Research

Increasing evidence suggests that most of the mammalian genome is transcribed as RNAs. However, not all of them are translated to become proteins. The current estimate is that only few percent of the mammalian genome encodes for protein-coding genes. Up until recently, many of the remaining RNAs were considered as transcriptional noises and experimental errors that do not have any functions. However, recent studies show that non-coding RNAs (ncRNAs) are functional as in the case of microRNAs (miRNAs). Besides miRNAs, there are more longer ncRNAs have been identified. If their lengths are longer than 200 nucleotides (nt), these ncRNAs are collectively called “long non-coding RNAs (lncRNAs)”. Although lncRNAs are of great interested in the research community, their functions are largely unknown. This is especially true in the field of cardiovascular research, which we recently reviewed (Link) (Link) (Link).

Life on our planet depends on RNA. Despite our early understanding of RNA as an enabling messenger, it is not simply a static reflection of genetic activation. Indeed, the lifespan of RNA is more complex than previously thought. Upon transcription from the DNA template, RNA can be modified by various enzymes, which results in over 100 RNA modifications. Because of the potential involvement of RNA modifications in a variety of pathophysiologies, epitranscriptomics is quickly gaining momentum and our gaps in understanding epitranscriptomics requires further study. This is especially true in the field of cardiovascular research, which we recently reviewed (Link).

In last few years, we have developed a number of bioinformatics tools:

• “ANGIOGENES” (Link) for expression profiles of transcripts in endothelial cells
• “C-It” (Link) for evolutionary-conserved, tissue-enriched, uncharacterized genes
• “C-It-Loci” (Link) for evolutionary-conserved, tissue-enriched, protein-coding genes and lncRNAs
• “CrohnDB” (Link) for expression profiles of transcripts in Crohn disease
• “DoxoDB” (Link) for expression profiles of doxorubicin-induced transcripts
• “DRETools” (Link) for studying differential RNA editings
• “Exon Array Analyzer (EAA)” (Link) for analyzing GeneChip Exon 1.0 ST Arrays (Affymetrix, Inc.)
• “FibroDB” (Link) for expression profiles of transcripts in fibroblasts and during fibrosis
• “Gene Array Analyzer (GAA)” (Link) for analyzing GeneChip Gene 1.0 ST Arrays (Affymetrix, Inc.)
• “IBDB” (Link) for expression profiles of transcripts in inflammatory bowel disease
• “InflammasomeDB” (Link) for expression profiles of transcripts in inflammasome activation
• “LiverDB”” (Link) for expression profiles of transcripts in nonalcoholic fatty liver disease (NAFLD)
• “noncoder” (Link) for quantifying the expression changes of lncRNAs and protein-coding genes from GeneChip Exon 1.0 ST Arrays (Affymetrix, Inc.)
• “RenalDB” (Link) for in silico screening of enriched/specific transcripts of humans, mice, and zebrafish with respect to nephrotic tissues and cells, developmental stages, and other metadata.
• “RNAEditor” (Link) for analyzing RNA editing sites and islands from RNA-seq data
• “SNP4Disease” (Link) for disease-related and/or -suspected SNPs
• “T2DB” (Link) for expression profiles of transcripts in type II diabetes
• “UGAHash” (Link) for mapping human genomic features among various bioinformatics databases and versions of databases
• “Vectools” (Link) for working with vectors, matrices, and tables to perform statistics and machine learning analysis

Using the above bioinformatics tools combined with biological experiments, our research goal is to uncover the functions of miRNAs and lncRNAs as well as RNA modifications.