Transcript 0 - dimacs
Recombination based population genomics
Jaume Bertranpetit Marta Melé Francesc Calafell Asif Javed Laxmi Parida
Recall: IRiS
Identification of Recombinations in Sequences
IRiS is a computational method developed with biological insight detects evidence of historical recombinations minimizes number of recombinations in Ancestral Recombinational Graph (ARG)
Recotypes
Two chromosomes share a recombination if the junction is co-inherited.
mutation edge recombination edge extant sequence
Recotypes
Two chromosomes share a recombination if the junction is co-inherited.
a r1 b
Recotypes
Two chromosomes share a recombination if the junction is co-inherited.
r2 c a r1 b
Recotypes
Two chromosomes share a recombination if the junction is co-inherited.
r1 r2 … a b c …
1 1 0 0 0 1
r2 c a r1 b
Validity of inferred recombinations
Comparison with sperm typing Computer simulated recombinations
in vitro
Jeffreys et al. 2005 80 UK semen donor of North European origin - Sperm typing - LDhat and Phase (200 SNPs) HapMap 2 CEU population similar SNP density
Chr 1 near MS32 minisatellite
sperm typing LDhat Phase IRiS
in silico
HapMap 3 X chromosome data
•Select 2 chromosomes at random.
•Pick a random breakpoint.
•Create a new chromosome.
•Check if it is unique, add to the dataset.
•Run IRiS on the dataset to see if the breakpoint is detected.
Chromosomes
in silico
HapMap 3 X chromosome data
•Select 2 chromosomes at random.
•Pick a random breakpoint.
•Create a new chromosome.
•Check if it is unique, add to the dataset.
•Run IRiS on the dataset to see if the breakpoint is detected.
Chromosomes
in silico
HapMap 3 X chromosome data
•Select 2 chromosomes at random.
•Pick a random breakpoint.
•Create a new chromosome.
•Check if it is unique, add to the dataset.
•Run IRiS on the dataset to see if the breakpoint is detected.
Chromosomes
in silico
HapMap 3 X chromosome data
•Select 2 chromosomes at random.
•Pick a random breakpoint.
•Create a new chromosome.
•Check if it is unique, add to the dataset.
•Run IRiS on the dataset to see if the breakpoint is detected.
Chromosomes
in silico
HapMap 3 X chromosome data
•Select 2 chromosomes at random.
•Pick a random breakpoint.
•Create a new chromosome.
•Check if it is unique, add to the dataset.
•Run IRiS on the dataset to see if the breakpoint is detected.
Chromosomes
in silico
Chromosomes
HapMap 3 X chromosome data
•Select 2 chromosomes at random.
•Pick a random breakpoint.
•Create a new chromosome.
•Check if it is unique, add to the dataset.
•Run IRiS on the dataset to see if the breakpoint is detected.
IRiS
recombination detected?
in silico
Chromosomes
HapMap 3 X chromosome data
•Select 2 chromosomes at random.
•Pick a random breakpoint.
•Create a new chromosome.
•Check if it is unique, add to the dataset.
•Run IRiS on the dataset to see if the breakpoint is detected.
69% recombinations detected All detected recombinations detect the correct sequence No false positives
IRiS
recombination detected?
Recombinomics
Strong population structure Agreement with traditional methods FST vs. recombinational distance More informative than SNPs STRUCTURE PCA
Regions
18 regions selected from HapMap 3 X-chromosome in males (
to avoid phasing errors
) 50 KB away from known CNV and SD (
to avoid genotyping errors
) 50 KB away from genes (
to avoid selection
) at least 80 SNPs
Chromosomes
: LWK( 43 ), MKK ( 88 ), YRI ( 88 ), ASW ( 42 ), GIH ( 42 ), CHB ( 40 ), CHD ( 21 ), JPT( 25 ), MEX( 21 ), CEU ( 74 ), TSI ( 40 )
Analysis
For each region IRiS inferred recotypes for each chromosome 5166 recombinations were inferred 3459 co-occurred in at least two chromosomes
Recombination Chromosome LK1 LK2 : LK43 MK1 : TI40 r1
0 1 1 0 0
r2
1 0 0 1 0
r3
1 1 1 0 0
r4
0 1 0 0 0
r5
0 0 0 1 0
r6
0 0 0 1 1
… r3459
0 0 1 0
Analysis
For each region IRiS inferred recotypes for each chromosome 5166 recombinations were inferred 3459 co-occurred in at least two chromosomes
Recombination Chromosome LK1 LK2 : LK43 MK1 : TI40 r1
0 1 1 0 0
r2
1 0 0 1 0
r3
1 1 1 0 0
r4
0 1 0 0 0
r5
0 0 0 1 0
