表觀基因控制機制（epigenetic regulation）可解釋為在基因體上控制各基因位點開啟或關閉的機制。因此，表觀基因特徵往往決定了基因轉錄表現及細胞身份。表觀基因體亦具有遺傳特性。因此在細胞命運決定過程中，表觀基因不但參與分化進程，並能保存分化「記憶」並依此進行後繼調控。表觀基因控制機制概括涵蓋DNA甲基化修飾（DNA methylation）、組蛋白修飾（histone modification）、功能性非編碼RNA（functional non-coding RNA）等多層次分子控制機制。因此，表觀基因控制機制如何系統性影響細胞命運決定，變成為相當值得研究的課題。我在這篇論文中提出兩個研究主題，主旨皆在以系統生物學方法，分析探討在不同發育位置和發育時間上，表觀基因調控對細胞命運決定的影響。本論文使用雞為模式生物。
在第一個研究主題中（第二章），我們知道雞的背部羽毛生成皮膚和蹠部鱗片生成皮膚構型上有顯著差異，但文獻指出未分化的早期胚胎表皮可在一段短暫期間內，依照所接觸的真皮層決定分化進程。我認為表皮的表觀基因控制機制，尤其在增強子（enhancer）調控方面，可能反應真皮層訊號，從而參與此命運決定現象。在合作夥伴的協助下，我們以無偏見餘弦相似性（cosine similarity）分析20組涵蓋分化、未分化、表皮、真皮、背部、蹠部的微陣列基因表現資料，並發現鈣離子訊號網路基因可能系統性參與並影響表皮命運決定的進程。我更進一步克服未分化表皮細胞不足的弊端，以微量細胞進行染色質免疫沉澱定序分析（ChIP-seq），取得增強子調控相關的組蛋白修飾位點，並藉此得知早期未分化細胞在鈣離子訊號網路基因的增強子活動上已有的不同，並可能依此引導表皮命運決定的進程。
在第二個研究主題中（第三章），已知PIWI/piRNA調控路徑在抑制跳躍子（transposable elements）機制中扮演重要角色。但是目前學界對piRNA的前驅體—piRNA基因簇（piRNA cluster）的轉錄調控所知甚少。在已知piRNA基因簇和蛋白表現基因同是經由第二型RNA聚合酶（Pol II）轉錄的情況下，我進一步假設一些與Pol II合作的轉錄因子也可能參與piRNA基因簇的轉錄調控。我與研究同儕合作設計並優化判定piRNA序列的生物資訊分析平台，取得雞胚盤細胞piRNA、第11天及第14天的雄雞胚胎生殖腺、與雄雞睪丸的piRNA資料。我發現雞性腺piRNA會循發育階段，逐漸由跳躍子相關的piRNA序列轉為基因間區段（intergenic region）相關的piRNA序列。我在進一步分析piRNA基因簇表現時，發現階段性表現的piRNA基因簇通常具有階段性表現的轉錄因子的作用位點，顯示兩者的相關性。在延伸研究時我意外發現，在第11天及第14天的雄雞胚胎生殖腺高量表現的piRNA可能參與抑制神經發育相關基因的轉錄。這個發現暗示piRNA可能參與抑制生殖細胞往非生殖細胞方向分化。
對於本論文探討的兩個主題中，我實踐運用系統生物學的分析理論及方法，綜合生物資訊、生物統計、及細胞與分子生物學操作，找出兩種表觀基因在細胞命運決定時的調控機制，並對表觀基因調控在發育上的影響產生更深一層的認知。

