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We 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.   Electronic supplementary material  The online version of this article (doi:10.1186/s13059-015-0729-7) contains supplementary material, which is available to authorized users.

Exploiting single-molecule transcript sequencing for eukaryotic gene prediction