Evidence map›Paper›PMID 40069611›Full record

ArticleBMC genomics2025

Identification of key LncRNAs and mRNAs associated with intramuscular fat in pig via WGCNA.

Wenqiang Li, Suozhou Yang, Huixin Liu, Zhi Cao, Fei Xu, Chao Ning, Qin Zhang, Dan Wang, Hui Tang

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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

9 authors.

Wenqiang LiShandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science & Technology, Shandong Agricultural University, 61 Daizong Street, Taian City, Shandong Province, 271018, China.
Suozhou YangShandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science & Technology, Shandong Agricultural University, 61 Daizong Street, Taian City, Shandong Province, 271018, China.
Huixin LiuShandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science & Technology, Shandong Agricultural University, 61 Daizong Street, Taian City, Shandong Province, 271018, China.
Zhi CaoShandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science & Technology, Shandong Agricultural University, 61 Daizong Street, Taian City, Shandong Province, 271018, China.
Fei XuShandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science & Technology, Shandong Agricultural University, 61 Daizong Street, Taian City, Shandong Province, 271018, China.
Chao NingShandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science & Technology, Shandong Agricultural University, 61 Daizong Street, Taian City, Shandong Province, 271018, China.
Qin ZhangShandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science & Technology, Shandong Agricultural University, 61 Daizong Street, Taian City, Shandong Province, 271018, China.
Dan WangShandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science & Technology, Shandong Agricultural University, 61 Daizong Street, Taian City, Shandong Province, 271018, China. wangd_18@163.com.
Hui TangShandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, College of Animal Science & Technology, Shandong Agricultural University, 61 Daizong Street, Taian City, Shandong Province, 271018, China. tanghui@sdau.edu.cn.

Funding

Agricultural Animal Breeding Project of Shandong Province 2020LZGC012National Outstanding Youth Science Fund Project of National Natural Science Foundation of China 32002172the 14th Five-Year Plan" national key research Project 2021YFD1301203The National Natural Science Foundation of China 32102526the Shandong Provincial Natural Science Foundation ZR2020QC175the Shandong Provincial Natural Science Foundation ZR2020QC176
6 · The paper itself

Abstract

backgroundIntramuscular fat (IMF) not only directly affects the tenderness, juiciness, and overall flavour of meat but also plays a significant role in influencing consumer preferences for pork. Therefore, exploring key biomarkers that influence IMF deposition is highly important for breeding high-quality pork. IMF is a typical quantitative trait that is regulated by the interaction of multiple coding and noncoding RNAs. Traditional differential analysis methods typically focus on individual genes, making it difficult to identify key genes and their underlying mechanisms accurately. Weighted gene coexpression network analysis (WGCNA) is an efficient and accurate method for identifying and characterizing key pathways and genes associated with complex traits. Therefore, the aim of this study was to construct an mRNA‒lncRNA coexpression network related to IMF using WGCNA to explore and identify potential candidate genes that influence IMF in pigs.

resultsFull-length transcriptome sequencing was performed on 31 220-day-old Jiangquan black pigs raised in the same environment, and a gene expression matrix comprising 25,609 genes was constructed. Nine coexpression modules were identified through WGCNA, with the number of genes in these modules ranging from 33 to 3648. The magenta module (corr = 0.7, P < 0.01) and the turquoise module (corr = -0.77, P < 0.01) were significantly associated with IMF deposition. Hub genes in each module were identified on the basis of the screening criteria of GS > 0.4 and MM > 0.8. Combined with enrichment analysis and protein‒protein interaction (PPI) analysis, 18 key mRNAs potentially related to IMF were selected: CRKL, CBL, PDGFRB, DOCK1, YWHAH, HSP90AB1, LOC100524873, NDUFA1, NDUFA11, NDUFA12, NDUFA2, NDUFAB1, NDUFB10, NDUFB3, NDUFB7, NDUFS5, NDUFS6, and UQCR10. To explore the regulatory role of lncRNAs in the process of IMF deposition, we constructed an lncRNA‒mRNA‒pathway network on the basis of the relationships between lncRNAs and key mRNAs, as well as the results of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. This network includes four key lncRNAs (TGOLN2, LOC100521518, LOC100524915, and LOC100622481) and predicts the potential mechanisms by which lncRNAs regulate IMF deposition.

conclusionsThrough WGCNA, enrichment analysis, and PPI analysis, 18 mRNAs and four lncRNAs potentially involved in IMF deposition were identified, and the lncRNA regulatory pathways were preliminarily explored. Our findings provide new insights into the regulatory mechanisms of pig IMF deposition and lay the foundation for further exploration of the molecular mechanisms underlying pig fat deposition.

Indexed as

Adipose TissueGene Regulatory NetworksMuscle, SkeletalRNA, Long NoncodingRNA, MessengerAnimalsGene Expression ProfilingSwineTranscriptomeRNA, Long NoncodingRNA, MessengerIntramuscular fat (IMF)LncRNAPigsProtein‒protein interaction (PPI)RNA-seqWeighted gene coexpression network analysis (WGCNA)

Identifiers

PMID40069611
PMCPMC11895181

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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.