Genometric analysis of quantitative traits

数量性状的基因组分析

• 批准号: 8948360
• 负责人: alexander f wilson
• 金额: $ 148.66万
• 依托单位: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
• 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/8948360
• 关键词: Address; Adult; Alleles; Area; Austria; Breeding; Case-Control Studies; Caucasians; Caucasoid Race; Cells; Chromosomes; Clinical; Collaborations; Computer Simulation; Computer software; Craniosynostosis; DNA Markers; Data; Dependency; Detection; Development; Economic Inflation; Educational workshop; Embryo; Enhancers; Family; Fishes; Functional RNA; GRP gene; Genes; Genetic; Genetic Heterogeneity; Genetic Recombination; Genets; Genome; Genotype; Goals; Heritability; Hot Spot; Individual; International; Linear Models; Linear Regressions; Linkage Disequilibrium; Manuscripts; Mentors; Methodology; Methods; Microscopy; Midbrain structure; NF1 gene; National Human Genome Research Institute; National Institute of Child Health and Human Development; Nature; Pattern; Phenotype; Population; Positioning Attribute; Preparation; Programming Languages; Property; Proteins; Publishing; Quantitative Genetics; Regression Analysis; Regulatory Element; Reporting; Research; Research Design; Sampling; Single Nucleotide Polymorphism; Site-Directed Mutagenesis; Societies; Spottings; Staging; Statistical Methods; Stratification; Structure; Students; Testing; United States National Institutes of Health; Variant; Work; Writing; Zebrafish; base; case control; density; functional group; genetic analysis; genetic epidemiology; genetic linkage analysis; genome wide association study; insight; meetings; member; method development; next generation; next generation sequencing; population based; proband; rare variant; research study; simulation; statistics; telomere; trait; vector; web site

Methods Development Because the non-independence of marker data is particularly relevant in next generation sequencing data, most of the theoretical work during the past year has focused on the testing, implementation and extension of Tiled regression, a linear regression based method for intra-familial tests of association that address non-independence both at the marker and observational level. Although most of the major methodological development has been completed, extensions implemented during the past year have focused on the incorporation of penalized regression methods and the use of family data, and the use of simulation to test the statistical properties of these methods in tiled regression when compared to the use of stepwise regression. The tiled regression methodology has been implemented in the Tiled Regression Analysis Package (TRAP), a software package written in the R programming language. The package is freely available on the NHGRI website: http://research.nhgri.nih.gov/software/TRAP. Simulation experiments to test the statistical properties of tiled regression Two simulation projects were completed during the past year and the results are being prepared for submission Suktitipat et al, Kim et al.. The Suktitpat et al. project focused on the statistical properties of tiled regression compared to those of simple linear regression. Tiled regression had comparable power, a more conservative type I error and a lower FDR than corresponding results from simple linear regression of single markers in a GWAS setting. Kim et al. investigated penalized regression methods as an alternative to stepwise regression. Results from this study suggested that stepwise regression outperformed penalized regression when the causal variants are present in the genotyping data, but