Functional Characterization of BAFF-induced Genes

描述（由申请人提供）：功能基因组学的最新实验正在以前所未有的速度生成新数据。现在的挑战是将这些大量的新信息整合到对生物系统如何工作的机械理解中。我们已经开发了一种生物信息学算法，CLASSIFI，它使用基因本体信息分类微阵列基因簇的基础上协调的表达模式。采用CLASSIFI技术分析在调节B细胞稳态和功能中起重要作用的两种配体BAFF和CD 40 L刺激的脾B细胞表达谱芯片数据。一簇响应BAFF上调的探针/基因含有高比例的先前未被表征的序列，表明BAFF正在诱导一组可能参与新生物过程的新基因的表达。本项目将追求两个总体目标--开发用于选择和表征以前未表征的基因的客观方法，并研究由BAFF控制的调节B淋巴细胞稳态和功能的分子过程。这些目标将通过数据挖掘和假设驱动的实验相结合来实现。该项目的具体目标是表征由BAFF控制的B细胞反应，通过生物信息学方法和组织表达研究的组合来过滤和优先化未表征的探针/基因集，使用生物信息学分析来开发关于候选基因的可能生物学功能的假设，并通过确定相互作用蛋白来研究候选基因的可能功能，可能的生物化学活性的研究和对BAFF介导的B细胞应答的表达扰动效应的测量。B细胞对BAFF应答的机制研究是医学相关的，因为BAFF的失调与动物模型和人类中自身免疫性疾病的发展相关。

DESCRIPTION (provided by applicant): Recent experimentation in functional genomics is generating new data at an unprecedented rate. The challenge now is to integrate this large amount of new information into a mechanistic understanding of how biological systems work. We have developed a bioinformatics algorithm, CLASSIFI, which uses gene ontology information to classify microarray gene clusters based on coordinated expression patterns. CLASSIFI was used to analyze expression microarray data from splenic B cells stimulated with two ligands, BAFF and CD40L, which play important roles in regulating B cell homeostasis and function. One cluster of probes/genes up-regulated in response to BAFF contains a high proportion of sequences that have not been previously characterized, suggesting that BAFF is inducing the expression of a panel of new genes that may be involved in novel biological processes. Two general goals will be pursued in this project - to develop objective approaches for the selection and characterization of previously uncharacterized genes, and to investigate the molecular processes controlled by BAFF that regulate B lymphocyte homeostasis and function. These goals will be achieved through a combination of data mining and hypothesis-driven experimentation. The specific aims of this project are to characterize the B cell responses controlled by BAFF, to filter and prioritize the uncharacterized probe/gene set through a combination of bioinformatics approaches and tissue expression studies, to develop hypotheses regarding possible biological functions of the candidate genes using bioinformatics analysis, and to investigate possible functions of the candidate genes through a determination of interacting proteins, an investigation of possible biochemical activities and a measurement of expression perturbation effects on BAFF-mediated B cell responses. Mechanistic studies of B cell responses to BAFF are medically relevant since dysregulation of BAFF is associated with the development of autoimmune disease in both animal models and humans.