Evidence mapPaperPMID 41634852Full record

ArticleAnimal microbiome2026

The developmental trajectory and maturation of the Hulunbuir sheep (Ovis aries) microbiome.

Aifei Yan, Xiunan Li, Jie Cheng, Yan Cheng, Kefyalew Gebeyew, Zhiliang Tan, Jinhe Kang, Zhixiong He

Abstract read
In one paragraph

Article in Animal microbiome, 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

8 authors.

Aifei YanState Key Laboratory of Forage Breeding-by-Design and Utilization, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, and Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan, 410125, China.
Xiunan LiInner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Hohhot, Inner Mongolia, 010031, China.
Jie ChengState Key Laboratory of Forage Breeding-by-Design and Utilization, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, and Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan, 410125, China.
Yan ChengState Key Laboratory of Forage Breeding-by-Design and Utilization, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, and Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan, 410125, China.
Kefyalew GebeyewState Key Laboratory of Forage Breeding-by-Design and Utilization, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, and Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan, 410125, China.
Zhiliang TanState Key Laboratory of Forage Breeding-by-Design and Utilization, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, and Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan, 410125, China.
Jinhe KangState Key Laboratory of Forage Breeding-by-Design and Utilization, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, and Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan, 410125, China. kangjh@isa.ac.cn.
Zhixiong HeState Key Laboratory of Forage Breeding-by-Design and Utilization, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, and Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan, 410125, China. zxhe@isa.ac.cn.

Funding

National Natural Science Foundation of China 32350410422Natural Science Foundation of China 32302783Natural Science Foundation of Hunan Province of China 2022JJ10054the National Natural Science Foundation of China 32350410422
6 · The paper itself

Abstract

The rumen microbiota plays a pivotal role in the growth performance of host animals, primarily due to its ability to ferment ingested feed. Hulunbuir sheep exhibited a slow growth rate compared to other local breeds. A deeper comprehension of the development of the rumen bacteria community in Hulunbuir sheep can offer insights into the factors contributing to their slow growth rate. This study utilized metagenomic analysis of rumen content samples from Hulunbuir sheep to investigate the patterns of microbial growth and their relationship with the ADG. The results of the PCoA and enterotype analyses demonstrated that the ruminal bacterial community developed distinct characteristics following weaning. The dominant bacterial phyla in the rumen of Hulunbuir sheep, Bacteroidetes and Firmicutes, exhibited a significant age-related change. At the genus level, while the abundance of dominant bacterial genera changed with the growth of Hulunbuir sheep, Prevotella consistently maintained a high abundance across all age time points. We then examined the effects of age on microbial function by analyzing carbohydrate-metabolizing enzymes and protein-metabolizing peptidases. The abundance of carbohydrate-metabolizing enzymes decreased with growth, while peptidases showed opposite dynamics. Under the current feeding conditions correlation analysis showed that the abundances of Firm-04, CAG-83, and GCA-900,199,385 were negatively correlated with ADG (R<-0.4, p < 0.05), while the abundance of Ga6A1 was positively correlated with ADG (R > 0.5, p < 0.05). In addition, we found 67 MAGs related to ADG, which are capable of secreting carbohydrates-metabolizing enzymes and peptidase. This study uncovers the temporal dynamics of rumen microbiota development during the early to late fattening phase and identifies microbes associated with ADG, which could inform strategies to improve growth and production efficiency.

Indexed as

ADGCAZymesMicrobial successionPeptidaseRumen microbiome

Identifiers

PMID41634852
PMCPMC12869976

What Socratic 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 Socratic graph.