980 resultados para Gene network


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TIE2 is a vascular endothelial-specific receptor tyrosine kinase essential for the regulation of vascular network formation and remodeling. Previously, we have shown that the 1.2-kb 5' flanking region of the TIE2 promoter is capable of directing beta-galactosidase reporter gene expression specifically into a subset of endothelial cells (ECs) of transgenic mouse embryos. However, transgene activity was restricted to early embryonic stages and not detectable in adult mice. Herein we describe the identification and characterization of an autonomous endothelial-specific enhancer in the first intron of the mouse TIE2 gene. Furthermore, combination of the TIE2 promoter with an intron fragment containing this enhancer allows it to target reporter gene expression specifically and uniformly to virtually all vascular ECs throughout embryogenesis and adulthood. To our knowledge, this is the first time that an in vivo expression system has been assembled by which heterologous genes can be targeted exclusively to the ECs of the entire vasculature. This should be a valuable tool to address the function of genes during physiological and pathological processes of vascular ECs in vivo. Furthermore, we were able to identify a short region critical for enhancer function in vivo that contains putative binding sites for Ets-like transcription factors. This should, therefore, allow us to determine the molecular mechanisms underlying the vascular-EC-specific expression of the TIE2 gene.

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A number of molecular tools enable us to study the mechanisms of muscle plasticity. Ideally, this research is conducted in view of the structural and functional consequences of the exercise-induced changes in gene expression. Muscle cells are able to detect mechanical, metabolic, neuronal and hormonal signals which are transduced over multiple pathways to the muscle genome. Exercise activates many signaling cascades--the individual characteristic of the stress leading to a specific response of a network of signaling pathways. Signaling typically results in the transcription of multiple early genes among those of the well known for and jun family, as well as many other transcription factors. These bind to the promoter regions of downstream genes initiating the structural response of muscle tissue. While signaling is a matter of minutes, early genes are activated over hours leading to a second wave of transcript adjustments of structure genes that can then be effective over days. Repeated exercise sessions thus lead to a concerted accretion of mRNAs which upon translation results in a corresponding protein accretion. On the structural level, the protein accretion manifests itself for instance as an increase in mitochondrial volume upon endurance training or an increase in myofibrillar proteins upon strength training. A single exercise stimulus carries a molecular signature which is typical both for the type of stimulus (i.e. endurance vs. strength) as well as the actual condition of muscle tissue (i.e. untrained vs. trained). Likewise, it is clearly possible to distinguish a molecular signature of an expressional adaptation when hypoxic stress is added to a regular endurance exercise protocol in well-trained endurance athletes. It therefore seems feasible to use molecular tools to judge the properties of an exercise stimulus much earlier and at a finer level than is possible with conventional functional or structural techniques.

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The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

