Evidence map›Paper›PMID 42777361›Full record

ArticlePoultry science2026

Cecal microbiota-host phenotype associations in young White Leghorn and Silky Fowl chickens.

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. Not yet cited in PubMed.

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

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

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

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

Genetic background and intestinal region both shape the gut microbiota, yet their relative contributions before the onset of laying remain poorly defined. This study compared intestinal traits and luminal microbiota of the duodenum, jejunum, ileum, and cecum between White Leghorn (WL) and Silky Fowl (SF) chickens at 42 days of age (20 birds per breed; 160 samples). Microbiota were characterized by 16S rRNA gene sequencing, followed by diversity, differential abundance, co-occurrence network, functional prediction, and microbiota-phenotype association analyses. Body weight did not differ between breeds, whereas WL showed higher liver, spleen, and bursa of Fabricius indices and greater length and relative length in all four segments (P < 0.05); SF showed a higher eviscerating rate (P < 0.05). Intestinal segment explained more community variation than breed, with Lactobacillus dominating the small intestine and richness and phylogenetic diversity highest in the cecum. Community composition differed between breeds in the duodenum, jejunum, and cecum (q < 0.05) but not in the ileum. Cecal richness was higher in WL, whereas Shannon diversity did not differ between breeds. In the cecum, Bacteroides was enriched in SF and Megamonas and Lactobacillus in WL (P < 0.05). Co-occurrence networks and predicted functions were breed- and segment-specific, with pathways showing higher predicted abundance in WL concentrated in the duodenum and jejunum and predicted glycan- and carbohydrate-degradation pathways showing higher abundance in SF in the ileum and cecum. Of the four segments, only the cecal predicted functional profile was associated with the measured host phenotypes (RDA P = 0.022), with Bacteroides associated with body weight and eviscerating rate and Megamonas associated with intestinal length traits. Breed-associated microbial differences were therefore detectable at 42 days of age, well before the onset of laying, and were distributed unevenly along the intestinal tract, with the cecum the only compartment in which microbial composition, richness, and predicted functional profiles showed associations with the measured host phenotypes.

Indexed as

CecumGut microbiota, White LeghornIntestinal segmentSilky Fowl

Identifiers

PMID42777361
PMCPMC13625771

What Socratic holds

Textmetadata
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 Socratic graph.