Functional Characterization of BAFF-induced Genes

描述（由申请人提供）：最近的功能基因组学实验正在以前所未有的速度产生新的数据。现在的挑战是将这大量的新信息整合到对生物系统如何工作的机械理解中。我们开发了一种生物信息学算法CLASSIFI，它使用基因本体信息对基于协调表达模式的微阵列基因簇进行分类。使用CLASSIFI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CD40L刺激脾脏B细胞的表达微阵列数据。一组响应BAFF而上调的探针/基因包含了大量以前未被表征的序列，这表明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-开发客观的方法来选择和表征以前未表征的基因，并研究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实验的结合来实现。该项目的具体目标是表征BAFF控制的B细胞反应，通过结合生物信息学方法和组织表达研究筛选和优先考虑未表征的探针/基因集，利用生物信息学分析对候选基因的可能生物学功能提出假设，并通过测定相互作用蛋白来研究候选基因的可能功能。对baff介导的B细胞反应可能的生化活性和表达扰动效应的研究。B细胞对BAFF反应的机制研究具有医学意义，因为在动物模型和人类中，BAFF的失调与自身免疫性疾病的发展有关。

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.