ΔNp63 REGULATES A COMPLEX NETWORK OF TARGET GENES IN LIMB AND EPIDERMAL DEVELOPMENT

The skin is composed of two major compartments, the dermis and epidermis. The epidermis forms a barrier to protect the body. The stratified epithelium has self-renewing capacity throughout life, and continuous turnover is mediated by stem cells in the basal layer. p63 is structurally and functionally related to p53. In spite of their structural similarities, p63 is critical for the development and maintenance of stratified epithelial tissues, unlike p53. p63 is highly expressed in the epidermis and previously has been shown to play a critical role in the development and maintenance of the epidermis. The study of p63 has been complicated due to the existence of multiple isoforms: those with a transactivation domain (TAp63) and those lacking this domain (ΔNp63). Mice lacking p63 cannot form skin, have craniofacial and skeletal defects and die within hours after birth. These defects are due to the ability of p63 to regulate multiple processes in skin development including epithelial stem cell proliferation, differentiation, and adherence programs. To determine the roles of these isoforms in skin development and maintenance, isoform specific p63 conditional knock out mice were generated by our lab. TAp63-/- mice age prematurely, develop blisters, and display wound-healing defects that result from hyperproliferation of dermal stem cells. That results in premature depletion of these cells, which are necessary for wound repair, that indicates TAp63 plays a role in dermal/epidermal maintenance. To study the role of ΔNp63, I generated a ΔNp63-/- mouse and analyzed the skin by performing immunofluorescence for markers of epithelial differentiation. The ΔNp63-/- mice developed a thin, disorganized epithelium but differentiation markers were expressed. Interestingly, the epidermis from ΔNp63-/- mice co-expressed K14 and K10 in the same cell suggesting defects in epidermal differentiation and stratification. This phenotype is reminiscent of the DGCR8fl/fl;K14Cre and Dicerfl/fl;K14Cre mice skin. Importantly, DGCR8-/- embryonic stem cells (ESCs) display a hyperproliferation defect by failure to silence pluripotency genes. Furthermore, I have observed that epidermal cells lacking ΔNp63 display a phenotype reminiscent of embryonic stem cells instead of keratinocytes. Thus, I hypothesize that genes involved in maintaining pluripotency, like Oct4, may be upregulated in the absence of ΔNp63. To test this, q-RT PCR was performed for Oct4 mRNA with wild type and ΔNp63-/- 18.5dpc embryo skin. I found that the level of Oct4 was dramatically increased in the absence of ΔNp63-/-. Based on these results, I hypothesized that ΔNp63 induces differentiation by silencing pluripotency regulators, Oct4, Sox2 and Nanog directly through the regulation of DGCR8. I found that DGCR8 restoration resulted in repression of Oct4, Sox2 and Nanog in ΔNp63-/- epidermal cells and rescue differentiation defects. Loss of ΔNp63 resulted in pluripotency that caused defect in proper differentiation and stem cell like phenotype. This led me to culture the ΔNp63-/- epidermal cells in neuronal cell culture media in order to address whether restoration of DGCR8 can transform epidermal cells to neuronal cells. I found that DGCR8 restoration resulted in a change in cell fate. I also found that miR470 and miR145 play a role in the induction of pluripotency by repressing Oct4, Sox2 and Nanog. This indicates that ΔNp63 induces terminal differentiation through the regulation of DGCR8.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

CREB trans-activation of disruptor of telomeric silencing-1 mediates forskolin inhibition of CTGF transcription in mesangial cells.

