Six Autosomal STR Loci
5.4.3.1 Regional genetic comparisons with the present UAE study
The locus-by-locus test for the common six loci showed the dataset from the Saudi
Arabia population was significantly different at all of the common loci with the present
UAE study. Saudi Arabia is a large country, which includes Bedouin and isolated
tribes that have not dispersed from the region and have inhabited the region for
thousands of years (13). This is supported by the degree of significant differences
observed in this study between Saudi Arabia and the present UAE study, Lebanon and
Jordan. Less significant differences between Saudi Arabia and Arabian Peninsula
populations such as Oman are likely to reflect the historical migration of Omani
individuals to Saudi Arabia (and additional peninsula countries) prior to the 1970s for
work and education (9, 13). Previous analysis of historical human dispersal between
Yemen and Saudi Arabia (4) indicates that these two populations are similar.
However, the analysis here shows that additional STR loci are required to improve the
resolution of this study.
Minimal significant differences were seen between the present UAE study and the
previously published dataset on the UAE publication (11). This supports the present
95
study representing the genetic information of the UAE. The present UAE study also
showed minimal significant differences at the common six loci with Arabian Peninsula
populations (excluding Saudi Arabia and Kuwait). The lack of significant differences
between Oman and the UAE is indicative of the neighbouring countries sharing
historical events relating to dispersal and ethnic admixture (4, 9). Furthermore, the
genetic relationship between the UAE, Yemen and Qatar likely reflects the shared
human dispersal route from the initial migration out of Africa from the Horn of Africa
and into the Arabian Peninsula. The greater distance between Kuwait and additional
Levant populations of Jordan and Lebanon, is indicative of how the Levant region
shared a different initial migration route out of Africa through Egypt and into Europe
(1). Lebanon has been highlighted within the literature as being part of an expansion
of ethnicities during historical times such as during the Ottoman Empire and involving
a greater variety of cultural and religious practices within the ethnicities in the country
(32). This is supported in this analysis as the Lebanese population shared a number
of close relationships (indicated by less significant differences) with North African
populations such as Malta, Middle Eastern populations such as Syria and Iraq and
South Asian populations such as Iran.
5.4.3.2 Broader population genetic comparison with the present UAE study
The Moroccan and Indian populations were seen to have significant differences with
the present UAE study for all of the common loci. Additionally, Morocco appeared
to be one of the more genetically distant populations compared to all the populations
in this analysis. This observation supports the literature, which indicates no
relationship clustering in published Multidimensional Scaling plots between Morocco
and Middle East populations such as Syria (18, 25), and North African populations
such as Libya (21) and Egypt (18). The degree of variation amongst the Moroccan
96
population and the North African and Middle East populations can be explained due
to the additional migration between Morocco and European countries such as Spain
(25).
The Indian population also showed a large number of significant differences when
compared to the populations of the Middle East and North Africa. There are many
endogamous groups across the large country that is India (33). The ethnic history
using genetic literature suggests that the Indian population belongs to two different
classifications known commonly as the Dravidians and the Aryans. The tribal groups
in contemporary India arose historically from these two groups, and inhabit different
areas throughout India. This presumably increases the observed heterozygosity and
the presence of genetic diversity, with cultural and linguistic differences seen between
closely proximate groups (33, 34). Due to the high degree of genetic diversity of the
Indian population, it is not surprising that genetic differences are seen between the
Indian population, the Middle East and North Africa.
Less significant differences were seen between the present UAE study and Iran. The
Iranian population was also seen to show less significant differences with other Middle
East populations such as Iraq, the UAE (published data) and Lebanon. These genetic
relationships are supported in the literature as Iran plays a significant role in human
dispersal from South Asia and Europe, such as maritime trade across the Persian Gulf
to the UAE and historical events shared between the Levant populations (7, 35). A
greater degree of significant differences is seen with further geographical distance
between the Middle Eastern and South Asian countries. This is supported in the
literature (36) and the analysis shows the other South Asian countries (Pakistan,
Bangladesh and India) compared to the present UAE study and other Middle Eastern
countries exhibit an increase in significant differences with greater geographical
97
distance between them. The impact of geographical distance on the number of
significant genetic differences was also observed between the North African
populations with closer proximity to the Middle East when compared to the present
UAE study. Libya and Egypt had less significant genetic differences with the present
UAE study than with Malta and Morocco.
5.4.4 Significance of Increasing Number of Autosomal STR Loci in Analyses
Even though the calculated parameters for the common six loci were found to show
strong CPD, CPE and low CMP results with high heterozygosity values (excluding
Jordan), the number of loci used in such analyses must be increased. Improved
interpretation of results can be seen when the number of autosomal STRs was
increased up to 15 loci between the present UAE study and the published population
data. For example, when the present UAE study was compared to the UAE publication
for the common six loci (33.33% significant differences) the outcome did not reflect
the likely “true” relationships when compared to the outcome from the comparison of
15 loci (13.33% significant differences) showing how there is a greater genetic
relationship between the two datasets. Furthermore, greater understanding of the
impact between populations with more significant differences can occur with the use
of 15 loci. The Indian population showed 100% significant differences when the
common six loci were compared to the present UAE study, however the impact was
reduced when 15 loci were compared showing only 80% significant differences,
lessening the impact of genetic difference between India and the present UAE study
than what was observed between the Moroccan population and present UAE study
(100% significant differences). Furthermore, inconsistent relationships such as seen
between Yemen and Saudi Arabia have to be analysed further with additional STR
markers.
98
5.5 Conclusion
This analysis has provided the ability to understand the variety of significant
differences amongst populations from the Middle East, North Africa and South Asia.
The results have indicated the relationship between historical events, migration routes
and likely impacts upon genetic diversity. Future research of populations using an
increased number of autosomal STR loci and greater sample sizes would allow for
improvements into factors that impact genetic diversity.
The UAE population shows wide variation of relationships throughout the MENA
region and South Asia. The significant relationships coincide with migratory factors,
cultural and linguistic relationships and past and present trade across the region. This
analysis has provided greater understanding into multi-ethnic countries within the
Middle East. Additionally, the analysis has highlighted the importance of increasing
the number of autosomal STRs in the analyses to provide a greater understanding of
the degree of genetic variation amongst close and distant populations.
99
5.6 References
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3. Maca-Meyer N, González AM, Pestano J, Flores C, Larruga JM, Cabrera VM.
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5. Beyin A. The Bab al Mandab vs the Nile-Levant: An Appraisal of the two
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6. Ermini L, Der Sarkissian C, Willerslev E, Orlando L. Major transitions in
human evolution revisited: A tribute to ancient DNA. J Hum Evol. 2015;79:4-
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7. Shepard EM, Herrera RJ. Iranian STR variation at the fringes of
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8. Fernandes V, Alshamali F, Alves M, Costa MD, Pereira JB, Silva NM et al.
The Arabian cradle: Mitochondrial relicts of the first steps along the southern
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9. Anthony JD, Hearty JA. Eastern Arabian States: Kuwait, Bahrain, Qatar, the
United Arab Emirates, and Oman. The Government and Politics of the Middle
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10. Alshamali F, Alkhayat AQ, Budowle B, Watson ND. STR population diversity
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12. Ali Alhmoudi O, Jones RJ, Tay GK, Alsafar H, Hadi S. Population genetics
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13. Osman AE, Alsafar H, Tay GK, Theyab J, Mubasher M, Sheikh N, et al.
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population from the Central Region (Riyadh Province) of Saudi Arabia. J
Forensic Res. 2015;6(1):1-5.
14. Perez-Miranda AM, Alfonso-Sanchez MA, Pena JA, Herrera RJ. Qatari DNA
variation at a crossroad of human migrations. Hum Hered. 2006;61(2):67-79.
15. Alenizi M, Goodwin W, Ismael S, Hadi S. STR data for the AmpFlSTR
Identifiler loci in Kuwaiti population. Leg Med. 2008;10(6):321-5.
16. Barni F, Berti A, Pianese A, Boccellino A, Miller MP, Caperna A, et al. Allele
frequencies of 15 autosomal STR loci in the Iraq population with comparisons
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2007;167(1):87-92.
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17. Azab M, Al-Bashir N, Momani SN, Al-Nasser A, Alkaraki AK, Khabour O.
Comparison between frequencies of several STRs loci in Jordan with
neighboring countries. Jordan Med J. 2010;44(1):55-60.
18. Abdin L, Shimada I, Brinkmann B, Hohoff C. Analysis of 15 short tandem
repeats reveals significant differences between the Arabian populations from
Morocco and Syria. Leg Med. 2003;5:S150-S5.
19. El Andari A, Othman H, Taroni F, Mansour I. Population genetic data for 23
STR markers from Lebanon. Forensic Sci Int Genet. 2013;7(4):e108-13.
20. Coudray C, Guitard E, el-Chennawi F, Larrouy G, Dugoujon JM. Allele
frequencies of 15 short tandem repeats (STRs) in three Egyptian populations
of different ethnic groups. Forensic Sci Int. 2007;169(2-3):260-5.
21. Khodjet-el-Khil H, Fadhlaoui-Zid K, Gusmao L, Alves C, Benammar-
Elgaaied A, Amorim A. Allele frequencies for 15 autosomal STR markers in
the Libyan population. Annals of Hum Biol. 2012;39(1):80-3.
22. Cassar M, Farrugia C, Vidal C. Allele frequencies of 14 STR loci in the
population of Malta. Leg Med. 2008;10(3):153-6.
23. Cherni L, Loueslati Yaacoubi B, Pereira L, Alves C, Khodjet-El-Khil H, Ben
Ammar El Gaaied A, et al. Data for 15 autosomal STR markers (Powerplex 16
System) from two Tunisian populations: Kesra (Berber) and Zriba (Arab).
Forensic Sci Int. 2005;147(1):101-6.
24. Bosch E, Clarimon J, Perez-Lezaun A, Calafell F. STR data for 21 loci in
northwestern Africa. Forensic Sci Int. 2001;116:41-51.
25. Bentayebi K, Abada F, Ihzmad H, Amzazi S. Genetic ancestry of a Moroccan
population as inferred from autosomal STRs. Meta Gene. 2014;2:427-38.
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26. Rakha A, Yu B, Hadi S, Sheng-bin L. Population genetic data on 15 autosomal
STRs in a Pakistani population sample. Leg Med. 2009;11(6):305-7.
27. Singh A, Trivedi R, Kashyap VK. Polymorphisms at fifteen tetrameric short
tandem repeat loci in three ethnic populations of Bengal, India. Leg Med.
2006;8(3):191-3.
28. Ferdous A, Ali ME, Alam S, Hasan M, Hossain T, Akhteruzzaman S. Forensic
evaluation of STR data for the PowerPlex 16 System loci in a Bangladeshi
population. Leg Med. 2009;11(4):198-9.
29. Huston KA, Statistical analysis of STR data. Profiles in DNA. 1998;1(3):14-
5.
30. Excoffier L, Laval G, Schneider S. Arlequin (version 3.0): An integrated
software package for population genetics data analysis. Evol Bioinformatics
Online. 2005;1:47-50.
31. Zanetti D, Sadiq M, Carreras-Torres R, Khabour O, Alkaraki A, Esteban E, et
al. Human diversity in Jordan: Polymorphic Alu insertions in general
Jordanian and Bedouin groups. Hum Biol. 2014;86 (2):131-8.
32. Chouery E, Coble MD, Strouss KM, Saunier JL, Jalkh N, Medlej-Hashim M,
et al. Population genetic data for 17 STR markers from Lebanon. Leg Med.
2010;12(6):324-6.
33. Ashma R, Kashyap VK. Genetic profile based upon 15 microsatellites of four
caste groups of the eastern Indian state, Bihar. Ann Hum Biol. 2003;30(5):570-
8.
34. Fareed M, Afzal M. Genetic structure of human populations based on 5 gene
loci: A preliminary report. Northern India Gene Reports. 2016;4:244-8.
103
35. Grugni, V., Battaglia, V., Kashani, B., Parolo, S., Al-Zahery, N, et al. Ancient
migratory events in the Middle East: New clues from the Y-chromosome
variation of modern Iranians. PLoS One. 2012;7(7):1-14.
36. Silva NM, Pereira L, Poloni ES, Currat M. Human neutral genetic variation
and forensic STR data. PLoS One. 2012;7(11):1-11.
