Refining the Use of Linkage Disequilibrium as a Robust Signature of Selective Sweeps

Abstract

During a selective sweep, characteristic patterns of linkage disequilibrium can arise in the genomic region surrounding a selected locus. These have been used to infer past selective sweeps. However, the recombination rate is known to vary substantially along the genome for many species. We here investigate the effectiveness of current (Kelly's Z nS and v max ) and novel statistics at inferring hard selective sweeps based on linkage disequilibrium distortions under different conditions, including a human-realistic demographic model and recombination rate variation. When the recombination rate is constant, Kelly's Z nS offers high power, but is outperformed by a novel statistic that we test, which we call Z a : We also find this statistic to be effective at detecting sweeps from standing variation. When recombination rate fluctuations are included, there is a considerable reduction in power for all linkage disequilibrium-based statistics. However, this can largely be reversed by appropriately controlling for expected linkage disequilibrium using a genetic map. To further test these different methods, we perform selection scans on well-characterized HapMap data, finding that all three statistics-v max ; Kelly's Z nS ; and Z a -are able to replicate signals at regions previously identified as selection candidates based on population differentiation or the site frequency spectrum. While v max replicates most candidates when recombination map data are not available, the Z nS and Z a statistics are more successful when recombination rate variation is controlled for. Given both this and their higher power in simulations of selective sweeps, these statistics are preferred when information on local recombination rate variation is available.KEYWORDS linkage disequilibrium; positive selection; recombination rate; genetic map G ENOME-WIDE selection scans now form part of the standard repertoire of techniques through which to probe the evolutionary past of a population. These attempt to identify genomic regions showing evidence of nonneutral evolution by iteratively calculating a test statistic at different locations for a sample of genetic data. As the availability of genetic data and computational power has increased, so too have the number of scans performed and the range of statistics used. In the case of human genetics, thousands of putative selection signals have been suggested (Akey 2009). For the vast majority of these, it is unclear what phenotypic association may have allowed selection to operate, and a relatively small number of signals are replicated between studies.Given the large number of hypotheses tested in genome scans for selection, many signals are likely to be false positives (Kelley et al. 2006;Akey 2009;Nei et al. 2010). This concern is compounded by systematic biases related to ascertainment or data quality (Mallick et al. 2009). Distinguishing true signatures of selection is challenging, requiring a multifaceted approach (Barrett and Hoekstra 2011), but improving statistics used to infer se...

Understanding the disease genome: gene essentiality and the interplay of selection, recombination and mutation

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Population structure and local selection yield high genomic variation in Mimulus guttatus

“…Third, we test the prediction that loci under local selection should exhibit distinct patterns of linkage disequilibria from the rest of the genome (Strobeck ; Charlesworth ; Storz & Kelly ; Jacobs et al . ). Finally, theory predicts that population genetic signatures of selection should be most pronounced when recombination is reduced (Kaplan et al .…”

“…Loci under local selection should have lower intrapopulation nucleotide diversity (p), but also higher F ST and elevated absolute divergence between populations (Dxy), if gene flow occurs in other regions of the genome (Lewontin & Krakauer 1973;Beaumont & Nichols 1996;Charlesworth et al 1997;Cruickshank & Hahn 2014). Third, we test the prediction that loci under local selection should exhibit distinct patterns of linkage disequilibria from the rest of the genome (Strobeck 1983;Charlesworth 2006;Storz & Kelly 2008;Jacobs et al 2016). Finally, theory predicts that population genetic signatures of selection should be most pronounced when recombination is reduced (Kaplan et al 1989;Begun & Aquadro 1992;Charlesworth et al 1993).…”

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