Fertility plays a key role in the success of calf production, but there is evidence that reproductive efficiency in beef cattle has decreased during the past half-century worldwide. Therefore, identifying animals with superior fertility could significantly impact cow-calf production efficiency. The objective of this research was to identify candidate regions affecting bull fertility in beef cattle and positional candidate genes annotated within these regions. A GWAS using a weighted single-step genomic BLUP approach was performed on 265 crossbred beef bulls to identify markers associated with scrotal circumference (SC) and sperm motility (SM). Eight windows containing 32 positional candidate genes and five windows containing 28 positional candidate genes explained more than 1% of the genetic variance for SC and SM, respectively. These windows were selected to perform gene annotation, QTL enrichment, and functional analyses. Functional candidate gene prioritization analysis revealed 14 prioritized candidate genes for SC of which MAP3K1 and VIP were previously found to play roles in male fertility. A different set of 14 prioritized genes were identified for SM and five were previously identified as regulators of male fertility (SOD2, TCP1, PACRG, SPEF2, PRLR). Significant enrichment results were identified for fertility and body conformation QTLs within the candidate windows. Gene ontology enrichment analysis including biological processes, molecular functions, and cellular components revealed significant GO terms associated with male fertility. The identification of these regions contributes to a better understanding of fertility associated traits and facilitates the discovery of positional candidate genes for future investigation of causal mutations and their implications.

Ruminant supply chains contribute 5.7 gigatons of CO2-eq per annum, which represents approximately 80% of the livestock sector emissions. One of the largest sources of emission in the ruminant sector is methane (CH4), accounting for approximately 40% of the sectors total emissions. With climate change being a growing concern, emphasis is being put on reducing greenhouse gas emissions, including those from ruminant production. Various genetic and environmental factors influence cattle CH4 production, such as breed, genetic makeup, diet, management practices, and physiological status of the host. The influence of genetic variability on CH4 yield in ruminants indicates that genomic selection for reduced CH4 emissions is possible. Although the microbiology of CH4 production has been studied, further research is needed to identify key differences in the host and microbiome genomes and how they interact with one another. The advancement of “-omics” technologies, such as metabolomics and metagenomics, may provide valuable information in this regard. Improved understanding of genetic mechanisms associated with CH4 production and the interaction between the microbiome profile and host genetics will increase the rate of genetic progress for reduced CH4 emissions. Through a systems biology approach, various “-omics” technologies can be combined to unravel genomic regions and genetic markers associated with CH4 production, which can then be used in selective breeding programs. This comprehensive review discusses current challenges in applying genomic selection for reduced CH4 emissions, and the potential for “-omics” technologies, especially metabolomics and metagenomics, to minimize such challenges. The integration and evaluation of different levels of biological information using a systems biology approach is also discussed, which can assist in understanding the underlying genetic mechanisms and biology of CH4 production traits in ruminants and aid in reducing agriculture’s overall environmental footprint.

Pregnancy failure in dairy cattle appears to be attributable to losses during embryogenesis, mainly within the first month. Models have estimated that pregnancies lost after day 30 of fertilization cost producers US $550/cow. The reasons for these losses are not well understood, and the transcriptome profile of the reproductive tract during the establishment of pregnancy may point to mechanisms. Thirty-eight cows in lactations 1 to 3 were artificially inseminated, and endometrial biopsies were collected on day 15 after artificial insemination to investigate the effect of parity on the preimplantation pregnancy outcome. Pregnancy status was determined by the presence of interferon-tau in the uterine flushing, revealing 19 pregnant (P) and 19 non-pregnant (NP) cows. Nineteen biopsy samples [9 cows in lactation 1 (6 P and 3 NP), 4 in lactation 2 (2 P and 2 NP), and 6 in lactation 3 (3P and 3NP)] with an average RNA integrity number of 7 were selected for RNA sequencing with an Illumina HiSeq analyzer. Sequence reads were assembled to the ARS_USD1.2.99 bovine reference genome using the CLC genomics workbench software. On average, the samples generated ~56 million reads and 94.99% were mapped to the reference genome. Differential gene expression analysis between P and NP cows identified 187, 60, and 136 differentially expressed genes (DEG) in lactation 1, 2 and 3, respectively (P < 0.01, FDR < 0.05, FC > ±2). Metabolic pathway enrichment analysis identified several DEG upregulated in lactations 2 and 3 associated with IL-17 signaling pathway, although expression of IL-17 itself was not different. This pathway is part of the protective response against extracellular bacteria and likely participates in pregnancy maintenance through local regulation of immune function. Further functional genomic analyses will be performed to determine additional metabolic pathways, key regulator genes, and functional SNPs associated with the establishment of pregnancy.

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