Background There is an increasing need to account for genotype-by-environment (G × E) interactions in livestock breeding programs to improve productivity and animal welfare across environmental and management conditions. This is even more relevant for pigs because selection occurs in high-health nucleus farms, while commercial pigs are raised in more challenging environments. In this study, we used single-step homoscedastic and heteroscedastic genomic reaction norm models (RNM) to evaluate G × E interactions in Large White pigs, including 8686 genotyped animals, for reproduction (total number of piglets born, TNB; total number of piglets born alive, NBA; total number of piglets weaned, NW), growth (weaning weight, WW; off-test weight, OW), and body composition (ultrasound muscle depth, MD; ultrasound backfat thickness, BF) traits. Genetic parameter estimation and single-step genome-wide association studies (ssGWAS) were performed for each trait. Results The average performance of contemporary groups (CG) was estimated and used as environmental gradient in the reaction norm analyses. We found that the need to consider heterogeneous residual variance in RNM models was trait dependent. Based on estimates of variance components of the RNM slope and of genetic correlations across environmental gradients, G × E interactions clearly existed for TNB and NBA, existed for WW but were of smaller magnitude, and were not detected for NW, OW, MD, and BF. Based on estimates of the genetic variance explained by the markers in sliding genomic windows in ssGWAS, several genomic regions were associated with the RNM slope for TNB, NBA, and WW, indicating specific biological mechanisms underlying environmental sensitivity, and dozens of novel candidate genes were identified. Our results also provided strong evidence that the X chromosome contributed to the intercept and slope of RNM for litter size traits in pigs. Conclusions We provide a comprehensive description of G × E interactions in Large White pigs for economically-relevant traits and identified important genomic regions and candidate genes associated with GxE interactions on several autosomes and the X chromosome. Implementation of these findings will contribute to more accurate genomic estimates of breeding values by considering G × E interactions, in order to genetically improve the environmental robustness of maternal-line pigs.

Milk fat composition has important implications in the nutritional and processing properties of milk. Additionally, milk fat composition is associated with cow physiological and health status. The main objectives of this study were (1) to estimate genetic parameters for 5 milk fatty acid (FA) groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted from milk infrared spectra using a large data set; (2) to predict genomic breeding values using a longitudinal single-step genomic BLUP approach; and(3) to conduct a single-step GWAS aiming to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA, and consequently, to understand the underlying biology of these traits. We used 629,769 test-day records of 201,465 first-parity Holstein cows from 6,105 herds. A total of 8,865 genotyped (Illumina BovineSNP50K BeadChip, Illumina, San Diego, CA) animals were considered for the genomic analyses. The average daily heritability ranged from 0.24 (unsaturated FA) to 0.47 (medium-chain and saturated FA). The reliability of the genomic breeding values ranged from 0.56 (long-chain fatty acid) to 0.74 (medium-chain fatty acid) when using the default τ and ω scaling parameters, whereas it ranged from 0.58 (long-chain fatty acid) to 0.73 (short-chain fatty acid) when using the optimal τ and ω values (i.e., τ = 1.5 and ω = 0.6), as defined in a previous study in the same population. Relevant chromosomal regions were identified in Bos taurus autosomes 5 and 14. The proportion of the variance explained by 20 adjacent single nucleotide polymorphisms ranged from 0.71% (saturated FA) to 15.12% (long-chain FA). Important candidate genes and pathways were also identified. In summary, our results contribute to a better understanding of the genetic architecture of predicted milk FA in dairy cattle and reinforce the relevance of using genomic information for genetic analyses of these traits.

