Welcome to the UPF Digital Repository

High-throughput annotation of full-length long noncoding RNAs with capture long-read sequencing

Show simple item record

dc.contributor.author Lagarde, Julien
dc.contributor.author Uszczynska-Ratajczak, Barbara
dc.contributor.author Carbonell, Silvia
dc.contributor.author Pérez-Lluch, Sílvia
dc.contributor.author Davis, Carrie A.
dc.contributor.author Gingeras, Thomas R.
dc.contributor.author Frankish, Adam
dc.contributor.author Harrow, Jennifer
dc.contributor.author Guigó Serra, Roderic
dc.contributor.author Johnson, Rory
dc.date.accessioned 2019-04-03T07:34:43Z
dc.date.available 2019-04-03T07:34:43Z
dc.date.issued 2017
dc.identifier.citation Lagarde J, Uszczynska-Ratajczak B, Carbonell S, Pérez-Lluch S, Abad A, Davis C, Gingeras TR et al. High-throughput annotation of full-length long noncoding RNAs with capture long-read sequencing. Nat Genet. 2017;49(12):1731-40. DOI: 10.1038/ng.3988
dc.identifier.issn 1061-4036
dc.identifier.uri http://hdl.handle.net/10230/37031
dc.description.abstract Accurate annotation of genes and their transcripts is a foundation of genomics, but currently no annotation technique combines throughput and accuracy. As a result, reference gene collections remain incomplete-many gene models are fragmentary, and thousands more remain uncataloged, particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), which combines targeted RNA capture with third-generation long-read sequencing. Here we present an experimental reannotation of the GENCODE intergenic lncRNA populations in matched human and mouse tissues that resulted in novel transcript models for 3,574 and 561 gene loci, respectively. CLS approximately doubled the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enabled us to definitively characterize the genomic features of lncRNAs, including promoter and gene structure, and protein-coding potential. Thus, CLS removes a long-standing bottleneck in transcriptome annotation and generates manual-quality full-length transcript models at high-throughput scales.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Nature Research
dc.relation.ispartof Nature Genetics. 2017;49(12):1731-40
dc.rights © Nature Publishing Group. http://dx.doi.org/10.1038/ng.3988
dc.title High-throughput annotation of full-length long noncoding RNAs with capture long-read sequencing
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1038/ng.3988
dc.subject.keyword Bioinformatics
dc.subject.keyword Gene expression analysis
dc.subject.keyword RNA probes
dc.subject.keyword RNA sequencing
dc.subject.keyword Sequence annotation
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account

Statistics

In collaboration with Compliant to Partaking