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Sample records for identifying disease genes

  1. A literature based method for identifying gene-disease connections.

    PubMed

    Adamic, Lada A; Wilkinson, Dennis; Huberman, Bernardo A; Adar, Eytan

    2002-01-01

    We present a statistical method that can swiftly identify, from the literature, sets of genes known to be associated with given diseases. It offers a comprehensive way to treat alias symbols, a statistical method for computing the relevance of the gene to the query, and a novel way to disambiguate gene symbols from other abbreviations. The method is illustrated by finding genes related to breast cancer. PMID:15838128

  2. Identifying Mendelian disease genes with the Variant Effect Scoring Tool

    PubMed Central

    2013-01-01

    Background Whole exome sequencing studies identify hundreds to thousands of rare protein coding variants of ambiguous significance for human health. Computational tools are needed to accelerate the identification of specific variants and genes that contribute to human disease. Results We have developed the Variant Effect Scoring Tool (VEST), a supervised machine learning-based classifier, to prioritize rare missense variants with likely involvement in human disease. The VEST classifier training set comprised ~ 45,000 disease mutations from the latest Human Gene Mutation Database release and another ~45,000 high frequency (allele frequency >1%) putatively neutral missense variants from the Exome Sequencing Project. VEST outperforms some of the most popular methods for prioritizing missense variants in carefully designed holdout benchmarking experiments (VEST ROC AUC = 0.91, PolyPhen2 ROC AUC = 0.86, SIFT4.0 ROC AUC = 0.84). VEST estimates variant score p-values against a null distribution of VEST scores for neutral variants not included in the VEST training set. These p-values can be aggregated at the gene level across multiple disease exomes to rank genes for probable disease involvement. We tested the ability of an aggregate VEST gene score to identify candidate Mendelian disease genes, based on whole-exome sequencing of a small number of disease cases. We used whole-exome data for two Mendelian disorders for which the causal gene is known. Considering only genes that contained variants in all cases, the VEST gene score ranked dihydroorotate dehydrogenase (DHODH) number 2 of 2253 genes in four cases of Miller syndrome, and myosin-3 (MYH3) number 2 of 2313 genes in three cases of Freeman Sheldon syndrome. Conclusions Our results demonstrate the potential power gain of aggregating bioinformatics variant scores into gene-level scores and the general utility of bioinformatics in assisting the search for disease genes in large-scale exome sequencing studies. VEST is

  3. Identifying disease candidate genes via large-scale gene network analysis.

    PubMed

    Kim, Haseong; Park, Taesung; Gelenbe, Erol

    2014-01-01

    Gene Regulatory Networks (GRN) provide systematic views of complex living systems, offering reliable and large-scale GRNs to identify disease candidate genes. A reverse engineering technique, Bayesian Model Averaging-based Networks (BMAnet), which ensembles all appropriate linear models to tackle uncertainty in model selection that integrates heterogeneous biological data sets is introduced. Using network evaluation metrics, we compare the networks that are thus identified. The metric 'Random walk with restart (Rwr)' is utilised to search for disease genes. In a simulation our method shows better performance than elastic-net and Gaussian graphical models, but topological quantities vary among the three methods. Using real-data, brain tumour gene expression samples consisting of non-tumour, grade III and grade IV are analysed to estimate networks with a total of 4422 genes. Based on these networks, 169 brain tumour-related candidate genes were identified and some were found to relate to 'wound', 'apoptosis', and 'cell death' processes. PMID:25796737

  4. MIClique: An algorithm to identify differentially coexpressed disease gene subset from microarray data.

    PubMed

    Zhang, Huanping; Song, Xiaofeng; Wang, Huinan; Zhang, Xiaobai

    2009-01-01

    Computational analysis of microarray data has provided an effective way to identify disease-related genes. Traditional disease gene selection methods from microarray data such as statistical test always focus on differentially expressed genes in different samples by individual gene prioritization. These traditional methods might miss differentially coexpressed (DCE) gene subsets because they ignore the interaction between genes. In this paper, MIClique algorithm is proposed to identify DEC gene subsets based on mutual information and clique analysis. Mutual information is used to measure the coexpression relationship between each pair of genes in two different kinds of samples. Clique analysis is a commonly used method in biological network, which generally represents biological module of similar function. By applying the MIClique algorithm to real gene expression data, some DEC gene subsets which correlated under one experimental condition but uncorrelated under another condition are detected from the graph of colon dataset and leukemia dataset. PMID:20169000

  5. Identifying Human Disease Genes through Cross-Species Gene Mapping of Evolutionary Conserved Processes

    PubMed Central

    Poot, Martin; Badea, Alexandra; Williams, Robert W.; Kas, Martien J.

    2011-01-01

    Background Understanding complex networks that modulate development in humans is hampered by genetic and phenotypic heterogeneity within and between populations. Here we present a method that exploits natural variation in highly diverse mouse genetic reference panels in which genetic and environmental factors can be tightly controlled. The aim of our study is to test a cross-species genetic mapping strategy, which compares data of gene mapping in human patients with functional data obtained by QTL mapping in recombinant inbred mouse strains in order to prioritize human disease candidate genes. Methodology We exploit evolutionary conservation of developmental phenotypes to discover gene variants that influence brain development in humans. We studied corpus callosum volume in a recombinant inbred mouse panel (C57BL/6J×DBA/2J, BXD strains) using high-field strength MRI technology. We aligned mouse mapping results for this neuro-anatomical phenotype with genetic data from patients with abnormal corpus callosum (ACC) development. Principal Findings From the 61 syndromes which involve an ACC, 51 human candidate genes have been identified. Through interval mapping, we identified a single significant QTL on mouse chromosome 7 for corpus callosum volume with a QTL peak located between 25.5 and 26.7 Mb. Comparing the genes in this mouse QTL region with those associated with human syndromes (involving ACC) and those covered by copy number variations (CNV) yielded a single overlap, namely HNRPU in humans and Hnrpul1 in mice. Further analysis of corpus callosum volume in BXD strains revealed that the corpus callosum was significantly larger in BXD mice with a B genotype at the Hnrpul1 locus than in BXD mice with a D genotype at Hnrpul1 (F = 22.48, p<9.87*10−5). Conclusion This approach that exploits highly diverse mouse strains provides an efficient and effective translational bridge to study the etiology of human developmental disorders, such as autism and schizophrenia

  6. Applying the Fisher score to identify Alzheimer's disease-related genes.

    PubMed

    Yang, J; Liu, Y L; Feng, C S; Zhu, G Q

    2016-01-01

    Biologists and scientists can use the data from Alzheimer's disease (AD) gene expression microarrays to mine AD disease-related genes. Because of disadvantages such as small sample sizes, high dimensionality, and a high level of noise, it is difficult to obtain accurate and meaningful biological information from gene expression profiles. In this paper, we present a novel approach for utilizing AD microarray data to identify the morbigenous genes. The Fisher score, a classical feature selection method, is utilized to evaluate the importance of each gene. Genes with a large between-classes variance and small within-class variance are selected as candidate morbigenous genes. The results using an AD dataset show that the proposed approach is effective for gene selection. Satisfactory accuracy can be achieved by using only a small number of selected genes. PMID:27420981

  7. Genomic convergence: identifying candidate genes for Parkinson's disease by combining serial analysis of gene expression and genetic linkage.

    PubMed

    Hauser, Michael A; Li, Yi-Ju; Takeuchi, Satoshi; Walters, Robert; Noureddine, Maher; Maready, Melinda; Darden, Tiffany; Hulette, Christine; Martin, Eden; Hauser, Elizabeth; Xu, Hong; Schmechel, Don; Stenger, Judith E; Dietrich, Fred; Vance, Jeffery

    2003-03-15

    We present a multifactorial, multistep approach called genomic convergence that combines gene expression with genomic linkage analysis to identify and prioritize candidate susceptibility genes for Parkinson's disease (PD). To initiate this process, we used serial analysis of gene expression (SAGE) to identify genes expressed in two normal substantia nigras (SN) and adjacent midbrain tissue. This identified over 3700 transcripts, including the three most abundant SAGE tags, which did not correspond to any known genes or ESTs. We developed high-throughput bioinformatics methods to map the genes corresponding to these tags and identified 402 SN genes that lay within five large genomic linkage regions, previously identified in 174 multiplex PD families. These genes represent excellent candidates for PD susceptibility alleles and further genomic convergence and analyses. PMID:12620972

  8. A fast and high performance multiple data integration algorithm for identifying human disease genes

    PubMed Central

    2015-01-01

    Background Integrating multiple data sources is indispensable in improving disease gene identification. It is not only due to the fact that disease genes associated with similar genetic diseases tend to lie close with each other in various biological networks, but also due to the fact that gene-disease associations are complex. Although various algorithms have been proposed to identify disease genes, their prediction performances and the computational time still should be further improved. Results In this study, we propose a fast and high performance multiple data integration algorithm for identifying human disease genes. A posterior probability of each candidate gene associated with individual diseases is calculated by using a Bayesian analysis method and a binary logistic regression model. Two prior probability estimation strategies and two feature vector construction methods are developed to test the performance of the proposed algorithm. Conclusions The proposed algorithm is not only generated predictions with high AUC scores, but also runs very fast. When only a single PPI network is employed, the AUC score is 0.769 by using F2 as feature vectors. The average running time for each leave-one-out experiment is only around 1.5 seconds. When three biological networks are integrated, the AUC score using F3 as feature vectors increases to 0.830, and the average running time for each leave-one-out experiment takes only about 12.54 seconds. It is better than many existing algorithms. PMID:26399620

  9. De Novo Transcriptome Sequencing of Oryza officinalis Wall ex Watt to Identify Disease-Resistance Genes

    PubMed Central

    He, Bin; Gu, Yinghong; Tao, Xiang; Cheng, Xiaojie; Wei, Changhe; Fu, Jian; Cheng, Zaiquan; Zhang, Yizheng

    2015-01-01

    Oryza officinalis Wall ex Watt is one of the most important wild relatives of cultivated rice and exhibits high resistance to many diseases. It has been used as a source of genes for introgression into cultivated rice. However, there are limited genomic resources and little genetic information publicly reported for this species. To better understand the pathways and factors involved in disease resistance and accelerating the process of rice breeding, we carried out a de novo transcriptome sequencing of O. officinalis. In this research, 137,229 contigs were obtained ranging from 200 to 19,214 bp with an N50 of 2331 bp through de novo assembly of leaves, stems and roots in O. officinalis using an Illumina HiSeq 2000 platform. Based on sequence similarity searches against a non-redundant protein database, a total of 88,249 contigs were annotated with gene descriptions and 75,589 transcripts were further assigned to GO terms. Candidate genes for plant–pathogen interaction and plant hormones regulation pathways involved in disease-resistance were identified. Further analyses of gene expression profiles showed that the majority of genes related to disease resistance were all expressed in the three tissues. In addition, there are two kinds of rice bacterial blight-resistant genes in O. officinalis, including two Xa1 genes and three Xa26 genes. All 2 Xa1 genes showed the highest expression level in stem, whereas one of Xa26 was expressed dominantly in leaf and other 2 Xa26 genes displayed low expression level in all three tissues. This transcriptomic database provides an opportunity for identifying the genes involved in disease-resistance and will provide a basis for studying functional genomics of O. officinalis and genetic improvement of cultivated rice in the future. PMID:26690414