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BACKGROUND: Phaeochromocytomas and paragangliomas are neuro-endocrine tumours that occur sporadically and in several hereditary tumour syndromes, including the phaeochromocytoma-paraganglioma syndrome. This syndrome is caused by germline mutations in succinate dehydrogenase B (SDHB), C (SDHC), or D (SDHD) genes. Clinically, the phaeochromocytoma-paraganglioma syndrome is often unrecognised, although 10-30% of apparently sporadic phaeochromocytomas and paragangliomas harbour germline SDH-gene mutations. Despite these figures, the screening of phaeochromocytomas and paragangliomas for mutations in the SDH genes to detect phaeochromocytoma-paraganglioma syndrome is rarely done because of time and financial constraints. We investigated whether SDHB immunohistochemistry could effectively discriminate between SDH-related and non-SDH-related phaeochromocytomas and paragangliomas in large retrospective and prospective tumour series. METHODS: Immunohistochemistry for SDHB was done on 220 tumours. Two retrospective series of 175 phaeochromocytomas and paragangliomas with known germline mutation status for phaeochromocytoma-susceptibility or paraganglioma-susceptibility genes were investigated. Additionally, a prospective series of 45 phaeochromocytomas and paragangliomas was investigated for SDHB immunostaining followed by SDHB, SDHC, and SDHD mutation testing. FINDINGS: SDHB protein expression was absent in all 102 phaeochromocytomas and paragangliomas with an SDHB, SDHC, or SDHD mutation, but was present in all 65 paraganglionic tumours related to multiple endocrine neoplasia type 2, von Hippel-Lindau disease, and neurofibromatosis type 1. 47 (89%) of the 53 phaeochromocytomas and paragangliomas with no syndromic germline mutation showed SDHB expression. The sensitivity and specificity of the SDHB immunohistochemistry to detect the presence of an SDH mutation in the prospective series were 100% (95% CI 87-100) and 84% (60-97), respectively. INTERPRETATION: Phaeochromocytoma-paraganglioma syndrome can be diagnosed reliably by an immunohistochemical procedure. SDHB, SDHC, and SDHD germline mutation testing is indicated only in patients with SDHB-negative tumours. SDHB immunohistochemistry on phaeochromocytomas and paragangliomas could improve the diagnosis of phaeochromocytoma-paraganglioma syndrome. FUNDING: The Netherlands Organisation for Scientific Research, Dutch Cancer Society, Vanderes Foundation, Association pour la Recherche contre le Cancer, Institut National de la Santé et de la Recherche Médicale, and a PHRC grant COMETE 3 for the COMETE network.

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Clinical studies indicate that exaggerated postprandial lipemia is linked to the progression of atherosclerosis, leading cause of Cardiovascular Diseases (CVD). CVD is a multi-factorial disease with complex etiology and according to the literature postprandial Triglycerides (TG) can be used as an independent CVD risk factor. Aim of the current study is to construct an Artificial Neural Network (ANN) based system for the identification of the most important gene-gene and/or gene-environmental interactions that contribute to a fast or slow postprandial metabolism of TG in blood and consequently to investigate the causality of postprandial TG response. The design and development of the system is based on a dataset of 213 subjects who underwent a two meals fatty prandial protocol. For each of the subjects a total of 30 input variables corresponding to genetic variations, sex, age and fasting levels of clinical measurements were known. Those variables provide input to the system, which is based on the combined use of Parameter Decreasing Method (PDM) and an ANN. The system was able to identify the ten (10) most informative variables and achieve a mean accuracy equal to 85.21%.

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The development of a completely annotated sheep genome sequence is a key need for understanding the phylogenetic relationships and genetic diversity among the many different sheep breeds worldwide and for identifying genes controlling economically and physiologically important traits. The ovine genome sequence assembly will be crucial for developing optimized breeding programs based on highly productive, healthy sheep phenotypes that are adapted to modern breeding and production conditions. Scientists and breeders around the globe have been contributing to this goal by generating genomic and cDNA libraries, performing genome-wide and trait-associated analyses of polymorphism, expression analysis, genome sequencing, and by developing virtual and physical comparative maps. The International Sheep Genomics Consortium (ISGC), an informal network of sheep genomics researchers, is playing a major role in coordinating many of these activities. In addition to serving as an essential tool for monitoring chromosome abnormalities in specific sheep populations, ovine molecular cytogenetics provides physical anchors which link and order genome regions, such as sequence contigs, genes and polymorphic DNA markers to ovine chromosomes. Likewise, molecular cytogenetics can contribute to the process of defining evolutionary breakpoints between related species. The selective expansion of the sheep cytogenetic map, using loci to connect maps and identify chromosome bands, can substantially contribute to improving the quality of the annotated sheep genome sequence and will also accelerate its assembly. Furthermore, identifying major morphological chromosome anomalies and micro-rearrangements, such as gene duplications or deletions, that might occur between different sheep breeds and other Ovis species will also be important to understand the diversity of sheep chromosome structure and its implications for cross-breeding. To date, 566 loci have been assigned to specific chromosome regions in sheep and the new cytogenetic map is presented as part of this review. This review will also summarize the current cytogenomic status of the sheep genome, describe current activities in the sheep cytogenomics research sector, and will discuss the cytogenomics data in context with other major sheep genomics projects.

