Physiological plasticity to water flow habitat in the damselfish, Acanthochromis polyacanthus: linking phenotype to performance

The relationships among animal form, function and performance are complex, and vary across environments. Therefore, it can be difficult to identify morphological and/or physiological traits responsible for enhancing performance in a given habitat. In fishes, differences in swimming performance across water flow gradients are related to morphological variation among and within species. However, physiological traits related to performance have been less well studied. We experimentally reared juvenile damselfish, Acanthochromis polyacanthus, under different water flow regimes to test 1) whether aspects of swimming physiology and morphology show plastic responses to water flow, 2) whether trait divergence correlates with swimming performance and 3) whether flow environment relates to performance differences observed in wild fish. We found that maximum metabolic rate, aerobic scope and blood haematocrit were higher in wave-reared fish compared to fish reared in low water flow. However, pectoral fin shape, which tends to correlate with sustained swimming performance, did not differ between rearing treatments or collection sites. Maximum metabolic rate was the best overall predictor of individual swimming performance; fin shape and fish total length were 3.3 and 3.7 times less likely than maximum metabolic rate to explain differences in critical swimming speed. Performance differences induced in fish reared in different flow environments were less pronounced than in wild fish but similar in direction. Our results suggest that exposure to water motion induces plastic physiological changes which enhance swimming performance in A. polyacanthus. Thus, functional relationships between fish morphology and performance across flow habitats should also consider differences in physiology.

Primitive ontology and quantum state in the GRW matter density theory

The paper explains in what sense the GRW matter density theory (GRWm) is a primitive ontology theory of quantum mechanics and why, thus conceived, the standard objections against the GRW formalism do not apply to GRWm. We consider the different options for conceiving the quantum state in GRWm and argue that dispositionalism is the most attractive one.

TUMOR PROGRESSION: ANALYSIS OF THE INSTABILITY OF THE METASTATIC PHENOTYPE, SENSITIVITY TO RADIATION AND CHEMOTHERAPY (PHENOTYPIC DRIFT, BREAST CANCER)

The major complications for tumor therapy are (i) tumor spread (metastasis); (ii) the mixed nature of tumors (heterogeneity); and (iii) the capacity of tumors to evolve (progress). To study these tumor characteristics, the rat 13762NF mammary adenocarcinoma was cloned and studied for metastatic properties and sensitivities to therapy (chemotherapy, radiation and hyperthermia). The cell clones were heterogeneous and no correlation between metastatic potential and therapeutic sensitivities was observed. Further, these phenotypes were unstable during passage in vitro; yet, the changes were clone dependent and reproducible using different cryoprotected cell stocks. To understand the phenotypic instability, subclones were isolated from low and high passage cell clones. Each subclone possessed a unique composite phenotype. Again, no apparent correlation was seen between metastatic potential and sensitivity to therapy. The results demonstrated that (1) tumor cells are heterogeneous for multiple phenotypes; (2) tumor cells are unstable for multiple phenotypes; (3) the magnitude, direction and time of occurrence of phenotypic drift is clone dependent; (4) the sensitivity of cell clones to ionizing radiation (gamma or heat) and chemotherapy agents is independent of their metastatic potential; (5) shifts in metastatic potential and sensitivity to therapy may occur simultaneously but are not linked; and (6) tumor cells independently diverge to form several subpopulations with unique phenotypic profiles. ^

Loss of activator protein-2alpha results in overexpression of the thrombin receptor and correlates with the malignant phenotype of human melanoma

