Towards full sequence design of functional chromosomes by AI

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Current progress in synthetic genomics means that the scale at which we design and build DNA israpidly increasing. In parallel, AI-enabled tools are accelerating our capabilities to designgenetically-encoded parts to achieve desired specifications. It is logical, therefore, that we shouldexpect the 'biodesigner of the future' to be using AI to help write custom DNA sequences that canbe assembled to build whole chromosomes and genomes that drive cells to perform desired tasks.In this project, we plan to see how close we already are to AI-led full sequence design of asynthetic yeast chromosome. In designing, building and testing AI-written regions of yeastchromosomes, we will learn what genomic knowledge and AI design capabilities are currentlymissing that would enable bespoke chromosome design in the next decade. We plan to developsolutions to these current gaps, so that by the end of the project we can use AI to generate the fullsequence of a synthetic chromosome arm, providing the AI with only a list of genes to be included,the peptide sequences of these, their target expression levels and any regulation they require.The project will leverage existing work in our two research groups on building and testingsynthetic chromosome regions in yeast (Ellis), and in designing AI-driven tools for engineeringbiology (Stan). Importantly, it will build on the existing success of key published AI tools that useGANs and CNNs to write synthetic yeast promoters [1], 5'UTRs [2] and 3'UTRs [3] to specification.These 3 genetic parts together account for >85% of non-coding DNA in a yeast chromosome