title: SubmiRine: assessing variants in microRNA targets using clinical genomic data sets.
abstract: MicroRNAs (miRNAs) regulate gene expression by binding to partially complementary sequences on target mRNA transcripts, thereby causing their degradation, deadenylation, or inhibiting their translation. Genomic variants can alter miRNA regulation by modifying miRNA target sites, and multiple human disease phenotypes have been linked to such miRNA target site variants (miR-TSVs). However, systematic genome-wide identification of functional miR-TSVs is difficult due to high false positive rates; functional miRNA recognition sequences can be as short as six nucleotides, with the human genome encoding thousands of miRNAs. Furthermore, while large-scale clinical genomic data sets are becoming increasingly commonplace, existing miR-TSV prediction methods are not designed to analyze these data. Here, we present an open-source tool called SubmiRine that is designed to perform efficient miR-TSV prediction systematically on variants identified in novel clinical genomic data sets. Most importantly, SubmiRine allows for the prioritization of predicted miR-TSVs according to their relative probability of being functional. We present the results of SubmiRine using integrated clinical genomic data from a large-scale cohort study on chronic obstructive pulmonary disease (COPD), making a number of high-scoring, novel miR-TSV predictions. We also demonstrate SubmiRine's ability to predict and prioritize known miR-TSVs that have undergone experimental validation in previous studies.
authors: Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA Bioinformatics Program, Boston University, Boston, MA 02215, USA.
authors: Evan K
authors: EK
authors: Maxwell
authors: Bioinformatics Program, Boston University, Boston, MA 02215, USA Division of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02215, USA.
authors: Joshua D
authors: JD
authors: Campbell
authors: Bioinformatics Program, Boston University, Boston, MA 02215, USA Division of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02215, USA.
authors: Avrum
authors: A
authors: Spira
authors: Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA andy@mail.nih.gov.
authors: Andreas D
authors: AD
authors: Baxevanis
mesh_terms: D020413:3' Untranslated Regions; D001665:Binding Sites; D023281:Genomics; D006801:Humans; D035683:MicroRNAs / Q000378:metabolism*; D020641:Polymorphism, Single Nucleotide; D029424:Pulmonary Disease, Chronic Obstructive / Q000235:genetics; D012984:Software
chemical_list: D020413:3' Untranslated Regions; D035683:MicroRNAs