Abstract
The aim of this study was to estimate genotype by time-lagged heat stress (HS) variance components as well as main and interaction SNP-marker effects for maternal HS during the last eight weeks of cow pregnancy, considering milk production traits recorded in the offspring generation. The HS indicator was the temperature humidity index (THI) for each week. A dummy variable with the code = 1 for the respective week for THI ≥ 60 indicated HS, otherwise, for no HS, the code = 0 was assigned. The dataset included test-day and lactation production traits from 14,188 genotyped first parity Holstein cows. After genotype quality control, 41,139 SNP markers remained for the genomic analyses. Genomic animal models without (model VC_nHS) and with in-utero HS effects (model VC_wHS) were applied to estimate variance components. Accordingly, for genome-wide associations, models GWA_nHS and GWA_wHS, respectively, were applied to estimate main and interaction SNP effects. Common genomic and residual variances for the same traits were very similar from models VC_nHS and VC_wHS. Genotype by HS interaction variances varied, depending on the week with in-utero HS. Among all traits, lactation milk yield with HS from week 5 displayed the largest proportion for interaction variances (0.07). For main effects from model GWA_wHS, 380 SNPs were suggestively associated with all production traits. For the SNP interaction effects from model GWA_wHS, we identified 31 suggestive SNPs, which were located in close distance to 62 potential candidate genes. The inferred candidate genes have various biological functions, including mechanisms of immune response, growth processes and disease resistance. Two biological processes excessively represented in the overrepresentation tests addressed lymphocyte and monocyte chemotaxis, ultimately affecting immune response. The modelling approach considering time-lagged genotype by HS interactions for production traits inferred physiological mechanisms being associated with health and immunity, enabling improvements in selection of robust animals.
Highlights
The tripled number of days with extreme temperatures in European countries from 1950 to 2018 [1] indicates the increasing importance of studying the effect of climate change on primary and functional traits in dairy cattle
Genetic markers significantly associated with heat stress (HS) response and underlying candidate genes were detected via genome-wide association studies (GWAS)
Four single nucleotide polymorphisms (SNPs) contributing to a milk yield decline under HS were identified by Hayes et al [8] in Australian Holstein Friesian cattle
Summary
The tripled number of days with extreme temperatures in European countries from 1950 to 2018 [1] indicates the increasing importance of studying the effect of climate change on primary and functional traits in dairy cattle. Random regression models were applied to infer genetic (co)variance components along a continuous THI scale [6] Such modelling approach was used to detect possible genotype x environment interactions (GxE), and THI dependent re-rankings of sires have been observed [7]. Four single nucleotide polymorphisms (SNPs) contributing to a milk yield decline under HS were identified by Hayes et al [8] in Australian Holstein Friesian cattle. The SNP BFGL-NGS-30169 on BTA29 was identified in Jersey cattle, and the strongest annotated candidate gene for the variation of milk yield under HS was the fibroblast growth factor 4 [8]. Selection of cattle displaying the ability to regulate body temperature under HS will contribute to improved heat resistance genetically, implying only marginal detrimental effects on primary and functional traits. Rectal temperature was used an indicator for HS [11], and respiration rate reflects the ability to maintain body temperature through evaporative cooling [10]
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