Genetic analysis of phenotypic indicators for heat tolerance in crossbred dairy cattle.

Climate change-induced rise in global temperatures has intensified heat stress on dairy cattle and is contributing to the generally observed low milk productivity. Selective breeding aimed at enhancing animals' ability to withstand rising temperatures while maintaining optimal performance is crucial for ensuring future access to dairy products. However, phenotypic indicators of heat tolerance are yet to be effectively factored into the objectives of most selective breeding programs. This study investigated the response of milk production to changing heat load as an indication of heat tolerance and the influence of calving season on this response in multibreed dairy cattle performing in three agroecological zones Kenya. First-parity 7-day average milk yield (65 261 milk records) of 1 739 cows were analyzed. Based on routinely recorded weather data that were accessible online, the Temperature-Humidity Index (THI) was calculated and used as a measure of heat load. THI measurements used represented averages of the same 7-day periods corresponding to each 7-day average milk record. Random regression models, including reaction norm functions, were fitted to derive two resilience indicators: slope of the reaction norm (Slope) and its absolute value (Absolute), reflecting changes in milk yield in response to the varying heat loads (THI 50 and THI 80). The genetic parameters of these indicators were estimated, and their associations with average test-day milk yield were examined. There were no substantial differences in the pattern of milk yield response to heat load between cows calving in dry and wet seasons. Animals with ≤50% Bos taurus genes were the most thermotolerant at extremely high heat load levels. Animals performing in semi-arid environments exhibited the highest heat tolerance capacity. Heritability estimates for these indicators ranged from 0.06 to 0.33 and were mostly significantly different from zero (P < 0.05). Slope at THI 80 had high (0.64-0.71) negative correlations with average daily milk yield, revealing that high-producing cows are more vulnerable to heat stress and vice versa. A high (0.63-0.74) positive correlation was observed between Absolute and average milk yield at THI 80. This implied that low milk-producing cows have a more stable milk production under heat-stress conditions and vice versa. The study demonstrated that the slope of the reaction norms and its absolute value can effectively measure the resilience of crossbred dairy cattle to varying heat load conditions. The implications of these findings are valuable in improving the heat tolerance of livestock species through genetic selection.

Genomic prediction of crossbred dairy cattle in Tanzania: A route to productivity gains in smallholder dairy systems.

Selection based on genomic predictions has become the method of choice for genetic improvement in dairy cattle. This offers huge opportunity for developing countries with little or no pedigree data, and preliminary studies have shown promising results. The African Dairy Genetic Gains (ADGG) project initiated a digital system of dairy performance data collection, accompanied by genotyping in Tanzania in 2016. Currently, ADGG has the largest body of dairy performance data generated in East Africa from a smallholder dairy system. This study examines the use of genomic best linear unbiased prediction (GBLUP) and single-step (ss)GBLUP for the estimation of genetic parameters and accuracy of genomic prediction for daily milk yield and body weight in Tanzania. The estimates of heritability for daily milk yield from GBLUP and ssGBLUP were essentially the same, at 0.12 ± 0.03. The heritability estimates for daily milk yield averaged over the whole lactation from random regression model (RRM) GBLUP or ssGBLUP were 0.22 and 0.24, respectively. The heritability of body weight from GBLUP was 0.24 ± 04 but was 0.22 ± 04 from the ssGBLUP analysis. Accuracy of genomic prediction for milk yield from a forward validation was 0.57 for GBLUP based on fixed regression model or 0.55 from an RRM. Corresponding estimates from ssGBLUP were 0.59 and 0.53, respectively. Accuracy for body weight, however, was much higher at 0.83 from GBLUP and 0.77 for ssGBLUP. The moderate to high levels of accuracy of genomic prediction (0.53-0.83) obtained for milk yield and body weight indicate that selection on the basis of genomic prediction is feasible in smallholder dairy systems and most probably the only initial possible pathway to implementing sustained genetic improvement programs in such systems.

Evaluating the impact of heat stress as measured by temperature-humidity index (THI) on test-day milk yield of small holder dairy cattle in a sub-Sahara African climate.

