Evidence map›Paper›PMID 42603398›Full record

ArticlePoultry science2026

Genetic dissection of leg and back feather follicle density in yellow-feathered broiler: integrative GWAS and transcriptome analysis reveal the regulatory role of SERPINF1.

Xiaohuan Chao, Shuya Chen, Tong OuYang, Chutian Ye, Jie Chen, Jiongwen Wu, XueRong Ma, Aijun Liu, Weiming Liang, Tianxi Cui and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Poultry science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

16 authors.

Xiaohuan ChaoCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Shuya ChenCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Tong OuYangCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Chutian YeCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Jie ChenGuangzhou Kwangfeng Seed Industry Technology Co., Ltd, China.
Jiongwen WuCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
XueRong MaCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Aijun LiuCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Weiming LiangCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Tianxi CuiCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Lulu XiaCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Kaifan XiaoCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Youcheng HeCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Xiquan ZhangCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China.
Cheng FangCollege of Engineering, South China Agricultural University, Guangzhou, 510642, China.
Qingbin LuoCollege of Animal Science, South China Agricultural University, Guangzhou, 510642, China; State Key Laboratory of Livestock and Poultry Breeding, South China Agricultural University, China. Electronic address: qbluo@scau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, chilled chicken has emerged as a new market trend. Skin feather follicle density, an important carcass appearance trait characterized by "fine and dense" features, is increasingly preferred by consumers. This study analyzed hair follicle density in the leg and back regions of 1,382 yellow-feathered broiler. The results showed that back feather follicle density was significantly higher than that of the leg (P < 0.01), with a significant positive correlation between the two regions. Meanwhile, feather follicle density in both the leg and back showed negative correlations with abdominal fat weight, body weight, dressed weight, full-eviscerated weight, semi-eviscerated weight. mRNA-seq analysis of leg and back skin tissues from four individuals identified differentially expressed genes (DEGs) affecting feather follicle density traits across different anatomical locations, including GTF2A1, RPSA2, COX3, and CNKSR2. Furthermore, Genome-Wide Association Study (GWAS) analysis of 505 chickens identified 223 single-nucleotide polymorphisms (SNPs) significantly associated with leg feather follicle density and 107 SNPs associated with back feather follicle density, including candidate SNPs such as C19014967G, C17514817T, G1847078C, and C34389948G, as well as candidate genes including ELF5, MAP3K1, HIF1AN, and SERPINF1. mRNA-seq analysis of skin tissues from high and low feather follicle density groups in the leg (TG vs. TD) and back (BG vs. BD) identified 541 leg-related DEGs and 1,130 back-related DEGs, respectively. Joint analysis of TG vs. TD and BG vs. BD revealed 174 commonly DEGs, including candidate genes such as NSA2, IGF2, RPL17, and NRP1. Through integrated GWAS and RNA-seq analysis, five genes significantly associated with leg feather follicle density and twelve candidate genes associated with back feather follicle density were identified. Notably, individuals with the AA genotype at the SERPINF1 SNP locus Chr19:5636537 showed extremely significantly higher feather follicle density than those with the GG genotype, and both mRNA and protein expression levels of SERPINF1 were significantly upregulated in high feather follicle density individuals.

Indexed as

Chr19:5636537Feather follicle densityGWASmRNA-seqSERPINF1

Identifiers

PMID42603398
PMCPMC13499478

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.