2018
DOI: 10.1186/s12864-018-4441-3
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Genetical genomics of growth in a chicken model

Abstract: BackgroundThe genetics underlying body mass and growth are key to understanding a wide range of topics in biology, both evolutionary and developmental. Body mass and growth traits are affected by many genetic variants of small effect. This complicates genetic mapping of growth and body mass. Experimental intercrosses between individuals from divergent populations allows us to map naturally occurring genetic variants for selected traits, such as body mass by linkage mapping. By simultaneously measuring traits a… Show more

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Cited by 31 publications
(32 citation statements)
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“…Conversely, the data structure in our research did not reveal a significant influence on abdominal fat weight between different genotypes carrying the novel SNP. This contrasting result may come from the fact that different determinants including hormonal levels, nutrition, genotypes, and even data structure are responsible for phenotypic plasticity (De-Jong and Bijma 2002;Johnsson et al, 2018). The strategy of using UCP3 polymorphism as a DNA marker would increase body weight, improve production quality and decrease abdominal fat next will cause low production costs in the poultry industry (Liu et al, 2007;Moazeni et al, 2016;An et al, 2018;Jin et al, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…Conversely, the data structure in our research did not reveal a significant influence on abdominal fat weight between different genotypes carrying the novel SNP. This contrasting result may come from the fact that different determinants including hormonal levels, nutrition, genotypes, and even data structure are responsible for phenotypic plasticity (De-Jong and Bijma 2002;Johnsson et al, 2018). The strategy of using UCP3 polymorphism as a DNA marker would increase body weight, improve production quality and decrease abdominal fat next will cause low production costs in the poultry industry (Liu et al, 2007;Moazeni et al, 2016;An et al, 2018;Jin et al, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…These birds have been previously demonstrated to be an excellent model for the genetic regulation of brain size variation due to the large differences in brain size and composition generated via domestication [5]. By combining these results with previous analyses of the genetic regulation of the hypothalamus [17] and liver transcriptomes [18] in the same chicken intercross, we can compare the regulation of gene expression in both brain regions, as well as between the brain and distant somatic tissue. This allows a comparison of the transcriptomic regulation of these different tissues and the relative similarity between them, that can help shed light on the evolutionary pattern of brain evolution.…”
Section: Introductionmentioning
confidence: 86%
“…The microarray probesets were based on Ensembl transcripts and RefSeq mRNA sequences, with a total of 20,771 probesets representing 11,776 annotated genes. For further details about the microarray design see Johnsson et al (2018) [ 18 ]. 2–3 probes were used for each probeset and summarised to one value per probeset using the R-package ‘preprocessCore’ [ 38 ].…”
Section: Methodsmentioning
confidence: 99%
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“…From previous studies done on the same intercross 1123 eQTL have been identified for the hypothalamus (17) and 1462 eQTL for liver (18). These eQTL was used to compare gene expression profiles between the tissues.…”
Section: Cerebrum Gene Profile Compared To Neuronal-and Non-neuronal mentioning
confidence: 99%