Increasing evidence demonstrates that the thrombin receptor (protease activated receptor-1, PAR-1) plays a major role in tumor invasion and contributes to the metastatic phenotype of human melanoma. We demonstrate that the metastatic potential of human melanoma cells correlates with overexpression of PAR-1. The promoter of the PAR-1 gene contains multiple putative AP-2 and Sp1 consensus elements. We provide evidence that an inverse correlation exists between the expression of AP-2 and the expression of PAR-1 in human melanoma cells. Re-expression of AP-2 in WM266-4 melanoma cells (AP-2 negative) resulted in decreased mRNA and protein expression of PAR-1 and significantly reduced the tumor potential in nude mice. ChIP analysis of the PAR-1 promoter regions bp −365 to −329 (complex 1) and bp −206 to −180 (complex 2) demonstrates that in metastatic cells Sp1 is predominantly binding to the PAR-1 promoter, while in nonmetastatic cells AP-2 is bound. In vitro analysis of complex 1 demonstrates that AP-2 and Sp1 bind to this region in a mutually exclusive manner. Transfection experiments with full-length and progressive deletions of the PAR-1 promoter luciferase constructs demonstrated that metastatic cells had increased promoter activity compared to low and nonmetastatic melanoma cells. Our data shows that exogenous AP-2 expression decreased promoter activity, while transient expression of Sp1 further activated expression of the reporter gene. Mutational analysis of complex 1 within PAR-1 luciferase constructs further demonstrates that the regulation of PAR-1 is mediated through interactions with AP-2 and Sp1. Moreover, loss of AP-2 in metastatic cells alters the AP-2 to Sp1 ratio and DNA-binding activity resulting in overexpression of PAR-1. In addition, we evaluated the expression of AP-2 and PAR-1 utilizing a tissue microarray of 93 melanocytic lesions spanning from benign nevi to melanoma metastasis. We report loss of AP-2 expression in malignant tumors compared to benign tissue while PAR-1 was expressed more often in metastatic melanoma cells than in benign melanocytes. We propose that loss of AP-2 results in increased expression of PAR-1, which in turn results in upregulation of gene products that contribute to the metastatic phenotype of melanoma. ^

Single nucleotide polymorphism (SNP) selection for genotype-phenotype association studies

With hundreds of single nucleotide polymorphisms (SNPs) in a candidate gene and millions of SNPs across the genome, selecting an informative subset of SNPs to maximize the ability to detect genotype-phenotype association is of great interest and importance. In addition, with a large number of SNPs, analytic methods are needed that allow investigators to control the false positive rate resulting from large numbers of SNP genotype-phenotype analyses. This dissertation uses simulated data to explore methods for selecting SNPs for genotype-phenotype association studies. I examined the pattern of linkage disequilibrium (LD) across a candidate gene region and used this pattern to aid in localizing a disease-influencing mutation. The results indicate that the r2 measure of linkage disequilibrium is preferred over the common D′ measure for use in genotype-phenotype association studies. Using step-wise linear regression, the best predictor of the quantitative trait was not usually the single functional mutation. Rather it was a SNP that was in high linkage disequilibrium with the functional mutation. Next, I compared three strategies for selecting SNPs for application to phenotype association studies: based on measures of linkage disequilibrium, based on a measure of haplotype diversity, and random selection. The results demonstrate that SNPs selected based on maximum haplotype diversity are more informative and yield higher power than randomly selected SNPs or SNPs selected based on low pair-wise LD. The data also indicate that for genes with small contribution to the phenotype, it is more prudent for investigators to increase their sample size than to continuously increase the number of SNPs in order to improve statistical power. When typing large numbers of SNPs, researchers are faced with the challenge of utilizing an appropriate statistical method that controls the type I error rate while maintaining adequate power. We show that an empirical genotype based multi-locus global test that uses permutation testing to investigate the null distribution of the maximum test statistic maintains a desired overall type I error rate while not overly sacrificing statistical power. The results also show that when the penetrance model is simple the multi-locus global test does as well or better than the haplotype analysis. However, for more complex models, haplotype analyses offer advantages. The results of this dissertation will be of utility to human geneticists designing large-scale multi-locus genotype-phenotype association studies. ^

