Please use this identifier to cite or link to this item: http://223.31.159.10:8080/jspui/handle/123456789/1314
Title: In silico methods for the identification of viral-derived small interfering RNAs (vsiRNAs) and their application in plant genomics
Authors: Narayan, Aditya
Zahra, Shafaque
Singh, Ajeet
Kumar, Shailesh
Keywords: Detection
Diagnostics
In silico tools
Plant virus
Viroid
vsiRNAs
Issue Date: 2022
Publisher: Springer Nature Publishing AG
Citation: Methods in Molecular Biology, 2408: 71-84
Abstract: The current era of high-throughput sequencing (HTS) technology has expedited the detection and diagnosis of viruses and viroids in the living system including plants. HTS data has become vital to study the etiology of the infection caused by both known as well as novel viral elements in planta, and their impact on overall crop health and productivity. Viral-derived small interfering RNAs are generated as a result of defence response by the host via RNAi machinery. They are immensely exploited for performing exhaustive viral investigations in plants using bioinformatics as well as experimental approaches. This chapter briefly presents the basics of virus-derived small interfering RNAs (vsiRNAs) biology in plants and their applications in plant genomics and highlights in silico strategies exploited for virus/viroid detection. It gives a systematic pipeline for vsiRNAs identification using currently available bioinformatics tools and databases. This will surely work as a quick beginner’s recipe for the in silico revelation of plant vsiRNAs as well as virus/viroid diagnosis using high-throughput sequencing data.
Description: Accepted date: 25 March 2022
URI: https://link.springer.com/protocol/10.1007/978-1-0716-1875-2_4
http://223.31.159.10:8080/jspui/handle/123456789/1314
ISBN: 978-1-0716-1875-2
978-1-0716-1874-5
Appears in Collections:Institutional Publications

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