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Genome-wide characterization of genetic variants and putative regions under selection in meat and egg-type chicken lines

Overview of attention for article published in BMC Genomics, January 2018
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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7 tweeters

Citations

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21 Dimensions

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Title
Genome-wide characterization of genetic variants and putative regions under selection in meat and egg-type chicken lines
Published in
BMC Genomics, January 2018
DOI 10.1186/s12864-018-4444-0
Pubmed ID
Authors

Clarissa Boschiero, Gabriel Costa Monteiro Moreira, Almas Ara Gheyas, Thaís Fernanda Godoy, Gustavo Gasparin, Pilar Drummond Sampaio Corrêa Mariani, Marcela Paduan, Aline Silva Mello Cesar, Mônica Corrêa Ledur, Luiz Lehmann Coutinho

Abstract

Meat and egg-type chickens have been selected for several generations for different traits. Artificial and natural selection for different phenotypes can change frequency of genetic variants, leaving particular genomic footprints throghtout the genome. Thus, the aims of this study were to sequence 28 chickens from two Brazilian lines (meat and white egg-type) and use this information to characterize genome-wide genetic variations, identify putative regions under selection using Fst method, and find putative pathways under selection. A total of 13.93 million SNPs and 1.36 million INDELs were identified, with more variants detected from the broiler (meat-type) line. Although most were located in non-coding regions, we identified 7255 intolerant non-synonymous SNPs, 512 stopgain/loss SNPs, 1381 frameshift and 1094 non-frameshift INDELs that may alter protein functions. Genes harboring intolerant non-synonymous SNPs affected metabolic pathways related mainly to reproduction and endocrine systems in the white-egg layer line, and lipid metabolism and metabolic diseases in the broiler line. Fst analysis in sliding windows, using SNPs and INDELs separately, identified over 300 putative regions of selection overlapping with more than 250 genes. For the first time in chicken, INDEL variants were considered for selection signature analysis, showing high level of correlation in results between SNP and INDEL data. The putative regions of selection signatures revealed interesting candidate genes and pathways related to important phenotypic traits in chicken, such as lipid metabolism, growth, reproduction, and cardiac development. In this study, Fst method was applied to identify high confidence putative regions under selection, providing novel insights into selection footprints that can help elucidate the functional mechanisms underlying different phenotypic traits relevant to meat and egg-type chicken lines. In addition, we generated a large catalog of line-specific and common genetic variants from a Brazilian broiler and a white egg layer line that can be used for genomic studies involving association analysis with phenotypes of economic interest to the poultry industry.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 23%
Student > Bachelor 7 13%
Researcher 6 11%
Student > Ph. D. Student 5 9%
Professor 4 8%
Other 12 23%
Unknown 7 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 51%
Biochemistry, Genetics and Molecular Biology 9 17%
Engineering 3 6%
Veterinary Science and Veterinary Medicine 2 4%
Computer Science 1 2%
Other 5 9%
Unknown 6 11%

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 06 September 2018.
All research outputs
#5,230,678
of 19,191,572 outputs
Outputs from BMC Genomics
#2,408
of 9,726 outputs
Outputs of similar age
#116,389
of 385,017 outputs
Outputs of similar age from BMC Genomics
#7
of 25 outputs
Altmetric has tracked 19,191,572 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 9,726 research outputs from this source. They receive a mean Attention Score of 4.5. This one has gotten more attention than average, scoring higher than 74% 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 385,017 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 69% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.