Assessing different metrics of pedigree and genomic inbreeding and inbreeding effect on growth, fertility, and feed efficiency traits in a closed-herd Nellore cattle population.

BACKGROUND: The selection of individuals based on their predicted breeding values and mating of related individuals can increase the proportion of identical-by-descent alleles. In this context, the objectives of this study were to estimate inbreeding coefficients based on alternative metrics and data sources such as pedigree (FPED), hybrid genomic relationship matrix H (FH), and ROH of different length (FROH); and calculate Pearson correlations between the different metrics in a closed Nellore cattle population selected for body weight adjusted to 378 days of age (W378). In addition to total FROH (all classes) coefficients were also estimated based on the size class of the ROH segments: FROH1 (1-2 Mb), FROH2 (2-4 Mb), FROH3 (4-8 Mb), FROH4 (8-16 Mb), and FROH5 (> 16 Mb), and for each chromosome (FROH_CHR). Furthermore, we assessed the effect of each inbreeding metric on birth weight (BW), body weights adjusted to 210 (W210) and W378, scrotal circumference (SC), and residual feed intake (RFI). We also evaluated the chromosome-specific effects of inbreeding on growth traits. RESULTS: The correlation between FPED and FROH was 0.60 while between FH and FROH and FH and FPED were 0.69 and 0.61, respectively. The annual rate of inbreeding was 0.16% for FPED, 0.02% for FH, and 0.16% for FROH. A 1% increase in FROH5 resulted in a reduction of up to -1.327 ± 0.495 kg in W210 and W378. Four inbreeding coefficients (FPED, FH, FROH2, and FROH5) had a significant effect on W378, with reductions of up to -3.810 ± 1.753 kg per 1% increase in FROH2. There was an unfavorable effect of FPED on RFI (0.01 ± 0.0002 kg dry matter/day) and of FROH on SC (-0.056 ± 0.022 cm). The FROH_CHR coefficients calculated for BTA3, BTA5, and BTA8 significantly affected the growth traits. CONCLUSIONS: Inbreeding depression was observed for all traits evaluated. However, these effects were greater for the criterion used for selection of the animals (i.e., W378). The increase in the genomic inbreeding was associated with a higher inbreeding depression on the traits evaluated when compared to pedigree-based inbreeding. Genomic information should be used as a tool during mating to optimize control of inbreeding and, consequently, minimize inbreeding depression in Nellore cattle.

Benchmarking machine learning and parametric methods for genomic prediction of feed efficiency-related traits in Nellore cattle.

Genomic selection (GS) offers a promising opportunity for selecting more efficient animals to use consumed energy for maintenance and growth functions, impacting profitability and environmental sustainability. Here, we compared the prediction accuracy of multi-layer neural network (MLNN) and support vector regression (SVR) against single-trait (STGBLUP), multi-trait genomic best linear unbiased prediction (MTGBLUP), and Bayesian regression (BayesA, BayesB, BayesC, BRR, and BLasso) for feed efficiency (FE) traits. FE-related traits were measured in 1156 Nellore cattle from an experimental breeding program genotyped for ~ 300 K markers after quality control. Prediction accuracy (Acc) was evaluated using a forward validation splitting the dataset based on birth year, considering the phenotypes adjusted for the fixed effects and covariates as pseudo-phenotypes. The MLNN and SVR approaches were trained by randomly splitting the training population into fivefold to select the best hyperparameters. The results show that the machine learning methods (MLNN and SVR) and MTGBLUP outperformed STGBLUP and the Bayesian regression approaches, increasing the Acc by approximately 8.9%, 14.6%, and 13.7% using MLNN, SVR, and MTGBLUP, respectively. Acc for SVR and MTGBLUP were slightly different, ranging from 0.62 to 0.69 and 0.62 to 0.68, respectively, with empirically unbiased for both models (0.97 and 1.09). Our results indicated that SVR and MTGBLUBP approaches were more accurate in predicting FE-related traits than Bayesian regression and STGBLUP and seemed competitive for GS of complex phenotypes with various degrees of inheritance.

Genotype by Prenatal Environment Interaction for Postnatal Growth of Nelore Beef Cattle Raised under Tropical Grazing Conditions.

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.

Meta-analysis across Nellore cattle populations identifies common metabolic mechanisms that regulate feed efficiency-related traits.

