Post on 04-Jan-2016
description
Сравнительная геномикаПолиморфизм генома человека
ФББ, 4 курс
Василий Евгеньевич Раменский, Институт молекулярной биологии РАН
…caccagctcctgtgGggggaggccctgct… …caccagctcctgtgGggggaggccctgct… …caccagctcctgtgGggggaggccctgct… …caccagctcctgtgCggggaggccctgct… …caccagctcctgtgCggggaggccctgct…
…and so are their genomes
Определение
SNP (single nucleotide polymorphism): существование в популяции на одной и той же позиции геномной ДНК двух нуклеотидных вариантов с частотой более редкого варианта (аллеля) ≥1%
5’---------------A---------------3’ |||||||||||||||||||||||||||||||3’---------------T---------------5’
5’---------------G---------------3’ |||||||||||||||||||||||||||||||3’---------------C---------------5’
Na
Ng
Na+Ng = N, Na/N ≥0.01, Ng/N ≥0.01
Комментарии к определению
•речь идет о сравнении последовательностей одного биол. вида
•слово «полиморфизм» не имеет в русском языке
множественного числа (Н.Ляпунова, личное сообщение)
•в обыденной речи под «полиморфизмом» чаще всего
подразумевают именно нуклеотид (т.е. используют его как
синоним слова «мутация»)
•определение подразумевает достоверное измерение частот в
популяции(-ях), что в текущей практике пока редкость
Типы полиморфизма в геноме
* однонуклеотидный (SNP)
* короткая вставка/делеция
* микросателлитный повтор различной длины (VNTR,
variable number tandem repeat)
* вставка объекта
* множественный нуклеотидный (MNP)
Некоторые свойства SNPs
• Comprise the ~90% of human genetic variation
• Occur with an average density ~1/1000 bp
• Transition C↔T(G↔A) occurs at ~2/3 of all cases, three
transversions C↔A (G↔T), C↔G(G↔C), T↔A(A↔T) in
~1/6 of all cases each
• Most of them (~85%) are common to all populations
(with differing allele frequencies)
Why SNPs are important?
• Convenient genetic markers
• Responsible for existence of various phenotypes,
with primary interest in disease ones
• Pharmacogenomics: individual response to drugs
• Clues to understand human evolution
Build Date # rs’s, x106
10? Feb. 01. . . . . . . . . .1.42
106 Aug. 02. . . . . . . . . .2.81
110 Jan. 03. . . . . . . . . . 3.05
119 Jan. 04. . . . . . . . . . 7.23
124 Jan. 05 . . . . . . . . . .10.0
dbSNP build statistics
Estimates of SNP density in the human genome
• Li and Sadler (1991), Genetics, ~1/1000 bp
• Zhao et al., (2003), Gene: ~1/1200 bp
• dbSNP, build 124 (2005): ~1/300 bp (?)
Классификация SNP по положению в геноме
1. гены
1.1 UTR
1.2 экзоны (cSNP)
1.2.1 синонимичные(sSNP)
1.2.2 несинонимичные (nsSNP)
1.3 интроны
1.4 сайты сплайсинга
2. регуляторные участки генов (rSNP)
3. межгенные участки
Synonymous vs. non-synonymous SNPs:
…CAC CAG CTC CTG TGG GGG GAG GCC CTG CT…
…CAC CAG CTC CTG TGC GGG GAG GCT CTG CT…
HGVBase ID: SNP000003023 G C Hypothetical SNP: C T
… H Q L L W G E A L …
… H Q L L C G E A L …
Example: Lysosomal alpha-glucosidase precursor (SwissProt P10253)
nsSNP Trp746Cys sSNP Ala749Ala
Summary of Annotation on human Genome Build 33 dbSNP Build 124 :
FUNCTION CLASS CODE
SNP COUNTGENE
COUNT
FUNCTIONAL
CLASSIFICATION
1 338787 26210 Locus region
3 39214 14342Allele synonymous to contig nucleotide
4 50772 15710Allele nonsynonymous to contig nucleotide
5 546965 17898 untranslated region
6 2925773 19332 intron
7 832 769 splice site
8 89554 18655 Allele is same as contig nucleotide
9 7111 1006 Coding: synonymy unknown
Упражнение
В одной базе ~11,000 nsSNPs в ~6,000 белков. В другой базе
~47,000 последовательностей белков общей длиной
~19.5x106 остатков. Оценить
(а) среднюю длину белка
(б) среднее число nsSNP в одном белке
(в) среднее число nsSNP на единицу длины белка
Жизненный цикл SNP (по Miller&Kwok, 2001)
I. Появление нового аллельного варианта путем мутации
(~100 мутаций на индивидуум)
II. «Выживание» до момента появления гомозигот по этому
аллелю
III. Медленное увеличение частоты в популяции
IV. Фиксация нового аллеля (0 vs. 100%), превращение в
between-species difference
Упражнение
Описанный выше жизненный цикл SNP занимает ~0.3 млн
лет. Предполагая, что разделение человека и шимпанзе
произошло ~5 млн лет назад, а выход H.sapiens из Африки и
разделение различных популяций ~0.1-0.2 млн лет назад,
аргументировать возможность существования (а) одинаковых
SNPs у человека и других видов, (б) «private» SNP, т.е.
