Biogenesis and molecular function are two key subjects in the field of microRNA (miRNA) research. Deep sequencing has become the principal technique in cataloging of miRNA repertoire and generating expression profiles in an unbiased manner. Here, we describe the miRGator v3.0 update (http://mirgator.kobic.re.kr) that compiled the deep sequencing miRNA data available in public and implemented several novel tools to facilitate exploration of massive data. The miR-seq browser supports users to examine short read alignment with the secondary structure and read count information available in concurrent windows. Features such as sequence editing, sorting, ordering, import and export of user data would be of great utility for studying iso-miRs, miRNA editing and modifications. miRNA–target relation is essential for understanding miRNA function. Coexpression analysis of miRNA and target mRNAs, based on miRNA-seq and RNA-seq data from the same sample, is visualized in the heat-map and network views where users can investigate the inverse correlation of gene expression and target relations, compiled from various databases of predicted and validated targets. By keeping datasets and analytic tools up-to-date, miRGator should continue to serve as an integrated resource for biogenesis and functional investigation of miRNAs.
The association between body size, weight change and depression has not been systematically summarised, especially for individuals who are underweight.To conduct a systematic review and a meta-analysis to examine the association between indices of body size, weight change and depression.A total of 183 studies were selected. Fully adjusted hazard ratios (HRs) or odds ratios (ORs) were extracted. A total of 76 studies contributed to data synthesis with a random-effect model, and subgroup analyses were conducted to evaluate the effect of potential moderators.In cohort studies, underweight at baseline increased the risk of subsequent depression (OR = 1.16, 95% CI 1.08-1.24). Overweight (BMI 25-29.9 kg/m) showed no statistically significant relationship with depression overall; however, the subgroup analyses found different results according to gender (men: OR = 0.84, 95% CI 0.72-0.97, women: OR = 1.16, 95% CI 1.07-1.25). In cross-sectional designs, obesity with BMI >40 kg/m showed a greater pooled odds ratio than obesity with BMI >30 kg/mBoth underweight and obesity increase the risk of depression. The association between overweight and depression differs by gender.
BackgroundDeep sequencing techniques provide a remarkable opportunity for comprehensive understanding of tumorigenesis at the molecular level. As omics studies become popular, integrative approaches need to be developed to move from a simple cataloguing of mutations and changes in gene expression to dissecting the molecular nature of carcinogenesis at the systemic level and understanding the complex networks that lead to cancer development.ResultsHere, we describe a high-throughput, multi-dimensional sequencing study of primary lung adenocarcinoma tumors and adjacent normal tissues of six Korean female never-smoker patients. Our data encompass results from exome-seq, RNA-seq, small RNA-seq, and MeDIP-seq. We identified and validated novel genetic aberrations, including 47 somatic mutations and 19 fusion transcripts. One of the fusions involves the c-RET gene, which was recently reported to form fusion genes that may function as drivers of carcinogenesis in lung cancer patients. We also characterized gene expression profiles, which we integrated with genomic aberrations and gene regulations into functional networks. The most prominent gene network module that emerged indicates that disturbances in G2/M transition and mitotic progression are causally linked to tumorigenesis in these patients. Also, results from the analysis strongly suggest that several novel microRNA-target interactions represent key regulatory elements of the gene network.ConclusionsOur study not only provides an overview of the alterations occurring in lung adenocarcinoma at multiple levels from genome to transcriptome and epigenome, but also offers a model for integrative genomics analysis and proposes potential target pathways for the control of lung adenocarcinoma.
the trial was registered with the Clinical Trial Registry of Korea: https://cris.nih.go.kr/cris/index.jsp. Identifier: KCT0001078.
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