CORE--GENOMICS AND NEUROBIOLOGY RESEARCH CORE

GNRC联合了三个研究精神分裂症的神经生物学和病理生理学的小组，以及哥伦比亚基因组中心（CGC）的核心科学家，致力于“基因组”策略以识别精神分裂症相关基因。这些GNRC有两个主要目标。第一个目标是阐明精神分裂症的神经生物学基础，包括神经化学异常（突触蛋白和MAP 2）和神经免疫学异常（与异常伴侣蛋白HSP 60的免疫原性有关）。关键基因，蛋白质，蛋白质-蛋白质相互作用，以及由这些和其他研究产生的调节机制，然后为两个计算基因组“搜索引擎”中的第一个提供模板。第一个引擎的目的是通过预测新的蛋白质-蛋白质相互作用的基础上系统的系统发育同源性搜索，阐述生化和监管途径。通过将人类基因和蛋白质与它们在低等生物中的直系同源物相匹配，可以预测新的相互作用模式。因此，这些新的“蛋白质网络”形成了一个与精神分裂症相关的DNA改变的可能靶基因数据库。GNRC的第二个目标是将联合收割机分子和计算策略相结合，以系统地鉴定和表征给定的大的精神分裂症连锁染色体区域中的所有基因。第二个“搜索引擎”将收集所有的基因和预测的基因从这些地区和特点，他们的系统发育同源性关系。同时，我们将使用已建立的高通量技术对连接区域的大片段进行测序，并分析预测的蛋白质编码区。总之，这些策略将产生一组新的基因和蛋白质序列，形成一个位置候选基因数据库。接下来，蛋白质相互作用和位置候选搜索引擎将交叉分析以预测高优先级候选基因。在提案的最后阶段，我们将制定一项策略，对患者和对照DNA样本中的多个候选基因进行DNA测序。通过这种方式，我们将产生一个精神分裂症相关DNA改变的公共数据库，这将为大样本的DNA微芯片检测奠定基础。这种“基因组”搜索策略的一个重要特征是，它绕过了检测共享染色体片段的必要性，这是所有当前遗传搜索策略的基础。

The GNRC unites three groups studying the neurobiology and pathophysiology of schizophrenia with a core of scientists in the Columbia Genome Center (CGC) working on "genomic" strategies to identify schizophrenia-related genes. These GNRC has two major objectives. The first goal is to elucidate the neurobiological underpinnings of schizophrenia, including neurochemical abnormalities (in synaptic proteins and MAP2), and neuroimmunological abnormalities (relating to the immunogenicity of an abnormal chaperonin, hsp60). The key genes, proteins, protein-protein interactions, and regulatory mechanisms generated by these and other studies then provide the template for the first of two computational genomic "search engines". The first engine is designed to elaborate biochemical and regulatory pathways by predicting novel protein-protein interactions based upon systematic phylogenetic homology searchers. By matching human genes and proteins with their orthologues in lower, well-characterized organisms, new patterns of interaction can be predicted. These new "protein networks" thereby form a database of likely target genes for schizophrenia-related DNA alterations. The second goal of the GNRC is to combine molecular and computational strategies to systematically identify and characterize all genes in a given large schizophrenia-linked chromosomal region. A second "search engine" will collect all genes and predicted genes from such regions and characterize their phylogenetic homology relationships. Simultaneously, we will use established high throughout technologies to sequence large segments of the linked regions and analyze for predicted protein coding regions. Together, these strategies will yield a new set of gene and protein sequences that form a positional candidate gene database. Next, the protein-interaction and positional candidate search engines will cross- analyze to predict high priority candidate genes. In the final phase of the proposal we will develop a strategy to DNA sequence multiple candidate genes in a collection of patient and control DNA samples. In this way we will generate a public database of schizophrenia-related DNA alterations that will lay the foundation for a DNA microchip assay for large samples. A significant feature of this "genomic" search strategy is that it bypasses the necessity of detecting shared chromosomal segments, the basis of all current genetic search strategies.