CircNet: a database of circular RNAs derived from transcriptome sequencing data

Circular RNAs (circRNAs) represent a new type of regulatory noncoding RNA that only recently has been identified and cataloged. Emerging evidence indicates that circRNAs exert a new layer of post-transcriptional regulation of gene expression. In this study, we utilized transcriptome sequencing datasets to systematically identify the expression of circRNAs (including known and newly identified ones by our pipeline) in 464 RNA-seq samples, and then constructed the CircNet database (http://circnet.mbc.nctu.edu.tw/) that provides the following resources: (i) novel circRNAs, (ii) integrated miRNA-target networks, (iii) expression profiles of circRNA isoforms, (iv) genomic annotations of circRNA isoforms (e.g. 282 948 exon positions), and (v) sequences of circRNA isoforms. The CircNet database is to our knowledge the first public database that provides tissue-specific circRNA expression profiles and circRNA–miRNA-gene regulatory networks. It not only extends the most up to date catalog of circRNAs but also provides a thorough expression analysis of both previously reported and novel circRNAs. Furthermore, it generates an integrated regulatory network that illustrates the regulation between circRNAs, miRNAs and genes

Carbonaceous Materials in the Fault Zone of the Longmenshan Fault Belt: 2. Characterization of Fault Gouge from Deep Drilling and Implications for Fault Maturity

In recent works on the determination of graphitization of carbonaceous materials (CM) within the principal slip zone (PSZ) of the Longmenshan fault (China), we demonstrated that the formation of graphite, resulted from strain and frictional heating, could be evidence of past seismic slip. Here we utilize Raman Spectroscopy of CM (RSCM) on the CM-bearing gouges in the fault zone of the Longmenshan fault belt, at the borehole depth of 760 m (FZ760) from the Wenchuan earthquake Fault Scientific Drilling project-1 (WFSD-1), to quantitatively characterize CM and further retrieve ancient fault deformation information in the active fault. RSCM shows that graphitization of CM is intense in the fault core with respect to the damage zone, with the graphitized carbon resembling those observed on experimentally formed graphite that was frictionally generated. Importantly, compared to the recognized active fault zone of the Longmenshan fault, the RSCM of measured CM-rich gouge shows a higher degree of graphitization, likely derived from high-temperature-perturbation faulting events. It implies that FZ760 accommodated numerous single-event displacement and/or at higher normal stresses and/or in the absence of pore fluid and/or along a more localized slip surface(s). Because graphite is a well-known lubricant, we surmise that the presence of the higher degree graphitized CM within FZ760 will reduce the fault strength and inefficiently accumulate tectonic stress during the seismic cycle at the current depth, and further infer a plausible mechanism for fault propagation at the borehole depth of 590 m during the Mw 7.9 Wenchuan earthquake

Multivariate analysis of genomics data to identify potential pleiotropic genes for type 2 diabetes, obesity and dyslipidemia using Meta-CCA and gene-based approach.

Previous studies have demonstrated the genetic correlations between type 2 diabetes, obesity and dyslipidemia, and indicated that many genes have pleiotropic effects on them. However, these pleiotropic genes have not been well-defined. It is essential to identify pleiotropic genes using systematic approaches because systematically analyzing correlated traits is an effective way to enhance their statistical power. To identify potential pleiotropic genes for these three disorders, we performed a systematic analysis by incorporating GWAS (genome-wide associated study) datasets of six correlated traits related to type 2 diabetes, obesity and dyslipidemia using Meta-CCA (meta-analysis using canonical correlation analysis). Meta-CCA is an emerging method to systematically identify potential pleiotropic genes using GWAS summary statistics of multiple correlated traits. 2,720 genes were identified as significant genes after multiple testing (Bonferroni corrected p value < 0.05). Further, to refine the identified genes, we tested their relationship to the six correlated traits using VEGAS-2 (versatile gene-based association study-2). Only the genes significantly associated (Bonferroni corrected p value < 0.05) with more than one trait were kept. Finally, 25 genes (including two confirmed pleiotropic genes and eleven novel pleiotropic genes) were identified as potential pleiotropic genes. They were enriched in 5 pathways including the statin pathway and the PPAR (peroxisome proliferator-activated receptor) Alpha pathway. In summary, our study identified potential pleiotropic genes and pathways of type 2 diabetes, obesity and dyslipidemia, which may shed light on the common biological etiology and pathogenesis of these three disorders and provide promising insights for new therapies

P63 and P73 Activation in Cancers with p53 Mutation

The members of the p53 family comprise p53, p63, and p73, and full-length isoforms of the p53 family have a tumor suppressor function. However, p53, but not p63 or p73, has a high mutation rate in cancers causing it to lose its tumor suppressor function. The top and second-most prevalent p53 mutations are missense and nonsense mutations, respectively. In this review, we discuss possible drug therapies for nonsense mutation and a missense mutation in p53. p63 and p73 activators may be able to replace mutant p53 and act as anti-cancer drugs. Herein, these p63 and p73 activators are summarized and how to improve these activator responses, particularly focusing on p53 gain-of-function mutants, is discussed