Strain-specific genomic diversity in the Mycobacterium tuberculosis complex (MTBC) is an important factor in tuberculosis pathogenesis that may affect virulence, transmissibility, host response and emergence of drug resistance [1,2]. Some modern strains (e.g. Beijing, Euro-American, Haarlem) are believed to exhibit more virulent phenotypes compared to ancient ones (e.g. East African, Indian, M. africanum) [2]. M. tuberculosis is relatively clonal, with little recombination and a low mutation rate [3]. Like other bacterial genomic settings, the construction of phylogenetic trees using sequence data facilitates taxonomic localisation and the evolutionary analysis. The growing availability of M. tuberculosis whole genome sequences is leading to the full characterisation of single nucleotide polymorphisms (SNPs) and other nucleotide variation, such as insertions and deletions (indels). A SNP–based barcode has been developed to discriminate strain-types [2]. Trees constructed using genome-wide variation have greater discriminatory power than traditional genotyping approaches such as MIRU-VNTR and spoligotyping [4]. Clades reflecting strain type variations may be used to investigate disease outbreaks or transmission events, where samples are identified through apparent identical genomic signatures [5,6]. The tree also provides a structure to identify variants that can be used to investigate clinically important traits such as drug resistance [5]. The primary mechanism for acquiring resistance is the accumulation of point mutations in genes coding for drug-targets or -converting enzymes (e.g. katG, inhA, rpoB, pncA, embB, rrs, gyrA, gyrB genes) [7], and these mutations may exist in multiple lineages in the tree, reflecting homoplasy events. Some mutations thought to be related to drug resistance are actually not, but instead strain-informative [2]. With the increased application of sequencing technologies within clinical and microbiological research settings, it is important that informatic tools are available to identify informative strain-type and drug resistance related variants. Web-browsers for the visualisation of M. tuberculosis genomic variation exist [8-10], but there is limited connectivity with phylogenetic trees and downstream analysis, especially involving strain-types and drug resistance. In addition, there is little provision for uploading new data, such as standard variant call files (VCFs) (www.htslib.org). Here we present the PhyTB tool, which facilitates the phylogenetic exploration of M. tuberculosis isolates, including the display of clade-specific informative and drug resistance markers and their genomic annotation. Using the browser, it is possible to upload multiple standard genomic variant call files (VCF format) to identify the closest relative within the M. tuberculosis complex global phylogeny, thereby potentially assisting their interpretation in a clinical or epidemiological context. Source code is available to facilitate the development of sites for other organisms with genomes that can be represented in a phylogeny.

PhyTB is a JavaScript–based web-browsing tool that uses the D3.js library for data visualization [11] and the JBrowse tool for genome browser representation [12]. The source code has been integrated and called PhyloTrack, enabling websites for other organisms to be developed (http://sourceforge.net/projects/phylotrack). The software requires a phylogenetic tree of the common Newick data format as input, and tab delimited meta data files for samples, clade-defining nodes and clade colour definitions. The phylogenetic tree was constructed using 91 k SNPs mapped against the H37Rv reference genome [Genbank:NC_000962.3]. These SNPs were identified using a combination of bwa-mem alignment software (bio-bwa.sourceforge.net) and the SAMtools/BCFtools suite (samtools.sourceforge.net) complemented by GATK (https://www.broadinstitute.org/gatk/). Variants at Q-score of 30 or more were then selected from the intersection dataset between those obtained from both SAMtools and GATK. SNPs in non-unique regions, including repeat regions in PE/PPE genes were removed (see [2] for details). The best-scoring maximum likelihood phylogenetic tree was computed using RAxML v7.4.2 (http://sco.h-its.org/exelixis/web/software/raxml/index.html) based on 91,648 sites spanning the whole genome. Given the considerable size of the dataset (1,601 samples, 91,648 SNP sites), the rapid bootstrapping algorithm (N = 100, ×= 12,345) combined with maximum likelihood search was chosen to construct the phylogenetic tree including only branches with bootstrap values greater than 95%. The resulting tree was rooted on M. canettii [Genbank: NC_019950.1] and nodes were annotated. Subsequently, the ancestral sequence at all internal nodes was computed using DnaPars from the Phylip package (http://evolution.genetics.washington.edu/phylip/). The main lineage- and sublineage-defining nodes were initially identified from the tree, based on the spoligotypes in each clade. Informative markers at each node in the phylogenetic tree are stored in VCF files and displayed, highlighting clade-defining polymorphism. This functionality has been implemented using the tabix tool [13] on the server side. The informative variants have been established by comparing allele frequencies between strain-types using ancestral node comparisons [2]. Perl scripts used to generate these data is included within the PhyloTrack package. These include scripts to convert a tree in JSON format for use by the D3.js library, produce metadata for each node, and process VCF files containing information for each node and SNP. VCF files containing clade informative and drug resistance markers [2] are compressed using bgzip and indexed using tabix to improve computational efficiency, as well as to act as a database. Variants in user uploaded VCF files are compared to those in the database to establish a sample’s position within the tree. Using node-specific SNPs, the possible paths inside the tree are reconstructed, and the one with the most SNP matches is reported. PhyTB’s map view shows allele and strain-type frequencies by geographical location, developed from PolyTB source code [9].

Project name: PhyTB Project home page: http://pathogenseq.lshtm.ac.uk/phytblive/index.php Source code: PhyloTrack - http://sourceforge.net/projects/phylotrack Operating system(s): Platform independent Programming language: JavaScript and Perl Other requirements: None License: None Any restrictions to use by non-academics: None