Connective tissue growth factor (CTGF) participates in diverse fibrotic processes including glomerulosclerosis. The adenylyl cyclase agonist forskolin inhibits CTGF expression in mesangial cells by unclear mechanisms. We recently reported that the histone H3K79 methyltransferase disruptor of telomeric silencing-1 (Dot1) suppresses CTGF gene expression in collecting duct cells (J Clin Invest 117: 773-783, 2007) and HEK 293 cells (J Biol Chem In press). In the present study, we characterized the involvement of Dot1 in mediating the inhibitory effect of forskolin on CTGF transcription in mouse mesangial cells. Overexpression of Dot1 or treatment with forskolin dramatically suppressed basal CTGF mRNA levels and CTGF promoter-luciferase activity, while hypermethylating H3K79 in chromatin associated with the CTGF promoter. siRNA knockdown of Dot1 abrogated the inhibitory effect of forskolin on CTGF mRNA expression. Analysis of the Dot1 promoter sequence identified a CREB response element (CRE) at -384/-380. Overexpression of CREB enhanced forskolin-stimulated Dot1 promoter activity. A constitutively active CREB mutant (CREB-VP16) strongly induced Dot1 promoter-luciferase activity, whereas overexpression of CREBdLZ-VP16, which lacks the CREB DNA-binding domain, abolished this activation. Mutation of the -384/-380 CRE resulted in 70% lower levels of Dot1 promoter activity. ChIP assays confirmed CREB binding to the Dot1 promoter in chromatin. We conclude that forskolin stimulates CREB-mediated trans-activation of the Dot1 gene, which leads to hypermethylation of histone H3K79 at the CTGF promoter, and inhibition of CTGF transcription. These data are the first to describe regulation of the Dot1 gene, and disclose a complex network of genetic and epigenetic controls on CTGF transcription.

Genes to blood pressure: The effects of variation in genes of the renin-angiotensin system on the hormonal and renal control of blood pressure

Objective. Essential hypertension affects 25% of the US adult population and is a leading contributor to morbidity and mortality. Because BP is a multifactorial phenotype that resists simple genetic analysis, intermediate phenotypes within the complex network of BP regulatory systems may be more accessible to genetic dissection. The Renin-Angiotensin System (RAS) is known to influence intermediate and long-term blood pressure regulation through alterations in vascular tone and renal sodium and fluid resorption. This dissertation examines associations between renin (REN), angiotensinogen (AGT), angiotensin-converting enzyme (ACE) and angiotensin II type 1 receptor (AT1) gene variation and interindividual differences in plasma hormone levels, renal hemodynamics, and BP homeostasis.^ Methods. A total of 150 unrelated men and 150 unrelated women, between 20.0 and 49.9 years of age and free of acute or chronic illness except for a history of hypertension (11 men and 7 women, all off medications), were studied after one week on a controlled sodium diet. RAS plasma hormone levels, renal hemodynamics and BP were determined prior to and during angiotensin II (Ang II) infusion. Individuals were genotyped by PCR for a variable number tandem repeat (VNTR) polymorphism in REN, and for the following restriction fragment length polymorphisms (RFLP): AGT M235T, ACE I/D, and AT1 A1166C. Associations between clinical measurements and allelic variation were examined using multiple linear regression statistical models.^ Results. Women homozygous for the AT1 1166C allele demonstrated higher intracellular levels of sodium (p = 0.044). Men homozygous for the AGT T235 allele demonstrated a blunted decrement in renal plasma flow in response to Ang II infusion (p = 0.0002). There were no significant associations between RAS gene variation and interindividual variation in RAS plasma hormone levels or BP.^ Conclusions. Rather than identifying new BP controlling genes or alleles, the study paradigm employed in this thesis (i.e., measured genes, controlled environments and interventions) may provide mechanistic insight into how candidate genes affect BP homeostasis. ^

A study in the molecular and cellular functions of GSK3beta in prostate adenocarcinoma