104
Chapter 6
Y-CHROMOSOME STR HAPLOTYPES CAN BE USED TO
DIFFERENTIATE LINEAGES IN THE UNITED ARAB EMIRATES
POPULATION
The following chapter has been submitted and presented in the format for the
journal Annals of Human Biology. The study was developed to address a gap in
the knowledge related to genetic diversity of populations of the Middle East. Y-
STR markers were analysed for this purpose. The research questions were
developed by the candidate in collaboration with her supervisors. She also
provided technical assistance in the laboratory, collating the results and
preparation of the multiple drafts of the manuscript.
105
Annals of Human Biology (submitted)
Y-Chromosome STR haplotypes can be used to differentiate lineages in the
United Arab Emirates population
Rebecca J Jones1, Guan K Tay1,2,3, Aurélie Mawart4 and Habiba Alsafar 4,5.
1 School of Anatomy, Physiology and Human Biology, University of Western
Australia, Crawley, Western Australia.
2 School of Psychiatry and Clinical Neurosciences, University of Western Australia,
Crawley, Western Australia.
3 School of Medical and Health Sciences, Edith Cowan University, Joondalup,
Western Australia.
4 Center for Biotechnology, Khalifa University of Science, Technology and
Research, Abu Dhabi, United Arab Emirates.
5 Faculty of Biomedical Engineering, Khalifa University of Science, Technology and
Research, Abu Dhabi, United Arab Emirates.
106
6.1 Introduction
The Y-chromosome haplotype is commonly constructed using Short Tandem Repeat
(STR) markers. As the Y-chromosome is subject to rapid genetic drift, haplotypes can
be used to study the geographical distribution of ethnic groups (1). The Y-
chromosome contains the largest non-recombining section within the human genome,
providing informative haplotypes for genetic analyses of populations (2). The
investigation into how the male lineage contributes to migration and population
distribution requires an understanding of the global distribution of these haplotypes.
Worldwide population data on the Y-chromosome indicate that these haplotypes are
region-specific, providing applications in genetic studies, human identification,
forensic investigation and paternity testing (3).
This study describes the first published information for the expanded 27 Y-
chromosome STR (Y-STR) panel for an Arab population within the United Arab
Emirates (UAE), designed to explore the impact of increasing the number of Y-STR
loci on population genetic analyses. The population studied comprised nationals of
the UAE, a country located on the South Eastern tip of the Arabian Peninsula,
comprising seven Emirates or principalities. The geographical location of the Arabian
Peninsula; at the crossroads of the African, Asian and European continents; means that
populations of this region have been shaped by the initial human migration out of
Africa and subsequently by the bidirectional flow of people between the three
continents. Factors that influence migration, such as conflict, availability of food and
water, trade, and the pursuit of knowledge have contributed to the bidirectional
migration patterns across this part of the world (4, 5). The Middle East region in the
western reaches of Asia, including the Arabian Peninsula, is central to two proposed
routes out of Africa with the southern part of the peninsula around what now includes
107
the UAE being a staging point on passage across the Red Sea, through this region and
onwards through Asia (6). Human dispersal through the Middle East has resulted in
the region containing numerous ethnic groups. The ethnic diversity has arisen from
the variety of social and cultural influences throughout the Middle East (7). Studying
the genomic distribution of genetic markers, such as Y-chromosome haplotypes, will
result in an understanding of the influence of human migration, which has given rise
to different ethnic groups (eg. the Bedouin) as well as different nationalities (Egyptian,
Jordanian, Yemenite, etc.) in the region.
The residents of the UAE are predominantly immigrants. The UAE comprise a
mixture of local (national) and expatriates, with the 2015 census estimating that 11.3%
national of the approximate 9.6 million residents throughout the country. The national
population of the UAE consists predominately of people of Arab descent. A recent
genetic study using Y-STR haplotypes in 2015 showed that UAE nationals are
genetically similar with populations in close geographical proximity, such as Kuwait
(8). Others have also confirmed the relationship between genetic relatedness and
geographic proximity through phylogenetic analyses of populations from the UAE,
Oman, Qatar and Yemen (9, 10). Additionally, significant genetic relationships
between the populations of the UAE with some in North Africa and South Asia have
been observed (9-11), highlighting the importance of understanding the impact of
bidirectional migration in this region of the world.
In contrast to genetic relationships observed through chromosomal analyses between
populations of the Middle East and surrounding regions, Y-STR analyses have shown
that genetic diversity is more complicated than expected (4, 5, 7, 9, 11). The genetic
structure of the Middle East and surrounding regions has been described as a mosaic
pattern due to the fluctuating degree of genetic diversity (11). The term “mosaic
108
pattern” describes a flow of genetic diversity throughout the Middle East that is not
accountable by factors such as geographical distance alone. Throughout the region,
the degree of genetic diversity has been found to be highly variable between both
populations residing in close proximity and those at distant locations. These complex
relationships highlight the need to continue to characterise the genetic make-up of
people of the Middle East region as well as those from the surrounding regions such
as Northern Africa and Southern Asia.
Y-STR analyses have been successfully used to develop an understanding of human
migration patterns and how movement has influenced the gene pool of specific
populations (6). Studies of this uni-parental transfer of genetic material have provided
insights into human movement patterns within Eurasian lineages (8). Although
previous Y-STR studies have provided information on individuals of Arabian descent
from multiple regions of the peninsula – Saudi Arabia, Yemen (10), Oman (9, 10) and
the UAE (10, 12), this present study focuses exclusively on UAE nationals. This study
also uses an additional 10 STR markers for haplotype construction, increasing the
number of markers to 27 as compared to the 17 Y-STR markers used in previous
efforts.
6.2 Materials and Methods
6.2.1 Study Population
The DNA samples of 217 consented healthy unrelated males from the UAE were used
in this study. These samples were available as de-identified DNA samples stored for
research purposes within the Emirates Family Registry (EFR), a biobank resource
available for genetic association studies (13). Prior to commencement of this present
109
study, approval to undertake the work was obtained from the Ethics committee of the
Ministry of Health of the UAE (2011) and the Human Research Ethics Committee of
the University of Western Australia (RA/4/1/7778).
6.2.2 Genotyping
Extraction of DNA was performed using the Oragene-DNA kit (Genotek, Ottawa,
Canada) in accordance with manufacturer’s guidelines using buccal cells from saliva.
A NanoDrop Spectrophotometer (Thermo Scientific, Wilmington DE, USA) was used
to determine the quality and quantity of the individual DNA samples. The 27 Y-STR
used in this study were amplified using half reactions (7.5µl) with the Y-Filer PLUS
Amplification kit (Life Technologies, Foster City CA, USA). The amplification was
performed on a Veriti Thermal Cycler (Life Technologies, Foster City CA, USA). The
27 Y-STR loci were DYS576, DYS389I, DYS635, DYS389II, DYS627, DYS460,
DYS458, DYS19, YGATA H4, DYS448, DYS391, DYS456, DYS390, DYS438,
DYS392, DYS518, DYS570, DYS437, DYS385a/ DYS385b, DYS449, DYS393,
DYS439, DYS481, DYF387SI/DYF387S1II and DYS533. Size determination of the
alleles of each Y-STR locus was carried-out by capillary electrophoresis using the
Applied Biosystems Genetic Analyzer 3500 (Life Technologies, Foster City CA,
USA) with the POP-4 polymer and using the 600LIZ Internal Lane Standard. The
computer software GeneMapper ID-X v1.2 (Life Technologies, Foster City CA, USA)
was used for fragment analysis for allele sizing.
Allelic designations were determined by comparing the size of PCR products
separated by capillary gel electrophoresis with the reference allelic ladders provided
with the Y-Filer PLUS Amplification kit (Life Technologies, Foster City CA, USA).
The alleles from all loci reported here were designated according to the published
nomenclatures and the guidelines of the International Society for Forensic Genetics
110
(ISFG) for performing STR analyses (14). Positive controls (provided in the Y-Filer
PLUS kit) and negative controls (deionized water) were used with each batch of
reactions. Additionally, a specific set of samples (approximately 10% of total
samples) were selected for replication and showed the assay was reproducible.
6.2.3 Statistical Analysis
The frequencies of the Y-STR haplotypes were determined by counting. Diversity in
the population studied was determined using Nei’s Formula (15) with the match
probability being 1 minus the haplotype diversity. The discriminatory capacity was
the number of unique (individual-specific) haplotypes divided by the total number of
individuals in the population (16).
Populations from the Y-chromosome Haplotype Reference Database (YHRD) were
chosen and compared to this study (referred to as the “present study”)
(www.yhrd.org). The YHRD database provides high-resolution and large reference
sample collections of world populations for genetic analyses (17). RST values were
calculated by Analysis of Molecular Variance (AMOVA) using information on
comparative populations from the YHRD database (10,000 permutations) and
Multidimensional Scaling (MDS) plots were constructed based on Kruskal’s non-
metric MDS algorithm (18) using the YHRD online program (www.yhrd.org).
6.3 Results and Discussion
A total of 217 individual samples from the UAE were analysed in this present study.
The total number of haplotypes identified in this study was 212. The unique number
of haplotypes, where there was only one individual observed with the haplotype, was
207 (see Table 6.1 and Appendix 4). The haplotype diversity was 0.9998 with a match
111
probability of 0.0002. The discriminatory capacity was 95.4% (Table 6.1).
Replication studies for quality control purposes showed that there was complete
concordance between two sets of data from the same individual.
At the time of this study, there were 15 populations in YHRD with data generated
using the commercial Y-Filer PLUS kit that comprises 27 Y-STRs. The haplotype
data generated in this present study was compared to the haplotype distribution from
these 15 populations. The resultant MDS plot (Figure 6.1) shows the relationship
between the Arabian population of this present study with populations from Lebanon,
Poland, Hungary, Germany, Denmark, Austria, Switzerland, Spain, Italy, the United
States of America, Greenland, China, Somalia, Peru and the Russian Federation. The
UAE population studied in this present study clustered with populations of Europe in
the MDS plot generated (see Figure 6.1). The relatively tight clustering of the
populations of Germany, Austria, Switzerland and Denmark is reassuring, and
presumably reflects the close geographical proximity of the four countries. These
central European countries share some common elements. Germany shares common
borders with the other three and German is an official language of three of the four
nations and a minor language in Denmark, reflecting elements of a common ancestral
and cultural origin.
A Lebanese population of unknown description in the YHRD database was found to
be distant from all other populations including that of the present study (AMOVA RST
= 0.1951). Although Arabic is the national language with just over half the population
of the Muslim faith, the culture of Lebanon reflects the range of different ethnic and
religious groups that have arisen through numerous civilizations that have resided in
this region throughout the centuries (19).
112
Figure 6.1: MDS plot comparing the Y-chromosome haplotypes of 15
populations constructed with 27 Y-STRs in the YHRD database with haplotypes
in Arabs from the UAE population typed in this present study.
The populations from the Far East (China), South America (Peru), Africa (Somalia)
and the Russian Federation were separate from the European cluster, relative to the
Arabian population of this study. Previously, a close relationship between the Arabs
and Europeans (20) has been suggested, which is supported in this study.
To allow a comparison with similar populations from the region, the number of Y-
STR loci analysed was reduced to 17 loci (DYS389I, DYS635, DYS389II, DYS458,
DYS19, YGATA H4, DYS448, DYS391, DYS456, DYS390, DYS438, DYS392,
DYS437, DYS385a/b, DYS393, DYS439). This combination is used in the Y-Filer
Lebanon
Peru
US (European)
0.2
MDS Plot
Dimension 1
Stress = 0.03487
0.1
0
.0
-0.1
-0
.2
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3
Dim
ensi
on
2
Poland
Hungary Germany Denmark
Austria Switzerland Spain
Present study
China
Greenland Somalia
Russian Federation
Italy
113
Amplification kit. Y-STR haplotypes from population studies in countries from the
Middle East and North Africa (MENA) region and South Asian countries (India,
Pakistan and Bangladesh) were extracted from the YHRD for comparison.
Additionally, a distant population (Peru) from the original analysis shown in Figure
6.1 was used to provide context.
