Abstract :
[en] The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (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. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue cows.
Funding text :
H. Atashi acknowledges the support of the Walloon Government (Service Public de Wallonie – Direction Générale Opérationnelle Agriculture, Ressources Naturelles et Environnement, SPW-DGARNE, Namur, Belgium) for its financial support facilitating his stay in Belgium through the WALLeSmart Project (D31-1392 and D65-1435). H. Wilmot, as a current research fellow, and N. Gengler, as a former senior research associate, acknowledge the support of the Fonds de la Recherche Scientifique–FNRS (Brussels, Belgium). The authors thank the INTERREG VA France-Wallonie-Vlaanderen program and the Walloon Government (Service Public de Wallonie – Direction Générale Opérationnelle Agriculture, Ressources Naturelles et Environnement, SPW-DGARNE, Namur, Belgium) for their financial support through the BlueSter project and previous projects. The authors also acknowledge the technical support by the Walloon Breeders Association (elevéo). The University of Liège–Gembloux Agro-Bio Tech (Liège, Belgium) supported computations through the technical platform Calcul et Modélisation Informatique (CAMI) of the TERRA Teaching and Research Centre, partly supported by the Fonds de la Recherche Scientifique–FNRS under grant no. T.0095.19 (PDR “DEEPSELECT”). Genotyping was facilitated through the support of the Fonds de la Recherche Scientifique–FNRS under grant no. J.0174.18 (CDR “PREDICT-2”). Relevant information supporting the results not presented here is provided in supplemental data ( https://github.com/hadiatashi/milk-fatty-acids-DBBB ). None of the data were deposited in an official repository because they are the property of the breeding organizations, and they are available upon reasonable request. Author contributions were as follows: Hadi Atashi, conceptualization, formal analysis, investigation, methodology, writing the original draft; Yansen Chen, reviewing and editing the draft; Hélène Wilmot, reviewing and editing the draft; Sylvie Vanderick, reviewing and editing the draft; Xavier Hubin, data curation, reviewing and editing the draft; Hélène Soyeurt , data curation, resources, writing, review and editing the draft; Nicolas Gengler, conceptualization, funding acquisition, project administration, resources, supervision, reviewing and editing the draft. The authors have not stated any conflicts of interest.H. Atashi acknowledges the support of the Walloon Government (Service Public de Wallonie – Direction Générale Opérationnelle Agriculture, Ressources Naturelles et Environnement, SPW-DGARNE, Namur, Belgium) for its financial support facilitating his stay in Belgium through the WALLeSmart Project (D31-1392 and D65-1435). H. Wilmot, as a current research fellow, and N. Gengler, as a former senior research associate, acknowledge the support of the Fonds de la Recherche Scientifique–FNRS (Brussels, Belgium). The authors thank the INTERREG VA France-Wallonie-Vlaanderen program and the Walloon Government (Service Public de Wallonie – Direction Générale Opérationnelle Agriculture, Ressources Naturelles et Environnement, SPW-DGARNE, Namur, Belgium) for their financial support through the BlueSter project and previous projects. The authors also acknowledge the technical support by the Walloon Breeders Association (elevéo). The University of Liège–Gembloux Agro-Bio Tech (Liège, Belgium) supported computations through the technical platform Calcul et Modélisation Informatique (CAMI) of the TERRA Teaching and Research Centre, partly supported by the Fonds de la Recherche Scientifique–FNRS under grant no. T.0095.19 (PDR “DEEPSELECT”). Genotyping was facilitated through the support of the Fonds de la Recherche Scientifique–FNRS under grant no. J.0174.18 (CDR “PREDICT-2”). Relevant information supporting the results not presented here is provided in supplemental data ( https://github.com/hadiatashi/milk-fatty-acids-DBBB). None of the data were deposited in an official repository because they are the property of the breeding organizations, and they are available upon reasonable request. Author contributions were as follows: Hadi Atashi, conceptualization, formal analysis, investigation, methodology, writing the original draft; Yansen Chen, reviewing and editing the draft; Hélène Wilmot, reviewing and editing the draft; Sylvie Vanderick, reviewing and editing the draft; Xavier Hubin, data curation, reviewing and editing the draft; Hélène Soyeurt, data curation, resources, writing, review and editing the draft; Nicolas Gengler, conceptualization, funding acquisition, project administration, resources, supervision, reviewing and editing the draft. The authors have not stated any conflicts of interest.
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