This study evaluates the effect of heat stress on milk production and describes the pattern of response of milk yield to increasing heat load, using temperature-humidity index (THI) on test-day milk records of small holder dairy cattle herds in the sub-Saharan African climate of Tanzania. Climate data obtained from aWhere, an agricultural weather data platform (http://www.awhere.com) was analysed with 14,367 first lactation test day milk records of 3511 dairy cows collected between 2016 and 2019. THI was calculated from daily maximal temperatures and daily minimum humidity. Three sets of analysis were performed. In the first and second analysis, two mixed effect repeatability models were fitted with THI treated as a categorical variable grouped into 5 classes (THI1= [61 - 66], THI2= [67 - 71], THI3= [72 - 78], THI4=[79 - 81], THI5=[82 - 86]), to obtain least squares estimates of THI effect on milk production, and as a continuous variable within THI classes to identify THI thresholds at which milk yield started to decline. In the third analyses, one quadratic polynomial regression (POL) and three regression spline functions namely piecewise linear spline function (PLF), natural splines function (NSF) and cubic splines function (CSF) were fitted to determine the average effect of THI on milk yield in the population and describe the pattern of response of milk yield to increasing head load. The results show that heat stress reduced milk yield by 4.16% to 14.42% across THI groups, with daily milk yield being the highest in THI1 (7.40±0.39 litres) and the lowest in THI4 (6.33±0.32). Regression coefficients within groups showed significant daily milk yield decrease in THI2 (-0.09) and THI3 (-0.06), but not for other THI classes, indicating that cows experienced heat stress between THI values of 67 and 76 and milk loss plateaued afterwards, suggesting that the animals acclimatized to heat stress conditions beyond THI value of 76. At the population level, THI and its squared term were significantly negatively and positively (-0.61, 0.004) associated with milk production, indicating a non-linear relationship between milk yield and THI. The CSF model showed better goodness of fit and predictive ability than other models for predicting future population response of milk yield to heat stress in small holder dairy farms in Tanzania. Herd management strategies and animal husbandry measures are needed in small holder dairy farms in Tanzania to minimize the impact of heat stress on milk yield and income of the farmers.

Phenotypic and genetic relationships of residual feed intake measures and their component traits with fatty acid composition in subcutaneous adipose of beef cattle.

Feed efficiency is of particular interest to the beef industry because feed is the largest variable cost in production and fatty acid composition is emerging as an important trait, both economically and socially, due to the potential implications of dietary fatty acids on human health. Quantifying correlations between feed efficiency and fatty acid composition will contribute to construction of optimal multiple-trait selection indexes to maximize beef production profitability. In the present study, we estimated phenotypic and genetic correlations of feed efficiency measures including residual feed intake (RFI), RFI adjusted for final ultrasound backfat thickness (RFIf); their component traits ADG, DMI, and metabolic BW; and final ultrasound backfat thickness measured at the end of feedlot test with 25 major fatty acids in the subcutaneous adipose tissues of 1,366 finishing steers and heifers using bivariate animal models. The phenotypic correlations of RFI and RFIf with the 25 individual and grouped fatty acid traits were generally low (<0.25 in magnitude). However, relatively stronger genetic correlation coefficients of RFI and RFIf with PUFA traits including the -6:-3 ratio (0.52 ± 0.29 and 0.45 ± 0.31, respectively), 18:2-6 (0.45 ± 0.18 and 0.40 ± 0.19, respectively), -6 (0.43 ± 0.18 and 0.38 ± 0.19, respectively), PUFA (0.42 ± 0.18 and 0.36 ± 0.20, respectively), and 9-16:1 (-0.43 ± 0.20 and -0.33 ± 0.22, respectively) were observed. Hence, selection for low-RFI or more efficient beef cattle will improve fatty acid profiles by lowering the content of -6 PUFA, thus reducing the ratio of -6 to -3 along with increasing the amount of 9-16:1. Moderate to moderately high genetic correlations were also observed for DMI with 9-14:1 (-0.32 ± 0.17) and the sum of CLA analyzed (SumCLA; -0.45 ± 0.21), suggesting that selection of beef cattle with lower DMI will lead to an increase amount of 9-14:1 and SumCLA in the subcutaneous adipose tissue. However, unfavorable genetic correlations were detected for ADG with 11-18:1 (-0.38 ± 0.23) and SumCLA (-0.73 ± 0.26), implying that selection of beef cattle with a better growth rate will decrease the contents of healthy fatty acids 11-18:1 and SumCLA. Therefore, it is recommended that a multiple-trait selection index be used when genetic improvements of fatty acid composition, feed efficiency, feed intake, and growth are important in the breeding objective.

