調控特定腦區的腦神經細胞在研究腦神經迴路與動物行為之間扮演很重要的一個角色，在果蠅中，GAL4-UAS這個系統是最常用來調控基因的工具。盡管已經有上千種表達在不同位置的GAL4被製作出來，但他們表達的位置仍不夠專一用以進行特定神經的調控。現在，一個用來限縮GAL4表達區域的系統被發展出來，其名為FINGR(FLP-induced intersectional GAL80/GAL4 repression)系統。FINGR包含了兩大部分，第一個是約莫1000個能在細胞中持續表達的增強子陷阱翻轉酶；另一個是帶有GAL80的翻轉酶識別位置的序列，我們稱之為"flip-out"的工具。雖然如此，FINGR系統仍面對到兩個很重要的障礙，其一為這1000個增強子陷阱翻轉酶所表達的位置仍是未知的；其二，缺乏用簡單的方法分析計算增強子陷阱翻轉酶與GAL4共同表達交集的位置。所以，在這篇文章中，我們全面性的分析這1000個增強子陷阱翻轉酶的表達位置並將結果分門別類地輸入FlyDriver。在FlyDriver網站上，可以提供使用者分析增強子陷阱翻轉酶與GAL4共同表達交集的位置。為了使使用者更方便、更容易成功的製作轉基因果蠅，我們提供一個預測增強子陷阱翻轉酶與GAL4共同表達交集位置的標準程序流程。利用以上調控的工具，我們希望能提供神經科學家理解腦袋是如何編排與處理複雜的行為。

Transgenic manipulation of target neurons is increasingly important for understanding how brain circuits control complex behaviors. In Drosophila, the GAL4–upstream activating sequence (UAS) binary system is widely used to manipulate functions of gene expression and neuronal activity. Though thousands of GAL4 lines are available, their expression patterns are usually not specific enough to manipulate target neurons. The FLP-induced intersectional GAL80/GAL4 repression (FINGR) system consisting of tissue-specific enhancer-trap Flippase lines and a FRT-dependent GAL80 “flip-out” construct has recently been developed to narrow down the GAL4 expressed pattern. Nevertheless, application of FINGR system faces two obstacles: First, the numbers of expression patterns of enhancer-trap Flippase lines are limited. Second, there are no easy ways to analyze GAL4/FLP intersection. Here, I comprehensively examined nearly 1000 FLP expression patterns and cataloged these results into a driver database, called FlyDriver. The FlyDriver allows users to predict GAL4/FLP intersection. As a proof of concept, I have established a standard operation procedure for predicting GAL4/FLP intersection before generating the genetic flies through combining several transgenes into the same fly. My study will help neuroscientists to generate circuit controlling tool for understanding how the brain orchestrates complex behavior in Drosophila.

目錄
致謝 1
中文摘要 2
Abstract 3
1. Introduction 4
2. Materials and Methods 7
2.1 Fly Stocks 7
2.2 Sample Preparation and Immunohistochemistry 7
2.3 Confocal Microscopy and Image Processing 9
3. Results 10
3.1 The Strategy of intersection tool building procedure 10
3.2 Screening ET-FLP lines 10
3.3 Classification of ET-FLP lines pattern 11
3.4 Defined region stable pattern from ET-FLP lines 12
3.5 Search the predict expression pattern from FlyCircuit. 13
3.6 Demonstrate the Mushroom body α/β lobe by using intersection tools 13
4. Discussion 16
5. References 19
6. Figures and Figure legends 21
7. Tables 38
8. Appendix Figures 42

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