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      Distinct brain transcriptome profiles in C9orf72-associated and sporadic ALS

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          Abstract

          Increasing evidence suggests that defective RNA processing contributes to the development of amyotrophic lateral sclerosis (ALS). This may be especially true for ALS caused by a repeat expansion in C9orf72 (c9ALS), in which the accumulation of RNA foci and dipeptide-repeat proteins are expected to modify RNA metabolism. We report extensive alternative splicing (AS) and alternative polyadenylation (APA) defects in the cerebellum of c9ALS cases (8,224 AS, 1,437 APA), including changes in ALS-associated genes (e.g. ATXN2 and FUS), and cases of sporadic ALS (sALS; 2,229 AS, 716 APA). Furthermore, hnRNPH and other RNA-binding proteins are predicted as potential regulators of cassette exon AS events for both c9ALS and sALS. Co-expression and gene-association network analyses of gene expression and AS data revealed divergent pathways associated with c9ALS and sALS.

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          Integration of biological networks and gene expression data using Cytoscape.

          Melissa Cline, Michael Smoot, Ethan Cerami … (2007)
          Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.
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            RNA toxicity from the ALS/FTD C9ORF72 expansion is mitigated by antisense intervention.

            Christopher J Donnelly, Ping-Wu Zhang, Jacqueline T Pham … (2013)
            A hexanucleotide GGGGCC repeat expansion in the noncoding region of the C9ORF72 gene is the most common genetic abnormality in familial and sporadic amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The function of the C9ORF72 protein is unknown, as is the mechanism by which the repeat expansion could cause disease. Induced pluripotent stem cell (iPSC)-differentiated neurons from C9ORF72 ALS patients revealed disease-specific (1) intranuclear GGGGCCexp RNA foci, (2) dysregulated gene expression, (3) sequestration of GGGGCCexp RNA binding protein ADARB2, and (4) susceptibility to excitotoxicity. These pathological and pathogenic characteristics were confirmed in ALS brain and were mitigated with antisense oligonucleotide (ASO) therapeutics to the C9ORF72 transcript or repeat expansion despite the presence of repeat-associated non-ATG translation (RAN) products. These data indicate a toxic RNA gain-of-function mechanism as a cause of C9ORF72 ALS and provide candidate antisense therapeutics and candidate human pharmacodynamic markers for therapy. Copyright © 2013 Elsevier Inc. All rights reserved.
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              Is Open Access

              MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing

              Krishna Kalari, Asha A. Nair, Jaysheel Bhavsar … (2014)
              Background Although the costs of next generation sequencing technology have decreased over the past years, there is still a lack of simple-to-use applications, for a comprehensive analysis of RNA sequencing data. There is no one-stop shop for transcriptomic genomics. We have developed MAP-RSeq, a comprehensive computational workflow that can be used for obtaining genomic features from transcriptomic sequencing data, for any genome. Results For optimization of tools and parameters, MAP-RSeq was validated using both simulated and real datasets. MAP-RSeq workflow consists of six major modules such as alignment of reads, quality assessment of reads, gene expression assessment and exon read counting, identification of expressed single nucleotide variants (SNVs), detection of fusion transcripts, summarization of transcriptomics data and final report. This workflow is available for Human transcriptome analysis and can be easily adapted and used for other genomes. Several clinical and research projects at the Mayo Clinic have applied the MAP-RSeq workflow for RNA-Seq studies. The results from MAP-RSeq have thus far enabled clinicians and researchers to understand the transcriptomic landscape of diseases for better diagnosis and treatment of patients. Conclusions Our software provides gene counts, exon counts, fusion candidates, expressed single nucleotide variants, mapping statistics, visualizations, and a detailed research data report for RNA-Seq. The workflow can be executed on a standalone virtual machine or on a parallel Sun Grid Engine cluster. The software can be downloaded from http://bioinformaticstools.mayo.edu/research/maprseq/.
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                Author and article information

                Journal
                Journal ID (nlm-journal-id): 9809671
                Journal ID (pubmed-jr-id): 21092
                Journal ID (nlm-ta): Nat Neurosci
                Journal ID (iso-abbrev): Nat. Neurosci.
                Title: Nature neuroscience
                ISSN (Print): 1097-6256
                ISSN (Electronic): 1546-1726
                Publication date Nihms-submitted: 8 April 2016
                Publication date (Electronic): 20 July 2015
                Publication date (Print): August 2015
                Publication date PMC-release: 13 April 2016
                Volume: 18
                Issue: 8
                Pages: 1175-1182
                Affiliations
                [1 ]Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, Florida 32224, USA
                [2 ]Information Technology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905, USA
                [3 ]Department of Neurology, Mayo Clinic, 4500 San Pablo Road, Jacksonville, Florida 32224, USA
                [4 ]Mayo Graduate School, Mayo Clinic College of Medicine, Rochester, Minnesota 55905, USA
                [5 ]Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905, USA
                [6 ]Integrative Physiology, Institute for Behavioral Genetics University of Colorado, Campus Box 354, Boulder, CO 80309, USA
                Author notes
                [* ]Corresponding authors: Leonard Petrucelli, Ph.D., Department of Research, Neuroscience, Mayo Clinic College of Medicine, 4500 San Pablo road, Jacksonville, FL 32224, Office: 1-904-953-2855, Fax: 1-904-953-6276, petrucelli.leonard@ 123456mayo.edu . Hu Li, Ph.D., Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, Office: 1-507-293-1182, Fax: 1-507-284-4455, li.hu@ 123456mayo.edu
                [7]

                These authors contributed equally to this work.

                Article
                Manuscript ID: NIHMS702153
                DOI: 10.1038/nn.4065
                PMC ID: 4830686
                PubMed ID: 26192745
                SO-VID: 71e3bbf8-e35f-4ee7-9a2d-2e393d8d8b4c
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                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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                ScienceOpen disciplines: Neurosciences

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