Phenotypic and genetic correlations of fatty acid composition in subcutaneous adipose tissue with carcass merit and meat tenderness traits in Canadian beef cattle.

Bivariate animal models were used to estimate phenotypic and genetic correlations between 9 carcass merit and meat tenderness traits with 25 individual and grouped fatty acids in the subcutaneous adipose tissue of a population of 1,366 Canadian beef cattle finishing heifers and steers. In general, phenotypic correlations were low (<0.25 in magnitude) except for moderate phenotypic correlations of 9-17:1 (-0.29 ± 0.16), 18:0 (0.26 ± 0.14), 11-18:1 (-0.33 ± 0.15), 11-18:1 (0.35 ± 0.14) with Warner-Bratzler shear force measured 3 d postmortem and between 14:0 (-0.36 ± 0.1), 9-14:1 (-0.34 ± 0.08), 9-16:1 (-0.36 ± 0.08), 9-18:1 (0.26 ± 0.07), and sum of branched-chain fatty acids (BCFA; -0.27 ± 0.06) and back fat thickness (BFAT). Genetic correlations were also low for most of the traits. However, moderate to moderately high genetic correlations (0.25 to 0.50 in magnitude) were detected for some traits, including 17:0 (0.4 ± 0.11), 18:0 (0.44 ± 0.12), 9-14:1 (-0.47 ± 0.11), 9-16:1 (-0.43 ± 0.11), and the -6:-3 PUFA ratio (-0.5 ± 0.15) with HCW; 9-14:1 (-0.41 ± 0.13) and 9-16:1 (-0.42 ± 0.13) with BFAT; 17:0 (0.43 ± 0.19) and BCFA (0.45 ± 0.19) with lean meat yield; 13-18:1 (0.40 ± 0.15) with carcass marbling score; sum of CLA (0.45 ± 0.22), 18:2-6 (0.47 ± 0.17), and sum of PUFA (0.48 ± 0.17) with overall tenderness measured 3 d postmortem; the -6:-3 PUFA ratio (0.41 ± 0.22) and sum of CLA (0.42 ± 0.25) with overall tenderness measured 29 d postmortem; and BCFA (0.41 ± 0.27) with Warner-Bratzler shear force measured 29 d postmortem. The genetic correlations observed in this study suggest that contents of some fatty acids in beef tissue and carcass merit and meat tenderness traits are likely influenced by a subset of the same genes in beef cattle. Due to some antagonistic genetic correlations, multiple-trait economic indexes are recommended when fatty acid composition, carcass merit, and meat tenderness traits are included in the breeding objective.

Estimates of genetic parameters for fatty acids in brisket adipose tissue of Canadian commercial crossbred beef steers.

Heritability and genetic and phenotypic correlations between 15 individuals and 10 groups of fatty acids with a concentration greater than 0.5% in the brisket adipose tissue of 223 Angus and Charolais based crossbred commercial steers were estimated using univariate and bivariate animal models. Individual saturated fatty acids were low to moderately heritable, with heritability estimates ranging from 0.05 (C16:0) to 0.31 (C15:0). Individual monounsaturated fatty acids were low to moderately highly heritable ranging from 0.04 (9c C17:1 and 11c C18:1) to 0.51 (9c C14:1). Polyunsaturated fatty acid C18:2n-6 was moderately heritable (0.17). Among groups of fatty acids, heritability estimates ranged from 0.03 for branched chain fatty acid (BCFA) and n-6/n-3 to 0.16 for n-6 and Health Index. A range of low (0.00) to high (1.00) phenotypic and genetic correlations was observed among the 25 fatty acids considered in this study. In general, fatty acids such as conjugated linoleic acid (CLA) and 11t C18:1, with potential health benefits, showed significant antagonistic correlations with unhealthy fatty acids such as C14:0 and C16:0. The results from this study provide insight into the direct genetic control of host genes on fatty acid composition of beef tissues and will facilitate designs of genetic selection and/or genetic based diet management to improve fatty acid composition in beef cattle.