Abstract
High-throughput pooled resequencing offers significant potential for whole genome population sequencing. However, its main drawback is the loss of haplotype information. In order to regain some of this information, we present LDx, a computational tool for estimating linkage disequilibrium (LD) from pooled resequencing data. LDx uses an approximate maximum likelihood approach to estimate LD (r2) between pairs of SNPs that can be observed within and among single reads. LDx also reports r2 estimates derived solely from observed genotype counts. We demonstrate that the LDx estimates are highly correlated with r2 estimated from individually resequenced strains. We discuss the performance of LDx using more stringent quality conditions and infer via simulation the degree to which performance can improve based on read depth. Finally we demonstrate two possible uses of LDx with real and simulated pooled resequencing data. First, we use LDx to infer genomewide patterns of decay of LD with physical distance in D. melanogaster population resequencing data. Second, we demonstrate that r2 estimates from LDx are capable of distinguishing alternative demographic models representing plausible demographic histories of D. melanogaster.
Highlights
Linkage disequilibrium (LD) is a measure of the association between alleles at two loci encapsulating how often these alleles are observed together
That our ability to estimate LD accurately between any two specific points is low even at reasonably high sequencing depths and even if they are physically close to each other, because the number of reads that overlap any two particular SNPs is much lower than the coverage at any one specific SNP (Fig. 2B)
Certain conditions make the extraction of useful LD information from pooled data very difficult
Summary
Linkage disequilibrium (LD) is a measure of the association between alleles at two loci encapsulating how often these alleles are observed together. Measurement of LD fundamentally requires knowledge of multi-locus haplotype frequencies within a species and these frequencies have been traditionally obtained through direct observation of haplotypes or statistical inference of haplotypes from unphased genotype data [4,5]. While these approaches are feasible for single locus studies, they can become logistically and computationally difficult when applied genomewide. We present a simple and cost effective method to directly measure short-scale LD genomewide using pooled next-generation resequencing data without any prior knowledge of genotype frequencies or of the haplotypes present in the population. Pooled resequencing is a highly accurate method to estimate SNP [9,10,11,12,13,14,15,16] frequencies and has been used to estimate haplotype frequencies from pooled samples when haplotypes are known a priori [17]
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