22:T45f,The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential expression testing and pathway analysis with the results obtained informing future experiments and validation studies. In this workflow article, we analyse RNA-sequencing data from the mouse mammary gland, demonstrating use of the popular edgeR package to import, organise, filter and normalise the data, followed by the limma package with its voom method, linear modelling and empirical Bayes moderation to assess differential expression and perform gene set testing. This pipeline is further enhanced by the Glimma package which enables interactive exploration of the results so that individual samples and genes can be examined by the user. The complete analysis offered by these three packages highlights the ease with which researchers can turn the raw counts from an RNA-sequencing experiment into biological insights using Bioconductor.23:T452,The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential expression testing and pathway analysis with the results obtained informing future experiments and validation studies. In this workflow article, we analyse RNA-sequencing data from the mouse mammary gland, demonstrating use of the popular edgeR package to import, organise, filter and normalise the data, followed by the limma package with its voom method, linear modelling and empirical Bayes moderation to assess differential expression and perform gene set testing. This pipeline is further enhanced by the Glimma package which enables interactive exploration of the results so that individual samples and genes can be examined by the user. The complete analysis offered by these three packages highlights the ease with which researchers can turn the raw counts from an RNA-sequencing experiment into biological insights using Bioconductor.24:T511,MicroRNAs (miRNAs) belong to a class of endogenously expressed non-coding small RNAs that function primarily as gene regulators. Growing evidence suggests that miRNAs play a significant role in tumor development, making them potential biomarkers for cancer diagnosis and prognosis. The miR-17-92 cluster has emerged as an important locus, being highly overexpressed in several cancers in association with cancer development and progression. The miR-17-92 miRNA cluster generates a single polycistronic primary transcript that yields six mature miRNAs: miR-17, miR-18a, miR-19a, miR-20a, miR-19b, and miR-92a. In colon cancer development, the pathophysiologic roles of these transcripts and their targets are largely unknown. In the present study, we performed copy number analyses of the six miRNAs transcribed from the miR-17-92 cluster in colon tumor tissues. We determined that miR-92a was transcribed at higher levels than the other five miRNAs in both adenomas and carcinoma. In addition, miR-92a directly targeted the anti-apoptotic molecule BCL-2-interacting mediator of cell death (BIM) in colon cancer tissues. An anti-miR-92a antagomir induced apoptosis of colon cancer-derived cell lines. These data indicate that miR-92a plays a pivotal role in the development of colorectal carcinoma.

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