Background: Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes that are present in an individual due to parents transmitting identical haplotypes to their offspring. The extent and frequency of ROHs may inform on the ancestry of an individual and its population. Here we use high density (n = 777,962) bi-allelic SNPs in a range of cattle breed samples to correlate ROH with the pedigree-based inbreeding coefficients and to validate subsequent analyses using 54,001 SNP genotypes. This study provides a first testing of the inference drawn from ROH through comparison with estimates of inbreeding from calculations based on the detailed pedigree data available for several breeds. Results: All animals genotyped on the HD panel displayed at least one ROH that was between 1–5 Mb in length with certain regions of the genome more likely to be involved in a ROH than others. Strong correlations (r = 0.75, p < 0.0001) existed between the pedigree-based inbreeding coefficient and a statistic based on sum of ROH of length > 0.5 KB and suggests that in the absence of an animal’s pedigree data, the extent of a genome under ROH may be used to infer aspects of recent population history even from relatively few samples. Conclusions: Our findings suggest that ROH are frequent across all breeds but differing patterns of ROH length and burden illustrate variations in breed origins and recent management.

Domestication and the subsequent selection of animals for either economic or morphological features can leave a variety of imprints on the genome of a population. Genomic regions subjected to high selective pressures often show reduced genetic diversity and frequent runs of homozygosity (ROH). Therefore, the objective of the present study was to use 42,182 autosomal SNPs to identify genomic regions in 3,191 sheep from six commercial breeds subjected to selection pressure and to quantify the genetic diversity within each breed using ROH. In addition, the historical effective population size of each breed was also estimated and, in conjunction with ROH, was used to elucidate the demographic history of the six breeds. ROH were common in the autosomes of animals in the present study, but the observed breed differences in patterns of ROH length and burden suggested differences in breed effective population size and recent management. ROH provided a sufficient predictor of the pedigree inbreeding coefficient, with an estimated correlation between both measures of 0.62. Genomic regions under putative selection were identified using two complementary algorithms; the fixation index and hapFLK. The identified regions under putative selection included candidate genes associated with skin pigmentation, body size and muscle formation; such characteristics are often sought after in modern-day breeding programs. These regions of selection frequently overlapped with high ROH regions both within and across breeds. Multiple yet uncharacterised genes also resided within putative regions of selection. This further substantiates the need for a more comprehensive annotation of the sheep genome as these uncharacterised genes may contribute to traits of interest in the animal sciences. Despite this, the regions identified as under putative selection in the current study provide an insight into the mechanisms leading to breed differentiation and genetic variation in meat production.

Increasing consumer concern exists over the relationship between food composition and human health. Because of the known effects of fatty acids on human health, the development of a quick, inexpensive, and accurate method to directly quantify the fatty acid (FA) composition in milk would be valuable for milk processors to develop a payment system for milk pertinent to their customer requirements and for farmers to adapt their feeding systems and breeding strategies accordingly. The aim of this study was (1) to confirm the ability of mid-infrared spectrometry (MIR) to quantify individual FA content in milk by using an innovative procedure of sampling (i.e., samples were collected from cows belonging to different breeds, different countries, and in different production systems); (2) to compare 6 mathematical methods to develop robust calibration equations for predicting the contents of individual FA in milk; and (3) to test interest in using the FA equations developed in milk as basis to predict FA content in fat without corrections for the slope and the bias of the developed equations. In total, 517 samples selected based on their spectral variability in 3 countries (Belgium, Ireland, and United Kingdom) from various breeds, cows, and production systems were analyzed by gas chromatography (GC). The samples presenting the largest spectral variability were used to calibrate the prediction of FA by MIR. The remaining samples were used to externally validate the 28 FA equations developed. The 6 methods were (1) partial least squares regression (PLS); (2) PLS+repeatability file (REP); (3) first derivative of spectral data+PLS; (4) first derivative+REP+PLS; (5) second derivative of spectral data+PLS; and (6) second derivative+REP+PLS. Methods were compared on the basis of the cross-validation coefficient of determination (R2cv), the ratio of standard deviation of GC values to the standard error of cross-validation (RPD), and the validation coefficient of determination (R2v). The third and fourth methods had, on average, the highest R2cv, RPD, and R2v. The final equations were built using all GC and the best accuracy was observed for the infrared predictions of C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C16:0, C18:0, C18:1 trans, C18:1 cis-9, C18:1 cis, and for some groups of FA studied in milk (saturated, monounsaturated, unsaturated, short-chain, medium-chain, and long-chain FA). These equations showed R2cv greater than 0.95. With R2cv equal to 0.85, the MIR prediction of polyunsaturated FA could be used to screen the cow population. As previously published, infrared predictions of FA in fat are less accurate than those developed from FA content in milk (g/dL of milk) and no better results were obtained by using milk FA predictions if no corrections for bias and slope based on reference milk samples with known contents of FA were used. These results indicate the usefulness of equations with R2cv greater than 95% in milk payment systems and the usefulness of equations with R2cv greater than 75% for animal breeding purposes.

