Exploiting single-molecule transcript sequencing for eukaryotic gene prediction

Genome Biol. 2015 Sep 2;16(1):184. doi: 10.1186/s13059-015-0729-7.


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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Beta vulgaris / genetics
  • DNA, Complementary / chemistry
  • Gene Expression Profiling / methods*
  • Genes, Plant
  • Molecular Sequence Data
  • Sequence Analysis, RNA / methods*
  • Spinacia oleracea / genetics


  • DNA, Complementary

Associated data

  • GENBANK/AYZS02000000
  • GENBANK/AYZV02000000
  • SRA/SRR1508751
  • SRA/SRR1508753
  • SRA/SRR1508755
  • SRA/SRR1508756
  • SRA/SRR1508758
  • SRA/SRX674044
  • SRA/SRX674050