Literature DB >> 34395787

In planta Transcriptome Analysis of Pseudomonas syringae.

Tatsuya Nobori1, Kenichi Tsuda1.   

Abstract

Profiling bacterial transcriptome in planta is challenging due to the low abundance of bacterial RNA in infected plant tissues. Here, we describe a protocol to profile transcriptome of a foliar bacterial pathogen, Pseudomonas syringae pv. tomato DC3000, in the leaves of Arabidopsis thaliana at an early stage of infection using RNA sequencing (RNA-Seq). Bacterial cells are first physically isolated from infected leaves, followed by RNA extraction, plant rRNA depletion, cDNA library synthesis, and RNA-Seq. This protocol is likely applicable not only to the A. thaliana-P. syringae pathosystem but also to different plant-bacterial combinations.
Copyright © 2018 The Authors; exclusive licensee Bio-protocol LLC.

Entities:  

Keywords:  Arabidopsis; Bacterial pathogen; Pseudomonas; RNA-Seq; Transcriptome

Year:  2018        PMID: 34395787      PMCID: PMC8328654          DOI: 10.21769/BioProtoc.2987

Source DB:  PubMed          Journal:  Bio Protoc        ISSN: 2331-8325


  3 in total

1.  Fast gapped-read alignment with Bowtie 2.

Authors:  Ben Langmead; Steven L Salzberg
Journal:  Nat Methods       Date:  2012-03-04       Impact factor: 28.547

2.  Transcriptome landscape of a bacterial pathogen under plant immunity.

Authors:  Tatsuya Nobori; André C Velásquez; Jingni Wu; Brian H Kvitko; James M Kremer; Yiming Wang; Sheng Yang He; Kenichi Tsuda
Journal:  Proc Natl Acad Sci U S A       Date:  2018-03-12       Impact factor: 11.205

3.  HTSeq--a Python framework to work with high-throughput sequencing data.

Authors:  Simon Anders; Paul Theodor Pyl; Wolfgang Huber
Journal:  Bioinformatics       Date:  2014-09-25       Impact factor: 6.937

  3 in total

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