snpTree - a web-server to identify and construct SNP trees from whole genome sequence data

Leekitcharoenphon et al. BMC Genomics snpTree - a web-server to identify and construct SNP trees from whole genome sequence data Pimlapas Leekitcharoenphon 0 1 Rolf S Kaas 0 1 Martin Christen Frlund Thomsen 1 Carsten Friis 0 Simon Rasmussen 1 Frank M Aarestrup 0 0 National Food Institute , Building 204 , Technical University of Denmark , 2800 Kgs Lyngby, Denmark 4444 1 Center for Biological Sequence Analysis , Building 208 , Department of Systems Biology, Technical University of Denmark , 2800 Kgs Lyngby , Denmark Background: The advances and decreasing economical cost of whole genome sequencing (WGS), will soon make this technology available for routine infectious disease epidemiology. In epidemiological studies, outbreak isolates have very little diversity and require extensive genomic analysis to differentiate and classify isolates. One of the successfully and broadly used methods is analysis of single nucletide polymorphisms (SNPs). Currently, there are different tools and methods to identify SNPs including various options and cut-off values. Furthermore, all current methods require bioinformatic skills. Thus, we lack a standard and simple automatic tool to determine SNPs and construct phylogenetic tree from WGS data. Results: Here we introduce snpTree, a server for online-automatic SNPs analysis. This tool is composed of different SNPs analysis suites, perl and python scripts. snpTree can identify SNPs and construct phylogenetic trees from WGS as well as from assembled genomes or contigs. WGS data in fastq format are aligned to reference genomes by BWA while contigs in fasta format are processed by Nucmer. SNPs are concatenated based on position on reference genome and a tree is constructed from concatenated SNPs using FastTree and a perl script. The online server was implemented by HTML, Java and python script. The server was evaluated using four published bacterial WGS data sets (V. cholerae, S. aureus CC398, S. Typhimurium and M. tuberculosis). The evalution results for the first three cases was consistent and concordant for both raw reads and assembled genomes. In the latter case the original publication involved extensive filtering of SNPs, which could not be repeated using snpTree. Conclusions: The snpTree server is an easy to use option for rapid standardised and automatic SNP analysis in epidemiological studies also for users with limited bioinformatic experience. The web server is freely accessible at http://www.cbs.dtu.dk/services/snpTree-1.0/. - Background The dramatic decrease in cost for whole-genome sequencing (WGS) has made this technology economically feasible as a routine tool for scientific research, including infectious disease epidemiology. In addition, WGS has major applications for health service providers working with infectious diseases [1] as such to deliver high-resolution genomic epidemiology as the ultimate typing method for bacteria. The ideal microbial typing technique should enable differentiation of epidemiological unrelated strains and group epidemiological related (outbreak) strains, [2] and give information that will help to understand the evolutionary history of multiple strains within a clonal lineage [1,2]. Although some current technologies are highly informative like MLST or PFGE, they have limited resolution when applied to closely related isolates and different methods often have to be applied in different situations [1,2]. Especially outbreak isolates normally have very little diversity and require extensive genomic methods to differentiate and catagorize the isolates [3]. Single nucleotide polymorphisms (SNPs) also show relatively low mutation rates and are evolutionarily stable. Moreover, SNPs analysis has successfully been used for determining broad patterns of evolution in many recent studies [4-6]. Currently, There are a number of available non-commercial NGS genotype analysis software such as SOAP2 [7], GATK [8] and SAMtools [9]. Nonetheless, all of the software require bioinformatic skills, various options, various setting and they do not have a user friendly web-interface. Here we introduce snpTree. A server for online-automatic SNP analysis and SNP tree construction from sequencing reads as well as from assembled genomes or contigs. The server is a pipeline which intregrates avaliable SNPs analysis softwares such as SAMtools [9] and MUMmer [10], with customized scripts. The performance of the server was evaluated with four published bacterial WGS data set; Vibrio cholerae [3], Staphylococcus aureus CC398 [6], Salmonella Typhimurium [11] and Mycobacterium tuberculosis [12]. Implementation The snpTree server was created to handle both WGS data and assembled genomes to generate a phylogenetic tree based on SNPs data. The overall process is shown in Figure 1. For raw reads (Figure 1A), snpTree use an inhouse toolbox (Genobox) for mapping and genotyping which consists of avaliable programs for next-generation sequencing analysis such as Burrows-Wheeler Aligner, BWA [13] and software package for SNPs calling and genotyping, SAMtools [9]. The source code of Genebox is available at https://github.com/srcbs/GenoBox. For contigs or assembled genomes (Figure 1B), MUMmer [10] is used for both reference genome alignment and SNPs identification processes. The web-server contains more than 2,000 completed reference genomes collected from NCBI Genome database (accessed on April 2012). SNPs identification from WGS Prior to mapping raw reads to a proper reference genome, the sequence data in fastq format are filtered and trimmed according to the following criteria [14]: (i) reads with Ns are removed, (ii) if a read matches a minimum of 25 nt of a sequencing primer/adaptor the reads are trimmed at the 5 coordinate of match, (iii) the 3 tail bases are trimmed if the quality score is less than 20, (iv) the minimum average quality of the read should be 20 and the read length after trimming should be at least 20 nt. Trimmed raw reads are aligned against a reference genome using BWA [13] with minimum mapping quality equal to 30 as a default (Figure 1A). BWA is based on an effective data compression algorithm called BurrowsWheeler transform (BWT) that is fast, memory-efficient and espectially useful for aligning short reads [15]. SNPs calling and filtering are accomplished by SAMtools that is a software package for parsing and manipulating alignments in the generic alignment format (SAM/ BAM format) [9]. The snpTree server allows users to set a couple of parameters to filter SNPs, a minimum coverage and a minimum distance between each SNPs (prune). The default for both cut-offs is set to 10 and additionally all heterozygous SNPs are filtered because these are likely mapping errors in haploid chromosomes. The identifed SNPs are concluded into a VCF file. SNPs identification from assembled genomes A pipeline has been developed around the software package MUMmer version 3.23 [10] (Figure 1B). An application named Nucmer, which (...truncated)