X-MATE: a flexible system for mapping short read data

Summary: Accurate and complete mapping of short-read sequencing to a reference genome greatly enhances the discovery of biological results and improves statistical predictions. We recently presented RNA-MATE, a pipeline for the recursive mapping of RNA-Seq datasets. With the rapid increase in genome re-sequencing projects, progression of available mapping software and the evolution of file formats, we now present X-MATE, an updated version of RNA-MATE, capable of mapping both RNA-Seq and DNA datasets and with improved performance, output file formats, configuration files, and flexibility in core mapping software

The i-School movement

No Abstract.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57317/1/14504301131_ftp.pd

Digital Twin of a Network and Operating Environment Using Augmented Reality

We demonstrate the digital twin of a network, network elements, and operating environment using machine learning. We achieve network card failure localization and remote collaboration over 86 km of fiber using augmented reality

Overexpression of miRNA-25-3p inhibits Notch1 signaling and TGF-β-induced collagen expression in hepatic stellate cells

During chronic liver injury hepatic stellate cells (HSCs), the principal source of extracellular matrix in the fibrotic liver, transdifferentiate into pro-fibrotic myofibroblast-like cells - a process potentially regulated by microRNAs (miRNAs). Recently, we found serum miRNA-25-3p (miR-25) levels were upregulated in children with Cystic Fibrosis (CF) without liver disease, compared to children with CF-associated liver disease and healthy individuals. Here we examine the role of miR-25 in HSC biology. MiR-25 was detected in the human HSC cell line LX-2 and in primary murine HSCs, and increased with culture-induced activation. Transient overexpression of miR-25 inhibited TGF-β and its type 1 receptor (TGFBR1) mRNA expression, TGF-β-induced Smad2 phosphorylation and subsequent collagen1α1 induction in LX-2 cells. Pull-down experiments with biotinylated miR-25 revealed Notch signaling (co-)activators ADAM-17 and FKBP14 as miR-25 targets in HSCs. NanoString analysis confirmed miR-25 regulation of Notch- and Wnt-signaling pathways. Expression of Notch signaling pathway components and endogenous Notch1 signaling was downregulated in miR-25 overexpressing LX-2 cells, as were components of Wnt signaling such as Wnt5a. We propose that miR-25 acts as a negative feedback anti-fibrotic control during HSC activation by reducing the reactivity of HSCs to TGF-β-induced collagen expression and modulating the cross-talk between Notch, Wnt and TGF-β signaling

Refining transcriptional programs in kidney development by integration of deep RNA-sequencing and array-based spatial profiling

<p>Abstract</p> <p>Background</p> <p>The developing mouse kidney is currently the best-characterized model of organogenesis at a transcriptional level. Detailed spatial maps have been generated for gene expression profiling combined with systematic <it>in situ </it>screening. These studies, however, fall short of capturing the transcriptional complexity arising from each locus due to the limited scope of microarray-based technology, which is largely based on "gene-centric" models.</p> <p>Results</p> <p>To address this, the polyadenylated RNA and microRNA transcriptomes of the 15.5 dpc mouse kidney were profiled using strand-specific RNA-sequencing (RNA-Seq) to a depth sufficient to complement spatial maps from pre-existing microarray datasets. The transcriptional complexity of RNAs arising from mouse RefSeq loci was catalogued; including 3568 alternatively spliced transcripts and 532 uncharacterized alternate 3' UTRs. Antisense expressions for 60% of RefSeq genes was also detected including uncharacterized non-coding transcripts overlapping kidney progenitor markers, Six2 and Sall1, and were validated by section <it>in situ </it>hybridization. Analysis of genes known to be involved in kidney development, particularly during mesenchymal-to-epithelial transition, showed an enrichment of non-coding antisense transcripts extended along protein-coding RNAs.</p> <p>Conclusion</p> <p>The resulting resource further refines the transcriptomic cartography of kidney organogenesis by integrating deep RNA sequencing data with locus-based information from previously published expression atlases. The added resolution of RNA-Seq has provided the basis for a transition from classical gene-centric models of kidney development towards more accurate and detailed "transcript-centric" representations, which highlights the extent of transcriptional complexity of genes that direct complex development events.</p