The resultant MDS plot in Figure 6.2 shows that the present UAE population studied
clusters with other countries of the Arabian Peninsula. The AMOVA RST between
this present study and the Arabian Peninsula countries were 0.0097 (UAE), 0.0059
(Kuwait) and 0.0241 (Yemen). Additionally, the Levant population from Iraq was
found to closely cluster with the present UAE study (RST = 0.0321).
The closer genetic relationship with the Lebanese population observed in this
comparison (Figure 6.2) appears to be a discrepancy when contrasted to the distance
matrix shown in Figure 6.1, suggesting that the additional 10 Y-STR loci provides
greater discrimination and are separating these lineage haplotypes in the two
populations. The distance between the Lebanese population and the present study
using 27 STR loci was AMOVA RST = 0.1951 compared to AMOVA RST = 0.0111 in
the latter. This could be due to the Lebanese population within the YHRD database
for the 27 Y-STR loci including numerous ethnic backgrounds increasing the
uniqueness of the country, distancing further from the UAE. Within the literature,
Lebanon has been described as being influenced by numerous ethnic backgrounds
impacting the genetic diversity (21). For this matter to be understood, an increase of
Middle Eastern populations using 27 Y-STR loci should be undertaken to analyse the
relationship of the UAE and Lebanon in a suitable context.
114
To address the suggestion of improved discrimination with increased loci analysed, a
comparison was undertaken of the Y-Chromosome haplotypes of the 217 samples
from the present UAE study constructed using 27 Y-STR loci and 17 Y-STR loci (see
Table 6.1). The number of unique Y-Chromosome haplotypes using the 27 Y-STR
loci was 207, which was 26 more than the number of unique haplotypes constructed
using 17 Y-STR loci. The Haplotype Diversity increased and the Match Probability
decreased when more Y-STR loci were used to construct the haplotypes. Furthermore,
Figure 6.2: MDS plot comparing the Y-chromosome haplotypes (using 17 Y-
STR loci) of the UAE population described in this study with populations from
North Africa ( ), Arabian Peninsula ( ), the Levant region ( ) and South Asia
( ). Data from Peru was also available ( ).
0.0
5
0.0
0
-0.0
5
-0.1
0
-0.1
5
-0.10 -0.05 0.00 0.05 0.10 0.15 0.20
MDS Plot
Dim
ensi
on
2
Dimension 1
Stress = 0.03701
Lebanon Iraq Iran
India Bangladesh
United Arab Emirates
Kuwait Present Study
Egypt Yemen
Pakistan
Jordan
Libya Algeria Morocco
Tunisia
Peru
115
the discrimination capacity increased by over 10% when the 27 Y-STR loci were
analysed. Other studies (22-24) have also shown improvements in haplotype
discrimination with the use of 27 Y-STR loci. These results show that the 27 Y-STR
loci provide greater discrimination and a lesser chance of incorrectly matching two
unique haplotypes than for lower numbers of STR loci.
The other unexpected result highlighted in Figure 6.2 was the distance of the Jordanian
population, a country in the Levant, from the Middle East group (AMOVA RST =
0.2763). Jordan is located close to Lebanon and shares a common border with Iraq,
yet the population does not cluster with the populations of these two neighbouring
countries based on the Y-STR assigned haplotype data.
Upon further interrogation, the Jordanian population in YHRD was found to be from
two separate subpopulations, Arab Adnanit and Arab Qahtanit. According to
historical scriptures, the two groups of Arabs, the Qahtanite and the Adnanite are
distinct populations, with the former referring to Arabs who originated from the
Southern region of the Arabian Peninsula around Yemen. The Qahtanit group
comprises the family of Qahtan and his 24 sons, who inhabited the southern parts of
the Arabian Peninsula. Between the 7th and 14th centuries, the expansion of the Arabic
empire extended into most of Spain, southern France and western China. During this
expansion period, Arabic populations including the Qahtanit tribes spread and
intermingled through these lands (25). Adnanites are Arabized Arabs (meaning those
who travelled into Arabia before the Mesopotamia period) descended from Adnan, the
father of the Ishmaelite Arabs who occupied Hijaz, Yamama regions as well as most
parts of northern Arabia (26).
116
Table 6.1. The improvement in discrimination capacity following an increase in reportable Y-STRs from 17 (Y-Filer) to 27 loci
(Y-Filer PLUS).
Present study Austria (22) Italy (23) Spain (24)
Y-Filer Y-Filer
PLUS Y-Filer
Y-Filer
PLUS Y-Filer
Y-Filer
PLUS Y-Filer
Y-Filer
PLUS
Population Size 217 217 425 425 203 203 203 203
Unique Haplotype Count 181 207 407 423 191 197 171 203
Haplotype Diversity 0.9989 0.9998 0.9999 0.999989 0.9997 0.9999 0.9972 0.9999
Haplotype Match Probability 0.0011 0.0002 0.0024 0.0025 0.0052 0.0051 0.0028 0.000004
Discrimination Capacity 83.40% 95.40% 97.88% 99.77% 97.04% 98.52% 84.24% 99.99%
117
Distance relationships were recalculated using the Jordanian groups as two distinct
populations and the MDS plot redrawn (see Figure 6.3). It shows the Arab Adnanit
group of Jordan clustering with the Middle East group and in close proximity to the
present UAE study (AMOVA RST = 0.0717) with the Arab Qahtanit group remaining
some distance away (RST = 0.4425). Previous studies have also suggested the great
diversity between different ethnic populations within Jordan, indicative of the distance
between the Qahtanit and Adnanit groups in Figure 6.3 (27). The distance of the
Jordan-Qahtanit population in Figure 6.3 is consistent with different waves of people
migrating to lands outside of the Arabian Peninsula towards the north-east, during the
expansionism period. Additionally, due to the Peninsula’s “wide array of variables
impacting the movement of human groups” (7) such as climate changes and trade that
are likely impacting the genetic diversity. However, further studies with
classifications of individuals into the Adnanit and Qahtanit groups would be required
to understand the relationship between the two subpopulations.
Since the populations in North Africa used in this analysis are potentially a mixture of
Arabian and African populations, 17 Y-STR haplotype data on Arabian populations
including a linguistic Arabic group within Iran (28), were extracted from YHRD.
These were compared with the 17 Y-STR haplotypes of this present UAE study to
establish the relationship between the Arabian populations (Figure 6.4). The North
African defined Arabian populations (Algeria, Morocco and Libya) are seen to cluster
together within the MDS plot, a not surprising observation due to their close
geographic proximity and relative distance away from the peninsula.
118
MDS Plot
0.0
5
0.0
0
-0.0
5
-0.1
0
-0.1
5
-0.1 0.0 0.1 0.2 0.3
Dimension 1
Stress = 0.04885
Dim
ensi
on
2
Present Study Jordan [Adnanit]
United Arab Emirates Egypt
Yemen
Kuwait Lebanon
Bangladesh India
Iran Iraq
Pakistan
Jordan [Qahtanit]
Peru
Libya Morocco
Algeria
Tunisia
Figure 6.3: MDS plot comparing the Y-STR haplotypes (using 17 Y-STR loci)
of population from North Africa ( ), Arabian Peninsula ( ), the Levant
region ( ) and South Asia ( ), with the Jordanian population separated into
two genealogical groups. Data from Peru was also available ( ).
119
The populations of Iraq, Kuwait, UAE, Jordan Adnanit, an Iranian Linguistic Arabic
group (Khuzestani Arabic) from Ahvaz, Iran and the present study form a second
cluster in Figure 6.4. Quite distinct from the North African defined Arabian
populations and the Middle Eastern cluster is the Yemen population. The distance of
Yemen to the North African populations coincides with the two separate migratory
routes into the Middle East out of Africa, one across the land bridge that is now Egypt
0.1
0
0.0
5
0.0
0
-0.0
5
-0.1
0
-0.1
5
-0.1 0.0 0.1 0.2 0.3 0.4
MDS Plot
Dim
ensi
on
2
Dimension 1
Stress = 0.04405
Jordan [Arab-Qahtanit]
Jordan [Arab-Adnanit] Present Study Abu Dhabi, UAE [Arab]
Kuwait City, Kuwait [Arab] Ahvaz, Iran [Arab]
Iraq [Iraqi]
Sanaa, Yemen [Yemeni]
Peru
Banghazi, Libya [Arab]
Rabat, Morocco [Arabs]
Casablanca, Morocco [Arab]
Oran, Algeria [Arab]
Figure 6.4: MDS plot of present study and defined Arab populations from
YHRD using 17 Y-STR loci. Countries differentiated according to region using
the following symbols: North Africa ( ), Arabian Peninsula ( ), the Levant
region ( ) and South Asia ( ). Data from Peru was also available ( ).
120
and the second across the Red Sea (6, 7, 29, 30). The Jordan Qahtanit population still
remained significantly distant from the Middle Eastern cluster.
In the analyses shown in Figures 6.2-6.4; the location of the present study within the
MDS plot is consistently close to that of a UAE population studied previously (12)
with AMOVA values of R ST=0.0097; 0.0097; 0.0003. Additionally, the present study
can be seen to closely cluster with the Kuwaiti populations within Figures 6.2-6.4
(AMOVA RST = 0.0059; 0.0059; 0.0067). This relationship is indicative of the
historically regular interaction between the Arabian coastal populations such as during
the ancient civilisation of Dilmun (centred in Bahrain) from around 4000 to 2000 BCE.
Furthermore, the Phoenician ancestors were believed to have developed the maritime
skills within the gulf, linking all the coastal countries known today (31).
Both Figure 6.2 and Figure 6.3 show clustering of North African populations, which
is consistent with close links in this region. However, the Egyptian population appears
to be a part of the clustering of the Middle Eastern populations, which include that of
the present study (AMOVA RST = 0.0191) and further from the Arab populations in
North Africa. Additionally, the North African defined Arabian populations in Figure
6.4, clustered close to the Middle Eastern grouping, which included the present study.
Furthermore, Figures 6.2 and 6.3 show Southern Asia populations (Iran, India and
Bangladesh) cluster in closer proximity than to the present study and Middle Eastern
populations. These relationships appear to coincide with migratory factors and the
geographical closeness of the UAE to Southern Asian countries such as Iran (AMOVA
RST = 0.0308), India (RST = 0.0413) and Bangladesh (RST = 0.0497). Trade between
these regions have been documented for centuries.
The fact that the North African populations cluster opposite to those from Southern
Asian countries, with Middle Eastern populations in the middle (Figure 6.2), suggests
121
that migratory routes and trade factors flowed back and forth from the east to west and
through the Middle East region, including the UAE. This region is at the crossroads
through which humans dispersed and migrated between the continents of Africa and
Asia. Additionally, the fact that Egypt clusters with the Middle Eastern populations
studied in comparison to the other North African populations supports the idea that
migration between Africa and the Middle East flowed through the land bridge that is
Egypt (7, 21).
6.4 Conclusion
This present study has shown the UAE population to be diverse with 207 unique
haplotypes observed in 217 individuals. The present UAE study has commonalties
with other Middle Eastern populations, and appears to be particularly close to the
Kuwaiti populations.
The genetic distance between Jordan and the UAE population can be explained by the
geographical distance between the two countries, with further research required into
the significance of subpopulation genetic analyses.
The array of genetic relationships within the MDS plot structures support the Middle
East region reflecting a ‘mosaic pattern’ of genetic structure using Y-chromosome
analyses. In addition, the discrepancy of distance between the Lebanese populations
when 27 or 17 Y-STR loci are analysed supports the need for further research to
determine whether the relationship is due to the discrimination values of the number
of loci used. This present study has highlighted the importance of further research
required for populations within the region. Nevertheless, the diversity of the
haplotypes identified in the UAE population using 27 Y-STR loci provides an
122
effective tool for human identification, paternity testing and population genetic
studies.
123
6.5 References
1. Qamar R, Ayub Q, Mohyuddin A, Helgason A, Mazhar K, Mansoor A, et al.
Y-Chromosome DNA variation in Pakistan. Am J Hum Genet. 2002;70:1107-
24.
2. Underhill PA, Kivisild T. Use of y chromosome and mitochondrial DNA
population structure in tracing human migrations. Ann Rev Genet.
2007;41:539-64.
3. Immel UD, Kleiber M, Klintschar M. Y-chromosomal STR haplotypes in an
Arab population from Yemen. Int Congress Series. 2004;1261:340-3.