penalized regression methods outperformed stepwise methods when the causal variant were not among the variants genotyped. Thus, penalized methods may be more appropriate for a GWAS, whereas stepwise methods may be the preferred approach for next generation whole genome data. A third simulation study investigated the effects of boundary definition on the type I error rate and power in tiled regression Sorant et al., in preparation. This project is being presented at the International Genetic Epidemiology Society meeting in late August. In this project, several criteria to define hot spot boundaries are evaluated and the power and type I error rate is determined for each criteria. At the genome level, there does not appear to be substantial differences between any of the criteria for boundary selection. However, at the definition of the tile level, defining actual hot spot recombination blocks and the intervening cold spot blocks, there are differences. Although from a mathematical standpoint, boundary definition is arbitrary, it appears that the criteria to define recombination hot spots may be important in identifying the local regions that are biologically relevant, rather than simply statistically relevant. Additional simulations are being performed on data provided as part of the Genetic Analysis Workshop 19, to be held in Vienna, Austria in late August An et al., in preparation. Inflation of type I error had previously been reported in linkage analysis with STRPs at the telomere regions of the chromosomes, possible due in part to the increased density of STRPs in these regions and corresponding possible duplications and increased correlations between STRPs. In this project, the effects of variant position and the distribution of the trait phenotype on the distribution of type I error, were examined in standard tests of association with next generation sequence data. The GAW 19 data was used to test this concept on both common and rare next generation sequence variants. With respect to the physical position of the type I errors, there does not appear to be any consistent patterns of inflated type I errors at the telomeres, although isolated areas of increased type I error were observed. The data are being more thoroughly annotated and the distribution of type I error will be considered within several different ENCODE defined functional groups. The effect of the distribution of the trait phenotype was also examined. Although it is well known that the type I error rate of rare variants is substantially inflated, the reason for this is not clear. Although non-normally distributed traits had inflated type I error rates for rare variants as expected, when these traits were transformed to be more normally distributed, the inflation was reduced and eventually disappeared depending on the strength of the transformation. More common alleles (with MAFs > 0.05) do not appear to have inflated type I error rates for any of the non-normally distributed traits considered, and transformation of these variants appears to be unnecessary. Collaborations Craniosynostosis Justice et al., as part of a long-term collaboration with Dr. Simeon (Boyd) Boyadjiev at UC Davis, reported a genome-wide association study (GWAS) for non-syndromic sagittal craniosynostosis and these associations were replicated in an independent Caucasian population of 186 unrelated probands with non-syndromic sagittal craniosynostosis and 564 unaffected controls Nat Genet 2012. During the past year, zebrafish were used to test the expression of the conserved non-coding regulatory elements previously identified, in