Genome-wide associations for heat stress response suggest potential candidate genes underlying milk fatty acid composition in dairy cattle

Abstract

Contents of milk fatty acids (FA) display remarkable alterations along climatic gradients. Detecting candidate genes underlying such alterations might be beneficial for the exploration of climate sensitivity in dairy cattle. Consequently, we aimed on the definition of FA heat stress indicators, considering FA breeding values in response to temperature-humidity index (THI) alterations. Indicators were used in GWAS, in ongoing gene annotations and for the estimation of chromosome-wide variance components. The phenotypic data set consisted of 39,600 test-day milk FA records from 5,757 first-lactation Holstein dairy cows kept in 16 large-scale German cooperator herds. The FA traits were C18:0, polyunsaturated fatty acids (PUFA), saturated fatty acids (SFA), and unsaturated fatty acids (UFA). After genotype quality control, 40,523 SNP markers from 3,266 cows and 930 sires were considered. Meteorological data from the weather station in closest herd distance were used for the calculation of maximum hourly daily THI, which were allocated to 10 different THI classes. The same FA from 3 stages of lactation were considered as different, but genetically correlated traits. Consequently, a 3-trait reaction norm model was used to estimate genetic parameters and breeding values for FA along THI classes, considering either pedigree (A) or genomic (G) relationship matrices. De-regressed proofs and genomic estimated breeding values at the intermediate THI class 5 and at the extreme THI class 10 were used as pseudophenotypes in ongoing genomic analyses for thermoneutral (TNC) and heat stress conditions (HSC), respectively. The differences in de-regressed proofs and in genomic estimated breeding values from both THI classes were pseudophenotypes for heat stress response (HSR). Genetic correlations between the same FA under TNC and HSC were smallest in the first lactation stage and ranged from 0.20 for PUFA to 0.87 for SFA when modeling with the A matrix, and from 0.35 for UFA to 0.86 for SFA when modeling with the G matrix. In the first lactation stage, larger additive genetic variances under HSC compared with TNC indicate climate sensitivity for C18:0, PUFA, and UFA. Climate sensitivity was also reflected by pronounced chromosome-wide genetic variances for HSR of PUFA and UFA in the first stage of lactation. For all FA under TNC, HSC, and HSR, quite large genetic variance proportions were explained by BTA14. In GWAS, 30 SNP (within or close to 38 potential candidate genes) overlapped for HSR of the different FA. One unique potential candidate gene (AMFR) was detected for HSR of PUFA, 15 for HSR of SFA (ADGRB1, DENND3, DUSP16, EFR3A, EMP1, ENSBTAG00000003838, EPS8, MGP, PIK3C2G, STYK1, TMEM71, GSG1, SMARCE1, CCDC57, and FASN) and 3 for HSR of UFA (ENSBTAG00000048091, PAEP, and EPPK1). The identified unique genes play key roles in milk FA synthesis and are associated with disease resistance in dairy cattle. The results suggest consideration of FA in combination with climatic responses when inferring genetic mechanisms of heat stress in dairy cows.