Periodic Reporting for period 4 - PHOTONET-C4 (Characterising the Gene Regulatory Networks Governing Photosynthesis: From Basic Understanding to Targeted Engineering)
Okres sprawozdawczy: 2020-05-01 do 2021-10-31
Understanding and manipulating the gene regulatory network governing photosynthesis is one way in which engineer food and fuel crops for increased productivity. This may help contribute to future food security through enhanced sustainable agricultural production.
In addition to these biological discoveries, my group has also developed a number of software methods for comparative genomic analyses. To date, we have published 10 open source bioinformatic methods (and associated papers) for solving difficult problems in gene and genome analyses. These include methods for phylogenetic inference, gene family inference, orthology inference, transcriptome assembly, genome annotation, RNA splicing, estimating the strength of selection acting on genes, estimating protein/transcript abundance from codon usage bias, and gene expression/data clustering. Thus, in summary, we have initiated and led research programs that have resulted in significant discoveries in the regulation and evolution of photosynthesis and the development of novel algorithms for comparative genomics.
We have also provided new insight into the evolution of photosynthesis. Specifically, rubisco is the enzyme that makes the sugars that fuel life on earth. The enzyme is thought to be locked in evolutionary stasis by catalytic trade-offs which prevent evolutionary optimisation of its kinetics. We showed that this text-book paradigm was wrong, and that although there is evidence for weak catalytic trade-offs, rubisco adaptation has been more limited by phylogenetic constraint than by the combined action of all catalytic trade-offs. This discovery has revealed there is huge potential to engineer enhanced rubisco variants if the phylogenetic constraints on the enzyme can be circumvented.
We also developed the OrthoFInder comparative genomic method. This is a landmark method in comparative genomics that provides phylogenetic inference of orthologs, rooted gene trees, gene duplication events, the rooted species tree, and a wealth of comparative genomics statistics. This method is the first fully phylogenetic method for identifying orthologous genes from whole genome sequences, and is most accurate method currently available. This method has been cited ~3000 times, and it is the way in which the majority of comparative genomic studies published today identify orthologous genes. It also underpins dozens of genomics databases, and it has also become a key component of undergraduate and graduate teaching in bioinformatics at universities around the world.