Big Data Infrastructure for Crop Genomics

测序技术和计算工具的最新进展使得对世界上一些最重要的作物物种（如水稻、大麦、油菜籽、玉米、大豆和小麦）的基因组进行测序成为可能。这些作物构成了世界上大多数人口每日食物摄入量的很大一部分，在培育更有效和更有营养的品种方面的任何改进都将对确保全球粮食安全产生直接影响。虽然获得这些作物的基因组序列为深入了解物种之间的差异提供了非常有用的资源，但通过对来自相同或密切相关物种的不同个体进行测序，使我们能够识别出在植物育种过程中可以选择的有用遗传变异。这些方法需要结合序列和表型数据，再加上分析工具。我们建议开发一个作物生物信息学平台，使用户能够访问这种遗传和表型变异，并进行分析，以探索基因表达以及遗传变异与性状之间的关联。该平台将采用开源原则和公开数据开发。人口范围内的遗传变异将在基因组数据结构中表示；将开发用于存储植物表型数据的归档系统；将实施允许查询这些数据集和分析将基因型与表型联系起来的工具；该平台可以通过TGAC和EBI服务器访问，也可以打包成虚拟机，方便用户在本地硬件上安装。这个新颖的作物生物信息学平台将促进与产业界、研究界和学术界的研发小组合作的机会。公共资助资源产生的数据的可用性，以及随之而来的新的生产质量工具的开发，将降低信息作物科学的障碍，刺激新的研究和应用机会。该平台还将通过围绕生物技术和农业食品开发替代职业道路，为传统上专注于生物医学应用的英国生物信息学社区开辟新的机会。

Recent advances in sequencing technologies and computational tools have made it possible to sequence the genomes of some of the world's most important crop species, such as rice, barley, rapeseed, maize, soya and wheat. These crops constitute a substantial part of the daily food intake for most of the population of the world and any improvements in the breeding for more efficient and nutritious varieties will have a direct impact on ensuring global food security. Whilst obtaining the genome sequences for these crops provides a hugely useful resource for giving insights into the differences between species, it is through sequencing different individuals from the same or closely-related species which allows us to identify useful genetic variants which can be selected for during plant breeding. These approaches require a combination of sequence and phenotypic data, plus analysis tools. We propose to develop a crop bioinformatics platform which enables users to access this genetic and phenotypic variation and perform analyses to explore gene expression and associations between genetic variation and traits. The platform will be developed using open source principles and publicly available data. Population-wide genetic variants will be represented on a genomic data structure; an archiving system for storing plant phenotype data will be developed; tools to allow the querying of these datasets and analyses to link genotype to phenotype will be implemented; and the platform will be accessible via TGAC and EBI servers but also packaged into a virtual machine for easy installation on users' local hardware. This novel platform for crop bioinformatics will promote opportunities for collaborative work with R&D groups in industry, research and academia. The availability of data generated by publicly funded resources, and the concomitant development of new, production-quality tools will lower the barriers to information-enabled crop science, stimulating new opportunities for research and application. The platform will also open up new opportunities for the UK bioinformatics community, traditionally focused on biomedical applications, by developing alternative career paths around biotechnology and agri-food.