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Submitted by ChenLiang on Thu, 04/06/2017 - 19:35


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Small non-coding RNAs, in particular microRNAs, are critical for normal physiology and are candidate biomarkers, regulators, and therapeutic targets for a wide variety of diseases. There is an ever-growing interest in the comprehensive and accurate annotation of microRNAs across diverse cell types, conditions, species, and disease states. Highthroughput sequencing technology has emerged as the method of choice for profiling microRNAs. Specialized bioinformatic strategies are required to mine as much meaningful information as possible from the sequencing data to provide a comprehensive view of the microRNA landscape. Here we present miRquant 2.0, an expanded bioinformatics tool for accurate annotation and quantification of microRNAs and their isoforms (termed isomiRs) from small RNA-sequencing data. We anticipate that miRquant 2.0 will be useful for researchers interested not only in quantifying known microRNAs but also mining the rich well of additional information embedded in small RNA-sequencing data.[1]

Next-generation deep sequencing of small RNAs has unveiled the complexity of the microRNA (miRNA) transcriptome, which is in large part due to the diversity of miRNA sequence variants ("isomiRs"). Changes to a miRNA's seed sequence (nucleotides 2-8), including shifted start positions, can redirect targeting to a dramatically different set of RNAs and alter biological function. We performed deep sequencing of small RNA from mouse insulinoma (MIN6) cells (widely used as a surrogate for the study of pancreatic beta cells) and developed a bioinformatic analysis pipeline to profile isomiR diversity. Additionally, we applied the pipeline to recently published small RNA-seq data from primary human beta cells and whole islets and compared the miRNA profiles with that of MIN6. We found that: (1) the miRNA expression profile in MIN6 cells is highly correlated with those of primary human beta cells and whole islets; (2) miRNA loci can generate multiple highly expressed isomiRs with different 5'-start positions (5'-isomiRs); (3) isomiRs with shifted start positions (5'-shifted isomiRs) are highly expressed, and can be as abundant as their unshifted counterparts (5'-reference miRNAs). Finally, we identified 10 beta cell miRNA families as candidate regulatory hubs in a type 2 diabetes (T2D) gene network. The most significant candidate hub was miR-29, which we demonstrated regulates the mRNA levels of several genes critical to beta cell function and implicated in T2D. Three of the candidate miRNA hubs were novel 5'-shifted isomiRs: miR-375+1, miR-375-1 and miR-183-5p+1. We showed by in silico target prediction and in vitro transfection studies that both miR-375+1 and miR-375-1 are likely to target an overlapping, but distinct suite of beta cell genes compared to canonical miR-375. In summary, this study characterizes the isomiR profile in beta cells for the first time, and also highlights the potential functional relevance of 5'-shifted isomiRs to T2D.[2]