Literature DB >> 31866366

Patterns of Genetic Variability in Genomic Regions with Low Rates of Recombination.

Hannes Becher1, Benjamin C Jackson2, Brian Charlesworth2.   

Abstract

The amount of DNA sequence variability in a genomic region is often positively correlated with its rate of crossing over (CO) [1-3]. This pattern is caused by selection acting on linked sites, which reduces genetic variability and biases the frequency distribution of segregating variants toward more rare variants than are expected without selection (skew). These effects may involve the spread of beneficial mutations (selective sweeps [SSWs]), the elimination of deleterious mutations (background selection [BGS]), or both, and are expected to be stronger with lower CO rates [1-3]. However, in a recent study of human populations, the skew was reduced in the lowest CO regions compared with regions with somewhat higher CO rates [4]. A low skew in very low CO regions, compared with theoretical predictions, is seen in the population genomic studies of Drosophila simulans described here and in other Drosophila species. Here, we propose an explanation for lower than expected skew in low CO regions, and validate it using computer simulations; explanations for higher skew with higher CO rates, as in D. simulans, will be explored elsewhere. Partially recessive, linked deleterious mutations can increase neutral variability when the product of the effective population size (Ne) and the selection coefficient against homozygous carriers of mutations (s) is ≤1, i.e., there is associative overdominance (AOD) rather than BGS [5]. AOD can operate in low CO regions, producing a lower skew than in its absence. This opens up a new perspective on how selection affects patterns of variability at linked sites.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Drosophila simulans; associative overdominance; crossing over; genetic diversity; no-crossover region; site-frequency spectrum; skew

Mesh:

Year:  2019        PMID: 31866366     DOI: 10.1016/j.cub.2019.10.047

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


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