by Ng Mei Yu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 173-183). / Abstracts in English and Chinese. / Acknowledgements --- p.2 / Abbreviations --- p.3 / Abstracts --- p.4 / List of figures and tables --- p.7 / Contents Page No / General Introduction --- p.13 / Chapter CHAPTER ONE --- Biological Characterization of A431 Cells & SiHa Cells Under Different Microenvironments --- p.16 / Chapter 1.1 --- Introduction --- p.17 / Chapter 1.1.1 --- Microenvironment Surrounding Tumor Cells --- p.18 / Chapter 1.1.2 --- Hypoxic Environment --- p.20 / Chapter 1.1.2.1 --- The Hypoxic Chamber --- p.20 / Chapter 1.1.3 --- Reoxygenation --- p.22 / Chapter 1.1.4 --- Acidic Environment --- p.23 / Chapter 1.1.5 --- Glucose Depletion --- p.24 / Chapter 1.1.6 --- Irradiation --- p.25 / Chapter 1.2 --- Objectives --- p.26 / Chapter 1.3 --- Materials and Methods --- p.27 / Chapter 1.3.1 --- Materials --- p.27 / Chapter 1.3.2 --- Methods --- p.29 / Chapter 1.3.2.1 --- Cell Lines --- p.29 / Chapter 1.3.2.2 --- The Working Procedure for the Hypoxic Chamber --- p.30 / Chapter 1.3.2.3 --- "Aerobic, Hypoxic and Reoxygenated Conditions" --- p.33 / Chapter 1.3.2.4 --- Acidic Condition --- p.35 / Chapter 1.3.2.5 --- Glucose Depleted Condition --- p.36 / Chapter 1.3.2.6 --- Gamma-Irradiation --- p.37 / Chapter 1.3.2.7 --- Analysis of the Growth Pattern by MTT Assay and Cell Counting --- p.38 / Chapter 1.3.2.8 --- Cell Cycle Analysis --- p.39 / Chapter 1.3.2.9 --- Western Blot Analysis --- p.40 / Chapter 1.3.2.10 --- DNA Fragmentation Analysis --- p.42 / Chapter 1.4 --- Results --- p.43 / Chapter 1.4.1 --- Cell Proliferation Profile by MTT Assay --- p.43 / Chapter 1.4.1.1 --- Proliferation of cells under hypoxia --- p.43 / Chapter 1.4.1.2 --- Proliferation of cells under acidic pH environments --- p.49 / Chapter 1.4.1.3 --- Proliferation of cells under glucose depleted environment --- p.52 / Chapter 1.4.2 --- Distribution of cell cycles under different micro environments --- p.54 / Chapter 1.4.3 --- General Protein Expression Pattern by Western Blot Analysis --- p.57 / Chapter 1.4.4 --- Detection of Apoptosis by DNA Fragmentation Assay --- p.59 / Chapter 1.5 --- Discussion --- p.58 / Chapter CHAPTER TWO --- REACTION KINETICS OF A431 CELLS AND SiHa CELLS INDUCED BY EGF --- p.71 / Chapter 2.1 --- Introduction --- p.72 / Chapter 2.1.1 --- Structure of EGF and EGFR --- p.74 / Chapter 2.1.2 --- EGF Signaling Pathway --- p.76 / Chapter 2.2 --- Objectives --- p.79 / Chapter 2.3 --- Materials and Methods --- p.80 / Chapter 2.3.1 --- Materials --- p.80 / Chapter 2.3.2 --- Methods --- p.82 / Chapter 2.3.2.1 --- Cell Lines --- p.82 / Chapter 2.3.2.2 --- EGF Sensitivity Assay --- p.83 / Chapter 2.3.2.3 --- Combination Effect of Hypoxia and EGF --- p.83 / Chapter 2.3.2.4 --- Early Kinetics Analysis by Low EGF Concentration Treatment --- p.84 / Chapter 2.3.2.5 --- Late Kinetics Analysis by High EGF Concentration Treatment --- p.85 / Chapter 2.4 --- Results --- p.86 / Chapter 2.4.1 --- Sensitivity of A431 cells and SiHa cells to EGF by MTT Assay --- p.86 / Chapter 2.4.2 --- Early/Late Kinetics of EGF induced protein tyrosine phosphorylation Pattern --- p.90 / Chapter 2.4.3 --- Raf protein expression --- p.96 / Chapter 2.4.4 --- EGFR expression level --- p.100 / Chapter 2.5 --- Discussions --- p.104 / Chapter CHAPTER THREE --- IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN A431 CELLS BY DIFFERENTIAL DISPLAY UNDER DIFFERENT TUMOR MICROENVIRONMENTS --- p.107 / Chapter 3.1 --- Introduction --- p.108 / Chapter 3.2 --- Materials and Methods --- p.112 / Chapter 3.2.1 --- Materials --- p.112 / Chapter 3.2.2 --- Methods --- p.114 / Chapter 3.2.2.1 --- Spheroid Cells --- p.114 / Chapter 3.2.2.2 --- Identification of Differentally Expressed Genes by RT-PCR --- p.117 / Chapter 3.2.2.3 --- Ligation and Cloning of Differentially Expressed cDNA --- p.120 / Chapter 3.2.2.4 --- Screening and Sequencing of the cDNA Inserts --- p.121 / Chapter 3.2.2.5 --- Northern Blot Analysis --- p.123 / Chapter 3.3 --- Results --- p.124 / Chapter 3.4 --- Discussions --- p.161 / GENERAL CONCLUSION --- p.165 / REFERENCES --- p.167

