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Integrated systems analysis reveals a molecular network underlying autism spectrum disorders.

Li J, Shi M, Ma Z, Zhao S, Euskirchen G, Ziskin J, Urban A, Hallmayer J, Snyder M - Mol. Syst. Biol. (2014)

Bottom Line: Expression of this module was dichotomized with a ubiquitously expressed subcomponent and another subcomponent preferentially expressed in the corpus callosum, which was significantly affected by our identified mutations in the network center.RNA-sequencing of the corpus callosum from patients with autism exhibited extensive gene mis-expression in this module, and our immunochemical analysis showed that the human corpus callosum is predominantly populated by oligodendrocyte cells.Our analysis delineates a natural network involved in autism, helps uncover novel candidate genes for this disease and improves our understanding of its molecular pathology.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, Stanford Center for Genomics and Personalized Medicine Stanford University School of Medicine, Stanford, CA, USA.

No MeSH data available.


Related in: MedlinePlus

A modular protein interaction network with modules containing enrichment of autism-associated genesTwo topological modules (#2 and #13) on human protein interaction network showed significant enrichment for autism genes (in red). The topological modules are physical clusters on the network where their member genes intensively interact with each other but sparsely interact with non-member genes on the network. A zoom-in view of module #13 is also shown, where known autism genes and genes affected by ASD-associated de novo CNVs were colorized in red and green, respectively. Genes annotated by both were in blue. The false discovery rate indicates its significant enrichment for the known autism genes.
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fig01: A modular protein interaction network with modules containing enrichment of autism-associated genesTwo topological modules (#2 and #13) on human protein interaction network showed significant enrichment for autism genes (in red). The topological modules are physical clusters on the network where their member genes intensively interact with each other but sparsely interact with non-member genes on the network. A zoom-in view of module #13 is also shown, where known autism genes and genes affected by ASD-associated de novo CNVs were colorized in red and green, respectively. Genes annotated by both were in blue. The false discovery rate indicates its significant enrichment for the known autism genes.

Mentions: We first generated a new topological protein interaction network using the most comprehensive human protein interactome from BioGrid (Stark et al, 2011) comprising 13,039 proteins and 69,113 curated interactions (see Materials and Methods, and Supplementary Dataset S1). Since interacting proteins are presumably co-expressed, the quality of these protein interactions was often analyzed by co-expression analysis (Yu et al, 2008). We found significantly increased gene co-expression from this dataset relative to a set of previously benchmarked interacting proteins (Das & Yu, 2012) and also to randomly paired proteins (Supplementary Fig S2, and also see Materials and Methods, P < 1e-10, Wilcoxon rank-sum test), demonstrating high quality of this human protein interactome dataset. We then topologically clustered the proteins that constituted the network into highly interacting modules using a parameter-free algorithm (Materials and Methods) that was specifically designed for detecting community structures in a large-scale network (Blondel et al, 2008). By maximizing the score for network modularity, the human interactome was decomposed into 817 topological modules (Fig1, Supplementary Dataset S1) of non-uniform sizes (Supplementary Fig S3A). Within each module, the proteins tightly interacted with each other, but sparsely with proteins in other modules. This observed modularity of the human interactome was then tested against a set of shuffled networks of the same size by randomly rewiring existing interactions while maintaining the same number of interacting partners. None of the randomized networks achieved the same modularity observed from the network in this study (Supplementary Fig S3B), confirming the significance of these topological clusters (P < 0.01, estimated from the 100 random shufflings).


Integrated systems analysis reveals a molecular network underlying autism spectrum disorders.

Li J, Shi M, Ma Z, Zhao S, Euskirchen G, Ziskin J, Urban A, Hallmayer J, Snyder M - Mol. Syst. Biol. (2014)

A modular protein interaction network with modules containing enrichment of autism-associated genesTwo topological modules (#2 and #13) on human protein interaction network showed significant enrichment for autism genes (in red). The topological modules are physical clusters on the network where their member genes intensively interact with each other but sparsely interact with non-member genes on the network. A zoom-in view of module #13 is also shown, where known autism genes and genes affected by ASD-associated de novo CNVs were colorized in red and green, respectively. Genes annotated by both were in blue. The false discovery rate indicates its significant enrichment for the known autism genes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4300495&req=5

fig01: A modular protein interaction network with modules containing enrichment of autism-associated genesTwo topological modules (#2 and #13) on human protein interaction network showed significant enrichment for autism genes (in red). The topological modules are physical clusters on the network where their member genes intensively interact with each other but sparsely interact with non-member genes on the network. A zoom-in view of module #13 is also shown, where known autism genes and genes affected by ASD-associated de novo CNVs were colorized in red and green, respectively. Genes annotated by both were in blue. The false discovery rate indicates its significant enrichment for the known autism genes.
Mentions: We first generated a new topological protein interaction network using the most comprehensive human protein interactome from BioGrid (Stark et al, 2011) comprising 13,039 proteins and 69,113 curated interactions (see Materials and Methods, and Supplementary Dataset S1). Since interacting proteins are presumably co-expressed, the quality of these protein interactions was often analyzed by co-expression analysis (Yu et al, 2008). We found significantly increased gene co-expression from this dataset relative to a set of previously benchmarked interacting proteins (Das & Yu, 2012) and also to randomly paired proteins (Supplementary Fig S2, and also see Materials and Methods, P < 1e-10, Wilcoxon rank-sum test), demonstrating high quality of this human protein interactome dataset. We then topologically clustered the proteins that constituted the network into highly interacting modules using a parameter-free algorithm (Materials and Methods) that was specifically designed for detecting community structures in a large-scale network (Blondel et al, 2008). By maximizing the score for network modularity, the human interactome was decomposed into 817 topological modules (Fig1, Supplementary Dataset S1) of non-uniform sizes (Supplementary Fig S3A). Within each module, the proteins tightly interacted with each other, but sparsely with proteins in other modules. This observed modularity of the human interactome was then tested against a set of shuffled networks of the same size by randomly rewiring existing interactions while maintaining the same number of interacting partners. None of the randomized networks achieved the same modularity observed from the network in this study (Supplementary Fig S3B), confirming the significance of these topological clusters (P < 0.01, estimated from the 100 random shufflings).

Bottom Line: Expression of this module was dichotomized with a ubiquitously expressed subcomponent and another subcomponent preferentially expressed in the corpus callosum, which was significantly affected by our identified mutations in the network center.RNA-sequencing of the corpus callosum from patients with autism exhibited extensive gene mis-expression in this module, and our immunochemical analysis showed that the human corpus callosum is predominantly populated by oligodendrocyte cells.Our analysis delineates a natural network involved in autism, helps uncover novel candidate genes for this disease and improves our understanding of its molecular pathology.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, Stanford Center for Genomics and Personalized Medicine Stanford University School of Medicine, Stanford, CA, USA.

No MeSH data available.


Related in: MedlinePlus