Genotypic spectrum and genotype-phenotype correlation of trimethylaminuria

Trimethylaminuria (TMAU) or Fish odor syndrome is an autosomal recessive disease that is characterized by pungent body odor with subsequent psychosocial complications. There are limited studies of the sequence variants causing TMAU in the literature with most studies describing only one or two patients and lacking genotype-phenotype correlations. Also to date, there is no laboratory in the US or Europe that offers TMA genetic testing on a clinical basis. We have recently validated genetic testing in the University of Colorado DNA Diagnostic Laboratory. We have a database of a few dozen patients with a biochemical diagnosis of TMA at the University of Colorado at Denver Health Sciences Center (UCDHSC) which includes a few patients with the classical form of the disease. We have used the newly established clinical test in our institution to attempt to characterize the genotype (sequence variants including mutations and polymorphisms) of classical TMAU patients and to establish a genotype-phenotype (biochemical and clinical) association. The questionnaire results confirmed most of the previously reported epidemiological findings of TMAU and also indicated that TMAU patients use multiple intervention measures in attempt to control their symptoms with dietary control being most effective. Despite the complexity of intervention, most patients did not have any medical follow up and there was underutilization of specialist care. In a set of our patients, two deleterious mutations were identified in 4/12 patients including a novel T237P sequence variant, while the majority of our patients (8/12) did not reveal any mutations. Some of the latter were double heterozygous for the E158K and E308G polymorphisms which could explain a mild phenotype while others had only the E158K variant which raised the question of undetected mutations. These results indicate that further experiments are needed to further delineate the full mutational spectrum of the FMO3 gene. ^

Polycomb repressive complex 2 and induced basal-like breast cancer phenotype mediated by cyclin E/Cdk2

Despite of much success of breast cancer treatment, basal-like breast cancer subtype still presented as a clinical challenge to mammary oncologist for its lack of available targeted therapy owing to their negative expression of targeted molecules, such as PgR, ERα and Her2. These molecules are all critical regulators in mammary gland development. EZH2, a histone methyltransferase, by forming Polycomb Repressive Complex 2(PRC2) can directly suppress a large array of developmental regulators. Overexpression of cyclin E has also been correlated with basal-like (triple-negative) breast cancer and poor prognosis. We found an important functional link between these two molecules. Cyclin E/Cdk2 can enhance PRC2 function by phosphorylating a specific residue of EZH2, threonine 416 and increasing EZH2's ability to complex with SUZ12. This regulation would further recruit whole PRC2 complex to core promoter regions of these developmental regulators. The local enrichment of PRC2 complex would then trimethylate H3K27 around the core promoter regions and suppress the expression of targeted genes, which included PgR, ERα, erbB2 and BRCA1. This widespread gene suppressive effect imposed by highly active PRC2 complex would then transform the lumina) type cell to adopt a basal-like phenotype. This finding suggested deregulated Cdk2 activity owing to cyclin E overexpression may contribute to basal phenotype through enhancing epigenetic silencing effects by regulating PRC2 function. Inhibition of Cdk2 activity in basal-like cancer cells may help release the suppression, reexpress the silenced genes and become responsive to existing anti-hormone or anti-Her2 therapy. From this study, the mechanisms described here provided a rationale to target basal-like breast cancer by new combinational therapy of Cdk2 inhibitors together with Lapatinib, or Aromatin. ^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

EFFECTS OF THE ACTA2 R258C MUTATION ON VASCULAR SMOOTH MUSCLE CELL PHENOTYPE AND PROPERTIES

Thoracic Aortic Aneurysms and Dissections (TAAD) are the fifteenth leading cause of death in the United States. About 15% of TAAD patients have family history of the disease. The most commonly mutated gene in these families is ACTA2, encoding smooth muscle-specific α-actin. ACTA2 missense mutations predispose individuals both to TAAD and to vascular occlusive disease of small, muscular arteries. Mice carrying an Acta2 R258C mutant transgene with a wildtype Acta2 promoter were generated and bred with Acta2-/- mice to decrease the wildtype: mutant Acta2 ratio. Acta2+/+ R258C TGmice have decreased aortic contractility without aortic disease. Acta2+/- R258C TG mice, however, have significant aortic dilatations by 12 weeks of age and a hyperproliferative response to injury. We characterized smooth muscle cells (SMCs) from bothmouse models under the hypothesis that mutant α-actin has a dominant negative effect, leading to impaired contractile filament formation/stability, improper focal adhesion maturation and increased proliferation. Explanted aortic SMCs from Acta2+/+ R258C TG mice are differentiated - they form intact filaments, express higher levels of contractile markers compared to wildtype SMCs and have predominantly nuclear Myocardin-Related Transcription Factor A (MRTF-A) localization. However, ultracentrifugation assays showed large unpolymerized actin fractions, suggesting that the filaments are brittle. In contrast, Acta2+/- R258C TG SMCs are less well-differentiated, with pools of unpolymerized actin, more cytoplasmic MRTF-A and decreased contractile protein expression compared to wildtype cells. Ultracentrifugation assays after treating Acta2+/- R258C TGSMCs with phalloidin showed actin filament fractions, indicating that mutant α-actin can polymerize into filaments. Both Acta2+/+ R258C TGand Acta2+/- R258C TGSMCs have larger and more peripheral focal adhesions compared to wildtype SMCs. Rac1 was more activated in Acta2+/+ R258C TGSMCs; both Rac1 and RhoA were less activated in Acta2+/- R258C TG SMCs, and FAK was more activated in both transgenic SMC lines compared to wildtype. Proliferation in both cell lines was significantly increased compared to wildtype cells and could be partially attenuated by inhibition of FAK or PDGFRβ. These data support a dominant negative effect of the Acta2 R258C mutation on the SMC phenotype, with increasing phenotypic severity when wildtype: mutant α-actin levels are decreased.

