Evidence map›Paper›PMID 41431940›Full record

ArticleAnimal genetics2026

Identification of key gut microbiota and microbial QTL in contributing to the significant differences in body weight between two Chinese local chicken breeds.

Linna Zhang, Chenglong Wang, Xiaojian Zhang, Guohui Li, Zheya Sheng

Abstract read
In one paragraph

Article in Animal genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

5 authors.

Linna ZhangState Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.
Chenglong WangState Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.ORCID https://orcid.org/0009-0006-5059-4689
Xiaojian ZhangState Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.
Guohui LiJiangsu Institute of Poultry Science, Yangzhou, China.
Zheya ShengState Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.ORCID https://orcid.org/0000-0002-4487-2682

Funding

Key Research and Develpment Project of Hubei province 2021BBA234Major Program (JD) OF Hubei province 2023BAA029National Key R&D Program of China 2021YFD1300100Open Research Fund of Tianjin Key Laboratory of Animal Molecular Breeding and Biotechnology XM202403the Supporting High Quality Development of Seed Industry Fund Project of Hubei Province HBZY2023B007
6 · The paper itself

Abstract

Previous studies have identified genetic loci that are associated with both feed conversion efficiency and gut microbiota in chickens, suggesting that interactions between the host genome and gut microbiota may influence chicken growth. However, the number of microbial QTL and gut microbiota associated with chicken body weight remains largely unknown. To further explore the impact of host-gut microbiota interactions on chicken body weight and to identify gut microbiota associated with chicken body weight, this study strictly controlled environmental interference and obtained phenotypic, genotypic, and gut microbiota composition data from 100 Langshan and Tibetan chickens (with significant differences in body weight) raised under identical standardized housing conditions. Through genome-wide association studies of chicken body weight, microbiome genome-wide association studies, and Mendelian randomization analysis, we have identified 145 microbial QTL as instrumental variables and screened out seven genera that have a significant causal relationship with chicken body weight, including the genera Blautia and Faecalibacterium. This study identified potential molecular and microbial markers associated with chicken body weight, offering a valuable theoretical framework for enhancing economic efficiency in poultry production.

Indexed as

Body WeightChickensGastrointestinal MicrobiomeQuantitative Trait LociAnimalsChinaGenome-Wide Association StudyMalePhenotypechicken body weightgut microbiotahost geneticsMendelian randomization analysismicrobiome genome‐wide association study

Identifiers

PMID41431940
PMCPMC12723572

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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 OpenQuestion graph.