ABSTRACT
MicroRNAs (miRNAs) are noncoding RNAs with 18-26 nucleotides; they pair with target mRNAs to regulate gene expression and produce significant changes in various physiological and pathological processes. In recent years, the interaction between miRNAs and their target genes has become one of the mainstream directions for drug development. As a large-scale biological database that mainly provides miRNA-target interactions (MTIs) verified by biological experiments, miRTarBase has undergone five revisions and enhancements. The database has accumulated >2 200 449 verified MTIs from 13 389 manually curated articles and CLIP-seq data. An optimized scoring system is adopted to enhance this update's critical recognition of MTI-related articles and corresponding disease information. In addition, single-nucleotide polymorphisms and disease-related variants related to the binding efficiency of miRNA and target were characterized in miRNAs and gene 3' untranslated regions. miRNA expression profiles across extracellular vesicles, blood and different tissues, including exosomal miRNAs and tissue-specific miRNAs, were integrated to explore miRNA functions and biomarkers. For the user interface, we have classified attributes, including RNA expression, specific interaction, protein expression and biological function, for various validation experiments related to the role of miRNA. We also used seed sequence information to evaluate the binding sites of miRNA. In summary, these enhancements render miRTarBase as one of the most research-amicable MTI databases that contain comprehensive and experimentally verified annotations. The newly updated version of miRTarBase is now available at https://miRTarBase.cuhk.edu.cn/.
Subject(s)
3' Untranslated Regions , Databases, Nucleic Acid , Gene Regulatory Networks , MicroRNAs/genetics , Neoplasms/genetics , RNA, Untranslated/genetics , Animals , Binding Sites , Biomarkers/metabolism , Data Mining/statistics & numerical data , Exosomes/chemistry , Exosomes/metabolism , Gene Expression Regulation , Humans , Internet , Mice , MicroRNAs/classification , MicroRNAs/metabolism , Molecular Sequence Annotation , Neoplasms/metabolism , Neoplasms/pathology , Polymorphism, Single Nucleotide , RNA, Untranslated/classification , RNA, Untranslated/metabolism , Tumor Cells, Cultured , User-Computer InterfaceABSTRACT
DNA methylation is an important epigenetic regulator in gene expression and has several roles in cancer and disease progression. MethHC version 2.0 (MethHC 2.0) is an integrated and web-based resource focusing on the aberrant methylomes of human diseases, specifically cancer. This paper presents an updated implementation of MethHC 2.0 by incorporating additional DNA methylomes and transcriptomes from several public repositories, including 33 human cancers, over 50 118 microarray and RNA sequencing data from TCGA and GEO, and accumulating up to 3586 manually curated data from >7000 collected published literature with experimental evidence. MethHC 2.0 has also been equipped with enhanced data annotation functionality and a user-friendly web interface for data presentation, search, and visualization. Provided features include clinical-pathological data, mutation and copy number variation, multiplicity of information (gene regions, enhancer regions, and CGI regions), and circulating tumor DNA methylation profiles, available for research such as biomarker panel design, cancer comparison, diagnosis, prognosis, therapy study and identifying potential epigenetic biomarkers. MethHC 2.0 is now available at http://awi.cuhk.edu.cn/â¼MethHC.
Subject(s)
Biomarkers, Tumor/genetics , DNA Methylation , Databases, Genetic , Epigenesis, Genetic , Gene Expression Regulation, Neoplastic , Neoplasms/genetics , Biomarkers, Tumor/metabolism , Circulating Tumor DNA/blood , Circulating Tumor DNA/genetics , DNA Copy Number Variations , Disease Progression , Enhancer Elements, Genetic , High-Throughput Nucleotide Sequencing , Humans , Internet , Microarray Analysis , Molecular Sequence Annotation , Mutation , Neoplasms/classification , Neoplasms/diagnosis , Neoplasms/metabolism , Software , TranscriptomeABSTRACT
MicroRNAs (miRNAs) are small non-coding RNAs (typically consisting of 18-25 nucleotides) that negatively control expression of target genes at the post-transcriptional level. Owing to the biological significance of miRNAs, miRTarBase was developed to provide comprehensive information on experimentally validated miRNA-target interactions (MTIs). To date, the database has accumulated >13,404 validated MTIs from 11,021 articles from manual curations. In this update, a text-mining system was incorporated to enhance the recognition of MTI-related articles by adopting a scoring system. In addition, a variety of biological databases were integrated to provide information on the regulatory network of miRNAs and its expression in blood. Not only targets of miRNAs but also regulators of miRNAs are provided to users for investigating the up- and downstream regulations of miRNAs. Moreover, the number of MTIs with high-throughput experimental evidence increased remarkably (validated by CLIP-seq technology). In conclusion, these improvements promote the miRTarBase as one of the most comprehensively annotated and experimentally validated miRNA-target interaction databases. The updated version of miRTarBase is now available at http://miRTarBase.cuhk.edu.cn/.
Subject(s)
Databases, Nucleic Acid , MicroRNAs/metabolism , Circulating MicroRNA/metabolism , Data Mining , Gene Expression Regulation , RNA, Messenger/metabolism , User-Computer InterfaceABSTRACT
The larval segment formation and secondary loss in echiurans is a special phenomenon, which is considered to be one of the important characteristics in the evolutionary relationship between the Echiura and Annelida. To better understand the molecular mechanism of this phenomenon, we revealed the larval transcriptome profile of the echiuran worm Urechis unicinctus using RNA-Seq technology. Twelve cDNA libraries of U. unicinctus larvae, late-trochophore (LT), early-segmentation larva (ES), segmentation larva (SL), and worm-shaped larva (WL) were constructed. Totally 243,381 unigenes were assembled with an average length of 1125 bp and N50 of 1836 bp, and 149,488 unigenes (61.42%) were annotated. We obtained 70,517 differentially expressed genes (DEGs) by pairwise comparison of the larval transcriptome data at different developmental stages and clustered them into 20 gene expression profiles using STEM software. Based on the typical profiles during the larval segment formation and secondary loss, eight signaling pathways were enriched, and five of which, mTOR, PI3K-AKT, TGF-ß, MAPK, and Dorso-ventral axis formation signaling pathway, were proposed for the first time to be involved in the segment formation. Furthermore, we identified 119 unigenes related to the segment formation of annelids, arthropods, and chordates, in which 101 genes were identified in Drosophila and annelids. The function of most segment polarity gene homologs (hedgehog, wingless, engrailed, etc.) was conserved in echiurans, annelids, and arthropods based on their expression profiles, while the gap and pair-rule gene homologs were not. Finally, we verified that strong positive signals of Hedgehog were indeed located on the boundary of larval segments using immunofluorescence. Data in this study provide molecular evidence for the understanding of larval segment development in echiurans and may serve as a blueprint for segmented ancestors in future research.