DETERMINING THE GENOTYPE-PHENOTYPE CONNECTION IN SYNTHETIC INDUCIBLE GENE EXPRESSION SYSTEMS

Introduction Gene expression is an important process whereby the genotype controls an individual cell’s phenotype. However, even genetically identical cells display a variety of phenotypes, which may be attributed to differences in their environment. Yet, even after controlling for these two factors, individual phenotypes still diverge due to noisy gene expression. Synthetic gene expression systems allow investigators to isolate, control, and measure the effects of noise on cell phenotypes. I used mathematical and computational methods to design, study, and predict the behavior of synthetic gene expression systems in S. cerevisiae, which were affected by noise. Methods I created probabilistic biochemical reaction models from known behaviors of the tetR and rtTA genes, gene products, and their gene architectures. I then simplified these models to account for essential behaviors of gene expression systems. Finally, I used these models to predict behaviors of modified gene expression systems, which were experimentally verified. Results Cell growth, which is often ignored when formulating chemical kinetics models, was essential for understanding gene expression behavior. Models incorporating growth effects were used to explain unexpected reductions in gene expression noise, design a set of gene expression systems with “linear” dose-responses, and quantify the speed with which cells explored their fitness landscapes due to noisy gene expression. Conclusions Models incorporating noisy gene expression and cell division were necessary to design, understand, and predict the behaviors of synthetic gene expression systems. The methods and models developed here will allow investigators to more efficiently design new gene expression systems, and infer gene expression properties of TetR based systems.

Galectin-3 Enhances the Malignant Melanoma Phenotype by Regulating Autotaxin

In melanoma patient specimens and cell lines, the over expression of galectin-3 is associated with disease progression and metastatic potential. Herein, we have sought out to determine whether galectin-3 affects the malignant melanoma phenotype by regulating downstream target genes. To that end, galectin-3 was stably silenced by utilizing the lentivirus-incorporated small hairpin RNA in two metastatic melanoma cell lines, WM2664 and A375SM, and subjected to gene expression microarray analysis. We identified and validated the lysophospholipase D enzyme, autotaxin, a promoter of migration, invasion, and tumorigenesis, to be down regulated after silencing galectin-3. Silencing galectin-3 significantly reduced the promoter activity of autotaxin. Interestingly, we also found the transcription factor NFAT1 to have reduced protein expression after silencing galectin-3. Electrophoretic mobility shift assays from previous reports have shown that NFAT1 binds to the autotaxin promoter in two locations. ChIP analysis was performed, and we observed a complete loss of bound NFAT1 to the autotaxin promoter after silencing galectin-3 in melanoma cells. Mutation of the NFAT1 binding sites at either location reduces autotaxin promoter activity. Silencing NFAT1 reduces autotaxin expression while over expressing NFAT1 in NFAT1 negative SB-2 melanoma cells induces autotaxin expression. These data suggest that galectin-3 silencing reduces autotaxin transcription by reducing the amount of NFAT1 protein expression. Rescue of galectin-3 rescues both NFAT1 and autotaxin. We also show that the re-expression of autotaxin in galectin-3 shRNA melanoma cells rescues the angiogenic phenotype in vivo. Furthermore, we identify NFAT1 as a potent inducer of tumor growth and experimental lung metastasis. Our data elucidate a previously unidentified mechanism by which galectin-3 regulates autotaxin and assign a novel role for NFAT1 during melanoma progression.

RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features.