Evidence map›Paper›PMID 39245742›Full record

ArticleJournal of animal science and biotechnology2024

Host genetics and gut microbiota synergistically regulate feed utilization in egg-type chickens.

Wenxin Zhang, Fangren Lan, Qianqian Zhou, Shuang Gu, Xiaochang Li, Chaoliang Wen, Ning Yang, Congjiao Sun

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of animal science and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

12 citing papers in PubMed.

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  9. Quantitative genetics of microbiome-mediated traits.Evolution; international journal of organic evolution · 2025
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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

8 authors.

Wenxin ZhangState Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China.
Fangren LanState Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China.
Qianqian ZhouState Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China.
Shuang GuState Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China.
Xiaochang LiState Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China.
Chaoliang WenState Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China.
Ning YangState Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China.
Congjiao SunState Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China. cjsun@cau.edu.cn.ORCID http://orcid.org/0000-0003-0520-4355

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFeed efficiency is a crucial economic trait in poultry industry. Both host genetics and gut microbiota influence feed efficiency. However, the associations between gut microbiota and host genetics, as well as their combined contributions to feed efficiency in laying hens during the late laying period, remain largely unclear.

methodsIn total, 686 laying hens were used for whole-genome resequencing and liver transcriptome sequencing. 16S rRNA gene sequencing was conducted on gut chyme (duodenum, jejunum, ileum, and cecum) and fecal samples from 705 individuals. Bioinformatic analysis was performed by integrating the genome, transcriptome, and microbiome to screen for key genetic variations, genes, and gut microbiota associated with feed efficiency.

resultsThe heritability of feed conversion ratio (FCR) and residual feed intake (RFI) was determined to be 0.28 and 0.48, respectively. The ileal and fecal microbiota accounted for 15% and 10% of the FCR variance, while the jejunal, cecal, and fecal microbiota accounted for 20%, 11%, and 10% of the RFI variance. Through SMR analysis based on summary data from liver eQTL mapping and GWAS, we further identified four protein-coding genes, SUCLA2, TNFSF13B, SERTM1, and MARVELD3, that influence feed efficiency in laying hens. The SUCLA2 and TNFSF13B genes were significantly associated with SNP 1:25664581 and SNP rs312433097, respectively. SERTM1 showed significant associations with rs730958360 and 1:33542680 and is a potential causal gene associated with the abundance of Corynebacteriaceae in feces. MARVELD3 was significantly associated with the 1:135348198 and was significantly correlated with the abundance of Enterococcus in ileum. Specifically, a lower abundance of Enterococcus in ileum and a higher abundance of Corynebacteriaceae in feces were associated with better feed efficiency.

conclusionsThis study confirms that both host genetics and gut microbiota can drive variations in feed efficiency. A small portion of the gut microbiota often interacts with host genes, collectively enhancing feed efficiency. Therefore, targeting both the gut microbiota and host genetic variation by supporting more efficient taxa and selective breeding could improve feed efficiency in laying hens during the late laying period.

Indexed as

Feed efficiencyGenetic variationsGut microbiotaLaying hensMulti-omics

Identifiers

PMID39245742
PMCPMC11382517

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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.