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Updating microbial genomic sequences: improving accuracy & innovation
© Tae et al.; licensee BioMed Central Ltd. 2014
- Received: 11 July 2014
- Accepted: 25 October 2014
- Published: 7 November 2014
Many bacterial genome sequences completed using the Sanger method may contain assembly errors due in-part to low sequence coverage driven by cost.
To illustrate the need for re-sequencing of pre-nextgen genomes and to validate sequenced genomes, we conducted a series of experiments, using high coverage sequencing data generated by a Illumina Miseq sequencer to sequence genomic DNAs of Bacteroides fragilis NCTC 9343, Salmonella enterica subsp. enterica serovar Paratyphi A str. ATCC 9150, Vibrio cholerae O1 biovar El Tor str. N16961, Bacillus halodurans C-125 and Caulobacter crescentus CB15, which had previously been sequenced by the Sanger method during the early 2000’s.
This study revealed a number of discrepancies between the published assemblies and sequence read alignments for all five bacterial species, suggesting that the continued use of these error-containing genomes and their genetic information may contribute to false conclusions and/or incorrect future discoveries when they are used.
The completed genome sequences of over 2,000 bacterial species have been published during the last decade and many of them (we estimate at least 500) were sequenced exclusively by the Sanger method; however this method was frequently deployed at low sequence coverage due to cost constraints. Even though the Sanger method assemblies targeted high accuracy (99.5%), low coverage might leave assembly errors in the completed genome sequences, which have been frequently used as references for re-sequencing projects. At the start of a re-sequencing analysis, it is important to choose a suitable reference genome sequence to compare against, to better identify high probability variants. These “variations” are then a foundation for many downstream correlative and functional analyses. Significantly, in the analysis of pathogens such as Brucella, Salmonella and Vibrio species, the results of variation detection are the basis for developing assays that are critical to the detection and validation of these pathogens.
In our previous work with Brucella suis 1330, which was sequenced with the Sanger method in 2002 and re-sequenced in 2011 using the Illumina GAIIx platform, we identified a number of discrepancies between the published and the new assembly. We used a hybrid approach of mapping and assembly with the Illumina sequencing data, and identified a total of twelve very high confidence sequence differences including ten INDELs (insertions or deletions) and two substitutions between the assemblies. Among them, six INDELs caused frameshifts within protein-coding loci. The differences were significant enough that the published sequence could lead downstream studies into inaccurate reporting and understanding of genomic mutations. Another re-sequencing study by Wynne for the genome of Mycobacterium avium subsp. paratuberculosis K10 also showed differences between its original assembly and revised assembly which was originally sequenced in 2005 (Sanger method) and later with the Illumina GAIIx platform in 2010. Importantly, these studies implicate that other completed bacterial genome assemblies sequenced with the Sanger method may contain assembly errors resulting in inaccurate variation analyses. It also highlights the need for re-sequencing efforts using high coverage sequencing data generated by efficient and cost effective next-generation sequencing (NGS) technologies to validate these genome sequences. Especially for pathogen genomes, accurate references are essential for studying, detecting, and preventing public safety threats. Additionally, billions of dollars are invested by multiple federal agencies (i.e. CDC, FDA, USDA, and NIH) and private institutions (i.e. food production facilities, pharmaceutical companies, diagnostics labs etc.…), annually, to maintain safety from these biological agents; consequently, these efforts are now more frequently reliant upon standardized genomic information for genetic testing that utilize established markers for pathogen identification. Inaccurate or incomplete genomic information could contribute to misinformation to these agencies, impacting human health in addition to their effect on basic research.
Citations linked to originally sequenced bacterial genomes
Citations associated with originally published genome sequences
Salmonella enterica subsp. Enterica serovar Paratyphi A 9150
Crump et al., 2010. Global trends in typhoid and paratyphoid Fever. Clin Infect Dis 50:241–246.
Yang F, et al., 2005. Genome dynamics and diversity of Shigella species, the etiologic agents of bacillary dysentery. Nucleic acids research 33:6445–6458.
Thomson NR, et., 2008. Comparative genome analysis of Salmonella Enteritidis PT4 and Salmonella Gallinarum 287/91 provides insights into evolutionary and host adaptation pathways. Genome research 18:1624–1637.
V.cholerae O1 N16961
Thompson FL, et al., 2004. Biodiversity of vibrios. Microbiology and molecular biology reviews 68:403–431.
Makino K, et al., 2003. Genome sequence of Vibrio parahaemolyticus: a pathogenic mechanism distinct from that of V cholerae. The Lancet 361:743–749.
Zhu J, et al., 2002. Quorum-sensing regulators control virulence gene expression in Vibrio cholerae. Proceedings of the National Academy of Sciences 99:3129–3134.
