Evidence map›Paper›PMID 40575980›Full record

ArticleAnimal bioscience2025

Comprehensive co-expression analysis reveals candidate regulatory genes associated with carcass and meat quality traits in Neijiang and Large White pigs.

Patrick Kofi Makafui Tecku, Dong Chen, Kai Wang, Shixin Yu, Jiamiao Chen, Guoqing Tang

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Article in Animal bioscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Patrick Kofi Makafui TeckuKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Dong ChenKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Kai WangNew Hope Liuhe Co., Ltd., Key Laboratory of Digital Intelligent Breeding Technological Innovation for Swine and Poultry, Ministry of Agriculture and Rural Affairs, Chengdu, China.
Shixin YuKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Jiamiao ChenKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Guoqing TangKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.

Funding

Earmarked Fund for China Agriculture Research System CARS-35-01ANational Center of Technology Innovation for Pigs NCTIP-XD/B01National Key R&D Program of China 2018YFD0501204National Natural Science Foundation of China C170102Sichuan Innovation Team of Pig sccxtd-2021-08Sichuan Science and Technology Program 2020YFN0024Sichuan Science and Technology Program 2021YFYZ0030Sichuan Science and Technology Program 2021ZDZX0008
6 · The paper itself

Abstract

objectiveThe Neijiang indigenous pig breed of China and the Western Large White pig breed have unique meat quality and carcass characteristics. However, the genetic factors and mechanisms influencing their distinct meat and carcass traits are still not well understood. Therefore, using weighted gene co-expression network analysis (WGCNA), this study aimed to identify key genes influencing these traits.

methodsTranscriptome data from 17 Neijiang and 22 Large White pigs, along with their carcass weight, backfat thickness, eye muscle area, meat color, and muscle pH phenotypic data, were analyzed using WGCNA. A total of 9,249 genes were used to construct a weighted gene co-expression network.

resultsTwenty-two co-expression gene modules were identified. Genes in the top modules were enriched in processes relevant to carcass and meat quality, such as protein transport. Further analysis identified six key genes, including HSPH1, HSPA4, DNAJA4, MRPL3, SEC63, and SRP54, for the Neijiang breed. Also, five key genes, consisting of EP300, SETD2, NIPBL, NAT10, and VCP, were identified for the Large White population. These genes were involved in biological processes related to mitochondrial function, protein targeting, chromatin organization, and morphogenesis.

conclusionThe findings from this study elucidate the regulatory mechanisms influencing the carcass and meat characteristics of the Neijiang and Large White pigs. The key genes could serve as potential biomarkers for enhancing breeding strategies aimed at improving pork quality.

Indexed as

Carcass TraitKey GeneMeat QualityPigWeighted Gene Co-expression Network Analysis (WGCNA)

Identifiers

PMID40575980
PMCPMC12580783

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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.