Deep sequencing studies for cannabis and stimulant dependence

描述(由申请人提供)：这项提案的目标是利用全基因组测序和基因归因来识别影响对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为识别连锁或关联方法没有检测到的与特征相关的序列变异提供了新的机会。然而，目前还不能确定识别性状相关基因的最有效的分析方法是什么。因此，我们建议研究四种不同的分析方法，以识别影响兴奋剂和大麻依赖的三个队列中的序列变量，使用最先进的信息学基础设施。这三个研究队列被确定为印度使命研究(Pi Cindy Ehler)、耶鲁-康涅狄格大学成瘾研究样本(Pi Joel Gelernter)和旧金山家庭研究(Pi Kirk Wilhelmsen)的一部分。由于我们正在研究来自三个不同大陆的人群，我们将确定感兴趣的性状的主要遗传风险因素是共同的还是特定于人群的。组成我们样本的三个群体中的两个(即美洲原住民和非裔美国人)没有得到充分的研究。纳入这些队列将允许在人群内和人群之间进行分析，这些分析在确定策略和种族构成方面存在差异，允许对人群之间的复制进行强有力的测试，并能够直接比较应用于成瘾遗传研究的确定和分析方法。我们期望这项研究所采用的方法会有所发展。目前，我们计划使用四种互补的分析策略：1)对使用&gt检测到的基因型进行常规的SNP分析；5)对微小等位基因频率(MAF)大于0.1%的多态进行5X序列覆盖；2)基于基因的方法，确定是否有比对照更多的病例具有可能影响特定基因功能的罕见序列变异(MAF&lt；1%)；3)使用简化形式的仅受影响的已知和远亲个体的连锁分析，以确定可能因血统而共享相同的长染色体片段；以及4)更高水平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5倍全基因组测序。我们决定追求低通基因组测序的关键是多点归因法的发展。模拟分析表明，在相同的成本下，与外显子测序相比，更多的受试者可以进行&gt；5X全基因组测序，从而为其余基因组提供更多的外显子数据和丰富的数据。这项研究的发现可能提供对其他滥用物质的遗传学的洞察，这可以通过与响应该RFA的其他项目以及NIDA遗传学联合会的其他项目的数据共享来证实。

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.