Genetic Parameters of Resilience Indicators Across Growth in Beef Heifers and Their Associations With Weight, Reproduction, Calf Performance and Pre-Weaning Survival

肉牛小母牛生长过程中韧性指标的遗传参数及其与体重、繁殖、犊牛性能和断奶前存活率的关系

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Abstract

In tropical extensive beef cattle systems, heifers raised on pasture are exposed to various environmental challenges that affect their growth and reproductive performance during the first breeding. Resilience indicators derived from deviations in longitudinal traits can quantify the magnitude of these challenges and the ability of an animal to recover after disturbances. Hence, this study aimed to estimate genetic parameters for resilience indicators derived from weight deviations across growth in Nellore heifers, and their genetic correlations with yearling weight (YW), reproductive traits, calf performance and pre-weaning survival (PWS(c)). Phenotypic records were available for 3072 heifers, while 3226 animals were genotyped with 383,856 SNP markers (after quality control). A total of 30,720 weight records were used for growth curve modelling across three developmental phases: yearling, first breeding and first calf weaning. The resilience indicators derived and analysed were as follows: (i) natural logarithm of residual variance (LnVar); (ii) lag(-1) autocorrelation of residuals (r(auto)); and (iii) skewness of residuals. The weight, reproductive, calf performance and survival traits analysed were as follows: YW, weight at the beginning of the breeding season (WBS), heifer pregnancy (HP), calves birth weight (BW(c)), calves weaning weight (WW(c)), calves average daily gain from birth to weaning (ADG(c)) and PWS(c). Genetic parameters were estimated using the ssGBLUP method under a Bayesian framework. Heritability estimates (h(2)) were highest for LnVar, ranging from 0.32 ± 0.03 (calf weaning) to 0.42 ± 0.03 (breeding). Moderate h(2) values were observed for r(auto) (0.22 ± 0.03 to 0.29 ± 0.03), whereas skewness had low heritability (0.08 ± 0.02 to 0.13 ± 0.02). Genetic correlations (r(g)) between LnVar and weight traits were unfavourable. In contrast, r(auto) exhibited favourable correlations with YW (-0.29 ± 0.08 to -0.50 ± 0.08). LnVar at breeding showed favourable and moderate r(g) with HP (-0.37 ± 0.10). All resilience indicators were favourably correlated with PWS(c), with the strongest estimate observed for LnVar at calf weaning (-0.28 ± 0.15). These findings provide novel insights into the genetic basis of resilience in growing beef heifers. LnVar and r(auto), in particular, emerge as promising traits for selecting animals better adapted to environmental variability. Additionally, favourable genetic correlations with fertility and survival traits suggest that more resilient heifers are more likely to become pregnant during their first breeding season and raise calves with higher survival rates until weaning.

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