  10. Gene interaction enrichment and network analysis to identify dysregulated pathways and their interactions in complex diseases

    PubMed Central

    2012-01-01

    Background The molecular behavior of biological systems can be described in terms of three fundamental components: (i) the physical entities, (ii) the interactions among these entities, and (iii) the dynamics of these entities and interactions. The mechanisms that drive complex disease can be productively viewed in the context of the perturbations of these components. One challenge in this regard is to identify the pathways altered in specific diseases. To address this challenge, Gene Set Enrichment Analysis (GSEA) and others have been developed, which focus on alterations of individual properties of the entities (such as gene expression). However, the dynamics of the interactions with respect to disease have been less well studied (i.e., properties of components ii and iii). Results Here, we present a novel method called Gene Interaction Enrichment and Network Analysis (GIENA) to identify dysregulated gene interactions, i.e., pairs of genes whose relationships differ between disease and control. Four functions are defined to model the biologically relevant gene interactions of cooperation (sum of mRNA expression), competition (difference between mRNA expression), redundancy (maximum of expression), or dependency (minimum of expression) among the expression levels. The proposed framework identifies dysregulated interactions and pathways enriched in dysregulated interactions; points out interactions that are perturbed across pathways; and moreover, based on the biological annotation of each type of dysregulated interaction gives clues about the regulatory logic governing the systems level perturbation. We demonstrated the potential of GIENA using published datasets related to cancer. Conclusions We showed that GIENA identifies dysregulated pathways that are missed by traditional enrichment methods based on the individual gene properties and that use of traditional methods combined with GIENA provides coverage of the largest number of relevant pathways. In addition

  11. A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases.

    PubMed

    Gustafsson, Mika; Gawel, Danuta R; Alfredsson, Lars; Baranzini, Sergio; Björkander, Janne; Blomgran, Robert; Hellberg, Sandra; Eklund, Daniel; Ernerudh, Jan; Kockum, Ingrid; Konstantinell, Aelita; Lahesmaa, Riita; Lentini, Antonio; Liljenström, H Robert I; Mattson, Lina; Matussek, Andreas; Mellergård, Johan; Mendez, Melissa; Olsson, Tomas; Pujana, Miguel A; Rasool, Omid; Serra-Musach, Jordi; Stenmarker, Margaretha; Tripathi, Subhash; Viitala, Miro; Wang, Hui; Zhang, Huan; Nestor, Colm E; Benson, Mikael

    2015-11-11

    Early regulators of disease may increase understanding of disease mechanisms and serve as markers for presymptomatic diagnosis and treatment. However, early regulators are difficult to identify because patients generally present after they are symptomatic. We hypothesized that early regulators of T cell-associated diseases could be found by identifying upstream transcription factors (TFs) in T cell differentiation and by prioritizing hub TFs that were enriched for disease-associated polymorphisms. A gene regulatory network (GRN) was constructed by time series profiling of the transcriptomes and methylomes of human CD4(+) T cells during in vitro differentiation into four helper T cell lineages, in combination with sequence-based TF binding predictions. The TFs GATA3, MAF, and MYB were identified as early regulators and validated by ChIP-seq (chromatin immunoprecipitation sequencing) and small interfering RNA knockdowns. Differential mRNA expression of the TFs and their targets in T cell-associated diseases supports their clinical relevance. To directly test if the TFs were altered early in disease, T cells from patients with two T cell-mediated diseases, multiple sclerosis and seasonal allergic rhinitis, were analyzed. Strikingly, the TFs were differentially expressed during asymptomatic stages of both diseases, whereas their targets showed altered expression during symptomatic stages. This analytical strategy to identify early regulators of disease by combining GRNs with genome-wide association studies may be generally applicable for functional and clinical studies of early disease development. PMID:26560356

  12. Genomic convergence to identify candidate genes for Parkinson disease: SAGE analysis of the substantia nigra.

    PubMed

    Noureddine, Maher A; Li, Yi-Ju; van der Walt, Joelle M; Walters, Robert; Jewett, Rita M; Xu, Hong; Wang, Tianyuan; Walter, Jeffrey W; Scott, Burton L; Hulette, Christine; Schmechel, Don; Stenger, Judith E; Dietrich, Fred; Vance, Jeffery M; Hauser, Michael A

    2005-10-01

    Genomic convergence is a multistep approach that combines gene expression with genomic linkage to identify and prioritize susceptibility genes for complex disease. As a first step, we previously performed linkage analysis on 174 multiplex Parkinson's disease (PD) families, identifying five peaks for PD risk and two for genes affecting age at onset (AAO) in PD [Hauser et al., Hum Mol Genet 2003;12:671-677]. We report here the next step: serial analysis of gene expression [SAGE; Scott et al., JAMA 2001;286:2239-2242] to analyze substantia nigra tissue from three PD patients and two age-matched controls. We find 933 differentially expressed genes (P<0.05) between PD and controls, but of these, only 50 genes represented by unique SAGE tags map within our previously described PD linkage regions. Furthermore, genes encoded by mitochondrial DNA are expressed 1.5-fold higher in PD patients versus controls, without an increase in the corresponding nuclear-encoded mitochondrial components, suggesting an increase in mtDNA genomes in PD or a disjunction with nuclear expression. The next step in the genomic convergence process will be to screen these 50 high-quality candidate genes for association with PD risk susceptibility and genetic effects on AAO. PMID:15966006

  13. Neurodegenerative mutants in Drosophila: a means to identify genes and mechanisms involved in human diseases?

    PubMed

    Kretzschmar, Doris

    2005-11-01

    There are 50 ways to leave your lover (Simon 1987) but many more to kill your brain cells. Several neurodegenerative diseases in humans, like Alzheimer's disease, have been intensely studied but the underlying cellular and molecular mechanisms are still unknown for most of them. For those syndromes where associated gene products have been identified their biochemistry and physiological as well as pathogenic function is often still under debate. This is in part due to the inherent limitations of genetic analyses in humans and other mammals and therefore experimentally accessible invertebrate in vivo models, such as Caenorhabditis elegans and Drosophila melanogaster, have recently been introduced to investigate neurodegenerative syndromes. Several laboratories have used transgenic approaches in Drosophila to study the human genes associated with neurodegenerative diseases. This has added substantially to our understanding of the mechanisms leading to neurodegenerative diseases in humans. The isolation and characterization of Drosophila mutants, which display a variety of neurodegenerative phenotypes, also provide valuable insights into genes, pathways, and mechanisms causing neurodegeneration. So far only about two dozen such mutants have been described but already their characterization reveals an involvement of various cellular functions in neurodegeneration, ranging from preventing oxidative stress to RNA editing. Some of the isolated genes can already be associated with human neurodegenerative diseases and hopefully the isolation and characterization of more of these mutants, together with an analysis of homologous genes in vertebrate models, will provide insights into the genetic and molecular basis of human neurodegenerative diseases. PMID:16187075

  14. Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach

    PubMed Central

    Song, Min

    2016-01-01

    In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications. PMID:27195695

  15. Gene Expression-Based Screen for Parkinson's Disease Identifies GW8510 as a Neuroprotective Agent.

    PubMed

    Wimalasena, Nivanthika K; Le, Viet Q; Wimalasena, Kandatege; Schreiber, Stuart L; Karmacharya, Rakesh

    2016-07-20

    We carried out a gene expression-based in silico screen in order to identify small molecules with gene-expression profiles that are anticorrelated with a gene-expression profile for Parkinson's disease (PD). We identified the cyclin-dependent kinase 2/5 (CDK2/5) inhibitor GW8510 as our most significant hit and characterized its effects in rodent MN9D cells and in human neuronal cells derived from induced pluripotent stem cells. GW8510 demonstrated neuroprotective ability in MN9D cells in the presence of 1-methyl-4-phenylpyridium (MPP(+)), a widely used neurotoxin model for Parkinson's disease. In order to delineate the nature and extent of GW8510's neuroprotective properties, we studied GW8510 in human neuronal cells in the context of various mechanisms of cellular stress. We found that GW8510 was protective against small-molecule mitochondrial and endoplasmic reticulum stressors. Our findings illustrate an approach to using small-molecule gene expression libraries to identify compounds with therapeutic potential in human diseases. PMID:27270122

  16. A Special Local Clustering Algorithm for Identifying the Genes Associated With Alzheimer’s Disease

    PubMed Central

    Pang, Chao-Yang; Hu, Wei; Hu, Ben-Qiong; Shi, Ying; Vanderburg, Charles R.; Rogers, Jack T.