order to determine if the expression of identified sequence variants differed from that of the wildtype expression. To accomplish this, a putative regulatory element was created with site-directed mutagenesis and inserted into the Zebrafish Enhancer Detection (ZED) vector construct. The ZED vector was microinjected into one-cell stage zebrafish embryos. The embryos were screened with fluorescent microscopy for red and green florescent protein (RFP and GFP, respectively) positive embryos. Embryos demonstrating RFP/GRP expression were grown to adulthood and bred with wildtype fish. Several germline transmitting founders were identified for each ZED vector construct and their progeny were screened for patterns of RFP/GFP expression, again using fluorescent microscopy. The variant showed substantially enhanced GFP expression in the mid-brain, when compared to wildtype expression Justice et al., in preparation. Methods development Two methods development manuscripts focusing on generalized linear models for gene- based case-control association studies were published during 2013 - 2014. Both were authored or co-authored by Dr. Ruzong Fan (NICHD) and published in Genetic Epidemiology. Dr. Wilson is both a collaborator and member of Dr. Fans mentoring committee. Other ongoing collaborations include: 1) Clinical characterization of NF1 (Dr. Douglas Stewart, NIH/NCI) 2) The ClinSeq project (Les Biesecker, NIH/NHGRI) 3) Variation in metabolites in the Irish Trinity Student Study (Dr. Larry Brody, NHGRI)

方法开发 由于标记数据的非独立性在下一代测序数据中特别重要，因此过去一年的大部分理论工作都集中在 Tiled 回归的测试、实施和扩展上，Tiled 回归是一种基于线性回归的方法，用于家族内关联测试，解决标记和观察水平上的非独立性问题。 虽然大部分主要方法的开发已经完成，但去年实施的扩展主要集中在惩罚回归方法的结合和家庭数据的使用，以及与使用逐步回归相比，使用模拟来测试这些方法在平铺回归中的统计特性。 平铺回归方法已在平铺回归分析包 (TRAP) 中实现，这是一个用 R 编程语言编写的软件包。 该软件包可在 NHGRI 网站上免费获取：http://research.nhgri.nih.gov/software/TRAP。 测试平铺回归统计特性的模拟实验 去年完成了两个模拟项目，正在准备提交结果 Suktitipat 等人、Kim 等人。项目重点关注平铺回归与简单线性回归相比的统计特性。 与 GWAS 设置中单个标记的简单线性回归的相应结果相比，平铺回归具有相当的功效、更保守的 I 型错误和更低的 FDR。 金等人。研究了惩罚回归方法作为逐步回归的替代方法。 这项研究的结果表明，当基因分型数据中存在因果变异时，逐步回归优于惩罚回归，但当因果变异不在基因分型变异中时，惩罚回归方法优于逐步方法。 因此，惩罚方法可能更适合 GWAS，而逐步方法可能是下一代全基因组数据的首选方法。 第三项模拟研究调查了边界定义对平铺回归中 I 类错误率和功效的影响 Sorant 等人正在准备中。 该项目将于八月下旬在国际遗传流行病学协会会议上提出。 在此项目中，评估了定义热点边界的几个标准，并确定了每个标准的功率和 I 类错误率。 在基因组水平上，任何边界选择标准之间似乎都没有显着差异。 然而，在瓦片级别的定义上，定义实际的热点重组块和介入的冷点块，存在差异。 尽管从数学的角度来看，边界定义是任意的，但定义重组热点的标准似乎对于识别生物学相关的局部区域很重要，而不仅仅是统计相关。 An 等人正在对将于 8 月底在奥地利维也纳举行的遗传分析研讨会 19 的一部分提供的数据进行额外的模拟。 先前在染色体端粒区域的 STRP 连锁分析中报告了 I 型错误的增加，部分原因可能是这些区域中 STRP 密度增加以及相应的可能重复和 STRP 之间相关性增加。 在该项目中，在与下一代序列数据关联的标准测试中检查了变异位置和性状表型分布对I型错误分布的影响。 GAW 19 数据用于在常见和罕见的下一代序列变体上测试这一概念。 关于 I 型错误的物理位置，尽管观察到 I 型错误增加的孤立区域，但端粒处似乎没有任何一致的 I 型错误膨胀模式。 正在对数据进行更彻底的注释，并且将在几个不同的 ENCODE 定义的功能组中考虑 I 类错误的分布。 还检查了性状表型分布的影响。 尽管众所周知，罕见变异的 I 型错误率大幅升高，但其原因尚不清楚。 尽管非正态分布的性状如预期那样夸大了罕见变异的 I 型错误率，但当这些性状转变为更正态分布时，通货膨胀会减少并最终消失，具体取决于转换的强度。 对于所考虑的任何非正态分布性状，更常见的等位基因（MAF > 0.05）似乎没有夸大的 I 型错误率，并且这些变体的转化似乎是不必要的。 合作 颅缝早闭 Justice 等人与加州大学戴维斯分校的 Simeon (Boyd) Boyadjiev 博士长期合作，报告了一项针对非综合征矢状颅缝早闭的全基因组关联研究 (GWAS)，这些关联在由 186 名患有非综合征矢状颅缝早闭的无关先证者和 564 名未受影响的对照组成的独立白人群体中得到了复制。 Nat Genet 2012。在过去的一年中，斑马鱼被用来测试先前鉴定的保守非编码调控元件的表达，以确定所鉴定的序列变体的表达是否与野生型表达不同。 为了实现这一目标，通过定点诱变创建了一个假定的调控元件，并将其插入斑马鱼增强子检测 (ZED) 载体构建体中。 将 ZED 载体显微注射到单细胞阶段斑马鱼胚胎中。 用荧光显微镜筛选胚胎中红色和绿色荧光蛋白（分别为RFP和GFP）阳性胚胎。 表现出 RFP/GRP 表达的胚胎生长至成年并与野生型鱼一起繁殖。 为每个 ZED 载体构建体鉴定了几个种系传递创始人，并再次使用荧光显微镜筛选其后代的 RFP/GFP 表达模式。 与Justice等人准备的野生型表达相比，该变体在中脑中的GFP表达显着增强。 方法开发 2013 年至 2014 年期间发表了两篇方法开发手稿，重点关注基于基因的病例对照关联研究的广义线性模型。两篇方法开发手稿均由范如宗博士 (NICHD) 撰写或共同撰写，并发表在《遗传流行病学》杂志上。 Wilson 博士既是 Fans 博士指导委员会的合作者，也是成员。 其他正在进行的合作包括： 1) NF1 的临床特征（Douglas Stewart 博士，NIH/NCI） 2) ClinSeq 项目（Les Biesecker，NIH/NHGRI） 3) 爱尔兰三一学生研究中代谢物的变化（Larry Brody 博士，NHGRI）