Kongning Li

Mammalian ncRNA-disease repository: a global view of ncRNA-mediated disease network

Dear Editor  Recently, substantial studies have begun to explore the functional diversity and mechanistic roles of ncRNAs in mammals.1 Now, it has become increasingly apparent that ncRNAs are involved in multiple major biological processes, such as developmental timing, fat metabolism and cell death.2 Furthermore, the epigenetic and genetic defects in ncRNAs and their processing machinery have been implicated in the etiology of many forms of diseases.3 Several databases that documented the relevance of the microRNAs(miRNAs) to diseases have been constructed and provided useful results.4, 5 However, miRNAs are just the tip of the iceberg, other ncRNAs such as long non-coding RNAs (lncRNAs), PIWI-interacting RNAs (piRNAs) and small nucleolar RNAs (snoRNAs) have also been demonstrated to contribute to diseases.3, 6 Accumulated evidence suggest the diverse non-coding RNAs (ncRNAs) involved in a wide variety of diseases progression.3, 6, 7 It is a key challenge for understanding the precise behavior of diverse ncRNAs in mammalian diseases and deciphering the cross-regulations among disease-associated ncRNAs. Because there was no repository focused on diverse ncRNA-disease relationships in mammals, we have developed a manually curated diverse ncRNA-disease repository (MNDR, www.rna-society.org/mndr/) by integrating evidence in three mammals. Totally, 807 lncRNA-associated, 229 miRNA-associated, 13 piRNA-associated and 100 snoRNA-associated entries for 1149 curated entries were documented for three mammals (866 Homo sapiens-associated, 251 Mus musculus-associated and 32 Rattus norvegicus-associated entries) (Table 1). Table 1 The statistics of the ncRNA-disease entries in MNDR database Recent investigations indicated there are complex regulations among diverse ncRNAs and protein-coding genes. Such as, PTEN gene and the PTEN pseudogenes (ptenp1, one of lncRNAs) share a high degree of sequence homology, changes in ptenp1 expression levels indirectly affect PTEN expression by sequestering PTEN-targeting miRNAs.8 Thus understanding the mutual regulating pattern among diverse ncRNAs and protein-coding genes, particularly in disease conditions, is a key challenge. Thus, MNDR is not only a knowledge depository but providing us a good opportunity to view the ncRNA-mediated disease network globally (in visualization page: www.rna-society.org/mndr/visualization.html). Diverse ncRNAs and interaction genes were represented as nodes and the regulations were denoted as edges. Based on such a simplified ncRNA-mediated disease network, interesting observations have been achieved. The result showed that snoRNA htr, as a hub node, has intensively linked to 21 interaction genes in the network. More important, through BCL2, BCL2L1 and BAX, the snoRNA htr can communicate with the lncRNA malat1 (Supplementary Figure 1). Another example is snoRNA htr and lncRNA h19 are linked by E2F1 and MYC. When combined with human disease-associated miRNA evidence from mir2disease database, lncRNAs, miRNAs and snoRNAs, together with their interaction/target genes, can be integrated into bigger expanding ncRNA-mediated disease network. The biggest sub-network has 129 nodes and 149 edges, involving 33 lncRNAs, 1 snoRNA, 19 miRNAs and 76 interaction protein-coding genes(Supplementary Figure 2). In this network, more regulations among diverse ncRNAs directly or indirectly via intermediate genes, lncRNA dgcr5, har1a and har1b, were connected with hsa-mir-21 via intermediate gene REST. Interestingly, hsa-mir-21 and snoRNA htr were linked by key anti-apoptosis gene BCL2. Similar results were observed that lncRNA dgcr5, har1a and har1b can also communicate with snoRNA htr through alternative route NFKB1-hsa-mir-9-REST. Hence, according to current data, the two pivot protein-coding genes (BCL2 and NFKB1) and several ncRNAs (lncRNA malat1, snoRNA htr and miRNA hsa-mir-21, has-mir-9) collectively play an important role in the ncRNA-mediated disease network (Supplementary Figure 2). Importantly, the crosstalk between lncRNA malat1 and miRNA hsa-mir-21 can be found conserved in mouse ncRNA-mediated disease network. Above observations indicated diverse ncRNAs could communicate with each other in disease state through some disease-associated genes in mammals, highlighting the complexity, conservative and plasticity of the regulatory relationships between diverse ncRNAs and protein-coding genes in diseases.

