Genetics and Bioinformatics Core Laboratory

遗传学与生物信息学核心实验室

• 批准号: 7735226
• 负责人: Daniel Weinberger
• 金额: $ 217.31万
• 依托单位: NATIONAL INSTITUTE OF MENTAL HEALTH
• 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/7735226
• 关键词: Address; Admixture; Alleles; Animal Model; Anxiety; Autopsy; Bioinformatics; Biological; Biological Assay; Biological Models; Brain; Brain Diseases; Brain region; COMT gene; Candidate Disease Gene; Cataloging; Catalogs; Catechol O-Methyltransferase; Caucasians; Caucasoid Race; Chromosomes; Clinical; Clinical Trials; Cognition; Collaborations; Complex; Computer Simulation; Computer software; DNA; DNA Sequence; Data; Data Set; Disease; Equilibrium; ErbB4 gene; Ethnic group; Exons; FGF20 gene; Family; Frequencies; Gene Combinations; Gene Frequency; Genes; Genetic; Genetic Risk; Genetic Variation; Genomics; Genotype; Gold; Haplotypes; Hereditary Disease; Human; Image; In Situ Hybridization; Individual; Introns; Laboratories; Laboratory Research; Length; Linkage Disequilibrium; Literature; Logistic Regressions; Measures; Messenger RNA; Methods; Microsatellite Repeats; Modeling; Moods; Morphologic artifacts; Mutation; National Institute of Mental Health; Neurofibromin 2; Neuropsychology; Numbers; Odds Ratio; Online Systems; Open Reading Frames; Outsourcing; PIP5K2A gene; PPP3CC gene; Parents; Phase; Phenotype; Phosphatidylinositol-4-Phosphate 5-Kinase Type II Alpha; Polymorphism Analysis; Population; Proteins; Psychotic Disorders; RNA Splicing; Race; Recombinants; Reproducibility; Research Personnel; Reverse Transcriptase Polymerase Chain Reaction; Risk; Sampling; Schizophrenia; Screening procedure; Single Nucleotide Polymorphism; Site; Spottings; Stratification; Susceptibility Gene; System; Technology; Testing; Transcript; Variant; Work; base; cDNA Library; case control; clinical phenotype; data mining; follow-up; gene interaction; genetic variant; human FGF20 protein; human PPP3CC protein; novel; proband; programs; statistics; trait; transmission process

