Dataset Information

IIIDB: a database for isoform-isoform interactions and isoform network modules.

ABSTRACT: Protein-protein interactions (PPIs) are key to understanding diverse cellular processes and disease mechanisms. However, current PPI databases only provide low-resolution knowledge of PPIs, in the sense that "proteins" of currently known PPIs generally refer to "genes." It is known that alternative splicing often impacts PPI by either directly affecting protein interacting domains, or by indirectly impacting other domains, which, in turn, impacts the PPI binding. Thus, proteins translated from different isoforms of the same gene can have different interaction partners.Due to the limitations of current experimental capacities, little data is available for PPIs at the resolution of isoforms, although such high-resolution data is crucial to map pathways and to understand protein functions. In fact, alternative splicing can often change the internal structure of a pathway by rearranging specific PPIs. To fill the gap, we systematically predicted genome-wide isoform-isoform interactions (IIIs) using RNA-seq datasets, domain-domain interaction and PPIs. Furthermore, we constructed an III database (IIIDB) that is a resource for studying PPIs at isoform resolution. To discover functional modules in the III network, we performed III network clustering, and then obtained 1025 isoform modules. To evaluate the module functionality, we performed the GO/pathway enrichment analysis for each isoform module.The IIIDB provides predictions of human protein-protein interactions at the high resolution of transcript isoforms that can facilitate detailed understanding of protein functions and biological pathways. The web interface allows users to search for IIIs or III network modules. The IIIDB is freely available at http://syslab.nchu.edu.tw/IIIDB.

SUBMITTER: Tseng YT

PROVIDER: S-EPMC4331710 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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IIIDB: a database for isoform-isoform interactions and isoform network modules.

Tseng Yu-Ting YT Li Wenyuan W Chen Ching-Hsien CH Zhang Shihua S Chen Jeremy J W JJ Zhou Xianghong X Liu Chun-Chi CC

BMC genomics 20150121

<h4>Background</h4>Protein-protein interactions (PPIs) are key to understanding diverse cellular processes and disease mechanisms. However, current PPI databases only provide low-resolution knowledge of PPIs, in the sense that "proteins" of currently known PPIs generally refer to "genes." It is known that alternative splicing often impacts PPI by either directly affecting protein interacting domains, or by indirectly impacting other domains, which, in turn, impacts the PPI binding. Thus, protein ...[more]

PMID: 25707505

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Project description:Invasive fungal infections are a significant reason for morbidity and mortality among organ transplant recipients. Therefore, it is critical to investigate the host and candida niches to understand the epidemiology of fungal infections in transplantation. Candida albicans is an opportunistic fungal pathogen that causes fatal invasive mucosal infections, particularly in solid organ transplant patients. Therefore, identifying and characterizing these genes would play a vital role in understanding the complex regulation of host-pathogen interactions. Using 32 RNA-sequencing samples of human cells infected with C. albicans, we developed WGCNA coexpression networks and performed DESeq2 differential gene expression analysis to identify the genes that positively correlate with human candida infection. Using hierarchical clustering, we identified 5 distinct modules. We studied the inter- and intramodular gene network properties in the context of sample status traits and identified the highly enriched genes in the correlated modules. We identified 52 genes that were common in the most significant WGCNA turquoise module and differentially expressed genes in human endothelial cells (HUVEC) infection vs. control samples. As a validation step, we identified the differentially expressed genes from the independent Candida-infected human oral keratinocytes (OKF6) samples and validated 30 of the 52 common genes. We then performed the functional enrichment analysis using KEGG and GO. Finally, we performed protein-protein interaction (PPI) analysis using STRING and CytoHubba from 30 validated genes. We identified 8 hub genes (JUN, ATF3, VEGFA, SLC2A1, HK2, PTGS2, PFKFB3, and KLF6) that were enriched in response to hypoxia, angiogenesis, vasculogenesis, hypoxia-induced signaling, cancer, diabetes, and transplant-related disease pathways. The discovery of genes and functional pathways related to the immune system and gene coexpression and differential gene expression analyses may serve as novel diagnostic markers and potential therapeutic targets.

Dataset Information

IIIDB: a database for isoform-isoform interactions and isoform network modules.

Publications

IIIDB: a database for isoform-isoform interactions and isoform network modules.

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