Evidence map›Paper›PMID 40344088›Full record

ArticlePloS one2025

Integrating genomics and transcriptomics reveals candidate genes affecting loin muscle area in Huaxi cattle.

Qingqing Xue, Lili Du, Tianyu Deng, Mang Liang, Keanning Li, Li Qian, Shiyuan Qiu, Yan Chen, Xue Gao, Lingyang Xu and 5 more

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. New Sights into Bioinformatics of Gene Regulations and Structure.International journal of molecular sciences · 2025
    Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Qingqing XueDepartment of College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, Heilongjiang, China.
Lili DuDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Tianyu DengDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Mang LiangDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Keanning LiDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Li QianDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Shiyuan QiuDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Yan ChenDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Xue GaoDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Lingyang XuDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Zezhao WangDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Caihong ZhengDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Lupei ZhangDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Junya LiDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Huijiang GaoDepartment of Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-5502-2528

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Loin muscle area (LMA) is an indicator of carcass composition and is related to weight gain, animal musculature and meat quality traits. Therefore, integrating multi-omics data to reveal candidate genes affecting LMA has attracted extensive attention. We used the combined analysis method of GWAS and RNA-seq to find the candidate genes that affect the size of LMA. The association of 770K SNPs with the LMA captured four significant SNPs within or near three genes. Additionally, seven overlapping genes regarding LMA were determined via the analysis of differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA). There is an overlapping gene (CD93) between the results of GWAS and DEGs. Through functional enrichment analysis of the above genes, candidate genes were identified as THBD, CD93, RIMS2, PLP1, SNCA, and NDUFS8, and it was found that they mainly affected the size of LMA by affecting muscle fiber diameter, muscle cell development, differentiation, and function. The findings provide valuable molecular insights into the mechanisms that influence LMA content in beef cattle.

Indexed as

GenomicsMuscle, SkeletalTranscriptomeAnimalsCattleGene Expression ProfilingGenome-Wide Association StudyPolymorphism, Single Nucleotide

Identifiers

PMID40344088
PMCPMC12064012

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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.