title: Large-scale prokaryotic gene prediction and comparison to genome annotation.
abstract: BACKGROUND
  Prokaryotic genomes are sequenced and annotated at an increasing rate. The methods of annotation vary between sequencing groups. It makes genome comparison difficult and may lead to propagation of errors when questionable assignments are adapted from one genome to another. Genome comparison either on a large or small scale would be facilitated by using a single standard for annotation, which incorporates a transparency of why an open reading frame (ORF) is considered to be a gene.
  
  
  RESULTS
  A total of 143 prokaryotic genomes were scored with an updated version of the prokaryotic genefinder EasyGene. Comparison of the GenBank and RefSeq annotations with the EasyGene predictions reveals that in some genomes up to approximately 60% of the genes may have been annotated with a wrong start codon, especially in the GC-rich genomes. The fractional difference between annotated and predicted confirms that too many short genes are annotated in numerous organisms. Furthermore, genes might be missing in the annotation of some of the genomes. We predict 41 of 143 genomes to be over-annotated by >5%, meaning that too many ORFs are annotated as genes. We also predict that 12 of 143 genomes are under-annotated. These results are based on the difference between the number of annotated genes not found by EasyGene and the number of predicted genes that are not annotated in GenBank. We argue that the average performance of our standardized and fully automated method is slightly better than the annotation.
authors.affiliation: Bioinformatics Centre, Institute of Molecular Biology and Physiology, University of Copenhagen Universitetsparken 15, 2100 Copenhagen, Denmark. pern@binf.ku.dk
authors.forename: Pernille
authors.initials: P
authors.lastname: Nielsen
authors.forename: Anders
authors.initials: A
authors.lastname: Krogh
mesh_terms: D001482:Base Composition; D019295:Computational Biology; D004247:DNA / Q000737:chemistry / Q000235:genetics; D030541:Databases, Genetic; D023281:Genomics / Q000706:statistics & numerical data*; D008390:Markov Chains; D008957:Models, Genetic; D016366:Open Reading Frames; D011387:Prokaryotic Cells; D012984:Software
chemical_list: D004247:DNA