Evidence mapPaperPMID 42365829Full record

ArticlePoultry science2026

Weighted single-step GWAS identified candidate genes associated with semen traits in Rhode Island Red chickens.

Hailai Hagos Tesfay, Xiaoke Zhang, Yunlei Li, Yunhe Zong, Zhong Ma, Xintong Han, Yi Zhao, Ziting Pan, Adamu Isa Mani, Fujian Yang and 4 more

Abstract read
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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0citing papers in PubMed
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Hailai Hagos TesfayState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China; Tigray Agricultural Research Institute, Mekelle, P.O. Box 492, Ethiopia.
Xiaoke ZhangState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China. Electronic address: zxkstar@163.com.
Yunlei LiState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China.
Yunhe ZongState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China; Institute of Animal Husbandry and Veterinary Science, Hubei Academy of Agricultural Sciences, Wuhan 430064, PR China.
Zhong MaState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China.
Xintong HanState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China.
Yi ZhaoState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China.
Ziting PanState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China.
Adamu Isa ManiState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China; Department of Animal Science, Usmanu Danfodiyo University, Sokoto 840104, Nigeria.
Fujian YangGuangxi Shenghuang Group Ltd., Yuling 537000, PR China.
Zongyao ZhangGuangxi Shenghuang Group Ltd., Yuling 537000, PR China.
Jiming ChenGuangxi Shenghuang Group Ltd., Yuling 537000, PR China.
Yanyan SunState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China.
Jilan ChenState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China. Electronic address: chen.jilan@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Semen quality traits in chickens are critical indicators reflecting reproductive efficiency, breeding progress, and economic profitability in the poultry industry. Understanding the genetic architecture and enabling targeted genetic improvement of these traits are essential for enhancing poultry production efficiency. In this study, we estimated genetic parameters and performed weighted single-step GWAS for five semen traits in RIR chickens to reveal their genetic architecture and identify key candidate genes and QTLs associated with semen quality. The results showed that heritability estimates for SEVOL, SECON, SPMOT, SPABR, and SPCOUNT ranged from 0.097 to 0.322, indicating low to moderate heritability. 29 significant QTL regions and 12 candidate genes (NFKB1, UBE2D3, PPP3CA, EIF4E, H2AFZ, DOCK2, MTNR1A, TACC3, ADCYAP1, GFRA1, ABLIM1, and CASP7) associated with semen traits were identified by WssGWAS. These QTL regions were located on chromosomes 4 and 13 for SEVOL, chromosome 4 for SPMOT, and chromosomes 2 and 6 for SPABR. Interestingly, four prominent consecutive QTL regions were shared between SEVOL and SPMOT. These QTL were located at 59.83-61.43 Mb, explaining 11.55% and 16.33% of the genetic variance for SEVOL and SPMOT, respectively. The largest-effect SNPs within these four QTL intervals exhibited significant effects on both semen volume and sperm motility, and these markers could be used for marker-assisted selection of semen traits. This study provides further insights into the genetic architecture of chicken semen traits, improves our understanding of their molecular regulation, and identifies valuable QTL and candidate genes. These findings offer a scientific basis for genetic improvement and marker-assisted selection of semen quality.

Indexed as

Candidate genesChickensGenetic variancesSemen traitsWeighted single-step GWAS

Identifiers

PMID42365829
PMCPMC13329495

What Socratic holds

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LicenceCC BY-NC-ND
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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.