» Articles » PMID: 26350629

Using the Variability of Linkage Disequilibrium Between Subpopulations to Infer Sweeps and Epistatic Selection in a Diverse Panel of Chickens

Overview
Specialty Genetics
Date 2015 Sep 10
PMID 26350629
Citations 7
Authors
Affiliations
Soon will be listed here.
Abstract

A whole-genome scan for identifying selection acting on pairs of linked loci is proposed and implemented. The scan is based on , one of Ohta's 1982 measures of between-population linkage disequilibrium (LD). An approximate empirical null distribution for the statistic is suggested. Although the partitioning of LD into between-population components was originally used to investigate epistatic selection, we demonstrate that values of may also be influenced by single-locus selective sweeps with linkage but no epistasis. The proposed scan is implemented in a diverse panel of chickens including 72 distinct breeds genotyped at 538 298 single-nucleotide polymorphisms. In all, 1723 locus pairs are identified as putatively corresponding to a selective sweep or epistatic selection. These pairs of loci generally cluster to form overlapping or neighboring signals of selection. Known variants that were expected to have been under selection in the panel are identified, as well as an assortment of novel regions that have putatively been under selection in chickens. Notably, a promising pair of genes located 8 MB apart on chromosome 9 are identified based on as demonstrating strong evidence of dispersive epistatic selection between populations.

Citing Articles

Large-scale genome-wide SNP analysis reveals the rugged (and ragged) landscape of global ancestry, phylogeny, and demographic history in chicken breeds.

Dementieva N, Shcherbakov Y, Stanishevskaya O, Vakhrameev A, Larkina T, Dysin A J Zhejiang Univ Sci B. 2024; 25(4):324-340.

PMID: 38584094 PMC: 11009443. DOI: 10.1631/jzus.B2300443.


Parent-offspring genotyped trios unravelling genomic regions with gametic and genotypic epistatic transmission bias on the cattle genome.

Id-Lahoucine S, Casellas J, Miglior F, Schenkel F, Canovas A Front Genet. 2023; 14:1132796.

PMID: 37091801 PMC: 10117652. DOI: 10.3389/fgene.2023.1132796.


Complex fitness landscape shapes variation in a hyperpolymorphic species.

Stolyarova A, Neretina T, Zvyagina E, Fedotova A, Kondrashov A, Bazykin G Elife. 2022; 11.

PMID: 35532122 PMC: 9187340. DOI: 10.7554/eLife.76073.


Finding Hybrid Incompatibilities Using Genome Sequences from Hybrid Populations.

Blanckaert A, Payseur B Mol Biol Evol. 2021; 38(10):4616-4627.

PMID: 34097068 PMC: 8476132. DOI: 10.1093/molbev/msab168.


Tracing the footprints of a moving hybrid zone under a demographic history of speciation with gene flow.

Menon M, Landguth E, Leal-Saenz A, Bagley J, Schoettle A, Wehenkel C Evol Appl. 2020; 13(1):195-209.

PMID: 31892952 PMC: 6935588. DOI: 10.1111/eva.12795.


References
1.
Smith J, Haigh J . The hitch-hiking effect of a favourable gene. Genet Res. 1974; 23(1):23-35. View

2.
Hirsch C, Flint-Garcia S, Beissinger T, Eichten S, Deshpande S, Barry K . Insights into the effects of long-term artificial selection on seed size in maize. Genetics. 2014; 198(1):409-21. PMC: 4174951. DOI: 10.1534/genetics.114.167155. View

3.
Akey J . Constructing genomic maps of positive selection in humans: where do we go from here?. Genome Res. 2009; 19(5):711-22. PMC: 3647533. DOI: 10.1101/gr.086652.108. View

4.
Wisser R, Murray S, Kolkman J, Ceballos H, Nelson R . Selection mapping of loci for quantitative disease resistance in a diverse maize population. Genetics. 2008; 180(1):583-99. PMC: 2535707. DOI: 10.1534/genetics.108.090118. View

5.
Nagylaki T . The evolution of multilocus systems under weak selection. Genetics. 1993; 134(2):627-47. PMC: 1205503. DOI: 10.1093/genetics/134.2.627. View