    2010-01-01

    Clustering is the grouping of similar objects into a class. Local clustering feature refers to the phenomenon whereby one group of data is separated from another, and the data from these different groups are clustered locally. A compact class is defined as one cluster in which all similar elements cluster tightly within the cluster. Herein, the essence of the local clustering feature, revealed by mathematical manipulation, results in a novel clustering algorithm termed as the special local clustering (SLC) algorithm that was used to process gene microarray data related to Alzheimer’s disease (AD). SLC algorithm was able to group together genes with similar expression patterns and identify significantly varied gene expression values as isolated points. If a gene belongs to a compact class in control data and appears as an isolated point in incipient, moderate and/or severe AD gene microarray data, this gene is possibly associated with AD. Application of a clustering algorithm in disease-associated gene identification such as in AD is rarely reported. PMID:20089478

  17. Identifying human disease genes: advances in molecular genetics and computational approaches.

    PubMed

    Bakhtiar, S M; Ali, A; Baig, S M; Barh, D; Miyoshi, A; Azevedo, V

    2014-01-01

    The human genome project is one of the significant achievements that have provided detailed insight into our genetic legacy. During the last two decades, biomedical investigations have gathered a considerable body of evidence by detecting more than 2000 disease genes. Despite the imperative advances in the genetic understanding of various diseases, the pathogenesis of many others remains obscure. With recent advances, the laborious methodologies used to identify DNA variations are replaced by direct sequencing of genomic DNA to detect genetic changes. The ability to perform such studies depends equally on the development of high-throughput and economical genotyping methods. Currently, basically for every disease whose origen is still unknown, genetic approaches are available which could be pedigree-dependent or -independent with the capacity to elucidate fundamental disease mechanisms. Computer algorithms and programs for linkage analysis have formed the foundation for many disease gene detection projects, similarly databases of clinical findings have been widely used to support diagnostic decisions in dysmorphology and general human disease. For every disease type, genome sequence variations, particularly single nucleotide polymorphisms are mapped by comparing the genetic makeup of case and control groups. Methods that predict the effects of polymorphisms on protein stability are useful for the identification of possible disease associations, whereas structural effects can be assessed using methods to predict stability changes in proteins using sequence and/or structural information. PMID:25061732

  18. Application of biclustering of gene expression data and gene set enrichment analysis methods to identify potentially disease causing nanomaterials

    PubMed Central

    Halappanavar, Sabina

    2015-01-01

    Summary Background: The presence of diverse types of nanomaterials (NMs) in commerce is growing at an exponential pace. As a result, human exposure to these materials in the environment is inevitable, necessitating the need for rapid and reliable toxicity testing methods to accurately assess the potential hazards associated with NMs. In this study, we applied biclustering and gene set enrichment analysis methods to derive essential features of altered lung transcriptome following exposure to NMs that are associated with lung-specific diseases. Several datasets from public microarray repositories describing pulmonary diseases in mouse models following exposure to a variety of substances were examined and functionally related biclusters of genes showing similar expression profiles were identified. The identified biclusters were then used to conduct a gene set enrichment analysis on pulmonary gene expression profiles derived from mice exposed to nano-titanium dioxide (nano-TiO2), carbon black (CB) or carbon nanotubes (CNTs) to determine the disease significance of these data-driven gene sets. Results: Biclusters representing inflammation (chemokine activity), DNA binding, cell cycle, apoptosis, reactive oxygen species (ROS) and fibrosis processes were identified. All of the NM studies were significant with respect to the bicluster related to chemokine activity (DAVID; FDR p-value = 0.032). The bicluster related to pulmonary fibrosis was enriched in studies where toxicity induced by CNT and CB studies was investigated, suggesting the potential for these materials to induce lung fibrosis. The pro-fibrogenic potential of CNTs is well established. Although CB has not been shown to induce fibrosis, it induces stronger inflammatory, oxidative stress and DNA damage responses than nano-TiO2 particles. Conclusion: The results of the analysis correctly identified all NMs to be inflammogenic and only CB and CNTs as potentially fibrogenic. In addition to identifying several

  19. Integromic Analysis of Genetic Variation and Gene Expression Identifies Networks for Cardiovascular Disease Phenotypes

    PubMed Central

    Yao, Chen; Chen, Brian H.; Joehanes, Roby; Otlu, Burcak; Zhang, Xiaoling; Liu, Chunyu; Huan, Tianxiao; Tastan, Oznur; Cupples, L. Adrienne; Meigs, James B.; Fox, Caroline S.; Freedman, Jane E.; Courchesne, Paul; O’Donnell, Christopher J.; Munson, Peter J.; Keles, Sunduz; Levy, Daniel

    2015-01-01

    Background Cardiovascular disease (CVD) reflects a highly coordinated complex of traits. Although genome-wide association studies have reported numerous single nucleotide polymorphisms (SNPs) to be associated with CVD, the role of most of these variants in disease processes remains unknown. Methods and Results We built a CVD network using 1512 SNPs associated with 21 CVD traits in genome-wide association studies (at P≤5×10−8) and cross-linked different traits by virtue of their shared SNP associations. We then explored whole blood gene expression in relation to these SNPs in 5257 participants in the Framingham Heart Study. At a false discovery rate <0.05, we identified 370 cis-expression quantitative trait loci (eQTLs; SNPs associated with altered expression of nearby genes) and 44 trans-eQTLs (SNPs associated with altered expression of remote genes). The eQTL network revealed 13 CVD-related modules. Searching for association of eQTL genes with CVD risk factors (lipids, blood pressure, fasting blood glucose, and body mass index) in the same individuals, we found examples in which the expression of eQTL genes was significantly associated with these CVD phenotypes. In addition, mediation tests suggested that a subset of SNPs previously associated with CVD phenotypes in genome-wide association studies may exert their function by altering expression of eQTL genes (eg, LDLR and PCSK7), which in turn may promote interindividual variation in phenotypes. Conclusions Using a network approach to analyze CVD traits, we identified complex networks of SNP-phenotype and SNP-transcript connections. Integrating the CVD network with phenotypic data, we identified biological pathways that may provide insights into potential drug targets for treatment or prevention of CVD. PMID:25533967

  20. Genetic similarity between cancers and comorbid Mendelian diseases identifies candidate driver genes

    PubMed Central

    Melamed, Rachel D.; Emmett, Kevin J.; Madubata, Chioma; Rzhetsky, Andrey; Rabadan, Raul

    2015-01-01

    Despite large-scale cancer genomics studies, key somatic mutations driving cancer, and their functional roles, remain elusive. Here we propose that analysis of comorbidities of Mendelian diseases with cancers provides a novel, systematic way to discover new cancer genes. If germline genetic variation in Mendelian loci predisposes bearers to common cancers, the same loci may harbor cancer-associated somatic variation. Compilations of clinical records spanning over 100 million patients provide an unprecedented opportunity to assess clinical associations between Mendelian diseases and cancers. We systematically compare these comorbidities against recurrent somatic mutations from more than five thousand patients across many cancers. Using multiple measures of genetic similarity, we show that a Mendelian disease and comorbid cancer indeed have genetic alterations of significant functional similarity. This result provides a basis to identify candidate drivers in cancers including melanoma and glioblastoma. Some Mendelian diseases demonstrate “pan-cancer” comorbidity and shared genetics across cancers. PMID:25926297

  1. Identifying driving gene clusters in complex diseases through critical transition theory

    NASA Astrophysics Data System (ADS)

    Wolanyk, Nathaniel; Wang, Xujing; Hessner, Martin; Gao, Shouguo; Chen, Ye; Jia, Shuang

    A novel approach of looking at the human body using critical transition theory has yielded positive results: clusters of genes that act in tandem to drive complex disease progression. This cluster of genes can be thought of as the first part of a large genetic force that pushes the body from a curable, but sick, point to an incurable diseased point through a catastrophic bifurcation. The data analyzed is time course microarray blood assay data of 7 high risk individuals for Type 1 Diabetes who progressed into a clinical onset, with an additional larger study requested to be presented at the conference. The normalized data is 25,000 genes strong, which were narrowed down based on statistical metrics, and finally a machine learning algorithm using critical transition metrics found the driving network. This approach was created to be repeatable across multiple complex diseases with only progression time course data needed so that it would be applicable to identifying when an individual is at risk of developing a complex disease. Thusly, preventative measures can be enacted, and in the longer term, offers a possible solution to prevent all Type 1 Diabetes.

  2. Exome sequencing identified FGF12 as a novel candidate gene for Kashin-Beck disease.

    PubMed

    Zhang, Feng; Dai, Lanlan; Lin, Weimin; Wang, Wenyu; Liu, Xuanzhu; Zhang, Jianguo; Yang, Tielin; Liu, Xiaogang; Shen, Hui; Chen, Xiangding; Tan, Lijun; Tian, Qing; Deng, Hong-Wen; Xu, Xun; Guo, Xiong

    2016-01-01

    The objective of this study was to identify novel causal genes involved in the pathogenesis of Kashin-Beck disease (KBD). A representative grade III KBD sib pair with serious skeletal growth and development failure was subjected to exome sequencing using the Illumina Hiseq2000 platform. The detected gene mutations were then filtered against the data of 1000 Genome Project, dbSNP database, and BGI inhouse database, and replicated by a genome-wide association study (GWAS) of KBD. Ninety grade II or III KBD patients with extreme KBD phenotypes and 1627 healthy controls were enrolled in the GWAS. Affymetrix Genome-Wide Human SNP Array 6.0 was applied for genotyping. PLINK software was used for association analysis. We identified a novel 106T>C at the 3'UTR of the FGF12 gene, which has not been reported by now. Sequence alignment observed high conversation at the mutated 3'UTR+106T>C locus across various vertebrates. In the GWAS of KBD, we detected nine SNPs of the FGF12 gene showing association evidence (P value < 0.05) with KBD. The most significant association signal was observed at rs1847340 (P value = 1.90 × 10(-5)). This study suggests that FGF12 was a susceptibility gene of KBD. Our results provide novel clues for revealing the pathogenesis of KBD and the biological function of FGF12. PMID:26290467

  3. Integrated analysis of differential gene expression profiles in hippocampi to identify candidate genes involved in Alzheimer's disease

    PubMed Central

    HU, WANHUA; LIN, XIAODONG; CHEN, KELONG

    2015-01-01

    Alzheimer's disease (AD) is a complex neurodegenerative disorder with largely unknown genetic mechanisms. Identifying altered neuronal gene expression in AD may provide diagnostic or therapeutic targets for AD. The present study aimed to identify differentially expressed genes (DEGs) and their further association with other biological processes that regulate causative factors for AD. The present study performed an integrated analysis of publicly available gene expression omnibus datasets of AD hippocampi. Gene ontology (GO) enrichment analyses, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Protein-Protein interaction (PPI) network analysis were performed. The present study detected 295 DEGs (109 upregulated and 186 downregulated genes) in hippocampi between AD and control samples by integrating four datasets of gene expression profiles of hippocampi of patients with AD. Respiratory electron transport chain (GO: 0022904; P=1.64×10−11) was the most significantly enriched GO term among biological processes, while for molecular functions, the most significantly enriched GO term was that of protein binding (GO: 0005515; P=3.03×10−29), and for cellular components, the most significantly enriched GO term was that of the cytoplasm (GO: 0005737; P=8.67×10−33). The most significant pathway in the KEGG analysis was oxidative phosphorylation (P=1.61×10−13). PPI network analysis showed that the significant hub proteins contained β-actin (degree, 268), hepatoma-derived growth factor (degree, 218) and WD repeat-containing protein 82 (degree, 87). The integrated analysis performed in the present study serves as a basis for identifying novel drug targets to develop improved therapies and interventions for common and devastating neurological diseases such as AD. PMID:26324066

  4. Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets.

