Heat stress adaptation in cows - Physiological responses and underlying molecular mechanisms.

Heat stress is a key abiotic stressor for dairy production in the tropics which is further compounded by the ongoing climate change. Heat stress not only adversely impacts the production and welfare of dairy cows but severely impacts the economics of dairying due to production losses and increased cost of rearing. Over the years, selection has ensured development of high producing breeds, however, the thermotolerance ability of animals has been largely overlooked. In the past decade, the ill effects of climate change have made it pertinent to rethink the selection strategies to opt for climate resilient breeds, to ensure optimum production and reproduction. This has led to renewed interest in evaluation of the impacts of heat stress on cows and the underlying mechanisms that results in their acclimatization and adaptation to varied thermal ambience. The understanding of heat stress and associated responses at various level of animal is crucial to device amelioration strategies to secure optimum production and welfare of cows. With this review, an effort has been made to provide an overview on temperature humidity index as an important indicator of heat stress, general effect of heat stress in dairy cows, and impact of heat stress and subsequent response at physiological, haematological, molecular and genetic level of dairy cows.

Bayesian estimates for genetic and phenotypic parameters of growth traits in Sahiwal cattle.

Analyses were carried out for the estimation of (co)variance components and genetic parameters for birth weight (BWT), 6-month weight (6WT), 12-month weight (12WT), 18-month weight (18WT), 24-month weight (24WT), 30-month weight (30WT), 36-month weight (36WT), weight at first service (WFS), and weight at first calving(WFC) in Sahiwal cattle. Data for 802 lifetime records (raw data) were collected over a period of 30 years (1990-2019) for various growth traits in the herd for Sahiwal cows maintained at the livestock farm unit of ICAR-NDRI Karnal, Haryana, India. Bayesian estimates using the multi-trait Gibbs sampling animal model approach were calculated in the present study. Total heritability for BWT, 6WT, 12WT, 18WT, 24WT, 30WT, 36WT, WFS, and WFC by Bayesian modeling was estimated as 0.22 ± 0.0052, 0.47 ± 0.0037, 0.30 ± 0.0025, 0.65 ± 0.0021, 0.32 ± 0.0039, 0.33 ± 0.0027, 0.39 ± 0.0031, 0.49 ± 0.0020, and 0.57 ± 0.0023, respectively, along with its Monte Carlo error in Sahiwal cattle. Direct genetic covariances between body weight traits were ranging from - 2762.5 for 18WT and WFC to 4739.6 between WFS and WFC. Environmental covariances were ranging from - 169.98 for 30WT and 36WT to 4539.4 between WFS and WFC. Family relationships as well as the existing interaction effects between two or more traits in opposite direction effect lead to negative estimates for genetic covariances between some of the combinations with various growth traits. Although most of the estimates for posteriori were somewhat skewed, the marginalization effect enabled them to fit into the Gaussian distribution, by comparing the mean, mode, and median with each other. Results suggest that genetic progress through growth traits can be achieved if the selection is carried out for highly heritable 18-month weight as well as for the selection of pubertal and fertility traits, viz., 24WT, 30WT, 36WT, WFS, and WFC with a balanced feeding and optimum management.

Comparative genetic analysis of frequentist and Bayesian approach for reproduction, production and life time traits showing favourable association of age at first calving in Tharparkar cattle.

OBJECTIVE: The present study was aimed primarily for estimating various genetic parameters (heritability, genetic correlations) of reproduction (age at first calving [AFC], first service period [FSP]); production (first lactation milk, solid-not fat, and fat yield) and lifetime traits (lifetime milk yield, productive life [PL], herd life [HL]) in Tharparkar cattle to check the association of reproduction traits with lifetime traits through two different methods (Frequentist and Bayesian) for comparative purpose. METHODS: Animal breeding data of Tharparkar cattle (n = 964) collected from Livestock farm unit of ICAR-NDRI Karnal for the period 1990 through 2019 were analyzed using a Frequentist least squares maximum likelihood method (LSML; Harvey, 1990) and a multitrait Bayesian-Gibbs sampler approach (MTGSAM) for genetic correlations estimation of all the traits. Estimated breeding values of sires was obtained by BLUP and Bayesian analysis for the production traits. RESULTS: Heritability estimates of most of the traits were medium to high with the LSML (0.20±0.44 to 0.49±0.71) and Bayesian approach (0.24±0.009 to 0.61±0.017), respectively. However, more reliable estimates were obtained using the Bayesian technique. A higher heritability estimate was obtained for AFC (0.61±0.017) followed by first lactation fat yield, first lactation solid-not fat yield, FSP, first lactation milk yield (FLMY), PL (0.60±0.013, 0.60±0.006, 0.57±0.024, 0.57±0.020, 0.42±0.025); while a lower estimate for HL (0.38±0.034) by MTGSAM approach. Genetic and phenotypic correlations were negative for AFC-PL, AFC-HL, FSP-PL, and FSP-HL (-0.59±0.19, -0.59±0.24, -0.38±0.101 and -0.34±0.076) by the multi-trait Bayesian analysis. CONCLUSION: Breed and traits of economic importance are important for selection decisions to ensure genetic gain in cattle breeding programs. Favourable genetic and phenotypic correlations of AFC with production and lifetime traits compared to that of FSP indicated better scope of AFC for indirect selection of life-time traits at an early age. This also indicated that the present Tharparkar cattle herd had sufficient genetic diversity through the selection of AFC for the improvement of first lactation production and lifetime traits.

Comparative assessment of the effective population size and linkage disequilibrium of Karan fries composite cattle revealed viable population dynamics.

Objective: Karan Fries (KF), a high-producing composite cattle was developed through crossing indicine Tharparkar cows with taurine bulls (Holstein Friesian, Brown Swiss, and Jersey), to increase the milk yield across India. This composite cattle population must maintain sufficient genetic diversity for long-term development and breed improvement in the coming years. The level of Linkage disequilibrium (LD) measures the influence of population genetic forces on the genomic structure and provides insights into the evolutionary history of populations, while the decay of LD is important in understanding the limits of genome-wide association studies for a population. Effective population size (Ne) which is genomically based on LD accumulated over the course of previous generations, is a valuable tool for evaluation of the genetic diversity and level of inbreeding. The present study was undertaken to understand KF population dynamics through the estimation of Ne and LD for the long-term sustainability of these breeds. Methods: The present study included 96 KF samples genotyped using Illumina HDBovine array to estimate the effective population and examine the LD pattern. The genotype data were also obtained for other crossbreds (Santa Gertrudis, Brangus, and Beefmaster) and Holstein Friesian cattle for comparison purposes. Results: The average LD between SNPs was r2 = 0.13 in the present study. LD decay (r2 = 0.2) was observed at 40 kb inter-marker distance, indicating a panel with 62765 SNPs was sufficient for genomic breeding value estimation in KF cattle. The pedigree-based effective population size (Ne) of KF was determined to be 78, while the Ne estimates obtained using LD-based methods were 52 (SNeP) and 219 (Genetic Optimization for Ne Estimation - GONE), respectively. Conclusion: KF cattle have an effective population size (Ne) exceeding the FAO's minimum recommended level of 50, which was desirable. The study also revealed significant population dynamics of KF cattle and increased our understanding of devising suitable breeding strategies for long-term sustainable development.