The molecular basis of planarian regeneration

描述(申请人提供)：提出的实验的目的是识别和功能特征的基因和遗传途径调控后生动物的再生，使用稻曲线虫作为一个模式系统。选择浮游生物是因为它们是最简单的生物体的代表，表现出两侧对称、头状结构和复杂的器官系统，并被赋予了惊人的全潜能干细胞(新生细胞)群体，从这些干细胞中它们获得了非凡的再生能力。考虑到关于再生的分子基础还有很多需要了解的地方，研究这个问题的最佳策略是对基因表达进行大规模的时空分析，同时进行功能丧失的遗传筛选。利用基因芯片，我们将确定从地中海链霉菌克隆株4(CIW4)的头部、头部胚芽和新母细胞(干细胞)文库中获得的-4,500个非冗余cDNA的表达谱。打印在微阵列上的基因的时间序列表达谱将通过杂交从再生的不同时间点获得的组织中的Cy标记的cDNA来生成。这些数据将进行聚类分析，以确定具有相似表达动力学的基因组。微阵列结果将由阵列中所代表的基因的空间特征来补充。通过整体原位杂交获得的空间表达数据将根据组织和/或细胞类型特异性进行聚类。空间基因表达簇将与微阵列衍生的时间表达簇进行比较，以确定细胞特异性和表达动力学的重叠。这应该会导致根据基因表达的时间和地点来识别可能属于相同遗传途径的基因子集。为了测试基因功能，并确定在再生事件中的作用，我们将使用RNAi进行反向遗传筛选。基于RNAi的筛选将用于：1)测试时空关系；2)识别其功能消除能够干扰再生的基因；以及3)识别微阵列分析中遗漏的基因，其产物的活性变化而不是表达水平的变化负责调节再生事件。最后，我们将试图通过在稳态微阵列研究中定义RNAi处理的动物的表达谱，为那些被确定在再生过程中发挥关键作用的基因建立上位性交互作用。

DESCRIPTION (provided by applicant): The experiments proposed aim to identify and functionally characterize genes and genetic pathways regulating metazoan regeneration using Schmidtea mediterranea as a model system. Planarians were chosen because they are representatives of the simplest organisms displaying bilateral symmetry, cephalization, and complex organ systems and are endowed with a remarkable population of totipotential stem cells (neoblasts) from which they derive extraordinary regenerative abilities. Considering that much remains to be learned about the molecular basis of regeneration, the best strategy to study this problem is to perform large-scale temporo-spatial analyses of gene expression along with loss-of-function genetic screens. Using microarrays, we will define the expression profile of -4,500 non-redundant cDNAs obtained from head, head blastema and neoblast (stem cells) cDNA libraries derived from clonal line 4 (CIW4) of S. mediterranea. A time-series expression profile of the genes printed on the microarrays will be generated by hybridizing Cy-labeled cDNAs from tissues obtained at various time points of regeneration. The data will be subjected to cluster analyses to identify groups of genes sharing similar expression kinetics. The microarray results will be complemented by the spatial characterization of the genes represented in the arrays. Spatial expression data obtained by whole-mount in situ hybridizations will be clustered according to tissue and/or cell type specificity. The spatial gene expression clusters will be compared to microarray-derived temporal expression clusters to identify overlaps in cell specificity and expression kinetics. This should result in the identification of subsets of genes that may belong to the same genetic pathways based on when and where they are expressed. To test for gene function, and to determine roles in regenerative events, we will carry out reverse genetic screens using RNAi. The RNAi-based screen will serve to: 1) test the temporo-spatial relationships; 2) identify genes whose functional abrogation are capable of perturbing regeneration; and 3) identify genes missed by microarray analyses to which changes in the activity of their products, rather than changes in expression levels are responsible for modulating regenerative events. Finally, we will attempt to establish epistatic interactions for those genes identified as playing key roles in the progress of regeneration by defining expression profiles of RNAi-treated animals in steady-state microarray studies.