This study aimed at (1) assessing the genomic stratification of experimental lines of Nelore cattle that have experienced different selection regimes for growth traits, and (2) identifying genomic regions that have undergone recent selection. We used a sample of 763 animals genotyped with the Illumina BovineHD BeadChip, among which 674 animals originated from two lines that are maintained under directional selection for increased yearling body weight and 89 animals from a control line that is maintained under stabilizing selection. Multidimensional analysis of the genomic dissimilarity matrix and admixture analysis revealed a substantial level of population stratification between the directional selection lines and the stabilizing selection control line. Two of the three tests used to detect selection signatures (FST, XP-EHH and iHS) revealed six candidate regions with indications of selection, which strongly indicates truly positive signals. The set of identified candidate genes included several genes with roles that are functionally related to growth metabolism, such as COL14A1, CPT1C, CRH, TBC1D1, and XKR4. The current study identified genetic stratification that resulted from almost four decades of divergent selection in an experimental Nelore population, and highlighted autosomal genomic regions that present patterns of recent selection. Our findings provide a basis for a better understanding of the metabolic mechanism that underlies the growth traits, which are modified by selection for yearling body weight.

The prenatal environment is recognized as crucial for the postnatal performance in cattle. In tropical regions, pregnant beef cows commonly experience nutritional restriction during the second half of the gestation period. Thus, the present study was designed to analyze the genotype by prenatal environment interaction (G × Epn) and to identify genomic regions associated with the level and response in growth and reproduction-related traits of beef cattle to changes in the prenatal environment. A reaction norm model was applied to data from two Nelore herds using the solutions of contemporary groups for birth weight as a descriptor variable of the gestational environment quality. A better gestational environment favored weights until weaning, scrotal circumference at yearling, and days to first calving of the offspring. The G × Epn was strong enough to result in heterogeneity of variance components and genetic parameters in addition to reranking of estimated breeding values and SNPs effects. Several genomic regions associated with the level of performance and specific responses of the animals to variations in the gestational environment were revealed, which harbor QTLs and can be exploited for selection purposes. Therefore, genetic evaluation models considering G × Epn and special management and nutrition care for pregnant cows are recommended.

The present study aimed to evaluate the effects of immunocastration on the animal growth, carcass traits, and meat quality of Nellore cattle receiving or not Ionophore supplementation at pasture or pasture with concentrate (semi-feedlot). The first experiment (Pasture) was carried out during the rainy season, while the second (supplemented = Semi-feedlot) was conducted during the dry season. In each assessment, 60 males were allocated into three treatments, in a completely randomized design: non-castrated, immunocastrated (anti-gonadotropin-releasing hormone vaccine), and immunocastrated animals receiving ionophore. The highly energetic supplemented diet was prepared using 85 % corn and 10 % soybean meal at 1 % body weight, while the ionophore was provided with salt containing 1,650 mg kg−1 of lasalocid. After slaughter, the carcasses were graded, and Longissimus thoracis et lumborum samples were collected for meat quality analysis. The non-castrated animals exhibited a more significant final body weight and hot carcass weight than those immunocastrated regardless of ionophore supplementation (p < 0.05). The carcasses of non-castrated animals had less fat cover and marbling than castrated animals. A high incidence of dark cutting beef was verified in non-castrated animals. The immunocastrated cattle produced tenderer beef, mainly at pasture rearing. In conclusion, regardless of production system or ionophore supplementation, immunocastration was an adequate choice to generate high-quality meat, since it increased marbling and improved beef tenderness. However, limitations regarding animal growth should be estimated.

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.