Small RNA changes en route to distinct cellular states of induced pluripotency

MicroRNAs (miRNAs) are critical to somatic cell reprogramming into induced pluripotent stem cells (iPSCs), however, exactly how miRNA expression changes support the transition to pluripotency requires further investigation. Here we use a murine secondary reprogramming system to sample cellular trajectories towards iPSCs or a novel pluripotent ‘F-class’ state and perform small RNA sequencing. We detect sweeping changes in an early and a late wave, revealing that distinct miRNA milieus characterize alternate states of pluripotency. miRNA isoform expression is common but surprisingly varies little between cell states. Referencing other omic data sets generated in parallel, we find that miRNA expression is changed through transcriptional and post-transcriptional mechanisms. miRNA transcription is commonly regulated by dynamic histone modification, while DNA methylation/demethylation consolidates these changes at multiple loci. Importantly, our results suggest that a novel subset of distinctly expressed miRNAs supports pluripotency in the F-class state, substituting for miRNAs that serve such roles in iPSCs

Development and validation of an online emotional intelligence training program

IntroductionEmotional intelligence (EI) is associated with a range of positive health, wellbeing, and behavioral outcomes. The present article describes the development and validation of an online training program for increasing EI abilities in adults. The training program was based on theoretical models of emotional functioning and empirical literature on successful approaches for training socioemotional skills and resilience.MethodsAfter an initial design, programming, and refinement process, the completed online program was tested for efficacy in a sample of 326 participants (72% female) from the general population. Participants were randomly assigned to complete either the EI training program (n = 168) or a matched placebo control training program (n = 158). Each program involved 10-12 hours of engaging online content and was completed during either a 1-week (n = 175) or 3-week (n = 151) period.ResultsParticipants who completed the EI training program showed increased scores from pre- to post-training on standard self-report (i.e., trait) measures of EI (relative to placebo), indicating self-perceived improvements in recognizing emotions, understanding emotions, and managing the emotions of others. Moreover, those in the EI training also showed increased scores in standard performance-based (i.e., ability) EI measures, demonstrating an increased ability to strategically use and manage emotions relative to placebo. Improvements to performance measures also remained significantly higher than baseline when measured six months after completing the training. The training was also well-received and described as helpful and engaging.DiscussionFollowing a rigorous iterative development process, we created a comprehensive and empirically based online training program that is well-received and engaging. The program reliably improves both trait and ability EI outcomes and gains are sustained up to six months post-training. This program could provide an easy and scalable method for building emotional intelligence in a variety of settings

Genome-wide dissection of microRNA functions and cotargeting networks using gene-set signatures

MicroRNAs are emerging as important regulators of diverse biological processes and pathologies in animals and plants. Though hundreds of human microRNAs are known, only a few have known functions. Here, we predict human microRNA functions by using a new method that systematically assesses the statistical enrichment of several microRNA-targeting signatures in annotated gene sets such as signaling networks and protein complexes. Some of our top predictions are supported by published experiments, yet many are entirely new or provide mechanistic insights to known phenotypes. Our results indicate that coordinated microRNA targeting of closely connected genes is prevalent across pathways. We use the same method to infer which microRNAs regulate similar targets and provide the first genome-wide evidence of pervasive cotargeting, in which a handful of “hub” microRNAs are involved in a majority of cotargeting relationships. Our method and analyses pave the way to systematic discovery of microRNA functions.National Science Foundation (U.S.) (Grant PHY-0548484)National Institutes of Health (U.S.) (Grant R01-GM068957)National Institutes of Health (U.S.). Pioneer Award (1DP1OD003936)Howard Hughes Medical Institute. Predoctoral ScholarshipNatural Sciences and Engineering Research Council of Canada (NSERC). Doctoral Scholarshi

RNA-Seq Mapping and Detection of Gene Fusions with a Suffix Array Algorithm

High-throughput RNA sequencing enables quantification of transcripts (both known and novel), exon/exon junctions and fusions of exons from different genes. Discovery of gene fusions–particularly those expressed with low abundance– is a challenge with short- and medium-length sequencing reads. To address this challenge, we implemented an RNA-Seq mapping pipeline within the LifeScope software. We introduced new features including filter and junction mapping, annotation-aided pairing rescue and accurate mapping quality values. We combined this pipeline with a Suffix Array Spliced Read (SASR) aligner to detect chimeric transcripts. Performing paired-end RNA-Seq of the breast cancer cell line MCF-7 using the SOLiD system, we called 40 gene fusions among over 120,000 splicing junctions. We validated 36 of these 40 fusions with TaqMan assays, of which 25 were expressed in MCF-7 but not the Human Brain Reference. An intra-chromosomal gene fusion involving the estrogen receptor alpha gene ESR1, and another involving the RPS6KB1 (Ribosomal protein S6 kinase beta-1) were recurrently expressed in a number of breast tumor cell lines and a clinical tumor sample