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. ^

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.

Characterization of the cholesterol 7$\alpha$-hydroxylase promoter in hypercholesterolemia -resistant rabbits

Our laboratory has developed and partially characterized a strain of New Zealand white rabbits that are resistant to the hypercholesterolemia which typically occurs in normal rabbits when fed a cholesterol-enriched diet. This phenotype is most likely attributed to an increase in bile acid excretion by hypercholesterolemia-resistant (CRT) rabbits as a result of elevated enzyme activity of cholesterol 7$\alpha$-hydroxylase (C7$\alpha$H), the rate-limiting enzyme in bile acid synthesis. Northern analysis revealed that CRT rabbits, in comparison to normal rabbits, have a 7-fold greater steady-state C7$\alpha$H mRNA levels irrespective of dietary regimen. The C7$\alpha$H gene in both phenotypes was determined to be a single copy gene. The hypothesis was that the elevated C7$\alpha$H mRNA levels in CRT rabbits, in comparison to normal animals, was due to an increase in the transcription rate of the C7$\alpha$H gene as a result of a mutation in a cis-acting element and/or a trans-acting factor within the hepatocyte. To isolate the C7$\alpha$H gene from both normal and CRT rabbits, genomic libraries were prepared from both phenotypes into $\lambda$GEM12 vectors using conventional techniques. Three CRT and one normal phage clones that contained the C7$\alpha$H gene were identified by screening the library with a series of probes located within different exons of the C7$\alpha$H cDNA. Sequencing analysis confirmed that approximately 1100 bp of the C7$\alpha$H 5'-flanking region from both normal and CRT phenotypes was identical. The increase in C7$\alpha$H mRNA levels was not attributed to a cis-acting mutation within this region. Liver nuclear extracts were prepared from normal and CRT rabbits maintained either on a basal or 0.25% cholesterol-enriched diet and incubated with several radiolabeled DNA fragments from the C7$\alpha$H gene. A 37 basepair region, located between nucleotides $-$452 to $-$416 was identified that had altered binding patterns between normal and CRT rabbits as a function of diet. Two additional regions, $-$747 to $-$575 and $-$580 to $-$442, produced banding patterns which were identical, irrespective of phenotype or diet. In conclusion, these studies suggested that the increase in C7$\alpha$H mRNA in CRT rabbits was due to differences in binding of a cholesterol-responsive transcription factor to the C7$\alpha$H promoter. ^

Transcriptional regulation of the rat {\it mdr1b\/} gene

The expression of P-glycoproteins encoded by the mdr gene family is associated with the emergence of multidrug-resistance phenotype in animal cells. This gene family includes two members, MDR1 and MDR2, in humans, and three members, mdr1a, mdr1b, and mdr2, in rodents. Among them, the rat mdr1b is known to be highly activated during hepatocarcinogenesis, and its expression is sensitive to the treatment with growth factors, cytotoxic drugs, as well as other physical or chemical stresses. It is believed that the transcriptional regulation plays an important role in above events, however little has been known about mechanisms involved.^ To elucidate how mdr1b expression is regulated, we isolated the genomic sequence of the rat mdr1b and functionally dissected its 5$\prime$ promoter region. Our results demonstrated that: (1) the transcription start site of the rat mdr1b is identical to that of the murine mdr1b homologue; (2) a palindromic sequence from bp $-$189 to $-$180 bp is essential for the basal promoter function of the rat mdr1b, and binds to a specific protein that appears to be a novel transcription factor implicated in the regulation of the rat mdr1b expression; (3) a NF-$\kappa$B-binding site from bp $-$167 to $-$159 is also involved in the basal promoter function. The p65/p50 subunits of the NF-$\kappa$B and raf-1 kinase are implicated in the insulin-inducible promoter activity of the mdr1b, suggesting the important role of NF-$\kappa$B in the regulation of the mdr1b by growth factors; (4) a p53-binding site from bp $-$199 to $-$180 is not only essential for the basal promoter activity but also responsible for the induction of mdr1b by cytotoxic agents. In addition, we provided evidence showing that endogenous mdr1b expression can be modulated by wild-type p53. On the basis of these findings, a model of transcriptional regulation of the rat mdr1b was proposed. ^

Altered tumorigenic phenotype in mice with a hypomorphic p53 mutant allele

Mutations in the p53 tumor suppressor gene are found in over 50% of human tumors and in the germline of Li-Fraumeni syndrome families. About 80% of these mutations are missense in nature. In order to study how p53 missense mutations affect tumorigenesis in vivo, we focused on the murine p53 arg-to-his mutation at amino acid 172, which corresponds to the human hot spot mutation at amino acid 175. The double replacement procedure was employed to introduce the p53 R172H mutation into the p53 locus of ES cells and mice were generated. An additional 1bp deletion in the intron 2 splice acceptor site was detected in the same allele in mice. We named this allele p53R172HΔg. This allele makes a small amount of full length p53 mutant protein. ^ Spontaneous tumor formation and survival were studied in these mice. Mice heterozygous for the p53R172HΔg allele showed 50% survival at 17 months of age, similar to the p53+/− mice. Moreover, the p53R172HΔg/+ mice showed a distinct tumor spectrum: 55% sarcomas, including osteosarcoms, fibrosarcomas and angiosarcomas; 27% carcinomas, including lung adenocarcinomas, squamous cell carcinomas, hepatocellular carcinomas and islet cell carcinomas; and 18% lymphomas. Compared to the p53+/− mice, there was a clear increase in the frequency of carcinoma development and a decrease in lymphoma incidence. Among the sarcomas that developed, fibrosarcomas in the skin were also more frequently observed. More importantly, osteosarcomas and carinomas that developed in the p53R172HΔg/+ mice metastasized at very high frequency (64% and 67%, respectively) compared with less than 10% in the p53+/− mice. The metastatic lesions were usually found in lung and liver, and less frequently in other tissues. The altered tumor spectrum in the mice and increased metastatic potential of the tumors suggested that the p53R172H mutation represents a gain-of-function. ^ Mouse embryonic fibroblasts (MEFs) from the mice homozygous and heterozygous for the p53R172HΔg allele were studied for growth characteristics, immortalization potential and genomic instability. All of the p53R172HΔg /+ MEF lines are immortalized under a 3T3 protocol while under the same protocol p53+/− MEFs are not immortalized. Karyotype analysis showed a persistent appearance of chromosome end-to-end fusion in the MEFs both homozygous and heterozygous for the p53R172HΔg allele. These observations suggest that increased genomic instability in the cells may cause the altered tumor phenotypes. ^