To date, we have tested numerous single nucleotide polymorphisms (SNPs) in well over 118 genes, including some of the less established but intriguing candidates such as PRODH, RGS4, CHRNA7, PIP5K2A, and PPP3CC. Among our accomplishments, we have fully sequenced the 10 exons and flanking sequences of 180 proband chromosomes for dysbindin, sequenced two exons of MRDS1, and sequenced 1.5 kb of the GAD1 upstream region. A total of 21 new SNPs were discovered in these genes, 15 of which were genotyped in the clinical samples. We have re-sequenced the exons and splice sites of GRM3 in 180 chromosomes, which led to the discovery of a few rare SNPs. We have likewise re-sequenced risk regions of KCNH2, ErbB4, PIk3d, FGF20, DAARP, and COMT and identified novel variants in these genes as well. We routinely submit our Taqman genotype assay to reproducibility checks by re-genotyping (avg. accuracy >99%) and spot accuracy checks done by double stranded sequencing (avg. >99% for most SNP assays). Genotypes are called manually within the ABI SDS software and confirmed. We perform Mendelian checks and higher order (e.g. multiple recombinants) error checking with the program MERLIN. Microsatellite genotyping has been performed in collaboration with the NIMH Mood and Anxiety Program. We measure linkage disequilibrium (LD) between markers with the D prime and r2 statistics from cases and controls in parallel using the GOLD software package. All SNPs are tested for departures from Hardy-Weinberg equilibrium. For large numbers of loci, we use SNPHAP to reconstruct haplotypes and estimate their frequencies in unrelated individuals. For family based association studies of the discrete clinical phenotype, we use the programs FBAT, TDTPHASE and TRANSMIT for unknown phase haplotype estimation. Case-control analysis of individual SNPs and SNP haplotypes is done using logistic regression in STATA and COCAPHASE. All P values are computed empirically with 10,000 permutations or bootstraps as the programs provide. Tests of association to quantitative traits such as the intermediate phenotypes are performed by the FBAT and QTDT, which allows variance-components testing of family-based samples for association and transmission disequilibrium. The orthogonal model used is robust to population stratification because, analogous to the conventional TDT, it only considers transmissions from heterozygous parents. To control for possible artifacts due to allele frequency differences across ethnic groups, analysis limited to Caucasians is performed in parallel. We have also established a panel unlinked SNPs to use as a potential genomic control panel for case control association studies, including intermediate phenotype analyses, to address potential population admixture artifacts. In our genomics project we acquire extensive genetic variation data in our susceptibility genes and complete the catalog of genetic risk genes in our datasets. As part of the GCAP program, we have greatly increased the genotyping throughput by outsourcing. We project that about every 4 months for the next 2 years we will genotype a minimum of 768 SNPs, perform follow-up work on established genes and test novel genes. In addition, we outsource the majority of re-sequencing for SNP detection to DNA sequencing companies. All exons, splice sites, and 10 kb of the upstream region will be re-sequenced in an initial pass, then some regions of some genes are sequenced further (e.g. the introns or positive haplotypes) and/or more individuals. Because most functional SNPs and mutations are not in protein coding regions, it is critical to fully characterize transcripts species in several regions of post mortem human brain. To accomplish this, we routinely execute basic mRNA transcript characterization technologies such as 5' and 3' RACE and screening of full-length transcripts, normalized cDNA libraries from multiple brain regions. This work also serves to guide quantitative RT-PCR and in situ hybridization expression studies. Another project of central importance is the statistical analyses of gene-gene interactions. It is likely that certain gene and allele combinations interact epistatically to produce risk greater than that predicted by the individual odds ratios. It is also likely that some gene combinations will increase risk even in the absence of main effects in each gene. We are using the data driven analytic approach developed at Vanderbilt called multifactor dimensionality reduction (MDR) in an attempt to detect sets of interacting alleles that predict disease status. We also engage in collaborative discussions with Salford Systems, originator of the programs CART, MARS, and TREENET, to explore and execute other data mining strategies. Our statistical geneticist uses the wealth of data to model and test complex gene-gene and gene-environmental interactions, and establish some objective criteria for integrating statistical genetic (disease and intermediate phenotype) data with convergent biological data both to gauge overall significance of given genotype/haplotype, phenotype correlations and to evaluate attributable risk.

迄今为止，我们已经测试了超过118个基因的大量单核苷酸多态性（snp），包括一些不太确定但有趣的候选基因，如PRODH， RGS4, CHRNA7， PIP5K2A和PPP3CC。在我们的研究成果中，我们对180个先证染色体的10个外显子和侧链进行了dysbinding的完整测序，对MRDS1的两个外显子进行了测序，并对GAD1上游区域的1.5 kb进行了测序。在这些基因中共发现了21个新的snp，其中15个在临床样本中进行了基因分型。我们对180条染色体中GRM3的外显子和剪接位点进行了重新测序，发现了一些罕见的SNPs。我们同样对KCNH2、ErbB4、PIk3d、FGF20、DAARP和COMT的风险区域进行了重新测序，并在这些基因中发现了新的变异。我们定期提交Taqman基因型分析，通过重新基因分型进行重复性检查（平均准确度bbbb99 %），并通过双链测序进行斑点准确性检查（大多数SNP分析的平均准确度b> 99%）。基因型在ABI SDS软件中手动调用并确认。我们使用MERLIN程序执行孟德尔检查和高阶（例如多个重组）错误检查。微卫星基因分型是与NIMH情绪和焦虑项目合作进行的。