    PubMed

    Vinayagam, Arunachalam; Gibson, Travis E; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

    2016-05-01

    The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. PMID:27091990

  5. Large-scale gene-centric analysis identifies novel variants for coronary artery disease.

    PubMed

    2011-09-01

    Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ∼2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p<10(-33); LPA:p<10(-19); 1p13.3:p<10(-17)) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p<5×10(-7)). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06-1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ∼4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity = 0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and

  6. Integrated immunogenomics in the chicken: Deciphering the immune response to identify disease resistance genes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Resistance to infection takes place at many levels, and involves both non-specific and specific immune mechanisms. The chicken has a different repertoire of immune genes, molecules, cells and organs compared to mammals. To understand the role of any disease resistance gene(s), it is therefore impo...

  7. Novel applications of motif-directed profiling to identify disease resistance genes in plants

    PubMed Central

    2013-01-01

    Background Molecular profiling of gene families is a versatile tool to study diversity between individual genomes in sexual crosses and germplasm. Nucleotide binding site (NBS) profiling, in particular, targets conserved nucleotide binding site-encoding sequences of resistance gene analogs (RGAs), and is widely used to identify molecular markers for disease resistance (R) genes. Results In this study, we used NBS profiling to identify genome-wide locations of RGA clusters in the genome of potato clone RH. Positions of RGAs in the potato RH and DM genomes that were generated using profiling and genome sequencing, respectively, were compared. Largely overlapping results, but also interesting discrepancies, were found. Due to the clustering of RGAs, several parts of the genome are overexposed while others remain underexposed using NBS profiling. It is shown how the profiling of other gene families, i.e. protein kinases and different protein domain-coding sequences (i.e., TIR), can be used to achieve a better marker distribution. The power of profiling techniques is further illustrated using RGA cluster-directed profiling in a population of Solanum berthaultii. Multiple different paralogous RGAs within the Rpi-ber cluster could be genetically distinguished. Finally, an adaptation of the profiling protocol was made that allowed the parallel sequencing of profiling fragments using next generation sequencing. The types of RGAs that were tagged in this next-generation profiling approach largely overlapped with classical gel-based profiling. As a potential application of next-generation profiling, we showed how the R gene family associated with late blight resistance in the SH*RH population could be identified using a bulked segregant approach. Conclusions In this study, we provide a comprehensive overview of previously described and novel profiling primers and their genomic targets in potato through genetic mapping and comparative genomics. Furthermore, it is shown how

  8. Sensitized phenotypic screening identifies gene dosage sensitive region on chromosome 11 that predisposes to disease in mice

    PubMed Central

    Ermakova, Olga; Piszczek, Lukasz; Luciani, Luisa; Cavalli, Florence M G; Ferreira, Tiago; Farley, Dominika; Rizzo, Stefania; Paolicelli, Rosa Chiara; Al-Banchaabouchi, Mumna; Nerlov, Claus; Moriggl, Richard; Luscombe, Nicholas M; Gross, Cornelius

    2011-01-01

    The identification of susceptibility genes for human disease is a major goal of current biomedical research. Both sequence and structural variation have emerged as major genetic sources of phenotypic variability and growing evidence points to copy number variation as a particularly important source of susceptibility for disease. Here we propose and validate a strategy to identify genes in which changes in dosage alter susceptibility to disease-relevant phenotypes in the mouse. Our approach relies on sensitized phenotypic screening of megabase-sized chromosomal deletion and deficiency lines carrying altered copy numbers of ∼30 linked genes. This approach offers several advantages as a method to systematically identify genes involved in disease susceptibility. To examine the feasibility of such a screen, we performed sensitized phenotyping in five therapeutic areas (metabolic syndrome, immune dysfunction, atherosclerosis, cancer and behaviour) of a 0.8 Mb reciprocal chromosomal duplication and deficiency on chromosome 11 containing 27 genes. Gene dosage in the region significantly affected risk for high-fat diet-induced metabolic syndrome, antigen-induced immune hypersensitivity, ApoE-induced atherosclerosis, and home cage activity. Follow up studies on individual gene knockouts for two candidates in the region showed that copy number variation in Stat5 was responsible for the phenotypic variation in antigen-induced immune hypersensitivity and metabolic syndrome. These data demonstrate the power of sensitized phenotypic screening of segmental aneuploidy lines to identify disease susceptibility genes. PMID:21204268

  9. Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease.

    PubMed

    Johnson, Michael R; Shkura, Kirill; Langley, Sarah R; Delahaye-Duriez, Andree; Srivastava, Prashant; Hill, W David; Rackham, Owen J L; Davies, Gail; Harris, Sarah E; Moreno-Moral, Aida; Rotival, Maxime; Speed, Doug; Petrovski, Slavé; Katz, Anaïs; Hayward, Caroline; Porteous, David J; Smith, Blair H; Padmanabhan, Sandosh; Hocking, Lynne J; Starr, John M; Liewald, David C; Visconti, Alessia; Falchi, Mario; Bottolo, Leonardo; Rossetti, Tiziana; Danis, Bénédicte; Mazzuferi, Manuela; Foerch, Patrik; Grote, Alexander; Helmstaedter, Christoph; Becker, Albert J; Kaminski, Rafal M; Deary, Ian J; Petretto, Enrico

    2016-02-01

    Genetic determinants of cognition are poorly characterized, and their relationship to genes that confer risk for neurodevelopmental disease is unclear. Here we performed a systems-level analysis of genome-wide gene expression data to infer gene-regulatory networks conserved across species and brain regions. Two of these networks, M1 and M3, showed replicable enrichment for common genetic variants underlying healthy human cognitive abilities, including memory. Using exome sequence data from 6,871 trios, we found that M3 genes were also enriched for mutations ascertained from patients with neurodevelopmental disease generally, and intellectual disability and epileptic encephalopathy in particular. M3 consists of 150 genes whose expression is tightly developmentally regulated, but which are collectively poorly annotated for known functional pathways. These results illustrate how systems-level analyses can reveal previously unappreciated relationships between neurodevelopmental disease-associated genes in the developed human brain, and provide empirical support for a convergent gene-regulatory network influencing cognition and neurodevelopmental disease. PMID:26691832

  10. Next generation exome sequencing of paediatric inflammatory bowel disease patients identifies rare and novel variants in candidate genes

    PubMed Central

    Christodoulou, Katja; Wiskin, Anthony E; Gibson, Jane; Tapper, William; Willis, Claire; Afzal, Nadeem A; Upstill-Goddard, Rosanna; Holloway, John W; Simpson, Michael A; Beattie, R Mark; Collins, Andrew

    2013-01-01

    Background Multiple genes have been implicated by association studies in altering inflammatory bowel disease (IBD) predisposition. Paediatric patients often manifest more extensive disease and a particularly severe disease course. It is likely that genetic predisposition plays a more substantial role in this group. Objective To identify the spectrum of rare and novel variation in known IBD susceptibility genes using exome sequencing analysis in eight individual cases of childhood onset severe disease. Design DNA samples from the eight patients underwent targeted exome capture and sequencing. Data were processed through an analytical pipeline to align sequence reads, conduct quality checks, and identify and annotate variants where patient sequence differed from the reference sequence. For each patient, the entire complement of rare variation within strongly associated candidate genes was catalogued. Results Across the panel of 169 known IBD susceptibility genes, approximately 300 variants in 104 genes were found. Excluding splicing and HLA-class variants, 58 variants across 39 of these genes were classified as rare, with an alternative allele frequency of <5%, of which 17 were novel. Only two patients with early onset Crohn's disease exhibited rare deleterious variations within NOD2: the previously described R702W variant was the sole NOD2 variant in one patient, while the second patient also carried the L1007 frameshift insertion. Both patients harboured other potentially damaging mutations in the GSDMB, ERAP2 and SEC16A genes. The two patients severely affected with ulcerative colitis exhibited a distinct profile: both carried potentially detrimental variation in the BACH2 and IL10 genes not seen in other patients. Conclusion For each of the eight individuals studied, all non-synonymous, truncating and frameshift mutations across all known IBD genes were identified. A unique profile of rare and potentially damaging variants was evident for each patient with this

  11. Disease-Targeted Sequencing of Ion Channel Genes identifies de novo mutations in Patients with Non-Familial Brugada Syndrome

    PubMed Central

    Juang, Jyh-Ming Jimmy; Lu, Tzu-Pin; Lai, Liang-Chuan; Ho, Chia-Chuan; Liu, Yen-Bin; Tsai, Chia-Ti; Lin, Lian-Yu; Yu, Chih-Chieh; Chen, Wen-Jone; Chiang, Fu-Tien; Yeh, Shih-Fan Sherri; Lai, Ling-Ping; Chuang, Eric Y.; Lin, Jiunn-Lee

    2014-01-01

    Brugada syndrome (BrS) is one of the ion channelopathies associated with sudden cardiac death (SCD). The most common BrS-associated gene (SCN5A) only accounts for approximately 20–25% of BrS patients. This study aims to identify novel mutations across human ion channels in non-familial BrS patients without SCN5A variants through disease-targeted sequencing. We performed disease-targeted multi-gene sequencing across 133 human ion channel genes and 12 reported BrS-associated genes in 15 unrelated, non-familial BrS patients without SCN5A variants. Candidate variants were validated by mass spectrometry and Sanger sequencing. Five de novo mutations were identified in four genes (SCNN1A, KCNJ16, KCNB2, and KCNT1) in three BrS patients (20%). Two of the three patients presented SCD and one had syncope. Interestingly, the two patients presented with SCD had compound mutations (SCNN1A:Arg350Gln and KCNB2:Glu522Lys; SCNN1A:Arg597* and KCNJ16:Ser261Gly). Importantly, two SCNN1A mutations were identified from different families. The KCNT1:Arg1106Gln mutation was identified in a patient with syncope. Bioinformatics algorithms predicted severe functional interruptions in these four mutation loci, suggesting their pivotal roles in BrS. This study identified four novel BrS-associated genes and indicated the effectiveness of this disease-targeted sequencing across ion channel genes for non-familial BrS patients without SCN5A variants. PMID:25339316

  12. Using gene chips to identify organ-specific, smooth muscle responses to experimental diabetes: potential applications to urological diseases

    PubMed Central

    Tar, Moses; Valcic, Mira; Knoll, Abraham; Melman, Arnold

    2007-01-01

    OBJECTIVE To identify early diabetes-related alterations in gene expression in bladder and erectile tissue that would provide novel diagnostic and therapeutic treatment targets to prevent, delay or ameliorate the ensuing bladder and erectile dysfunction. MATERIALS AND METHODS The RG-U34A rat GeneChip® (Affymetrix Inc., Sunnyvale, CA, USA) oligonucleotide microarray (containing ≈8799 genes) was used to evaluate gene expression in corporal and male bladder tissue excised from rats 1 week after confirmation of a diabetic state, but before demonstrable changes in organ function in vivo. A conservative analytical approach was used to detect alterations in gene expression, and gene ontology (GO) classifications were used to identify biological themes/pathways involved in the aetiology of the organ dysfunction. RESULTS In all, 320 and 313 genes were differentially expressed in bladder and corporal tissue, respectively. GO analysis in bladder tissue showed prominent increases in biological pathways involved in cell proliferation, metabolism, actin cytoskeleton and myosin, as well as decreases in cell motility, and regulation of muscle contraction. GO analysis in corpora showed increases in pathways related to ion channel transport and ion channel activity, while there were decreases in collagen I and actin genes. CONCLUSIONS The changes in gene expression in these initial experiments are consistent with the pathophysiological characteristics of the bladder and erectile dysfunction seen later in the diabetic disease process. Thus, the observed changes in gene expression might be harbingers or biomarkers of impending organ dysfunction, and could provide useful diagnostic and therapeutic targets for a variety of progressive urological diseases/conditions (i.e. lower urinary tract symptoms related to benign prostatic hyperplasia, erectile dysfunction, etc.). PMID:17313427

  13. Genome-wide transcriptional analysis of flagellar regeneration in Chlamydomonas reinhardtii identifies orthologs of ciliary disease genes

    NASA Technical Reports Server (NTRS)

    Stolc, Viktor; Samanta, Manoj Pratim; Tongprasit, Waraporn; Marshall, Wallace F.

