Background: The genetic structure of a diverse set of 15 Indian indigenous breeds and non-descript indigenous cattle sampled from eight states was examined, based on 777 k single nucleotide polymorphism (SNP) genotypes obtained on 699 animals, with sample sizes ranging from 17 to 140 animals per breed. To date, this is the largest and most detailed assessment of the genetic diversity of Indian cattle breeds.

Results: Admixture analyses revealed that 109 of the indigenous animals analyzed had more than 1% Bos taurus admixture of relatively recent origin. Pure indigenous animals were defined as having more than 99% Bos indicus ancestry. Assessment of the genetic diversity within and between breeds using principal component analyses, F statistics, runs of homozygosity, the genomic relationship matrix, and maximum likelihood clustering based on allele frequencies revealed a low level of genetic diversity among the indigenous breeds compared to that of Bos taurus breeds. Correlations of SNP allele frequencies between breeds indicated that the genetic variation among the Bos indicus breeds was remarkably low. In addition, the variance in allele frequencies represented less than 1.5% between the Indian indigenous breeds compared to about 40% between Bos taurus dairy breeds. Effective population sizes (N_e) increased during a period post-domestication, notably for Ongole cattle, and then declined during the last 100 generations. Although we found that most of the identified runs of homozygosity are short in the Indian indigenous breeds, indicating no recent inbreeding, the high F_ROH coefficients and low F_IS values point towards small population sizes. Nonetheless, the N_e of the Indian indigenous breeds is currently still larger than that of Bos taurus dairy breeds.

Conclusions: The changes in the estimates of effective population size are consistent with domestication from a large native population followed by consolidation into breeds with a more limited population size. The surprisingly low genetic diversity among Indian indigenous cattle breeds might be due to their large N_e since their domestication, which started to decline only 100 generations ago, compared to approximately 250 to 500 generations for Bos taurus dairy cattle.

The productivity of smallholder dairy farms is very low in developing countries. Important genetic gains could be realized using genomic selection, but genetic evaluations need to be tailored for lack of pedigree information and very small farm sizes. To accommodate this situation, we propose a flexible Bayesian model for the genetic evaluation of milk yield, which allows us to simultaneously account for nongenetic random effects for farms and varying SNP variance (BayesR model). First, we used simulations based on real genotype data from Indian crossbred dairy cattle to demonstrate that the proposed model can separate the true genetic and nongenetic parameters even for small farm sizes (2 cows on average) although with high standard errors in scenarios with low heritability. The accuracy of genomic genetic evaluation increased until farm size was approximately 5. We then applied the model to real data from 4,655 crossbred cows with 106,109 monthly test day milk records and 689,750 autosomal SNPs. We estimated a heritability of 0.16 (0.04) for milk yield and using cross-validation, a genomic estimated breeding value (GEBV) accuracy of 0.45 and bias (regression of phenotype on GEBV) of 1.04 (0.26). Estimated genetic parameters were very similar using BayesR, BayesC, and genomic BLUP approaches. Candidate genes near the top variants, IMMP2L and ARHGEF2, have been previously associated with milk protein composition, mastitis resistance, and milk cholesterol content. The estimated heritability and GEBV accuracy for milk yield are much lower than those from intensive or pasture-based systems in many countries. Further increases in the number of phenotyped and genotyped animals in farms with at least 2 cows (preferably 3–5, to allow for dropout of cows) are needed to improve the estimation of genetic effects in these smallholder dairy farms.

Introduction: In India, crossbred cows incorporate the high production of B. taurus dairy breeds and the environmental adaptation of local B. indicus cattle. Adaptation to different environments and selection in milk production have shaped the genetic differences between B. indicus and B. taurus cattle. The aim of this paper was to detect, for milk yield of crossbred cows, quantitative trait loci (QTL) that differentiate B. indicus from B. taurus ancestry, as well as QTL that are segregating within the ancestral breeds.

Methods: A total of 123,042 test-day milk records for 4,968 crossbred cows, genotyped with real and imputed 770 K SNP, were used. Breed origins were assigned to haplotypes of crossbred cows, and from that, were assigned to SNP alleles.

