Regulatory mechanisms defining the blastocyst cell lineages

REGULATORY MECHANISMS DEFINING THE BLASTOCYST CELL LINEAGES GUO GUOJI (B.S WHU) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF BIOLOGICAL SCIENCES NATIONAL UNIVERSITY OF SINGAPORE 2009 Acknowledgements I would like to thank my supervisor Paul Robson for all his support and guidance During my past four years of Ph.D life, he gave me the freedom to try whatever I want, while supporting me with whatever he had This freedom eventually freed my mind in the area of science and in other aspects of my life too I would like to thank my co-supervisor Hong Yunhan for his valuable suggestions on my career life He has been a good mentor, ever since I started applying for NUS, and he will continue to guide me in the area of science after I graduate I owe my special thanks to Erik Mikael Huss and Neil Clarke for their expertise in bioinformatics analysis Their unique interpretation on the single cell data introduced me into the area of systems biology, which I believe should be a cornerstone of future bioscience research I want to thank Tong Guoqing for teaching me how to work on mouse embryos His extensive transcription factor expression data (which is discussed in this thesis) built up the basis for my study I also want to thank other members in the lab that either directly or indirectly contributed to my work I would like to thank Amy Ralston and Janet Rossant for their generous offer of mouse lines and cell lines as well as valuable suggestions during the collaboration I also would like to thank Magdalena Zernicka-Goetz and members of her lab for collaborative work on the characterization of the developmental bias in early blastomeres Finally I want to thank Davor Solter and Barbara Knowles for their insightful suggestions on my project Table of Contents Acknowledgements Table of Contents Summary List of Figures List of Abbreviations Chapter Overview 1.1 Mouse preimplantation development 1.2 Current controversies 1.3 Technical problems 1.4 Research objectives 11 11 12 13 14 Chapter Literature Review 2.1 Early cleavages and developmental bias 2.2 Compaction and polarization 2.3 Heterogeneity in the ICM 2.4 The selector gene model 2.5 Stem cells from the blastocyst 2.6 Important pathways 2.6.1 Cell adhesion 2.6.2 Protein kinase C 2.6.3 Fibroblast growth factor 2.6.4 Mitogen-activated protein kinases 2.7 Key transcription factors 2.7.1 Oct4, Sox2 and Nanog 2.7.2 Cdx2, Eomes and Tead4 2.7.3 Gata6 and Gata4 2.8 Common research methods 2.9 Single cell gene expression profiling 16 16 18 20 21 22 23 23 24 25 26 27 27 30 32 33 35 Chapter Methods 3.1 Cell culture 3.2 RNA extraction, realtime PCR and gene expression microarray 3.3 Embryo collection and culture 3.4 Immunocytochemical staining 3.5 Embryo treatment with specific pathway inhibitors 3.6 Gene expression profiling of pre-implantation embryos 3.7 Isolation of single cells from pre-implantation embryos 3.8 High throughput single cell qPCR 3.9 Blastocyst RNA titration series 3.10 Single cell data processing 3.11 Single cell data visualization 3.12 mRNA copy count in single cells 42 42 42 43 44 45 45 46 47 49 52 52 53 Chapter Results 4.1 Identification of candidate transcription factors for single cell analysis 4.2 Single cell expression profiling 4.3 Dynamic gene expression pattern through preimplantation Development 4.3.1 Single cell developmental heatmap 4.3.2 Cellular differentiation dynamics 4.3.3 Developmental profiles of individual genes 4.3.4 Stage specific principle components 4.3.5 Expression level distribution 4.4 Poised state of 16-cell blastomeres 79 4.5 Earliest differences during TE/ICM segregation 4.6 Earliest differences during EPI/PE segregation 4.7 Disruption of cell adhesion 4.8 aPKC signals activate the TE program 4.9 Inhibition of MAPK during the 8-cell to 16-cell transition 4.10 FGF signalling is required for EPI/PE lineage segregation 4.11 The role of zygotic Sox2 in the inner cells 4.12 Inducible Cdx2 overexpression in ES cells 4.13 Analysis of Cdx2 knockout embryos 4.14 Cdx2 correlation map 54 82 85 89 92 94 96 97 99 101 104 Chapter Discussion 5.1 Model for blastocyst lineage decision 5.2 Biased development and stochastic patterning 5.3 Independent regulation of different transcriptional factors 5.4 Single cell methodology 107 107 112 115 117 Chapter Implications 123 Bibliography 126 54 59 65 65 69 72 75 78 Summary The first cellular differentiation event in mouse development leads to the formation of the blastocyst consisting of the inner cell mass (ICM) and a functional epithelium (trophectoderm; TE) The ICM shortly thereafter gives rise to the pluripotent epiblast (EPI) and the extra-embryonic primitive endoderm (PE) The molecular mechanisms that regulate the differentiation of totipotent blastomeres to the three distinct cell types remain unclear In my thesis, by utilizing microfluidic technology and TaqMan realtime PCR, I have achieved high throughput gene expression quantification in single cells I applied the single cell technology to profile the expression of 48 genes, in parallel, from more than 576 individual cells harvested throughout preimplantation development I found clear gene expression signatures defining the earliest differentiated cell lineages (TE, EPI and PE) I was able to show that each blastomere at the 16-cell stage abundantly expresses numerous transcription factors that subsequently become lineage-restricted Next, I perturbed the preimplantation developmental system with