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Genomic resources and their influence on the detection of the signal of positive selection in genome scans
Author(s) -
Manel S.,
Perrier C.,
Pratlong M.,
AbiRached L.,
Paganini J.,
Pontarotti P.,
Aurelle D.
Publication year - 2016
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/mec.13468
Subject(s) - genome , biology , natural selection , computational biology , genomics , selection (genetic algorithm) , imputation (statistics) , population , genetics , reference genome , gene , computer science , artificial intelligence , machine learning , missing data , demography , sociology
Genome scans represent powerful approaches to investigate the action of natural selection on the genetic variation of natural populations and to better understand local adaptation. This is very useful, for example, in the field of conservation biology and evolutionary biology. Thanks to Next Generation Sequencing, genomic resources are growing exponentially, improving genome scan analyses in non‐model species. Thousands of SNP s called using Reduced Representation Sequencing are increasingly used in genome scans. Besides, genome sequences are also becoming increasingly available, allowing better processing of short‐read data, offering physical localization of variants, and improving haplotype reconstruction and data imputation. Ultimately, genome sequences are also becoming the raw material for selection inferences. Here, we discuss how the increasing availability of such genomic resources, notably genome sequences, influences the detection of signals of selection. Mainly, increasing data density and having the information of physical linkage data expand genome scans by (i) improving the overall quality of the data, (ii) helping the reconstruction of demographic history for the population studied to decrease false‐positive rates and (iii) improving the statistical power of methods to detect the signal of selection. Of particular importance, the availability of a high‐quality reference genome can improve the detection of the signal of selection by (i) allowing matching the potential candidate loci to linked coding regions under selection, (ii) rapidly moving the investigation to the gene and function and (iii) ensuring that the highly variable regions of the genomes that include functional genes are also investigated. For all those reasons, using reference genomes in genome scan analyses is highly recommended.