    2005-01-01

    The important role that cilia and flagella play in human disease creates an urgent need to identify genes involved in ciliary assembly and function. The strong and specific induction of flagellar-coding genes during flagellar regeneration in Chlamydomonas reinhardtii suggests that transcriptional profiling of such cells would reveal new flagella-related genes. We have conducted a genome-wide analysis of RNA transcript levels during flagellar regeneration in Chlamydomonas by using maskless photolithography method-produced DNA oligonucleotide microarrays with unique probe sequences for all exons of the 19,803 predicted genes. This analysis represents previously uncharacterized whole-genome transcriptional activity profiling study in this important model organism. Analysis of strongly induced genes reveals a large set of known flagellar components and also identifies a number of important disease-related proteins as being involved with cilia and flagella, including the zebrafish polycystic kidney genes Qilin, Reptin, and Pontin, as well as the testis-expressed tubby-like protein TULP2.

  14. Genome-wide transcriptional analysis of flagellar regeneration in Chlamydomonas reinhardtii identifies orthologs of ciliary disease genes

    PubMed Central

    Stolc, Viktor; Samanta, Manoj Pratim; Tongprasit, Waraporn; Marshall, Wallace F.

    2005-01-01

    The important role that cilia and flagella play in human disease creates an urgent need to identify genes involved in ciliary assembly and function. The strong and specific induction of flagellar-coding genes during flagellar regeneration in Chlamydomonas reinhardtii suggests that transcriptional profiling of such cells would reveal new flagella-related genes. We have conducted a genome-wide analysis of RNA transcript levels during flagellar regeneration in Chlamydomonas by using maskless photolithography method-produced DNA oligonucleotide microarrays with unique probe sequences for all exons of the 19,803 predicted genes. This analysis represents previously uncharacterized whole-genome transcriptional activity profiling study in this important model organism. Analysis of strongly induced genes reveals a large set of known flagellar components and also identifies a number of important disease-related proteins as being involved with cilia and flagella, including the zebrafish polycystic kidney genes Qilin, Reptin, and Pontin, as well as the testis-expressed tubby-like protein TULP2. PMID:15738400

  15. Chicks and SNPs--an entree into identifying genes conferring disease resistance in chicken

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With high-density chicken rearing, control of infectious diseases are critical for economic viability and maintaining public confidence in poultry products. Among poultry diseases, Marek’s disease (MD), a lymphoproliferative disease caused by the highly oncogenic herpesvirus Marek's disease virus (M...

  16. Diagnostic Exome Sequencing Identifies a Novel Gene, EMILIN1, Associated with Autosomal‐Dominant Hereditary Connective Tissue Disease

    PubMed Central

    Capuano, Alessandra; Bucciotti, Francesco; Farwell, Kelly D.; Tippin Davis, Brigette; Mroske, Cameron; Hulick, Peter J.; Weissman, Scott M.; Gao, Qingshen; Spessotto, Paola; Doliana, Roberto

    2015-01-01

    ABSTRACT Heritable connective tissue diseases are a highly heterogeneous family of over 200 disorders that affect the extracellular matrix. While the genetic basis of several disorders is established, the etiology has not been discovered for a large portion of patients, likely due to rare yet undiscovered disease genes. By performing trio‐exome sequencing of a 55‐year‐old male proband presenting with multiple symptoms indicative of a connective disorder, we identified a heterozygous missense alteration in exon 1 of the Elastin Microfibril Interfacer 1 (EMILIN1) gene, c.64G>A (p.A22T). The proband presented with ascending and descending aortic aneurysms, bilateral lower leg and foot sensorimotor peripheral neuropathy, arthropathy, and increased skin elasticity. Sanger sequencing confirmed that the EMILIN1 alteration, which maps around the signal peptide cleavage site, segregated with disease in the affected proband, mother, and son. The impaired secretion of EMILIN‐1 in cells transfected with the mutant p.A22T coincided with abnormal protein accumulation within the endoplasmic reticulum. In skin biopsy of the proband, we detected less EMILIN‐1 with disorganized and abnormal coarse fibrils, aggregated deposits underneath the epidermis basal lamina, and dermal cells apoptosis. These findings collectively suggest that EMILIN1 may represent a new disease gene associated with an autosomal‐dominant connective tissue disorder. PMID:26462740

  17. Chicks and single-nucleotide polymorphisms: an entree into identifying genes conferring disease resistance in chicken

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek's disease (MD) is one of the most serious chronic infectious disease threats to the U.S. poultry industry. Selecting for increased genetic resistance to MD is a control strategy that can augment current vaccinal control measures. Although our previous efforts integrating various genomic scre...

  18. Saccharomyces Fungemia Associated with Esophageal Disease Identified by D1/D2 Ribosomal RNA Gene Sequence

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Disseminated Saccharomyces infection has been reported in immunosuppressed patients treated with probiotics, but disseminated Saccharomyces cerevisiae infection associated with underlying esophageal disease is not previously described. Saccharomyces cerevisiae (which occasionally colonizes the gast...

  19. Multistudy Fine Mapping of Chromosome 2q Identifies XRCC5 as a Chronic Obstructive Pulmonary Disease Susceptibility Gene

    PubMed Central

    Hersh, Craig P.; Pillai, Sreekumar G.; Zhu, Guohua; Lomas, David A.; Bakke, Per; Gulsvik, Amund; DeMeo, Dawn L.; Klanderman, Barbara J.; Lazarus, Ross; Litonjua, Augusto A.; Sparrow, David; Reilly, John J.; Agusti, Alvar; Calverley, Peter M. A.; Donner, Claudio F.; Levy, Robert D.; Make, Barry J.; Paré, Peter D.; Rennard, Stephen I.; Vestbo, Jørgen; Wouters, Emiel F. M.; Scholand, Mary Beth; Coon, Hilary; Hoidal, John; Silverman, Edwin K.

    2010-01-01

    Rationale: Several family-based studies have identified genetic linkage for lung function and airflow obstruction to chromosome 2q. Objectives: We hypothesized that merging results of high-resolution single nucleotide polymorphism (SNP) mapping in four separate populations would lead to the identification of chronic obstructive pulmonary disease (COPD) susceptibility genes on chromosome 2q. Methods: Within the chromosome 2q linkage region, 2,843 SNPs were genotyped in 806 COPD cases and 779 control subjects from Norway, and 2,484 SNPs were genotyped in 309 patients with severe COPD from the National Emphysema Treatment Trial and 330 community control subjects. Significant associations from the combined results across the two case-control studies were followed up in 1,839 individuals from 603 families from the International COPD Genetics Network (ICGN) and in 949 individuals from 127 families in the Boston Early-Onset COPD Study. Measurements and Main Results: Merging the results of the two case-control analyses, 14 of the 790 overlapping SNPs had a combined P < 0.01. Two of these 14 SNPs were consistently associated with COPD in the ICGN families. The association with one SNP, located in the gene XRCC5, was replicated in the Boston Early-Onset COPD Study, with a combined P = 2.51 × 10−5 across the four studies, which remains significant when adjusted for multiple testing (P = 0.02). Genotype imputation confirmed the association with SNPs in XRCC5. Conclusions: By combining data from COPD genetic association studies conducted in four independent patient samples, we have identified XRCC5, an ATP-dependent DNA helicase, as a potential COPD susceptibility gene. PMID:20463177

  20. Genome-Wide Association Study Identifies Novel Susceptibility Genes Associated with Coronary Artery Aneurysm Formation in Kawasaki Disease

    PubMed Central

    Guo, Mindy Ming-Huey; Huang, Ying-Hsien; Yu, Hong-Ren; Huang, Fu-Chen; Jiao, Fuyong; Kuo, Hsing-Chun; Andrade, Jorge

    2016-01-01

    Kawasaki disease (KD) or Kawasaki syndrome is known as a vasculitis of small to medium-sized vessels, and coronary arteries are predominantly involved in childhood. Generally, 20–25% of untreated with IVIG and 3–5% of treated KD patients have been developed coronary artery lesions (CALs), such as dilatation and aneurysm. Understanding how coronary artery aneurysms (CAAs) are established and maintained in KD patients is therefore of great importance. Upon our previous genotyping data of 157 valid KD subjects, a genome-wide association study (GWAS) has been conducted among 11 (7%) CAA-developed KD patients to reveal five significant genetic variants passed pre-defined thresholds and resulted in two novel susceptibility protein-coding genes, which are NEBL (rs16921209 (P = 7.44 × 10−9; OR = 32.22) and rs7922552 (P = 8.43 × 10−9; OR = 32.0)) and TUBA3C (rs17076896 (P = 8.04 × 10−9; OR = 21.03)). Their known functions have been reported to associate with cardiac muscle and tubulin, respectively. As a result, this might imply their putative roles of establishing CAAs during KD progression. Additionally, various model analyses have been utilized to determine dominant and recessive inheritance patterns of identified susceptibility mutations. Finally, all susceptibility genes hit by significant genetic variants were further investigated and the top three representative gene-ontology (GO) clusters were regulation of cell projection organization, neuron recognition, and peptidyl-threonine phosphorylation. Our results help to depict the potential routes of the pathogenesis of CAAs in KD patients and will facilitate researchers to improve the diagnosis and prognosis of KD in personalized medicine. PMID:27171184

  1. Genome-Wide Association Study Identifies Novel Susceptibility Genes Associated with Coronary Artery Aneurysm Formation in Kawasaki Disease.

