Deep sequencing studies for cannabis and stimulant dependence

描述（由申请人提供）：本提案的目标是使用全基因组测序和基因型插补来确定影响兴奋剂和大麻依赖易感性的基因。越来越经济的全基因组测序的出现提供了新的机会，以确定未检测到的连锁或关联方法的性状相关的序列变异。然而，目前还不确定什么是鉴定性状相关基因座的最有效的分析方法。因此，我们建议研究四种不同的分析方法，以确定使用最先进的信息学基础设施在三个队列中影响兴奋剂和大麻依赖的序列变异。这三个研究队列被确定为使命印度研究（PI辛迪埃勒斯），合并耶鲁大学康涅狄格州成瘾研究样本（PI乔尔Gelernter）和旧金山弗朗西斯科家庭研究（PI柯克Wilhelmsen）的一部分。因为我们正在研究具有三个不同大陆起源的人群，我们将确定感兴趣的特征的主要遗传风险因素是共享的还是特定的。构成我们样本的三个群体中的两个（即，美洲原住民和非洲裔美国人）是研究不足。纳入这些队列将允许在不同的确定策略和种族组成的人群内和人群之间进行分析，允许在人群之间进行强有力的复制测试，并使确定和分析方法的直接比较成为可能，因为它们适用于成瘾的遗传研究。我们预计，用于这项研究的方法将不断发展。目前，我们计划使用四种互补的分析策略：1）使用>5X序列覆盖度检测基因型的常规SNP分析，以检测次要等位基因频率（MAF）大于0.1%的多态性; 2）基于基因的方法，以确定是否有比对照更多的病例具有可能影响给定基因功能的罕见序列变异（MAF<1%）; 3）对已知的和远缘的个体使用简化形式的仅受影响的连锁分析，以鉴定可能通过血统而共享相同的长染色体片段;以及4）更高水平的结构变异的扩展分析。DNA序列分析的技术和经济正在迅速发展。根据目前的成本，我们计划完成至少3000名受试者的>5X全基因组测序。我们决定采用低通基因组测序的关键是多点插补方法的发展。模拟分析表明，对于相同的成本，更多的受试者可以经历比外显子组测序多5倍的具有插补的全基因组测序，从而提供更多的外显子组数据以及基因组其余部分的丰富数据。这项研究的结果可以提供对其他滥用物质的遗传学的深入了解，这些物质可以通过与响应该RFA的其他项目和NIDA遗传学联盟的其他项目共享数据来证实。

DESCRIPTION (provided by applicant): The goal of this proposal is to identify genes that affect susceptibility to stimulant and cannabis dependence using whole genome sequencing with genotype imputation. The advent of increasingly economical whole genome sequencing provides new opportunities to identify trait-associated sequence variations not detected by linkage or association methods. It is not certain, however, what the most effective analytic method for identifying trait-related loci will be. Thus, we propose to study four distinct analytic approaches to identify sequence variants that affect stimulant and cannabis dependence in three cohorts using a state-of-the-art informatics infrastructure. The three study cohorts were ascertained as part of the Mission Indian Study (PI Cindy Ehlers), the combined Yale-University of Connecticut Addiction Study samples (PI Joel Gelernter) and the San Francisco Family Study (PI Kirk Wilhelmsen). Because we are studying populations with three different continental origins, we will ascertain whether the major genetic risk factors for the traits of interest are shared or population-specific. Two of the three populations that make up our sample (i.e., Native Americans and African Americans) are understudied. Inclusion of these cohorts will allow for analyses within and across populations that differ in ascertainment strategies and ethnic composition, permitting strong tests of replication across populations and enabling direct comparisons of ascertainment and analytic approaches as they apply to genetic studies of addiction. We expect that the approach used for this study will evolve. Currently we plan to use four complementary analytic strategies: 1) a conventional SNP analysis of genotypes detected using >5X sequence coverage for polymorphisms with minor allele frequency (MAF) greater than 0.1%; 2) a gene-based approach to determine whether more cases than controls have rare sequence variants (MAF<1%) likely to affect the function of a given gene; 3) use of a simplified form of affected-only linkage analysis of known and distantly related individuals to identify long chromosomal segments that are likely to be shared identical by descent; and 4) extended analysis of higher-level structural variation. The technology and economics of DNA sequence analysis is rapidly evolving. Based on current costs we plan to complete >5X whole genome sequencing of at least 3000 subjects. Critical to our decision to pursue low-pass genomic sequencing was the development of multipoint imputation methods. Simulation analysis indicates that for the same cost more subjects can undergo >5X whole genome sequencing with imputation than exomic sequencing, thus providing more exomic data as well as rich data for the rest of the genome. The findings from this study may provide insight into the genetics of other substances of abuse which can be confirmed by data sharing with other projects responding to this RFA and to other projects in the NIDA Genetics Consortium.