Drug Discovery
Herbal healing, mining plant genomes
Mining Plant Genomes - A modern approach to herbal healing

Mining Plant Genomes - A modern approach to herbal healing

By Michelle Vierra
Spring 2019

Plants are stationary soldiers. Rooted to one spot, they are not able to chase nutrients or flee from herbivores and pathogens. So in addition to the basic metabolites they synthesise for their survival, they produce a diverse array of organic compounds through specialised biochemical pathways to counterattack threats.

Some of these compounds have been found to combat human threats as well, and herbalists have been scouring these palettes of secondary metabolites for their health-promoting properties for centuries.

Modern medicine also incorporates plant compounds. Around 80% of the world’s population already relies on ethnobotanical remedies and plant drugs, such as the antineoplastic Taxol, the antimalarial artemisinin, the analgesic codeine, the antidiabetic allicin, and the cardiac depressant quinidine.

The high cost of new drugs, unpalatable side-effects and microbial resistance are driving a constant and renewed public interest on alternative and complementary medicine. Yet only a small fraction of the vast diversity of plant metabolism has been explored.

This is quickly changing, as synthetic biologists set out to mine the quarry of alkaloids, terpenoids and phenolic plant compounds in order to manufacture new natural products and molecular ‘pharmers’ try to identify ways to use the plants themselves as biopharmaceutical factories.

The increased affordability and sophistication of genetic sequencing technology is making all of this possible. But is it being used to its full potential? How can the technology be best utilised in drug discovery and development?

It is no longer enough to simply sequence bits of a genome. In order to understand the full metabolic potential of plants, comprehensive genomic information must be combined with transcriptomic, proteomic and metabolomic data. We need to be able to answer questions such as: How are the genes coded? Where are they clustered? Clustered genes in Arabidopsis, for example, are enriched in phenylpropanoid and terpenoid metabolism. Gene duplication, such as whole-genome duplications (WGDs) and local (tandem) duplication (LDs), can also play an important role in specialised metabolism, including the expression of flavonoid related genes.

Fortunately, sequencing technology has evolved to equip researchers with the tools to tackle nearly all of these questions.

Single Molecule, Real-Time (SMRT) Sequencing, which works like a giant microscope that can literally ‘see’ DNA synthesis in real time, enables researchers to assemble highly contiguous and accurate megabase-size stretches, or contigs, of plant genomes. These ‘long reads’ capture undetected structural variations, fully intact genes and regulatory regions embedded in complex structures that fragmented draft genomes often miss.

Most genome-wide knowledge is obtained at the level of gene expression (ie, variations in mRNA quantity). It is often assumed that each individual gene transcribes identical RNA molecules. But in reality, one gene may produce several different isoforms by the use of alternative promoters, exons and terminators. During transcription, alternative RNA molecules (ie, isoforms) are often produced. They can vary in length and differ markedly in function and expression pattern. Alternatively, spliced multiple transcript isoforms can dramatically increase the protein-coding potential of the genome. And spliced isoforms transcribed from the same gene can have significantly different and even antagonistic effects.

As such, accurately capturing isoform activity can be crucial to understanding gene structure, regulatory elements and coding regions. And covering the entire length of cDNA sequences and transcripts can even enable the discovery of new genes.

Enter the isoform sequence (Iso-Seq) method, which uses long-read technology and requires no assembly, making it an increasingly popular tool – especially in the absence of reference genomes, which is a reality for many researchers working on non-model organisms and plants with genomes that are large and complex.

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