Epigenetic regulation describes multiple layers of signatures that are involved in governing the accessibilities of genomic regions. These signatures hence configure the gene expression patterns that define cell identity as well as drive cell fate decision. Additionally, epigenomes are mitotically heritable that serve to “remember” the differentiation progress and prepare for further modulation. Nevertheless, the relationships between epigenetic regulation and cell fate decision involved in many faces that have yet been understood. This thesis is comprised by two separate hypothesis, but all pointing to the understanding of spatiotemporal regulation of epigenome that lead to cell fate commitment. Here, chicken is used as the model organism in this thesis.
In my first project (chapter 2), given feather forming dorsal skin and scale forming metatarsal skin display dramatically different characteristics, but was found having interchangeable fate in early embryonic skin epithelium. How primal skins can develop into distinct features is becoming of interest. I hypothesize that region specific differentiation of skin epithelium cells is, at least partially, regulated by specific regulatory pathways and histone modification machineries triggered by mesenchymal signaling. In collaboration efforts, we applied unbiased cosine similarity analysis on 20 microarray expression profiles of undifferentiated and differentiated epithelium and mesenchymes for dorsal and metatarsal skin regions, and found genes involved calcium signaling pathway are regulated spatiotemporally regulated in association with each skin part in question. For investigation of cis enhancer activities associated with these genes, I successfully applied ChIP-seq for small number of cells and solved the limitation of low cell yields from undifferentiated skins. The result identified the enhancer signatures on calcium signaling pathway subunits are correlated with their gene expression, and in turn favor the fate decision toward scale-forming skins.
In the next project (chapter 3), I was focused in PIWI/piRNA pathway which is an important epigenetic regulatory machinery in silencing transposable elements (TEs) during germ cell development. Nevertheless, transcriptional regulation of piRNA cluster, which crucially shape piRNA profiles, was scarcely reported, particularly for piRNA clusters localized on intergenic regions. PiRNA clusters are transcribed by Pol II as for typical genes. I hypothesize some specific transcriptional factors may be involved in stage-dependent piRNA cluster regulations. In collaboration with colleagues, we designed and optimized bioinformatics pipeline for piRNA candidate filtering. I found transition of piRNA profiles from TE associated piRNAs to intergenic region orientated piRNAs along development from blastodermal cell to adult, which the result imply stage dependent regulation. Based on transcription factor binding site analysis, I identified some transcription factors may be involved in the developmental stage-dependent expression of piRNA clusters. The expression analysis further showed most of these transcription factors are also regulated in stage-dependent manner. In extension of this study, I found the stage-dependently regulated piRNAs in E11 and E14 male gonads are preferentially targeting to genes involved in neurogenesis. This finding imply expression repression, and therefore likely suppress cell fate development toward neuron lineages.
In summary, I applied systems biology perspective to both research arms, and identified two epigenetic regulatory features that likely contribute to epigenomic landscape for cell fate decision. These discoveries contribute to the further understanding of how epigenomic regulation may be involved for cell fate decision.

