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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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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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1 news outlet
twitter
3 tweeters

Citations

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16 Dimensions

Readers on

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39 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.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 26%
Student > Ph. D. Student 5 13%
Professor 4 10%
Student > Bachelor 4 10%
Student > Postgraduate 2 5%
Other 8 21%
Unknown 6 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 62%
Biochemistry, Genetics and Molecular Biology 3 8%
Veterinary Science and Veterinary Medicine 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Materials Science 1 3%
Other 1 3%
Unknown 8 21%

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
#1,384,430
of 13,796,475 outputs
Outputs from BMC Genomics
#613
of 8,032 outputs
Outputs of similar age
#45,674
of 274,122 outputs
Outputs of similar age from BMC Genomics
#2
of 21 outputs
Altmetric has tracked 13,796,475 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,032 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 92% 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 274,122 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 83% of its contemporaries.
We're also able to compare this research output to 21 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 90% of its contemporaries.