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Genetic diversity and biogeography of T. officinale inferred from multi locus sequence typing approach.

ABSTRACT: Taraxacum officinale (Asteraceae) is widely distributed weedy plant used as a traditional medicinal herb. The population genetics and historical biogeography of this plant have remained relatively unexplored. This study explores phylogeny, population genetics and ancestral reconstructions adopting multi locus sequence typing (MLST) approach. MLST sequences dataset was generated from genomics and chloroplast DNA sequences obtained from 31 T. officinale haplotypes located in 16 different countries. Phylogenetic analysis distributed these haplotypes in well differentiated geographic clades. The study suggested a close relationship between Europe and adjacent Asian countries. Populations of these regions predominantly formed common haplogroups, showed considerable level of gene flow and evidence for recombination events across European and Asian population. Biogeographical inferences obtained by applying statistical dispersal-vicariance analysis (S-DIVA) and Bayesian binary MCMC (BBM) analysis showed that T. officinale was putatively originated in Europe. Molecular clock analysis based on ITS dataset suggested that the divergence between Europe and East Asian populations can be dated to 1.07 Mya with subsequent dispersal and vicariance events. Among different spatial process long distance seed dispersal mediated by wind had potentially assisted the population expansion of T. officinale.

SUBMITTER: Jafari M

PROVIDER: S-EPMC6143195 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Project description:Multi-locus sequence typing (MLST) has become the gold standard for population analyses of bacterial pathogens. This method focuses on the sequences of a small number of loci (usually seven) to divide the population and is simple, robust and facilitates comparison of results between laboratories and over time. Over the last decade, researchers and population health specialists have invested substantial effort in building up public MLST databases for nearly 100 different bacterial species, and these databases contain a wealth of important information linked to MLST sequence types such as time and place of isolation, host or niche, serotype and even clinical or drug resistance profiles. Recent advances in sequencing technology mean it is increasingly feasible to perform bacterial population analysis at the whole genome level. This offers massive gains in resolving power and genetic profiling compared to MLST, and will eventually replace MLST for bacterial typing and population analysis. However given the wealth of data currently available in MLST databases, it is crucial to maintain backwards compatibility with MLST schemes so that new genome analyses can be understood in their proper historical context.We present a software tool, SRST, for quick and accurate retrieval of sequence types from short read sets, using inputs easily downloaded from public databases. SRST uses read mapping and an allele assignment score incorporating sequence coverage and variability, to determine the most likely allele at each MLST locus. Analysis of over 3,500 loci in more than 500 publicly accessible Illumina read sets showed SRST to be highly accurate at allele assignment. SRST output is compatible with common analysis tools such as eBURST, Clonal Frame or PhyloViz, allowing easy comparison between novel genome data and MLST data. Alignment, fastq and pileup files can also be generated for novel alleles.SRST is a novel software tool for accurate assignment of sequence types using short read data. Several uses for the tool are demonstrated, including quality control for high-throughput sequencing projects, plasmid MLST and analysis of genomic data during outbreak investigation. SRST is open-source, requires Python, BWA and SamTools, and is available from http://srst.sourceforge.net.

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Genetic diversity and biogeography of T. officinale inferred from multi locus sequence typing approach.

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