Improving Genomic Selection for Heat Tolerance in Dairy Cattle: Current Opportunities and Future Directions

Abstract

Heat tolerance is the ability of an animal to maintain production and reproduction levels under hot and humid conditions and is now a trait of economic relevance in dairy systems worldwide because of an escalating warming climate. The Australian dairy population is one of the excellent study models for enhancing our understanding of the biology of heat tolerance because they are predominantly kept outdoors on pastures where they experience direct effects of weather elements (e.g., solar radiation). In this article, we focus on evidence from recent studies in Australia that leveraged large a dataset [∼40,000 animals with phenotypes and 15 million whole-genome sequence variants] to elucidate the genetic basis of thermal stress as a critical part of the strategy to breed cattle adapted to warmer environments. Genotype-by-environment interaction (i.e., G × E) due to temperature and humidity variation is increasing, meaning animals are becoming less adapted (i.e., more sensitive) to changing environments. There are opportunities to reverse this trend and accelerate adaptation to warming climate by 1) selecting robust or heat-resilient animals and 2) including resilience indicators in breeding goals. Candidate causal variants related to the nervous system and metabolic functions are relevant for heat tolerance and, therefore, key for improving this trait. This could include adding these variants in the custom SNP panels used for routine genomic evaluations or as the basis to design specific agonist or antagonist compounds for lowering core body temperature under heat stress conditions. Indeed, it was encouraging to see that adding prioritized functionally relevant variants into the 50k SNP panel (i.e., the industry panel used for genomic evaluation in Australia) increased the prediction accuracy of heat tolerance by up to 10% units. This gain in accuracy is critical because genetic improvement has a linear relationship with prediction accuracy. Overall, while this article used data mainly from Australia, this could benefit other countries that aim to develop breeding values for heat tolerance, considering that the warming climate is becoming a topical issue worldwide.

Keywords: Australia; dairy; genomic selection; heat tolerance; prediction accuracy; snps.

FIGURE 1

Overview of this review. The boxes colored in light blue represent the three research studies covered in this article and their respective key findings.

FIGURE 2

Locations of dairy herds (red points) used in the analysis of heat tolerance.

FIGURE 3

Illustrative description of heat tolerance. Cow A and Cow B produce a comparable quantity of milk at thermoneutral conditions (i.e., at low THI). As the THI increase, the milk yield at first remains unaffected up to a given point called a threshold at which the yield begins to decline for both cows, but the rate of decline (slopes) is more for Cow B than Cow A which is G × E. Therefore, Cow A is considered more tolerant to heat than Cow B, and the slope trait can be for milk, fat, and protein yield.

FIGURE 4

Comparing the percentage of heat stress resilient and sensitive bulls in Australia between earlier years (2003–2008) versus recent (2009–2017) years [Adapted from (Cheruiyot et al., 2020)]. The heat-tolerance profiles of the bulls were defined based on the reaction norms of their EBVs along the THI trajectory for heat tolerance milk (A), fat (B), and protein (C) yield slope traits.

FIGURE 5

Reaction norm of the EBVs along the trajectory of THI (heat stress) for a sample of bulls in Australia for heat tolerance milk (A), fat (B), and protein (C) yield slope traits [adapted from (Cheruiyot et al., 2020)].

FIGURE 6

Illustration of heat stress and recovery period between two cows: Cow A is more resilient to heat than Cow B because its trait (e.g., milk yield) returns to the baseline more quickly after exposure to heat stress or other environmental stressors (e.g., disease and parasites).

FIGURE 7

Representation of heat tolerance breeding values (HT GEBVs) that were released to the Australian dairy industry in 2017 (Nguyen et al., 2017). The daughters of a bull with HT GEBV above average (positive) are expected to be more tolerant than the daughters of an average bull and vice versa for bulls with below-average HT GEBVs.

FIGURE 8

Skin and rectal temperature measures for 10 Holstein calves and correlation (R = 0.44) after heat stress (19:02 h); adapted from Srikanth et al. (2017).

FIGURE 9

Incorporating a pre-selected “refined” set of heat-tolerance SNPs (HT-SNPs) into the combined set of real genotypes from standard-industry 50 k (ST-50K) and XT-50K SNP panel developed recently by Xiang et al. (2021).