Dairy production in Holstein cows in a semiarid environment is challenging due to heat stress. Under such conditions, genetic selection for heat tolerance appears to be a useful strategy. The objective was to validate molecular markers associated with milk production and thermotolerance traits in Holstein cows managed in a hot and humid environment. Lactating cows (n = 300) exposed to a heat stress environment were genotyped using a medium-density array including 53,218 SNPs. A genome-wide association study (GWAS) detected six SNPs associated with total milk yield (MY305) that surpassed multiple testing (p < 1.14 × 10⁻⁶). These SNPs were further validated in 216 Holstein cows from two independent populations that were genotyped using the TaqMan bi-allelic discrimination method and qPCR. In these cows, only the SNPs rs8193046, rs43410971, and rs382039214, within the genes TLR4, GRM8, and SMAD3, respectively, were associated (p < 0.05) with MY305, rectal temperature (RT), and respiratory rate. Interestingly, these variables improved as the number of favorable genotypes of the SNPs increased from 0 to 3. In addition, a regression analysis detected RT as a significant predictor (R² = 0.362) for MY305 in cows with >1 favorable genotype, suggesting this close relationship was influenced by genetic markers. In conclusion, SNPs in the genes TLR4, GRM8, and SMAD3 appear to be involved in the molecular mechanism that regulates milk production in cows under heat-stressed conditions. These SNPs are proposed as thermotolerance genetic markers for a selection program to improve the milk performance of lactating Holstein cows managed in a semiarid environment.

Heifer pregnancy (HPG) and Stayability (STAY) are female reproductive traits that have EPD reported by the Red Angus Association of America. Challenges arise when making genetic predictions for these traits. Specifically, HPG and STAY phenotypes can only be collected on females retained in the breeding herd and have low heritability estimates. Additionally, STAY is measured late in an animal’s life. The objective of this research was to investigate the genetic relationships between HPG or STAY and 13 other traits, which included measurements of growth, carcass, ultrasound, and scrotal circumference. For STAY relationships between mature weight (MW), body condition score (BCS), teat score (TS), and udder suspension score (US) were also evaluated. Data from 142,146 and 164,235 animals were used in the analyses for HPG and STAY, respectively. Genetic relationships were investigated using a series of 2 trait animal models and a REML procedure. In all analyses, the appropriate contemporary groups were included as a fixed effect, and direct genetic as a random effect. Additional fixed effects included as follows: sex for weight, carcass and ultrasound traits, age of dam for weight traits, and age of measurement for ultrasound, carcass, BCS, udder traits, and MW. Maternal genetic effects for preweaning gain (Pre-WG), weaning weight (WW), and yearling weight (YW) were also modeled. Permanent environmental effects of the dam were modeled for the traits Pre-WG and WW. Permanent environment of the individual for the traits MW, BCS, TS, and US was also included. Heritability estimates were 0.12 ± 0.01 and 0.10 ± 0.01 for HPG and STAY, respectively. Heritability estimates for direct genetic effects of production traits were moderate to high in magnitude, maternal heritability estimates were low, and permanent environmental effects accounted for 0.00 to 0.18 of the total variation. The strongest genetic correlations were those among Pre-WG_D (0.24 ± 0.08), WW_D (0.18 ± 0.08), YW_D (0.20 ± 0.07), ultrasound rib eye area direct (0.16 ± 0.08), and ultrasound backfat direct (0.14 ± 0.08) and HPG. The highest genetic correlations were between STAY and WW_M (0.54 ± 0.05), YW_M (0.36 ± 0.07), backfat (0.53 ± 0.20), marbling score (0.40 ± 0.20), UREA (0.19 ± 0.07), ultrasound backfat (0.37 ± 0.07), TS (0.30 ± 0.11), and US (0.23 ± 0.11). Relationships between HPG or STAY and other traits were minimal. These results suggest that genetic relationships exist between HPG or STAY and other more densely recorded traits.