4. Valeri M. Nation-building and communities in Oman since 1970: The Swahili-
Speaking Omani in search of identity. Oxford Journals 2007;106(424):479-96.
5. Abu-Amero KK, Gonzalez AM, Larruga JM, Bosley TM, Cabrera VM.
Eurasian and African mitochondrial DNA influences in the Saudi Arabian
population. BMC Evol Biol. 2007;7(32):1-15.
6. Kundu S, Ghosh SK. Trend of different molecular markers in the last decades
for studying human migrations. Gene. 2015;556(2):81-90.
7. Petraglia MD, Rose JI. The evolution of human populations in Arabia:
Paleoenvironments, prehistory and genetics. Netherlands: Springer 2009.
8. Triki-Fendri S, Sanchez-Diz P, Rey-Gonzalez D, Ayadi I, Carracedo A, Rebai
A. Paternal lineages in Libya inferred from Y-chromosome haplogroups. Am
J Phys Anthropol. 2015;157(2):242-51.
9. Cadenas AM, Zhivotovsky LA, Cavalli-Sforza LL, Underhill PA, Herrera RJ.
Y-chromosome diversity characterizes the Gulf of Oman. Euro J Hum Genet.
2008;16(3):374-86.
124
10. Alshamali F, Pereira L, Iacute SA, Budowle B, Poloni ES, et al. Local
population structure in Arabian Peninsula revealed by Y-STR diversity. Hum
Hered. 2009;68(1):45-54.
11. Petraglia MD, Haslam M, Fuller DQ, Boivin N, Clarkson C. Out of Africa:
New hypotheses and evidence for the dispersal of Homo sapiens along the
Indian Ocean rim. Ann Human Biol. 2010;37(3):288-311.
12. Nazir M, Alhaddad H, Alenizi M, Alenizi H, Taqi Z, Sanqoor S, et al. A
genetic overview of 23 Y-STR markers in UAE population. Forensic Sci Int
Genet. 2016;23:150-2.
13. Alsafar H, Jama-Alol KA, Hassoun AAK, Tay GK. The prevalence of Type 2
Diabetes Mellitus in the United Arab Emirates: Justification for the
establishment of the Emirates Family Registry. Int J Diabetes Dev Ctries.
2012;32(1):25-32.
14. Schneider PM. Scientific standards for studies in forensic genetics. Forensic
Sci Int. 2007;165(2-3):238-43.
15. Nei M. Molecular Evolutionary Genetics New York, USA: Columbia
University Press 1987.
16. Chang YM, Swaran Y, Phoon YK, Sothirasan K, Sim HT, Lim KB, et al.
Haplotype diversity of 17 Y-chromosomal STRs in three native Sarawak
populations (Iban, Bidayuh and Melanau) in East Malaysia. Forensic Sci Int
Genet. 2009;3(3):e77-80.
17. Willuweit S, Roewer L. The new Y chromosome haplotype reference database.
Forensic Sci Int Genet. 2015;15:43-8.
18. Kruskal JB. Nonmetric Multidimensional Scaling: A numerical method.
Psychometrika. 1964;29(2):115-29.
125
19. Chouery E, Coble MD, Strouss KM, Saunier JL, Jalkh N, Medlej-Hashim M,
et al. Population genetic data for 17 STR markers from Lebanon. Leg Med.
2010;12(6):324-6.
20. Garcia-Bertrand R, Simms TM, Cadenas AM, Herrera RJ. United Arab
Emirates: phylogenetic relationships and ancestral populations. Gene.
2014;533(1):411-9.
21. El Andari A, Othman H, Taroni F, Mansour I. Population genetic data for 23
STR markers from Lebanon. Forensic Sci Int Genet. 2013;7(4):e108-13.
22. Pickrahn I, Muller E, Zahrer W, Dunkelmann B, Cemper-Kiesslich J, Kreindl
G, et al. Yfiler(R) Plus amplification kit validation and calculation of forensic
parameters for two Austrian populations. Forensic Sci Int Genet. 2016;21:90-
4.
23. Rapone C, D'Atanasio E, Agostino A, Mariano M, Papaluca MT, Cruciani F,
et al. Forensic genetic value of a 27 Y-STR loci multiplex (Yfiler((R)) Plus
kit) in an Italian population sample. Forensic Sci Int Genet. 2016;21:e1-5.
24. Garcia O, Yurrebaso I, Mancisidor ID, Lopez S, Alonso S, Gusmao L. Data
for 27 Y-chromosome STR loci in the Basque Country autochthonous
population. Forensic Sci Int Genet. 2016;20:e10-2.
25. Ram P. Yemen History and Culture: A Book by AnVi OpenSource Knowledge
Trust: GBO 2015.
26. Thesiger W. Desert borderlands of Oman. Geograph J. 1950;116 (4/6):137-68.
27. Gonzalez AM, Karadsheh N, Maca-Meyer N, Flores C, Cabrera VM, Larruga
JM. Mitochondrial DNA variation in Jordanians and their genetic relationship
to other Middle East populations. Ann Hum Biol. 2008;35(2):212-31.
126
28. Roewer L, Willuweit S, Stoneking M, Nasidze I. A Y-STR database of Iranian
and Azerbaijanian minority populations. Forensic Sci Int Genet.
2009;4(1):e53-5.
29. Tadmouri GO, Sastry KS, Chouchane L. Arab gene geography: From
population diversities to personalized medical genomics. Glob Cardiol Sci
Pract. 2014;2014(4):394-408.
30. Shepard EM, Herrera RJ. Genetic encapsulation among near Eastern
populations. J Hum Genet. 2006;51(5):467-76.
31. Anthony JD, Hearty JA. Eastern Arabian States: Kuwait, Bahrain, Qatar, the
United Arab Emirates, and Oman: The Government and Politics of the Middle
East and North Africa. Colorado: Westview Press 1980.
32. Manni F, Leonardi P, Barakat A, Rouba H, Heyer E, Klintschar M, et al. Y-
chromosome analysis in Egypt suggests a genetic regional continuity in
Northeastern Africa. Hum Biol. 2002;74(5):645-58.
127
Chapter 7
GENERAL DISCUSSION AND CONCLUSION
128
7.1 Discussion
Due to the paucity of literature on genetic analyses of Middle Eastern populations such
as the United Arab Emirates (UAE) (1, 2), this project was designed with the objective
to add to the knowledge base of human genetic diversity within the Middle East.
Contributions towards the literature were carried-out by increasing sample sizes and
number of short tandem repeat (STR) loci tested to show improved measures of
genetic diversity within the UAE and greater resolution of the genetic relationships
between populations in the Middle East and surrounding regions. The outcomes from
this project provide an increased understanding of the factors that impact genetic
diversity in the Middle East such as human dispersal following the initial migration
out of Africa, geographic location, historic, trade relationships, socio-cultural
influences and overall increases in population size from large- scale urbanization.
Although the recent introduction of next generation sequencing allows the comparison
of whole genomes, the vast amount of population-based genetic data still focuses on
autosomal and Y-chromosome STRs (Y-STRs). Furthermore, the minimal research
on the Middle East region, and particularly the UAE given its geographical location
at the crossroads of human dispersal from Africa, means that using STR analyses is
still an important research tool. The data from the variable STR loci provide for
population databases with high analytical power and allelic abundance.
The aim of characterizing allele frequencies and statistical forensic parameters for the
UAE population was carried-out with the use of both autosomal STRs and Y-STRs.
In regards to the autosomal STR analyses, the initial publication of UAE population
data allowed for the establishment of research quality assessments within the literature
(3). The same amplification kit and manufacturer’s instructions were utilised for both
data sets improving the quality of the results and providing reassurance in the
129
reduction of biases and potential errors. Furthermore, the statistical analyses of the
two datasets was important to understand the extent of significant differences between
the two UAE subpopulations, which reflected minimal and nonsignificant variation
allowing for the combination of the two datasets for further analyses. The minimal
variation observed between the Emirati Bedouins (Chapter Three) and Emirati Arabs
of mixed ethnic origin (Chapter Four) is supported in the literature. Even though the
Arabian Peninsula and the UAE comprises remote Bedouin communities (4),
agricultural settlements during the 1920s within the UAE saw some Bedouin join the
socio-economic progresses of the region reducing the isolation between the various
Emirati nationals (4). It is important to analyse subpopulations to understand the
degree of relationships and impact of historical socio-cultural factors as seen within
the UAE from the 1920s agricultural settlements. Overall, the consolidation of the two
datasets highlighted the high degree of genetic heterozygosity in the various ethnic
groups making up the UAE nationals as supported in the literature (5) and improved
the meta-analysis of the genetic relationships between the UAE populations and
surrounding Middle East, North African and South Asian populations. Furthermore,
increasing the number of autosomal STR loci in the meta-analysis to 13-15 STR loci
(from six STR loci) better delineated the genetic relationships in the region.
The Y-STR analyses provided knowledge towards the genetic diversity of the UAE
male lineages. The genetic diversity and high heterozygosity within the UAE
population were confirmed through the use of the Y-chromosome Haplotype
Reference Database (YHRD), providing online access for haplotype interpretations
(6). Similar to the autosomal STR analyses, Y- STR analyses highlighted the
importance of increased number of loci for haplogroup characterisation. For example,
increasing the number of Y-STR loci compared between the UAE and Lebanon better
130
reflected the genetic distance between the Lebanese and the UAE populations as
supported by the autosomal STR meta-analysis. Furthermore, the literature highlights
the effectiveness of the increased number of STR loci in improving genetic analyses
(7, 8, 9). As Lebanon was the only Middle Eastern population that could be used for
the 27 Y-STR loci comparison as opposed to the 17 Y-STR loci comparison, further
Middle Eastern populations require genetic analyses using 27 Y-STR loci to identify
any potential discrepancies and/or better delineate the genetic relationship.
An introductory meta-analysis was undertaken in Chapter Three with the first UAE
population autosomal STR dataset, highlighting the significance of involving the UAE
in comparative analyses. Inconsistencies were observed between the introductory
meta-analysis and the main meta-analysis using autosomal STR analyses (Chapter
Five). The Saudi and Egyptian population data sets compared in the introductory meta-
analysis showed less significant differences compared to the UAE population.
However, greater significant differences were seen between these two populations in
the main meta-analysis. This can be explained due to the collection of two separate
data sets of Egyptian and Saudi populations used for the two different meta-analyses.
The introductory meta-analysis used data from a Saudi and Egyptian population,
which were residing within Kuwait (10). Whilst the major meta-analysis used data
from a Saudi population residing within the central region of Saudi Arabia (11) and
an Egyptian population with individuals residing within Egypt for at least three
generations (12). The contrast of significant relationships towards the UAE
population highlights the importance of population and location specific data
collections for a better understanding of genetic diversity. Furthermore, this situation
highlights how the use of autosomal STRs can identify the impact on genetic diversity
of potential admixture and isolation, as shown by the example of the Saudi and
131
Egyptian populations residing in Kuwait. Phylogenetic analysis should occur in many
research areas providing valuable insights. However, the process of obtaining the
appropriate phylogenetic perspective can be difficult as the chosen method of
phylogenetic analysis does not provide trees of equal quality and takes an invested
amount of time (13). Future research into using phylogenetic analysis towards the
UAE population should be considered with stress into rigorous analysis of the data.
The significance of population and subpopulation specific genetic analyses was also
highlighted through the Y-chromosome analysis using YHRD. The discrepancies
noted between the two separate Jordanian populations (Adnanit and Qahtanit)
highlight the importance of initially testing the relationship between subpopulations
before combining data to be used for comparisons such as the process accomplished
during the autosomal STR analysis (Chapter 4). Analysis of the relationship between
Jordan and the UAE population using autosomal STRs also highlighted how
populations within Jordan can be seen to show genetic distance from Middle East
populations and minimal heterozygosity values due to the impact of isolation even
though Jordan is the “major transit zone” (14). Once the two subpopulations of Jordan
were separated within YHRD, a better understanding of the relationship of Jordanians
towards the UAE population was provided. The importance of comparing
subpopulations is supported within the literature (5, 7, 14-17). The fact that
subpopulations have been observed to show genetic distance and diversity within close
proximity supports the description of the Middle East portraying a “mosaic pattern”
of genetic relationships impacted by the particular subpopulations analysed (18).
