ArticleFrontiers in genetics2011
Tests of selection in pooled case-control data: an empirical study.
Article in Frontiers in genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Whole genome sequencing of Ethiopian highlanders reveals conserved hypoxia tolerance genes.Genome biology · 2014Article
- Whole-genome sequencing uncovers the genetic basis of chronic mountain sickness in Andean highlanders.American journal of human genetics · 2013Article
- Learning natural selection from the site frequency spectrum.Genetics · 2013Article
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Authors and funding
4 authors.
Funding
Abstract
For smaller organisms with faster breeding cycles, artificial selection can be used to create sub-populations with different phenotypic traits. Genetic tests can be employed to identify the causal markers for the phenotypes, as a precursor to engineering strains with a combination of traits. Traditional approaches involve analyzing crosses of inbred strains to test for co-segregation with genetic markers. Here we take advantage of cheaper next generation sequencing techniques to identify genetic signatures of adaptation to the selection constraints. Obtaining individual sequencing data is often unrealistic due to cost and sample issues, so we focus on pooled genomic data. We explore a series of statistical tests for selection using pooled case (under selection) and control populations. The tests generally capture skews in the scaled frequency spectrum of alleles in a region, which are indicative of a selective sweep. Extensive simulations are used to show that these approaches work well for a wide range of population divergence times and strong selective pressures. Control vs control simulations are used to determine an empirical False Positive Rate, and regions under selection are determined using a 1% FPR level. We show that pooling does not have a significant impact on statistical power. The tests are also robust to reasonable variations in several different parameters, including window size, base-calling error rate, and sequencing coverage. We then demonstrate the viability (and the challenges) of one of these methods in two independent Drosophila populations (Drosophila melanogaster) bred under selection for hypoxia and accelerated development, respectively. Testing for extreme hypoxia tolerance showed clear signals of selection, pointing to loci that are important for hypoxia adaptation. Overall, we outline a strategy for finding regions under selection using pooled sequences, then devise optimal tests for that strategy. The approaches show promise for detecting selection, even several generations after fixation of the beneficial allele has occurred.
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