RAID: a comprehensive resource for human RNA-associated (RNA–RNA/RNA–protein) interaction

Transcriptomic analyses have revealed an unexpected complexity in the eukaryote transcriptome, which includes not only protein-coding transcripts but also an expanding catalog of noncoding RNAs (ncRNAs). Diverse coding and noncoding RNAs (ncRNAs) perform functions through interaction with each other in various cellular processes. In this project, we have developed RAID (http://www.rna-society.org/raid), an RNA-associated (RNA-RNA/RNA-protein) interaction database. RAID intends to provide the scientific community with all-in-one resources for efficient browsing and extraction of the RNA-associated interactions in human. This version of RAID contains more than 6100 RNA-associated interactions obtained by manually reviewing more than 2100 published papers, including 4493 RNA-RNA interactions and 1619 RNA-protein interactions. Each entry contains detailed information on an RNA-associated interaction, including RAID ID, RNA/protein symbol, RNA/protein categories, validated method, expressing tissue, literature references (Pubmed IDs), and detailed functional description. Users can query, browse, analyze, and manipulate RNA-associated (RNA-RNA/RNA-protein) interaction. RAID provides a comprehensive resource of human RNA-associated (RNA-RNA/RNA-protein) interaction network. Furthermore, this resource will help in uncovering the generic organizing principles of cellular function network.

ViRBase: a resource for virus-host ncRNA-associated interactions.

Increasing evidence reveals that diverse non-coding RNAs (ncRNAs) play critically important roles in viral infection. Viruses can use diverse ncRNAs to manipulate both cellular and viral gene expression to establish a host environment conducive to the completion of the viral life cycle. Many host cellular ncRNAs can also directly or indirectly influence viral replication and even target virus genomes. ViRBase (http://www.rna-society.org/virbase) aims to provide the scientific community with a resource for efficient browsing and visualization of virus-host ncRNA-associated interactions and interaction networks in viral infection. The current version of ViRBase documents more than 12 000 viral and cellular ncRNA-associated virus–virus, virus–host, host–virus and host–host interactions involving more than 460 non-redundant ncRNAs and 4400 protein-coding genes from between more than 60 viruses and 20 hosts. Users can query, browse and manipulate these virus–host ncRNA-associated interactions. ViRBase will be of help in uncovering the generic organizing principles of cellular virus–host ncRNA-associated interaction networks in viral infection.

ncRDeathDB: A comprehensive bioinformatics resource for deciphering network organization of the ncRNA-mediated cell death system

Programmed cell death (PCD) is a critical biological process involved in many important processes, and defects in PCD have been linked with numerous human diseases. In recent years, the protein architecture in different PCD subroutines has been explored, but our understanding of the global network organization of the noncoding RNA (ncRNA)-mediated cell death system is limited and ambiguous. Hence, we developed the comprehensive bioinformatics resource (ncRDeathDB, www.rna-society.org/ncrdeathdb) to archive ncRNA-associated cell death interactions. The current version of ncRDeathDB documents a total of more than 4600 ncRNA-mediated PCD entries in 12 species. ncRDeathDB provides a user-friendly interface to query, browse and manipulate these ncRNA-associated cell death interactions. Furthermore, this resource will help to visualize and navigate current knowledge of the noncoding RNA component of cell death and autophagy, to uncover the generic organizing principles of ncRNA-associated cell death systems, and to generate valuable biological hypotheses.

RNALocate: a resource for RNA subcellular localizations

Increasing evidence has revealed that RNA subcellular localization is a very important feature for deeply understanding RNAs biological functions after being transported into intra- or extra-cellular regions. RNALocate is a web-accessible database that aims to provide a high-quality RNA subcellular localization resource and facilitate future researches on RNA function or structure. The current version of RNALocate documents more than 37 700 manually curated RNA subcellular localization entries with experimental evidence, involving more than 21 800 RNAs with 42 subcellular localizations in 65 species, mainly including Homo sapiens, Mus musculus and Saccharomyces cerevisiae etc. Besides, RNA homology, sequence and interaction data have also been integrated into RNALocate. Users can access these data through online search, browse, blast and visualization tools. In conclusion, RNALocate will be of help in elucidating the entirety of RNA subcellular localization, and developing new prediction methods. The database is available at http://www.rna-society.org/rnalocate/.