Merrell DS et., 2002. Host-induced epidemic spread of the cholera bacterium. Nature 417:642–645.
C. crescentus CB15
Hu P, et al., 2005. Whole-genome transcriptional analysis of heavy metal stresses in Caulobacter crescentus. Journal of bacteriology 187:8437–8449.
Laub MT, et al., 2002. Genes directly controlled by CtrA, a master regulator of the Caulobacter cell cycle. Proceedings of the National Academy of Sciences 99:44632–4637.
Hottes AK, et al., 2005. DnaA coordinates replication initiation and cell cycle transcription in Caulobacter crescentus. Molecular microbiology 58:1340–1353.
Reisenauer A, et al., 2002. DNA methylation affects the cell cycle transcription of the CtrA global regulator in Caulobacter. The EMBO journal 21:4969–4977.
Re-sequenced bacterial genomes from six organisms
Comparison of genomic sequencing quality between sanger & NGS methods
First published year
Last updated year
Re-sequenced by illumina sequencer
Number of Inconsistent Loci
Brucelli suis 1330
Chr.1 2.1 M
Chr.2 1.2 M
Caulobacter crescentus CB15
Salmonella enterica ATCC 9150
Bacteroides fragilis NCTC 9343
Bacillus halodurans C-125
Vibrio cholerae O1 N16961
Chr.1 2.9 M
Chr.2 1.1 M
From the read alignments, we found 89, 17, 6, 147 and 165 loci of which read sequences were not consistent with the reference sequences for C.crescentus CB15, S.enterica ATCC 9150, B.fragilis NCTC 9343, B.halodurans C-125 and V.cholerae O1 N16961, respectively. All five reference sequences appeared to have loci covered by inconsistent read sequences, and the numbers of inconsistent loci were unexpectedly high for four bacteria, and modest for B. fragilis NCTC 9343. However, as we have shown in our previous studies of Brucella, not every inconsistent locus could be detected by the first alignment because alignment programs have limitations in properly aligning reads to loci containing repeat sequences, long INDELs or other structural differences. To detect structural assembly errors from read alignments, we inspected loci where at least 20% of the reads covering them were clipped (partially unaligned) at the same bases. About 4 ~ 20 loci covered by clipped reads were detected from read alignments of the five reference sequences. More than half of the loci were in the G/C homopolymer regions which frequently cause sequencing systems to generate incorrect random sequences, thus unaligned parts of read sequences were not consistent. At other loci, the unaligned parts of read sequences were consistent and able to generate consensus sequences, which are duplications of other loci or do not exist in the reference sequences, indicating potential structural assembly errors (or they may be the results of rapid evolutionary changes).
The usage of genomic sequencing material derived from Sanger sequencing methods were a valuable, pioneering tool towards current methods. However, this method is highly error prone and the continued use of these sequenced genomes to identify anomalous and unique genomic traits could be additive in error to original findings, unless these sequences are updated. A few, such as Escherichia coli K-12 sub-strain MG1655, have been continuously updated by the original submitters, but many completed sequences contain assembly errors and lack necessary revisions. Species specific genome sequences are used in a variety of platforms in basic and applied research, including: understanding evolutionary relationships, mechanisms of microbial virulence and disease pathogenesis, diagnostics, and food and health safety. As a scientific community, we are able to illustrate the needs and the capability to rectify these errors by next-gen, re-sequencing as seen in the reanalysis of multiple organisms[1, 2]. Now, with advances in NGS technologies which can generate tremendous amounts of raw sequencing data in a cost and time efficient way, high sequence coverage of bacterial genomes has been enabled to validate these data and revise single nucleotide or short INDEL errors. In this small study we have successfully demonstrated that these errors can be minimized with NGS methods and also propose a concerted initiative to re-sequence genomes from the ‘Sanger-era’. As concerns for reproducibility in science are ever increasing- with special emphasis linked to ‘big-data’ and genomics- science must address sequenced microbial genomes and establish standards for highlighting older sequenced material and flagging these data to be used with caution. This is a contemporary issue, for the genomes previously measured years ago are still very much in use, a current solution (and investment to science) is nextgen re-sequencing. By conducting large scale evaluations of genome sequences published during the early 2000s, as a scientific community we would safeguard public interests and the integrity of future endeavors from the consequence of existing errors.
This work was funded by the Medical Informatics and Systems Division directors fund to Dr. Garner at VBI/Virginia Tech. We thank the system administrators in the VBI computational core (Jason Decker, Michael Snow, Dominik Borkowski, David Bynum, Douglas McMaster, Jeremy Johnson, and Vedavyas Duggirala) for technical support.
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