Similar genetic relationships were observed using the two different STR analyses
(autosomal and Y-chromosomal). Close genetic relationships between the UAE and
South Asian populations such as Iran were seen in both autosomal and Y-
132
chromosomal STR analyses. This highlights how both autosomal and Y-chromosome
STR analyses provide supporting information towards human dispersal from the
Arabian Peninsula through South Asia impacting on genetic diversity via trade, history
and socio-cultural relationships (18). Additionally, significant genetic distance
between North African populations such as Morocco and the UAE were highlighted
through both autosomal and Y-chromosome STR analysis. Within the literature,
shared ancestry has been described between the Arab populations in Morocco and the
Arab populations in the Middle East (18, 19). However, significant genetic distance
between Morocco and the Middle East has been observed in these analyses. This is
not surprising due to genetic influences from Spain and African populations in close-
geographical distance with Morocco and the larger contribution of Berber genes to the
Moroccan gene pool, impacting the genetic diversity from the original shared ancestry
(19).
Different genetic relationships between the UAE population and others can be
observed when using autosomal and Y-chromosome STRs. Differences between the
UAE populations and Kuwait as well as Egypt were seen when 15 autosomal STRs
were compared. However, Y-STR analysis showed close clustering between the UAE
and these two populations. In the literature, Y-STR analyses have shown genetic
relationships between the UAE and Kuwait (20). This close genetic relationship
between the UAE and Kuwait can be explained by the shared historical relationships
between countries of the east coast of the Arabian Peninsula and the maritime trade
between the countries bordering the Arabian Gulf (21). In contrast, the genetic
distance observed using autosomal markers between Kuwait and the UAE may be
explainable by the geographic location of Kuwait relative to the main migration routes
out of Africa. Kundu and Ghosh (2015) have suggested that there are differences in
133
human dispersal patterns passing through both the UAE and Kuwait (22). The
contributions of the maternal lineage could not be observed, since the study did not
consider mitochondrial DNA lineages. Furthermore, more detailed analyses of the
populations in Kuwait may be able to shed light on autosomal variations that are
inherited maternally. In the early 1900s, Kuwait comprised various cultures and
ethnicities due to extensive trade with Iran, Yemen, India and East Africa.
Furthermore, the attractive political and commercial environment with cultural
tolerance of Kuwait at this time, attracted travellers from mixed ethnic backgrounds
(e.g. Armenians, Baluchi and Jews) and an increase in immigrants continued after the
oil boom due to work opportunities (21). Marriage between different ethnic families
is uncommon in Kuwait, however there were exceptions. Kuwaiti nationals followed
traditional family values common in Arab cultures where a newlywed couple
(including intermarriages) would customarily reside at the husband’s geographical
location (21). This would impact the genetic diversity. Richards et al (2003)
commented on the presence of predominant female migration through the Middle East
using mitochondrial DNA analyses (23). Furthermore, the fact that women and men
did not necessarily accompany each other equally through dispersal (24, 25). However
it was common for women to move to the home of the husband after marriage (26).
The contribution of the maternal lineages would not be observed through Y-
chromosome analyses, explaining the variable results towards autosomal STR
analysis. At present, there is a lack of mitochondrial DNA studies involving UAE
populations within the literature (26). Furthermore, the practice of polygyny
throughout the Middle East, North Africa and South Asia populations would impact
the Y-chromosome gene pool more than observed through autosomal STR analysis
(27, 28). The difference in the genetic relationship observed when comparing Egypt
134
to the UAE supports two main migration routes out of Africa. Dispersal through Egypt
and the UAE were part of the two separate dispersal routes, resulting in the genetic
differences observed in autosomal analysis. The same genetic relationships seen
through Y-chromosome analyses may be a result of factors based on trade and
employment, which would increase the dispersal of male lineages, looking for work
(1, 21, 26). The variable relationships between male and female lineages highlight the
importance of using different forms of genetic analyses on the same populations.
Through a combination of autosomal STR and lineage STR analyses, it is possible to
elucidate sociocultural impacts upon genetic diversity.
7.2 Conclusion
The overall analysis in the thesis of the UAE has contributed knowledge to
understanding the relationship between the population of the UAE and others. It
supports the relationship between human dispersal and its impact on genetic diversity.
Furthermore, the importance of comparing two subpopulations from the one country
(Emirati Bedouin and Emirati Arab of mixed ethnic origin) can be seen as it allows
the identification of potential discrepancies such as observed between the two
Jordanian populations in the Y-chromosome analyses. The thesis aims were carried-
out through the calculation of allele frequencies and the meta-analyses providing
insight into the diversity observed in the UAE, the Middle East and surrounding
regions. The thesis also highlights how using different types of STR analyses allow
for greater in-depth understanding of the history of populations and the impact on
genetic diversity of contemporary populations. The study of the UAE population has
further highlighted the relationship between human migration patterns and additional
impact factors of historical events and socio-cultural relationships towards genetic
135
diversity. The analysis of the UAE population has also highlighted the importance of
population specific databases throughout the Middle East. By extending this UAE
genetic analyses to include mitochondrial DNA will further expand this study to assess
the impact of female migration, identified from the discrepancies observed between
the autosomal and Y-chromosome STR analyses. Finally, the overall analysis of the
UAE populations emphasises the significance of increasing both sample sizes and
number of STR markers used for efficacy in forensic human identification, paternity
testing and disease susceptibility.
136
7.3 References
1. Petraglia MD, Rose JI. The evolution of human populations in Arabia:
Paleoenvironments, prehistory and genetics. Netherlands: Springer 2009.
2. Cadenas AM, Zhivotovsky LA, Cavalli-Sforza LL, Underhill PA, Herrera RJ.
Y-chromosome diversity characterizes the Gulf of Oman. Euro J Hum Genet.
2008;16(3):374-86.
3. Schneider PM. Scientific standards for studies in forensic genetics. Forensic
Sci Int. 2007;165(2-3):238-43.
4. Al-Semmari F. A history of the Arabian Peninsula. London: I.B. Tauris 2009.
5. Garcia-Bertrand R, Simms TM, Cadenas AM, Herrera RJ. United Arab
Emirates: phylogenetic relationships and ancestral populations. Gene.
2014;533(1):411-9.
6. Willuweit S, Roewer L. The new Y Chromosome Haplotype Reference
Database. Forensic Sci Int Genet. 2015;15:43-8.
7. Pickrahn I, Muller E, Zahrer W, Dunkelmann B, Cemper-Kiesslich J, Kreindl
G, et al. Yfiler(R) Plus amplification kit validation and calculation of forensic
parameters for two Austrian populations. Forensic Sci Int Genet. 2016;21:90-
4.
8. Rapone C, D'Atanasio E, Agostino A, Mariano M, Papaluca MT, Cruciani F,
et al. Forensic genetic value of a 27 Y-STR loci multiplex (Yfiler(R) Plus kit)
in an Italian population sample. Forensic Sci Int Genet. 2016;21:e1-5.
9. Garcia O, Yurrebaso I, Mancisidor ID, Lopez S, Alonso S, Gusmao L. Data
for 27 Y-chromosome STR loci in the Basque Country autochthonous
population. Forensic Sci Int Genet. 2016;20:e10-2.
137
10. Al-Enizi M, Ge J, Ismael S, Al-Enezi H, Al-Awadhi A, Al-Duaij W et al.
Population genetic analyses of 15 STR loci from seven forensically-relevant
populations residing in the state of Kuwait. Forensic Sci Int Genet.
2013;7(4):e106-7.
