Characterization of Normal Genomic Variability

正常基因组变异的表征

• 批准号: 7732357
• 负责人: Andrew Singleton
• 金额: $ 65.77万
• 依托单位: NATIONAL INSTITUTE ON AGING
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7732357
• 关键词: Address; Affect; Africa; Base Pairing; Biological; Brain; Brain region; Cataloging; Catalogs; Cerebellum; Communicable Diseases; Complex; DNA; DNA Methylation; Data; Data Analyses; Data Set; Development; Disease; Foundations; Founder Effect; Gene Expression; Genetic; Genetic Polymorphism; Genetic Research; Genetic Transcription; Genetic Variation; Genome; Genomics; Genotype; Goals; Haplotypes; Human; Human Genetics; Human Resources; Individual; Linkage Disequilibrium; Measures; Methylation; MicroRNAs; Modification; Nature; Numbers; Pathway interactions; Pattern; Phase; Poly(A)+ RNA; Pontine structure; Population; RNA; Regulation; Sampling; Single Nucleotide Polymorphism; Site; Structure; Techniques; Temporal Lobe; Thinking; Tissues; Transcript; Variant; Work; base; brain tissue; design; genetic variant; human population genetics; interest; mRNA Expression; nervous system disorder; research study; response; trait

We have performed two separate but complementary sets of experiments in the last period; the first to understand the scope and distribution of genomic variability on worldwide human populations; the second, to characterize the effects of such variability in human brain on expression of mRNA and miRNA in addition to CpG methylation. Using more than 500 samples from 31 distinct worldwide human populations we performed very dense genome wide single nucleotide polymorphism (SNP) genotyping at 550,000 loci. We analyzed these data and the distribution of genotypes, haplotypes and copy number variants across populations. We showed that these data were able to assign individuals to populations and that the resulting predictions supported fine-scale inferences about population structure. Increasing linkage disequilibrium was observed with increasing geographic distance from Africa, as expected under a serial founder effect for the out-of-Africa spread of human populations. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations. In addition we have defined the nature of a large inversion polymorphism that occurs in distinct human populations and is thought to be under positive selection (it is suggested that this is in response to infectious disease). Gene expression influences normal brain development and function as well as propensity to some neurological diseases. The expression levels of mRNAs are controlled at multiple levels, including polymorphic sequence variants in DNA, genomic modifications such as methylation, and the expression of microRNAs (miRNAs). Understanding how multiple layers of control interact in a complex and heterogenous tissue such as the brain is challenging but can be addressed using high throughput techniques designed at capturing large amounts of information for each level of variability. In the current study, we have used a panel of four brain regions (frontal and temporal cortex, cerebellum and pons) from 150 neurologically normal individuals. For each individual, we genotyped 500,000 single nucleotide polymorphisms (SNPs) and measured DNA methylation at 27,000 CpG sites in all four brain regions. We also measured expression of 740 microRNA and 22,500 polyadenylated RNA transcripts. In this way, we will capture information on variability in mRNA expression based on two major variables of genotype and brain region, with methylation status and miRNA expression as modifiers. For initial analysis, we have used unsupervised clustering to focus on differences between brain regions. Brain regions coud be fully separated by examining any of CpG methylation, miRNA and polyA RNA expression. The separation by the different RNA measures is especially interesting, given that only 350-400 miRNA species but 13-14,000 polyA RNA were reliably detected in different brain regions. This result implies that miRNAs exert relatively large effects influencing RNA expression networks. Ongoing analysis involves these datasets with genotyping to identify how normal genetic variation within the human population affects expression.

在过去的一段时间里，我们进行了两组独立但互补的实验;第一组是为了了解全世界人群基因组变异的范围和分布;第二组是为了表征人类大脑中这种变异对mRNA和miRNA表达以及CpG甲基化的影响。 使用来自31个不同的全球人群的500多个样本，我们在550，000个位点进行了非常密集的全基因组单核苷酸多态性（SNP）基因分型。我们分析了这些数据以及基因型、单倍型和拷贝数变异在人群中的分布。我们表明，这些数据能够将个体分配到种群中，并且由此产生的预测支持关于种群结构的精细尺度推断。随着与非洲的地理距离的增加，观察到越来越多的连锁不平衡，正如预期的那样，在非洲以外的人口传播的一系列创始人效应。我们的研究结果产生了关于群体间变异的新推论，支持CNV在人类群体遗传研究中的应用，并作为全球不同人群人类遗传研究的基因组资源。此外，我们还定义了一个大的倒位多态性的性质，它发生在不同的人群中，并被认为是在积极的选择（这表明这是对传染病的反应）。 基因表达影响正常的大脑发育和功能，以及一些神经系统疾病的倾向。 mRNA的表达水平在多个水平上受到控制，包括DNA中的多态性序列变体、基因组修饰（如甲基化）和microRNA（miRNA）的表达。 了解多层控制如何在复杂和异质的组织（如大脑）中相互作用是具有挑战性的，但可以使用高通量技术来解决，这些技术旨在为每个可变性水平捕获大量信息。 在目前的研究中，我们使用了150名神经系统正常的人的四个大脑区域（额叶和颞叶皮层，小脑和脑桥）。 对于每个人，我们对500，000个单核苷酸多态性（SNP）进行基因分型，并在所有四个大脑区域的27，000个CpG位点测量DNA甲基化。 我们还测量了740个microRNA和22，500个多聚腺苷酸化RNA转录物的表达。 通过这种方式，我们将基于基因型和脑区域这两个主要变量，以甲基化状态和miRNA表达作为修饰符，捕获mRNA表达变异性的信息。 对于初始分析，我们使用无监督聚类来关注大脑区域之间的差异。 通过检测CpG甲基化、miRNA和polyA RNA表达中的任何一种，可以完全分离脑区域。 通过不同的RNA测量进行分离是特别有趣的，因为在不同的脑区域中仅可靠地检测到350-400种miRNA种类，但13- 14，000种polyA RNA。 这一结果表明，miRNA发挥相对较大的影响RNA表达网络的影响。 正在进行的分析涉及这些具有基因分型的数据集，以确定人群中的正常遗传变异如何影响表达。