Identifying and Classifying Shared Selective Sweeps from Multilocus Data

Abstract

Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term H2Tot and H1Tot to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.

A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data

“…Whereas haplotypes are character strings indicating the state of a biallelic SNP as either reference or alternate along a region of one copy of an individual’s genome, MLGs have three possible states for each biallelic SNP—homozygous reference, homozygous alternate, or heterozygous—and half the sample size of phased haplotypes. We found that, as with the transition between phased and unphased data for haplotype homozygosity statistics ( Harris et al 2018 ; Harris and DeGiorgio 2020 ), trends in power for the unphased application of the T statistic were wholly consistent with those of the phased application, for both hard and soft sweeps ( supplementary fig. S15 , Supplementary Material online).…”

“…2011 ; Kern and Schrider 2018 ; Mughal and DeGiorgio 2019 ), or drawing inferences from a posterior distribution by approximate Bayesian computation ( Garud et al. 2015 ; Harris et al 2018 ; Harris and DeGiorgio 2020 ). We demonstrate with simulated data that the T statistic identifies recent hard and soft sweeps and performs especially well for population size expansion models.…”

Contrasting signatures of genomic divergence during sympatric speciation

“… 99 ), and SS- H 12 (ref. 100 )) summary statistics for each subwindow. All summary statistics were normalized by dividing each statistic by its sum across all subwindows.…”

Understanding the Adaptive Evolutionary Histories of South American Ancient and Present-Day Populations via Genomics

“…These methods employ both model-free approaches based on allele frequencies, which can detect shared ancestral selection between a set of populations since they diverged from a closely related outgroup ( Figure 4 B) (ancestral branch statistic (ABS) [ 39 ], the similar levels of exclusively shared differences (LSD) method [ 40 , 41 ], and the model-based 3P-CLR [ 42 ]). A wealth of additional approaches also exist for detecting shared ancestral selection events [ 43 , 44 , 45 , 46 , 47 ]. This collection of methods could potentially be utilized to test ancestral selection in ancient and living indigenous populations that share coastal environments and marine sustenance strategies.…”

“…New methods are also available that directly compare populations without the need of an outgroup. One such approach is SS-H12 [ 47 ], which employs haplotype data. This method has great power to detect shared positive selection events, and excellent accuracy at distinguishing between events that occurred prior to population splits (ancestral selection) and independently in each population after their split (convergent selection).…”