Dataset Information

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle.

ABSTRACT: Nelore is the most economically important cattle breed in Brazil, and the use of genetically improved animals has contributed to increased beef production efficiency. The Brazilian beef feedlot industry has grown considerably in the last decade, so the selection of animals with higher growth rates on feedlot has become quite important. Genomic selection (GS) could be used to reduce generation intervals and improve the rate of genetic gains. The aim of this study was to evaluate the prediction of genomic-estimated breeding values (GEBV) for average daily weight gain (ADG) in 718 feedlot-finished Nelore steers. Analyses of three Bayesian model specifications [Bayesian GBLUP (BGBLUP), BayesA, and BayesC?] were performed with four genotype panels [Illumina BovineHD BeadChip, TagSNPs, and GeneSeek High- and Low-density indicus (HDi and LDi, respectively)]. Estimates of Pearson correlations, regression coefficients, and mean squared errors were used to assess accuracy and bias of predictions. Overall, the BayesC? model resulted in less biased predictions. Accuracies ranged from 0.18 to 0.27, which are reasonable values given the heritability estimates (from 0.40 to 0.44) and sample size (568 animals in the training population). Furthermore, results from Bos taurus indicus panels were as informative as those from Illumina BovineHD, indicating that they could be used to implement GS at lower costs.

SUBMITTER: Somavilla AL

PROVIDER: S-EPMC5473763 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle.

Somavilla Adriana L AL Somavilla Adriana L AL Regitano Luciana C A LCA Rosa Guilherme J M GJM Mokry Fabiana B FB Mudadu Mauricio A MA Tizioto Polyana C PC Oliveira Priscila S N PSN Souza Marcela M MM Coutinho Luiz L LL Munari Danísio P DP

G3 (Bethesda, Md.) 20170607 6

Nelore is the most economically important cattle breed in Brazil, and the use of genetically improved animals has contributed to increased beef production efficiency. The Brazilian beef feedlot industry has grown considerably in the last decade, so the selection of animals with higher growth rates on feedlot has become quite important. Genomic selection (GS) could be used to reduce generation intervals and improve the rate of genetic gains. The aim of this study was to evaluate the prediction of ...[more]

PMID: 28391242

Similar Datasets

Project description:BackgroundBackgrounding (BKG), the stage between weaning and finishing, significantly impacts feedlot performance in beef cattle; however, the contributions of the rumen microbiome to this growth stage remain unexplored. A longitudinal study was designed to assess how BKG affects rumen bacterial communities and average daily gain (ADG) in beef cattle. At weaning, 38 calves were randomly assigned to three BKG systems for 55 days (d): a high roughage diet within a dry lot (DL, n = 13); annual cover crop within a strip plot (CC, n = 13); and perennial pasture vegetation within rotational paddocks (PP, n = 12), as before weaning. After BKG, all calves were placed in a feedlot for 142 d and finished with a high energy ration. Calves were weighed periodically from weaning to finishing to determine ADG. Rumen bacterial communities were profiled by collecting fluid samples via oral probe and sequencing the V4 region of the 16S rRNA bacterial gene, at weaning, during BKG and finishing.ResultsRumen bacterial communities diverged drastically among calves once they were placed in each BKG system, including sharp decreases in alpha diversity for CC and DL calves only (P < 0.001). During BKG, DL calves showed a substantial increase of Proteobacteria (Succinivibrionaceae family) (P < 0.001), which also corresponded with greater ADG (P < 0.05). At the finishing stage, Proteobacteria bloomed for all calves, with no previous alpha or beta diversity differences being retained between groups. However, at finishing, PP calves showed a compensatory ADG, particularly greater than that in calves coming from DL BKG (P = 0.02). Microbiome network traits such as lower average shortest path length, and increased neighbor connectivity, degree, number and strength of bacterial interactions between rumen bacteria better predicted ADG during BKG and finishing than variation in specific taxonomic profiles.ConclusionsBacterial co-abundance interactions, as measured by network theory approaches, better predicted growth performance in beef cattle during BKG and finishing, than the abundance of specific taxa. These findings underscore the importance of early post weaning stages as potential targets for feeding interventions that can enhance metabolic interactions between rumen bacteria, to increase productive performance in beef cattle.

Project description:Intensive production systems require high-yield genetics as obtained in Bos taurus × Bos indicus crossbreeding. Generally, high-producing taurine cattle are more susceptible to parasites and heat stress. This study evaluated animal performance, heat-stress measurement (infrared temperatures), and internal parasite infection with daily weight gain in heifers from 2 genetic groups (Nelore and F1-Nelore × Angus) reared in 2 forage production systems (with or without crop-livestock system) during 1 yr. The main objectives were to determine the relationship between infrared measures and animal performance and whether it differs between genetic groups and environments. Thirty-six heifers were randomly assigned to 2 forage production systems, one considered as high-input system with crop-livestock system and other exclusive livestock system considered as low input. At each 28 d, infrared thermography (IR) temperatures, weight, and internal parasite infection (fecal egg count) were measured. The temperatures of the eye, snout, forehead, dewlap, body, ground and squeeze chute were determined. F1 heifers had higher weight gain than Nelore (P < 0.05) and both did not differ in internal parasite infection (P > 0.05). F1 heifers had higher IR than Nelore (P < 0.05). The main body points that differentiate between genetic groups were dewlap, forehead, and eye. Higher dewlap IR temperature (DW) was associated with higher average daily gain (ADG) during dry season (independently of genetic groups) (ADG = -0.755 + 0.032 × DW; R2 = 0.44). Otherwise, the IR temperatures had a negative relationship with ADG during rainy season and low forehead IR temperature was related to higher average daily gain (ADG = 1.81 - 0.033 × forehead; R2 = 0.12 for F1 animals and ADG = 1.46 - 0.025 × forehead; R2 = 0.07 for Nelore). The infrared temperatures were more related to animal performance during the dry season, which had high temperature and low humidity. The infrared temperatures were able to identify the animal response to the environment challenge. Animals with higher temperatures (dewlap and forehead) had higher daily gain during the dry season.

Dataset Information

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle.

Publications

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets