Mining Meadows: Biosynthesis and Bioactivity of Phytochemicals from UK Plants

Mining Meadows：英国植物植物化学物质的生物合成和生物活性

• 批准号: 2578291
• 金额: --
• 依托单位: University of East Anglia
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2578291
• 关键词: Mining; Meadows; Biosynthesis; Bioactivity; Phytochemicals

The process of domestication invariably leads to a loss of genetic diversity and a reduction in population size, leaving the animals more vulnerable to mutations. As these populations interbreed and mutations accumulate, they can cause disease, developmental disorders and infertility - making them ideal models for rare human disorders. Most studies focus on the ~2% of the genome encoding proteins, mainly due to the difficulty in identifying functional non-coding elements. This leaves aside the non-coding regions - sometimes called 'the dark genome' - which harbours functional regulatory sequences. The majority of disease- or trait-associated variants are present in these non-coding, often conserved, sequences.The aim of the project is to use a unique resource consisting of 252 mammal genomes, along with population data, to assess the extent by which population sizes have been reduced and deleterious mutations accumulated. The latest developments in machine learning will be applied to transfer models and information from highly-studied organisms (human, mouse) to genomes with scarce resources, identifying functional elements and predicting the impact of mutations within them.

驯化过程不可避免地导致遗传多样性的丧失和种群规模的减少，使动物更容易受到突变的影响。随着这些种群的杂交和突变的积累，它们可能导致疾病、发育障碍和不孕症——使它们成为罕见人类疾病的理想模型。大多数研究集中在编码蛋白质的约2%的基因组上，这主要是由于难以识别功能性非编码元件。这就不包括非编码区域——有时被称为“暗基因组”——它包含功能调控序列。大多数与疾病或性状相关的变异存在于这些非编码、通常保守的序列中。该项目的目的是利用由252种哺乳动物基因组组成的独特资源，以及种群数据，来评估种群规模减少和有害突变积累的程度。机器学习的最新发展将应用于将模型和信息从高度研究的生物体（人类，小鼠）转移到具有稀缺资源的基因组，识别功能元素并预测其中突变的影响。