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Multi-breed and multi-trait co-association analysis of meat tenderness and other meat quality traits in three French beef cattle breeds

Overview of attention for article published in Genetics Selection Evolution, April 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#49 of 822)
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

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Citations

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51 Dimensions

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73 Mendeley
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Title
Multi-breed and multi-trait co-association analysis of meat tenderness and other meat quality traits in three French beef cattle breeds
Published in
Genetics Selection Evolution, April 2016
DOI 10.1186/s12711-016-0216-y
Pubmed ID
Authors

Yuliaxis Ramayo-Caldas, Gilles Renand, Maria Ballester, Romain Saintilan, Dominique Rocha

Abstract

Studies to identify markers associated with beef tenderness have focused on Warner-Bratzler shear force (WBSF) but the interplay between the genes associated with WBSF has not been explored. We used the association weight matrix (AWM), a systems biology approach, to identify a set of interacting genes that are co-associated with tenderness and other meat quality traits, and shared across the Charolaise, Limousine and Blonde d'Aquitaine beef cattle breeds. Genome-wide association studies were performed using ~500K single nucleotide polymorphisms (SNPs) and 17 phenotypes measured on more than 1000 animals for each breed. First, this multi-trait approach was applied separately for each breed across 17 phenotypes and second, between- and across-breed comparisons at the AWM and functional levels were performed. Genetic heterogeneity was observed, and most of the variants that were associated with WBSF segregated within rather than across breeds. We identified 206 common candidate genes associated with WBSF across the three breeds. SNPs in these common genes explained between 28 and 30 % of the phenotypic variance for WBSF. A reduced number of common SNPs mapping to the 206 common genes were identified, suggesting that different mutations may target the same genes in a breed-specific manner. Therefore, it is likely that, depending on allele frequencies and linkage disequilibrium patterns, a SNP that is identified for one breed may not be informative for another unrelated breed. Well-known candidate genes affecting beef tenderness were identified. In addition, some of the 206 common genes are located within previously reported quantitative trait loci for WBSF in several cattle breeds. Moreover, the multi-breed co-association analysis detected new candidate genes, regulators and metabolic pathways that are likely involved in the determination of meat tenderness and other meat quality traits in beef cattle. Our results suggest that systems biology approaches that explore associations of correlated traits increase statistical power to identify candidate genes beyond the one-dimensional approach. Further studies on the 206 common genes, their pathways, regulators and interactions will expand our knowledge on the molecular basis of meat tenderness and could lead to the discovery of functional mutations useful for genomic selection in a multi-breed beef cattle context.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 1%
Argentina 1 1%
Unknown 71 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 16%
Researcher 11 15%
Student > Master 9 12%
Student > Doctoral Student 6 8%
Student > Bachelor 6 8%
Other 14 19%
Unknown 15 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 49%
Veterinary Science and Veterinary Medicine 6 8%
Biochemistry, Genetics and Molecular Biology 5 7%
Medicine and Dentistry 4 5%
Arts and Humanities 1 1%
Other 4 5%
Unknown 17 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 11 December 2018.
All research outputs
#2,965,971
of 25,373,627 outputs
Outputs from Genetics Selection Evolution
#49
of 822 outputs
Outputs of similar age
#45,293
of 313,367 outputs
Outputs of similar age from Genetics Selection Evolution
#1
of 14 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 93% 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 313,367 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.