Artificial selection for economically important traits in cattle is expected to have left distinctive selection signatures on the genome. Access to high-density genotypes facilitates the accurate identification of genomic regions that have undergone positive selection. These findings help to better elucidate the mechanisms of selection and to identify candidate genes of interest to breeding programs. Information on 705 243 autosomal single nucleotide polymorphisms (SNPs) in 3122 dairy and beef male animals from seven cattle breeds (Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental) were used to detect selection signatures by applying two complementary methods, integrated haplotype score (iHS) and global fixation index (FST). To control for false positive results, we used false discovery rate (FDR) adjustment to calculate adjusted iHS within each breed and the genome-wide significance level was about 0.003. Using the iHS method, 83, 92, 91, 101, 85, 101 and 86 significant genomic regions were detected for Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental cattle, respectively. None of these regions was common to all seven breeds. Using the FST approach, 704 individual SNPs were detected across breeds. Annotation of the regions of the genome that showed selection signatures revealed several interesting candidate genes i.e. DGAT1, ABCG2, MSTN, CAPN3, FABP3, CHCHD7, PLAG1, JAZF1, PRKG2, ACTC1, TBC1D1, GHR, BMP2, TSG1, LYN, KIT and MC1R that play a role in milk production, reproduction, body size, muscle formation or coat color. Fifty-seven common candidate genes were found by both the iHS and global FST methods across the seven breeds. Moreover, many novel genomic regions and genes were detected within the regions that showed selection signatures; for some candidate genes, signatures of positive selection exist in the human genome. Multilevel bioinformatic analyses of the detected candidate genes suggested that the PPAR pathway may have been subjected to positive selection. This study provides a high-resolution bovine genomic map of positive selection signatures that are either specific to one breed or common to a subset of the seven breeds analyzed. Our results will contribute to the detection of functional candidate genes that have undergone positive selection in future studies.

The objective of this study was to determine the inbreeding levels and to analyze the pedigree of Irish purebred populations of Charolais, Limousin, Hereford, Angus, and Simmental beef cattle, as well as the Holstein-Friesian dairy breed. Pedigree analyses included quantifying the depth of known pedigree, average generation intervals, effective population size, the effective number of founders, ancestors, and founder genomes, as well as identifying the most influential animals within the current population of each breed. The annual rate of increase in inbreeding over the past decade was 0.13% (P < 0.001) in the Hereford, 0.06% (P < 0.001) in the Simmental, and 0.10% (P < 0.001) in the Holstein-Friesian breeds. Inbreeding in the other breeds remained relatively constant over the past decade. Herefords had the greatest mean inbreeding in 2004, at 2.19%, whereas Charolais had the lowest, at 0.54%. Over half of each purebred population in 2004 was inbred to some degree; the population with the greatest proportion of animals inbred was the Hereford breed (85%). All 6 breeds displayed a generation interval of approximately 6 yr in recent years. In the pure-bred females born in 2004, the 3 most influential animals contributed between 11% (Limousin) and 24% (Hereford) of the genes. Effective population size was estimated for the Hereford, Simmental, and Holstein-Friesian only, and was 64, 127, and 75, respectively. The effective number of founders varied from 55 (Simmental) to 357 (Charolais), whereas the effective number of ancestors varied from 35 (Simmental and Hereford) to 82 (Limousin). Thus, despite the majority of animals being inbred, the inbreeding level across breeds is low but rising at a slow rate in the Hereford, Simmental, and Holstein-Friesian.

The objective of this study was to determine the effect of inbreeding on milk production, somatic cell count, fertility, survival, calving performance, and cow conformation in Irish Holstein-Friesian pluriparous dairy cows. Inbreeding was included in a linear mixed model as either a class variable or a continuous variable, where higher order polynomials of the latter were also tested in the model as an indicator of nonlinear inbreeding depression. The effects of dam inbreeding and calf inbreeding on calving-related traits were analyzed separately. Inbreeding had a deleterious effect on most of the traits analyzed, although inbreeding depression was sometimes nonlinear or differed significantly across parities. A primiparous animal, 12.5% inbred (i.e., following the mating of noninbred half-sibs), had milk, fat, and protein yields reduced by 61.8, 5.3, and 1.2 kg, respectively; fat and protein concentrations reduced by 0.05 and 0.01%, respectively; and somatic cell scores (i.e., natural log of somatic cell count divided by 1,000) increased by 0.03. The 12.5% inbred animal was also expected to have a 2% greater incidence of dystocia, a 1% greater incidence of stillbirth, a 0.7% greater incidence of male calves, an increase in calving interval of 8.8 d, an increase in age at first calving of 2.5 d, and a reduced survival to second lactation of 4 percentage units. Inbred animals were also taller, narrower, and more angular. Although the effects of inbreeding were statistically significant, they were small and are unlikely to cause great financial loss on Irish dairy farms.