Abstract
The availability of data produced from various sequencing platforms offer the possibility to answer complex questions in plant research. However, drawbacks can arise when there are gaps in the information generated, and complementary platforms are essential to obtain more comprehensive data sets relating to specific biological process, such as responses to environmental perturbations in plant systems. The investigation of transcriptional regulation raises different challenges, particularly in associating differentially expressed transcription factors with their downstream responsive genes. In this paper, we discuss the integration of transcriptional factor studies through RNA sequencing (RNA-seq) and Chromatin Immunoprecipitation sequencing (ChIP-seq). We show how the data from ChIP-seq can strengthen information generated from RNA-seq in elucidating gene regulatory mechanisms. In particular, we discuss how integration of ChIP-seq and RNA-seq data can help to unravel transcriptional regulatory networks. This review discusses recent advances in methods for studying transcriptional regulation using these two methods. It also provides guidelines for making choices in selecting specific protocols in RNA-seq pipelines for genome-wide analysis to achieve more detailed characterization of specific transcription regulatory pathways via ChIP-seq.
Highlights
The transcriptome defines the functional element in a genome as it encompasses the complete set of coding and non-coding RNA molecules present in a single cell or a population of cells [1]
Genome-wide identification of transcription factors of interest or novel transcription factors through RNA-seq can result in a more in-depth understanding of transcriptional networks associated with these transcription factors and their regulons when followed with ChIP-seq analysis
The ChIP-seq technique can provide valuable information about transcriptional regulation based on transcription factor binding to target DNA promoter motifs for coordinating transcriptional regulation in response to environmental cues, while RNA-seq alone does not provide complete information
Summary
The transcriptome defines the functional element in a genome as it encompasses the complete set of coding and non-coding RNA molecules present in a single cell or a population of cells [1]. Transcriptome profiling can greatly facilitate the understanding of a functional genome via characterization of the gene structures, identification of the alternative splicing events, as well as detection of the dynamic regulation of transcripts in various tissues during development, diseased, or stressed conditions [3] Ever since they were first introduced in 2005, high throughput next-generation DNA sequencing (NGS) technologies have revolutionized the transcriptomics field through massively parallel sequencing of complementary DNA (cDNAs) derived from a transcript population. We provide examples of genome-wide identification of transcription factor co-regulated genes by RNA-seq and ChIP-seq, which highlight the potential of such studies in elucidating transcriptional regulatory network in important biological processes in plants These examples will show how combining these tools will help in addressing hormonal response like jasmonic acid in Arabidopsis [1], gibberellic acid in rice [2], and the developmental stage effect in maize [3] to reveal some important insights on their transcriptional regulatory mechanisms. We introduce the third-generation sequencing, which expands the application of sequencing technology due to the longer read length offering higher capability in sequence assembly and identifying sequence variance in RNA-seq
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