LncVar: a database of genetic variation associated with long non-coding genes.
Bioinformatics
; 33(1): 112-118, 2017 01 01.
Article
em En
| MEDLINE
| ID: mdl-27605101
MOTIVATION: Long non-coding RNAs (lncRNAs) are essential in many molecular pathways, and are frequently associated with disease but the mechanisms of most lncRNAs have not yet been characterized. Genetic variations, including single nucleotide polymorphisms (SNPs) and structural variations, are widely distributed in the genome, including lncRNA gene regions. As the number of studies on lncRNAs grows rapidly, it is necessary to evaluate the effects of genetic variations on lncRNAs. RESULTS: Here, we present LncVar, a database of genetic variation associated with long non-coding genes in six species. We collected lncRNAs from the NONCODE database, and evaluated their conservation. We systematically integrated transcription factor binding sites and m6A modification sites of lncRNAs and provided comprehensive effects of SNPs on transcription and modification of lncRNAs. We collected putatively translated open reading frames (ORFs) in lncRNAs, and identified both synonymous and non-synonymous SNPs in ORFs. We also collected expression quantitative trait loci of lncRNAs from the literature. Furthermore, we identified lncRNAs in CNV regions as prognostic biomarker candidates of cancers and predicted lncRNA gene fusion events from RNA-seq data from cell lines. The LncVar database can be used as a resource to evaluate the effects of the variations on the biological function of lncRNAs. AVAILABILITY AND IMPLEMENTATION: LncVar is available at http://bioinfo.ibp.ac.cn/LncVar CONTACT: rschen@ibp.ac.cnSupplementary information: Supplementary materials are available at Bioinformatics online.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Variação Genética
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Bases de Dados de Ácidos Nucleicos
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RNA Longo não Codificante
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Limite:
Animals
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Humans
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article