Genetic evaluation of semen production potential in Indigenous bulls using random regression models in a Bayesian framework.

Genetic potential of indigenous bulls with respect to semen production traits over the age of the bulls at semen collection was analyzed using random regression models (RRMs). Data pertaining to 59,641 ejaculates from 189 bulls of 18 indigenous breeds collected from BAIF (Bharatiya Agro Industries Foundation) was utilized for this study. Six semen production traits, viz., ejaculate volume (EV, ml), sperm concentration (SC, 109/ml), initial sperm motility (ISM, %), post-thaw motility (PTM, %), the total number of spermatozoa per ejaculate (TNS, 109/ejaculate), and the theoretical number of semen doses (TNSD) were studied. Univariate and RRM were used to obtain variance components and genetic parameter estimates. Two hundred thousand Gibbs samples were generated for each trait with a burn-in of 20,000 and thinning interval of 50 in a Bayesian framework. Legendre polynomials with orders of fit up to 5 for additive and permanent environmental effects were used. RRM modeled the heritability and repeatability for all ages between 3 and 10 years (productive lifespan). Heritability estimates ranged from 0.18 to 0.36, 0.18 to 0.45, 0.02 to 0.06, 0 to 0.001, 0.09 to 0.32, and 0.14 to 0.42 while the repeatability estimates ranged from 0.41 to 0.72, 0.36 to 0.79, 0.04 to 0.10, 0 to 0.001, 0.37 to 0.56, and 0.32 to 0.57 for EV, SC, ISM, PTM, TNS, and TNSD, respectively. Variability of estimates over the age of the bulls obtained through RRM could be useful to further refine the breeding program for age at selection, deciding the production period and age at culling.

Detection of genomic regions that differentiate Bos indicus from Bos taurus ancestral breeds for milk yield in Indian crossbred cows.

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.

Genetic and non-genetic factors affecting conception rate of frozen semen in small holder dairy farmer system of rural India.

Fertility traits are as important as production traits in crossbred bovine population. Assessment of the fertility of bull in any frozen semen production program and evaluation of the conception rate under actual field conditions provide valuable information. The objective of this retrospective study was to estimate the effect of genetic and non-genetic influence on conception rate of frozen semen bulls maintained at Bharatiya Agro-Industries Foundation (BAIF) Pune based on the conception rate in cattle population of small holder dairy farmer system. The data comprising of 1,08,238 insemination records pertaining to 83 Holstein Friesian pure and crossbred bulls available at BAIF Pune were used to analyze conception rate. The fixed effect solutions and covariance components were estimated by linear mixed model using the restricted maximum likelihood method in WOMBAT software. The genetic correlations were estimated using bivariate analysis between post thaw motility and conception rate. The study was based on fertility related information from cows maintained in different villages of India and thus reflects the actual fertility of frozen semen used. The study was suggestive of influence of very small fraction of genetic effect and higher impact of management effect on conception rate. Fertility-related information available from this study is an invaluable asset in decision making process of breeding policies.

Genomic evaluation of milk yield in a smallholder crossbred dairy production system in India.

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.

Genetic diversity and effective population sizes of thirteen Indian cattle breeds.

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 (Ne) 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 FROH coefficients and low FIS values point towards small population sizes. Nonetheless, the Ne 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 Ne since their domestication, which started to decline only 100 generations ago, compared to approximately 250 to 500 generations for Bos taurus dairy cattle.

Small SNP panels for breed proportion estimation in Indian crossbred dairy cattle.

Reliably identifying breed proportions in crossbred cattle in smallholder farms is a crucial step to improve mating decisions and optimizing management in these systems. High-density genotype information is able to estimate higher-order breed proportions accurately, but, are too expensive for mass application in smallholder systems. We used high-density genotype information (777 k SNPs) of 623 crossbred cattle from India that had Holstein-Friesian (HFX) and/or Jersey and indigenous breeds in their ancestry to select a smaller number of SNPs for breed proportion estimation. The accuracy of estimates obtained from panels with 100-500 SNP was compared to estimates based on all SNPs. Panels were selected for highest absolute allele frequency difference between exotic dairy versus indigenous Bos indicus, or between HFX versus Jersey breeds. A step-wise pruning approach was developed showing that and increased physical distances between markers of 8.5 Mb improved breed proportion estimation compared to a standard 1 Mb distance. A panel of 500 SNPs optimized to estimate HFX versus Jersey versus indicine ancestry was able to estimate indicine breed proportions with r2  = .991, HFX proportions with r2  = .979 and Jersey proportions with r2  = .949. The number of markers was a deciding factor in estimation accuracy, together with the distribution of markers across the genome.

Genomics for Ruminants in Developing Countries: From Principles to Practice.

Using genomic information, local ruminant populations can be better characterized and compared to selected ones. Genetic relationships between animals can be established even without systematic pedigree recording, provided a budget is available for genotyping. Genomic selection (GS) can rely on a subset of the total population and does not require a costly national infrastructure, e.g., based on progeny testing. Yet, the use of genomic tools for animal breeding in developing countries is still limited. We identify three main reasons for this: (i) the instruments for cheap recording of phenotypes and data management are still limiting. (ii) many developing countries are recurrently exposed to unfavorable conditions (heat, diseases, poor nutrition) requiring special attention to fitness traits, (iii) a high level of expertise in quantitative genetics, modeling, and data manipulation is needed to perform genomic analyses. Yet, the potential outcomes go much beyond genetic improvements and can improve the resilience of the whole farming system. They include a better management of genetic diversity of local populations, a more balanced genetic progress and the possibility to unravel the genetic basis of adaptation of local breeds through whole genome approaches. A GS program being developed by BAIF, a large Indian NGO, is analyzed as a pilot case. It relies on the creation of a female reference population of Bos indicus and crossbreds, recorded with modern technology (e.g., smartphones) to collect performances at low cost in tiny herds on production and fertility. Finally, recommendations for the implementation of GS in developing countries are proposed.