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Genome-wide association for milk urea concentration in Dual-Purpose Belgian Blue cows.
Atashi, Hadi; Chen, Yansen; Wilmot, Hélène; Vanderick, Sylvie; Hubin, Xavier; Gengler, Nicolas.
Affiliation
  • Atashi H; TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
  • Chen Y; Department of Animal Science, Shiraz University, Shiraz, Iran.
  • Wilmot H; TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
  • Vanderick S; TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
  • Hubin X; National Fund for Scientific Research (F.R.S.-FNRS), Brussels, Belgium.
  • Gengler N; TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
J Anim Breed Genet ; 139(6): 710-722, 2022 Nov.
Article in En | MEDLINE | ID: mdl-35834354
The objectives of this study were to estimate genetic parameters and identify genomic regions associated with milk urea concentration (MU) in Dual-Purpose Belgian Blue (DPBB) cows. The data were 29,693 test-day records of milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (FP), protein percentage (PP) and MU collected between 2014 and 2020 on 2498 first parity cows (16,935 test-day records) and 1939 second-parity cows (12,758 test-day records) from 49 herds in the Walloon Region of Belgium. Data of 28,266 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA), on 1699 animals (639 males and 1060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method using a single chain of 100,000 iterations after a burn-in period of 20,000. SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by windows of 25 consecutive SNPs (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. The mean (SD) of MU was 22.89 (10.07) and 22.35 (10.07) mg/dl for first and second parity, respectively. The mean (SD) heritability estimates for daily MU were 0.18 (0.01) and 0.22 (0.02), for first and second parity, respectively. The mean (SD) genetic correlations between daily MU and MY, FY, PY, FP and PP were -0.05 (0.09), -0.07 (0.11), -0.03 (0.13), -0.05 (0.08) and -0.03 (0.11) for first parity, respectively. The corresponding values estimated for second parity were 0.02 (0.10), -0.02 (0.09), 0.02 (0.08), -0.08 (0.06) and -0.05 (0.05). The genome-wide association analyses identified three genomic regions (BTA2, BTA3 and BTA13) associated with MU. The identified regions showed contrasting results between parities and among different stages within each parity. This suggests that different groups of candidate genes underlie the phenotypic expression of MU between parities and among different lactation stages within a parity. The results of this study can be used for future implementation and use of genomic evaluation to reduce MU in DPBB cows.
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Full text: 1 Database: MEDLINE Main subject: Milk / Genome-Wide Association Study Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals / Pregnancy Country/Region as subject: Europa Language: En Journal: J Anim Breed Genet Journal subject: GENETICA / MEDICINA VETERINARIA Year: 2022 Type: Article Affiliation country: Belgium

Full text: 1 Database: MEDLINE Main subject: Milk / Genome-Wide Association Study Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals / Pregnancy Country/Region as subject: Europa Language: En Journal: J Anim Breed Genet Journal subject: GENETICA / MEDICINA VETERINARIA Year: 2022 Type: Article Affiliation country: Belgium