Evidence map›Paper›PMID 41719995›Full record

ArticlePoultry science2026

Distinct gut microbiota signatures in white leghorn and silky fowl are associated with divergent laying performance.

Xue Yang, Yurong Tai, Xin Wu, Deping Han, Ganxian Cai, Zihan Xu, Jiaqi Hao, Junying Li, Jiankui Wang, Xuemei Deng

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Xue YangState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; State Key Laboratory of Swine and Poultry Breeding Industry, Key Laboratory of Animal Nutrition and Feed Science in South China, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China.
Yurong TaiState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; Sanya Institute, China Agricultural University, Sanya, 572000, China.
Xin WuState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Deping HanState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Institute of Advanced Agricultural Sciences, Peking University, Weifang, 261325, China.
Ganxian CaiState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Zihan XuState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Jiaqi HaoState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Junying LiState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Jiankui WangState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Xuemei DengState Key Laboratory of Animal Biotech Breeding & Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture & Beijing Key Laboratory for Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China. Electronic address: deng@cau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The gut microbiota is a key modulator of nutrient utilization and egg production in laying hens. However, breed-associated differences in gut microbiota during the critical peak laying period, as well as their spatial distribution along the intestinal tract, remain poorly characterized. We compared the microbiota of duodenum, jejunum, ileum, and cecum in high-yielding White Leghorn (WL, n = 20) and niche-adapted Silky Fowl (SF, n = 20) hens at peak lay using 16S rRNA sequencing, with intestinal segments analyzed as within-individual compartments. The small intestinal segments exhibited conserved Lactobacillus dominance in both breeds. In contrast, the cecal microbiota diverged significantly: WL was enriched in Bacteroides (P < 0.05), which was linked to glycan degradation, while SF harbored a higher abundance of Faecalibacterium (P < 0.05), associated with vitamin B12 synthesis. Functional prediction revealed that WL upregulated energy-harvesting pathways such as glycolysis in the small intestines and glycosaminoglycan degradation in the cecum. Conversely, SF prioritized stress-resilience pathways including porphyrin metabolism. These functional profiles aligned with host phenotypes, where Lactobacillus and Bacteroides abundance correlated with hepatic efficiency in WL, and multiple microbiota taxa were associated with maintaining metabolic homeostasis and adaptation in SF. Collectively, our findings demonstrate that breed-specific cecal microbiota and their metabolic functions underlie divergent host resource-allocation strategies during peak lay. These results provide tangible targets for modulating the gut ecosystem through nutritional or breeding strategies, aiming to enhance disease resilience in commercial stocks or improve robustness and productivity in indigenous breeds.

Indexed as

ChickensGastrointestinal MicrobiomeReproductionAnimalsBacteriaFemaleRNA, BacterialRNA, Ribosomal, 16SRNA, BacterialRNA, Ribosomal, 16SEnergy harvestGut microbiotaHost metabolismLaying hensMicrobial interaction

Identifiers

PMID41719995
PMCPMC12934277

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.