r6
0 0 0 1 1
… r3459
0 0 1 0
Recotype
Agreement with LDhat
Each point represents a short haplotype segment in HapMap CEU population
Spearman correlation = 0.711
pvalue <10 -30 number of recombinations inferred by IRiS
Agreement with LDhat
Each point represents a short haplotype segment in HapMap CEU population
Spearman correlation = 0.711
pvalue <10 -30 Correlation in hotspots c 2 = 38.39
pvalue<6x10 -10 number of recombinations inferred by IRiS
Recombinational distance between populations
Two populations genetically closer will share a higher number of recombinations
Recombinational distance D AB = 1 R AB R A + R B -R AB Correlation between FST distance and recombinational distance for the 18 region [0.35 – 0.75 ] with pvalues < 0.025
MDS All regions combined stress=6.1%
PCA of population data
Recall recotypes r1 r2 LK1
0 1 1 0
LK2 : LK43 MK1 : TI40
1 0 0 0 1 0
r3
1 1 1 0 0
r4
0 1 0 0 0
r5
0 0 0 1 0
r6
0 0 0 1 1
… r3459
0 0 1 0
PCA of population data
Recall recotypes r1 r2 LK1
0 1 1 0
LK2 : LK43 MK1 : TI40
1 0 0 0 1 0
r3
1 1 1 0 0
r4
0 1 0 0 0
r5
0 0 0 1 0
r6
0 0 0 1 1
… r3459
0 0 1 0
LK MK : TI r1
14 1 0
r2
7 4 1
r3
4 7 7
r4
9 0 1
r5
0 5 0
r6
1 7 0
… r3459
0 24 1
PCA of population data
The first two PCs capture 66.4% of the variance
LK MK : TI r1
14 1 0
r2
7 4 1
r3
4 7 7
r4
9 0 1
r5
0 5 0
r6
1 7 0
… r3459
0 24 1
PCA of recotypes
Recotypes vs. SNPs
Due to ascertainment bias gene diversity does not reflect population structure
results similar to
Conrad 07 Percentage of variance
Across groups Within groups Within populations SNPs 9% 4% 87% Recotypes 6% 1% 93% in agreement with
Lewontin 72
Normalized comparison linearly scaled to [0,1] using 21 samples per population
K=2
from SNPs to haplotypes to recotypes (a
STRUCTURE
comparison
) SNPs haplotypes recotypes
K=3
from SNPs to haplotypes to recotypes (a
STRUCTURE
comparison
) SNPs haplotypes recotypes
K=4
from SNPs to haplotypes to recotypes (a
STRUCTURE
comparison
) SNPs haplotypes recotypes
K=5
from SNPs to haplotypes to recotypes (a
STRUCTURE
comparison
) SNPs haplotypes recotypes
Africa within global genetic variation
Structure k=4
minority African specific component
Avg. Number of recombinations in 21 random chromsomes
Out of Africa hypothesis Founder’s effect
Genetic variation within Africa
Structure k=5
Maasai specific minor component
Subsaharan Maasai are distinct among Africans.
African-American exhibit stronger recombinational affinity with African populations than European populations. ( Parra 98 )
Genetic variation outside Africa
Structure k=5
Avg. Number of recombinations in 21 random chromsomes
Outside Africa, Gujarati and Japanese exhibit the highest and lowest number of recombinations respectively.
Gujarati Indians show intermediate position between Europeans and East Asians.
Venturing outside the X-chromosome
Benefits The bigger picture More regions and hence more information Challenges Higher number of recombinations makes the picture murkier Phasing errors
Regions
81 regions selected from HapMap 3 50 KB away from known CNV and SD (
to avoid genotyping errors
) 50 KB away from genes (
to avoid selection
) at least 200 SNPs 25 samples per population (
each sample has two chromosomes
)
Analysis
For each region IRiS inferred recotypes for each chromosome 34140 recombinations were inferred For each sample the two recotypes were
merged
.
SNPs recotypes PCA plots
Quantifying population structure
PCA and by k nearest neighbors is used to predict population of every sample Perfectly classified Africans classified with errors (
0
,
7
) (
4
,
3
) ASW YRI LKK MKK Non- Africans GIH E. Asian MEX (
3
,
13
) CHB+CHD JPT European CEU (
8
,
13
) TSI Misclassification by (
recotypes
,
SNPs
)
East Asian population
Recotypes are more informative of underlying population structure.
SNPs recotypes PCA plots
in conclusion …
Recotypes
show strong agreement with in silico and in vetro recombination rates estimates are highly informative of the underlying population structure provide a novel approach to study the recombinational dynamics