Release 56
(Apr 24, 2025)

Reference # 27289149 Details:

Authors:Zhang Q, Guldbrandtsen B, Thomasen JR, Lund MS, Sahana G (Contact: qianqian.zhang@mbg.au.dk)
Affiliation:Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, DK-8830 Tjele, Denmark
Title:Genome-wide association study for longevity with whole-genome sequencing in 3 cattle breeds
Journal:Journal of Dairy Science, 2016, 99(9): 7289-98 DOI: S0022-0302(16)30348-4
Abstract:

Longevity is an important economic trait in dairy production. Improvements in longevity could increase the average number of lactations per cow, thereby affecting the profitability of the dairy cattle industry. Improved longevity for cows reduces the replacement cost of stock and enables animals to achieve the highest production period. Moreover, longevity is an indirect indicator of animal welfare. Using whole-genome sequencing variants in 3 dairy cattle breeds, we carried out an association study and identified 7 genomic regions in Holstein and 5 regions in Red Dairy Cattle that were associated with longevity. Meta-analyses of 3 breeds revealed 2 significant genomic regions, located on chromosomes 6 (META-CHR6-88MB) and 18 (META-CHR18-58MB). META-CHR6-88MB overlaps with 2 known genes: neuropeptide G-protein coupled receptor (NPFFR2; 89,052,210-89,059,348 bp) and vitamin D-binding protein precursor (GC; 88,695,940-88,739,180 bp). The NPFFR2 gene was previously identified as a candidate gene for mastitis resistance. META-CHR18-58MB overlaps with zinc finger protein 717 (ZNF717; 58,130,465-58,141,877 bp) and zinc finger protein 613 (ZNF613; 58,115,782-58,117,110 bp), which have been associated with calving difficulties. Information on longevity-associated genomic regions could be used to find causal genes/variants influencing longevity and exploited to improve the reliability of genomic prediction.

Links:   PubMed | List Data  

 

 

© 2003-2025: USA · USDA · NRPSP8 · Program to Accelerate Animal Genomics Applications. Contact: Bioinformatics Team