Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation
Year: 2018
Type: article
Abstract: Domestication and selective breeding has resulted in over 1000 extant cattle breeds. Many of these breeds do not excel in important traits but are adapted to local environments. These adaptations are a valuable source of genetic material for efforts to improve commercial breeds. As a step toward this goal we identified candidate regions to be under selection in genomes of nine Russian native cattle breeds adapted to survive in harsh climates. After comparing our data to other breeds of European and Asian origins we found known and novel candidate genes that could potentially be related to domestication, economically important traits and environmental adaptations in cattle. The Russian cattle breed genomes contained regions under putative selection with genes that may be related to adaptations to harsh environments (e.g., AQP5, RAD50, and RETREG1). We found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., DGAT1, ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2). Our data point to candidate genes which should be included in future studies attempting to identify genes to improve the extant breeds and facilitate generation of commercial breeds that fit better into the environments of Russia and other countries with similar climates.
Source: Scientific Reports
Institutions: Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, University of Glasgow, La Trobe University, Agriculture Victoria, AgriBio, University of Missouri, Siberian Research Institute of Animal Husbandry, Yakut Scientific Research Institute of Agriculture, University of London, Royal Veterinary College
Language: English
Subfield: Genetics
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $2,690
Funder: Russian Science Foundation
Award: G3861021016
OpenAlex ID: W2888347958
