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. ^

Identification and characterization of mutations in SMC contractile genes involved in thoracic aortic aneurysms and dissections

Aortic aneurysms and dissections are the 15th most common cause of death in the United States. Genetic factors contribute to the pathogenesis of thoracic aortic aneurysms and dissections (TAAD). Currently, six loci and four genes have been identified for familial TAAD. Notably, mutations in smooth muscle cell (SMC) contractile genes, ACTA2 and MYH11, are responsible for 15% of familial TAAD, suggesting that proper SMC contraction is important for normal aorta function. Therefore, we hypothesize that mutations in other genes encoding SMC contractile proteins also cause familial TAAD. ^ To test this hypothesis, we used a candidate gene approach to identify causative mutations in SMC contractile genes for familial TAAD. Sequencing DNA in 80 TAAD patients from unrelated families, we identified putative mutations in eight contractile genes. We chose myosin light chain kinase (MLCK ) S1759P for further study for the following reasons: (1) Serine 1759 is conserved between vertebrates and invertebrates. (2) S1759P is predicted to be functionally deleterious by bioinformatics. (3) Low blood pressure is observed in SMC-selective MLCK-deficient mice. ^ In the presence of Ca2+/Calmodulin (CaM), MLCK containing CaM binding and kinase domains are activated to phosphorylate myosin light chain, thereby initiate SMC contraction. The CaM binding sequence of MLCK forms an α-helix structure required for CaM binding. MLCK Serine 1759 is located within the CaM binding domain. S1759P is predicted to decrease the α-helix composition in the CaM binding domain. Hence, we hypothesize that MLCK mutations cause TAAD through disturbing CaM binding and MLCK activity. ^ We further sequenced MLCK in DNA samples from additional 86 probands with familial TAAD. Two more mutations, MLCK A1754T and R1480Stop, were identified, supporting that MLCK mutations cause familial TAAD. ^ To define whether MLCK mutations disrupted CaM binding and MLCK activity, we performed co-immunoprecipitation and kinase assays. Decreased CaM binding and kinase activity was detected in A1754T and S1759P. Moreover, R1480Stop is predicted to truncate kinase and CaM binding domains. We conclude that MLCK mutations disrupt CaM binding and MLCK activity. ^ Collectively, our study is first to show mutations in genes regulating SMC contraction cause TAAD. This finding further highlights the importance of SMC contraction in maintaining aorta function. ^

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.^

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.

Molecular Mechanisms of Vascular Disease in Patients with Rare Variants in MYH11

Thoracic aortic aneurysms and dissections (TAAD) are the primary disease affecting the thoracic ascending aorta, with an incidence rate of 10.4/100,000. Although about 20% of patients carry a mutation in a single gene that causes their disease, the remaining 80% of patients may also have genetic factors that increase their risk for developing TAAD. Many of the genes that predispose to TAAD encode proteins involved in smooth muscle cell (SMC) contraction and the disease-causing mutations are predicted to disrupt contractile function. SMCs are the predominant cell type in the ascending aortic wall. Mutations in MYH11, encoding the smooth muscle specific myosin heavy chain, are a rare cause of inherited TAAD. However, rare but recurrent non-synonymous variants in MYH11 are present in the general population but do not cause inherited TAAD. The goal of this study was to assess the potential role of these rare variants in vascular diseases. Two distinct variants were selected: the most commonly seen rare variant, MYH11 R247C, and a duplication of the chromosomal region spanning the MYH11 locus at 16p13.1. Genetic analyses indicated that both of these variants were significantly enriched in patients with TAAD compared with controls. A knock-in mouse model of the Myh11 R247C rare variant was generated, and these mice survive and reproduce normally. They have no structural abnormalities of the aorta or signs of aortic disease, but do have decreased aortic contractility. Myh11R247C/R247C mice also have increased proliferative response to vascular injury in vivo and increased proliferation of SMCs in vitro. Myh11R247C/R247C SMCs have decreased contractile gene and protein expression and are dedifferentiated. In fibroblasts, myosin force generation is required for maturation of focal adhesions, and enhancers of RhoA activity replace enhancers of Rac1 activity as maturation occurs. Consistent with these previous findings, focal adhesions are smaller in Myh11R247C/R247C SMCs, and there is decreased RhoA activation. A RhoA activator (CN03) rescues the dedifferentiated phenotype of Myh11R247C/R247C SMCs. Myh11R247C/R247C mice were bred with an existing murine model of aneurysm formation, the Acta2-/- mouse. Over time, mice carrying the R247C allele in conjunction with heterozygous or homozygous loss of Acta2 had significantly increased aortic diameter, and a more rapid accumulation of pathologic markers. These results suggest that the Myh11 R247C rare variant acts as a modifier gene increasing the risk for and severity of TAAD in mice. In patients with 16p13.1 duplications, aortic MYH11 expression is increased, but there is no corresponding increase in smooth muscle myosin heavy chain protein. Using SMCs that overexpress Myh11, we identified alterations in SMC phenotype leading to excessive protein turnover. All contractile proteins, not just myosin, are affected, and the proteins are turned over by autophagic degradation. Surprisingly, these cells are also more contractile compared with wild-type SMCs. The results described in this dissertation firmly establish that rare variants in MYH11 significantly affect the phenotype of SMCs. Further, the data suggests that these rare variants do increase the risk of TAAD via pathways involving altered SMC phenotype and contraction. Therefore, this study validates that these rare genetic variants alter vascular SMCs and provides model systems to explore the contribution of rare variants to disease.

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.

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. ^