Chapters authored
Recent Applications of RNA Sequencing in Food and Agriculture
RNA sequencing (RNA-Seq) is the leading, routine, high-throughput, and cost-effective next-generation sequencing (NGS) approach for mapping and quantifying transcriptomes, and determining the transcriptional structure. The transcriptome is a complete collection of transcripts found in a cell or tissue or organism at a given time point or specific developmental or environmental or physiological condition. The emergence and evolution of RNA-Seq chemistries have changed the landscape and the pace of transcriptome research in life sciences over a decade. This chapter introduces RNA-Seq and surveys its recent food and agriculture applications, ranging from differential gene expression, variants calling and detection, allele-specific expression, alternative splicing, alternative polyadenylation site usage, microRNA profiling, circular RNAs, single-cell RNA-Seq, metatranscriptomics, and systems biology. A few popular RNA-Seq databases and analysis tools are also presented for each application. We began to witness the broader impacts of RNA-Seq in addressing complex biological questions in food and agriculture.
Part of the book: Applications of RNA-Seq in Biology and Medicine
Transcriptome Analysis Using RNA Sequencing for Finding Genes Related to Fiber in Cotton: A Review
The cotton crop is economically important and primarily grown for its fiber. Although the genus Gossypium consists of over 50 species, only four domesticated species produce spinnable fiber. However, the genes determine the molecular phenotype of fiber, and variation in their expression primarily contributes to associated phenotypic changes. Transcriptome analyses can elucidate the similarity or variation in gene expression (GE) among organisms at a given time or a circumstance. Even though several algorithms are available for analyzing such high-throughput data generated from RNA Sequencing (RNA-Seq), a reliable pipeline that includes a combination of tools such as an aligner for read mapping, an assembler for quantitating full-length transcripts, a differential gene expression (DGE) package for identifying differences in the transcripts across the samples, a gene ontology tool for assigning function, and enrichment and pathway mapping tools for finding interrelationships between genes based on their associated functions are needed. Therefore, this chapter first introduces the cotton crop, fiber phenotype, transcriptome, then discusses the basic RNA-Seq pipeline and later emphasizes various transcriptome analyses studies focused on genes associated with fiber quality and its attributes.
Part of the book: Cotton