Genome-wide association studies (GWASes) have been performed to search for genomic regions associated with residual feed intake (RFI); however inconsistent results have been obtained. A meta-analysis may improve these results by decreasing the false-positive rate. Additionally, pathway analysis is a powerful tool that complements GWASes, as it enables identification of gene sets involved in the same pathway that explain the studied phenotype. Because there are no reports on GWAS pathways-based meta-analyses for RFI in beef cattle, we used several GWAS results to search for significant pathways that may explain the genetic mechanism underlying this trait. We used an efficient permutation hypothesis test that takes into account the linkage disequilibrium patterns between SNPs and the functional feasibility of the identified genes over the whole genome. One significant pathway (valine, leucine and isoleucine degradation) related to RFI was found. The three genes in this pathway-methylcrotonoyl-CoA carboxylase 1 (MCCC1), aldehyde oxidase 1 (AOX1) and propionyl-CoA carboxylase alpha subunit (PCCA)-were found in three different studies. This same pathway was also reported in a transcriptome analysis from two cattle populations divergently selected for high and low RFI. We conclude that a GWAS pathway-based metaanalysis can be an appropriate method to uncover biological insights into RFI by combining useful information from different studies.

Understanding the biological mechanisms of climatic adaptation is of paramount importance for the optimization of breeding programs and conservation of genetic resources. The aim of this study was to investigate genetic diversity and unravel genomic regions potentially under selection for heat and/or cold tolerance in thirty-two worldwide cattle breeds, with a focus on Chinese local cattle breeds adapted to divergent climatic conditions, Datong yak (Bos grunniens; YAK), and Bali (Bos javanicus) based on dense SNP data. In general, moderate genetic diversity levels were observed in most cattle populations. The proportion of polymorphic SNP ranged from 0.197 (YAK) to 0.992 (Mongolian cattle). Observed and expected heterozygosity ranged from 0.023 (YAK) to 0.366 (Sanhe cattle; SH), and from 0.021 (YAK) to 0.358 (SH), respectively. The overall average inbreeding (±SD) was: 0.118 ± 0.028, 0.228 ± 0.059, 0.194 ± 0.041, and 0.021 ± 0.004 based on the observed versus expected number of homozygous genotypes, excess of homozygosity, correlation between uniting gametes, and runs of homozygosity (ROH), respectively. Signatures of selection based on multiple scenarios and methods (FST, HapFLK, and ROH) revealed important genomic regions and candidate genes. The candidate genes identified are related to various biological processes and pathways such as heat-shock proteins, oxygen transport, anatomical traits, mitochondrial DNA maintenance, metabolic activity, feed intake, carcass conformation, fertility, and reproduction. This highlights the large number of biological processes involved in thermal tolerance and thus, the polygenic nature of climatic resilience. A comprehensive description of genetic diversity measures in Chinese cattle and YAK was carried out and compared to 24 worldwide cattle breeds to avoid potential biases. Numerous genomic regions under positive selection were detected using three signature of selection methods and candidate genes potentially under positive selection were identified. Enriched function analyses pinpointed important biological pathways, molecular function and cellular components, which contribute to a better understanding of the biological mechanisms underlying thermal tolerance in cattle. Based on the large number of genomic regions identified, thermal tolerance has a complex polygenic inheritance nature, which was expected considering the various mechanisms involved in thermal stress response.

Properly quantifying environmental heat stress (HS) is still a major challenge in livestock breeding programs, especially as adverse climatic events become more common. The definition of critical periods and climatic variables to be used as the environmental gradient is a key step for genetically evaluating heat tolerance (HTol). Therefore, the main objectives of this study were to define the best critical periods and environmental variables (ENV) to evaluate HT and estimate variance components for HT in Large White pigs. The traits included in this study were ultrasound backfat thickness (BFT), ultrasound muscle depth (MDP), piglet weaning weight (WW), off-test weight (OTW), interval between farrowing (IBF), total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets born dead (NBD), number of piglets weaned (WN), and weaning to estrus interval (IWE). Seven climatic variables based on public weather station data were compared based on three criteria, including the following: (1) strongest G×E estimate as measured by the slope term, (2) ENV yielding the highest theoretical accuracy of the genomic estimated breeding values (GEBV), and (3) variable yielding the highest distribution of GEBV per ENV. Relative humidity (for BFT, MDP, NBD, WN, and WW) and maximum temperature (for OTW, TNB, NBA, IBF, and IWE) are the recommended ENV based on the analyzed criteria. The acute HS (average of 30 days before the measurement date) is the critical period recommended for OTW, BFT, and MDP in the studied population. For WN, WW, IBF, and IWE, a period ranging from 34 days prior to farrowing up to weaning is recommended. For TNB, NBA, and NBD, the critical period from 20 days prior to breeding up to 30 days into gestation is recommended. The genetic correlation values indicate that the traits were largely (WN, WW, IBF, and IWE), moderately (OTW, TNB, and NBA), or weakly (MDP, BFT, and NBD) affected by G×E interactions. This study provides relevant recommendations of critical periods and climatic gradients for several traits in order to evaluate HS in Large White pigs. These observations demonstrate that HT in Large White pigs is heritable, and genetic progress can be achieved through genetic and genomic selection.

