Estimating the impact of genetic variants on the brain in space and time

估计遗传变异对大脑在空间和时间上的影响

• 批准号: 8798957
• 负责人: Jacob James Michaelson
• 金额: $ 38.8万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2017-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8798957
• 关键词: Accounting; Address; Affect; Alleles; Autistic Disorder; Binding; Bioinformatics; Bipolar Disorder; Brain; Chromatin; Clinic; Clinical; Code; Computational algorithm; Computing Methodologies; Data; Data Set; Development; Diagnosis; Disease; Foundations; Gene Cluster; Gene Expression; Gene Expression Profile; Genes; Genetic; Genetic Variation; Genome; Genomics; Goals; Human; Human Genome; Human Genome Project; Individual; Learning; Light; Measures; Medical; Methods; Modeling; Molecular; Mutation; Neurologic; Open Reading Frames; Other Genetics; Phenotype; Play; Potassium Hydroxide; Probability; Proteins; Reading; Reporting; Research; Resources; Risk; Role; Scientist; Shapes; Specificity; Staging; Sum; System; Time; Tissues; Training; Untranslated RNA; Variant; Weight; base; brain tissue; case control; cost; epigenomics; exome; experience; falls; genetic variant; genome sequencing; genome-wide; improved; insight; loss of function; model building; neuropsychiatry; novel; promoter; psychogenetics; public health relevance; research study; spatiotemporal; tool; trait; transcription factor

DESCRIPTION (provided by applicant): In the years since the completion of the human genome project, our ability to read the genome has improved tremendously. Frustratingly, our ability to interpret and comprehend what we can now easily read has lagged behind. Genetic variants that lie outside protein-coding regions are particularly challenging to interpret because the rules that govern their regulatory function are far less understood than the principles of protein- coding sequence. Addressing this challenge is particularly urgent because the drastic fall in whole genome sequencing costs will bring with it a wave of newly discovered non-coding and potentially causal variants. The recent completion of several genome-scale projects, and the release of pilot data from new and ongoing projects, have made it possible to begin building models whose goal is to predict the function of non-coding genetic variation. We propose the development of a brain-centric variant annotation framework that integrates temporal and spatial expression information from existing data sets, regulatory relationships established by eQTL studies, and chromatin state information uncovered by ENCODE and other studies, with the aim of providing, for any arbitrary input variant, an estimate of the magnitude of the effect, the systems or tissues most likely affected by the variant, and the stage of development at which the variant is most likely to produce a phenotype. Models will be trained on variants from whole genome sequencing studies of diagnosed and undiagnosed individuals. Development of this framework will proceed in three stages: 1) the above lines of genomic evidence will be combined with other features as predictors of enrichment for variants identified in individuals with diagnosed neuropsychiatric conditions, producing a score indicative of the variant's phenotype-shaping potential; 2) spatiotemporal gene expression matrices will be integrated to provide estimates of the tissues and time points most likely affected by variation at the non- coding query locus; 3) by combining the estimates produced in stages 1 and 2, we will create a single weighted context matrix that represents the individual's aggregate regulatory variant burden in space (i.e. brain tissue/region) and time. The framework will be demonstrated on previously unpublished variants in autism and bipolar disorder. The proposed framework would to our knowledge be the first non-coding variant annotation system that focuses on the effect on the brain, and is able to guide the user as to when and where the effects of potentially functional variants are likely to emerge in an individual. A further novel aspect of the proposed system is that it will provide an integrated estimate of the overall burden context for an individual in spac and time. The proposed project will provide a valuable resource for scientists performing research in the genomics of psychiatric and neurological conditions. Perhaps more importantly, the lessons learned in the course of this project will provide the foundation for developing tools that may one day make interpreting non-coding variation in the clinic a reality.

描述（由申请人提供）：在人类基因组项目完成以来的几年中，我们阅读基因组的能力得到了极大的提高。令人沮丧的是，我们解释和理解我们现在可以轻松阅读的内容的能力落后了。位于蛋白质编码区域之外的遗传变异对于解释特别具有挑战性，因为控制其调节功能的规则比蛋白质编码序列的原理知之甚少。解决这一挑战尤其紧迫，因为整个基因组测序成本的急剧下降将带来一波新发现的非编码和潜在的因果变体。最近完成了几个基因组规模项目，以及从新项目和正在进行的项目中释放飞行员数据的过程，使得开始建立模型，其目标是预测非编码遗传变异的功能。我们提出了一个以大脑为中心的变体注释框架的开发，该框架从现有数据集，EQTL研究建立的监管关系以及编码和其他研究发现的染色质状态信息中整合了时间和空间表达信息，以提供任何，旨在为任何任何提供任何信息。任意输入变体，对效应的大小，最有可能受变体影响的系统或组织的估计，以及该变体最有可能产生表型的发育阶段。模型将接受对诊断和未诊断个体的整个基因组测序研究的变体培训。该框架的开发将分为三个阶段：1）上述基因组证据线将与其他特征相结合，作为在具有诊断为神经精神疾病的个体中鉴定出的变体的富集的预测指标，从而产生了该变体的表型成形势的分数； 2）将整合时空基因表达矩阵，以提供组织和时间点的估计，最有可能受到非编码查询基因座变化影响的时间点； 3）通过结合第1阶段和第2阶段产生的估计值，我们将创建一个单个加权上下文矩阵，该矩阵代表个人在空间（即脑组织/区域）和时间的总调节变异负担。该框架将在自闭症和双相情感障碍的先前未发表的变体上证明。据我们所知，拟议的框架将是第一个侧重于对大脑影响的非编码变体注释系统，并能够指导用户何时何地 变体可能会在一个个体中出现。提出的系统的另一个新颖方面是，它将为SPAC和时间中个人的整体负担背景提供综合估计。拟议的项目将为从事精神病和​​神经系统疾病基因组学研究的科学家提供宝贵的资源。也许更重要的是，在该项目过程中所学到的经验教训将为开发工具提供基础，这些工具有一天可能使诊所中的非编码变化成为现实。