TABLE OF CONTENTS
Acknowledgement ii
口試委員會審定書 iii
ABSTRACT iv
中文摘要 vi
Publications Arising from This Thesis viii
Publications viii
Manuscripts ix
Table of Contents x
List of Figures xv
List of Tables xviii
CHAPTER 1 Overview 19
1.1 Introduction 20
1.2 Epigenetics 21
1.3 DNA methylation 22
1.3.1 Addition and Maintenance of DNA Methylation 22
1.3.2 DNA demethylation 23
1.4 Histone modification 23
1.4.1 Histone Signatures associated with Transcriptional Regulation 24
1.5 Functional non-coding RNA 25
1.5.1 Dicer-dependent small RNAs 25
1.5.2 PIWI-interacting RNAs 26
1.5.3 Long non-coding RNAs 27
1.6 Epigenetic Memory and Reprogramming 27
1.7 Summary 28
1.8 References 29
CHAPTER 2 Emergence of Differentially Regulated Pathways Associated with the Development of Regional Specificity in Chicken Skin 36
2.1 Abstract 37
2.2 Background 38
2.3 Methods 41
2.3.1 Animal ethics statement 41
2.3.2 Microarray Profiles 41
2.3.3 Cosine Similarity Analysis 42
2.3.3-1 Seed (candidate genes) selection 43
2.3.3-2 Identification of genes co-regulated or reciprocally regulated with seeds 44
2.3.3-3 Identification of key regulators by exploratory data analysis 44
2.3.4 Sample Collection for Gene Expression and Chromatin Analysis 44
2.3.5 RNA Purification 45
2.3.6 Reverse Transcription-qPCR (RT-qPCR) 45
2.3.7 In Situ Hybridization 46
2.3.8 Chromatin Immunoprecipitation (ChIP)-next generation sequencing (ChIP-seq) and qPCR 46
2.4 Results and Discussion 47
2.4.1 Identification of Differentially Regulated and Co-regulated Pathways in Different Skin Regions Using Cosine Similarity Analysis 47
2.4.2 The calcium signaling pathway is differentially expressed in developing feather and scale regions 52
2.4.3 Potential enhancers for calcium channel genes are identified based on the specific combination of histone modifications 58
2.5 Conclusion 60
2.6 List of abbreviations 67
2.7 References 68
2.8 Appendix 76
CHAPTER 3 Developmental Stage-Dependent Regulation of piRNA Clusters in Chicken and Their Potential Roles in Cell Fate Decision toward Germ Cell Development 79
3.1 Abstract 80
3.2 Introduction 80
3.3 Material and Method 83
3.3.1 Bioinformatics filtering for piRNA candidates 83
3.3.2 Strand-specific RNA-seq analysis 85
3.3.3 piRNA cluster analysis 85
3.3.4 Transcription factor binding site enrichment analysis 86
3.3.5 Animals and tissue sample collection 87
3.3.6 PGC isolation and in vitro culture 87
3.3.7 Germ cell purification 87
3.3.8 Immunocytochemistry 88
3.3.9 Total RNA isolation and Reverse Transcription Real-time PCR (RT-qPCR) 88
3.4 Result 89
3.4.1 piRNA components and composition varied according to developmental stages 89
3.4.2 piRNA Cluster analysis identified stage-dependent piRNA cluster expression patterns 93
3.4.3 Transcription factors likely contribute to the regulation of stage-enriched piRNA clusters 96
3.4.4 piRNAs from embryonic gonadal piRNA clusters may be involved in repressing genes involve in neurogenesis 100
3.5 Discussion 104
3.5.1 Comparison of the piRNA features along germ cell developmental timelines between chicken and mouse 104
3.5.2 Ping-pong cycle analysis may imply changes in ping-pong cycle machineries in different developmental stages 105
3.5.3 Stage-dependently expressed transcription factors may be involved in stage-enriched piRNA clusters 106
3.5.4 Stage-dependent transcription factors may be involved in the transcription of stage-enriched piRNA clusters 106
3.5.5 PiRNAs originated from stage-enriched piRNA clusters may be involved in fine tuning germ line developmental pathway 107
3.6 Summary 109
3.7. List of abbreviations 109
3.8 Reference 110
3.9 Appendix 122
CHAPTER 4 Discussions and perspectives 127
4.1 Unbiased Analysis towards a System 128
4.2 A Shift of Focus from Skin Development to Germ Cell Development 129
4.3 Advantages and Limitation 130
4.3.1 Chicken is an interesting model for comparative study with mammal (mouse) 130
4.3.2 Knowledge bias using public available databases 131
4.4 Potential Follow-ups 132
4.4.1 Follow-up experimental design for investigating roles of calcium signaling in embryonic skin epithelium fate decision 132
4.4.2 Analysis on the correlations between stage-enriched piRNA clusters and their potentially associated transcription factors 133
4.5 Additional discoveries from this study 134
4.5.1 Additional discovery and discussions based on the calcium signaling associated differentiation settings for feather/scale skin development (Chapter 2) 134
4.5.2 Additional discovery and discussions based on stage-dependently regulate piRNA clusters (Chapter 3) 136
4.6 Summary 138
4.7 References 139