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Synchrotron Microbeam Radiation Therapy (MRT) relies on the spatial fractionation of the synchrotron photon beam into parallel micro-beams applying several hundred of grays in their paths. Several works have reported the therapeutic interest of the radiotherapy modality at preclinical level, but biological mechanisms responsible for the described efficacy are not fully understood to date. The aim of this study was to identify the early transcriptomic responses of normal brain and glioma tissue in rats after MRT irradiation (400Gy). The transcriptomic analysis of similarly irradiated normal brain and tumor tissues was performed 6 hours after irradiation of 9 L orthotopically tumor-bearing rats. Pangenomic analysis revealed 1012 overexpressed and 497 repressed genes in the irradiated contralateral normal tissue and 344 induced and 210 repressed genes in tumor tissue. These genes were grouped in a total of 135 canonical pathways. More than half were common to both tissues with a predominance for immunity or inflammation (64 and 67% of genes for normal and tumor tissues, respectively). Several pathways involving HMGB1, toll-like receptors, C-type lectins and CD36 may serve as a link between biochemical changes triggered by irradiation and inflammation and immunological challenge. Most immune cell populations were involved: macrophages, dendritic cells, natural killer, T and B lymphocytes. Among them, our results highlighted the involvement of Th17 cell population, recently described in tumor. The immune response was regulated by a large network of mediators comprising growth factors, cytokines, lymphokines. In conclusion, early response to MRT is mainly based on inflammation and immunity which appear therefore as major contributors to MRT efficacy.

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High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

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The mechanisms regulating retinal ganglion cell (RGC) development are crucial for retinogenesis and for the establishment of normal vision. However, these mechanisms are only vaguely understood. RGCs are the first neuronal lineage to segregate from pluripotent progenitors in the developing retina. As output neurons, RGCs display developmental features very distinct from those of the other retinal cell types. To better understand RGC development, we have previously constructed a gene regulatory network featuring a hierarchical cascade of transcription factors that ultimately controls the expression of downstream effector genes. This has revealed the existence of a Pou domain transcription factor, Pou4f2, that occupies a key node in the RGC gene regulatory network and that is essential for RGC differentiation. However, little is known about the genes that connect upstream regulatory genes, such as Pou4f2 with downstream effector genes responsible for RGC differentiation. The purpose of this study was to characterize the retinal function of eomesodermin (Eomes), a T-box transcription factor with previously unsuspected roles in retinogenesis. We show that Eomes is expressed in developing RGCs and is a mediator of Pou4f2 function. Pou4f2 directly regulates Eomes expression through a cis-regulatory element within a conserved retinal enhancer. Deleting Eomes in the developing retina causes defects reminiscent of those in Pou4f2(-/-) retinas. Moreover, myelin ensheathment in the optic nerves of Eomes(-/-) embryos is severely impaired, suggesting that Eomes regulates this process. We conclude that Eomes is a crucial regulator positioned immediately downstream of Pou4f2 and is required for RGC differentiation and optic nerve development.

