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Polygenic Basis and Variable Genetic Architectures Contribute to the Complex Nature of Body Weight —A Genome-Wide Study in Four Chinese Indigenous Chicken Breeds

Overview of attention for article published in Frontiers in Genetics, July 2018
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  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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Title
Polygenic Basis and Variable Genetic Architectures Contribute to the Complex Nature of Body Weight —A Genome-Wide Study in Four Chinese Indigenous Chicken Breeds
Published in
Frontiers in Genetics, July 2018
DOI 10.3389/fgene.2018.00229
Pubmed ID
Authors

Yangyang Yuan, Dezhi Peng, Xiaorong Gu, Yanzhang Gong, Zheya Sheng, Xiaoxiang Hu

Abstract

Body weight (BW) is one of the most important economic traits for animal production and breeding, and it has been studied extensively for its phenotype-genotype associations. While mapping studies have mostly aimed at finding as many loci as possible that contributed to the variation in BW, the role of other factors in its genetic architecture, including their frequencies in the population and their interactions, have been largely overlooked. To comprehensively characterized the genetic architecture of BW, we performed a genome-wide association study (GWAS) both at the single-marker and haplotype level on birds from four indigenous Chinese chicken breeds (Chahua, Silkie, Langshan, and Beard), rather than studying crosses between two founder lines. Additionally, samples from two more breeds (Red Junglefowl and Recessive White) were included to better reflect variable genetic characteristics across populations. Six loci were mapped in this study, revealing the polygenic basis underlying BW. Moreover, by further examining the frequencies of the significantly associated haplotypes in each subpopulation and their effect sizes, most of the loci were found to affect BW in the Beard chicken breed alone. Two loci in GGA9 and GGA27, however, had a common effect on BW across subpopulations, showing that different underlying genetic mechanisms contribute to the phenotypic variability. These findings, particularly the variable genetic architectures found in different loci, improve our understanding of the overall genetic contributions to the large variability in BW among Chinese indigenous chicken breeds. These findings thus will have important implications for future chicken breeding.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 31%
Professor 2 13%
Student > Doctoral Student 1 6%
Unspecified 1 6%
Lecturer 1 6%
Other 1 6%
Unknown 5 31%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 38%
Biochemistry, Genetics and Molecular Biology 4 25%
Unspecified 1 6%
Chemistry 1 6%
Unknown 4 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 19 February 2020.
All research outputs
#7,542,848
of 26,313,853 outputs
Outputs from Frontiers in Genetics
#2,231
of 13,891 outputs
Outputs of similar age
#118,663
of 344,928 outputs
Outputs of similar age from Frontiers in Genetics
#43
of 141 outputs
Altmetric has tracked 26,313,853 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 13,891 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 83% 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 344,928 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 141 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 68% of its contemporaries.