@ARTICLE{TreeBASE2Ref22547, author = {Ruth Evangeline Timme and James B Pettengill and Marc Allard and Errol Strain and Rodolphe Barrangou and Chris Wehnes and JoAnn Van Kessel and Jeffrey Karns and Steven Musser and Eric Brown}, title = {Phylogenetic diversity of the enteric pathogen Salmonella enterica subsp. enterica inferred from genome-wide reference-free SNP characters.}, year = {2013}, keywords = {H antigens; serovar O antigens; CRISPR; lineage through time plot; comparative method}, doi = {10.1093/gbe/evt159}, url = {http://gbe.oxfordjournals.org/content/early/2013/10/23/gbe.evt159.abstract}, pmid = {}, journal = {Genome Biology and Evolution}, volume = {}, number = {}, pages = {}, abstract = {The enteric pathogen, Salmonella enterica is one of the leading causes of foodborne illness in the world. The species is extremely diverse, containing over 2,500 named serovars that are designated for their unique antigen characters and pathogenicity profiles - some are known to be virulent pathogens, while others are not. Questions regarding the evolution of pathogenicity, significance of antigen characters, diversity of CRISPR loci, among others, will remain elusive until a strong evolutionary framework is established. We present the first large scale Salmonella enterica subsp. enterica phylogeny inferred from new reference-free k-mer approach of gathering single nucleotide polymorphisms (SNPs) from whole genomes. The phylogeny of 156 isolates representing 78 serovars (107 were newly-sequenced) reveals two major lineages, each with many strongly supported sub-lineages. One of these lineages is the Salmonella Typhi group; well nested within the phylogeny. Lineage-through-time analyses suggest there have been two instances of accelerated rates of diversification within the subspecies. We also found that antigen characters and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) loci reveal different evolutionary patterns than that of the phylogeny, suggesting horizontal gene transfer might have influenced the present character distribution. Our study also shows the ability to extract reference-free SNPs from a large set of genomes, and then to use these SNPs for phylogenetic reconstruction. This automated, annotation-free approach is an important step forward for bacterial disease tracking and in efficiently elucidating the evolutionary history of highly clonal organisms.} }

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