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Updated: Apr 17, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Gene coexpression networks reveal key drivers of phenotypic divergence in porcine muscle
Xiao Zhao1, Zhao-Yang Liu2, Qing-Xin Liu3
1Laboratory of Developmental Genetics, Shandong Agricultural University, Tai'an, Shandong, China. zhxicgz@gmail.com.
Background:
Domestication of the wild pig has led to obese and lean phenotype breeds, and evolutionary genome research has sought to identify the regulatory mechanisms underlying this phenotypic diversity. However, revealing the molecular mechanisms underlying muscle phenotype variation based on differentially expressed genes has proved to be difficult. To characterize the mechanisms regulating muscle phenotype variation under artificial selection, we aimed to provide an integrated view of genome organization by weighted gene coexpression network analysis.
Results:
Our analysis was based on 20 publicly available next-generation sequencing datasets of lean and obese pig muscle generated from 10 developmental stages. The evolution of the constructed coexpression modules was examined using the genome resequencing data of 37 domestic pigs and 11 wild boars. Our results showed the regulation of muscle development might be more complex than had been previously acknowledged, and is regulated by the coordinated action of muscle, nerve and immunity related genes. Breed-specific modules that regulated muscle phenotype divergence were identified, and hundreds of hub genes with major roles in muscle development were determined to be responsible for key functional distinctions between breeds. Our evolutionary analysis showed that the role of changes in the coding sequence under positive selection in muscle phenotype divergence was minor.
Conclusions:
Muscle phenotype divergence was found to be regulated by the divergence of coexpression network modules under artificial selection, and not by changes in the coding sequence of genes. Our results present multiple lines of evidence suggesting links between modules and muscle phenotypes, and provide insights into the molecular bases of genome organization in muscle development and phenotype variation.
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