Literature DB >> 31228116

Computational Workflow for Small RNA Profiling in Virus-Infected Plants.

Livia Donaire1, César Llave2.   

Abstract

In this chapter we describe a series of computational pipelines for the in silico analysis of small RNAs (sRNA) produced in response to viral infections in plants. Our workflow is primarily focused on the analysis of sRNA populations derived from known or previously undescribed viruses infecting host plants. Furthermore, we provide an additional pipeline to examine host-specific endogenous sRNAs activated or specifically expressed during viral infections in plants. We present some key points for a successful and cost-efficient processing of next generation sequencing sRNA libraries, from purification of high quality RNA to guidance for library preparation and sequencing strategies. We report a series of free available tools and programs as well as in-house Perl scripts to perform customized sRNA-seq data mining. Previous bioinformatic background is not required, but experience with basic Unix commands is desirable.

Entities:  

Keywords:  Antiviral silencing; Bioinformatic analysis; Next generation sequencing; Plant viruses; Small RNAs; sRNA-seq

Mesh:

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Year:  2019        PMID: 31228116     DOI: 10.1007/978-1-4939-9635-3_11

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  1 in total

1.  The Potential of Molecular Indicators of Plant Virus Infection: Are Plants Able to Tell Us They Are Infected?

Authors:  Gardette R Valmonte-Cortes; Sonia T Lilly; Michael N Pearson; Colleen M Higgins; Robin M MacDiarmid
Journal:  Plants (Basel)       Date:  2022-01-11
  1 in total

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