Prediction of MicroRNA Precursors Using Parsimonious Feature Sets.

MicroRNAs (miRNAs) are a class of short noncoding RNAs that regulate gene expression through base pairing with messenger RNAs. Due to the interest in studying miRNA dysregulation in disease and limits of validated miRNA references, identification of novel miRNAs is a critical task. The performance of different models to predict novel miRNAs varies with the features chosen as predictors. However, no study has systematically compared published feature sets. We constructed a comprehensive feature set using the minimum free energy of the secondary structure of precursor miRNAs, a set of nucleotide-structure triplets, and additional extracted sequence and structure characteristics. We then compared the predictive value of our comprehensive feature set to those from three previously published studies, using logistic regression and random forest classifiers. We found that classifiers containing as few as seven highly predictive features are able to predict novel precursor miRNAs as well as classifiers that use larger feature sets. In a real data set, our method correctly identified the holdout miRNAs relevant to renal cancer.

MAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure.

SUMMARY: MAGI is a web service for fast MicroRNA-Seq data analysis in a graphics processing unit (GPU) infrastructure. Using just a browser, users have access to results as web reports in just a few hours->600% end-to-end performance improvement over state of the art. MAGI's salient features are (i) transfer of large input files in native FASTA with Qualities (FASTQ) format through drag-and-drop operations, (ii) rapid prediction of microRNA target genes leveraging parallel computing with GPU devices, (iii) all-in-one analytics with novel feature extraction, statistical test for differential expression and diagnostic plot generation for quality control and (iv) interactive visualization and exploration of results in web reports that are readily available for publication. AVAILABILITY AND IMPLEMENTATION: MAGI relies on the Node.js JavaScript framework, along with NVIDIA CUDA C, PHP: Hypertext Preprocessor (PHP), Perl and R. It is freely available at http://magi.ucsd.edu.

Differential expression of miR-145 in children with Kawasaki disease.

BACKGROUND: Kawasaki disease is an acute, self-limited vasculitis of childhood that can result in structural damage to the coronary arteries. Previous studies have implicated the TGF-ß pathway in disease pathogenesis and generation of myofibroblasts in the arterial wall. microRNAs are small non-coding RNAs that modulate gene expression at the post-transcriptional level and can be transported between cells in extracellular vesicles. To understand the role that microRNAs play in modifying gene expression in Kawasaki disease, we studied microRNAs from whole blood during the acute and convalescent stages of the illness. METHODOLOGY/PRINCIPAL FINDINGS: RNA isolated from the matched whole blood of 12 patients with acute and convalescent Kawasaki disease were analyzed by sequencing of small RNA. This analysis revealed six microRNAs (miRs-143, -199b-5p, -618, -223, -145 and -145* (complementary strand)) whose levels were significantly elevated during the acute phase of Kawasaki disease. The result was validated using targeted qRT-PCR using an independent cohort (n = 16). miR-145, which plays a critical role in the differentiation of neutrophils and vascular smooth muscle cells, was expressed at high levels in blood samples from acute Kawasaki disease but not adenovirus-infected control patients (p = 0.005). miR-145 was also detected in small extracellular vesicles isolated from acute Kawasaki disease plasma samples. Pathway analysis of the predicted targets of the 6 differentially expressed microRNAs identified the TGF-ß pathway as the top pathway regulated by microRNAs in Kawasaki disease. CONCLUSION: Sequencing of small RNA species allowed discovery of microRNAs that may participate in Kawasaki disease pathogenesis. miR-145 may participate, along with other differentially expressed microRNAs, in regulating expression of genes in the TGF-ß pathway during the acute illness. If the predicted target genes are confirmed, our findings suggest a model of Kawasaki disease pathogenesis whereby miR-145 modulates TGF-ß signaling in the arterial wall.