Integrating Genetic and Network Analysis to Characterize Genes Related to Mouse Weight
Open accessAbstract
Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight-related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.
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Subsequently, networks were modeled based on co-expression across a series of perturbations with genes as nodes and correlations as edges.
“Subsequently, networks were modeled based on co-expression across a series of perturbations with the genes encoding the transcripts corresponding to the nodes and the correlations to the edges [67–69].”
From Multi-omics approaches to disease (2017) · cites this paper as [67]
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- Authors
- Ghazalpour, A., Doss, S., Zhang, B., Wang, S., Plaisier, C., Castellanos, R., Brozell, A., Schadt, E. E., Drake, T. A., Lusis, A. J., & Horvath, S.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Horvath, Steve
- ORCID
- Venue
- PLoS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2006-08-18
- Volume
- 2
- Issue
- 8
- Pages
- e130
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- OpenAlex
- W1973651601
- Cited by
- 462
- References
- 52
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 15 · 2023: 14 · 2022: 25 · 2021: 38 · 2020: 27 · 2019: 27 · 2018: 22 · 2017: 14 · 2016: 17 · 2015: 18 · 2014: 20 · 2013: 26 · 2012: 32
- FWCI
- 11.95
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Genetics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (HL3 0568, HL28481, P01HL030568, P01HL028481)
- National Human Genome Research Institute (T32HG002536)
- National Institute of General Medical Sciences (T32GM007104, GM08234, GM 07104)
- National Institute of Allergy and Infectious Diseases (U19AI063603)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- mouse body weight, gene co-expression network, gene modules, hepatic gene expression, complex traits, systems biology
- MeSH terms
- Animals, Body Weight, Chromosome Mapping, Crosses, Genetic, Female, Liver, Mice, Inbred C3H, Mice, Inbred C57BL, Models, Genetic, Cluster Analysis, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Gene Expression Profiling, Quantitative Trait Loci, Mice
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