在农业科学大数据时代,基因型和表型数据的标准化,利用和整合
Cecilia H Deng1, Sushma Naithani2, Sunita Kumari3
1Molecular and Digital Breeding, New Cultivar Innovation, The New Zealand Institute for Plant and Food Research Limited, 120 Mt Albert Road, Auckland 1025, New Zealand.
Database : the journal of biological databases and curation
|December 11, 2023
概括
整合大规模的基因型和表型数据对于作物改进至关重要. 基因型-表型工作组确定了关键挑战,并建议基础设施,标准,生物保养和工具,以便在植物基因组学中更好地利用数据.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 农业科学 农业科学
背景情况:
- 大规模的基因型和表型数据对于遗传标记物识别,基因功能研究和农业中的基因组选择至关重要.
- 整合异质数据源的基因型和表型信息带来了重大挑战,限制了作物育种和可持续性的有效利用.
研究的目的:
- 在植物基因组研究社区内审查当前的数据类型和资源,以存档,分析和可视化植物基因组和表型数据.
- 确定研究人员在管理和整合大规模基因组和表型数据集时所面临的需求和挑战.
主要方法:
- 在AgBioData联盟下建立了基因型-表型工作组.
- 识别了各种数据集并检查了元数据注释 (实验设计,方法,样本采集).
- 审查了公共资助的存储库,二级数据库和数据集成能力的知识库.
主要成果:
- 确定了各种数据类型,并评估了基因型和表型信息的元数据完整性.
- 评估现有的存储库和数据库,以评估它们整合异质数据的能力.
- 强调需要改善基础设施,社区标准,生物保护资源和分析工具.
结论:
- 建议加强对新数据类型的基础设施支持,并制定有关数据注释和格式化的社区标准.
- 强调需要生物保养资源和先进的分析/可视化工具来连接基因型和表型数据.
- 建议解决这些需求将增强知识合成,促进植物基因组学的翻译性研究,与动物研究的潜在并行.
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