Abstract
Yersinia pestis is the causative agent of the plague. Y. pestis KIM 10+ strain was passaged and selected for loss of the 102 kb pgm locus, resulting in an attenuated strain, KIM D27. In this study, whole genome sequencing was performed on KIM D27 in order to identify any additional differences. Initial assemblies of 454 data were highly fragmented, and various bioinformatic tools detected between 15 and 465 SNPs and INDELs when comparing both strains, the vast majority associated with A or T homopolymer sequences. Consequently, Illumina sequencing was performed to improve the quality of the assembly. Hybrid sequence assemblies were performed and a total of 56 validated SNP/INDELs and 5 repeat differences were identified in the D27 strain relative to published KIM 10+ sequence. However, further analysis showed that 55 of these SNP/INDELs and 3 repeats were errors in the KIM 10+ reference sequence. We conclude that both 454 and Illumina sequencing were required to obtain the most accurate and rapid sequence results for Y. pestis KIMD27. SNP and INDELS calls were most accurate when both Newbler and CLC Genomics Workbench were employed. For purposes of obtaining high quality genome sequence differences between strains, any identified differences should be verified in both the new and reference genomes.
Highlights
Whole genome sequencing (WGS) has broadened the field of microbial forensics by allowing the identification of bacteria to the subspecies level, and to specific sequence types [1]
Using the 454 sequencing platform we obtained the genomic sequence of Y. pestis KIM D27 within days of obtaining the genomic DNA
After various attempts at assembling the genome, we discovered that 454-only sequencing yielded large numbers of single nucleotide polymorphisms (SNPs), INDELS, and VNTR differences when compared to the parental genome, most within poly(A) or poly(T) homopolymer tracts
Summary
Whole genome sequencing (WGS) has broadened the field of microbial forensics by allowing the identification of bacteria to the subspecies level, and to specific sequence types [1]. The data generated by NGS can be used to fully understand the lineage of naturally or maliciously constructed disease isolates, and could even yield information about past propagation and culturing conditions due to mutations that occur during passage [2,3]. Genome resequencing efforts with NGS have been used to study the evolutionary lineage of different strains within a single species [2,4,5], or to study the types of adaptations that occur during growth in specific conditions [3]. The study found that Y. pestis strains can be grouped into 4 specific lineages (1 root and 3 branches), that can be characterized further by lineagespecific SNPs [6]. For forensic applications, NGS data must be practically error-free since the data could potentially be used to identify and prosecute perpetrators of criminal or terrorist acts
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