Evidence map›Paper›PMID 40394515›Full record

ArticleBMC genomics2025

Application of multi-omics technology in pathogen identification and resistance gene screening of sheep pneumonia.

Kai Huang, Lvfeng Yuan, Jia Liu, Xiaolong Li, Dan Xu, Xiaoxue Zhang, Jie Peng, Huibin Tian, Fadi Li, Weimin Wang

Abstract read
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Genomic insights into the recent evolution and biodiversity of Italian sheep breeds.Mammalian genome : official journal of the International Mammalian Genome Society · 2025
    Article
  6. 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.

Kai HuangState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems; Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs; Engineering Research Center of Grassland Industry, Ministry of Education; College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, 730020, China.
Lvfeng YuanLanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Lanzhou, 730046, China.
Jia LiuCollege of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
Xiaolong LiState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems; Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs; Engineering Research Center of Grassland Industry, Ministry of Education; College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, 730020, China.
Dan XuState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems; Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs; Engineering Research Center of Grassland Industry, Ministry of Education; College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, 730020, China.
Xiaoxue ZhangCollege of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
Jie PengCollege of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
Huibin TianState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems; Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs; Engineering Research Center of Grassland Industry, Ministry of Education; College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, 730020, China.
Fadi LiState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems; Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs; Engineering Research Center of Grassland Industry, Ministry of Education; College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, 730020, China.
Weimin WangState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems; Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs; Engineering Research Center of Grassland Industry, Ministry of Education; College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, 730020, China. wangweimin@lzu.edu.cn.

Funding

Innovation 2030-Major Project of Agricultural Biotech Breeding 2022ZD04013
6 · The paper itself

Abstract

backgroundPneumonia constitutes a major health challenge in sheep, severely compromising growth rates and overall productivity, and resulting in considerable economic losses to the sheep industry. To address this issue, the development of disease-resistant breeding programs based on the identification of genetic markers associated with pneumonia susceptibility is of critical importance. This study investigated a sheep population on a farm where pneumonia was endemic. The purpose was to use multi-omics methods to rapidly identify the principal pathogens responsible for pneumonia outbreaks, and to screen for genetic loci and key genes related to pneumonia resistance, thereby providing a scientific basis for the implementation of targeted breeding strategies for pneumonia resistance.

resultsHere, we assessed the impact of pneumonia on sheep growth by evaluating the pneumonia phenotypes of 912 sheep. High-throughput transcriptome sequencing of 40 lungs was conducted to obtain exogenous RNA fragments for microbial sequence alignment. Additionally, 16S rRNA sequencing was performed on lung tissues from 10 healthy and 10 diseased sheep to identify biomarkers associated with phenotypic differences. Mycoplasma ovipneumoniae was identified as the primary pneumonia pathogen, and its presence was further validated by load quantification and immunohistochemical analysis. Integration of genome-wide association study (GWAS) data from 266 lung pathological scores with transcriptome-based differentially expressed genes analysis enabled the identification of five single nucleotide polymorphisms (SNPs) and three potential candidate genes associated with Mycoplasma pneumonia. Subsequent genotyping and phenotype association analyses confirmed the significance of two SNPs and established a strong association between the FOXF1 gene and resistance to Mycoplasma pneumonia.

conclusionsHigh-throughput sequencing technologies have enabled the rapid and accurate identification of the causative pathogen of sheep pneumonia. By integrating multi-omics data, two genomic loci significantly associated with Mycoplasma pneumonia were screened, as well as an anti-Mycoplasma pneumonia key gene, FOXF1.

Indexed as

Disease ResistanceGenomicsPneumoniaSheep DiseasesAnimalsGene Expression ProfilingGenome-Wide Association StudyHigh-Throughput Nucleotide SequencingLungMultiomicsMycoplasma ovipneumoniaePhenotypePolymorphism, Single NucleotideRNA, Ribosomal, 16SSheepTranscriptomeRNA, Ribosomal, 16SDisease-resistant breedingGenome-wide association studyMulti-omicsMycoplasma ovipneumoniaePathogen identificationSheep

Identifiers

PMID40394515
PMCPMC12090697

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LicenceCC BY-NC-ND
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Registered trials

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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.