Novel insights into genome-wide associations in Bos indicus reveal genetic linkages between fertility and growth.

Bos indicus breed Sahiwal, famous for its optimum performance, has so far been genetically improved for performance traits based on phenotypic records and the genomic knowhow regarding genes, regions and biological processes underlying the complex quantitative traits is lacking. In this context, a Genome-wide Association Study was performed for fertility and growth traits in Sahiwal cattle to shed light on its genomic profile. A total of 46 SNPs were found associated with the traits at genome-wide suggestive threshold of P ≤ 10-4. USP32, LRPPRC, PLA2G10, RRN3 and ASAP1 were identified as putative candidate genes for body weight at different ages. However, several genes mapped for growth traits like GREB1, PLA2G10, RAD51C, BIRC6, TEX14 and PEBP4 had significant physiological underpinnings in determining fertility of the animals. Moreover, Quantitative trait loci (QTL) identification revealed potential overlaps with the already reported QTLs for both fertility and growth for most of the traits. Further, candidate SNP enrichment analysis revealed an enriched biological process for birth weight with a significant reproductive role. Based on the findings, genetic linkages underlying fertility and growth could be discerned in Sahiwal population and may be utilized for improving fertility traits in future.

Genetic aspects of Wood's lactation curve parameters in Jersey crossbred cattle using Bayesian approach.

The study was undertaken to estimate the genetic parameters of lactation curve parameters of Wood's function in Jersey crossbred cattle using the Bayesian approach. Data on 33,906 fortnightly test day milk yields of 1,718 lactation records of Jersey crossbred cows, maintained at the ICAR-National Dairy Research Institute in West Bengal, were collected over a period of 40 years. The lactation curve parameters including 'a' (initial milk yield after calving), 'b' (ascending slope up to peak yield) and 'c' (descending slope after peak yield) and lactation curve traits, peak yield (ymax), time of peak yield (tmax) and persistency of milk yield (P) of individual cow for each lactation were estimated using the incomplete gamma function (Wood's model) by fitting the Gauss-Newton algorithm as an iteration method using PROC NLIN procedure of SAS 9.3. Variance components and genetic parameters of lactation curve parameters/traits were estimated by a repeatability animal model using the Bayesian approach. Estimates of heritabilities were found to be 0.18 ± 0.05, 0.09 ± 0.03 and 0.11 ± 0.04 for parameters 'a', 'b' and 'c', respectively and 0.24 ± 0.05, 0.12 ± 0.04, and 0.15 ± 0.05 for ymax, tmax and P, respectively. Repeatability estimates were 0.31 ± 0.03, 0.21 ± 0.04 and 0.30 ± 0.04 for parameters 'a', 'b' and 'c' respectively and 0.39 ± 0.03, 0.24 ± 0.03 and 0.37 ± 0.03 for ymax, tmax and p, respectively. Genetic correlations among lactation curve parameters/traits ranged from -0.75 to 0.95. Existence of genetic correlations among lactation curve parameters/traits indicated substantial genetic and physiological relationships among lactation curve parameters/traits of Jersey crossbred cattle.

Understanding the genomic architecture of clinical mastitis in Bos indicus.

This study elucidated potential genetic variants and QTLs associated with clinical mastitis incidence traits in Bos indicus breed, Sahiwal. Estimated breeding values for the traits (calculated using Bayesian inference) were used as pseudo-phenotypes for association with genome-wide SNPs and further QTL regions underlying the traits were identified. In all, 25 SNPs were found to be associated with the traits at the genome-wide suggestive threshold (p ≤ 5 × 10-4) and these SNPs were used to define QTL boundaries based on the linkage disequilibrium structure. A total of 16 QTLs were associated with the trait EBVs including seven each for clinical mastitis incidence (CMI) in first and second lactations and two for CMI in third lactation. Nine out of sixteen QTLs overlapped with the already reported QTLs for mastitis traits, whereas seven were adjudged as novel ones. Important candidates for clinical mastitis in the identified QTL regions included DNAJB9, ELMO1, ARHGAP26, NR3C1, CACNB2, RAB4A, GRB2, NUP85, SUMO2, RBPJ, and RAB33B genes. These findings shed light on the genetic architecture of the disease in Bos indicus, and present potential regions for fine mapping and downstream analysis in future.

Genome-Wide Association Studies in Indian Buffalo Revealed Genomic Regions for Lactation and Fertility.

Murrah breed of buffalo is an excellent dairy germplasm known for its superior milk quality in terms of milk fat and solids-not-fat (SNF); however, it is often reported that Indian buffaloes had lower lactation and fertility potential compared to the non-native cattle of the country. Recent techniques, particularly the genome-wide association studies (GWAS), to identify genomic variations associated with lactation and fertility traits offer prospects for systematic improvement of buffalo. DNA samples were sequenced using the double-digestion restriction-associated DNA (RAD) tag genotyping-by-sequencing. The bioinformatics pipeline was standardized to call the variants, and single-nucleotide polymorphisms (SNPs) qualifying the stringent quality check measures were retained for GWAS. Over 38,000 SNPs were used to perform GWAS on the first two principal components of test-day records of milk yields, fat percentages, and SNF percentages, separately. GWAS was also performed on 305 days' milk yield; lactation persistency was estimated through the rate of decline after attaining the peak yield method, along with three other standard methods; and breeding efficiency, post-partum breeding interval, and age at sexual maturity were considered fertility traits. Significant association of SNPs was observed for the first principal component, explaining the maximum proportion of variation in milk yield. Furthermore, some potential genomic regions were identified to have a potential role in regulating milk yield and fertility in Murrah. Identification of such genomic regions shall help in carrying out an early selection of high-yielding persistent Murrah buffaloes and, in the long run, would be helpful in shaping their future genetic improvement programs.