CAREER: Computational Infrastructure for Full-Sequence Association Studies with Pooled Individuals

该奖项是根据2009年《美国复苏和再投资法案》(Public Law 111-5)资助的。智力价值。允许人类遗传学获得罕见变异的高通量测序技术正在改变人类遗传学：几项颠覆性技术正在成熟，现在可以实现每美元百万碱基的再测序吞吐量。具体地说，现在可以在个体池中对数千个个体进行基因组目标区域的测序。这样揭示的常见和稀有等位基因的完整谱是了解我们物种的起源、基因组学和可遗传特征的关键资源。对一种可遗传性状与一种常见变异进行关联的幼稚测试不适合分析稀有基因变异，因为每一种这种罕见变异对该性状的贡献在统计上往往是无法检测到的。因此，找到相关基因的希望在于积累跨多个功能变体的关联信号。多变量关联问题因相邻变量之间的背景相关性而变得复杂.该方案解决了两个挑战：1.初始任务：从汇集的测序数据中恢复突变携带者的个体身份.2.主要任务：利用个体水平的突变数据对一个位点中的多个变异体的关联度进行评分.提出的解决方案：贝叶斯评分，可按个体和按变量分解.该方案包括设计重叠池以恢复突变携带者的身份.每个个体都将在一个独特的池组合中进行排序。在这样一组池中观察到的突变将被推断为由相应的个人携带，从而解决最初的任务。这一建议通过对包含功能变体的基因组区间进行贝叶斯评分来解决主要任务。比较基因组学被用来指导一个测序的变体是否可能具有功能的先验分布。关联分数被进一步分解为每个样本和每个位置的贡献，这些贡献之间沿基因组具有马尔可夫相关性。提出了一种优化因果轨迹边界的动态规划。影响广泛。该项目的成果将促进基因研究的新范式，以及最近推出的高通量实验技术。具体来说，预计的影响包括：-向研究社区传播软件工具和量身定做的界面。-通过实施拟议的研究任务的项目课程对本科生进行教育，通过课程开发和向高中多元化学生提供课程对K-12学生进行教育--使一代人能够广泛获得他们个人的DNA。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Intellectual Merit.High throughput sequencing that allows human genetics to access rare variation "Next Generation" sequencing is transforming human genetics: several disruptive technologies are coming of age and now enable resequencing throughput of megabases per dollar. Specifically, thousands of individuals can now be sequenced for targeted regions of the genome, in pools of individuals. The complete spectrum of common and rare alleles thus revealed is a key resource for understanding origins, genomics, and heritable traits of our species. Naïve tests of association of a heritable trait to a common variant are inappropriate for analysis of rare gene variants, since the contribution of each such rare variant to the trait is often statistically undetectable. The hope for finding an associated gene therefore lies in accumulating association signal across multiple functional variants. The problem of multiple-variant association is complicated by background correlations between nearby variants.This proposal tackles two challenges:1.Initial task: Recovery of individual identity of mutation carriers from pooled sequencing data2.Main task: Using individual-level mutation data for scoring of association to multiple variants in a locusProposed solution: Bayesian scoring, decomposable by individual and by variant.This proposal involves design of overlapping pools for recovering mutation carrier identity. Each individual will be sequenced in a unique combination of pools. Mutations observed in such a set of pools will be inferred to be carried by the corresponding individual, addressing the initial task. This proposal tackles the main task by Bayesian scoring for genomic intervals containing functional variants. Comparative genomics is used to guide a prior distribution for whether a sequenced variant is likely to be functional. The association score is further decomposed to contributions of each sample and each site, with Markovian dependency between such contributions along the genome. A dynamic-program is proposed for optimizing the causal locus boundaries.Broad Impact.The outcomes of the project would facilitate new paradigms in genetic research, alongside the recently launched high throughput experimental technologies. Specifically, projected impacts include:- software tools and tailored interfaces to be disseminated to the reseaerch community.- Education for undergraduates by project courses implementing proposed research tasks and for K-12 students by curriculum development and delivery to high-school diversity students- allowing a generation to have widespread access to their individual DNA.