Donaire Livia, Llave César
Departamento de Biología del Estrés y Patología Vegetal, Centro de Edafología y Biología Aplicada del Segura (CEBAS), Consejo Superior de Investigaciones Científicas (CSIC), Murcia, Spain.
Departamento de Biología Medioambiental, Centro de Investigaciones Biológicas (CIB), Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
Methods Mol Biol. 2019;2028:185-214. doi: 10.1007/978-1-4939-9635-3_11.
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.
在本章中，我们描述了一系列用于对植物中因病毒感染而产生的小RNA（sRNA）进行计算机分析的计算流程。我们的工作流程主要集中于分析来自感染宿主植物的已知或先前未描述病毒的sRNA群体。此外，我们还提供了一个额外的流程，用于检测在植物病毒感染期间被激活或特异性表达的宿主特异性内源性sRNA。我们介绍了从高质量RNA的纯化到文库制备和测序策略指导等一系列成功且经济高效地处理下一代测序sRNA文库的关键点。我们报告了一系列免费可用的工具和程序以及用于执行定制化sRNA测序数据挖掘的内部Perl脚本。不需要先前的生物信息学背景，但具备基本的Unix命令经验则更佳。
