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In the context of the PhénoFinLait project, a genome-wide analysis was performed to detect quantitative trait loci (QTL) that affect milk protein composition estimated using mid-infrared spectrometry in the Montbéliarde (MO), Normande (NO), and Holstein (HO) French dairy cattle breeds. The 6 main milk proteins (α-lactalbumin, β-lactoglobulin, and αS1-, αS2-, β-, and κ-caseins) expressed as grams per 100g of milk (% of milk) or as grams per 100g of protein (% of protein) were estimated in 848,068 test-day milk samples from 156,660 cows. Genotyping was performed for 2,773 MO, 2,673 NO, and 2,208 HO cows using the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). Individual test-day records were adjusted for environmental effects and then averaged per cow to define the phenotypes analyzed. Quantitative trait loci detection was performed within each breed using a linkage disequilibrium and linkage analysis approach. A total of 39 genomic regions distributed on 20 of the 29 Bos taurus autosomes (BTA) were significantly associated with milk protein composition at a genome-wide level of significance in at least 1 of the 3 breeds. The 9 most significant QTL were located on BTA2 (133 Mbp), BTA6 (38, 47, and 87 Mbp), BTA11 (103 Mbp), BTA14 (1.8 Mbp), BTA20 (32 and 58 Mbp), and BTA29 (8 Mbp). The BTA6 (87 Mbp), BTA11, and BTA20 (58 Mbp) QTL were found in all 3 breeds, and they had highly significant effects on κ-casein, β-lactoglobulin, and α-lactalbumin, expressed as a percentage of protein, respectively. Each of these QTL explained between 13% (BTA14) and 51% (BTA11) of the genetic variance of the trait. Many other QTL regions were also identified in at least one breed. They were located on 14 additional chromosomes (1, 3, 4, 5, 7, 15, 17, 19, 21, 22, 24, 25, 26, and 27), and they explained 2 to 8% of the genetic variance of 1 or more protein composition traits. Concordance analyses, performed between QTL status and sequence-derived polymorphisms from 13 bulls, revealed previously known causal polymorphisms in LGB (BTA11) and GHR (BTA20 at 32 Mbp) and excluded some other previously described mutations. These results constitute a first step in identifying causal mutations and using routinely collected mid-infrared predictions in future genomic selection programs to improve bovine milk protein composition.

International audience

International audience

International audience

National audience; This study, part of the PhénoFinlait project, was aimed at identifying the genes and mutations responsible for the genetic variability of milk fatty acids (FA) and proteins in Holstein, Montbéliarde and Normandy dairy cattle breeds. For 23 FA and 6 proteins, the analyzed phenotype was the mean of mid infra-red test-day measurements, adjusted for environmental effects. Whole genome sequences (WGS) of 8746 cows genotyped with the 50k Illumina chip were imputed with FImpute software, using 1147 sequenced bulls of the “1000 bull genomes” project as a reference. Over 28 million polymorphisms were predicted. GWAS analysis was carried out within breed with GCTA software and the model included a marker effect and a polygenic effect. Overall, 30 to 40 QTL regions were detected per trait over the genome. Many regions already detected with the 50k chip were confirmed but location confidence intervals were smaller. From this first analysis, several 500kb – 3Mb long regions were defined and analyzed by BayesC. This multi-marker method strongly reduces the effect of long distance linkage disequilibrium and pinpoints a limited number of candidate mutations. Breed comparison and functional annotation of variants also provide information. This work is illustrated by 10 examples on chromosomes 5, 14, 17, 19 and 27 for FA and 1, 2, 6, 11, and 20 for proteins. This study shows the value of WGS to identify candidate causal variants underlying the genetic variation of complex traits.; Cette étude réalisée dans le cadre du programme PhénoFinlait vise à identifier les gènes et les mutations responsables de la variabilité génétique de la composition du lait en acides gras (AG) et protéines dans les trois races bovines laitières Holstein, Montbéliarde et Normande. Pour 23 AG et 6 protéines, le phénotype analysé est la moyenne des mesures par moyen infra rouge à chaque contrôle, corrigées pour les effets de milieu. Les séquences du génome complet de 8746 vaches génotypées avec la puce Illumina 50k ont été reconstituées avec le logiciel FImpute, en utilisant comme référence la séquence de 1147 taureaux du projet « 1000 génomes bovins ». Au total, 28 millions de polymorphismes ont été prédits. L’analyse GWAS a été conduite intra-race avec le logiciel GCTA, le modèle incluant un effet marqueur et un effet polygénique. Cette approche a permis de caractériser 30 à 40 régions par caractère sur tout le génome. On retrouve la majorité des régions déjà détectées avec la puce 50k, mais les intervalles de localisation sont plus précis. Cette première analyse a permis de définir des régions de l’ordre de 500 kb à 3 Mb, analysées par BayesC. Cette méthode multi-marqueurs réduit considérablement l’effet du déséquilibre de liaison à grande distance et permet de proposer des mutations causales candidates. La comparaison entre races et l’annotation des variants aident au choix entre ces propositions. Ce travail est illustré avec 10 exemples sur les chromosomes 5, 14, 17, 19 et 27 pour les AG et 1, 2, 6, 11, et 20 pour les protéines. Cette étude montre l’intérêt du séquençage de génomes entiers pour identifier les mutations responsables du déterminisme génétique des caractères.