Combining DGE and RNA-sequencing data to identify new polyA+ non-coding transcripts in the human genome - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Accéder directement au contenu
Article Dans Une Revue Nucleic Acids Research Année : 2014

Combining DGE and RNA-sequencing data to identify new polyA+ non-coding transcripts in the human genome

Résumé

Recent sequencing technologies that allow massive parallel production of short reads are the method of choice for transcriptome analysis. Particularly, digital gene expression (DGE) technologies produce a large dynamic range of expression data by generating short tag signatures for each cell transcript. These tags can be mapped back to a reference genome to identify new transcribed regions that can be further covered by RNA-sequencing (RNA-Seq) reads. Here, we applied an integrated bioinformatics approach that combines DGE tags, RNA-Seq, tiling array expression data and species-comparison to explore new transcriptional regions and their specific biological features, particularly tissue expression or conservation. We analysed tags from a large DGE data set (designated as 'TranscriRef'). We then annotated 750000 tags that were uniquely mapped to the human genome according to Ensembl. We retained transcripts originating from both DNA strands and categorized tags corresponding to protein-coding genes, antisense, intronic- or intergenic-transcribed regions and computed their overlap with annotated non-coding transcripts. Using this bioinformatics approach, we identified ~34000 novel transcribed regions located outside the boundaries of known protein-coding genes. As demonstrated using sequencing data from human pluripotent stem cells for biological validation, the method could be easily applied for the selection of tissue-specific candidate transcripts. DigitagCT is available at http://cractools.gforge.inria.fr/softwares/digitagct.
Fichier principal
Vignette du fichier
Nucl. Acids Res.-2014-Philippe-2820-32.pdf (5.16 Mo) Télécharger le fichier
Origine : Publication financée par une institution
Loading...

Dates et versions

lirmm-01233107 , version 1 (24-11-2015)

Identifiants

Citer

Nicolas Philippe, Elias Bou Samra, Anthony Boureux, Alban Mancheron, Florence Rufflé, et al.. Combining DGE and RNA-sequencing data to identify new polyA+ non-coding transcripts in the human genome. Nucleic Acids Research, 2014, 42 (5), pp.2820-2832. ⟨10.1093/nar/gkt1300⟩. ⟨lirmm-01233107⟩
196 Consultations
501 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More