2016
DOI: 10.1371/journal.pone.0158165
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Pleiotropic Genes Affecting Carcass Traits in Bos indicus (Nellore) Cattle Are Modulators of Growth

Abstract: Two complementary methods, namely Multi-Trait Meta-Analysis and Versatile Gene-Based Test for Genome-wide Association Studies (VEGAS), were used to identify putative pleiotropic genes affecting carcass traits in Bos indicus (Nellore) cattle. The genotypic data comprised over 777,000 single-nucleotide polymorphism markers scored in 995 bulls, and the phenotypic data included deregressed breeding values (dEBV) for weight measurements at birth, weaning and yearling, as well visual scores taken at weaning and year… Show more

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Cited by 23 publications
(26 citation statements)
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“…Following the milestone publication by Karim et al . 12 , we and others 13 22 have previously reported that this CHR14 region is also a major pleiotropic quantitative trait locus (QTL) affecting cattle body size and reproduction, supporting an important role of PLAG1 in recent changes in stature in cattle. The candidacy of PLAG1 is further supported by functional evidence, since the transcription factor encoded by this gene regulates the expression of insulin-like growth factors 14 , 23 – 26 .…”
Section: Introductionmentioning
confidence: 57%
“…Following the milestone publication by Karim et al . 12 , we and others 13 22 have previously reported that this CHR14 region is also a major pleiotropic quantitative trait locus (QTL) affecting cattle body size and reproduction, supporting an important role of PLAG1 in recent changes in stature in cattle. The candidacy of PLAG1 is further supported by functional evidence, since the transcription factor encoded by this gene regulates the expression of insulin-like growth factors 14 , 23 – 26 .…”
Section: Introductionmentioning
confidence: 57%
“…To the authors knowledge, there is no comparable experimental information about the performance of adult animals in the study region, but it supports, the limited number of available on ranch observations. Thus, given the fact that irrespective of the year, all studied cattle were subject to a similar commercial management considerations, differences in LW performance most likely reflects a variability and/or interaction amongst environmental conditions (Domínguez et al 2003;; growth traits, including compensatory gains (Hernández-Hernández et al 2015); genetic parameters and their interacting networks (Ceacero et al 2016;Lopes et al 2013;Pereira et al 2016); hormones secretion (Kasuya 2016; Widmann et al 2013); maternal effects (Neidhardt et al 1979); grazing management (Vera and Ramírez-Restrepo 2017); diet selection (O'Neill et al 2013); nutritive and metabolic trigger factors in the forage resources (Tedeschi et al 2014); and the adaptive capacity of Brahman and Belmont Red Composite to respond to those triggers within a climate change environment (Ramírez-Restrepo and Charmley 2015). In parallel, a particularly relevant aspect is that putting weight on cull cows in thin to medium condition has been found to be more profitable than cows with higher body scores (Amadou et al 2014).…”
Section: Discussionmentioning
confidence: 99%
“…7). Previous QTLs studies detected genomic regions on BTA 2 and 14 play an important role in multiple traits ( Supplementary Table S2) 74,[78][79][80][81] . These genomic regions are known to act on age at puberty, calving to conception interval, the interval from first to last insemination, body weight and intramuscular fat ( Supplementary Table S2).…”
Section: Shared Regions Surround Genes For Afc On Low Medium and Higmentioning
confidence: 99%