title: Combining DGE and RNA-sequencing data to identify new polyA+ non-coding transcripts in the human genome.
abstract: 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 750,000 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 ∼34,000 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.
authors.affiliation: Transcriptomics, bioinformatics and myeloid leukaemia, INSERM, U1040, Institute for Research in Biotherapy, Montpellier F-34197, France, Université Montpellier 2, Montpellier, France, Institut de Biologie Computationnelle, Maison de la modélisation, Université Montpellier 2, France, LIRMM, MAB, CNRS UMR 5506, Université Montpellier 2, Montpellier, France and Genomic instability of pluripotent stem cells, INSERM, U1040, Institute for Research in Biotherapy, Montpellier F-34197, France.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Philippe
authors.forename: Elias
authors.initials: E
authors.lastname: Bou Samra
authors.forename: Anthony
authors.initials: A
authors.lastname: Boureux
authors.forename: Alban
authors.initials: A
authors.lastname: Mancheron
authors.forename: Florence
authors.initials: F
authors.lastname: Rufflé
authors.forename: Qiang
authors.initials: Q
authors.lastname: Bai
authors.forename: John
authors.initials: J
authors.lastname: De Vos
authors.forename: Eric
authors.initials: E
authors.lastname: Rivals
authors.forename: Thérèse
authors.initials: T
authors.lastname: Commes
mesh_terms: D002460:Cell Line; D020869:Gene Expression Profiling / Q000379:methods*; D015894:Genome, Human; D006801:Humans; D058977:Molecular Sequence Annotation; D011061:Poly A / Q000032:analysis; D022661:RNA, Untranslated / Q000032:analysis*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software; D014158:Transcription, Genetic
chemical_list: D022661:RNA, Untranslated; D011061:Poly A