Genetic improvement of economic traits in Murrah buffalo using significant SNPs from genome-wide association study

GWAS helps to identify QTL and candidate genes of specific traits. Buffalo breeding has primarily focused on milk production, but its negative correlation with reproduction traits resulted in unfavorable decline of reproductive performance among buffaloes. A genome wide scan was performed on a total...

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Published inTropical animal health and production Vol. 55; no. 3; p. 199
Main Authors George, Linda, Alex, Rani, Sukhija, Nidhi, Jaglan, Komal, Vohra, Vikas, Kumar, Ravi, Verma, Archana
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.06.2023
Springer Nature B.V
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Summary:GWAS helps to identify QTL and candidate genes of specific traits. Buffalo breeding has primarily focused on milk production, but its negative correlation with reproduction traits resulted in unfavorable decline of reproductive performance among buffaloes. A genome wide scan was performed on a total of 120 Murrah buffaloes genotyped by ddRAD sequencing for 13 traits related to female fertility, production, and growth. The identified 25 significant single nucleotide polymorphisms (SNPs) ( P <1×10 6 ) are associated with age at first calving (AFC), age at first service (AFS), period from calving to 1 st Artifical Insemination (AI), service period (SP) and 6 month body weight (6M). Fifteen genetic variants overlapped with different QTL regions of reported studies. Among the associated loci, outstanding candidate genes for fertility, including AQP1, TRNAE-CUC, NRIP1, CPNE4, and VOPP1, have effect in different fertility traits. AQP1 gene is expressed in ovulatory phase and various stages of pregnancy. TRNAE-CUC gene is associated with AFC and number . of calvings after 4 years of age. Glycogen content–associated gene CPNE4 regulates muscle glycogen and is upregulated during early pregnancy. NRIP1 generegulates ovulation, corpus luteum at pregnancy, and mammary gland development. The objective is to identify potential genomic regions and genetic variants associated with economic traits and to select the most significant SNP which have positive effect on all the traits.
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ISSN:0049-4747
1573-7438
DOI:10.1007/s11250-023-03606-3