локализованных в пределах одной человеческой популяции
Why polymorphisms are maintained in the population?
• Selectionists: because heterozygotes have higher fitness
• Neutralists: because all observed polymoprhisms are selectively neutral
- - - - - -- - - - - - - - - - - - - - - - - - - - - - - - - Reality: is always somewhat more complicated
Why SNPs are important?
• Convenient genetic markers
• Responsible for existence of various phenotypes,
with primary interest in disease ones
• Pharmacogenomics: individual response to drugs
• Clues to understand human evolution
nsSNPs vs. disease mutations
Disease mutations are rare (<<1%) and usually cause monogenic diseases (e.g., cystic fibrosis)
nsSNPs are frequent (>1%) and can modify risks of major common (multigenic, complex) diseases (e.g., cancer, cardiovascular disease, mental illness, autoimmune states, diabetes)
In some cases, however, it is difficult to make a distinction
Some common nsSNPs are known to affect critical structure features
Frequency of the haemochromatosis allelic variant of HLA-H protein Cys260Tyr (with destroyed disulphide
bond) is up to 6% in Northern Europe
Identifying SNPs responsible for specific phenotypes
whole genome scan – hypothesis free approach; extraordinary number of candidate SNPs
candidate gene studies – requires a priori models; nevertheless, large numbers of candidate SNPs to be tested
Both methods, however, require huge amounts of expensive experimental data and are are statistically unreliable. Therefore, in silico expertise is required
Methods for prediction of effect of nsSNPs
* Sequence-based methods: analysis of multiple alignment with homologs Ng-Henikoff [2002]
* Structure-based methods: analysis of various structural parameters Wang, Moult [2001]; Chasman, Adams [2001]
* Combined methods: sequence and structure analysis Sunyaev,Ramensky,Bork [2000, 2001, 2002]
PolyPhen: prediction of amino acid substitution effect on protein function
Data sources:
1. Sequence annotation of the query protein2. PSIC profile matrix values derived from multiple
alignment with homologous proteins3. Structural parameters and contacts of query protein
structure or its >50% homolog
Prediction: benign (neutral), damaging (deleterious)
PolyPhen query processing flowchart
INPUT:
•Sequence: …IMAGLQQTNSE…
•Position: 133
•Var1: Q
•Var2: P
•ACC/ID (if known protein): DMD_HUMAN
sequence annotation
PSIC profile scores for two amino acid variants
structural parameters and contacts
prediction rules
PREDICTION:•damaging•benign•unknown
I. Sequence annotation
Hereditary hemochromatosis protein precursor (HLA-H, Q30201)
Features checked:* bond: DISULFID, THIOLEST, THIOETH
* site: BINDING, ACT_SITE, LIPID, METAL, SITE, MOD_RES, SE_CYS
* region: TRANSMEM, SIGNAL, PROPEP
II. PSIC: profile analysis of homologous sequences
1. Align with homologous proteins with seq. ide. 30..94%
II. PSIC: profile analysis of homologous sequences
2. Calculate the profile matrix with PSIC algorithm
Profile matrix: Sa,j = ln[ pa,j / qa ], a = {1,..20}, j = {1,..N}, N = alignment length
SAsn,4 SCys,4
II. PSIC: profile analysis of homologous sequences
3. Analyse difference between profile scores for two a.a. variants:
SAsn,4 SCys,4
AsnCys: = | SAsn,4 – SCys,4 | = 1.591
III. 3D structure analysis1. Residues that are in spatial contact with a
ligand or other “critical” residues
Zen 999
residues in 5Å contact with Zen 999
Bos Taurus trypsin [PDB ID :1ql7]
III. 3D structure analysis2. Residues that form the hydrophobic core of
the protein (buried residues)
Bos Taurus trypsin [PDB ID :1ql7]
Surface residues
Buried residues
Structural parameters and contacts
Secondary structure Phi-psi dihedral angles Solvent accessible surface area, normed s.a.s.a Change in accessible surface propensity Change in residue side chain volume Contacts with heteroatoms Interchain contacts Contacts with functional sites (BINDING,
ACT_SITE, LIPID, and METAL) Region of the phi-psi map (Ramachandran map) Normalised B-factor (temperature factor)
RULES (connected with logical AND) PREDICTION
PSIC score difference :
Substitution site properties: Substitution type properties:
arbitraryannotated as a functional* or bond formation** site
arbitrary probably damaging
not consideredin a region annotated or predicted as transmembrane
PHAT matrix difference resulting from substitution is negative
possibly damaging
0.5 arbitrary arbitrary benign
