Gene Banks as Reservoirs to Detect Recent Selection: The Example of the Asturiana de los Valles Bovine Breed.

TitleGene Banks as Reservoirs to Detect Recent Selection: The Example of the Asturiana de los Valles Bovine Breed.
Publication TypeJournal Article
Year of Publication2021
AuthorsBoitard, S, Paris, C, Sevane, N, Servin, B, Bazi-Kabbaj, K, Dunner, S
JournalFront Genet
Volume12
Pagination575405
Date Published2021
ISSN1664-8021
Abstract

Gene banks, framed within the efforts for conserving animal genetic resources to ensure the adaptability of livestock production systems to population growth, income, and climate change challenges, have emerged as invaluable resources for biodiversity and scientific research. Allele frequency trajectories over the few last generations contain rich information about the selection history of populations, which cannot be obtained from classical selection scan approaches based on present time data only. Here we apply a new statistical approach taking advantage of genomic time series and a state of the art statistic (nSL) based on present time data to disentangle both old and recent signatures of selection in the Asturiana de los Valles cattle breed. This local Spanish originally multipurpose breed native to Asturias has been selected for beef production over the last few generations. With the use of SNP chip and whole-genome sequencing (WGS) data, we detect candidate regions under selection reflecting the effort of breeders to produce economically valuable beef individuals, e.g., by improving carcass and meat traits with genes such as , , , , , , or , while maintaining the ability to thrive under a semi-intensive production system, with the selection of immune (, , , and ) or olfactory receptor (, , , and ) genes. This kind of information will allow us to take advantage of the invaluable resources provided by gene bank collections from local less competitive breeds, enabling the livestock industry to exploit the different mechanisms fine-tuned by natural and human-driven selection on different populations to improve productivity.

DOI10.3389/fgene.2021.575405
Alternate JournalFront Genet
PubMed ID33633776
PubMed Central IDPMC7901938
dynagen