specific pathway inhibitors, and show that external signal is crucial to the proper differentiation of the blastocyst cell lineages Finally, I characterized the role of a key TE lineage transcription factor Cdx2 during the first cellular differentiation using inducible overexpression cell lines as well as the knockout embryos I show that Cdx2 activates TE transcriptional program while repressing the totipotent network The study integrated the external signalling pathways with the core internal transcriptional network through the differentiation of the blastocyst lineages and dramatized the power of single cell analysis to provide insight into developmental mechanisms List of Figures Figure 1.1: Mouse preimplantation development 12 Figure 2.1: Blastocyst lineage selector genes 22 Figure 2.2: High throughput single cell qPCR 40 Figure 3.1: Blastocyst RNA titration series and background determination 51 Figure 4.1: Histogram of TE specificity of different genes in the E4.5 blastocyst 56 Figure 4.2: Immunostaining of TE specific transcription factors in the blastocyst 56 Figure 4.3: Expression dynamics of lineage specific transcription factors in whole embryos 57 Figure 4.4: Gene expression heatmap of ~64-cell stage single cells 61 Figure 4.5: Principal component (PC) projections ~64-cell stage single cells 63 Figure 4.6: PC projections of the 48 genes 64 Figure 4.7: Single cell expression heatmap from 1-cell to ~64-cell stage 68 Figure 4.8: Single cell expression projections from 1-cell to 8-cell stage 70 Figure 4.9: Single cell expression projections from 8-cell stage to ~32-cell stage 71 Figure 4.10: Profiles of individual genes through preimplantation development 75 Figure 4.11: Principal component analysis of single cell data for different developmental stages Figure 4.12: Distribution of gene expression levels in single cells 78 79 Figure 4.13: Expression levels from 8-cell through to the ~64-cell stage for six lineage specific transcription factors Figure 4.14: mRNA copy number verification by digital PCR 80 82 Figure 4.15: Earliest difference during TE/ICM segregation 83 Figure 4.16: Expression fold difference between labeled outer and inner cells 85 Figure 4.17: Box plots of expression level distributions across developmental stages and predicted cell types for Fgf4 and Fgfr2 87 Figure 4.18: Expression levels of EPI- and PE-associated signalling molecules and transcription factors shown as pie plots Figure 4.19: Variation of EPI- and PE-associated genes across ICM cells 88 89 Figure 4.20: Compaction is not required for the activation of the TE transcriptional program 91 Figure 4.21: aPKC inhibition blocks the activation of the TE program 92 Figure 4.22: The effect of Gö6983 on mouse embryos during compaction 93 Figure 4.23: Summary of PKC inhibitor treatments 94 Figure 4.24: The effect of treatment with different MAPK inhibitors on compacting embryos 96 Figure 4.25: FGF signalling is required for PE differentiation 97 Figure 4.26: Sox2 during preimplantation development 99 Figure 4.27: Gene expression changes after inducible Cdx2 overexpression in ES cells 101 Figure 4.28: Gene expression profiling of blastocysts derived from Cdx2 heterozygous intercrosses 104 Figure 4.29: Expression correlation map of different genes to Cdx2 106 Figure 5.1: Molecular mechanism of blastocyst lineage segregation 108 List of Tables Table 1: Number of cells analyzed at different stages Information about labelled cells is shown in red letters 44 Table 2: List of the 48 Taqman gene expression assays used in the sing cell gene expression analysis 49 Table 3: The top three inversely correlated genes within the ~32-cell and ~64-cell stage ICM 87 List of Abbreviations c/n/aPKC Conventional/novel/atypical protein kinase C BIM Bisindolylmaleimide BSA Bovine serum albumin CD Cytochalasin D ChIP-seq Chromatin immunoprecipitation + sequencing Ct Threshold cycle DAPI 4'-6-Diamidino-2-phenylindole DMEM Dulbecco’s modified eagle’s medium DMSO Dimethyl sulfoxide EDTA Ethylene diamine tetraacetic acid EGFP Enhanced green fluorescent proteins EGTA Ethylene glycol tetraacetic acid EPI Epiblast ERK Extracellular signal-regulated kinase EST Expressed sequence tag ES cell Embryonic stem cell FACS Fluorescence-activated cell sorting FBS Fetal bovine serum FGF Fibroblast growth factor GFP Green fluorescent protein hCG Human chorionic gonadotropin ICM Inner cell mass JNK c-Jun N-terminal kinases KSOM Potassium simplex optimization medium LIF Leukemia inhibitory factor MAPK Mitogen-activated protein kinase MEF Mouse embryonic fibroblast MEK Mitogen-activated protein kinase kinase MGI Mouse genome informatic NCBI National center for biotechnology information PCA Principal component analysis PC Principal component PE Primitive endoderm PMSG Pregnant mare serum gonadotropin qPCR Quantitative realtime PCR RNAi RNA interference RNA-seq mRNA sequencing TE Trophectoderm TF Transcription factor TS cell Trophoblast stem cell XEN cell Extraembryonic endoderm cell 10 Loh, Y H., Wu, Q., Chew, J L., Vega, V B., Zhang, W., Chen, X., Bourque, G., George, J., Leong, B., Liu, J., et al (2006) The Oct4 and Nanog transcription network regulates pluripotency in mouse embryonic stem cells Nat Genet 38, 431-440 Lorentz, O., Cadoret, A., Duluc, I., Capeau, J., Gespach, C., Cherqui, G., and Freund, J N (1999) Downregulation of the colon tumour-suppressor homeobox gene Cdx-2 by oncogenic ras Oncogene 18, 87-92 Lorthongpanich, C., Yang, S H., 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