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Title: | AtFusionDB: a database of fusion transcripts in Arabidopsis thaliana |
Authors: | Singh, Ajeet Zahra, Shafaque Das, Durdam Kumar, Shailesh |
Keywords: | Database tool Arabidopsis thaliana AtFusionDB |
Issue Date: | 2019 |
Publisher: | Oxford University Press |
Citation: | Database, 2019: bay135 |
Abstract: | Fusion transcripts are chimeric RNAs generated as a result of fusion either at DNA or RNA level. These novel transcripts have been extensively studied in the case of human cancers but still remain underexamined in plants. In this study, we introduce the first plant-specific database of fusion transcripts named AtFusionDB (http://www. nipgr.res.in/AtFusionDB). This is a comprehensive database that contains the detailed information about fusion transcripts identified in model plant Arabidopsis thaliana. A total of 82 969 fusion transcript entries generated from 17 181 different genes of A. thaliana are available in this database. Apart from the basic information consisting of the Ensembl gene names, official gene name, tissue type, EricScore, fusion type, AtFusionDB ID and sample ID (e.g. Sequence Read Archive ID), additional information like UniProt, gene coordinates (together with the function of parental genes), junction sequence, expression level of both parent genes and fusion transcript may be of high utility to the user. Two different types of search modules viz. ‘Simple Search’ and ‘Advanced Search’ in addition to the ‘Browse’ option with data download facility are provided in this database. Three different modules for mapping and alignment of the query sequences viz. BLASTN, SW Align and Mapping are incorporated in AtFusionDB. This database is a head start for exploring the complex and unexplored domain of gene/transcript fusion in plants. Database URL: http://www.nipgr.res.in/AtFusionDB |
Description: | Accepted date: 29 November 2018 |
URI: | http://223.31.159.10:8080/jspui/handle/123456789/909 |
ISSN: | 1758-0463 |
Appears in Collections: | Institutional Publications |
Files in This Item:
File | Description | Size | Format | |
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Kumar Shai_2019_1.pdf | 1.84 MB | Adobe PDF | View/Open |
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