HIGH RESOLUTION ALLELE SPECIFIC EXPRESSION ASSAYS

高分辨率等位基因特异性表达检测

• 批准号: 9067438
• 负责人: Jin Billy Li
• 金额: $ 30.43万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-22 至 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9067438
• 关键词: Address; Alleles; Allelic Imbalance; Architecture; Biological Assay; Biology; Cells; Code; Collection; Data; Data Analyses; Data Collection; Disease; Exhibits; Frequencies; Future; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Variation; Genetic study; Genome; Genotype; Genotype-Tissue Expression Project; Goals; Gold; Health; Human; Imagery; Individual; Investigation; Investments; Joints; Link; Maps; Metadata; Methods; Microfluidics; Modeling; Molecular; Nonsense-Mediated Decay; Pattern; Penetrance; Population; Positioning Attribute; Process; Proteins; Quality Control; Quantitative Trait Loci; RNA; Regulator Genes; Reporting; Resolution; Resources; Sampling; Specificity; Statistical Data Interpretation; Statistical Methods; Statistical Models; System; Testing; Tissues; Triage; Validation; Variant; Work; base; cost; deep sequencing; exome; exome sequencing; genetic regulatory protein; genome sequencing; improved; insight; loss of function; novel strategies; research study; symposium; trait; transcriptome; transcriptome sequencing; working group

DESCRIPTION (provided by applicant): Genetic studies of gene expression have provided important insight into the architecture of gene regulation and gene regulatory networks as well as new opportunities to identify molecular mechanisms underlying diverse traits. At the moment, this experimental system enables us to identify regulatory variants and model the functional spectrum of human variation. Furthermore, such studies have been fundamental to current insight into the tissue-specific context of genetic effects. The Genotype-Tissue Expression (GTEx) project is now proposing considerable future effort to characterize the tissue-specificity of genetic effects on gene expression; by 2016, GTEx proposes to collect 20,000 tissue transcriptomes from nearly 900 individuals. Essential to maximizing this investment and developing a gold-standard resource, will be application of experimental methods which can validate discoveries particularly expression quantitative trait loci (eQTL). One such method for validating eQTL are tests of allele-specific expression (ASE); Unlike genotypic association with drives eQTL discovery, allelic tests implicate the presence of a cis-linked regulatory variant within an individual and are independent of the population frequency of a causal variant. However, a limitation of ASE data from RNA-Seq is that they can be biased by differences in sampling depths due to changes in expression level across genes; a challenge that is exacerbated in multi-tissue studies. To address this, we have developed and refined an assay which combines established methods of microfluidics-based multiplex PCR and deep sequencing (mmPCR-Seq) to provide deep and high-throughput resolution of allele-specific expression (ASE). This approach provides a high-throughput, efficient and low-cost solution for obtaining ASE data (<9 minutes and <$50 per sample) and we have demonstrated that mmPCR-Seq works effectively on RNA with low quantity (10ng) and low quality (RIN=2.8). In this project, we aim to apply this approach to the validation of 800 tissue- specific and shared eQTL genes across at least 20-30 tissues in 96 individuals. Furthermore, we validate patterns of ASE for rare deleterious and loss-of-function variation across at least 30 tissues in 50 individuals. This data will be quality-controlled and regularly released to the GTEX Statistical Analysis Working Group and larger GTEx Consortia. We expect that this data will aid discovery and validation of eQTL particularly in tissues with low or intermediate expression and for shared eQTL which may exhibit as weaker effects in some tissues. Furthermore, this data will enable sensitive tissue-based interpretation of deleterious and LoF variation with the goal of improving our ability to understand systemic patterns which may underlie variable penetrance and disease expressivity as well as novel approaches to triage presumably pathogenic variants from personal exomes and genomes. As studies of the tissue context of genetic variation have been and are principally driven by genetic studies of gene expression, application of mmPCR-Seq to the validation of eQTL and patterns of ASE is an essential step towards developing high-quality maps of regulatory variation.

描述（由申请人提供）：基因表达的遗传学研究为基因调控和基因调控网络的架构提供了重要的见解，并为识别不同性状背后的分子机制提供了新的机会。目前，这个实验系统使我们能够识别调控变异并对人类变异的功能谱进行建模。此外，此类研究对于当前了解遗传效应的组织特异性背景至关重要。基因型-组织表达（GTEx）项目现在提出了未来相当大的努力来表征遗传对基因表达影响的组织特异性； GTEx 计划到 2016 年从近 900 人身上收集 20,000 个组织转录组。要最大化这项投资并开发黄金标准资源，至关重要的是应用实验方法来验证发现，特别是表达数量性状基因座（eQTL）。验证 eQTL 的一种方法是等位基因特异性表达 (ASE) 测试；与驱动 eQTL 发现的基因型关联不同，等位基因测试表明个体内存在顺式连锁调节变异，并且与因果变异的群体频率无关。然而，RNA-Seq ASE 数据的局限性在于，由于基因表达水平的变化，它们可能会因采样深度的差异而产生偏差；在多组织研究中这一挑战更加严重。为了解决这个问题，我们开发并改进了一种检测方法，结合了基于微流体的多重 PCR 和深度测序 (mmPCR-Seq) 的既定方法，以提供等位基因特异性表达 (ASE) 的深度和高通量分辨率。这种方法为获取 ASE 数据提供了高通量、高效且低成本的解决方案（<9 分钟且每个样本 <50 美元），并且我们已经证明 mmPCR-Seq 对低数量 (10ng) 和低质量 (RIN=2.8) 的 RNA 有效。在这个项目中，我们的目标是应用这种方法来验证 96 个人至少 20-30 个组织中的 800 个组织特异性和共享的 eQTL 基因。此外，我们还验证了 50 个人的至少 30 个组织中罕见的有害和功能丧失变异的 ASE 模式。这些数据将受到质量控制，并定期发布给 GTEX 统计分析工作组和更大的 GTEx 联盟。我们期望这些数据将有助于 eQTL 的发现和验证，特别是在低或中等表达的组织中，以及在某些组织中可能表现出较弱作用的共享 eQTL。此外，这些数据将使基于组织的有害变异和LoF变异的敏感解释成为可能，目的是提高我们理解可能构成可变外显率和疾病表达性的系统模式的能力，以及从个人外显子组和基因组中对可能致病变异进行分类的新方法。由于遗传变异组织背景的研究主要是由基因表达的遗传研究驱动的，因此应用 mmPCR-Seq 来验证 eQTL 和 ASE 模式是开发高质量调控变异图谱的重要一步。