LIST OF FIGURES
Chapter 1
Figure 1. 1 Epigenomic settings pave the pathways for cell fate decision. 20
Chapter 2
Figure 2. 1 Cosine similarity analysis methodology for determining co-differentially regulated genes in the feather/scale region. 43
Figure 2. 2 Developmental progress of feather skin and scale skin. 48
Figure 2. 3 GSEA coupled with interaction pathway analysis on embryonic development GO terms. 49
Figure 2. 4 Differentially regulated genes involved in calcium signaling pathways. 53
Figure 2. 5 RT-qPCR validation of the differentially regulated calcium channel genes at the epithelium 55
Figure 2. 6 RT-qPCR for other calcium channel subunit genes. 56
Figure 2. 7 Whole mount in situ hybridization of CACNA1D and CACNA2D1 in E7 feather forming and E9 scale forming regions. 57
Figure 2. 8 ChIP-qPCR of the potential enhancer regions that may be associated with CACNA1D gene activities. 61
Figure 2. 9 ChIP-qPCR of the potential enhancer regions that may be associated with CACNA1H gene activities. 62
Figure 2. 10 ChIP-qPCR of the potential enhancer regions that may be associated with CACNA2D1 gene activities. 63
Figure 2. 11 ChIP-qPCR of the potential enhancer regions that may be associated with CACNA1C gene activities. 64
Figure 2. 12 ChIP-qPCR of the potential enhancer regions that may be associated with CACNA1G gene activities. 65
Figure 2. 13 ChIP-qPCR of the potential enhancer regions that may be associated with CACNA2D3 gene activities. 66
Chapter 3
Figure 3. 1 Bioinformatics analysis for identifying candidate piRNAs. 84
Figure 3. 2 Schematic presentation of merging piRNAs from multiple stages. 86
Figure 3. 3 Features of chicken piRNA Candidates 90
Figure 3. 4 Analysis for ping-pong cycle signature. 91
Figure 3. 5 Genomic association for piRNA candidates of stage-enriched sizes. 92
Figure 3. 6 piRNA cluster analysis and classification showing stage-dependent expression profiles of germ cell associated piRNA clusters. 94
Figure 3. 7 Analysis of germ cell properties to validate germ cell enrichment efficiency. 97
Figure 3. 8 Identification of transcription factors likely involved in stage dependent piRNA cluster regulation. 98
Figure 3. 9 Application of RT-qPCR to determine the expressions of picaTFs in circulating PGC (cPGC), E6 gonadal PGC (gPGC), and enriched germ cell populations from E11 gonad (E11G_Germ) and E14 gonad (E14G_Germ). 99
Figure 3. 10 Schematic representation of the regulation over piRNA clusters involve in the regulation over germ cell development. 100
Figure 3. 11 Target analysis for stage-enriched, cluster-able piRNAs. 101
Figure 3. 12 Ontology analysis for genes targeted by stage-enriched piRNAs, 102
Figure 3. 13 Application of RT-qPCR to evaluate expression pattern of genes involved in neurogenesis and targeted by stage-enriched piRNAs 103
Chapter 4
Figure 4. 1 Ordinary differential equations (ODE) used for dynamic modeling to exam negative crosstalk behaviors by WNT/β-catenin and WNT/Ca2+. 135
Figure 4. 2 Example of some piRNA clusters that may be conserved across high vertebrates but may be stage-dependently regulated. 136
Figure 4. 3 Example of varied piRNA targeting strength to ERVL family members in different germline developmental stages. 137


LIST OF TABLES
Chapter 2
Table 2. 1 Candidate microarray probes from the cosine similarity analysis. 50
Table 2. 2 Top 5 significant KEGG pathways identified based on the differentially regulated genes and co-regulated genes from cosine similarity analysis. 51

Supplementary Table 2. 1 Primer sets for RT-qPCR. 76
Supplementary Table 2. 2 Primer sets for ChIP-qPCR. 77
Supplementary Table 2. 3 KEGG pathways identified based on the differentially regulate genes and co-regulated genes from cosine similarity analysis. 78

Chapter 3
Table 3. 1 Cluster-able piRNAs before and after piRNA cluster merge 94
Table 3. 2 PiRNA clusters that embody TE sequences 95
Table 3. 3 TE associated Cluster-able piRNAs, by developmental stages 96

Supplementary Table 3 1 RT-qPCR primer sets 122

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Chapter 3
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Chapter 4
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