Network-based survival-associated module biomarker and its crosstalk with cell death genes in ovarian cancer

Ovarian cancer remains a dismal disease with diagnosing in the late, metastatic stages, therefore, there is a growing realization of the critical need to develop effective biomarkers for understanding underlying mechanisms. Although existing evidences demonstrate the important role of the single genetic abnormality in pathogenesis, the perturbations of interactors in the complex network are often ignored. Moreover, ovarian cancer diagnosis and treatment still exist a large gap that need to be bridged. In this work, we adopted a network-based survival-associated approach to capture a 12-gene network module based on differential co-expression PPI network in the advanced-stage, high-grade ovarian serous cystadenocarcinoma. Then, regulatory genes (protein-coding genes and non-coding genes) direct interacting with the module were found to be significantly overlapped with cell death genes. More importantly, these overlapping genes tightly clustered together pointing to the module, deciphering the crosstalk between network-based survival-associated module and cell death in ovarian cancer.

Current and emerging biomarkers of cell death in human disease.

Cell death is a critical biological process, serving many important functions within multicellular organisms. Aberrations in cell death can contribute to the pathology of human diseases. Significant progress made in the research area enormously speeds up our understanding of the biochemical and molecular mechanisms of cell death. According to the distinct morphological and biochemical characteristics, cell death can be triggered by extrinsic or intrinsic apoptosis, regulated necrosis, autophagic cell death, and mitotic catastrophe. Nevertheless, the realization that all of these efforts seek to pursue an effective treatment and cure for the disease has spurred a significant interest in the development of promising biomarkers of cell death to early diagnose disease and accurately predict disease progression and outcome. In this review, we summarize recent knowledge about cell death, survey current and emerging biomarkers of cell death, and discuss the relationship with human diseases.

SynBioLGDB: a resource for experimentally validated logic gates in synthetic biology

Synthetic biologists have developed DNA/molecular modules that perform genetic logic operations in living cells to track key moments in a cells life or change the fate of a cell. Increasing evidence has also revealed that diverse genetic logic gates capable of generating a Boolean function play critically important roles in synthetic biology. Basic genetic logic gates have been designed to combine biological science with digital logic. SynBioLGDB (http://bioinformatics.ac.cn/synbiolgdb/) aims to provide the synthetic biology community with a useful resource for efficient browsing and visualization of genetic logic gates. The current version of SynBioLGDB documents more than 189 genetic logic gates with experimental evidence involving 80 AND gates and 16 NOR gates, etc. in three species (Human, Escherichia coli and Bacillus clausii). SynBioLGDB provides a user-friendly interface through which conveniently to query and browse detailed information about these genetic logic gates. SynBioLGDB will enable more comprehensive understanding of the connection of genetic logic gates to execute complex cellular functions in living cells.

Composite functional module inference: detecting cooperation between transcriptional regulation and protein interaction by mantel test.

BackgroundFunctional modules are basic units of cell function, and exploring them is important for understanding the organization, regulation and execution of cell processes. Functional modules in single biological networks (e.g., the protein-protein interaction network), have been the focus of recent studies. Functional modules in the integrated network are composite functional modules, which imply the complex relationships involving multiple biological interaction types, and detect them will help us understand the complexity of cell processes.ResultsWe aimed to detect composite functional modules containing co-transcriptional regulation interaction, and protein-protein interaction, in our pre-constructed integrated network of Saccharomyces cerevisiae. We computationally extracted 15 composite functional modules, and found structural consistency between co-transcriptional regulation interaction sub-network and protein-protein interaction sub-network that was well correlated with their functional hierarchy. This type of composite functional modules was compact in structure, and was found to participate in essential cell processes such as oxidative phosphorylation and RNA splicing.ConclusionsThe structure of composite functional modules containing co-transcriptional regulation interaction, and protein-protein interaction reflected the cooperation of transcriptional regulation and protein function implementation, and was indicative of their important roles in essential cell functions. In addition, their structural and functional characteristics were closely related, and suggesting the complexity of the cell regulatory system.

Cancer-risk module identification and module-based disease risk evaluation: a case study on lung cancer.

Gene expression profiles have drawn broad attention in deciphering the pathogenesis of human cancers. Cancer-related gene modules could be identified in co-expression networks and be applied to facilitate cancer research and clinical diagnosis. In this paper, a new method was proposed to identify lung cancer-risk modules and evaluate the module-based disease risks of samples. The results showed that thirty one cancer-risk modules were closely related to the lung cancer genes at the functional level and interactional level, indicating that these modules and genes might synergistically lead to the occurrence of lung cancer. Our method was proved to have good robustness by evaluating the disease risk of samples in eight cancer expression profiles (four for lung cancer and four for other cancers), and had better performance than the WGCNA method. This method could provide assistance to the diagnosis and treatment of cancers and a new clue for explaining cancer mechanisms.