Bioinformatics Section

生物信息学组

• 批准号: 10670780
• 负责人: Aleksandar Milosavljevic
• 金额: $ 51.01万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10670780
• 关键词: Animal Model; Back; Bioinformatics; Biological Assay; Clinical; Communities; Data; Disease model; Elements; Engineering; Evaluation; Genes; Genetic; Human; Informatics; Infrastructure; Internet; Knowledge; Laboratory Organism; Link; Modeling; Molecular; Multiomic Data; Phenotype; Process; Production; Publications; Qualifying; Reporting; Research Personnel; Resources; Role; Services; System; Technology; Testing; Variant; bioinformatics infrastructure; community engagement; data integration; data modeling; data portal; digital; experience; experimental study; fly; genetic manipulation; genetic variant; genome repository; genome sequencing; human disease; information model; insight; interest; model organism; pre-clinical; precision medicine; prospective; repository; screening; tool; variant of interest; web portal; web site

ABSTRACT Model organisms are invaluable for understanding the role of genes in human disease and will be key to assessing the impact of millions of specific genetic variants uncovered by high-throughput genome sequencing. The modeling of specific genetic variants is predicated on model organisms engineered using precisely targeted genetic manipulations, careful and accurate variant annotation, and precise phenotyping. The modeling will also require advanced informatics capabilities to integrate variant information across species, support variant nomination and assessment, track model production and associated experimental data via a LIMS system, and to disseminate the information and engage the community via a web portal. Variant information from model organisms may provide insight into the molecular mechanism underlying a phenotype of interest, inform the specific genetic targeting strategy, and influence choice of model organism. As variant annotation resources continue to add information and new resources come online, informatics workflows must be able to accommodate and incorporate them into the model production process. The Bioinformatics Section of the BCM Center for Precision Medicine Modeling will develop these informatics capabilities by leveraging our extensive experience in multi-omic data integration and coordination, cross-species phenotype matching via the MARRVEL system, extension of our KOMP2 LIMS system implementation, and by leveraging key elements of the ClinGen Resource, an FDA-recognized repository for genomic information that we co-developed. By linking human and model information within integrated workflows, the infrastructure will facilitate precision modeling in one direction, and in the other direction will feed model-derived information and knowledge back to the community. By integrating variant resources and providing mechanisms for variant evaluation and information sharing, the Pre- Clinical/Co-Clinical and Disease Modeling Unit will more efficiently develop and evaluate model organisms. Bioinformatics infrastructure will support the variant evaluation process through final variant selection and presentation to the Steering Committee.

抽象的 模型生物对于理解基因在人类疾病中的作用具有不可估量的价值，并且将是 评估高通量基因组测序发现的数百万个特定遗传变异的影响。 特定遗传变异的建模基于使用精确靶向设计的模型生物体 遗传操作、仔细准确的变异注释以及精确的表型分析。建模还将 需要先进的信息学能力来整合跨物种的变异信息，支持变异 提名和评估，通过 LIMS 系统跟踪模型生产和相关实验数据，以及 通过门户网站传播信息并吸引社区参与。模型的变体信息 生物体可以深入了解感兴趣的表型背后的分子机制，告知 特定的遗传靶向策略，并影响模式生物的选择。作为变体注释资源 不断添加信息和新资源上线，信息学工作流程必须能够 将它们容纳并纳入模型生产过程中。 BCM 生物信息学部分 精准医学建模中心将利用我们广泛的信息学能力来开发这些信息学能力 具有多组学数据集成和协调、通过 MARRVEL 进行跨物种表型匹配的经验 系统，我们的 KOMP2 LIMS 系统实施的扩展，并利用 ClinGen 的关键要素 Resource，我们共同开发的 FDA 认可的基因组信息存储库。通过连接人类和 集成工作流程中的模型信息，基础设施将促进一个方向的精确建模， 另一方面，将把模型衍生的信息和知识反馈给社区。经过 整合变异资源，提供变异评估和信息共享机制， 临床/联合临床和疾病建模单位将更有效地开发和评估模型生物体。 生物信息学基础设施将通过最终的变体选择和 向指导委员会介绍。