ArticlePloS one2014
Correction of the Caulobacter crescentus NA1000 genome annotation.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Achieving Accurate Sequence and Annotation Data for Caulobacter vibrioides CB13.Current microbiology · 2018Article
- The global regulatory architecture of transcription during the Caulobacter cell cycle.PLoS genetics · 2015Article
- A comparison of the Caulobacter NA1000 and K31 genomes reveals extensive genome rearrangements and differences in metabolic potential.Open biology · 2014Article
- Estimating overannotation across prokaryotic genomes using BLAST+, UBLAST, LAST and BLAT.BMC research notes · 2014Article
- Biomineralization of uranium by PhoY phosphatase activity aids cell survival in Caulobacter crescentus.Applied and environmental microbiology · 2014Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%.
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Registered trials
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