Evidence map›Paper›PMID 41580592›Full record

ArticleBMC genomics2026

Integrated analysis of DNA methylome and transcriptome of the backfat and longissimus dorsi muscle of Chinese-European hybrid pigs.

Mei Ge, Chenyu Li, Tao Jiang, Yani Huang, Zhiyan Zhang

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Article in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mei Ge *National Key Laboratory for Swine Genetic Improvement and Germplasm innovation Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Chenyu Li *National Key Laboratory for Swine Genetic Improvement and Germplasm innovation Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Tao JiangNational Key Laboratory for Swine Genetic Improvement and Germplasm innovation Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Yani HuangNational Key Laboratory for Swine Genetic Improvement and Germplasm innovation Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Zhiyan ZhangNational Key Laboratory for Swine Genetic Improvement and Germplasm innovation Technology, Jiangxi Agricultural University, Nanchang, 330045, China. bioducklily@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe longissimus dorsi muscle and backfat are important components of pork and complement each other in physiological function, significantly influencing key traits such as growth performance, carcass traits, and meat quality. While the transcriptomic atlas across different tissues in pigs has been widely studied, the underlying epigenetic regulatory mechanisms remain to be explored. In this study, we collected muscle and adipose tissues from hybrid offspring of lean-type (Western commercial pigs) and fat-type (Chinese indigenous pigs) pigs (n = 6) and performed integrated transcriptomic (RNA-seq) and DNA methylome (GM-seq) analysis to explore how DNA methylation coordinates tissue-specific differential gene expression. This has practical implications for optimizing breeding strategies and selecting superior breeds.

resultsTranscriptome sequencing identified 2,908 differentially expressed genes, which are primarily involved in collagen fibril organization, skeletal muscle contraction, and muscle organ development. Whole-genome DNA methylation sequencing identified 2,787 differentially methylated genes in the promoter region. Through integrative analysis, we found 571 genes that were shared, 390 of which showed a significant negative correlation between gene expression and promoter DNA methylation. These genes are mainly involved in cholesterol metabolism, PPAR signaling pathway, cytoskeleton in muscle cell, and calcium ion signaling pathways. Notably, we discovered that the differential expression of genes such as APOE, FABP4, TNNI2, and TNNT3 between tissues is negatively regulated by promoter DNA methylation. In other words, low methylation of these gene promoters in one tissue was associated with high expression, while high methylation of the promoter in the opposite tissue suppressed expression.

conclusionsThese results suggest that DNA methylation plays an extensive and subtle regulatory role in tissue-specific gene expression, thereby facilitating different tissues to execute their specific physiological functions. This study further enriches our understanding of the integrative mechanisms between epigenetic regulation and transcriptomics in pigs and provides important theoretical foundations for precision molecular breeding.

Indexed as

Adipose TissueDNA MethylationEpigenomeMuscle, SkeletalTranscriptomeAnimalsEpigenesis, GeneticGene Expression ProfilingSwineBackfatChinese-European hybrid pigsDNA methylomeLongissimus dorsi muscleTranscriptome

Identifiers

PMID41580592
PMCPMC12914914

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.