Gene fragmentation in bacterial draft genomes: extent, consequences and mitigation - Klassen, Jonathan L (BioMed Central, 2012)
BACKGROUND: Ongoing technological advances in genome sequencing are allowing bacterial genomes to be sequenced at ever-lower cost. However, nearly all of these new techniques concomitantly decrease genome quality, primarily due to the inability of their relatively short read lengths to bridge certain genomic regions, e.g., those containing repeats. Fragmentation of predicted open reading frames (ORFs) is one possible consequence of this decreased quality. In this study we quantify ORF fragmentation in draft microbial genomes and its effect on annotation efficacy, and we propose a solution to ameliorate this problem. RESULTS: A survey of draft-quality genomes in GenBank revealed that fragmented ORFs comprised > 80% of the predicted ORFs in some genomes, and that increased fragmentation correlated with decreased genome assembly quality. In a more thorough analysis of 25 Streptomyces genomes, fragmentation was especially enriched in some protein classes with repeating, multi-modular structures such as polyketide synthases, non-ribosomal peptide synthetases and serine/threonine kinases. Overall, increased genome fragmentation correlated with increased false-negative Pfam and COG annotation rates and increased false-positive KEGG annotation rates. The false-positive KEGG annotation rate could be ameliorated by linking fragmented ORFs using their orthologs in related genomes. Whereas this strategy successfully linked up to 46% of the total ORF fragments in some genomes, its sensitivity appeared to depend heavily on the depth of sampling of a particular taxon's variable genome. CONCLUSIONS: Draft microbial genomes contain many ORF fragments. Where these correspond to the same gene they have particular potential to confound comparative gene content analyses. Given our findings, and the rapid increase in the number of microbial draft quality genomes, we suggest that accounting for gene fragmentation and its associated biases is important when designing comparative genomic projects.