Genomic Diversity Profiling and Breed-Specific Evolutionary Signatures of Selection in Arunachali Yak.
Genes (Basel)
; 13(2)2022 01 28.
Article
en En
| MEDLINE
| ID: mdl-35205299
ABSTRACT
Arunachali yak, the only registered yak breed of India, is crucial for the economic sustainability of pastoralist Monpa community. This study intended to determine the genomic diversity and to identify signatures of selection in the breed. Previously available double digest restriction-site associated DNA (ddRAD) sequencing data of Arunachali yak animals was processed and 99,919 SNPs were considered for further analysis. The genomic diversity profiled based on nucleotide diversity, π (π = 0.041 in 200 bp windows), effective population size, Ne (Ne = 83) and Runs of homozygosity (ROH) (predominance of shorter length ROHs) was found to be optimum. Subsequently, 207 regions were identified to be under selective sweeps through de-correlated composite of multiple signals (DCMS) statistic which combined three individual test statistics viz. π, Tajima's D and |iHS| in non-overlapping 100 kb windows. Mapping of these regions revealed 611 protein-coding genes including KIT, KITLG, CDH12, FGG, FGA, FGB, PDGFRA, PEAR1, STXBP3, olfactory receptor genes (OR5K3, OR5H6 and OR1E1) and taste receptor genes (TAS2R1, TAS2R3 and TAS2R4). Functional annotation highlighted that biological processes like platelet aggregation and sensory perception were the most overrepresented and the associated regions could be considered as breed-specific signatures of selection in Arunachali yak. These findings point towards evolutionary role of natural selection in environmental adaptation of Arunachali yak population and provide useful insights for pursuing genome-wide association studies in future.
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Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Selección Genética
/
Estudio de Asociación del Genoma Completo
Tipo de estudio:
Prognostic_studies
Límite:
Animals
Idioma:
En
Revista:
Genes (Basel)
Año:
2022
Tipo del documento:
Article
País de afiliación:
India