Tse Ka Ling Carol. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 72-76). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Factor Analysis Model --- p.1 / Chapter 1.2 --- Main Objectives --- p.2 / Chapter 1.2.1 --- Investigate the distribution of the estimated Factor Scores --- p.2 / Chapter 1.2.2 --- Propose an alternative method for getting the estimates of the LISREL model --- p.4 / Chapter 1.3 --- Summary --- p.4 / Chapter 2 --- Joint Bayesian Approach of the Factor Analysis Model --- p.6 / Chapter 2.1 --- Conditional Distribution --- p.7 / Chapter 2.1.1 --- Conditional distribution of Z given Y and θ --- p.7 / Chapter 2.1.2 --- Conditional distribution of θ given Y and Z --- p.7 / Chapter 2.2 --- Implementation of the Gibbs sampler for generating the random observations --- p.11 / Chapter 2.3 --- Bayesian Estimates and their Statistical Properties --- p.13 / Chapter 2.3.1 --- Estimates of unknown parameter --- p.13 / Chapter 2.3.2 --- Estimates of Factor Score --- p.14 / Chapter 3 --- Examine the distribution of the estimated factor scores --- p.15 / Chapter 3.1 --- The 1st Simulation Study --- p.15 / Chapter 3.2 --- The 2nd Simulation Study --- p.30 / Chapter 3.3 --- The 3rd Simulation Study --- p.31 / Chapter 4 --- An Alternative method for getting the parameter estimatesin the LISREL Model --- p.44 / Chapter 4.1 --- Full LISREL model --- p.44 / Chapter 4.2 --- Our proposed method --- p.46 / Chapter 4.3 --- Simulation Studies --- p.49 / Chapter 4.3.1 --- The 1st Simulation Study --- p.49 / Chapter 4.3.2 --- The 3rd Simulation Study --- p.50 / Chapter 4.4 --- Conclusion --- p.53 / Appendix --- p.56 / Bibliography --- p.72

We consider a Bayesian approach to the study of independence in a two-way contingency table obtained from a two-stage cluster sampling design. We study the association between two categorical variables when (a) there are no covariates and (b) there are covariates at both unit and cluster levels. Our main idea for the Bayesian test of independence is to convert the cluster sample into an equivalent simple random sample which provides a surrogate of the original sample. Then, this surrogate sample is used to compute the Bayes factor to make an inference about independence. For the test of independence without covariates, the Rao-Scott corrections to the standard chi-squared (or likelihood ratio) statistic were developed. They are ``large sample' methods and provide appropriate inference when there are large cell counts. However, they are less successful when there are small cell counts. We have developed the methodology to overcome the limitations of Rao-Scott correction. We have used a hierarchical Bayesian model to convert the observed cluster samples to simple random samples. This provides the surrogate samples which can be used to derive the distribution of the Bayes factor to make an inference about independence. We have used a sampling-based method to fit the model. For the test of independence with covariates, we first convert the cluster sample with covariates to a cluster sample without covariates. We use multinomial logistic regression model with random effects to accommodate the cluster effects. Our idea is to fit the cluster samples to the random effect models and predict the new samples by adjusting with the covariates. This provides the cluster sample without covariates. We then use a hierarchical Bayesian model to convert this cluster sample to a simple random sample which allows us to calculate