    PubMed

    Kuo, Ho-Chang; Li, Sung-Chou; Guo, Mindy Ming-Huey; Huang, Ying-Hsien; Yu, Hong-Ren; Huang, Fu-Chen; Jiao, Fuyong; Kuo, Hsing-Chun; Andrade, Jorge; Chan, Wen-Ching

    2016-01-01

    Kawasaki disease (KD) or Kawasaki syndrome is known as a vasculitis of small to medium-sized vessels, and coronary arteries are predominantly involved in childhood. Generally, 20-25% of untreated with IVIG and 3-5% of treated KD patients have been developed coronary artery lesions (CALs), such as dilatation and aneurysm. Understanding how coronary artery aneurysms (CAAs) are established and maintained in KD patients is therefore of great importance. Upon our previous genotyping data of 157 valid KD subjects, a genome-wide association study (GWAS) has been conducted among 11 (7%) CAA-developed KD patients to reveal five significant genetic variants passed pre-defined thresholds and resulted in two novel susceptibility protein-coding genes, which are NEBL (rs16921209 (P = 7.44 × 10-9; OR = 32.22) and rs7922552 (P = 8.43 × 10-9; OR = 32.0)) and TUBA3C (rs17076896 (P = 8.04 × 10-9; OR = 21.03)). Their known functions have been reported to associate with cardiac muscle and tubulin, respectively. As a result, this might imply their putative roles of establishing CAAs during KD progression. Additionally, various model analyses have been utilized to determine dominant and recessive inheritance patterns of identified susceptibility mutations. Finally, all susceptibility genes hit by significant genetic variants were further investigated and the top three representative gene-ontology (GO) clusters were regulation of cell projection organization, neuron recognition, and peptidyl-threonine phosphorylation. Our results help to depict the potential routes of the pathogenesis of CAAs in KD patients and will facilitate researchers to improve the diagnosis and prognosis of KD in personalized medicine. PMID:27171184

  2. Identifying Gene Interaction Networks

    PubMed Central

    Bebek, Gurkan

    2016-01-01

    In this chapter, we introduce interaction networks by describing how they are generated, where they are stored, and how they are shared. We focus on publicly available interaction networks and describe a simple way of utilizing these resources. As a case study, we used Cytoscape, an open source and easy-to-use network visualization and analysis tool to first gather and visualize a small network. We have analyzed this network’s topological features and have looked at functional enrichment of the network nodes by integrating the gene ontology database. The methods described are applicable to larger networks that can be collected from various resources. PMID:22307715

  3. Comparison of Expression Profiles in Ovarian Epithelium In Vivo and Ovarian Cancer Identifies Novel Candidate Genes Involved in Disease Pathogenesis

    PubMed Central

    Emmanuel, Catherine; Gava, Natalie; Kennedy, Catherine; Balleine, Rosemary L.; Sharma, Raghwa; Wain, Gerard; Brand, Alison; Hogg, Russell; Etemadmoghadam, Dariush; George, Joshy; Birrer, Michael J.; Clarke, Christine L.; Chenevix-Trench, Georgia; Bowtell, David D. L.; Harnett, Paul R.; deFazio, Anna

    2011-01-01

    Molecular events leading to epithelial ovarian cancer are poorly understood but ovulatory hormones and a high number of life-time ovulations with concomitant proliferation, apoptosis, and inflammation, increases risk. We identified genes that are regulated during the estrous cycle in murine ovarian surface epithelium and analysed these profiles to identify genes dysregulated in human ovarian cancer, using publically available datasets. We identified 338 genes that are regulated in murine ovarian surface epithelium during the estrous cycle and dysregulated in ovarian cancer. Six of seven candidates selected for immunohistochemical validation were expressed in serous ovarian cancer, inclusion cysts, ovarian surface epithelium and in fallopian tube epithelium. Most were overexpressed in ovarian cancer compared with ovarian surface epithelium and/or inclusion cysts (EpCAM, EZH2, BIRC5) although BIRC5 and EZH2 were expressed as highly in fallopian tube epithelium as in ovarian cancer. We prioritised the 338 genes for those likely to be important for ovarian cancer development by in silico analyses of copy number aberration and mutation using publically available datasets and identified genes with established roles in ovarian cancer as well as novel genes for which we have evidence for involvement in ovarian cancer. Chromosome segregation emerged as an important process in which genes from our list of 338 were over-represented including two (BUB1, NCAPD2) for which there is evidence of amplification and mutation. NUAK2, upregulated in ovarian surface epithelium in proestrus and predicted to have a driver mutation in ovarian cancer, was examined in a larger cohort of serous ovarian cancer where patients with lower NUAK2 expression had shorter overall survival. In conclusion, defining genes that are activated in normal epithelium in the course of ovulation that are also dysregulated in cancer has identified a number of pathways and novel candidate genes that may contribute

  4. Gene expression profiling to identify potentially relevant disease outcomes and support human health risk assessment for carbon black nanoparticle exposure.

    PubMed

    Bourdon, Julie A; Williams, Andrew; Kuo, Byron; Moffat, Ivy; White, Paul A; Halappanavar, Sabina; Vogel, Ulla; Wallin, Håkan; Yauk, Carole L

    2013-01-01

    New approaches are urgently needed to evaluate potential hazards posed by exposure to nanomaterials. Gene expression profiling provides information on potential modes of action and human relevance, and tools have recently become available for pathway-based quantitative risk assessment. The objective of this study was to use toxicogenomics in the context of human health risk assessment. We explore the utility of toxicogenomics in risk assessment, using published gene expression data from C57BL/6 mice exposed to 18, 54 and 162 μg Printex 90 carbon black nanoparticles (CBNP). Analysis of CBNP-perturbed pathways, networks and transcription factors revealed concomitant changes in predicted phenotypes (e.g., pulmonary inflammation and genotoxicity), that correlated with dose and time. Benchmark doses (BMDs) for apical endpoints were comparable to minimum BMDs for relevant pathway-specific expression changes. Comparison to inflammatory lung disease models (i.e., allergic airway inflammation, bacterial infection and tissue injury and fibrosis) and human disease profiles revealed that induced gene expression changes in Printex 90 exposed mice were similar to those typical for pulmonary injury and fibrosis. Very similar fibrotic pathways were perturbed in CBNP-exposed mice and human fibrosis disease models. Our synthesis demonstrates how toxicogenomic profiles may be used in human health risk assessment of nanoparticles and constitutes an important step forward in the ultimate recognition of toxicogenomic endpoints in human health risk. As our knowledge of molecular pathways, dose-response characteristics and relevance to human disease continues to grow, we anticipate that toxicogenomics will become increasingly useful in assessing chemical toxicities and in human health risk assessment. PMID:23146762

  5. Systems Analysis of Immune Responses in Marek's Disease Virus-Infected Chickens Identifies a Gene Involved in Susceptibility and Highlights a Possible Novel Pathogenicity Mechanism▿†

    PubMed Central

    Smith, Jacqueline; Sadeyen, Jean-Remy; Paton, Ian R.; Hocking, Paul M.; Salmon, Nigel; Fife, Mark; Nair, Venugopal; Burt, David W.; Kaiser, Pete

    2011-01-01

    Marek's disease virus (MDV) is a highly contagious oncogenic alphaherpesvirus that causes disease that is both a cancer model and a continuing threat to the world's poultry industry. This comprehensive gene expression study analyzes the host response to infection in both resistant and susceptible lines of chickens and inherent expression differences between the two lines following the infection of the host. A novel pathogenicity mechanism, involving the downregulation of genes containing HIC1 transcription factor binding sites as early as 4 days postinfection, was suggested from this analysis. HIC1 drives antitumor mechanisms, suggesting that MDV infection switches off genes involved in antitumor regulation several days before the expression of the MDV oncogene meq. The comparison of the gene expression data to previous QTL data identified several genes as candidates for involvement in resistance to MD. One of these genes, IRG1, was confirmed by single nucleotide polymorphism analysis to be involved in susceptibility. Its precise mechanism remains to be elucidated, although the analysis of gene expression data suggests it has a role in apoptosis. Understanding which genes are involved in susceptibility/resistance to MD and defining the pathological mechanisms of the disease gives us a much greater ability to try to reduce the incidence of this virus, which is costly to the poultry industry in terms of both animal welfare and economics. PMID:21865384

  6. Susceptibility to thyroid autoimmune disease: molecular analysis of HLA-D region genes identifies new markers for goitrous Hashimoto's thyroiditis.

    PubMed

    Badenhoop, K; Schwarz, G; Walfish, P G; Drummond, V; Usadel, K H; Bottazzo, G F

    1990-11-01

    Hashimoto's thyroiditis has been shown to be associated with the HLA-specificities DR4 and DR5. Since former association studies yielded variable results, we used novel molecular typing methods to assess predisposing immunogenetic factors. Gene analysis of the HLA-DR-DQ and tumor necrosis factor region was performed in a group of Hashimoto's thyroiditis patients and randomly chosen controls using standards and nomenclature of the 10th International Histocompatibility Workshop. Genomic DNA of patients and controls was analyzed using a cDNA probe of the DQB1 gene. The resulting restriction fragment patterns allowed the determination of newly defined DQw-types 1-9. We find the strongest relative risk conferred by DQw7 (RR = 4.7), that is observed in 36 of 64 patients (56%) and only 21 of 98 controls (21%) (P corr less than 0.002). Comparison of DNA sequence variation in the DQB1 gene, that is found predominantly in Hashimoto's thyroiditis patients, indicates that codons 45 and 57 are critical features in DQw7 which distinguish it from other DQw specificities. The adjacent DQA1 genes also display a significant association with Hashimoto's thyroiditis (DQA1*0201/*0301 heterozygotes were found in 37% of patients and 15% controls, P less than 0.03). No significant association could be found with polymorphisms of the tumor necrosis factor gene. These results provide a new basis for the concept of genetic susceptibility in Hashimoto's thyroiditis and will help to elucidate the underlying autoimmune mechanisms that lead to disease at the functional level. PMID:1977755

  7. A bivariate genome-wide association study identifies ADAM12 as a novel susceptibility gene for Kashin-Beck disease

    PubMed Central

    Hao, Jingcan; Wang, Wenyu; Wen, Yan; Xiao, Xiao; He, Awen; Guo, Xiong; Yang, Tielin; Liu, Xiaogang; Shen, Hui; Chen, Xiangding; Tian, Qing; Deng, Hong-Wen; Zhang, Feng

