ArticleEuropean journal of human genetics : EJHG2011
An atlas of tissue-specific conserved coexpression for functional annotation and disease gene prediction.
Article in European journal of human genetics : EJHG, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A comprehensive transcriptional reference for severity and progression in spinal cord injury reveals novel translational biomarker genes.Journal of translational medicine · 2025Pooled it
- Free D-aspartate modulates the expression of proteins linked to schizophrenia and autism spectrum disorder during early postnatal life.Cellular and molecular life sciences : CMLS · 2025Article
- Endometrial receptivity profiled through transcriptomic analysis of uterine fluid extracellular vesicles using systems biology and bayesian modeling for pregnancy prediction.Scientific reports · 2025Article
- Cell type heterogeneity in gene co-expression networks: implications for toxicological research.Briefings in bioinformatics · 2025Review
- Article
- Gene communities in co-expression networks across different tissues.PLoS computational biology · 2023Article
- MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies.PLoS genetics · 2021Article
- Enhanced Understanding of Molecular Interactions and Function Underlying Pain Processes Through Networks of Transcript Isoforms, Genes, and Gene Families.Advances and applications in bioinformatics and chemistry : AABC · 2021Article
- MyoMiner: explore gene co-expression in normal and pathological muscle.BMC medical genomics · 2020Article
- Conserved DNA Methylation Signatures in Early Maternal Separation and in Twins Discordant for COScientific reports · 2018Article
- Co-expression networks reveal the tissue-specific regulation of transcription and splicing.Genome research · 2017Article
- In silico prediction of lncRNA function using tissue specific and evolutionary conserved expression.BMC bioinformatics · 2017Article
- Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.Frontiers in systems neuroscience · 2017Article
- Synaptic Interactome Mining Reveals p140Cap as a New Hub for PSD Proteins Involved in Psychiatric and Neurological Disorders.Frontiers in molecular neuroscience · 2017Article
- Characterization of candidate genes in inflammatory bowel disease-associated risk loci.JCI insight · 2016Article
- Immuno-Navigator, a batch-corrected coexpression database, reveals cell type-specific gene networks in the immune system.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- It is time to take timing seriously in clinical genetics.European journal of human genetics : EJHG · 2015Article
- UNCLES: method for the identification of genes differentially consistently co-expressed in a specific subset of datasets.BMC bioinformatics · 2015Article
- Sharing and Specificity of Co-expression Networks across 35 Human Tissues.PLoS computational biology · 2015Article
- Systems genetics identifies Sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus.Nature communications · 2015Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene coexpression relationships that are phylogenetically conserved between human and mouse have been shown to provide important clues about gene function that can be efficiently used to identify promising candidate genes for human hereditary disorders. In the past, such approaches have considered mostly generic gene expression profiles that cover multiple tissues and organs. The individual genes of multicellular organisms, however, can participate in different transcriptional programs, operating at scales as different as single-cell types, tissues, organs, body regions or the entire organism. Therefore, systematic analysis of tissue-specific coexpression could be, in principle, a very powerful strategy to dissect those functional relationships among genes that emerge only in particular tissues or organs. In this report, we show that, in fact, conserved coexpression as determined from tissue-specific and condition-specific data sets can predict many functional relationships that are not detected by analyzing heterogeneous microarray data sets. More importantly, we find that, when combined with disease networks, the simultaneous use of both generic (multi-tissue) and tissue-specific conserved coexpression allows a more efficient prediction of human disease genes than the use of generic conserved coexpression alone. Using this strategy, we were able to identify high-probability candidates for 238 orphan disease loci. We provide proof of concept that this combined use of generic and tissue-specific conserved coexpression can be very useful to prioritize the mutational candidates obtained from deep-sequencing projects, even in the case of genetic disorders as heterogeneous as XLMR.
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