Genome wide association study identifies novel candidate genes for growth and body conformation traits in goats.
Sci Rep
; 12(1): 9891, 2022 06 14.
Article
em En
| MEDLINE
| ID: mdl-35701479
ABSTRACT
Pakistan is third largest country in term of goat population with distinct characteristics of breeds and estimated population of 78.2 million. Punjab province has 37% of country's total population with seven important documented goat breeds namely Beetal, Daira Din Pannah, Nachi, Barbari, Teddi, Pahari and Pothwari. There is paucity of literature on GWAS for economically important traits i.e., body weight and morphometric measurements. Therefore, we performed GWAS using 50 K SNP Chip for growth in term of age adjusted body weight and morphometric measurements in order to identify genomic regions influencing these traits among Punjab goat breeds. Blood samples were collected from 879 unrelated animals of seven goat breeds along with data for body weight and morphometric measurements including body length, body height, pubic bone length, heart girth and chest length. Genomic DNA was extracted and genotyped using 50 K SNP bead chip. Association of genotypic data with the phenotypic data was performed using Plink 1.9 software. Linear mixed model was used for the association study. Genes were annotated from Capra hircus genome using assembly ARS1. We have identified a number of highly significant SNPs and respective candidate genes associated with growth and body conformation traits. The functional aspects of these candidate genes suggested their potential role in body growth. Moreover, pleiotropic effects were observed for some SNPs for body weight and conformation traits. The results of current study contributed to a better understanding of genes influencing growth and body conformation traits in goat.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Cabras
/
Estudo de Associação Genômica Ampla
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
Idioma:
En
Revista:
Sci Rep
Ano de publicação:
2022
Tipo de documento:
Article