High Throughput Sequencing-Based Approaches for Gene Expression Analysis R. Raja Sekhara Reddy and M. V. Ramanujam Abstract Next-generation sequencing has emerged as the method of choice to answer fundamental questions in biology.


Chapter 4 High Throughput Sequencing-Based Approaches for Gene Expression Analysis R. Raja Sekhara Reddy and M. V. Ramanujam

Abstract Next-generation sequencing has emerged as the method of choice to answer fundamental questions in biology.

The massively parallel sequencing technology for RNA-Seq analysis enables better understanding of gene expression patterns in model and nonmodel organisms. Sequencing per se has reached the stage of commodity level while analyzing and interpreting huge amount of data has been a significant challenge. This chapter is aimed at discussing the complexities involved in sequencing and analysis, and tries to simplify sequencing based gene expression analysis. Biologists and experimental scientists were kept in mind while discussing the methods and analysis workflow. Key words RNA, RNAseq, Transcriptome, NGS, Gene expression 1 Introduction The next-generation sequencing (NGS) or high throughput DNA sequencing methods have emerged as central to answering fundamental biological questions on a genome wide scale, setting forth a revolution in biology. Since the invention of DNA sequencing, the technique has proven vital for studying the genome organization, stability and in turn molecular understanding of traits and diseases. The technical superiority of NGS makes it an excellent first step analysis choice to answer fundamental questions in modern biology [1]. Applications of NGS include genome sequencing, gene expression and epigenome analysis [2]. Molecular level comparison between species aided by NGS-based genome decoding facilitated better understanding of tree of life. The knowledge of gene conservation across species is providing insights to the molecular mechanisms of gene regulation. RNA sequencing (RNA-Seq) is emerging as a standard research tool to address basic questions in biology such as cell cycle regulation, division, and divergence. RNA-Seq is superior to microarray Nalini Raghavachari and Nata` lia Garcia-Reyero (eds.), Gene Expression Analysis: Methods and Protocols, Methods in Molecular Biology, vol. 1783, https://doi.org/10.1007/978-1-4939-7834-2_15, © Springer Science+Business Media, LLC, part of Springer Nature 2018 299 because it does not require prior sequence information of the organism and expression can be digitally quantified; it also detects the splicing patterns and posttranscriptional modifications [3]. RNA-Seq can be used to analyze the whole transcriptome, including mRNA, ncRNA, and smallRNA, and it has facilitated gene regulation profiling of nonmodel organisms like never before [4]. RNA-Seq can be performed using different NGS technologies such as pyrosequencing (Roche), sequencing by synthesis (Illumina), semiconductor sequencing (Ion torrent), single molecule real-time sequencing (Pacific Biosciences), and nanopore sequencing (Oxford nanopore). However, Illumina’s sequencing by synthesis technique is widely used for RNA-Seq because of the data quantity requirements [5].

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