Bioinformatics Section

摘要 模式生物对于理解基因在人类疾病中的作用是无价的，也将是 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。 对特定遗传变异的建模是基于使用精确靶向技术设计的生物模型 基因操作，仔细和准确的变异注释，以及精确的表型。建模还将 需要高级信息学功能来集成跨物种的变异信息，支持变异 提名和评估，通过LIMS系统跟踪模型制作和相关实验数据，以及 通过门户网站传播信息并让社区参与进来。模型中的变量信息 生物体可以提供对潜在的感兴趣表型的分子机制的洞察，告知 特定的基因打靶策略，并影响模式生物的选择。作为变体注解资源 继续添加信息和新资源上线时，信息学工作流必须能够 适应并将它们纳入模型生产过程中。BCM生物信息学分会 精确医学建模中心将通过利用我们广泛的 有通过MARRVEL进行多组数据集成和协调、跨物种表型匹配的经验 系统，我们的KOMP2 LIMS系统实施的扩展，并通过利用Clingen的关键元素 一个FDA认可的基因组信息库，我们共同开发的。通过将人类和 集成工作流中的模型信息，基础设施将促进单向的精确建模， 而在另一个方向，将把模型衍生的信息和知识反馈给社区。通过 整合不同资源，提供不同评估和信息共享机制， 临床/联合临床和疾病模型股将更有效地开发和评估模型生物。 生物信息学基础设施将通过最终的变种选择和 向指导委员会提交的报告。

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.