11. Osman AE, Alsafar H, Tay GK, Theyab J, Mubasher M, Sheikh N, et al.
Autosomal short tandem repeat (STR) variation based on 15 loci in a
population from the Central Region (Riyadh Province) of Saudi Arabia. J
Forensic Res. 2015;6(1):1-5.
12. Coudray C, Guitard E, el-Chennawi F, Larrouy G, Dugoujon JM. Allele
frequencies of 15 short tandem repeats (STRs) in three Egyptian populations
of different ethnic groups. Forensic Sci Int. 2007;169(2-3):260-5.
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APPENDICES
153
Appendix 1: Published manuscript in the form of a Letter to the Editor for
Forensic Science International: Genetics (Chapter 3).
154
155
Appendix 2: Manuscript in Press in the form of a Letter to the Editor for Forensic
Science International: Genetics (Chapter 4).
156
157
Appendix 3: Exact test (FST) between 15 loci of 20 populations compared to the present GlobalFiler UAE population study
(Chapter 5).
POPULATION/
LOCI LEBANON JORDAN SYRIA IRAQ KUWAIT
SAUDI
ARABIA QATAR UAE OMAN YEMEN
D3S1358 0.00015+-
0.0001
n/a 0.41405+-
0.0434
0.04510+-
0.0084 0.00000+-
0.0000
0.00020+-
0.0002
0.01755+-
0.053
0.89195+-
0.0225
0.38170+-
0.0363
0.80405+-
0.0255
VWA 0.00000+-
0.0000
0.00000+-
0.0000
0.03510+-
0.0189
0.08580+-
0.0149 0.00000+-
0.0000
0.01070+-
0.0095
0.33510+-
0.0712
0.83715+-
0.0297
0.24680+-
0.0469 0.00005+-
0.0001
D16S539 0.00000+-
0.0000
n/a 0.00330+-
0.0037
0.52110+-
0.0436 0.00000+-
0.0000
0.00280+-
0.0016
0.00000+-
0.0000
0.26055+-
0.0395
0.87985+-
0.0278
0.22065+-
0.0291
CSF1PO 0.00645+-
0.0031
0.00055+-
0.0002
0.34240+-
0.0492
0.71080+-
0.0522 0.00000+-
0.0000
0.00095+-
0.0007
0.40180+-
0.0368
0.60405+-
0.0319
0.17475+-
0.0302
0.30315+-
0.0504
TPOX 0.00225+-
0.0024
0.45285+-
0.0293
0.08390+-
0.0144
0.32490+-
0.0387 0.00125+-
0.0010
0.00005+-
0.0001
0.37420+-
0.0446
0.89205+-
0.0119
0.18705+-
0.0415
0.28760+-
0.0346
D21S11 0.00000+-
0.0000
n/a 0.00000+-
0.0000
0.58890+-
0.0428
0.05385+-
0.0151 0.00000+-
0.0000
0.07435+-
0.0244
0.81435+-
0.0249 0.02800+-
0.0123
0.15185+-
0.0476
D8S1179 0.00000+-
0.0000
n/a 0.07835+-
0.0186
0.63605+-
0.0239 0.00160+-
0.0016
0.05120+-
0.0310
0.25580+-
0.0566
0.96235+-
0.0073
0.61750+-
0.0518 0.03670+-
0.0119
D18S51 0.00105+-
0.0010
n/a 0.32245+-
0.0478
0.85870+-
0.0250 0.00195+-
0.0012
0.00000+-
0.0000
0.89375+-
0.0320
0.56330+-
0.0520
0.68685+-
0.0561
0.64090+-
0.0478
D19S433 0.00055+-
0.0006
n/a n/a 0.14285+-
0.0343 0.00055+-
0.0004
0.00025+-
0.0003
0.00000+-
0.0000
0.89345+-
0.0240
n/a n/a
TH01 0.05120+-
0.0254 0.00000+-
0.0000
0.08825+-
0.0379
0.85055+-
0.0282
0.86470+-
0.0423 0.00000+-
0.0000
0.38910+-
0.0460
0.75295+-
0.0318
0.05590+-
0.0091
0.40555+-
0.0551
FGA 0.00270+-
0.0012
n/a 0.04710+-
0.0256
0.83170+-
0.0371 0.00855+-
0.0062
0.00120+-
0.0012
0.02235+-
0.0071
0.05855+-
0.0146
0.68955+-
0.0338
0.45740+-
0.0664
D5S818 0.11850+-
0.0534
n/a 0.24125+-
0.0526
0.56710+-
0.0416 0.00010+-
0.0001
0.00775+-
0.0037
0.00000+-
0.0000
0.82240+-
0.0298
0.59420+-
0.0425
0.08425+-
0.0229
D13S317 0.00310+-
0.0034
0.00000+-
0.0000
0.01950+-
0.0145
0.00010+-
0.0000
0.00000+-
0.0000
0.00000+-
0.0000
0.0000+-
0.0000
0.01110+-
0.0069
0.05195+-
0.0084
0.15140+-
0.0219
D7S820 0.00020+-
0.0002
0.00000+-
0.0000
0.41285+-
0.0529
0.57535+-
0.0377 0.00000+-
0.0000
0.00230+-
0.0016
0.11290+-
0.0207 0.03695+-
0.0202
0.22060+-
0.0250
0.06100+-
0.0127
D2S1338 0.00000+-
0.0000
n/a n/a 0.00985+-
0.0048
0.00660+-
0.0032
0.00000+-
0.0000
0.49100+-
0.0380
0.05815+-
0.0077
n/a n/a
158
Appendix 3 continued
POPULATION/
LOCI
MOROCCO ALGERIA TUNISIA MALTA LIBYA EGYPT IRAN PAKISTAN INDIA BANGLADESH
D3S1358 0.00785+-
0.0055
0.68355+-0.0353
0.00120+-
0.0006 0.00235+-
0.0012 0.04350+-
0.0135
0.00000+-
0.0000
0.66735+-0.0345
0.09405+-0.0404
0.60160+-0.0267
0.01935+-
0.0076
VWA 0.00000+-
0.0000
0.01205+-
0.0059
0.09510+-0.0215
0.12370+-0.0290
0.16250+-0.0301
0.04930+-
0.0131
0.12090+-0.0461
0.00000+-
0.0000 0.00000+-
0.0000
0.00000+-
0.0000
D16S539 0.00000+-
0.0000
n/a 0.16350+-0.0188
0.00000+-
0.0000 0.00000+-
0.0000
0.02850+-
0.0083
0.00635+-
0.0029
0.04595+-0.0192
0.00000+-
0.0000
0.03105+-
0.0074
CSF1PO 0.00000+-
0.0000
0.00060+-
0.0003
0.00000+-
0.0000
0.00010+-
0.0001
0.03450+-
0.0105
0.06200+-
0.0154
0.75345+-
0.0345
0.85235+-
0.0381 0.04465+-
0.0340
0.04920+-
0.0214
TPOX 0.00000+-
0.0000
0.96720+-0.0084
0.00000+-
0.0000
0.71595+-0.0339
0.10095+-0.0113
0.02200+-
0.0072
0.09820+-0.0195
0.00000+-
0.0000 0.00000+-
0.0000
0.00020+-
0.0002
D21S11 0.00000+-
0.0000
0.56260+-0.0290
0.05110+-0.0110
0.00000+-
0.0000 0.01495+-
0.0078 0.00000+-
0.0000
0.29100+-0.0709
0.00355+-
0.0015 0.00325+-
0.0034
0.12340+-
0.0298
D8S1179 0.00000+-
0.0000
0.00000+-
0.0000
0.24440+-0.0252
0.00000+-
0.0000
0.52045+-0.0447
0.06915+-0.0180
0.02765+-
0.0118 0.00000+-
0.0000 0.00000+-
0.0000
0.00000+-
0.0000
D18S51 0.00000+-
0.0000
0.28960+-0.0313
0.00000+-
0.0000
0.22510+-0.0381
0.00000+-
0.0000
0.00000+-
0.0000
0.11170+-0.0315
0.01610+-
0.0179 0.00040+-
0.0004
0.01735+-
0.0141
D19S433 0.00000+-
0.0000
n/a n/a n/a 0.80720+-0.0325
0.21340+-0.0589
0.76840+-0.0409
n/a 0.00000+-
0.0000
n/a
TH01 0.00000+-
0.0000
0.05420+-0.0170
0.04410+-
0.0090 0.00000+-
0.0000
0.13570+-0.0446
0.03265+-
0.0116
0.93710+-0.0185
0.02390+-
0.0112 0.00495+-
0.0029
0.00170+-
0.0014
FGA 0.00000+-
0.0000
0.02580+-
0.0147
0.00000+-
0.0000
0.07365+-
0.0213
0.65040+-
0.0548
0.00000+-
0.0000
0.02470+-
0.0192
0.00655+-
0.0044
0.06725+-
0.0261
0.49345+-
0.0757
D5S818 0.00000+-
0.0000
0.03230+-
0.0105
0.00000+-
0.0000
0.00000+-
0.0000
0.00000+-
0.0000
0.00000+-
0.0000
0.91200+-
0.0196
0.00020+-
0.0002
0.00000+-
0.0000
0.00925+-
0.0061
D13S317 0.00000+-
0.0000
0.37445+-0.0406
0.01230+-
0.0026
0.00075+-
0.0005
0.72170+-0.0383
0.25175+-0.0486
0.00015+-
0.0002
0.00010+-
0.0001
0.00000+-
0.0000
0.00000+-
0.0000
D7S820 0.00000+-
0.0000
0.00115+-
0.0005
0.05460+-0.0191
0.05200+-0.0273
0.00200+-
0.0013
0.06475+-0.0138
0.12705+-0.0131
0.04045+-
0.0101
0.00000+-
0.0000
0.00015+-
0.0002
D2S1338 0.00000+-
0.0000
n/a n/a 0.20115+-0.0429
0.00375+-
0.0019
0.00000+-
0.0000
0.00275+-
0.0023
n/a 0.00000+-
0.0000
n/a
“n/a” marked when loci absent within a publication. Significant difference in bold (P-value ≤ 0.05). Using 20,000 Markov steps
159
Appendix 4: Haplotype frequencies for 217 male individuals from UAE population using 27 Y-STR loci from Y-Filer PLUS
Amplification kit (Chapter 7).
Ha
plo
typ
e
DY
S5
76
DY
S3
89
I
DY
S6
35
DY
S3
89
II
DY
S6
27
DY
S4
60
DY
S4
58
DY
S1
9
YG
AT
A H
4
DY
S4
48
DY
S3
91
DY
S4
56
DY
S3
90
DY
S4
38
DY
S3
92
DY
S5
18
DY
S5
70
DY
S4
37
DY
S3
85
a
DY
S3
85
b
DY
S4
49
DY
S3
93
DY
S4
39
DY
S4
81
DY
F3
87
S1
I
DY
F3
87
S1
II
DY
S5
33
n
1 12 13 22 30 19 10 15 13 11 19 9 14 23 10 11 39 18 14 16 17 29 14 12 23 37 38 11 1
2 15 12 21 28 20 10 17 16 11 22 10 15 21 10 11 35 18 16 13 15 27 14 11 21 38 38 10 1
3 15 12 21 29 20 10 15 15 11 21 10 15 21 11 11 36 19 14 17 18 29 13 11 27 38 39 11 1
4 15 12 24 28 19 11 15 14 12 19 10 15 22 11 14 39 15 14 13 17 25 11 12 23 35 40 11 1
5 15 12 24 28 23 11 17 14 11 18 11 15 25 11 11 38 19 14 14 19 29 13 11 25 38 38 12 1
6 15 12 25 28 22 11 18 14 11 20 11 15 25 11 11 39 20 14 14 19 28 13 11 25 38 39 11 1
7 15 13 20 28 19 10 17 16 11 19 10 16 23 7 13 36 16 14 13 16 33 13 11 22 37 38 11 1
8 15 13 21 29 19 11 17 15 11 22 9 18 21 11 11 43 16 14 17 17 30 15 11 27 38 39 12 1
9 15 13 21 29 19 11 18.2 14 11 20 10 15 26 10 11 40 19 14 12 18 25 12 11 25 37 40 11 1
10 15 13 21 29 23 10 16 14 10 22 10 17 21 10 11 38 18 16 13 15 29 15 11 21 39 39 10 1
11 15 13 21 31 18 10 17 15 12 22 10 15 21 11 11 39 19 14 16 18 29 13 12 27 36 39 11 1
12 15 13 22 29 20 10 16 14 11 21 10 15 23 9 11 39 17 15 13 16 31 12 11 24 36 39 12 1
13 15 13 22 29 20 10 16 15 11 21 10 15 23 9 11 39 17 15 13 16 31 12 13 25 36 41 12 1
14 15 13 22 29 21 10 16 13 11 21 10 15 23 9 11 37 16 15 12 16 30 12 11 24 36 40 12 2
15 15 13 23 29 23 10 17 14 10 22 10 17 21 10 11 38 18 16 13 15 30 15 12 21 38 38 11 1
16 15 14 20 31 21 11 15 13 12 19 11 15 24 9 13 38 13 14 16 16 33 13 11 24 37 38 10 1
17 15 14 21 31 22 10 16 14 11 19 10 15 23 9 13 35 18 14 14 16 34 13 11 22 37 37 11 1
18 15 14 21 31 22 10 16 14 11 19 10 15 23 9 13 35 17 14 14 16 34 13 11 22 37 37 11 1
160
19 15 14 21 31 22 10 16 14 11 19 10 15 23 9 13 35 17 14 14 16 34 13 11 22 37 38 11 1
20 15 14 21 32 21 10 15 15 12 21 10 15 21 11 11 37 19 14 17 18 30 13 11 30 37 39 11 1
21 15 14 23 30 20 10 16 14 11 20 10 15 23 9 11 39 14 15 13 16 30 12 11 24 36 40 12 2