Kinases are part of a complex network of signaling pathways that enable a cell to respond to changes in environmental conditions in a regulated and coordinated way. For example, Glycogen Synthase Kinase 3 beta (GSK3β) modulates conformational changes, protein-protein interaction, protein degradation, and activation of unique domains in proteins that transduce signals from the extracellular milieu to the nucleus. ^ In this project, I investigated the expression and function that GSK3β exhibits in prostate cells. The capacity of GSK3β to regulate two transcription factors (JUN and CREB), which are known to be inversely utilized in prostate tumor cells, was measured. JUN/AP1 is constitutively activated in PC-3 cells; whereas, CREB/CRE activity is ∼20 fold less than the former. GSK3β overexpression obliterates JUN/AP1 activity. With respect to CREB GSK3β increases CREB/CRE activity. Cellular levels of active GSK3β can determine whether JUN or CREB is preferentially active in the PC-3s. Theoretically, in response to a particular cellular context or stimulus, a cell may coordinate JUN and CREB function by regulating GSK3β.^ A comparison of various prostate cell lines showed that active GSK3β is less expressed in normal prostate epithelial cells than in tumor cells. Differentially expressed active (GSK3β) may correlate with progression of prostate carcinoma. If a known marker associated with carcinoma of the prostate could be shown to be regulated by GSK3β then, further study of GSK3β may lead to a better understanding of both possible prevention of the disease and improved therapy for advanced stages. ^ The androgen receptor (AR) is an intriguing phosphoprotein whose regulation is potentially determined by a variety of kinases. One of these is (GSK3β) I found that (GSK3β) is a regulator of the androgen receptor in both the unliganded and liganded states. It can inhibit AR function as measured by reporter assays. Also, GSK3β associates with the AR at the DNA binding domain because deletion constructs expressing either the n-terminus or the c-terminus (both having the DBD in common) immunoprecipitated with GSK3β. Increased understanding of how GSK3β functions in prostate cancer would provide clues into how (1) certain signal pathways are coordinated and (2) the androgen receptor may be regulated. ^

Mammalian Snm1 participates in cellular responses to genotoxic and mitotic stress

Eukaryotic cells have evolved a complex network of metabolic processes and regulatory systems to help ensure that hereditary information is protected or restored when exposed to genotoxic agents. Two members of the Snm1 protein family have been characterized; scSNM1/PSO2, a yeast gene responsible for repair of DNA interstrand crosslinks, and hARTEMIS, a human gene that is mutated in radiosensitive severe combined immunodeficiency (RS-SCID). Here we report on another member of this protein family, hSNM1, and its response to DNA damage and mitotic stress. We have found that this protein colocalizes and physically associates with 53BP1, a crucial member of the mammalian response to DNA damage. In addition, hSnm1 interacts with several proteins involved in mitosis, and mSNM1 deficiency causes a mitotic checkpoint defect in mouse embryonic fibroblasts. ^

Bifurcation and singularity analysis of a molecular network for the induction of long-term memory.

Withdrawal reflexes of the mollusk Aplysia exhibit sensitization, a simple form of long-term memory (LTM). Sensitization is due, in part, to long-term facilitation (LTF) of sensorimotor neuron synapses. LTF is induced by the modulatory actions of serotonin (5-HT). Pettigrew et al. developed a computational model of the nonlinear intracellular signaling and gene network that underlies the induction of 5-HT-induced LTF. The model simulated empirical observations that repeated applications of 5-HT induce persistent activation of protein kinase A (PKA) and that this persistent activation requires a suprathreshold exposure of 5-HT. This study extends the analysis of the Pettigrew model by applying bifurcation analysis, singularity theory, and numerical simulation. Using singularity theory, classification diagrams of parameter space were constructed, identifying regions with qualitatively different steady-state behaviors. The graphical representation of these regions illustrates the robustness of these regions to changes in model parameters. Because persistent protein kinase A (PKA) activity correlates with Aplysia LTM, the analysis focuses on a positive feedback loop in the model that tends to maintain PKA activity. In this loop, PKA phosphorylates a transcription factor (TF-1), thereby increasing the expression of an ubiquitin hydrolase (Ap-Uch). Ap-Uch then acts to increase PKA activity, closing the loop. This positive feedback loop manifests multiple, coexisting steady states, or multiplicity, which provides a mechanism for a bistable switch in PKA activity. After the removal of 5-HT, the PKA activity either returns to its basal level (reversible switch) or remains at a high level (irreversible switch). Such an irreversible switch might be a mechanism that contributes to the persistence of LTM. The classification diagrams also identify parameters and processes that might be manipulated, perhaps pharmacologically, to enhance the induction of memory. Rational drug design, to affect complex processes such as memory formation, can benefit from this type of analysis.

