While autozygosity as a consequence of selection is well understood, there is limited information on the ability of different methods to measure true inbreeding. In the present study, a gene dropping simulation was performed and inbreeding estimates based on runs of homozygosity (ROH), pedigree, and the genomic relationship matrix were compared to true inbreeding. Inbreeding based on ROH was estimated using SNP1101, PLINK, and BCFtools software with different threshold parameters. The effects of different selection methods on ROH patterns were also compared. Furthermore, inbreeding coefficients were estimated in a sample of genotyped North American Holstein animals born from 1990 to 2016 using 50 k chip data and ROH patterns were assessed before and after genomic selection. Using ROH with a minimum window size of 20 to 50 using SNP1101 provided the closest estimates to true inbreeding in simulation study. Pedigree inbreeding tended to underestimate true inbreeding, and results for genomic inbreeding varied depending on assumptions about base allele frequencies. Using an ROH approach also made it possible to assess the effect of population structure and selection on distribution of runs of autozygosity across the genome. In the simulation, the longest individual ROH and the largest average length of ROH were observed when selection was based on best linear unbiased prediction (BLUP), whereas genomic selection showed the largest number of small ROH compared to BLUP estimated breeding values (BLUP-EBV). In North American Holsteins, the average number of ROH segments of 1 Mb or more per individual increased from 57 in 1990 to 82 in 2016. The rate of increase in the last 5 years was almost double that of previous 5 year periods. Genomic selection results in less autozygosity per generation, but more per year given the reduced generation interval. This study shows that existing software based on the measurement of ROH can accurately identify autozygosity across the genome, provided appropriate threshold parameters are used. Our results show how different selection strategies affect the distribution of ROH, and how the distribution of ROH has changed in the North American dairy cattle population over the last 25 years.

Most genetic variants associated with fertility in mammals fall in non-coding regions of the genome and it is unclear how these variants affect fertility. Here we use genome-wide association summary statistics for Heifer puberty (pubertal or not at 600 days) from 27,707 Bos indicus, Bos taurus and crossbred cattle; multi-trait GWAS signals from 2119 indicine cattle for four fertility traits, including days to calving, age at first calving, pregnancy status, and foetus age in weeks (assessed by rectal palpation of the foetus); and expression quantitative trait locus for whole blood from 489 indicine cattle, to identify 87 putatively functional genes affecting cattle fertility. Our analysis reveals a significant overlap between the set of cattle and previously reported human fertility-related genes, impling the existence of a shared pool of genes that regulate fertility in mammals. These findings are crucial for developing approaches to improve fertility in cattle and potentially other mammals.

Reproductive diseases and illnesses pose significant challenges in cattle farming, affecting fertility, milk production, and overall herd health. In recent years, the integration of various omics approaches, including transcriptomics, proteomics, metagenomics, miRNAomics, and metabolomics, has revolutionized the study of these conditions. This systematic review summarised the findings from studies that investigated reproductive disease biomarkers in both male and female cattle. After extracting 6137 studies according to exclusion and inclusion criteria, a total of 60 studies were included in this review. All studies identified were associated with female cattle and none were related to reproductive diseases in bulls. The analysis highlights specific biomarkers, metabolic pathways, and microbial compositions associated with bovine reproductive disease conditions, providing valuable insights into the underlying molecular mechanisms of disease. Pro-inflammatory cytokines such as IL-1 beta, IL-8, IL-4, IL-6, TNF alpha and acute-phase response proteins such as SAA and HP have been identified as promising biomarkers for bovine reproductive diseases. However, further research is needed to validate these markers clinically and to explore potential strategies for improving cow reproductive health. The role of bulls as carriers of venereal diseases has been underestimated in the current literature and therefore needs more attention to understand their impact on infectious reproductive diseases of female cattle.

To further the understanding of the evolution of transcriptional regulation, we profiled genome-wide transcriptional start sites (TSSs) in two sub-species,Bos taurus taurusandBos taurus indicus, that diverged approximately 500,000 years ago. Evolutionary and developmental-stage differences in TSSs were detected across the sub-species, including translocation of dominant TSS and changes in TSS distribution. The 16% of all SNPs located in significant differentially used TSS clusters across sub-species had significant shifts in allele frequency (472 SNPs), indicating they may have been subject to selection. In spleen and muscle, a higher relative TSS expression was observed inBos indicusthanBos taurusfor all heat shock protein genes, which may be responsible for the tropical adaptation ofBos indicus.

Most genetic variants associated with fertility in mammals fall in non-coding regions of the genome and it is unclear how these variants affect fertility. Here we used genome-wide association (GWAS) summary statistics for heifer puberty (pubertal or not at 600 days) from 27,707 cattle; multi-trait GWAS signals from 2,119 cattle for four fertility traits, including days to calving, age at first calving, heifer pregnancy status, and foetus age in weeks; and expression quantitative trait locus (eQTL) for whole blood from 489 cattle, to identify 87 putatively functional genes affecting cattle fertility. Our analysis revealed a significant overlap between the set of cattle and human fertility-related genes. This finding implies the existence of a shared pool of genes that regulate fertility in mammals. These findings have important implications for the development of novel approaches to improve fertility in cattle and potentially in other mammals as well.

Genomic selection (GS) has changed cattle breeding, but its use so far has been in selecting superior bulls for breeding. However, its farm-level impact, particularly on female selection, remains less explored. This study aimed to investigate the impact of implementing GS to identify superior cows and using artificial mating of those cows with sex-selected semen in a New Zealand Holstein-Friesian (HF) dairy herd (n = 1800 cows). Heifers (n = 2061) born over four consecutive years between 2021 and 2024 were genotyped and their genomic breeding values (GBVs) were estimated. These heifers were ranked based on the Balanced Performance Index (BPI; DataGene, Dairy Australia) Lower-performing cows producing less than 15 L/day (or 20 L/day for older cows) and those with severe mastitis were culled. Cows were mated with HF genetics based on production and udder breeding values, while lower-performing cows were mated to beef genetics. Milking adult cows were mated to bulls with similar BPI value. Annual genetic change was measured using Australian breeding values (ABVg) for milk fat production (FAT), protein production (PROT), fertility (FER), Mastitis Resistance (MAS), and BPI. The genetic merits of the heifers improved annually, with BPI increasing from 136 to 184 between 2021 and 2023, corresponding to a financial gain of NZD 17.53 per animal per year. The predicted BPI gain from 2023 to 2026 is expected to rise from 184 to 384, resulting in a financial gain of NZD 72.96 per animal per year. Using sex-selected semen on the top 50% of BPI-rated heifers in 2024 further accelerated genetic gain. Predicted BPI values for progeny born in 2025 and 2026 are 320 and 384, respectively. These findings revealed that the female GS, combined with sex-selected semen from genomically selected bulls, significantly accelerates genetic gain by improving the intensity and accuracy of selection. The approach achieves genetic progress equivalent to what traditionally would have required eight years of breeding without female GS, and has potential to improve dairy herd performance and profitability.