Periodic Reporting for period 4 - PHOTONET-C4 (Characterising the Gene Regulatory Networks Governing Photosynthesis: From Basic Understanding to Targeted Engineering) Reporting period: 2020-05-01 to 2021-10-31 Summary of the context and overall objectives of the project Photosynthesis is the primary energy source for life on earth. While the biochemistry and cell biology of photosynthesis are well understood, little is known of how the genes that mediate photosynthesis are regulated. Our research aims to address this knowledge gap by identifying the molecular regulators and mechanisms that control the expression of photosynthesis genes in the world’s most important food crops, the grasses. This work combines comparative genomics, evolutionary biology, high-throughput assays and genetic engineering.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. Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far Our work on photosynthesis focused on how it is regulated. In addition to key discoveries in the regulation and evolution of photosynthesis. My group also made significant discoveries in how the photosynthetic machinery has evolved since plants colonised the land, discovering new links between metabolism and genome evolution, discovering key evolutionary changes that occurred in plants that conduct highly efficient forms of photosynthesis such as C4 photosynthesis. We also integrated much of this insight to discover why the chloroplast genome shrank following endosymbiosis. 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. Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far) We have made major discoveries that go beyond the state of the art and expected results. For example we have provided major new insight into the drivers or organellar genome evolution. The endosymbiosis of the mitochondrion and the chloroplast are landmark events in the evolution of life on Earth. Following these endosymbioses there was a dramatic reduction in the gene content of the endosymbiont genomes such that they harbor fewer than 5% of the genes found in their free-living bacterial relatives. For decades it has remained a mystery why this process of gene loss and gene transfer occurs. In this work I provide the answer to this longstanding question and discover that it is more energetically efficient for the cell to encode organellar genes in the nucleus and import the requisite organellar proteins. This is a major advance in our understanding of dirving forces that have shaped the evolution of eukaryotic cytoplasmic genomes. 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. Light signalling networks