Results: At a false discovery rate (FDR) of 30%, a large number of genomic regions showed significant effects of B. indicus versus B. taurus origin on milk yield, with positive effects coming from both ancestors. No significant regions were detected for Holstein Friesian (HF) versus Jersey effects on milk yield. Additionally, no regions for SNP alleles segregating within indigenous, within HF, and within Jersey were detected. The most significant effects, at FDR 5%, were found in a region on BTA5 (43.98–49.44 Mbp) that differentiates B. indicus from B. taurus, with an estimated difference between homozygotes of approximately 10% of average yield, in favour of B. indicus origin.

Discussion: Our results indicate that evolutionary differences between B. indicus and B. taurus cattle for milk yield, as expressed in crossbred cows, occur at many causative loci across the genome. Although subject to the usual first estimation bias, some of the loci appear to have large effects that might make them useful for genomic selection in crossbreds, if confirmed in subsequent studies.

Background: India is the largest milk producer globally, with the largest proportion of cattle milk production coming from smallholder farms with an average herd size of less than two milking cows. These cows are mainly undefined multi-generation crosses between exotic dairy breeds and indigenous Indian cattle, with no performance or pedigree recording. Therefore, implementing genetic improvement based on genetic evaluation has not yet been possible. We present the first results from a large smallholder performance recording program in India, using single nucleotide polymorphism (SNP) genotypes to estimate genetic parameters for monthly test-day (TD) milk records and to obtain and validate genomic estimated breeding values (GEBV).

Results: The average TD milk yield under the high, medium, and low production environments were 9.64, 6.88, and 4.61 kg, respectively. In the high production environment, the usual profile of a lactation curve was evident, whereas it was less evident in low and medium production environments. There was a clear trend of an increasing milk yield with an increasing Holstein Friesian (HF) proportion in the high production environment, but no increase above intermediate grades in the medium and low production environments. Trends for Jersey were small but yield estimates had a higher standard error than HF. Heritability estimates for TD yield across the lactation ranged from 0.193 to 0.250, with an average of 0.230. The additive genetic correlations between TD yield at different times in lactation were high, ranging from 0.846 to 0.998. The accuracy of phenotypic validation of GEBV from the method that is believed to be the least biased was 0.420, which was very similar to the accuracy obtained from the average prediction error variance of the GEBV.

Conclusions: The results indicate strong potential for genomic selection to improve milk production of smallholder crossbred cows in India. The performance of cows with different breed compositions can be determined in different Indian environments, which makes it possible to provide better advice to smallholder farmers on optimum breed composition for their environment.

The aim of this study was to evaluate the effect of diet and animal shearing on the feed and nutrient intakes, water intake, in vitro ruminal methane production, and blood parameters of Omani sheep. A pens trial was carried out for 16 days each in March and June of 2017 using 20 Omani non-castrated yearling rams selected from the sheep herd in the research station and randomly assigned to four groups with 5 animals per group. Group 1: sheared animals fed a high concentrate (HC) diet, group 2: fleeced animals fed a HC diet, group 3: sheared animals fed a low concentrate (LC) diet, group 4: fleeced animals fed a LC diet. Furthermore, a metabolic crates trial was carried out in July of 2017 on three animals from each group over a 10-day period. The effect of diet and shearing on the tested parameters was evaluated using the mixed linear model, where animals were fitted as a random effect to account for the individual animal deviation from the overall mean. Results showed that rams fed on the high concentrate diet had a significantly increased organic matter intake of the total diet (62 g/kg ^0.75 Live Weight (LW) in HC group to 54 g/kg ^0.75 LW in LC group), an increased water intake (6.3 L/day vs 4.8 L/day in LC group), and a reduced in vitro methane production (i.e. the invitro ruminal CH₄ was measured and converted to daily CH4 using the daily feed intake data and was 20.4 g CH₄ per head/day in HC group vs 27.3 g CH4 per head/day in LC group), compared with rams fed on the low concentrate diet. Furthermore, shearing had a significant effect (P < 0.01) on increased feed and nutrients intake. The apparent and organic matter digestibility was significantly different (P < 0.01) between the experimental groups and was greater for those rams fed on the HC diet. Partial substitution of low-quality Rhodes grass hay by high-quality concentrate significantly improved the total diet organic matter digestibility (P < 0.01) and nutrients digestibility, whereas no significant effects on biochemical blood parameters or animal health were observed. These results show the importance of utilizing effective feeding and shearing plans to improve the productivity and reduce the methane emission of Omani sheep.