Introduction to RNA Sequencing in Food and Agriculture

With its advantages of high throughput and low cost, NGS has now enabled sufficient depth of sequencing for the comprehensive study of the entire transcriptome. This method, known as RNA-Seq (RNA sequencing), has several advantages over other approaches and is quickly becoming the most popular method for analyzing the transcriptome of eukaryotes. RNA-Seq also allows for a much more precise measurement of transcript levels and isoforms than other methods. RNA-Seq provides new methods for food and agricultural research.

Under infection with the cassava brown streak virus (CBSV), RNA sequencing was used to identify 700 uniquely overexpressed genes in the cassava brown streak disease (CBSD) resistant variety. Despite the fact that none of the overexpressed genes had known resistant gene orthologs, some of them belonged to hormone signaling pathways and secondary metabolites, both of which are linked to plant resistance. Correspondingly, researchers looked at the transcriptomes of vulnerable and tolerant cassava landraces contaminated with the South African cassava mosaic virus. They discovered that susceptibility was mediated by transcriptome repression rather than induction and that many R-gene homologs were repressed in susceptible individuals throughout infection.

NGS was used in another research to look into the role of miRNAs in plant growth and starch biosynthesis. Furthermore, an RNA-seq-based transcriptome disclosed rice genes associated with the Striga resistance signaling pathway, which may shed light on the method of resistance in other African crops susceptible to Striga. NGS was also used to clone a mutant gene in maize using a modified bulk segregant RNA-seq (BSR-seq) method.

RNA Sequencing in Food Crops Production

Global warming and the demand for food from an ever-increasing global population are important issues that are attracting a lot of attention around the world. The research of the links between gene function and agricultural traits in food crops is particularly interesting in this regard. Transcriptomic analysis of crops uncovers the expressed genes that regulate essential traits and gives valuable information about how the genome responds to cellular perturbations. Furthermore, the identification of novel transcripts and the detection of differential transcription patterns at particular stages of development or situations lays the groundwork for understanding the molecular mechanisms underpinning the production of proteins and metabolites pertinent to food science (e.g., bioactive compounds and nutrients). These findings point to new ways to manipulate gene expression in order to increase or decrease the accumulation of the compounds of interest.

Detection of Foodborne Pathogenic Microorganisms Using RNA Sequencing

One of the primary objectives of the food industry is to produce safe foods of the desired quality with minimal processing. When food is contaminated with harmful species, it causes foodborne disease, also known as food poisoning. In this field, RNA-Seq has a lot of promise for studying the activities of foodborne microorganisms in the lab, in industrial settings, and in food products under very strict conditions. RNA-Seq techniques have been used less frequently to investigate foodborne pathogens than to investigate food crops, despite their great potential. Enrichment for all transcripts other than the abundant rRNA and tRNA species in RNA samples can be difficult, particularly for bacterial transcriptomes that lack mRNAs with poly(A) tails. Depletion of 16S and 23S rRNA from total RNA fraction isolated from microbial cells is a common solution to this problem.

References:

1. Jagadeesan B, Gerner-Smidt P, Allard MW, et al. The use of next generation sequencing for improving food safety: Translation into practice. Food microbiology. 2019 Jun 1;79.
2. Gedil M, Ferguson M, Girma G, et al. Perspectives on the application of next-generation sequencing to the improvement of Africa's staple food crops. InNext Generation Sequencing–Advances, Applications and Challenges. 2016 Jan 14.