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The cause of Huntington disease (HD) is a polyglutamine repeat expansion of more than 36 units in the huntingtin protein, which is inversely correlated with the age at onset of the disease. However, additional genetic factors are believed to modify the course and the age at onset of HD. Recently, we identified the V471A polymorphism in the autophagy-related gene ATG7, a key component of the autophagy pathway that plays an important role in HD pathogenesis, to be associated with the age at onset in a large group of European Huntington disease patients. To confirm this association in a second independent patient cohort, we analysed the ATG7 V471A polymorphism in additional 1,464 European HD patients of the "REGISTRY" cohort from the European Huntington Disease Network (EHDN). In the entire REGISTRY cohort we could not confirm a modifying effect of the ATG7 V471A polymorphism. However, analysing a modifying effect of ATG7 in these REGISTRY patients and in patients of our previous HD cohort according to their ethnic origin, we identified a significant effect of the ATG7 V471A polymorphism on the HD age at onset only in the Italian population (327 patients). In these Italian patients, the polymorphism is associated with a 6-years earlier disease onset and thus seems to have an aggravating effect. We could specify the role of ATG7 as a genetic modifier for HD particularly in the Italian population. This result affirms the modifying influence of the autophagic pathway on the course of HD, but also suggests population-specific modifying mechanisms in HD pathogenesis.

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Hypertension is usually defined as having values of systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg. Hypertension is one of the main adverse effects of glucocorticoid on the cardiovascular system. Glucocorticoids are essential hormones, secreted from adrenal glands in circadian fashion. Glucocorticoid's effect on blood pressure is conveyed by the glucocorticoid receptor (NR3C1), an omnipresent nuclear transcription factor. Although polymorphisms in this gene have long been implicated to be a causal factor for cardiovascular diseases such as hypertension, no study has yet thoroughly interrogated the gene's polymorphisms for their effect on blood pressure levels. Therefore, I have first resequenced ∼30 kb of the gene, encompassing all exons, promoter regions, 5'/3' UTRs as well as at least 1.5 kb of the gene's flanking regions from 114 chromosome 5 monosomic cell lines, comprised of three major American ethnic groups—European American, African American and Mexican American. I observed 115 polymorphisms and 14 common molecularly phased haplotypes. A subset of markers was chosen for genotyping study populations of GENOA (Genetic Epidemiology Network of Atherosclerosis; 1022 non-Hispanic whites, 1228 African Americans and 954 Mexican Americans). Since these study populations include sibships, the family-based association test was performed on 4 blood pressure-related quantitative variables—pulse, systolic blood pressure, diastolic blood pressure and mean arterial pressure. Using these analyses, multiple correlated SNPs are significantly protective against high systolic blood pressure in non-Hispanic whites, which includes rsb198, a SNP formerly associated with beneficial body compositions. Haplotype association analysis also supports this finding and all p-values remained significant after permutation tests. I therefore conclude that multiple correlated SNPs on the gene may confer protection against high blood pressure in non-Hispanic whites. ^