    2016-01-01

    Kashin-Beck disease (KBD) is a chronic osteoarthropathy, which manifests as joint deformities and growth retardation. Only a few genetic studies of growth retardation associated with the KBD have been carried out by now. In this study, we conducted a two-stage bivariate genome-wide association study (BGWAS) of the KBD using joint deformities and body height as study phenotypes, totally involving 2,417 study subjects. Articular cartilage specimens from 8 subjects were collected for immunohistochemistry. In the BGWAS, ADAM12 gene achieved the most significant association (rs1278300 p-value = 9.25 × 10−9) with the KBD. Replication study observed significant association signal at rs1278300 (p-value = 0.007) and rs1710287 (p-value = 0.002) of ADAM12 after Bonferroni correction. Immunohistochemistry revealed significantly decreased expression level of ADAM12 protein in the KBD articular cartilage (average positive chondrocyte rate = 47.59 ± 7.79%) compared to healthy articular cartilage (average positive chondrocyte rate = 64.73 ± 5.05%). Our results suggest that ADAM12 gene is a novel susceptibility gene underlying both joint destruction and growth retardation of the KBD. PMID:27545300

  8. A diVIsive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary Disease

    PubMed Central

    2014-01-01

    Background An important step toward understanding the biological mechanisms underlying a complex disease is a refined understanding of its clinical heterogeneity. Relating clinical and molecular differences may allow us to define more specific subtypes of patients that respond differently to therapeutic interventions. Results We developed a novel unbiased method called diVIsive Shuffling Approach (VIStA) that identifies subgroups of patients by maximizing the difference in their gene expression patterns. We tested our algorithm on 140 subjects with Chronic Obstructive Pulmonary Disease (COPD) and found four distinct, biologically and clinically meaningful combinations of clinical characteristics that are associated with large gene expression differences. The dominant characteristic in these combinations was the severity of airflow limitation. Other frequently identified measures included emphysema, fibrinogen levels, phlegm, BMI and age. A pathway analysis of the differentially expressed genes in the identified subtypes suggests that VIStA is capable of capturing specific molecular signatures within in each group. Conclusions The introduced methodology allowed us to identify combinations of clinical characteristics that correspond to clear gene expression differences. The resulting subtypes for COPD contribute to a better understanding of its heterogeneity. PMID:25032995

  9. CSGene: a literature-based database for cell senescence genes and its application to identify critical cell aging pathways and associated diseases

    PubMed Central

    Zhao, M; Chen, L; Qu, H

    2016-01-01

    Cell senescence is a cellular process in which normal diploid cells cease to replicate and is a major driving force for human cancers and aging-associated diseases. Recent studies on cell senescence have identified many new genetic components and pathways that control cell aging. However, there is no comprehensive resource for cell senescence that integrates various genetic studies and relationships with cell senescence, and the risk associated with complex diseases such as cancer is still unexplored. We have developed the first literature-based gene resource for exploring cell senescence genes, CSGene. We complied 504 experimentally verified genes from public data resources and published literature. Pathway analyses highlighted the prominent roles of cell senescence genes in the control of rRNA gene transcription and unusual rDNA repeat that constitute a center for the stability of the whole genome. We also found a strong association of cell senescence with HIV-1 infection and viral carcinogenesis that are mainly related to promoter/enhancer binding and chromatin modification processes. Moreover, pan-cancer mutation and network analysis also identified common cell aging mechanisms in cancers and uncovered a highly modular network structure. These results highlight the utility of CSGene for elucidating the complex cellular events of cell senescence. PMID:26775705

  10. New mutation of the desmin gene identified in an extended Indian pedigree presenting with distal myopathy and cardiac disease.

    PubMed

    Nalini, Atchayaram; Gayathri, Narayanappa; Richard, Pascale; Cobo, Ana-Maria; Urtizberea, J Andoni

    2013-01-01

    In this report, we describe a new mutation located in the coiled 1B domain of desmin and associated with a predominant cardiac involvement and a high degree of cardiac sudden death in a large Indian pedigree with 12 affected members. The index cases was 38-year-old man who presented with progressive difficulty in gripping footwear of 5 years duration with the onset in the left lower limb followed by right lower limb in 6 months. 3 years from onset, he developed lower limb proximal and truncal muscle weakness. There was mild atrophy of the shoulder girdle muscles with grade 3 weakness, moderate wasting of thigh and anterior leg muscles with proximal muscle weakness and foot drop. At 40 years, he had a pacemaker implanted. The 9 exons and intronic boundaries of the desmin gene were sequenced and a heterozygous nucleotide change c. 734A > G in exon 3 was identified. PMID:24441330

  11. Twelve novel HGD gene variants identified in 99 alkaptonuria patients: focus on 'black bone disease' in Italy.

    PubMed

    Nemethova, Martina; Radvanszky, Jan; Kadasi, Ludevit; Ascher, David B; Pires, Douglas E V; Blundell, Tom L; Porfirio, Berardino; Mannoni, Alessandro; Santucci, Annalisa; Milucci, Lia; Sestini, Silvia; Biolcati, Gianfranco; Sorge, Fiammetta; Aurizi, Caterina; Aquaron, Robert; Alsbou, Mohammed; Lourenço, Charles Marques; Ramadevi, Kanakasabapathi; Ranganath, Lakshminarayan R; Gallagher, James A; van Kan, Christa; Hall, Anthony K; Olsson, Birgitta; Sireau, Nicolas; Ayoob, Hana; Timmis, Oliver G; Sang, Kim-Hanh Le Quan; Genovese, Federica; Imrich, Richard; Rovensky, Jozef; Srinivasaraghavan, Rangan; Bharadwaj, Shruthi K; Spiegel, Ronen; Zatkova, Andrea

    2016-01-01

    Alkaptonuria (AKU) is an autosomal recessive disorder caused by mutations in homogentisate-1,2-dioxygenase (HGD) gene leading to the deficiency of HGD enzyme activity. The DevelopAKUre project is underway to test nitisinone as a specific treatment to counteract this derangement of the phenylalanine-tyrosine catabolic pathway. We analysed DNA of 40 AKU patients enrolled for SONIA1, the first study in DevelopAKUre, and of 59 other AKU patients sent to our laboratory for molecular diagnostics. We identified 12 novel DNA variants: one was identified in patients from Brazil (c.557T>A), Slovakia (c.500C>T) and France (c.440T>C), three in patients from India (c.469+6T>C, c.650-85A>G, c.158G>A), and six in patients from Italy (c.742A>G, c.614G>A, c.1057A>C, c.752G>A, c.119A>C, c.926G>T). Thus, the total number of potential AKU-causing variants found in 380 patients reported in the HGD mutation database is now 129. Using mCSM and DUET, computational approaches based on the protein 3D structure, the novel missense variants are predicted to affect the activity of the enzyme by three mechanisms: decrease of stability of individual protomers, disruption of protomer-protomer interactions or modification of residues in the region of the active site. We also present an overview of AKU in Italy, where so far about 60 AKU cases are known and DNA analysis has been reported for 34 of them. In this rather small group, 26 different HGD variants affecting function were described, indicating rather high heterogeneity. Twelve of these variants seem to be specific for Italy. PMID:25804398

  12. Network Topology Analysis of Post-Mortem Brain Microarrays Identifies More Alzheimer's Related Genes and MicroRNAs and Points to Novel Routes for Fighting with the Disease.

    PubMed

    Chandrasekaran, Sreedevi; Bonchev, Danail

    2016-01-01

    Network-based approaches are powerful and beneficial tools to study complex systems in their entirety, elucidating the essential factors that turn the multitude of individual elements into a functional system. In this study we used critical network topology descriptors and guilt-by-association rule to explore and understand the significant molecular players, drug targets and underlying biological mechanisms of Alzheimer's disease. Analyzing two post-mortem brain gene microarrays (GSE4757 and GSE28146) with Pathway Studio software package we constructed and analyzed a set of protein-protein interaction, as well as miRNA-target networks. In a 4-step procedure the expression datasets were normalized using Robust Multi-array Average approach, while the modulation of gene expression by the disease was statistically evaluated by the empirical Bayes method from the limma Bioconductor package. Representative set of 214 seed-genes (p<0.01) common for the three brain sections of the two microarrays was thus created. The Pathway Studio analysis of the networks built identified 15 new potential AD-related genes and 17 novel AD-involved microRNAs. Using KEGG pathways relevant in Alzheimer's disease we built an integrated mechanistic network from the interactions between the overlapping genes in these pathways. Routes of possible disease initiation process were thus revealed through the CD4, DCN, and IL8 extracellular ligands. DAVID and IPA enrichment analysis uncovered a number of deregulated biological processes and pathways including neuron projection/differentiation, aging, oxidative stress, chemokine/ neurotrophin signaling, long-term potentiation and others. The findings in this study offer information of interest for subsequent experimental studies. PMID:26784894

  13. Genome-wide haplotype association study identifies the FRMD4A gene as a risk locus for Alzheimer's disease

    PubMed Central

    Lambert, J-C; Grenier-Boley, B; Harold, D; Zelenika, D; Chouraki, V; Kamatani, Y; Sleegers, K; Ikram, M A; Hiltunen, M; Reitz, C; Mateo, I; Feulner, T; Bullido, M; Galimberti, D; Concari, L; Alvarez, V; Sims, R; Gerrish, A; Chapman, J; Deniz-Naranjo, C; Solfrizzi, V; Sorbi, S; Arosio, B; Spalletta, G; Siciliano, G; Epelbaum, J; Hannequin, D; Dartigues, J-F; Tzourio, C; Berr, C; Schrijvers, E M C; Rogers, R; Tosto, G; Pasquier, F; Bettens, K; Van Cauwenberghe, C; Fratiglioni, L; Graff, C; Delepine, M; Ferri, R; Reynolds, C A; Lannfelt, L; Ingelsson, M; Prince, J A; Chillotti, C; Pilotto, A; Seripa, D; Boland, A; Mancuso, M; Bossù, P; Annoni, G; Nacmias, B; Bosco, P; Panza, F; Sanchez-Garcia, F; Del Zompo, M; Coto, E; Owen, M; O'Donovan, M; Valdivieso, F; Caffara, P; Scarpini, E; Combarros, O; Buée, L; Campion, D; Soininen, H; Breteler, M; Riemenschneider, M; Van Broeckhoven, C; Alpérovitch, A; Lathrop, M; Trégouët, D-A; Williams, J; Amouyel, P

