Background The profitability of the beef industry is directly influenced by the fertility rate and reproductive performance of both males and females, which can be improved through selective breeding. When performing genomic analyses, genetic markers located on the X chromosome have been commonly ignored despite the X chromosome being one of the largest chromosomes in the cattle genome. Therefore, the primary objectives of this study were to: (1) estimate variance components and genetic parameters for eighteen male and five female fertility and reproductive traits in Nellore cattle including X chromosome markers in the analyses; and (2) perform genome-wide association studies and functional genomic analyses to better understand the genetic background of male and female fertility and reproductive performance traits in Nellore cattle. Results The percentage of the total direct heritability (h²total) explained by the X chromosome markers (h²x) ranged from 3 to 32% (average: 16.4%) and from 9 to 67% (average: 25.61%) for female reproductive performance and male fertility traits, respectively. Among the traits related to breeding soundness evaluation, the overall bull and semen evaluation and semen quality traits accounted for the highest proportion of h²x relative to h²total with an average of 39.5% and 38.75%, respectively. The total number of significant genomic markers per trait ranged from 7 (seminal vesicle width) to 43 (total major defects). The number of significant markers located on the X chromosome ranged from zero to five. A total of 683, 252, 694, 382, 61, and 77 genes overlapped with the genomic regions identified for traits related to female reproductive performance, semen quality, semen morphology, semen defects, overall bulls’ fertility evaluation, and overall semen evaluation traits, respectively. The key candidate genes located on the X chromosome are PRR32, STK26, TMSB4X, TLR7, PRPS2, SMS, SMARCA1, UTP14A, and BCORL1. The main gene ontology terms identified are “Oocyte Meiosis”, “Progesterone Mediated Oocyte Maturation”, “Thermogenesis”, “Sperm Flagellum”, and “Innate Immune Response”. Conclusions Our findings indicate the key role of genes located on the X chromosome on the phenotypic variability of male and female reproduction and fertility traits in Nellore cattle. Breeding programs aiming to improve these traits should consider adding the information from X chromosome markers in their genomic analyses.

Climate change poses a growing threat to the livestock industry, impacting animal productivity, animal welfare, and farm management practices. Thus, enhancing livestock climatic resilience (CR) is becoming a key priority in various breeding programs. CR can be defined as the ability of an animal to be minimally affected or rapidly return to euthermia under thermally stressful conditions. The primary study objectives were to perform genome-wide association studies for 12 CR indicators derived from variability in longitudinal vaginal temperature in lactating sows under heat stress conditions. A total of 31 single nucleotide polymorphisms (SNPs) located on nine chromosomes were considered as significantly associated with nine CR indicators based on different thresholds. Among them, only two SNPs were simultaneously identified for different CR indicators, SSC6:16,449,770 bp and SSC7:39,254,889 bp. These results highlighted the polygenic nature of CR indicators with small effects distributed across different chromosomes. Furthermore, we identified 434 positional genes associated with CR. Key candidate genes include SLC3A2, STX5, POLR2G, and GANAB, which were previously related to heat stress responses, protein folding, and cholesterol metabolism. Furthermore, the enriched KEGG pathways and Gene Ontology (GO) terms associated with these candidate genes are linked to stress responses, immune and inflammatory responses, neural system, and DNA damage and repair. The most enriched quantitative trait loci are related to “Meat and Carcass”, followed by “Production”, “Reproduction”, “Health”, and “Exterior (conformation and appearance)” traits. Multiple genomic regions were identified associated with different CR indicators, which reveals that CR is a highly polygenic trait with small effect sizes distributed across the genome. Many heat tolerance or HS related genes in our study, such as HSP90AB1, DMGDH, and HOMER1, have been identified. The complexity of CR encompasses a range of adaptive responses, from behavioral to cellular. These results highlight the possibility of selecting more heat-tolerant individuals based on the identified SNP for CR indicators.

