The molecular basis of planarian regeneration

描述（由申请人提供）：本实验旨在以地中海Schmidtea mediterranea为模型系统，识别和功能表征调节后生动物再生的基因和遗传途径。选择涡虫是因为它们是最简单的生物体的代表，表现出两侧对称、头化和复杂的器官系统，并被赋予了大量的全潜能干细胞（新生细胞），从中获得了非凡的再生能力。考虑到再生的分子基础还有很多有待了解的地方，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，同时对功能丧失的基因筛选进行分析。利用微阵列技术，我们将确定从地中海南芥（S. mediterranea）克隆系4 （CIW4）获得的头、头胚和新母细胞（干细胞）cDNA文库中获得的-4,500个非冗余cDNA的表达谱。从再生的不同时间点获得的组织中杂交cy标记的cdna，将生成打印在微阵列上的基因的时序表达谱。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表征来补充。通过全载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。这将导致根据表达的时间和地点确定可能属于相同遗传途径的基因亚群。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的屏幕将用于：1)测试时空关系；2)鉴定功能缺失能够干扰再生的基因；3)识别被微阵列分析遗漏的基因，这些基因的产物活性的变化，而不是表达水平的变化，负责调节再生事件。最后，我们将尝试通过定义rnai处理动物在稳态微阵列研究中的表达谱，建立在再生过程中起关键作用的基因的上位性相互作用。

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.