Photosynthesis gene expression control
Most modern-day plants have evolved to use ~3000 genes to convert light, CO2 and water into sugars. These genes encode enzymes that catalyse the biochemical reactions as well as structural building blocks that are needed to make subcellular compartments where the light energy is captured and stored. This large cohort photosynthesis genes is dynamically regulated during plant development and in response to changing environmental conditions. We use a combination of bioinformatics and experimentation to discover how photosynthesis genes are coordinately regulated in grasses, how this regulation has evolved in different species, and use this knowledge to help engineer higher yielding crops for the future.
The evolution of C4 photosynthesis
With over 60 independent origins, C4 photosynthesis is one of the most remarkable examples of convergent evolution. Multiple studies have identified a large repertoire of genes that are differentially expressed between closely related C3 and C4 species, and within C4 species, thousands of genes have been implicated in biochemical and anatomical development. While the catalogue of genes that is associated with C4 biology continues to increase, the mechanisms that regulate C4-specific gene expression remain largely unknown. We are interested in identifying the gene expression regulators that control C4 gene expression and understanding how these regulators have evolved from their C3 ancestors. We hope that by understanding this we can help engineer advantageuos C4 traits into C3 plants.
The evolution of genes and genomes
Genomes are not just libraries of information they are dynamic storage-machines which temporally control access to information through a variety of different mechanisms. We are interested in the mechanisms of gene and genome evolution, and what that evolution can tell us about the biology of organisms.
Building better bioinformatic tools
We are interested in developing improved methods for both multiple sequence alignment, phylogenetic inference, genome annotation, orthologue detection, high throughput sequence analysis and anything else that helps us make better use of our data.