ArticleFrontiers in genetics2023
Identification of crucial modules and genes associated with backfat tissue development by WGCNA in Ningxiang pigs.
Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 4 citations in OpenAlex.
- Gene co-expression networks related to intramuscular fatty acid composition across different pig genotypes.BMC genomics · 2026Article
- Age-Driven Proteomic Networks in Ningxiang Pig Backfat Identify Candidate Regulators of Carcass Traits.Animals : an open access journal from MDPI · 2026Article
- Metabolomic profiling of backfat in Ningxiang pigs reveals lipid dynamics and carcass trait associations during the fattening stage.PloS one · 2026Article
- Integrative Analysis of Gene Networks Associated with Adipose and Muscle Traits in Hanwoo Steers.Animals : an open access journal from MDPI · 2025Article
- Integration of transcriptome and machine learning to identify the potential key genes and regulatory networks affecting drip loss in pork.Journal of animal science · 2024Article
- Integrated analysis of muscle lncRNA and mRNA of Chinese indigenous breed Ningxiang pig in four developmental stages.Frontiers in veterinary science · 2024Article
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
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Abstract
Fat deposition is an economically important trait in pigs. Ningxiang pig, one of the four famous indigenous breeds in China, is characterized by high fat content. The underlying gene expression pattern in different developmental periods of backfat tissue remains unclear, and the purpose of this investigation is to explore the potential molecular regulators of backfat tissue development in Ningxiang pigs. Backfat tissue (three samples for each stage) was initially collected from different developmental stages (60, 120, 180, 240, 300, and 360 days after birth), and histological analysis and RNA sequencing (RNA-seq) were then conducted. Fragments per kilobase of transcript per million (FPKM) method was used to qualify gene expressions, and differentially expressed genes (DEGs) were identified. Furthermore, strongly co-expressed genes in modules, which were named by color, were clustered by Weighted gene co-expression network analysis (WGCNA) based on dynamic tree cutting algorithm. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment were subsequently implemented, and hub genes were described in each module. Finally, QPCR analysis was employed to validate RNA-seq data. The results showed that adipocyte area increased and adipocyte number decreased with development of backfat tissue. A total of 1,024 DEGs were identified in five comparison groups (120 days vs. 60 days, 180 days vs. 120 days, 240 days vs. 180 days, 300 days vs. 240 days, and 360 days vs. 300 days). The turquoise, red, pink, paleturquoise, darkorange, and darkgreen module had the highest correlation coefficient with 60, 120, 180, 240, 300, and 360 days developmental stage, while the tan, black and turquoise module had strong relationship with backfat thickness, adipocyte area, and adipocyte number, respectively. Thirteen hub genes (
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