Towards full sequence design of functional chromosomes by AI

通过人工智能实现功能染色体的全序列设计

• 批准号: 2898853
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2898853
• 关键词: Towards; full; sequence; design; functional

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

目前合成基因组学的进展意味着我们设计和构建DNA的规模正在迅速增加。与此同时，支持人工智能的工具正在加速我们设计基因编码部件以达到所需规格的能力。因此，合乎逻辑的是，我们应该期待“未来的生物设计师”使用人工智能来帮助编写定制的DNA序列，这些序列可以组装成完整的染色体和基因组，从而驱动细胞执行所需的任务。在这个项目中，我们计划看看我们已经离人工智能主导的合成酵母染色体全序列设计有多近。在设计、构建和测试酵母染色体的人工智能编写区域的过程中，我们将了解目前缺失的基因组知识和人工智能设计能力，这些知识和能力将使未来十年的定制染色体设计成为可能。我们计划开发解决这些目前差距的方案，以便在项目结束时，我们可以使用人工智能生成合成染色体臂的完整序列，只向人工智能提供要包含的基因列表，这些基因的肽序列，它们的目标表达水平以及它们所需的任何调节。该项目将利用我们两个研究小组在酵母中构建和测试合成染色体区域（Ellis）以及设计用于工程生物学的人工智能驱动工具（Stan）方面的现有工作。重要的是，它将建立在现有成功的关键人工智能工具的基础上，这些工具使用egans和cnn来编写合成酵母启动子[1]，5'UTRs[2]和3' utrs[3]。这三个遗传部分加起来占酵母染色体非编码DNA的85%