Feral swine (Sus scrofa) are a destructive invasive species widespread throughout the United States that disrupt ecosystems, damage crops, and carry pathogens of concern for the health of domestic stock and humans includingBrucella suis—the causative organism for swine brucellosis. In domestic swine, brucellosis results in reproductive failure due to abortions and infertility. Contact with infected feral swine poses spillover risks to domestic pigs as well as humans, companion animals, wildlife, and other livestock. Genetic factors influence the outcome of infectious diseases; therefore, genome wide association studies (GWAS) of differential immune responses among feral swine can provide an understanding of disease dynamics and inform management to prevent the spillover of brucellosis from feral swine to domestic pigs. We sought to identify loci associated with differential antibody responses among feral swine naturally infected withB. suisusing a case-control GWAS. Tissue, serum, and genotype data (68,516 bi-allelic single nucleotide polymorphisms) collected from 47 feral swine were analyzed in this study. The 47 feral swine were culture positive forBrucellaspp. Of these 47, 16 were antibody positive (cases) whereas 31 were antibody negative (controls). Single-locus GWAS were performed using efficient mixed-model association eXpedited (EMMAX) methodology with three genetic models: additive, dominant, and recessive. Eight loci associated with seroconversion were identified on chromosome 4, 8, 9, 10, 12, and 18. Subsequent bioinformatic analyses revealed nine putative candidate genes related to immune function, most notably phagocytosis and induction of an inflammatory response. Identified loci and putative candidate genes may play an important role in host immune responses toB. suisinfection, characterized by a detectable bacterial presence yet a differential antibody response. Given that antibody tests are used to evaluate brucellosis infection in domestic pigs and for disease surveillance in invasive feral swine, additional studies are needed to fully understand the genetic component of the response toB. suisinfection and to more effectively translate estimates ofBrucellaspp. antibody prevalence among feral swine to disease control management action.

Anti-Müllerian hormone (AMH) is proposed as a biomarker for fertility in cattle, yet this associative relationship appears to be influenced by heat stress (HS). The objective was to test serum AMH and AMH-related single nucleotide polymorphisms (SNPs) as markers potentially predictive of reproductive traits in dairy cows experiencing HS. The study included 300 Holstein cows that were genotyped using BovineSNP50 (54,000 SNP). A genome-wide association study was then executed. Nine intragenic SNPs within the pathways that influence the AMH gene were found important with multiple comparisons adjustment tests (p < 1.09 × 10⁻⁶). A further validation study was performed in an independent Holstein cattle population, which was divided into moderate (MH; n = 152) and severe heat-stressed (SH; n = 128) groups and then subjected to a summer reproductive management program. Serum AMH was confirmed as a predictor of fertility measures (p < 0.05) in MH but not in the SH group. Cows were genotyped, which revealed four SNPs as predictive markers for serum AMH (p < 0.01), reproductive traits (p < 0.01), and additional physiological variables (p < 0.05). These SNPs were in the genes AMH, IGFBP1, LGR5, and TLR4. In conclusion, serum AMH concentrations and AMH polymorphisms are proposed as predictive markers that can be used in conjunction with genomic breeding value approaches to improve reproductive performance in Holstein cows exposed to summer HS conditions.

Currently, many different data types are collected by beef cattle breed associations for the purpose of genetic evaluation. These data points are all biological characteristics of individual animals that can be measured multiple times over an animal's lifetime. Some traits can only be measured once on an individual animal, whereas others, such as the body weight of an animal as it grows, can be measured many times. Data such as growth has been often referred to as "longitudinal" or "infinite-dimensional" since it is theoretically possible to observe the trait an infinite number of times over the life span of a given individual. Analysis of such data is not without its challenges, and as a result many different methods have been or are beginning to be implemented in the genetic analysis of beef cattle data, each an improvement over its predecessor. These methods of analysis range from the classic repeated measures to the more contemporary suite of random regressions that use covariance functions or even splines as their base function. Each of the approaches has both strengths and weaknesses in the analysis of longitudinal data. Here we summarize past and current genetic evaluation technology for analyzing this type of data and review some emerging technologies beginning to be implemented in national cattle evaluation schemes, along with their potential implications for the beef industry.

Feedlot heart disease (FHD) is a cardiopulmonary condition observed in fed cattle at elevations between 800 and 1,600 m ( Neary et al., 2015). Feedlot heart disease results in premature mortality as a result of right-sided heart failure stemming from increased pulmonary vessel pressures and cardiopulmonary remodeling, which is also known as pulmonary hypertension (PH) ( Krafsur et al., 2019). This is similar to the well-documented high mountain disease (HMD), which is characterized as the progression of PH resulting from chronic exposure to environmental hypoxia at high altitude ( Hecht et al., 1962). Pulmonary arterial pressure (PAP) is abnormally high when an animal experiences PH. Increased PAP leads to cor pulmonale, where the heart’s right ventricle becomes enlarged, causing increased work to move the blood from an area of lower pressure (i.e., right ventricle) to an area of higher pressure (i.e., pulmonary artery) resulting in excessive muscle contraction which stretches muscle fibers and can end in right-sided heart failure ( Thomas et al., 2018). An animal is given a heart score (HS; scale of 1 to 5 with 5 being extreme structural changes in the heart, Fig. 1) at harvest to categorize the degree to which heart remodeling occurred.