Body conformation traits are directly associated with longevity, fertility, health, and workability in dairy cows and have been under direct genetic selection for many decades in various countries worldwide. The main objectives of this study were to perform genome-wide association studies and functional enrichment analyses for fourteen body conformation traits using imputed high-density single nucleotide polymorphism (SNP) genotypes. The traits analyzed include body condition score (BCS), body depth (BD), bone quality (BQ), chest width (CW), dairy capacity (DC), foot angle (FAN), front legs view (FLV), heel depth (HDe), height at front end (HFE), locomotion (LOC), rear legs rear view (RLRV), rear legs side view (RLSV), stature (ST), and a composite feet and legs score index (FL) of Holstein cows scored in Canada. De-regressed estimated breeding values from a dataset of 39,135 North American Holstein animals were used as pseudo-phenotypes in the genome-wide association analyses. A mixed linear model was used to estimate the SNP effects, which ranged from 239,533 to 242,747 markers depending on the trait analyzed. Genes and quantitative trait loci (QTL) located up to 100 Kb upstream or downstream of the significant SNPs previously cited in the Animal QTLdb were detected, and functional enrichment analyses were performed for the candidate genes identified for each trait. A total of 20, 60, 13, 17, 27, 8, 7, 19, 4, 10, 13, 15, 7, and 13 genome-wide statistically significant SNPs for Bonferroni correction based on independent chromosomal segments were identified for BCS, BD, BQ, CW, DC, FAN, FLV, HDe, HFE, LOC, RLRV, RLSV, ST, and FL, respectively. The significant SNPs were located across the whole genome, except on chromosomes BTA24, BTA27, and BTA29. Four markers (for BCS, BD, HDe, and RLRV) were statistically significant when considering a much stricter threshold for the Bonferroni correction for multiple tests. Moreover, the genomic regions identified overlap with various QTL previously reported for the trait groups of exterior, health, meat and carcass, milk, production, and reproduction. The functional enrichment analyses revealed 27 significant gene ontology terms. These enriched genomic regions harbor various candidate genes previously reported as linked to bone development, metabolism, as well as infectious and immunological diseases.

Understanding and assessing dairy cattle behavior is critical for developing sustainable breeding programs and management practices. The behavior of individual animals can provide valuable information on their health and welfare status, improve reproductive management, and predict efficiency traits such as feed efficiency and milking efficiency. Routine genetic evaluations of animal behavior traits can contribute to optimizing breeding and management strategies for dairy cattle but require the identification of traits that capture the most important biological processes involved in behavioral responses. These traits should be heritable, repeatable, and measured in non-invasive and cost-effective ways in many individuals from the breeding populations or related reference populations. While behavior traits are heritable in dairy cattle populations, they are highly polygenic, with no known major genes influencing their phenotypic expression. Genetically selecting dairy cattle based on their behavior can be advantageous because of their relationship with other key traits such as animal health, welfare, and productive efficiency, as well as animal and handlers' safety. Trait definition and longitudinal data collection are still key challenges for breeding for behavioral responses in dairy cattle. However, the more recent developments and adoption of precision technologies in dairy farms provide avenues for more objective phenotyping and genetic selection of behavior traits. Furthermore , there is still a need to standardize phenotyping protocols for existing traits and develop guidelines for recording novel behavioral traits and integrating multiple data sources. This review gives an overview of the most common indicators of dairy cattle behavior, summarizes the main methods used for analyzing animal behavior in commercial settings, describes the genetic and genomic background of previously defined behavioral traits, and discusses strategies for breeding and improving behavior traits coupled with future opportunities for genetic selection for improved behavioral responses.

Traits related to calving have a significant impact on animal welfare and farm profitability in dairy production systems. Identifying genomic regions associated with calving traits could contribute to refining dairy cattle breeding programs and management practices in the dairy industry. Therefore, the primary objectives of this study were to estimate genetic parameters and perform genome-wide association studies (GWAS) and functional enrichment analyses for stillbirth, gestation length, calf size, and calving ease traits in North American Jersey cattle. A total of 40,503 animals with phenotypic records and 5,398 animals genotyped for 45,101 single nucleotide polymorphisms (SNPs) were included in the analyses. Genetic parameters were estimated based on animal models and Bayesian methods. The effects of SNPs were estimated using the Single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) method. The heritabil-ity (standard error) estimates ranged from 0.01 (0.01) for stillbirths (SB) in heifers to 0.11 (0.01) for gestation length (GL) in cows. The genetic correlations ranged from −0.58 (0.11) between calving ease (CE) and SB in heifers to 0.44 (0.14) between calving ease and calf size (CZ) in cows. CE showed the highest genetic correlation between heifers and cows, 0.8 (0.22) respectively. The candidate genes identified, including MTHFR, SERPINA5, IGFBP3, and ZRANB1, are involved in key biological processes and metabolic pathways related to the studied traits. Reducing environmental variation and identifying novel indicators of reproduction traits in the Jersey breed are needed given the low heritability estimates for most traits evaluated in this study. In conclusion , this study provides a characterization of the genetic background of calving-related traits in Jersey cattle. The estimates obtained can be used to improve or build selection indexes in Jersey cattle breeding programs in North America.