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A genome-wide association study reveals novel genomic regions and positional candidate genes for fat deposition in broiler chickens

Overview of attention for article published in BMC Genomics, May 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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1 news outlet
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3 X users

Citations

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29 Dimensions

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48 Mendeley
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Title
A genome-wide association study reveals novel genomic regions and positional candidate genes for fat deposition in broiler chickens
Published in
BMC Genomics, May 2018
DOI 10.1186/s12864-018-4779-6
Pubmed ID
Authors

Gabriel Costa Monteiro Moreira, Clarissa Boschiero, Aline Silva Mello Cesar, James M. Reecy, Thaís Fernanda Godoy, Priscila Anchieta Trevisoli, Maurício E. Cantão, Mônica Corrêa Ledur, Adriana Mércia Guaratini Ibelli, Jane de Oliveira Peixoto, Ana Silvia Alves Meira Tavares Moura, Dorian Garrick, Luiz Lehmann Coutinho

Abstract

Excess fat content in chickens has a negative impact on poultry production. The discovery of QTL associated with fat deposition in the carcass allows the identification of positional candidate genes (PCGs) that might regulate fat deposition and be useful for selection against excess fat content in chicken's carcass. This study aimed to estimate genomic heritability coefficients and to identify QTLs and PCGs for abdominal fat (ABF) and skin (SKIN) traits in a broiler chicken population, originated from the White Plymouth Rock and White Cornish breeds. ABF and SKIN are moderately heritable traits in our broiler population with estimates ranging from 0.23 to 0.33. Using a high density SNP panel (355,027 informative SNPs), we detected nine unique QTLs that were associated with these fat traits. Among these, four QTL were novel, while five have been previously reported in the literature. Thirteen PCGs were identified that might regulate fat deposition in these QTL regions: JDP2, PLCG1, HNF4A, FITM2, ADIPOR1, PTPN11, MVK, APOA1, APOA4, APOA5, ENSGALG00000000477, ENSGALG00000000483, and ENSGALG00000005043. We used sequence information from founder animals to detect 4843 SNPs in the 13 PCGs. Among those, two were classified as potentially deleterious and two as high impact SNPs. This study generated novel results that can contribute to a better understanding of fat deposition in chickens. The use of high density array of SNPs increases genome coverage and improves QTL resolution than would have been achieved with low density. The identified PCGs were involved in many biological processes that regulate lipid storage. The SNPs identified in the PCGs, especially those predicted as potentially deleterious and high impact, may affect fat deposition. Validation should be undertaken before using these SNPs for selection against carcass fat accumulation and to improve feed efficiency in broiler chicken production.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 25%
Student > Ph. D. Student 6 13%
Professor 5 10%
Student > Bachelor 5 10%
Student > Doctoral Student 3 6%
Other 9 19%
Unknown 8 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 54%
Biochemistry, Genetics and Molecular Biology 5 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Unspecified 1 2%
Veterinary Science and Veterinary Medicine 1 2%
Other 4 8%
Unknown 10 21%
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 17 September 2018.
All research outputs
#2,642,053
of 23,067,276 outputs
Outputs from BMC Genomics
#856
of 10,702 outputs
Outputs of similar age
#56,703
of 330,193 outputs
Outputs of similar age from BMC Genomics
#33
of 260 outputs
Altmetric has tracked 23,067,276 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 10,702 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 91% 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 330,193 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 82% of its contemporaries.
We're also able to compare this research output to 260 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.