Abstract
Characterization and profiling of the gene expression data or, more formally, called transcriptome are crucial steps in revealing the involvement of RNA in a variety of biological processes. RNA characteristics have been investigated in a number of researches employing whole transcriptome sequencing (RNA-seq) data in all the major crops. To date, a number of crop genomes have been sequenced, which allows researchers to understand the typical biological mechanism, which may further be utilized to discover and characterise candidate genes responsible. Gene expression profiling, that is, RNA-seq, is a useful tool for identifying and understanding biological processes/mechanisms, such as the coding, decoding, regulation, and expression of genes. A basic RNA-seq process may be divided into two broad categories, that is, reference based and de novo, as per the availability of the reference genome related to the species/crop under consideration. In this chapter, we introduce basic RNA-seq analysis approaches, pipelines and software, focusing particularly on de novo transcriptome assembly and identification of differentially expressed genes (DEGs)/transcripts by using finger millet as an example.
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Avashthi, H. et al. (2022). Transcriptome Data Analysis Using a De Novo Assembly Approach. In: Wani, S.H., Kumar, A. (eds) Genomics of Cereal Crops. Springer Protocols Handbooks. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2533-0_8
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DOI: https://doi.org/10.1007/978-1-0716-2533-0_8
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