An evaluation of alternative methods for constructing phylogenies from whole genome sequence data: a case study withSalmonella

Abstract

Comparative genomics based on whole genome sequencing (WGS) is increasingly being applied to investigate questions within evolutionary and molecular biology, as well as questions concerning public health (e.g., pathogen outbreaks). Given the impact that conclusions derived from such analyses may have, we have evaluated the robustness of clustering individuals based on WGS data to three key factors: (1) next-generation sequencing (NGS) platform (HiSeq, MiSeq, IonTorrent, 454, and SOLiD), (2) algorithms used to construct a SNP (single nucleotide polymorphism) matrix (reference-based and reference-free), and (3) phylogenetic inference method (FastTreeMP, GARLI, and RAxML). We carried out these analyses on 194 whole genome sequences representing 107 unique Salmonella enterica subsp. enterica ser. Montevideo strains. Reference-based approaches for identifying SNPs produced trees that were significantly more similar to one another than those produced under the reference-free approach. Topologies inferred using a core matrix (i.e., no missing data) were significantly more discordant than those inferred using a non-core matrix that allows for some missing data. However, allowing for too much missing data likely results in a high false discovery rate of SNPs. When analyzing the same SNP matrix, we observed that the more thorough inference methods implemented in GARLI and RAxML produced more similar topologies than FastTreeMP. Our results also confirm that reproducibility varies among NGS platforms where the MiSeq had the lowest number of pairwise differences among replicate runs. Our investigation into the robustness of clustering patterns illustrates the importance of carefully considering how data from different platforms are combined and analyzed. We found clear differences in the topologies inferred, and certain methods performed significantly better than others for discriminating between the highly clonal organisms investigated here. The methods supported by our results represent a preliminary set of guidelines and a step towards developing validated standards for clustering based on whole genome sequence data.

NASP: an accurate, rapid method for the identification of SNPs in WGS datasets that supports flexible input and output formats

“…For the case of this E. coli dataset, the phylogeny inferred by Mugsy, a reference-independent approach, was in topological agreement with other reference-dependent approaches (Table 2). In fact, kSNPv3 was one of the only methods that returned a topology that was inconsistent with all other methods (Table 2); an inconsistent kSNP phylogeny has also been reported in the analysis of other datasets (Pettengill et al, 2014). To analyze this further, we identified SNPs (n = 826) from the NASP run using simulated paired-end reads that were uniquely shared on a branch of the phylogeny that defines a monophyletic lineage (Fig.…”

“…Previously, it has been demonstrated that different phylogenies can be obtained for the same dataset using either RAxML or FastTree2 (Pettengill et al, 2014). To test this result across multiple phylogenetic inference methods, the NASP E. coli read dataset was used.…”

“…The program lyve-SET has been applied to outbreak investigations and uses raw or simulated reads to identify SNPs (Katz et al, 2013). Finally, the CFSAN SNP pipeline is a published method from the United States Food and Drug Administration that only supports the use of raw reads (Pettengill et al, 2014). There have been, to our knowledge, no published comparative studies to compare the functionality of these pipelines on a range of test datasets.…”

Listeria monocytogenes in Stone Fruits Linked to a Multistate Outbreak: Enumeration of Cells and Whole-Genome Sequencing

“…In the United States, nationwide real-time whole-genome sequencing (WGS) was implemented using the GenomeTrakr and PulseNet network to enhance listeriosis outbreak detection and investigation (14). In several outbreak investigations, the U.S. Centers for Disease Control and Prevention (CDC) had employed a whole-genome multilocus sequence typing (wgMLST) tool that targets the allelic differences in genome-wide coding regions (14), and the U.S. Food and Drug Administration (FDA) had employed a reference-based Center for Food Safety and Applied Nutrition (CFSAN) SNP Pipeline that identifies single nucleotide polymorphisms (SNPs) in the entire genome, including core genes, accessory genes, and intergenic regions (8, 11, 15). …”

A Primer on Infectious Disease Bacterial Genomics

“…This eliminates any biases potentially introduced due to the selection of a reference and allows for the detection of SNVs not present in the reference genome. However, as noted by Pettengill et al, a reference-free approach may lead to a higher SNV false discovery rate without appropriate thresholds (177). The software package kSNP (178,179) takes a reference-free approach to identifying SNVs by breaking up each genomic data set into k-mers and comparing these k-mers.…”