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Systems-level analyses identify extensive coupling among gene expression machines.

ABSTRACT: Here, we develop computational methods to assess and consolidate large, diverse protein interaction data sets, with the objective of identifying proteins involved in the coupling of multicomponent complexes within the yeast gene expression pathway. From among approximately 43 000 total interactions and 2100 proteins, our methods identify known structural complexes, such as the spliceosome and SAGA, and functional modules, such as the DEAD-box helicases, within the interaction network of proteins involved in gene expression. Our process identifies and ranks instances of three distinct, biologically motivated motifs, or patterns of coupling among distinct machineries involved in different subprocesses of gene expression. Our results confirm known coupling among transcription, RNA processing, and export, and predict further coupling with translation and nonsense-mediated decay. We systematically corroborate our analysis with two independent, comprehensive experimental data sets. The methods presented here may be generalized to other biological processes and organisms to generate principled, systems-level network models that provide experimentally testable hypotheses for coupling among biological machines.

SUBMITTER: Maciag K

PROVIDER: S-EPMC1681477 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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Systems-level analyses identify extensive coupling among gene expression machines.

Maciag Karolina K Altschuler Steven J SJ Slack Michael D MD Krogan Nevan J NJ Emili Andrew A Greenblatt Jack F JF Maniatis Tom T Wu Lani F LF

Molecular systems biology 20060117

Here, we develop computational methods to assess and consolidate large, diverse protein interaction data sets, with the objective of identifying proteins involved in the coupling of multicomponent complexes within the yeast gene expression pathway. From among approximately 43 000 total interactions and 2100 proteins, our methods identify known structural complexes, such as the spliceosome and SAGA, and functional modules, such as the DEAD-box helicases, within the interaction network of proteins ...[more]

PMID: 16738550

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Project description:PurposeIncreasing evidence suggests myopia is not a simple refractive error, many other factors might also be involved. Here, we assessed myopic and normal corneas' gene expression profiles to identify possible diagnostic and therapeutic biomarkers for myopia.Materials and methodsWe obtained the expression profile of ten patients and seven normal control samples from the GSE112155 and GSE151631 datasets based on the Gene Expression Omnibus (GEO) database. We used the "limma" R package to determine the differentially expressed genes (DEGs) between myopic and normal corneas. Weighted gene co-expression network analysis (WGCNA) was used to identify critical co-expressed modules related to myopia, and enrichment analyses were used to annotate the function of genes encompassed in the compulsory module. We also validated these findings in two external datasets (GSE24641 and GSE136701).ResultsWe identified that the DEGs were significantly enriched in ultraviolet (UV) response, TNF-α signaling via NFκB, Angiogenesis, Myogenesis pathways, etc. We used 2095 genes to construct the co-expression gene modules and found five interesting modules because the eigengene expression of these modules was significantly differentially expressed between myopic and normal corneas. Notably, the enrichment analysis found that the genes encompassed in lightgreen module were significantly enriched in immune-related pathways. These findings were proved by subsequent analysis based on Xcell software. We found the component of B cells, CD4+ memory T cells, CD8+ central memory T cells, plasmacytoid dendritic cells, T helper 2 (Th2) cells, regulatory T cells (Tregs), etc. were significantly increased in myopic corneas, while CD8+ T cells, CD4+ T central memory cells, natural killer T (NKT) cells, and T helper 1 (Th1) cells were significantly decreased.ConclusionOur findings identified some markers that might detect diagnosis and treatment for myopia from cornea aspect. Future studies are warranted to verify the functional role of immune-related pathways in cornea during the pathogenesis or progression of myopia.

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Systems-level analyses identify extensive coupling among gene expression machines.

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Systems-level analyses identify extensive coupling among gene expression machines.

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