Milk fat content and fatty acid (FA) composition have great economic value to the dairy industry as they are directly associated with taste and chemicalphysical characteristics of milk and dairy products. In addition, consumers' choices are not only based on the nutritional aspects of food, but also on products known to promote better health. Milk FA composition is also related to the metabolic status and physiological stages of cows and thus can also be used as indicator for other novel traits of interest (e.g., metabolic diseases and methane yield). Genetic selection is a promising alternative to manipulate milk FA composition. In this study, we aimed to (1) estimate time-dependent genetic parameters for 5 milk FA groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted based on milk mid-infrared spectroscopy, for Canadian Ayrshire and Jersey breeds, and (2) conduct a time-dependent, single-step genome-wide association study to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA. We analyzed 31,709 test-day records of 9,648 Ayrshire cows from 268 herds, and 34,341 records of 11,479 Jersey cows from 883 herds. The genomic database contained a total of 2,330 Ayrshire and 1,019 Jersey animals. The average daily heritability ranged from 0.18 (long-chain FA) to 0.34 (medium-chain FA) in Ayrshire, and from 0.25 (long-chain and unsaturated FA) to 0.52 (mediumchain and saturated FA) in Jersey. Important genomic regions were identified in Bos taurus autosomes BTA3,

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An accurate understanding of heat stress (HS) temperatures and phenotypes that indicate HS tolerance is necessary to improve swine HS resilience. Therefore, the study objectives were 1) to identify phenotypes indicative of HS tolerance, and 2) to determine moderate and severe HS threshold temperatures in lactating sows. Multiparous (4.10 ± 1.48) lactating sows and their litters (11.10 ± 2.33 piglets/litter) were housed in naturally ventilated (n = 1,015) or mechanically ventilated (n = 630) barns at a commercial sow farm in Maple Hill, NC USA between June 9 and July 24, 2021. In-barn dry bulb temperatures (TDB) and relative humidity were continuously recorded for naturally ventilated (26.38 ± 1.21°C and 83.38 ± 5.40%, respectively) and mechanically ventilated (26.91 ± 1.80°C and 77.13 ± 7.06%, respectively) barns using data recorders. Sows were phenotyped between lactation d 11.28 ± 3.08 and 14.25 ± 3.26. Thermoregulatory measures were obtained daily at 0800, 1200, 1600, and 2000 h and included respiration rate, and ear, shoulder, rump, and tail skin temperatures. Vaginal temperatures (TV) were recorded in 10 min intervals using data recorders. Anatomical characteristics were recorded, including ear area and length, visual and caliper-assessed body condition scores, and a visually assessed and subjective hair density score. Data were analyzed using PROC MIXED to evaluate the temporal pattern of thermoregulatory responses, phenotype correlations were based on mixed model analyses, and moderate and severe HS inflection points were established by fitting TV as the dependent variable in a cubic function against TDB. Statistical analyses were conducted separately for sows housed in mechanically or naturally ventilated barns because the sow groups were not housed in each facility type simultaneously. The temporal pattern of thermoregulatory responses was similar for naturally and mechanically ventilated barns and several thermoregulatory and anatomical measures were significantly correlated with one another (P < 0.05), including all anatomical measures as well as skin temperatures, respiration rates, and TV. For sows housed in naturally and mechanically ventilated facilities, moderate HS threshold TDB were 27.36 and 26.69°C, respectively, and severe HS threshold TDB were 29.45 and 30.60°C, respectively. In summary, this study provides new information on the variability of HS tolerance phenotypes and environmental conditions that constitute HS in commercially housed lactating sows.