Computational analysis of HTS data and its application in plant pathology

Abstract

High-throughput sequencing is a basic tool of biological research, and it is extensively used in plant pathology projects. Here, we describe how to handle data coming from a variety of sequencing experiments, focusing on the analysis of Illumina reads. We describe how to perform genome assembly and annotation with DNA reads, correctly analyze RNA-seq data to discover differentially expressed genes, handle amplicon sequencing data from microbial communities, and utilize small RNA sequencing data to predict miRNA sequences and their putative targets.

Keywords

High-throughput sequencing; Genome assembly; Functional annotation; Transcriptomics; Differential expression; Metabarcoding; Small RNA; miRNA; Target prediction

Published in

Methods in Molecular Biology
2022, number: 2536, pages: 275-307
Title: Plant Pathology : Method and Protocols
Publisher: Springer

SLU Authors

• Piombo, Edoardo

  • Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences
    

• Dubey, Mukesh

  • Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences
    

Associated SLU-program

SLU Plant Protection Network

UKÄ Subject classification

Genetics
Bioinformatics and Systems Biology

Publication identifier

• DOI: https://doi.org/10.1007/978-1-0716-2517-0_17
• ISBN: 978-1-0716-2516-3
• eISBN: 978-1-0716-2517-0

Permanent link to this page (URI)

https://res.slu.se/id/publ/120137