22 16 11 21 28 20 11 17 14 10 22 11 15 24 10 12 37 18 16 14 16 27 13 12 24 38 39 10 1
23 16 12 21 29 19 12 17 15 11 19 11 13 24 9 11 37 15 15 14 18 29 13 11 23 36 38 9 1
24 16 12 21 30 18 9 16 14 11 21 10 15 23 10 13 37 19 16 14 16 29 13 13 27 39 39 10 1
25 16 12 23 28 20 10 15 15 12 16 10 16 23 9 14 37 20 14 13 13 29 13 11 27 37 38 11 1
26 16 13 20 31 21 11 17.2 14 11 19 10 14 23 10 12 38 18 14 13 17 25 12 11 27 36 39 11 1
27 16 13 21 29 20 10 15 15 12 21 10 15 24 9 11 38 17 14 16 16 30 12 12 25 39 40 12 1
28 16 13 21 29 20 10 15 15 12 21 9 15 23 9 11 39 16 15 13 16 30 12 11 22 39 39 12 1
29 16 13 21 30 18 11 16 15 11 21 10 16 21 11 11 41 17 15 16 16 31 14 12 27 37 39 11 1
30 16 13 21 30 18 11 16 16 11 21 10 16 21 11 11 42 17 14 17 18 31 14 13 26 38 40 11 1
31 16 13 21 31 19 11 16 15 12 21 10 15 21 11 11 38 19 14 16 17 28 13 13 27 39 39 11 1
32 16 13 21 31 20 10 17 16 12 20 10 15 21 11 11 39 19 14 16 17 28 13 11 28 37 39 11 1
33 16 13 22 29 19 10 15 14 11 22 10 17 23 9 12 38 17 15 13 17 32 12 12 21 40 41 12 1
34 16 13 22 30 18 9 15 13 11 20 10 17 24 10 11 38 20 14 15 17 32 13 11 22 35 38 12 1
35 16 13 22 30 19 9 15 13 11 20 10 17 24 10 11 40 21 14 15 17 32 13 11 22 35 38 12 1
36 16 13 22 30 16.3 11 18.2 14 11 19 11 14 23 10 11 38 18 14 13 18 25 12 11 25 37 37 11 1
37 16 13 22 30 23 10 20.2 14 11 20 11 14 23 10 11 39 18 14 13 19 25 12 11 26 37 37 11 1
38 16 13 22 30 23 11 16 14 11 21 10 15 22 9 11 38 17 15 13 13 30 12 11 23 39 40 11 1
39 16 13 23 30 21.2 11 18.2 14 11 19 10 14 23 10 11 38 18 14 13 18 25 12 12 25 37 37 11 1
40 16 14 19 32 20 10 17 15 11 21 9 15 21 10 11 40 17 16 12 12 34 13 11 25 35 37 11 1
41 16 14 21 30 22 10 17 14 11 19 10 15 23 9 13 35 18 14 14 16 34 13 11 22 37 37 11 1
42 16 14 21 30 22 10 18 14 11 19 10 16 24 9 13 35 17 14 14 15 33 13 10 22 36 37 12 1
43 16 14 21 31 21 10 17 14 11 19 10 16 23 9 13 35 16 14 14 16 35 13 10 21 37 38 12 1
161
44 16 14 21 31 22 10 17 14 11 20 10 15 23 9 13 35 17 14 14 16 34 13 11 22 37 37 11 1
45 16 14 21 31 22 11 17 14 11 19 10 15 23 9 13 35 17 14 12 16 34 13 11 22 37 38 11 1
46 16 14 22 32 20 11 16 14 11 20 10 15 23 11 11 36 19 14 16 17 33 14 11 25 36 36 11 1
47 16 14 23 30 20 10 15 14 12 21 10 16 23 9 11 38 20 15 14 18 33 13 11 23 38 41 12 1
48 16 14 23 30 21 10 16 14 12 20 10 15 24 9 11 38 16 15 13 15 31 12 11 24 35 40 12 1
49 16 14 23 31 18 11 16 15 11 20 10 17 21 11 11 41 17 14 16 18 32 15 11 26 37 38 11 1
50 16 14 24 31 19 10 16 15 11 21 10 16 21 11 11 39 20 14 16 17 28 13 12 27 36 38 11 1
51 16 15 21 32 22 10 17 14 11 19 10 15 23 10 13 35 17 14 14 15 32 13 11 22 37 37 11 1
52 17 12 21 28 22 10 14 14 11 18 10 15 22 10 16 37 17 16 15 16 27 11 13 25 39 39 12 1
53 17 12 22 28 25 11 15 14 11 21 10 14 23 9 11 35 16 15 14 15 28 12 12 22 39 39 11 1
54 17 12 23 28 20 11 15 14 12 20 10 15 22 11 16 38 15 15 13 17 26 11 13 24 39 41 12 1
55 17 12 23 28 23 11 14 14 12 19 10 15 22 10 14 38 15 15 14 16 25 11 12 25 34 41 12 1
56 17 12 23 29 20 11 15 15 12 18 10 15 24 11 14 38 18 14 13 16 28 15 11 26 36 38 13 1
57 17 13 20 30 20 11 17 14 12 20 10 16 24 10 11 38 21 14 17 18 32 13 12 21 35 36 12 1
58 17 13 20 30 21 10 17.2 15 11 20 10 15 23 10 11 38 18 14 13 18 26 12 11 25 35 38 11 2
59 17 13 20 30 21 11 18 14 12 20 10 17 24 10 11 36 20 14 17 18 30 13 12 21 35 38 12 1
60 17 13 20 30 21 11 18 14 12 20 10 18 25 10 11 37 21 14 17 18 32 13 12 21 35 37 12 1
61 17 13 20 30 22 11 17 14 11 20 10 16 24 10 11 38 20 14 17 18 31 13 12 21 35 37 12 1
62 17 13 20 30 22 11 17 14 12 20 10 16 24 10 11 38 21 14 18 18 31 13 12 21 35 37 12 1
63 17 13 20 31 21 11 17.2 14 11 20 11 15 23 10 11 36 18 14 14 19 26 12 11 26 35 39 10 1
64 17 13 21 29 17 10 15 15 11 20 10 15 24 9 11 34 18 15 13 18 28 12 13 24 39 39 11 1
65 17 13 21 29 19 10 18 14 10 19 10 15 22 9 13 34 19 14 15 20 34 13 11 24 36 39 11 1
66 17 13 21 29 20 11 17.2 14 11 20 10 15 23 10 11 40 17 14 15 19 25 12 11 26 36 38 11 2
67 17 13 21 29 23 10 18.2 14 11 21 10 14 23 10 11 38 18 14 13 17 25 12 11 25 37 38 11 1
68 17 13 21 30 20 10 18.2 14 11 20 11 14 23 10 11 38 17 14 13 19 26 12 11 26 37 37 11 1
162
69 17 13 21 30 20 10 18.2 14 11 20 11 14 23 10 11 38 19 14 13 19 27 12 11 26 37 37 11 1
70 17 13 21 30 21 10 18.2 14 10 20 11 14 23 10 11 39 18 14 13 19 25 12 11 25 36 36 11 1
71 17 13 21 30 21 10 18.2 14 11 20 11 14 23 10 11 40 18 14 13 18 25 12 11 26 37 37 11 1
72 17 13 21 30 21 10 19.2 14 11 20 10 14 23 10 11 37 17 14 13 17 25 12 12 24 35 39 11 1
73 17 13 21 30 21 11 14 13 10 20 10 15 25 10 11 37 19 14 16 17 32 13 11 24 37 39 12 1
74 17 13 21 30 21 11 15 13 10 20 10 15 25 10 11 36 19 14 16 17 33 13 11 25 38 38 12 1
75 17 13 21 30 21 11 19.2 14 11 20 10 14 23 10 11 37 17 14 13 17 25 12 12 24 35 40 11 1
76 17 13 21 30 21 12 16.2 15 11 20 11 15 23 10 11 39 18 14 13 17 25 12 11 25 36 37 11 1
77 17 13 21 30 22 10 19.2 14 11 20 11 14 23 10 11 41 17 14 12 18 25 12 13 26 37 38 11 1
78 17 13 21 31 18 10 17 13 11 20 10 15 24 10 11 40 17 14 16 17 31 12 13 25 38 39 11 1
79 17 13 21 31 18 10 18 14 10 18 10 15 24 9 13 35 18 14 15 16 34 13 12 23 38 39 11 1
80 17 13 21 31 19 9 18 13 11 20 10 15 24 10 11 41 18 14 14 15 32 14 10 27 39 39 10 1
81 17 13 21 32 18 10 18 13 11 20 10 14 24 10 11 38 18 14 16 18 31 12 12 24 38 38 11 1
82 17 13 21 32 19 9 18 13 11 20 10 15 24 10 11 41 18 14 14 15 32 14 10 27 39 39 10 1
83 17 13 22 29 20 10 18 13 10 19 10 15 22 11 15 38 16 14 14 16 30 13 12 24 35 36 11 1
84 17 13 22 30 18 10 16 13 11 20 9 15 25 10 11 40 19 14 15 18 34 14 11 22 36 38 11 1
85 17 13 23 28 20 11 17 14 12 19 11 15 25 12 14 40 17 15 11 14 28 12 12 22 35 36 12 1
86 17 13 23 29 18 11 15 15 13 20 10 17 25 11 11 43 18 14 11 14 32 13 10 23 37 39 12 1
87 17 13 23 29 23 11 15 14 13 18 11 14 24 12 13 38 17 15 11 14 28 12 12 22 35 35 11 1
88 17 13 23 30 17 11 15 16 12 20 11 15 25 11 11 39 18 14 11 14 34 13 10 21 37 39 12 1
89 17 13 23 30 17 11 17 16 11 20 11 16 24 11 11 40 18 14 11 14 32 13 10 23 37 38 12 1
90 17 13 23 30 21 9 15 13 12 20 10 16 24 10 11 43 17 14 16 18 33 13 12 22 35 38 12 1
91 17 13 23 30 21 9 15 13 12 20 10 16 24 10 11 43 17 14 16 18 33 13 12 22 35 37 12 1
92 17 13 26 30 21 11 16 14 12 20 10 17 23 11 13 43 16 15 12 12 30 13 11 23 37 38 12 1
93 17 14 17 32 23 11 17 15 11 20 10 12 24 11 11 39 15 14 13 14 31 13 11 22 35 42.2 12 1
163
94 17 14 18 31 16 11 17 15 11 21 10 15 21 11 11 42 18 14 16 16 29 13 11 25 37 37 11 1
95 17 14 18 31 16 11 17 16 11 21 10 15 21 11 11 42 18 14 16 16 29 13 11 25 37 37 11 1
96 17 14 20 31 19 10 17 13 12 20 10 16 23 9 13 34 18 15 15 15 33 13 11 23 37 37 11 1
97 17 14 21 30 19 10 15 15 11 18 10 14 23 9 11 40 18 14 14 20 32 12 14 20 37 41 12 1
98 17 14 21 30 20 10 15 14 11 20 10 16 22 9 11 40 21 15 13 18 33 12 11 23 37 39 11 1
99 17 14 21 30 22 10 14 13 12 19 10 17 22 9 13 39 18 15 14 15 34 13 11 26 38 40 12 1
100 17 14 21 31 18 11 16 13 12 20 9 15 24 10 11 39 19 14 15 17 29 14 12 25 36 37 12 1
101 17 14 21 31 19 10 16 13 12 19 9 15 23 9 13 35 19 15 14 17 32 13 13 27 36 38 13 1
102 17 14 21 31 22 10 19.2 14 11 20 10 13 23 10 11 38 18 14 13 18 25 12 11 25 37 37 11 1
103 17 14 22 30 21 11 16 14 11 20 10 16 23 9 11 37 19 14 16 20 32 12 11 23 35 41 11 1
104 17 14 24 32 19 10 16 14 11 19 11 14 23 9 12 33 19 14 15 16 35 13 11 23 37 37 12 1
105 17.3 13 23 30 17 11 16 16 11 20 11 16 24 11 11 39 19 14 11 14 30 13 10 24 38 38 12 1
106 18 12 21 28 21 11 15 17 10 20 10 14 24 10 12 39 18 15 14 14 29 13 12 21 37 39 11 1
107 18 12 21 29 20 10 19.2 15 11 20 11 14 23 11 11 39 18 14 13 19 27 12 11 26 37 37 11 1
108 18 12 21 29 22 10 17.2 14 11 20 11 14 23 10 11 39 18 14 13 18 25 12 12 25 37 37 11 1
109 18 12 22 29 21 10 14 13 11 20 10 15 23 10 11 40 20 14 16 18 33 12 10 23 35 38 12 1
110 18 12 23 29 19 10 18.2 14 11 20 11 14 23 10 11 38 18 14 13 19 26 12 12 26 36 37 11 1
111 18 12 23 31 17 11 15 15 13 20 10 16 25 11 11 42 20 15 11 15 32 13 11 23 37 38 13 1
112 18 12 24 27 21 11 18 14 13 19 11 16 23 12 14 36 17 16 11 15 30 12 13 22 35 36 12 1
113 18 13 20 30 20 10 19.2 14 11 20 11 15 23 10 12 39 18 14 13 18 26 12 11 25 36 37 11 1
114 18 13 20 30 21 11 19 14 12 20 10 16 23 10 11 37 20 14 17 17 30 13 12 21 35 37 12 1
115 18 13 20 30 22 10 17.2 14 11 20 10 15 23 10 11 37 18 14 13 16 26 12 11 25 35 38 11 1
116 18 13 20 30 22 11 17 14 12 20 10 16 23 10 11 38 18 14 19 20 34 13 11 21 37 37 12 1
117 18 13 20 31 20 10 17.2 14 11 20 10 16 24 10 11 37 18 14 14 17 26 12 11 26 36 38 11 1
118 18 13 21 29 21 11 18.2 14 11 20 11 14 23 10 11 40 20 14 13 17 25 12 12 26 36 37 11 1
164
