| Summary: | <p>The terrestrialisation of embryophytes was preceded by, and precipitated, the evolution of diverse metabolic capabilities to aid growth and survival on land. A broad understanding of metabolism across all land plants is important for the discovery of novel metabolic enzymes and pathways which may be used commercially and to design metabolic engineering strategies for crop improvement. However, metabolic research has mainly focused on a small number of angiosperm crops and model plants. The research described in this thesis was carried out with the goal of correcting this knowledge bias, using bioinformatic and computational techniques to characterise metabolism, and its associated evolutionary processes, in early-diverging land plants.</p>
<p>The work is presented as three manuscripts. In the first I used metabolic modelling to investigate central metabolic fluxes in the liverwort Marchantia polymorpha, which exhibits extremely low carbon assimilation rates as a consequence of the low mesophyll conductance characteristic of bryophytes. I found that my constrained stoichiometric model of Marchantia was unable to achieve experimentally-defined growth rates without increasing carbon conversion efficiency by requiring either a very low cell maintenance cost, or some form of nocturnal carbon recycling. In the second manuscript I carried out a comparative analysis of secondary metabolism across the Chloroplastida, using homologous relationships between metabolic genes in 72 land plants and algae. The findings, supported by gene absences/presences in a further 305 plant and algal transcriptomes, elucidate details of the evolution of several phytohormone and biopolymer biosynthetic pathways. Finally, I used phylogenetic profiling and co-expression analysis to identify candidate genes associated with the previously discussed biosynthetic pathways. The results were validated by the identification of several known gene associations, and additional genes with various potential functional relationships with the pathways in question were detected.</p>
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