A genomic map of the effects of linked selection in Drosophila
Eyal Elyashiv, Shmuel Sattath, Tina T. Hu, Alon Strustovsky, Graham, McVicker, Peter Andolfatto, Graham Coop, Guy Sella

TL;DR
This study introduces a novel method to jointly infer the effects of background selection and selective sweeps on genetic diversity in Drosophila, revealing pervasive linked selection influences across the genome.
Contribution
The paper presents the first joint inference approach combining functional annotations, genetic maps, and diversity data to estimate linked selection parameters genome-wide.
Findings
High fraction of beneficial substitutions in proteins and UTRs
Evidence for widespread selective sweeps in untranslated regions
Linked selection significantly reduces diversity and increases variance
Abstract
Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of 'linked selection' on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and learning about the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a neutral site is polymorphic given local annotations, substitution patterns, and recombination rates. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter…
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