B cell memory and idiotype network regulation

This investigation examined the clonal dynamics of B-cell expression and evaluated the role of idiotype network interactions in shaping the expressed secondary B-cell repertoire. Three interrelated experimental approaches were applied. The first approach was designed to distinguish between regulatory influences controlled by the major histocompatibility complex (MHC) and regulatory influences controlled by non-MHC factors including the idiotype network. This approach consisted of studies on the clonal dynamics and heterogeneity of the expressed IgG antibody repertoire of BALB/c mice. The second approach involved the analysis of the clonal dynamics of antibody responses of outbred rabbits. This analysis was coupled with studies to detect the occurrence and activity of constituents of the idiotype network. In the third approach the transfer of rabbit lymphocytes from immunized donors to MHC matched naive recipients was used to examine the effects of recipient non-MHC immunoregulatory influences on the expression of donor memory B-cells. Although many memory B cells were unaffected by non-MHC influences, these data show that non-MHC immunoregulatory influences can affect the expression of B-cells in the secondary response of inbred mice and outbred rabbits. The results also indicate that most IgG antibody responses are heterogeneous and are characterized by a stable group of dominant clonotypes. Clonal dominance and B-cell memory were found to be established early in an immune response. The expression of B memory clones appeared to be favored over the expression of virgin B cells. The injection of anti-tetanus antibody induced the antigen independent production of anti-tetanus antibody, probably through idiotypic mechanisms. These results demonstrate that both antibody and antigen can affect the expressed B-ceIl repertoire. Thus, idiotypic interactions are capable of influencing the expression of B-cells and these findings support the existence and function of an idiotype network with strong immunoregulatory potential. ^

Relating one's social support network to one's mid term grade

Much has been written about the relation of social support to health outcomes. Support networks were found to be predictive of health status. Not so clear was the manner in which social support helped the individual to avoid health complications. Whereas some aspects of the support network were protective, others were burdensome. Duties to one's network could serve as a stressor and duties outside one's network might stress the support system itself. Exposure to one's network was associated with certain health risks while disruption in one's social support network was associated with other health risks.^ Many factors contributed to the impact of a social support network upon the individual member: the characteristics of the individual, the individual's role or position within the network, qualities of the network and duties or indebtedness of the individual to the network. This investigation considered the possibility that performance could serve as a stressor in a fashion similar to an exposure to a health hazard.^ Because the literature includes many examples of studies in which the subjects were college students, academic progress is a performance common to most subjects. A profile of the support networks of successful students was contrasted with those of less successful students in this correlational study.^ What was uncovered in this investigation was a very complex web of interrelated constructs. Most aspects of the social support network did not significantly predict academic performance. Only a limited number of characteristics were associated with academic success: the frequency of support, student age, the existence of a 'mentor' within one' s network, and the extent to which one received a predominant source of support. Other factors had a tendency to be negatively correlated with midterm grade, suggesting those factors may impede academic performance.^ Medical status did not predict grades, but was correlated with many aspects of the network. Disruptions in particular parts of one's network were correlated with particular health categories. In fact, disruption in social support was more predictive of academic outcomes than medical complications. Whereas the individual's values were related to the contributing factors, only the individual's satisfaction with certain aspects of the support network were predictive of higher midterm grades in a psychology class. Dissatisfaction was associated with lower grades, suggesting a disruptive effect within the network. Associations among the features of support networks which predicted academic progress were considered. ^

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^