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Jensen, R. V.

Publications and source records attributed to Jensen, R. V..

2 recordsLinked to original sources

Expanded Analysis of the Pantoea stewartii subsp. stewartii DC283 Complete Genome Reveals Plasmid-borne Virulence Factors

Pantoea stewartii subsp. stewartii, a Gram-negative proteobacterium, causes Stewarts wilt disease in corn. Bacterial transmission to plants occurs primarily via the corn flea beetle insect vector, which is native to North America. P. stewartii DC283 is the wild-type reference strain most used to study pathogenesis. Previously the complete genome of P. stewartii was released. Here, the method whereby the genome was assembled is described in greater detail. Data from a matepair library preparation with 3.5 kilobase insert size and high-throughput sequencing from the MiSeq Illumina platform, together with the available incomplete genome sequence of AHIE00000000.1 (containing 65 contigs) was used. This work resulted in the complete assembly of one circular chromosome, ten circular plasmids and one linear phage from P. stewartii DC283. A high number of sequences encoding repetitive transposases (> 400) were found in the complete genome. The separation of plasmids from genomic DNA revealed that two Type III secretion systems in P. stewartii DC283 are located on two separate mega-plasmids. Interestingly, the assembly identified a previously unknown 66-kb region in a location interior to a contig in the previous reference genome. Overall, a novel approach was successfully utilized to fully assemble a prokaryotic genome that contains large numbers of repetitive sequences and multiple plasmids, which resulted in some interesting biological findings.

bioinformatics

FastViromeExplorer: A Pipeline for Virus and Phage Identification and Abundance Profiling in Metagenomics Data

Identifying viruses and phages in a metagenomics sample has important implication in improving human health, preventing viral outbreaks, and developing personalized medicine. With the rapid increase in data files generated by next generation sequencing, existing tools for identifying and annotating viruses and phages in metagenomics samples suffer from expensive running time. In this paper, we developed a stand-alone pipeline, FastViromeExplorer, for rapid identification and abundance quantification of viruses and phages in big metagenomic data. Both real and simulated data validated FastViromeExplorer as a reliable tool to accurately identify viruses and their abundances in large data, as well as in a time efficient manner.

bioinformatics