Evidence map›Paper›PMID 23834466›Full record

ArticleBMC genomics2013

The identification of 14 new genes for meat quality traits in chicken using a genome-wide association study.

Yanfa Sun, Guiping Zhao, Ranran Liu, Maiqing Zheng, Yaodong Hu, Dan Wu, Lei Zhang, Peng Li, Jie Wen

Abstract read
In one paragraph

Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

70 citing papers in PubMed, 1 synthesis or guideline pooled it.

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10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yanfa SunChinese Academy of Agricultural Sciences, Beijing, People's Republic of China.
Guiping Zhao
Ranran Liu
Maiqing Zheng
Yaodong Hu
Dan Wu
Lei Zhang
Peng Li
Jie Wen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeat quality is an important economic trait in chickens. To identify loci and genes associated with meat quality traits, we conducted a genome-wide association study (GWAS) of F2 populations derived from a local Chinese breed (Beijing-You chickens) and a commercial fast-growing broiler line (Cobb-Vantress).

resultsIn the present study, 33 association signals were detected from the compressed mixed linear model (MLM) for 10 meat quality traits: dry matter in breast muscle (DMBr), dry matter in thigh muscle (DMTh), intramuscular fat content in breast muscle (IMFBr), meat color lightness (L*) and yellowness (b*) values, skin color L*, a* (redness) and b* values, abdominal fat weight (AbFW) and AbFW as a percentage of eviscerated weight (AbFP). Relative expressions of candidate genes identified near significant signals were compared using samples of chickens with High and Low phenotypic values. A total of 14 genes associated with IMFBr, meat color L*, AbFW, and AbFP, were differentially expressed between the High and Low phenotypic groups. These genes are, therefore, prospective candidate genes for meat quality traits: protein tyrosine kinase (TYRO3) and microsomal glutathione S-transferase 1 (MGST1) for IMFBr; collagen, type I, alpha 2 (COL1A2) for meat color L*; and RET proto-oncogene (RET), natriuretic peptide B (NPPB) and sterol regulatory element binding transcription factor 1 (SREBF1) for the abdominal fat (AbF) traits.

conclusionsBased on the association signals and differential expression of nearby genes, 14 candidate loci and genes for IMFBr, meat L* and b* values, and AbF are identified. The results provide new insight into the molecular mechanisms underlying meat quality traits in chickens.

Indexed as

GenomicsMeatAbdominal FatAnimalsChickensFemaleGene Expression ProfilingHybridization, GeneticMaleMusclesPhenotypeRNA, MessengerSkin PigmentationRNA, Messenger

Identifiers

PMID23834466
PMCPMC3707761

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.