the Bayes factor to make an inference about independence. We use Markov chain Monte Carlo methods to fit our models. We apply our first method to the Third International Mathematics and Science Study (1995) for third grade U.S. students in which we study the association between the mathematics test scores and the communities the students come from, and science test scores and the communities the students come from. We also provide a simulation study which establishes our methodology as a viable alternative to the Rao-Scott approximations for relatively small two-stage cluster samples. We apply our second method to the data from the Trend in International Mathematics and Science Study (2007) for fourth grade U.S. students to assess the association between the mathematics and science scores represented as categorical variables and also provide the simulation study. The result shows that if there is strong association between two categorical variables, there is no difference between the significance of the test in using the model (a) with covariates and (b) without covariates. However, in simulation studies, there is a noticeable difference in the significance of the test between the two models when there are borderline cases (i.e., situations where there is marginal significance).

BACKGROUND: Atrial Fibrillation (AF) is the most common cardiac arrhythmia, affecting over 3 million Americans. Many people who suffer from AF have pre-disposing factors such as hypertension, ischemia, and structural heart disease, but recent research has also demonstrated the importance of genetic factors that can contribute to AF. In the present study, we sought to determine the causative mutation in a family with AF, atrial septal, and ventricular septal defects. METHODS: We evaluated a pedigree with 16 family members, one of whom had an ASD, one a VSD, and three had AF. Exome sequencing was performed on three of the five affected family members followed by confirmation with Sanger sequencing in all family members. A separate cohort from the MGH AF Study with early-onset AF (age at onset 47.1 ± 10.9 years, 79.3% male) was also screened for mutations using a combination of Sanger sequencing and high resolution melting. Variants were then functionally characterized using reporter assays in a mammalian cell line using wild-type and mutant constructs driving NPPA, αMHC and NPPB promoter reporters. RESULTS: Exome sequencing of the three affected individuals in the family identified a highly conserved mutation, R585L, in the transcription factor gene, GATA6. We also identified three additional GATA6 variants (P91S, A177T, and A543G) in the cases with early-onset AF from the MGH AF Study. We found that three of the four variants had a marked upregulation of luciferase activity (R585L; 4.1 fold, p<0.0001; P91S; 2.5 fold, p=0.0002; A177T; 1.7 fold, p=0.03). Additionally, when co-overexpressed with GATA4 and MEF2C, all GATA6 variants exhibited upregulation of the αMHC and NPPA activity compared to control. CONCLUSION: Overall, we found gain-of-function mutations in GATA6 in both a family with early-onset AF and atrioventricular septal defects as well as in patients with sporadic, early-onset AF. This evidence suggests that specific gain of function mutations in GATA6 contribute to the development of AF. / 2017-06-16T00:00:00Z

Ko Samuel. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (p. 230-252). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Chan Chi-bun. / "May 2003." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (p. 162-185). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Kok Dick Shun , Louis. / Thesis (Ph.D.)--Chinese University of Honbg Kong, 1997. / Includes bibliographical references (p. i-xiii). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web.

