ORCID Profile
0000-0003-2939-4798
Current Organisation
Universidade de São Paulo
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Publisher: Springer Science and Business Media LLC
Date: 28-04-2016
Publisher: Springer Science and Business Media LLC
Date: 29-03-2019
DOI: 10.1038/S41598-019-41813-X
Abstract: Improving nutrient utilization efficiency is essential for livestock, given the current scenario of increasing demand for animal protein and sustainable resource use. In this context, understanding the biology of feed efficiency (FE) in beef cattle allows the development of markers for identification and selection of best animals for animal production. Thus, 98 young Nellore bulls were evaluated for FE and at the end of the experiment liver s les from six High Feed Efficient (HFE) and six Low Feed Efficient (LFE) animals were collected for protein extraction, digestion and analysis by HPLC-MS/MS. Data were analyzed for differential abundant proteins (DAPs), protein networks, and functional enrichment. Serum endotoxin was also quantified. We found 42 DAPs and 3 protein networks significantly related to FE. The main pathways associated with FE were: microbial metabolism biosynthesis of fatty acids, amino acids and vitamins glycolysis/gluconeogenesis xenobiotic metabolism and antigen processing and presentation. Serum endotoxins were significantly higher in LFE animals supporting the results. Therefore, the findings presented here confirmed the altered hepatic metabolism and pronounced hepatic inflammation in LFE animals supporting that the increased bacterial load is at least in part responsible for the hepatic lesions and inflammation in LFE animals.
Publisher: Genetics and Molecular Research
Date: 2019
DOI: 10.4238/GMR18226
Publisher: Springer Science and Business Media LLC
Date: 12-2015
Publisher: Wiley
Date: 18-12-2018
DOI: 10.1111/JBG.12369
Abstract: The objective of the present study was to investigate the impact of considering population structure in cow genotyping strategies over the accuracy and bias of genomic predictions. A small dairy cattle population was simulated to address these objectives. Based on four main traditional designs (random, top-yield, extreme-yield and top-accuracy cows), different numbers (1,000 2,000 and 5,000) of cows were s led and included in the reference population. Traditional designs were replicated considering or not population structure and compared among and with a reference population containing only bulls. The inclusion of cows increased accuracy in all scenarios compared with using only bulls. Scenarios accounting for population structure when choosing cows to the reference population slightly outperformed their traditional versions by yielding higher accuracy and lower bias in genomic predictions. Building a cow-based reference population from groups of related in iduals considering the frequency of in iduals from those same groups in the validation population yielded promising results with applications on selection for expensive- or difficult-to-measure traits. Methods here presented may be easily implemented in both new or already established breeding programs, as they improved prediction and reduced bias in genomic evaluations while demanding no additional costs.
No related grants have been discovered for Joanir Eler.