Validation and refinement of gene-regulatory pathways on a network of physical interactions

Yeang, Chen‐Hsiang; Mak, H. Craig; McCuine, Scott; Workman, Christopher T.; Jaakkola, Tommi S.; Ideker, Trey

doi:10.1186/gb-2005-6-7-r62

Cited by 76 publications

(26 citation statements)

References 29 publications

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“…In both of these cases, perturbed genes (either explicitly by gene deletion or implicitly through popula- Cold Spring Harbor Laboratory Press on May 11, 2018 -Published by genome.cshlp.org Downloaded from tion genetics) are linked to genes downstream whose expression levels are affected by perturbation. For integrative analysis of these data, a number of network-based approaches have been proposed that map the molecular interaction pathways leading from each causal gene to its affected genes (Yeang et al 2004(Yeang et al , 2005Ourfali et al 2007;Shachar et al 2007). These approaches typically model a signaling pathway as a path of interactions through a protein-protein or protein-DNA interaction network, in which each interaction is associated with a direction of information flow and a regulatory influence (activating "+" or repressing ‫.…”

Section: The Future Of Network and Diseasementioning

confidence: 99%

Protein networks in disease

Ideker¹,

Sharan²

2008

Genome Res.

Self Cite

737

573

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During a decade of proof-of-principle analysis in model organisms, protein networks have been used to further the study of molecular evolution, to gain insight into the robustness of cells to perturbation, and for assignment of new protein functions. Following these analyses, and with the recent rise of protein interaction measurements in mammals, protein networks are increasingly serving as tools to unravel the molecular basis of disease. We review promising applications of protein networks to disease in four major areas: identifying new disease genes; the study of their network properties; identifying disease-related subnetworks; and network-based disease classification. Applications in infectious disease, personalized medicine, and pharmacology are also forthcoming as the available protein network information improves in quality and coverage.

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Section: The Future Of Network and Diseasementioning

confidence: 99%

Protein networks in disease

Ideker¹,

Sharan²

2008

Genome Res.

Self Cite

737

573

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“…Studies suggest that Yaps 2 and 6 can function either as activators or repressors, depending on the regulated genes (6,29,30). To further explore this phenomenon and its underlying mechanisms, we applied network component analysis (NCA) (31) to infer the regulatory directions (activating, repressing) of each Yap on its target genes.…”

Section: Yaps 2 4 5 and 6 But Not Yap1 Can Function As Both Activamentioning

confidence: 99%

A systems approach to delineate functions of paralogous transcription factors: Role of the Yap family in the DNA damage response

Tan

Feizi

Luo

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

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Duplication of genes encoding transcription factors plays an essential role in driving phenotypic variation. Because regulation can occur at multiple levels, it is often difficult to discern how each duplicated factor achieves its regulatory specificity. In these cases, a ''systems approach'' may distinguish the role of each factor by integrating complementary large-scale measurements of the regulatory network. To explore such an approach, we integrate growth phenotypes, promoter binding profiles, and gene expression patterns to model the DNA damage response network controlled by the Yeast-specific AP-1 (YAP) family of transcription factors. This analysis reveals that YAP regulatory specificity is achieved by at least three mechanisms: (i) divergence of DNAbinding sequences into two subfamilies; (ii) condition-specific combinatorial regulation by multiple Yap factors; and (iii) interactions of Yap 1, 4, and 6 with chromatin remodeling proteins. Additional microarray experiments establish that Yap 4 and 6 regulate gene expression through interactions with the histone deacetylase, Hda1. The data further highlight differences among Yap paralogs in terms of their regulatory mode of action (activation vs. repression). This study suggests how other large TF families might be disentangled in the future.ChIP-chip ͉ evolution ͉ systems biology

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“…Previously, PPI and TI data have been integrated to infer hybrid network motifs (5), sets of interacting genes that are differentially expressed (6) and causal pathways that explain differential gene expression (7). In other recent studies (8,9), yeast TIs were mapped onto known protein complexes as recorded in the Munich Information Center for Protein Sequences (MIPS) database (10).…”

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confidence: 99%

Transcriptional regulation of protein complexes within and across species

Tan

Shlomi

Feizi

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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Yeast two-hybrid and coimmunoprecipitation experiments have defined large-scale protein-protein interaction networks for many model species. Separately, systematic chromatin immunoprecipitation experiments have enabled the assembly of large networks of transcriptional regulatory interactions. To investigate the functional interplay between these two interaction types, we combined both within a probabilistic framework that models the cell as a network of transcription factors regulating protein complexes. This framework identified 72 putative coregulated complexes in yeast and allowed the prediction of 120 previously uncharacterized transcriptional interactions. Several predictions were tested by new microarray profiles, yielding a confirmation rate (58%) comparable with that of direct immunoprecipitation experiments. Furthermore, we extended our framework to a cross-species setting, identifying 24 coregulated complexes that were conserved between yeast and fly. Analyses of these conserved complexes revealed different conservation levels of their regulators and provided suggestive evidence that protein-protein interaction networks may evolve more slowly than transcriptional interaction networks. Our results demonstrate how multiple molecular interaction types can be integrated toward a global wiring diagram of the cell, and they provide insights into the evolutionary dynamics of protein complex regulation. data integration ͉ network alignment ͉ network evolution T his decade has seen an enormous amount of data on molecular interactions released into the public domain. Although many types of molecules comprise the cell and can interact with one another, the two types that have been measured at largest scale are protein-protein interactions (PPIs) and transcriptional interactions (TIs). The two-hybrid system (1) and coimmunoprecipitation (co-IP) followed by mass spectrometry (2) have been the two most popular technologies to obtain large-scale PPI data. For transcriptional interactions, ChIP coupled with whole-genome DNA microarray (ChIP-chip) allow one to determine the entire spectrum of in vivo DNA-binding sites for any given protein (3, 4).The availability of large-scale PPI and TI data from multiple species has made it possible to study how these two interaction types are combined toward a coordinated cellular response. Previously, PPI and TI data have been integrated to infer hybrid network motifs (5), sets of interacting genes that are differentially expressed (6) and causal pathways that explain differential gene expression (7). In other recent studies (8, 9), yeast TIs were mapped onto known protein complexes as recorded in the Munich Information Center for Protein Sequences (MIPS) database (10). Although these studies did not consider PPI data directly, they established that proteins within the same complex are often encoded by genes that are regulated by the same transcription factors (TFs). Protein complexes were further shown to exhibit expression coherency (11) and to include synergistic TF pairs (12)....

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Validation and refinement of gene-regulatory pathways on a network of physical interactions

Cited by 76 publications

References 29 publications

Protein networks in disease

Protein networks in disease

A systems approach to delineate functions of paralogous transcription factors: Role of the Yap family in the DNA damage response

Transcriptional regulation of protein complexes within and across species

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