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Bioinformatics Advance Access originally published online on October 25, 2005
Bioinformatics 2005 21(24):4322-4329; doi:10.1093/bioinformatics/bti701
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oxfordjournals.org

Large-scale prokaryotic gene prediction and comparison to genome annotation

Pernille Nielsen * and Anders Krogh

Bioinformatics Centre, Institute of Molecular Biology and Physiology, University of Copenhagen Universitetsparken 15, 2100 Copenhagen, Denmark

*To whom correspondence should be addressed.

Motivation: 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 ~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.

Availability: The EasyGene 1.2 predictions and statistics can be accessed at http://www.binf.ku.dk/cgi-bin/easygene/search

Contact: pern{at}binf.ku.dk

Received on July 4, 2005; revised on September 13, 2005; accepted on September 30, 2005

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