2020
DOI: 10.1016/j.livsci.2020.104257
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Selection signatures in livestock genome: A review of concepts, approaches and applications

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Cited by 87 publications
(68 citation statements)
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“…In general, the various approaches each detect different panels of genes with only little overlap, indicating for all methods a high frequency of false negatives. At the same time, all methods are prone to delivering false positives, further complicating the interpretation ( Utsunomiya et al 2015 ; Saravanan et al 2020 ). On the other hand, our large WGS data set allows to identify candidate causative mutations, at least in coding sequences but also in plausible miRNA binding sites, and to test their correlation with the breed-dependent phenotypes.…”
Section: Discussionmentioning
confidence: 99%
“…In general, the various approaches each detect different panels of genes with only little overlap, indicating for all methods a high frequency of false negatives. At the same time, all methods are prone to delivering false positives, further complicating the interpretation ( Utsunomiya et al 2015 ; Saravanan et al 2020 ). On the other hand, our large WGS data set allows to identify candidate causative mutations, at least in coding sequences but also in plausible miRNA binding sites, and to test their correlation with the breed-dependent phenotypes.…”
Section: Discussionmentioning
confidence: 99%
“…Fay and Wu statistics [177], in contrast, assess the relationship between ancestral and derived alleles, which enables both positive and negative recent selection occurring in medium-to high-frequency alleles to be detected. However, knowledge of ancestral alleles is necessary to apply the method [178]. Various approaches have been used to assess positive and negative selection in populations.…”
Section: Selection Signaturesmentioning
confidence: 99%
“…The increased LD within parts of the genome indicates a reduced recombination rate, likely because of an occurrence of a beneficial mutation. The LD-based selection signature detection methods are especially useful to detect variants under partial or soft selective sweep (Saravanan et al, 2020). The two most important LD based methods used in this context are the EHH (Sabeti et al, 2002) and its derived method of iHS (Voight et al, 2006).…”
Section: Linkage Disequilibriummentioning
confidence: 99%