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dc.contributor.authorHassan, Musa A.
dc.contributor.authorMelo, Mariane Bandeira
dc.contributor.authorHaas, Brian J.
dc.contributor.authorSaeij, Jeroen
dc.contributor.authorJensen, Kirk D.
dc.date.accessioned2013-01-23T15:30:39Z
dc.date.available2013-01-23T15:30:39Z
dc.date.issued2012-12
dc.date.submitted2012-06
dc.identifier.issn1471-2164
dc.identifier.urihttp://hdl.handle.net/1721.1/76341
dc.description.abstractBackground: Accurate gene model predictions and annotation of alternative splicing events are imperative for genomic studies in organisms that contain genes with multiple exons. Currently most gene models for the intracellular parasite, Toxoplasma gondii, are based on computer model predictions without cDNA sequence verification. Additionally, the nature and extent of alternative splicing in Toxoplasma gondii is unknown. In this study, we used de novo transcript assembly and the published type II (ME49) genomic sequence to quantify the extent of alternative splicing in Toxoplasma and to improve the current Toxoplasma gene annotations. Results: We used high-throughput RNA-sequencing data to assemble full-length transcripts, independently of a reference genome, followed by gene annotation based on the ME49 genome. We assembled 13,533 transcripts overlapping with known ME49 genes in ToxoDB and then used this set to; a) improve the annotation in the untranslated regions of ToxoDB genes, b) identify novel exons within protein-coding ToxoDB genes, and c) report on 50 previously unidentified alternatively spliced transcripts. Additionally, we assembled a set of 2,930 transcripts not overlapping with any known ME49 genes in ToxoDB. From this set, we have identified 118 new ME49 genes, 18 novel Toxoplasma genes, and putative non-coding RNAs. Conclusion: RNA-seq data and de novo transcript assembly provide a robust way to update incompletely annotated genomes, like the Toxoplasma genome. We have used RNA-seq to improve the annotation of several Toxoplasma genes, identify alternatively spliced genes, novel genes, novel exons, and putative non-coding RNAs.en_US
dc.description.sponsorshipNew England Regional Center of Excellence for Biodefense and Emerging Infectious Diseases (Developmental grant (AIO57159))en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (grant RO1-AI080621)en_US
dc.description.sponsorshipPew Charitable Trustsen_US
dc.description.sponsorshipWellcome Trust (London, England) (Fellowship)en_US
dc.description.sponsorshipKnights Templar Eye Foundation (Postdoctoral fellowship)en_US
dc.description.sponsorshipCancer Research Institute (New York, N.Y.) (Postdoctoral fellowship)en_US
dc.publisherBioMed Central Ltd.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/1471-2164-13-696en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.sourceBioMed Central Ltden_US
dc.titleDe novo reconstruction of the Toxoplasma gondii transcriptome improves on the current genome annotation and reveals alternatively spliced transcripts and putative long non-coding RNAsen_US
dc.typeArticleen_US
dc.identifier.citationHassan, Musa A et al. “De Novo Reconstruction of the Toxoplasma Gondii Transcriptome Improves on the Current Genome Annotation and Reveals Alternatively Spliced Transcripts and Putative Long Non-coding RNAs.” BMC Genomics 13.1 (2012): 696. Web.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biologyen_US
dc.contributor.mitauthorHassan, Musa A.
dc.contributor.mitauthorMelo, Mariane Bandeira
dc.contributor.mitauthorJensen, Kirk D. C.
dc.contributor.mitauthorSaeij, Jeroen
dc.relation.journalBMC Genomicsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2013-01-16T06:38:46Z
dc.language.rfc3066en
dc.rights.holderMusa A Hassan et al.; licensee BioMed Central Ltd.
dspace.orderedauthorsHassan, Musa A; Melo, Mariane B; Haas, Brian; Jensen, Kirk D C; Saeij, Jeroen P Jen
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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