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Mapping QTL for white striping in relation to breast muscle yield and meat quality traits in broiler chickens

Overview of attention for article published in BMC Genomics, March 2018
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Title
Mapping QTL for white striping in relation to breast muscle yield and meat quality traits in broiler chickens
Published in
BMC Genomics, March 2018
DOI 10.1186/s12864-018-4598-9
Pubmed ID
Authors

Eva Pampouille, Cécile Berri, Simon Boitard, Christelle Hennequet-Antier, Stéphane A. Beauclercq, Estelle Godet, Christophe Praud, Yves Jégo, Elisabeth Le Bihan-Duval

Abstract

White striping (WS) is an emerging muscular defect occurring on breast and thigh muscles of broiler chickens. It is characterized by the presence of white striations parallel to the muscle fibers and has significant consequences for meat quality. The etiology of WS remains poorly understood, even if previous studies demonstrated that the defect prevalence is related to broiler growth and muscle development. Moreover, recent studies showed moderate to high heritability values of WS, which emphasized the role of genetics in the expression of the muscle defect. The aim of this study was to identify the first quantitative trait loci (QTLs) for WS as well as breast muscle yield (BMY) and meat quality traits using a genome-wide association study (GWAS). We took advantage of two divergent lines of chickens selected for meat quality through Pectoralis major ultimate pH (pHu) and which exhibit the muscular defect. An expression QTL (eQTL) detection was further performed for some candidate genes, either suggested by GWAS analysis or based on their biological function. Forty-two single nucleotide polymorphisms (SNPs) associated with WS and other meat quality traits were identified. They defined 18 QTL regions located on 13 chromosomes. These results supported a polygenic inheritance of the studied traits and highlighted a few pleiotropic regions. A set of 16 positional and/or functional candidate genes was designed for further eQTL detection. A total of 132 SNPs were associated with molecular phenotypes and defined 21 eQTL regions located on 16 chromosomes. Interestingly, several co-localizations between QTL and eQTL regions were observed which could suggest causative genes and gene networks involved in the variability of meat quality traits and BMY. The QTL mapping carried out in the current study for WS did not support the existence of a major gene, but rather suggested a polygenic inheritance of the defect and of other studied meat quality traits. We identified several candidate genes involved in muscle metabolism and structure and in muscular dystrophies. The eQTL analyses showed that they were part of molecular networks associated with WS and meat quality phenotypes and suggested a few putative causative genes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 11%
Student > Bachelor 7 11%
Student > Postgraduate 6 10%
Student > Master 6 10%
Researcher 5 8%
Other 9 14%
Unknown 23 37%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 32%
Biochemistry, Genetics and Molecular Biology 7 11%
Veterinary Science and Veterinary Medicine 6 10%
Medicine and Dentistry 2 3%
Engineering 2 3%
Other 4 6%
Unknown 22 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 August 2018.
All research outputs
#13,388,707
of 23,102,082 outputs
Outputs from BMC Genomics
#4,801
of 10,709 outputs
Outputs of similar age
#167,227
of 332,472 outputs
Outputs of similar age from BMC Genomics
#85
of 197 outputs
Altmetric has tracked 23,102,082 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,709 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 53% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 332,472 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 197 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.