Estimation of genetic parameters for BW and body measurements in Brahman cattle

Phenotypic and genetic diversity of domestic yak (Bos grunniens) in high-altitude rangelands of Gilgit-Baltistan, Pakistan

Due to climate change, irrigated agriculture may become restricted in the mountain valleys in northern Pakistan in the future. Hence, the importance of yak (Bos grunniens) keeping in the mountain ranges as risk-mitigating strategy for mountain dwellers will potentially increase. However, little is known about the current status of the domestic yak in this region. We therefore used phenotypic characteristics and 13 microsatellite loci to determine the phenotypic differences and the level of genetic differentiation between populations of six valleys. Larger body measures and partially different physical appearance were observed in Shimshal and Khaplu yaks, especially when compared with yaks in the Chapurson valley. Overall, the mean observed heterozygosity was similar to the mean expected heterozygosity. Average genetic diversity was highest in the Hopar population and lowest in the Haramosh population. A low F_IS value indicated that individuals were less related than expected under a model of random mating. Three distinct genetic clusters were found for the six yak populations under study. Genetic distances were largest between Shimshal and Khaplu populations, and lowest between populations of Phandar and Hopar. It is concluded that yaks of Shimshal, Khaplu and Haramosh valleys were genetically distinct from yak populations in Chapurson, Hopar and Phandar valleys, indicating that the free-range conditions and pastoral yak rearing system in the region have preserved the underlying genetic diversity of the yak populations.

Phenotypic differences for growth, feed efficiency, and age of first calving of Brazilian zebu females

This study investigated phenotypic differences of zebu females from four breeds using variables of growth, feed efficiency, and age at first calving. Weights throughout the life were recorded, and a growth curve was fitted using the Gompertz model. The growth was also evaluated at standardized ages (205, 365, and 550 days) using the body weight and the total and daily weight gains. The Kleiber index and age at first calving were used as measures of feed efficiency and sexual precocity, respectively, totaling 25 variables. New variables were created using the factor analysis and used in new multivariate analyzes. Only six factors explained 95.41% of the total variance and were used for the subsequent analyses. The factors were defined as maturity, precocity, feed efficiency postweaning, feed efficiency post 1 year of age, puberty, and birth weight. There were differences between breeds according to the multivariate analysis of variance. Each breed appeared in a quadrant on the Biplot graph, showing relationship with different factors, demonstrating the diversity of zebu females. There is a difference in growth, feed efficiency, and sexual precocity in Brazilian zebu females, allowing the identification of potentials of the animals and help breeders and decision-makers.

Genetic evaluation for reproductive and productive traits in Brahman cattle

Our objectives were to estimate genetic parameters for male and female reproductive traits and their genetic correlations with body weight and carcass traits, evaluate the genetic trends over the years, and verify the effect of inbreeding on the phenotypes of Brahman cattle. The traits evaluated were body weights at 120, 210, 365, and 450 days of age (W120, W210, W365, and W450); scrotal circumference at 365 and 450 days of age (SC365 and SC450), age at first calving (AFC), gestation length (GL), stayability (STAY), ribeye area (REA), backfat thickness (BFT), and rump fat thickness (RFT). Direct heritability estimates ranged from 0.10 ± 0.03 (AFC) to 0.43 ± 0.06 (GL). Maternal heritability estimates for body weights, scrotal circumferences, and GL ranged from 0.07 ± 0.02 to 0.15 ± 0.03. The proportion of the maternal permanent environment for W120 and W210 was equal to 0.11 ± 0.02. Genetic correlations varied between -0.60 ± 0.25 (STAY and BFT) to 0.97 ± 0.01 (W365 and W450). Except for AFC, all genetic trends were significant (p < 0.05) and presented favorable annual genetic gains. Unfavorable effects due to the increase of inbreeding coefficients were observed for body weights and AFC, suggesting greater attention be paid to the applied mating systems to control inbreeding. Reproductive traits, such as AFC and STAY, could be assisted indirectly by scrotal circumference selection. The emphasis applied to body weight selection, especially at W210, may assist REA. The BFT and RFT traits presented genetic variability and have responded to selection, although not included in the Brahman selection index.