BACKGROUND: Feed efficiency (FE) related traits play a key role in the economy and sustainability of beef cattle production systems. The accurate knowledge of the physiologic background for FE-related traits can help the development of more efficient selection strategies for them. Hence, multi-trait weighted GWAS (MTwGWAS) and meta-analyze were used to find genomic regions associated with average daily gain (ADG), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), and residual feed intake (RFI). The FE-related traits and genomic information belong to two breeding programs that perform the FE test at different ages: post-weaning (1,024 animals IZ population) and post-yearling (918 animals for the QLT population). RESULTS: The meta-analyze MTwGWAS identified 14 genomic regions (-log10(p -value) > 5) regions mapped on BTA 1, 2, 3, 4, 7, 8, 11, 14, 15, 18, 21, and 29. These regions explained a large proportion of the total genetic variance for FE-related traits across-population ranging from 20% (FCR) to 36% (DMI) in the IZ population and from 22% (RFI) to 28% (ADG) in the QLT population. Relevant candidate genes within these regions (LIPE, LPL, IGF1R, IGF1, IGFBP5, IGF2, INS, INSR, LEPR, LEPROT, POMC, NPY, AGRP, TGFB1, GHSR, JAK1, LYN, MOS, PLAG1, CHCD7, LCAT, and PLA2G15) highlighted that the physiological mechanisms related to neuropeptides and the metabolic signals controlling the body's energy balance are responsible for leading to greater feed efficiency. Integrated meta-analysis results and functional pathway enrichment analysis highlighted the major effect of biological functions linked to energy, lipid metabolism, and hormone signaling that mediates the effects of peptide signals in the hypothalamus and whole-body energy homeostasis affecting the genetic control of FE-related traits in Nellore cattle. CONCLUSIONS: Genes and pathways associated with common signals for feed efficiency-related traits provide better knowledge about regions with biological relevance in physiological mechanisms associated with differences in energy metabolism and hypothalamus signaling. These pleiotropic regions would support the selection for feed efficiency-related traits, incorporating and pondering causal variations assigning prior weights in genomic selection approaches.

Effect of high temperature on physiological parameters of Nelore (Bos taurus indicus) and Caracu (Bos taurus taurus) cattle breeds.

The climate-related problems that affect animal production in tropical countries have encouraged seeking solutions to increase herd productivity and one alternative is the use of breeds adapted to high-temperature environments. The objective of this study was to evaluate the effect of temperature on 77 Caracu and Nelore males submitted to three different environments: morning period (8:00 to 10:00 AM), afternoon in the sun, and afternoon in a shaded environment (11:00 AM to 1:00 PM). The following physiological parameters were measured in each treatment: heart and respiration rates, rectal and dorsal surface temperatures, and cortisol level. The data were analyzed with the MIXED procedure (SAS) and the model included the fixed effects of treatment (morning, sun, and shade), breed (Nelore and Caracu), month of measurement (December and February), and the interaction between effects. A higher dorsal surface temperature was observed in animals of both breeds in the sun treatment compared with the shade treatment. Caracu animals had a higher dorsal surface temperature than Nelore animals, which probably caused the higher rectal temperature observed in the sun treatment compared with the shade treatment in both breeds over the 2 months of the study. All physiological parameters measured in this study were efficient to detect the thermal stress in both breeds. Despite the variations in rectal temperature observed during the treatments, the animals of the two breeds exhibited no significant changes in heart rate, respiration rate, and cortisol level for the maintenance of thermal homeostasis. In conclusion, both breeds were considered tolerant to sun exposure, demonstrating adaptation of these animals to high-temperature environments, without evidence of harm to its health and welfare.

Evidence of negative relationship between female fertility and feed efficiency in Nellore cattle.

The objective of this study was to evaluate phenotypic and genetic relationships between fertility traits and feed efficiency in male and female Nellore cattle. Data from 320 females born between 2004 and 2011 were used for phenotypic evaluation. These animals were evaluated for postweaning residual feed intake (RFI) and classified as negative (RFI < 0, mean = -0.294 ± 0.017 kg DM/d) or positive RFI (RFI > 0, mean = 0.305 ± 0.0189 kg DM/d). Of these, 118 prepuberal heifers were submitted to ultrasonography of the uterus and ovaries for monitoring the presence (or absence) of a corpus luteum and for the measurement of endometrial thickness. The following fertility traits were evaluated in all females: age at first calving, days to calving, first calving interval, calving success, stayability, and longevity. The variance components were estimated by the average information restricted maximum likelihood method under an animal model in 5-trait analysis of backfat and rump fat thickness, scrotal circumference, days to calving, and RFI. The total number of animals with records was 6,718, including 927 males with records of scrotal circumference and RFI and 264 females with records of days to calving and RFI. Negative RFI females consumed 12.5% less DM daily than positive RFI females and had a lower rump fat thickness when evaluated postweaning. Among the fertility traits studied, only first calving interval differed (P = 0.0858) between RFI classes, with the interval of negative RFI females being 45 d shorter than that of positive RFI animals. The heritability estimates were 0.29, 0.34, 0.50, 0.12, and 0.16 for backfat and rump fat thickness, scrotal circumference, days to calving, and RFI, respectively. The genetic correlations between RFI and the other traits studied were unfavorable for selection and were of moderate magnitude with backfat thickness, rump fat thickness, and days to calving (0.53, 0.37, and -0.49, respectively) and close to zero with scrotal circumference (0.07). Scrotal circumference (0.17 and 0.15) and days to calving (-0.10 and -0.22) were weakly and favorably correlated with backfat and rump fat thickness. There is evidence of moderate genetic antagonism between female fertility and feed efficiency, but with no evidence of a genetic correlation between male fertility and feed efficiency. There is also evidence of low genetic synergism between fat thickness and fertility.