Genetic Variations

Lakshmi K Matukumalli

Human – Mouse Comparison

Ploidy (Down’s Syndrome)

Structural Variations

InversionsTranslocationsSegmental duplications

Single nucleotide polymorphismsShort IndelsSimple sequence repeatsCopy number variantsLoss of heterozygosity

Microsatellite

(2-9 bp core repeat)

Minisatellite

(10-60 bp core repeat)

Copy number variants

Molecular Variations

Type of polymorphisms

TC

Single-nucleotide Polymorphism (SNP)

5’ Flanking region

Promoter

5’ Untranslated

region

ATG

Coding

Nonsynonymous polymorphism

GAG Asp GUG Val

Intron

Transcript

Synonymous polymorphism

GAU Asp GAC Asp

Coding

End

3’ Untranslated

region

Insertion/deletion polymorphism (indel)

TAACGGTA GG

3’ Flanking region

Choosing the Technology

Extent of Variation (Human Genome)

> 5 million SNPs (dbSNP)Recent genome analysis of diploid individual showed 4.1 million DNA variants, encompassing 12.3 Mb.

- 3,213,401 single nucleotide polymorphisms (SNPs), - 53,823 block substitutions (2–206 bp), - 292,102 heterozygous insertion/deletion events (indels)(1–571 bp), - 559,473 homozygous indels (1–82,711 bp), - 90 inversions, - Plus segmental duplications and copy number variations.

Non-SNP DNA variation accounts for 22% of all events, however they involve 74% of all variant bases. This suggests an important role for non-SNP genetic alterations in defining the diploid genome structure.

Moreover, 44% of genes were heterozygous for one or more variants.

Importance of SNPs and other variants

Study Genetic variation in diverse populations in any species to understand evolutionary origins and history, estimate population size, breeding structure, or life-history characters Migration within and between sub-populations Understand evolutionary basis for maintenance of

genetic variation and speciation. Applications

Genetic association of traits Effects on gene expression (e.g., synonymous vs

nonsynonymous / TF binding sites) DNA finger printing or sample tracking

Fine Mapping with SNP Markers

Advantages of SNPs as genetic markersas compared to microsatellites.

•High abundance

•Distribution throughout the genome

•Ease of genotyping

•Improved accuracy

•Availability of high throughput

multiplex genotyping platforms

SNP Discovery - Sanger sequencing (EST)

SNP Discovery - Diploids (heterozygous loci)

SNP-PHAGE (Software package)

Important steps are Primer development Primer testing Sequencing Base calling, Sequence assembly Polymorphisms analysis Haplotype analysis GenBank submission of

confirmed polymorphisms

Primers

Sequence Variation

5’ amplicons

3’ amplicons

SNP Pipeline for Haplotype Analysis and GEnbank (dbSNP) submissions.

Application of Machine Learning in SNP Discovery

Inputs

Machine LearningProgram

Planning and Reasoning

Outputs

Model (Tree / Rules)

Model(Tree /Rules)

Inputs

Outputs

Training mode Testing/Prediction mode

Steps:•Parameter Selection •Parameter Optimization •Testing•Implementation.

Results:

Achieved substantial improvement in the accuracies as compared to using only polybayes or polyphred.

Objective: Reduce human intervention by using expert annotated datasetfor training a Machine learning (ML) program and use it to differentiate good/bad polymorphisms

SNP Discovery using next generation sequencers

Short sequences 23-35 bp long at a fraction of cost. Reduced Representation Sequencing

Digest genomic DNA with restriction enzyme Screen based on in silico digestion

Size select based on Repetitive DNA Number of fragments Sequencing platform

Allows “targeted” deep sequencing of pools of DNA Randomly distributed

Cost / Mb

ABI $880

454 $160

Solexa $5

SNP Discovery - Bioinformatics

Strategies to maximize performance High quality score stringencies

For each read At base for putative SNP

Require single map location of a 23-bp “tag” (and 4-bp restriction site)

Allow only one single base pair difference match for a putative SNP

Reduces repeat content Reduces gene family/paralog false positives

Require 2 copies of each allele – assembly can count as 1

Predicted & Observed Minor Allele Frequency

Population Genetics

Population genetics is the study of the allele frequency distribution and change under the influence of the four evolutionary forces: natural selection, genetic drift, mutation and gene flow. It attempts to explain phenomena as adaptation and speciation.(www.wikipedia.org)

X

Variation

Population Genetics

Neutral theory : Rate at which new genetic variants are formed is equal to the loss of genetic diversity due to drift.

C/T C/C T/T

Genotypes : CT, CC, TT

Alleles : C and T

Genotyping of a population of 1000 individuals for a SNP resulted in 100, 500 and 400 genotypes for CC, CT and TT respectively

Genotype Frequencies: CC (0.1), CT (0.5) and TT(0.4)Allele Frequencies: C (p) = (200+500)/2000 = 0.35 (minor allele -- MAF)

T (q) = (500+800)/2000 = 0.65 (major allele)Hardy-Weinberg Equilibrium: Expected genotype frequencies are p2, 2pq and q2 (122, 422 and 455)

HWE Deviations: Drift, Selection, Admixture etc.,

Useful to partition genetic variation into components:within populationsbetween populationsamong populations

Sewall Wright’s Fixation index (Fst is a useful index of genetic differentiation and comparison of overall effect of population substructure.

Measures reduction in heterozygosity (H) expected with non-random mating at any one level of population hierarchy relative to another more inclusive hierarchical level.

Fst = (HTotal - Hsubpop)/HTotal

Fst ranges between minimum of 0 and maximum of 1:

= 0 no genetic differentiation

<< 0.5 little genetic differentiation

>> 0.5 moderate to great genetic differentiation

= 1.0 populations fixed for different alleles

Fst

Genotype – Phenotype Association (Significance of Haplotypes)

Haplotype inference

The solution to the haplotype phasing problem is not straightforward due to resolution ambiguity

Computational and statistical algorithms for addressing ambiguity in Haplotype Phasing:

1) parsimony

2) phylogeny

3) maximum-likelihood

4) Bayesian inference

Linkage disequilibrium (LD)

Non-random association of alleles at two or more loci, not necessary in the same chromosome.

LD is generally caused by interactions between genes; genetic linkage and the rate of recombination; random drift or non-random mating; and population structure.

B1 B2 Total

A1 p11 = p1 q1 + D p12 = p1 q2 - D p1

A2 p21 = p2 q1 - D p22 = p2 q2 + D p2

Total q1 q2 1

Let A and B be two loci segregating two alleles each; a1 and a2 with frequencies p1 and p2 in A, and b1 and b2 with frequencies q1 and q2 in B.

A

B

D = p11 - p1q1

D depends on the allele frequencies at A and B.

D’ a scaled version of D:

Linkage disequilibrium (cont)

Dmin(p1q1 , p2q2)

D’ =

If D < 0

Dmin(p1q2 , p2q1)

If D > 0

Squared correlation coefficient

Linkage disequilibrium (cont)

r2 = D2

p1p2q1q2

* The measure preferred by population geneticists

* Is independent of of allele frequencies

* Ranges between 0 and 1

* r2 = 1 implies the markers provide exactly the same information

* r2 = 0 when they are in perfect equilibrium

Visualizing LD

2.4 Linkage disequilibrium (cont)

2.4 Linkage disequilibrium (cont)

Visualizing LD