Understanding multicellular function and disease with human tissue-specific networks

By Casey S. Greene, Arjun Krishnan, Aaron K. Wong, E. Ricciotti, R. A. Zelaya, Daniel S. Himmelstein, Ran Zhang, B. Hartmann, E. Zaslavsky, S. Sealfon and 5 more. 2015

816 citations recorded by the source corpus.

Tissue and cell-type identity lie at the core of human physiology and disease. Understanding the genetic underpinnings of complex tissues and individual cell lineages is crucial for developing improved diagnostics and therapeutics. We present genome-wide functional interaction networks for 144 human tissues and cell types developed using a data-driven Bayesian methodology that integrates thousands of diverse experiments spanning tissue and disease states. Tissue-specific networks predict lineage-specific responses to perturbation, identify the changing functional roles of genes across tissues and illuminate relationships among diseases. We introduce NetWAS, which combines genes with nominally significant genome-wide association study (GWAS) P values and tissue-specific networks to identify disease-gene associations more accurately than GWAS alone. Our webserver, GIANT, provides an interface to human tissue networks through multi-gene queries, network visualization, analysis tools including NetWAS and downloadable networks. GIANT enables systematic exploration of the landscape of interacting genes that shape specialized cellular functions across more than a hundred human tissues and cell types.

Subfields: Molecular Biology

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Citations in the corpus

Learning Explainable Models Using Attribution Priors (2019, methodology): “[4] A.”
Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases (2018, background): “Recent studies have further introduced comprehensive collections of tissue-specific networks (Greene et al., 2015; Marbach et al., 2016).”
Comprehensive Analysis of Tissue-wide Gene Expression and Phenotype Data Reveals Tissues Affected in Rare Genetic Disorders (2017, background): “For such genes, cross-tissue transcriptional activity may provide limited explanation with regard to the affected tissues (Barshir et al., 2014; stems 5, 1–9, August 23, 2017 ª 2017 Published by Elsevier Inc. 1 Greene et al., 2015; Melé et al., 2015).”
The BioGRID interaction database: 2017 update (2016, background): “These improvements will also allow the precise capture of more complex interaction contexts, for example higher order genetic interactions, splice isoform dependent protein interactions, and tissue-specific interactions (82).”
The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest (2022, background): “Among frequently used and actively maintained frameworks are ConsensusPathDB (14), FunCoup (15), GeneMANIA (16), HumanBase (17), HumanNet (18), IID (19) and STRING (20–22).”
Network propagation: a universal amplifier of genetic associations (2017, background): “There has been promising research into developing such networks 84,95 , with important developments underway from the Genotype-Tissue Expression (GTEx) project, which enables the construction of a specific network for each major human tissue 96 .”
Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder (2016, methodology): “We have shown that multiple genes associated with a particular disease often tend to have similar patterns of connectivity in a relevant tissue-specific functional network 21 .”