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Cellular development and function necessitate precise patterns of gene expression. Control of gene expression is in part orchestrated by a class of remote regulatory elements, termed enhancers, which are brought into contact with promoters via DNA looping. Enhancers typically contain clusters of transcription factor binding sites, and TF recruitment to them is thought to play a key role in transcriptional control. In this thesis I have addressed two issues regarding gene regulation by enhancers. First, with recent genome-wide enhancer mapping, it is becoming increasingly apparent that genes are commonly regulated by multiple enhancers in the same cell type. How a gene’s regulatory information is encoded across multiple enhancers, however, is still not fully understood. Second, numerous recent studies have found that enhancers are enriched for expression-modulating and disease-associated genetic variants. However, understanding and predicting the effects of enhancer variants remains a major challenge. I focussed on a human lymphoblastoid cell line (LCL), GM12878, for which ChIP-Seq data are available for 52 different TFs from the ENCODE project. Significantly, Promoter Capture Hi-C data for the same LCL are available, making it possible to link enhancers to target genes globally. In the first part of the thesis, I investigated how gene regulatory information is encoded across enhancers. Specifically, I asked whether a gene tends to use multiple enhancers to bring the same or distinct regulatory information. I found that there was a general trend towards a “shadow” enhancer architecture, whereby similar combinations of TFs were recruited to multiple enhancers. However, numerous examples of “integrating” enhancers were observed, where the same gene showed large variation in TF binding across enhancers. Distinct groups of TFs were associated with these contrasting models of TF enhancer binding. To investigate the functional effects of variation at enhancers, I additionally took advantage of a panel of LCLs derived from 359 individuals, which have been genotyped by the 1000 Genomes Project, and for which RNA-Seq data are publically available. I used TF binding models to computationally predict variants impacting TF binding, and tested the association of these variants with the expression of the target genes they contact based on Promoter Capture Hi-C. Compared to the standard eQTL calling approach, this offers increased sensitivity as only variants physically contacting the promoter and predicted to impact TF binding are tested. Using this approach, I discovered a set of predicted TF-binding affinity variants at distal regions that associate with gene expression. Interestingly, a large proportion of these binding variants fall at the promoters of other genes. This finding suggests that some promoters may be able to act in an enhancer-like manner via long-range interactions, consistent with very recent findings from alternative approaches.

Multicellular organisms are composed of a number of different specialised cells that all carry the same genetic material but are highly divergent in their functions and characteristics. This diversity is only allowed because sets of specific genes are expressed in one type of cells and silent in others. A precise control mechanism is required to fine-tune gene regulation and relies on chromatin structure and regulatory proteins. One of the largest families of DNA-binding factors that influence this in human and mouse is the KRAB zinc finger protein (KZFP) family. KZFPs are thought to have rapidly evolved alongside transposable elements and be mediators of transcriptional repression. The few KZFPs that have been characterised so far have been shown to be involved in a wide range of regulatory and biological processes; hence it is hard to make functional generalisations. During my PhD, I studied one member of the KZFP family in mouse, ZFP263, with the aim of understanding its mechanism of action in mouse embryonic stem cells (mESCs) and its role in mice. My work has shown that ZFP263 is an ancient protein highly conserved in mammals and under purifying selection. One of its two functional domains however is divergent from the consensus sequence found in most KZFPs and suggests that ZFP263 might have lost the ability to recruit repressive chromatin states. My research identified the targets of ZFP263 binding in mESCs and showed that it does not bind and silence transposable elements. Indeed it targets unique regions of the genome, mostly within transcribed regions of genes. These genes show a wide range of expression levels and are involved in several key biological processes. Surprisingly, binding sites are not associated with the canonical KZFP co-factor but mostly co-localize with active histone marks. My findings lead me to hypothesise that ZFP263 has evolved to target active epigenetic states to unique regions that are positive regulators of transcription, in contrast to the more canonical model of KZFP function. To test this hypothesis, I have generated targeted mutations at Zfp263 in mice using CRISPR-Cas9 and my preliminary results suggest that Zfp263 mutants have growth defects indicating a role for this protein in mouse development. My findings indicate that ZFP263 is a unique KZFP with non-canonical properties and provide novel insights into the evolution and functions of KZFPs in mammals.