>1.0atoms are closer than 3.0Å to atoms of a ligand or residue annotated as BINDING, ACT_SITE, LIPID, METAL
arbitrary probably damaging
0.5<1.5
normed accessibility ACC15%
absolute change of accessible surface propensity is 0.75 orabsolute change of side chain volume is 60
possibly damaging
normed accessibility ACC5%
absolute change of accessible surface propensity is 1.0 or absolute change of side chain volume is 80
probably damaging
1.5<2.0 arbitrary arbitrary possibly damaging
>2.0 arbitrary arbitrary probably damaging
Control sets
all dam unknown dam/(dam+ben)
–––––––––––––––––––––––––––––––––––––––––––––
Disease mutations
Strict set 444 366 3 82.9%
Total 2,782 2,047 70 75.4%
Between species substitutions
Total 671 58 5 8.7%
PolyPhen: predictions for nsSNPs
All SNPs from HGVBase, rel.12.............................983,589
synonymous...................................9,310 (5,378 proteins)
non-synonymous..............................11,152 (6,124 proteins)
Predictions for nsSNPs:
unknown................................................1,987
benign.................................................6,317
possibly damaging......................................1,591
probably damaging......................................1,257
Prediction basis:
multiple alignment...................................2,654
sequence annotation....................................118
structure...............................................76
PolyPhen predictions for dbSNP b.121All: 9,502 unknown27,991 benign...............67.6% 7,905 possibly damaging....19.1% 5,521 probably damaging....13.3%50,919 total (44,005 unique rs’s)
With structure: 42 unknown 2,142 benign...............57.1% 531 possibly damaging....14.2% 1,076 probably damaging....28.7% 3,791 total (,167 uniqe rs’s)
[ Ivan Adzhubei, 2004 ]
PolyPhen predictions for dbSNP b.121All: Filtered: 5 seq. in multiple alignment16,813 benign...............64.2% 5,195 possibly damaging....19.8% 4,168 probably damaging....15.9%26,176 total (21,677 unique rs’s)
With structure:Filtered: 5 seq. in multiple alignment2,021 benign...............56.6% 499 possibly damaging....14.0%1,050 probably damaging....29.4%3,570 total (2,983 unique rs’s)
[ Ivan Adzhubei, 2004 ]
Hydrophobic core stability parameters are the best predictors
Ramensky et al., Nucleic Acids Res. (2002) 30:3894-90
PolyPhen http://www.bork.embl.de/PolyPhen
PolyPhen input :
Protein identifier OR sequence
Substitution position
Substitution type
DAMAGING nsSNPs
Transphyretin
(PDB: 1tyr, SNP000012365)
Thr118 Asn occurs at the ligand (REA) binding site
Thr 118
REA 130
DAMAGING nsSNPs
Trypsin
(PDB: 1trn, SNP000012965)
Ser142Phe results in the strong side chain volume change at a buried position
Ser 142
PolyPhen: дитя семи нянек
ЦИКЛОП ПОЛИФЕМ ПРЕДСТАВЛЯЛ СОБОЙ УНИКАЛЬНЫЙ ПОДВИД КАРЛИКОВЫХ СЛОНОВ
Известия-Наука, 18 ноября 2003
Вонзая заостренное бревно в единственный глаз свирепого циклопа Полифема, легендарный Одиссей истреблял уникальный вид карликовых слонов, обитавших на острове Сицилия. Древний миф об одноглазых человекообразных исполинах развеяли итальянские палеонтологи на научной экспозиции "Полифем в Модене".
На выставке представлены черепа, обнаруженные исследователями на Сицилии, у которых одна фронтальная глазница. С первого взгляда она очень напоминает глаз во лбу. Найденные рядом с черепами кости действительно принадлежат немаленькому млекопитающему, которое имело габариты крупного медведя. Обладатель этих останков был не циклопом, а карликовым слоном. "Глаз" во лбу - отверстие для дыхательных путей, то есть для хобота.
Polyphenism: the ability of a single genome to produce two or more alternative morphologies within a single population in response to an environmental cue (such as temperature, photoperiod, or nutrition). [Dr. Ehab Abouheif, McGill University, Montréal Québec]
The seasonal morphs of the buckeye butterfly, Precis coenia (Nymphalidae). The ventral surfaces are shown. The Summer morph ("linea") is on the left; the Fall morph ("rosa") is on the right. [Scott F.Gilbert, A Companion to Developmental Biology. Chapter 22, Seasonal Polyphenism in Butterfly Wings]
Damaging nsSNPs
• We estimate that ~20% of non-synonymous cSNPs from databases are damaging
• Average allele frequency of non-synonymous cSNPs predicted to be damaging is twice lower than for benign non-synonymous cSNPs
• We propose to use these predictions for prioritisation of candidates for association studies