119 18 13 21 29 21 11 18.2 14 11 20 11 14 23 10 11 39 18 14 13 17 26 12 11 24 36 36 11 1
120 18 13 21 29 21 11 19.2 14 11 20 11 14 23 10 11 41 17 14 13 19 25 12 11 26 37 37 11 1
121 18 13 21 29 21 12 18.2 14 11 20 12 14 23 10 11 39 18 14 13 19 25 12 11 24 37 38 11 1
122 18 13 21 29 22 11 17.2 14 11 20 10 15 23 10 11 39 17 14 13 19 25 12 11 26 39 40 11 1
123 18 13 21 29 22 11 18.2 14 11 20 11 14 23 10 11 39 18 14 13 17 25 12 11 25 36 37 11 1
124 18 13 21 29 23 10 19.2 15 11 20 10 14 24 10 11 35 17 14 17 19 27 12 12 25 37 42 11 1
125 18 13 21 30 18 10 16 17 11 21 10 15 21 11 11 42 18 14 18 18 26 14 12 24 39 40 11 1
126 18 13 21 30 18 10 17 13 11 20 11 16 23 10 11 36 21 14 16 17 33 12 12 27 39 40 10 1
127 18 13 21 30 19 10 17 13 11 20 11 16 24 10 11 40 18 14 14 16 30 14 13 24 37 37 12 1
128 18 13 21 30 19 11 16 16 11 21 10 17 21 11 9 10 17 14 17 17 30 14 12 23 38 39 11 1
129 18 13 21 30 20 10 16 17 11 21 10 17 21 11 11 41 17 14 16 17 26 13 12 24 39 39 10 1
130 18 13 21 30 20 10 16 17 11 21 10 17 21 11 11 40 17 14 17 17 26 14 11 24 38 39 11 1
131 18 13 21 30 20 10 18.2 14 11 20 11 14 23 10 11 38 18 14 13 19 26 12 12 28 35 37 11 1
132 18 13 21 30 20 10 18.2 14 11 20 11 14 23 10 11 39 18 14 13 18 26 12 11 27 37 37 11 1
133 18 13 21 30 20 10 18.2 15 11 20 11 14 23 10 11 38 17 14 14 20 26 12 11 26 37 38 11 1
134 18 13 21 30 20 11 15 13 10 20 10 16 25 10 11 36 19 14 16 17 33 13 12 26 38 38 12 1
135 18 13 21 30 20 11 16 16 12 21 10 15 21 11 11 40 17 14 17 18 30 14 12 25 38 38 11 1
136 18 13 21 30 20 12 15 13 10 20 10 15 25 10 11 37 19 14 16 17 34 13 11 25 38 38 12 1
137 18 13 21 30 21 10 18.2 14 11 20 10 14 23 10 11 38 17 14 13 18 26 12 13 25 36 38 11 1
138 18 13 21 30 21 10 18.2 14 11 20 10 14 23 10 11 39 17 14 13 18 25 13 11 26 36 36 11 1
139 18 13 21 30 21 10 18.2 14 11 20 11 14 23 10 11 38 18 14 13 18 25 12 11 26 37 37 11 1
140 18 13 21 30 21 10 19.2 14 11 20 11 14 23 10 11 38 18 14 13 18 25 12 11 26 37 37 11 1
141 18 13 21 30 21 10 20.2 14 11 20 11 14 23 10 11 40 17 14 13 18 25 12 12 26 37 37 11 1
142 18 13 21 30 21 11 15 13 10 20 10 15 25 10 11 37 19 14 16 17 33 13 12 25 38 38 12 1
143 18 13 21 30 21 11 18.2 14 11 20 10 15 23 10 11 40 18 14 13 20 25 12 11 25 36 38 11 1
165
144 18 13 21 30 23 10 18.2 14 11 20 10 14 23 10 11 38 18 14 13 18 25 12 11 25 37 38 11 1
145 18 13 21 30 23 10 18.2 14 11 20 10 14 23 10 11 38 18 14 13 19 24 12 12 24 37 38 11 1
146 18 13 21 30 23 11 18.2 14 11 20 11 14 23 10 11 37 19 14 13 18 25 12 11 24 36 37 11 1
147 18 13 21 30 24 11 18.2 14 11 20 11 14 21 10 11 38 18 14 13 17 26 13 11 25 37 37 11 1
148 18 13 21 30 24 11 19.2 14 11 20 10 14 23 10 11 38 18 14 13 18 26 12 11 26 37 38 11 1
149 18 13 21 31 21 11 18.2 14 11 20 10 15 24 10 11 37 17 14 12 18 28 12 12 25 37 38 11 1
150 18 13 22 28 22 10 18 14 12 19 11 14 23 11 11 40 18 14 10 14 34 13 12 28 38.3 39.2 13 1
151 18 13 22 29 18 10 16 14 11 21 10 15 23 9 11 42 16 14 13 17 32 12 12 24 36 36 12 1
152 18 13 22 29 21 10 18 14 11 19 10 16 23 11 14 40 17 14 14 16 28 13 11 26 36 40 11 1
153 18 13 22 30 20 9 15 14 12 20 10 16 24 10 11 40 22 14 15 17 33 13 12 22 35 36 13 1
154 18 13 22 30 20 10 18.2 14 11 20 10 14 23 10 11 38 17 14 13 18 26 12 12 25 36 37 11 1
155 18 13 22 30 20 10 18.2 14 11 20 11 14 23 10 11 39 19 14 13 18 26 12 11 26 36 36 11 1
156 18 13 22 30 21 10 18.2 14 11 20 11 15 23 10 11 39 18 14 13 18 26 12 12 24 36 37 11 1
157 18 13 22 30 23 9 15 13 12 20 10 17 24 11 11 40 21 14 16 17 33 13 13 22 34 36 12 1
158 18 13 22 30 23 10 19.2 14 11 20 10 14 23 10 11 39 17 14 13 18 25 12 11 25 37 38 11 1
159 18 13 22 31 20 11 20 14 11 19 10 15 24 9 11 39 20 15 15 16 29 12 12 24 36 41 13 1
160 18 13 23 28 22 11 16 13 11 19 11 15 25 12 13 38 16 15 11 14 31 12 12 22 35 36 12 1
161 18 13 23 29 15 11 15 15 12 20 11 16 25 11 11 40 18 14 11 14 31 13 10 23 38 38 13 1
162 18 13 23 29 17 11 16 16 12 20 11 15 25 11 12 41 18 15 11 14 32 13 10 23 38 39 12 1
163 18 13 23 29 17 13 15 16 12 20 10 15 26 11 11 41 19 14 11 14 32 14 10 22 37 38 12 1
164 18 13 23 29 19 11 15 16 13 20 11 16 25 11 11 41 19 14 11 14 33 13 10 21 37 37 12 1
165 18 13 23 30 18 12 16 16 13 20 11 14 25 11 11 42 19 14 11 14 33 13 12 23 37 39 13 1
166 18 13 23 31 17 11 16 16 12 20 10 16 25 11 11 41 19 14 12 13 29 13 10 23 37 38 14 1
167 18 13 23 31 17 11 15 16 13 20 10 15 23 11 11 40 22 14 11 15 31 13 10 24 36.2 39 12 1
168 18 13 23 31 17 11 15 16 13 21 10 16 27 11 11 41 19 14 11 14 31 13 10 24 38 38 12 1
166
169 18 13 23 31 22 9 15 13 12 20 10 17 24 10 11 41 22 14 16 17 33 13 12 22 35 36 13 1
170 18 14 22 30 19 11 17.2 14 11 21 10 15 24 10 11 39 19 14 12 20 27 12 11 24 39 39 11 1
171 18 14 22 30 19 11 18.2 13 11 20 12 13 22 10 11 39 18 14 13 17 26 12 11 25 36 37 11 1
172 18 14 22 30 20 10 17 13 11 18 10 15 24 9 11 37 16 15 10 13 31 12 11 27 37 37 11 1
173 18 14 23 29 18 11 15 13 12 20 11 15 25 11 11 42 19 14 11 14 32 13 10 23 37 38 12 1
174 18 14 23 32 17 11 16 15 12 20 10 15 25 11 11 42 19 14 11 14 32 13 10 23 37 40 11 1
175 18 14 24 30 22 11 17 15 12 18 10 15 22 12 10 40 18 15 12 19 31 14 12 25 36 40 11 1
176 19 12 20 29 21 10 17.2 14 11 20 11 17 23 10 11 39 18 14 13 17 27 12 11 25 36 38 11 1
177 19 13 20 30 21 10 18.2 14 11 20 10 14 23 10 11 38 17 14 13 17 26 12 12 25 36 38 11 1
178 19 13 20 31 20 10 17.2 15 12 20 10 15 23 10 11 38 20 14 13 17 27 12 11 25 37 37 11 1
179 19 13 20 32 20 11 16 15 12 20 10 16 25 9 11 42 19 14 18 18 34 13 12 22 36 36 12 1
180 19 13 20 32 20 11 17.2 15 12 20 10 15 23 10 11 38 20 14 13 17 27 12 11 25 37 37 11 1
181 19 13 21 29 19 12 17.2 14 11 20 11 16 24 10 11 40 18 14 13 20 28 12 12 26 36 40 11 1
182 19 13 21 29 20 11 18.2 14 11 20 10 13 23 10 11 37 18 14 13 17 26 12 11 25 36 37 11 1
183 19 13 21 29 22 11 18.2 14 11 19 10 15 24 10 11 40 18 14 18 18 28 12 12 25 39 39 11 1
184 19 13 21 29 23 10 17.2 15 11 19 10 15 25 7 11 41 17 14 17 18 27 12 12 25 39 39 12 1
185 19 13 21 30 19 10 18.2 14 11 20 11 14 23 10 11 37 18 14 13 20 26 12 11 26 36 37 10 1
186 19 13 21 30 20 10 18.2 14 11 20 11 14 23 10 11 40 18 14 13 19 27 12 12 26 37 37 11 1
187 19 13 21 30 20 10 18.2 14 11 20 11 14 23 10 11 42 18 14 13 19 27 12 11 26 37 37 11 1
188 19 13 21 30 20 10 18.2 14 11 20 11 14 23 10 11 42 18 15 13 19 27 12 11 26 37 37 11 2
189 19 13 21 30 20 10 18.2 14 11 20 11 14 24 10 11 39 18 14 13 19 25 12 11 26 37 37 11 1
190 19 13 21 30 21 10 18.2 14 11 20 11 14 23 10 11 38 17 14 13 20 26 12 11 25 37 37 11 1
191 19 13 21 30 21 11 18.2 14 11 20 12 14 23 10 11 37 18 14 13 19 25 13 11 26 36 37 11 1
192 19 13 21 30 21 11 19.2 14 12 20 9 13 23 10 11 41 20 14 13 18 25 12 11 25 34 38 12 1
193 19 13 21 31 20 10 18.2 14 11 20 10 13 23 10 11 39 18 14 13 19 26 12 11 26 37 37 11 1
167
194 19 13 21 31 21 12 18.2 14 12 21 10 14 23 10 11 39 18 14 13 19 25 12 11 25 36 39 12 1
195 19 13 22 30 19 11 15 14 12 20 9 15 24 9 10 40 16 15 14 22 28 13 11 23 37 38 12 1
196 19 13 23 29 17 11 16 16 12 20 11 15 25 11 12 41 18 15 11 14 33 13 10 23 38 39 12 1
197 19 13 23 30 16 11 16 16 11 20 11 16 25 11 11 41 19 14 9 11 33 14 12 26 37 38 12 1
198 19 13 23 30 17 10 16 15 12 20 11 15 24 11 11 41 19 14 11 14 33 13 11 23 37 39 12 1
199 19 13 23 30 18 11 15 17 12 20 11 15 25 11 11 38 19 14 11 14 32 13 10 24 37 38 13 1
200 19 13 23 30 20 11 14 14 11 21 9 16 22 9 11 41 16 14 13 14 33 12 11 23 39 39 11 1
201 19 13 23 31 17 12 15 15 12 20 10 17 24 11 11 41 21 14 11 15 33 13 10 24 37 37 13 1
202 19 13 23 31 17 12 17 16 13 20 10 15 25 11 11 40 19 14 11 14 33 13 10 23 37 40 12 1
203 19 13 24 29 21 11 17 15 13 19 11 15 24 12 13 7 17 15 11 14 30 13 12 22 35 37 13 1
204 19 14 21 30 19 11 17.2 14 11 20 10 17 24 10 11 39 19 14 13 22 27 12 12 27 39 40 11 1
205 19 14 21 31 20 9 16 13 12 20 10 15 24 11 11 39 21 15 15 16 32 14 12 25 37 37 12 1
206 19 14 21 31 22 11 19.2 14 11 20 10 14 24 10 11 38 19 14 13 17 26 12 11 25 35 38 11 1
207 19 14 23 30 17 11 16 17 13 20 11 14 24 11 11 40 19 14 11 14 31 13 10 23 37 38 12 1
208 19 15 21 31 19 11 17.2 14 11 20 10 17 24 10 11 39 19 14 13 20 27 12 12 25 37 39 11 1
209 19 16 21 32 19 11 17.2 14 11 20 10 17 24 11 11 39 19 14 13 22 27 12 12 27 36 39 11 1
210 20 13 23 30 23 11 17 15 13 19 11 15 23 12 15 39 19 14 12 15 29 13 13 22 36 38 13 1
211 20 14 21 30 19 10 17.2 14 11 20 10 16 24 10 11 38 19 14 13 21 27 12 12 26 36 40 11 1
212 20 14 22 31 21 10 18.2 14 11 20 11 14 23 10 11 38 18 14 13 18 25 12 14 25 36 37 11 1
Total of Unique Haplotypes 207
Total of Different Haplotypes 212
Overall Total 217
168
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