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Transcription of the Bacillus anthracis structural genes for the anthrax toxin proteins and biosynthetic operon for capsule are positively regulated by AtxA, a transcription regulator with unique properties. Consistent with the role of atxA in virulence factor expression, a B. anthracis atxA-null mutant is avirulent in a murine model for anthrax. In batch culture, multiple signals impact atxA transcript levels, and the timing and steady state level of atxA expression is critical for optimal toxin and capsule synthesis. Despite the apparent complex control of atxA transcription, only one trans-acting protein, the transition state regulator AbrB, has been demonstrated to directly interact with the atxA promoter. The AbrB-binding site has been described, but additional cis-acting control sequences have not been defined. Using transcriptional lacZ fusions, electrophoretic mobility shift assays, and Western blot analysis, the cis-acting elements and trans-acting factors involved in regulation of atxA in B. anthracis strains containing either both virulence plasmids, pXO1 and pXO2, or only one plasmid, pXO1, were studied. This work demonstrates that atxA transcription from the major start site P1 is dependent upon a consensus sequence for the housekeeping sigma factor SigA, and an A+T-rich upstream element (UP-element) for RNA polymerase (RNAP). In addition, the data show that a trans-acting protein(s) other than AbrB negatively impacts atxA transcription when it binds specifically to a 9-bp palindrome within atxA promoter sequences located downstream of P1. Mutation of the palindrome prevents binding of the trans-acting protein(s) and results in a corresponding increase in AtxA and anthrax toxin production in a strain- and culture-dependent manner. The identity of the trans-acting repressor protein(s) remains elusive; however, phenotypes associated with mutation of the repressor binding site have revealed that the trans-acting repressor protein(s) indirectly controls B. anthracis development. Mutation of the repressor binding site results in misregulation and overexpression of AtxA in conditions conducive for development, leading to a marked sporulation defect that is both atxA- and pXO2-61-dependent. pXO2-61 is homologous to the sensor domain of sporulation sensor histidine kinases and is proposed to titrate an activating signal away from the sporulation phosphorelay when overexpressed by AtxA. These results indicate that AtxA is not only a master virulence regulator, but also a modulator of proper B. anthracis development. Also demonstrated in this work is the impact of the developmental regulators AbrB, Spo0A, and SigH on atxA expression and anthrax toxin production in a genetically incomplete (pXO1+, pXO2-) and genetically complete (pXO1+, pXO2+) strain background. AtxA and anthrax toxin production resulting from deletion of the developmental regulators are strain-dependent suggesting that factors on pXO2 are involved in control of atxA. The only developmental deletion mutant that resulted in a prominent and consistent strain-independent increase in AtxA protein levels was an abrB-null mutant. As a result of increased AtxA levels, there is early and increased production of anthrax toxins in an abrB-null mutant. In addition, the abrB-null mutant exhibited an increase in virulence in a murine model for anthrax. In contrast, virulence of the atxA promoter mutant was unaffected in a murine model for anthrax despite the production of 5-fold more AtxA than the abrB-null mutant. These results imply that AtxA is not the only factor impacting pathogenesis in an abrB-null mutant. Overall, this work highlights the complex regulatory network that governs expression of atxA and provides an additional role for AtxA in B. anthracis development.

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Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.

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Adherens junctions (AJs) and basolateral modules are important for the establishment and maintenance of apico-basal polarity. Loss of AJs and basolateral module members lead to tumor formation, as well as poor prognosis for metastasis. Recently, in mammalian studies it has been shown that loss of either AJ or basolateral module members deregulate Yorkie activity, the downstream transcriptional effector of the Hippo pathway. Importantly, it is unclear if AJ and basolateral components act through the same or parallel mechanisms to regulate Yorkie activity. Here, we dissect how loss of AJ and basolateral components affects Hippo signaling in Drosophila. Surprisingly, while scrib knock-down tissue displays increased reporter activity autonomously, α-cat knock-down tissue shows a cell autonomous decrease and a cell non-autonomous increase of Hippo reporter activity. We provided several lines of evidence to show the differential regulation in polarity protein localizations and oncogenic cooperative overgrowth by AJs and basolateral complexes. Finally, we show that Hippo pathway activity is induced in α-cat and scrib double knocked-down tissue. Taken together, our results provide evidence to show that basolateral modules and AJs act in parallel to modulate Hippo pathway activity. Non-muscle myosin II is an actomyosin component that interacts with the actin. Non-muscle myosin II also interacts with lgl, though the function of this interaction is not clear. Our lab demonstrated that modulating F-actin regulates Hippo pathway activity, and lgl also has been described as a Hippo pathway regulator. Therefore we suspect that myosin II is also involved in Hippo pathway regulation. We first characterized non-muscle Myosin II as a novel tumor suppressor gene by affecting Hippo pathway activity. Upstream regulators of Myosin II, members in the Rho signaling pathway, also displayed similar phenotypes as the Myosin II knock-down tissues. Apoptosis is also induced in myosin II knock-down tissues, however, blocking cell death does not affect myosin II knock-down induced Hippo activation. Our data suggested hyperactivating myosin II induced F-actin accumulation so therefore induces Hippo target activation. Unexpectedly, we also observed that reducing F-actin activity induced Hippo target activation in vivo. These controversial data indicated that actomyosin may regulate the Hippo pathway through multiple mechanisms.

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Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^