Minoche, André E.Dohm, Juliane C.Schneider, JessicaHoltgräwe, DanielaViehöver, PriscaMontfort, MagdaSörensen, Thomas RosleffWeisshaar, BerndHimmelbauer, Heinz2015-11-122015-11-122015Minoche AE, Dohm JC, Schneider J, Holtgräwe D, Viehöver P, Montfort M et al. Exploiting single-molecule transcript sequencing for eukaryotic gene prediction. Genome biology. 2015;16:184. DOI: 10.1186/s13059-015-0729-71474-7596http://hdl.handle.net/10230/25069We develop a method to predict and validate gene models using PacBio single-molecule, real-time (SMRT) cDNA reads. Ninety-eight percent of full-insert SMRT reads span complete open reading frames. Gene model validation using SMRT reads is developed as automated process. Optimized training and prediction settings and mRNA-seq noise reduction of assisting Illumina reads results in increased gene prediction sensitivity and precision. Additionally, we present an improved gene set for sugar beet (Beta vulgaris) and the first genome-wide gene set for spinach (Spinacia oleracea). The workflow and guidelines are a valuable resource to obtain comprehensive gene sets for newly sequenced genomes of non-model eukaryotes.application/pdfeng© 2015 Minoche et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.GenòmicaRNA missatgerinfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1186/s13059-015-0729-7Single-molecule real-time sequencingEukaryotic gene predictionmRNA-seqCaryophyllalesSugar beetSpinachNon-model speciesGenome annotationinfo:eu-repo/semantics/openAccess