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Cited by 106Bioinformatics and Genomic NetworksAdipokines, Inflammation, and Metabolic DiseasesGenetic and phenotypic traits in livestock

Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA sequencing in a porcine model

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Kogelman, Lisette J A, Cirera, Susanna, Zhernakova, Daria V, Fredholm, Merete, Franke, Lude, Kadarmideen, Haja N·2014·BMC Medical Genomics
DOI 10.1186/1755-8794-7-57PMC PMC4183073
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Abstract

BACKGROUND: Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model. METHODS: We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. RESULTS: WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P < 0.001). Functional annotation identified pathways enlightening the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and 34.58). Moreover, detection of differentially connected genes identified various genes previously identified to be associated with obesity in humans and rodents, e.g. CSF1R and MARC2. CONCLUSIONS: To our knowledge, this is the first study to apply systems biology approaches using porcine adipose tissue RNA-Sequencing data in a genetically characterized porcine model for obesity. We revealed complex networks, pathways, candidate and regulatory genes related to obesity, confirming the complexity of obesity and its association with immune-related disorders and osteoporosis.

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  • WGCNA was the first co-expression tool to be applied to RNA-seq data; it has effectively identified biologically relevant associations between phenotypes and modules, performing similarly to microarray-based analyses.

    “WGCNA was the first co-expression tool to be applied to RNA-seq data; it has effectively identified biologically relevant associations between phenotypes and modules [19, 66, 67], performing similarly to microarray-based analyses.”

    From Gene co-expression analysis for functional classification and gene–disease predictions (2017) · cites this paper as [66]

    The Results and discussion section reports that WGCNA identified modules correlated with obesity-related traits in porcine RNA-seq data, supporting the phenotype–module association. The Background does not say WGCNA was the first co-expression tool applied to RNA-seq; its narrower first-study claim concerns obesity in a porcine model. It also reports better estimation of network properties with RNA-seq than with microarrays, rather than establishing similar performance. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • Co-expression analysis of RNA-seq data of lean and obese porcines identified obesity-related modules and a link between obesity, the immune system and bone remodelling, with CCR1, MSR1 and SPI1 identified as possible regulators.

    “Co-expression analysis of RNA-seq data of lean and obese porcines identified obesity-related modules [66], and a link was found between obesity, the immune system and bone remodelling, with the study identifying CCR1, MSR1 and SPI1 as possible regulators in these processes.”

    From Gene co-expression analysis for functional classification and gene–disease predictions (2017) · cites this paper as [66]

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Research works printed but not linked: 1

  1. Kadarmideen HN Kogelman LJA RNA-Sequencing of lean, intermediate, and obese pigs NCBI's Gene Expression Omnibus 2014 1 http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61271

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Authors
Kogelman, L. J. A., Cirera, S., Zhernakova, D. V., Fredholm, M., Franke, L., & Kadarmideen, H. N.
Affiliations
  • University of Copenhagen (DK)
  • University Medical Center Groningen (NL)
Corresponding author
Kadarmideen, Haja N
ORCID
Venue
BMC Medical Genomics
Publisher
Springer Science and Business Media LLC
Published
2014-09-30
Volume
7
Issue
1
Pages
57-57
ISSN
1755-8794 (ISSN-L)
DOI
10.1186/1755-8794-7-57
PMC
PMC4183073
OpenAlex
W2153892583
Cited by
106
References
113
Citations by year
2026: 1 · 2025: 5 · 2024: 8 · 2023: 5 · 2022: 14 · 2021: 10 · 2020: 12 · 2019: 7 · 2018: 13 · 2017: 8 · 2016: 14 · 2015: 9
FWCI
4.24
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Medical Genomics (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
Funders
  • Strategiske Forskningsråd
  • European Commission (293511)
  • Copenhagen Graduate School for Nanoscience and Nanotechnology
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords
obesity, adipose tissue, porcine model, co-expression network, gene regulatory networks, transcriptional regulation, osteoclastogenesis, osteoporosis, immune pathways, CCR1, MSR1, CSF1R, type 2 diabetes, B cell receptor signaling, NK cell cytotoxicity
MeSH terms
Adipose Tissue, Animals, Disease Models, Animal, Female, Humans, Male, Obesity, Swine, Transcription, Genetic, Sequence Analysis, RNA, Systems Biology, Gene Regulatory Networks

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