Comparison of Genetic Merit for Weight and Meat Traits between the Polled and Horned Cattle in Multiple Beef Breeds

Breeding for polled animals is deemed the most practical solution to eradicate horns naturally and circumvent management costs and risks on health and welfare. However, there has been a historical reluctance by some farmers to select polled animals due to perceived lower productivity of their calves. This study has compared estimated breeding values (EBVs) between horned and polled animals (N = 2,466,785) for 12 production and carcass traits to assess historical (before 2000) and recent (2000-2018) genetic implications of poll breeding. Older generations of the polled animals in most breeds had significantly lower (Bonferroni-corrected p = 0.05) genetic merits for live (birth to maturity) and carcass weights, milk, meat quality, and fat content traits. Substantial gains of genetic potential were achieved during 2000 to 2018 in each breed, such that polled animals have significantly improved for the majority of traits studied. Generally, polled cohorts showed advantageous EBVs for live and carcass weights irrespective of the lower birth weights in some breeds. While Polled Brahman showed inferior production parameters, the poll genetics' effect size (d) and correlation (r) were very small on recent birth weight (d = -0.30, r = -0.08), 200 days (-0.19, -0.05), 400 days (-0.06, -0.02), 600 days (-0.05, -0.01), mature cow live weight (-0.08, -0.02), and carcass weight (-0.19, -0.05). In conclusion, although there is some evidence that historical selection for polled breeding animals may have reduced productivity, there is strong evidence that more recent selection for polled genotypes in the breeds studied has not resulted in any adverse effects on genetic merit.

A multi-breed GWAS for morphometric traits in four Beninese indigenous cattle breeds reveals loci associated with conformation, carcass and adaptive traits

BACKGROUND

Specific adaptive features including disease resistance and growth abilities in harsh environments are attributed to indigenous cattle breeds of Benin, but these breeds are endangered due to crossbreeding. So far, there is a lack of systematic trait recording, being the basis for breed characterizations, and for structured breeding program designs aiming on conservation. Bridging this gap, own phenotyping for morphological traits considered measurements for height at withers (HAW), sacrum height (SH), heart girth (HG), hip width (HW), body length (BL) and ear length (EL), including 449 cattle from the four indigenous Benin breeds Lagune, Somba, Borgou and Pabli. In order to utilize recent genomic tools for breed characterizations and genetic evaluations, phenotypes for novel traits were merged with high-density SNP marker data. Multi-breed genetic parameter estimations and genome-wide association studies (GWAS) for the six morphometric traits were carried out. Continuatively, we aimed on inferring genomic regions and functional loci potentially associated with conformation, carcass and adaptive traits.

RESULTS

SNP-based heritability estimates for the morphometric traits ranged between 0.46 ± 0.14 (HG) and 0.74 ± 0.13 (HW). Phenotypic and genetic correlations ranged from 0.25 ± 0.05 (HW-BL) to 0.89 ± 0.01 (HAW-SH), and from 0.14 ± 0.10 (HW-BL) to 0.85 ± 0.02 (HAW-SH), respectively. Three genome-wide and 25 chromosome-wide significant SNP positioned on different chromosomes were detected, located in very close chromosomal distance (±25 kb) to 15 genes (or located within the genes). The genes PIK3R6 and PIK3R1 showed direct functional associations with height and body size. We inferred the potential candidate genes VEPH1, CNTNAP5, GYPC for conformation, growth and carcass traits including body weight and body fat deposition. According to their functional annotations, detected potential candidate genes were associated with stress or immune response (genes PTAFR, PBRM1, ADAMTS12) and with feed efficiency (genes MEGF11 SLC16A4, CCDC117).

CONCLUSIONS

Accurate measurements contributed to large SNP heritabilities for some morphological traits, even for a small mixed-breed sample size. Multi-breed GWAS detected different loci associated with conformation or carcass traits. The identified potential candidate genes for immune response or feed efficiency indicators reflect the evolutionary development and adaptability features of the breeds.

Body Dimension Measurements of Qinchuan Cattle with Transfer Learning from LiDAR Sensing

For the time-consuming and stressful body measuring task of Qinchuan cattle and farmers, the demand for the automatic measurement of body dimensions has become more and more urgent. It is necessary to explore automatic measurements with deep learning to improve breeding efficiency and promote the development of industry. In this paper, a novel approach to measuring the body dimensions of live Qinchuan cattle with on transfer learning is proposed. Deep learning of the Kd-network was trained with classical three-dimensional (3D) point cloud datasets (PCD) of the ShapeNet datasets. After a series of processes of PCD sensed by the light detection and ranging (LiDAR) sensor, the cattle silhouettes could be extracted, which after augmentation could be applied as an input layer to the Kd-network. With the output of a convolutional layer of the trained deep model, the output layer of the deep model could be applied to pre-train the full connection network. The TrAdaBoost algorithm was employed to transfer the pre-trained convolutional layer and full connection of the deep model. To classify and recognize the PCD of the cattle silhouette, the average accuracy rate after training with transfer learning could reach up to 93.6%. On the basis of silhouette extraction, the candidate region of the feature surface shape could be extracted with mean curvature and Gaussian curvature. After the computation of the FPFH (fast point feature histogram) of the surface shape, the center of the feature surface could be recognized and the body dimensions of the cattle could finally be calculated. The experimental results showed that the comprehensive error of body dimensions was close to 2%, which could provide a feasible approach to the non-contact observations of the bodies of large physique livestock without any human intervention.