    2013-01-01

    Recently, several genome-wide association studies (GWASs) have led to the discovery of nine new loci of genetic susceptibility in Alzheimer's disease (AD). However, the landscape of the AD genetic susceptibility is far away to be complete and in addition to single-SNP (single-nucleotide polymorphism) analyses as performed in conventional GWAS, complementary strategies need to be applied to overcome limitations inherent to this type of approaches. We performed a genome-wide haplotype association (GWHA) study in the EADI1 study (n=2025 AD cases and 5328 controls) by applying a sliding-windows approach. After exclusion of loci already known to be involved in AD (APOE, BIN1 and CR1), 91 regions with suggestive haplotype effects were identified. In a second step, we attempted to replicate the best suggestive haplotype associations in the GERAD1 consortium (2820 AD cases and 6356 controls) and observed that 9 of them showed nominal association. In a third step, we tested relevant haplotype associations in a combined analysis of five additional case–control studies (5093 AD cases and 4061 controls). We consistently replicated the association of a haplotype within FRMD4A on Chr.10p13 in all the data set analyzed (OR: 1.68; 95% CI: (1.43–1.96); P=1.1 × 10−10). We finally searched for association between SNPs within the FRMD4A locus and Aβ plasma concentrations in three independent non-demented populations (n=2579). We reported that polymorphisms were associated with plasma Aβ42/Aβ40 ratio (best signal, P=5.4 × 10−7). In conclusion, combining both GWHA study and a conservative three-stage replication approach, we characterised FRMD4A as a new genetic risk factor of AD. PMID:22430674

  14. Follow-up of loci from the International Genomics of Alzheimer's Disease Project identifies TRIP4 as a novel susceptibility gene

    PubMed Central

    Ruiz, A; Heilmann, S; Becker, T; Hernández, I; Wagner, H; Thelen, M; Mauleón, A; Rosende-Roca, M; Bellenguez, C; Bis, J C; Harold, D; Gerrish, A; Sims, R; Sotolongo-Grau, O; Espinosa, A; Alegret, M; Arrieta, J L; Lacour, A; Leber, M; Becker, J; Lafuente, A; Ruiz, S; Vargas, L; Rodríguez, O; Ortega, G; Dominguez, M-A; Mayeux, R; Haines, J L; Pericak-Vance, M A; Farrer, L A; Schellenberg, G D; Chouraki, V; Launer, L J; van Duijn, C; Seshadri, S; Antúnez, C; Breteler, M M; Serrano-Ríos, M; Jessen, F; Tárraga, L; Nöthen, M M; Maier, W; Boada, M; Ramírez, A

    2014-01-01

    To follow-up loci discovered by the International Genomics of Alzheimer's Disease Project, we attempted independent replication of 19 single nucleotide polymorphisms (SNPs) in a large Spanish sample (Fundació ACE data set; 1808 patients and 2564 controls). Our results corroborate association with four SNPs located in the genes INPP5D, MEF2C, ZCWPW1 and FERMT2, respectively. Of these, ZCWPW1 was the only SNP to withstand correction for multiple testing (P=0.000655). Furthermore, we identify TRIP4 (rs74615166) as a novel genome-wide significant locus for Alzheimer's disease risk (odds ratio=1.31; confidence interval 95% (1.19–1.44); P=9.74 × 10−9). PMID:24495969

  15. New Test Helps Identify Rare Genetic Diseases in Newborns

    MedlinePlus

    ... fullstory_159097.html New Test Helps Identify Rare Genetic Diseases in Newborns 'Next-generation gene sequencing' could ... greatly improve doctors' ability to quickly diagnose rare genetic diseases in newborns, researchers say. The new test ...

  16. NIH Researchers Identify OCD Risk Gene

    MedlinePlus

    ... News From NIH NIH Researchers Identify OCD Risk Gene Past Issues / Summer 2006 Table of Contents For ... and Alcoholism (NIAAA) have identified a previously unknown gene variant that doubles an individual's risk for obsessive- ...

  17. Genome-Wide Analysis of Copy Number Variation Identifies Candidate Gene Loci Associated with the Progression of Non-Alcoholic Fatty Liver Disease

    PubMed Central

    Zain, Shamsul Mohd; Mohamed, Rosmawati; Cooper, David N.; Razali, Rozaimi; Rampal, Sanjay; Mahadeva, Sanjiv; Chan, Wah-Kheong; Anwar, Arif; Rosli, Nurul Shielawati Mohamed; Mahfudz, Anis Shafina; Cheah, Phaik-Leng; Basu, Roma Choudhury; Mohamed, Zahurin

    2014-01-01

    Between 10 and 25% of individuals with non-alcoholic fatty liver disease (NAFLD) develop hepatic fibrosis leading to cirrhosis and hepatocellular carcinoma (HCC). To investigate the molecular basis of disease progression, we performed a genome-wide analysis of copy number variation (CNV) in a total of 49 patients with NAFLD [10 simple steatosis and 39 non-alcoholic steatohepatitis (NASH)] and 49 matched controls using high-density comparative genomic hybridization (CGH) microarrays. A total of 11 CNVs were found to be unique to individuals with simple steatosis, whilst 22 were common between simple steatosis and NASH, and 224 were unique to NASH. We postulated that these CNVs could be involved in the pathogenesis of NAFLD progression. After stringent filtering, we identified four rare and/or novel CNVs that may influence the pathogenesis of NASH. Two of these CNVs, located at 13q12.11 and 12q13.2 respectively, harbour the exportin 4 (XPO4) and phosphodiesterase 1B (PDE1B) genes which are already known to be involved in the etiology of liver cirrhosis and HCC. Cross-comparison of the genes located at these four CNV loci with genes already known to be associated with NAFLD yielded a set of genes associated with shared biological processes including cell death, the key process involved in ‘second hit’ hepatic injury. To our knowledge, this pilot study is the first to provide CNV information of potential relevance to the NAFLD spectrum. These data could prove invaluable in predicting patients at risk of developing NAFLD and more importantly, those who will subsequently progress to NASH. PMID:24743702

  18. Caenorhabditis elegans expressing the Saccharomyces cerevisiae NADH alternative dehydrogenase Ndi1p, as a tool to identify new genes involved in complex I related diseases

    PubMed Central

    Cossard, Raynald; Esposito, Michela; Sellem, Carole H.; Pitayu, Laras; Vasnier, Christelle; Delahodde, Agnès; Dassa, Emmanuel P.

    2015-01-01

    Isolated complex I deficiencies are one of the most commonly observed biochemical features in patients suffering from mitochondrial disorders. In the majority of these clinical cases the molecular bases of the diseases remain unknown suggesting the involvement of unidentified factors that are critical for complex I function. The Saccharomyces cerevisiae NDI1 gene, encoding the mitochondrial internal NADH dehydrogenase was previously shown to complement a complex I deficient strain in Caenorhabditis elegans with notable improvements in reproduction and whole organism respiration. These features indicate that Ndi1p can functionally integrate the respiratory chain, allowing complex I deficiency complementation. Taking into account the Ndi1p ability to bypass complex I, we evaluate the possibility to extend the range of defects/mutations causing complex I deficiencies that can be alleviated by NDI1 expression. We report here that NDI1 expressing animals unexpectedly exhibit a slightly shortened lifespan, a reduction in the progeny, and a depletion of the mitochondrial genome. However, Ndi1p is expressed and targeted to the mitochondria as a functional protein that confers rotenone resistance to those animals without affecting their respiration rate and ATP content. We show that the severe embryonic lethality level caused by the RNAi knockdowns of complex I structural subunit encoding genes (e.g., NDUFV1, NDUFS1, NDUFS6, NDUFS8, or GRIM-19 human orthologs) in wild type animals is significantly reduced in the Ndi1p expressing worm. All together these results open up the perspective to identify new genes involved in complex I function, assembly, or regulation by screening an RNAi library of genes leading to embryonic lethality that should be rescued by NDI1 expression. PMID:26124772

  19. New Test Helps Identify Rare Genetic Diseases in Newborns

    MedlinePlus

    ... nlm.nih.gov/medlineplus/news/fullstory_159097.html New Test Helps Identify Rare Genetic Diseases in Newborns ' ... 31, 2016 MONDAY, May 30, 2016 (HealthDay News) -- New gene screening methods may greatly improve doctors' ability ...

  20. Identifying potential cancer driver genes by genomic data integration

    NASA Astrophysics Data System (ADS)

    Chen, Yong; Hao, Jingjing; Jiang, Wei; He, Tong; Zhang, Xuegong; Jiang, Tao; Jiang, Rui

    2013-12-01

    Cancer is a genomic disease associated with a plethora of gene mutations resulting in a loss of control over vital cellular functions. Among these mutated genes, driver genes are defined as being causally linked to oncogenesis, while passenger genes are thought to be irrelevant for cancer development. With increasing numbers of large-scale genomic datasets available, integrating these genomic data to identify driver genes from aberration regions of cancer genomes becomes an important goal of cancer genome analysis and investigations into mechanisms responsible for cancer development. A computational method, MAXDRIVER, is proposed here to identify potential driver genes on the basis of copy number aberration (CNA) regions of cancer genomes, by integrating publicly available human genomic data. MAXDRIVER employs several optimization strategies to construct a heterogeneous network, by means of combining a fused gene functional similarity network, gene-disease associations and a disease phenotypic similarity network. MAXDRIVER was validated to effectively recall known associations among genes and cancers. Previously identified as well as novel driver genes were detected by scanning CNAs of breast cancer, melanoma and liver carcinoma. Three predicted driver genes (CDKN2A, AKT1, RNF139) were found common in these three cancers by comparative analysis.

  1. NIH Researchers Identify OCD Risk Gene

    MedlinePlus

    ... Home Current Issue Past Issues Research News From NIH NIH Researchers Identify OCD Risk Gene Past Issues / Summer ... page please turn Javascript on. Scientists at the NIH's National Institute on Alcohol Abuse and Alcoholism (NIAAA) ...

  2. From SNPs to Genes: Disease Association at the Gene Level

    PubMed Central

    Lehne, Benjamin; Lewis, Cathryn M.; Schlitt, Thomas

    2011-01-01

    Interpreting Genome-Wide Association Studies (GWAS) at a gene level is an important step towards understanding the molecular processes that lead to disease. In order to incorporate prior biological knowledge such as pathways and protein interactions in the analysis of GWAS data it is necessary to derive one measure of association for each gene. We compare three different methods to obtain gene-wide test statistics from Single Nucleotide Polymorphism (SNP) based association data: choosing the test statistic from the most significant SNP; the mean test statistics of all SNPs; and the mean of the top quartile of all test statistics. We demonstrate that the gene-wide test statistics can be controlled for the number of SNPs within each gene and show that all three methods perform considerably better than expected by chance at identifying genes with confirmed associations. By applying each method to GWAS data for Crohn's Disease and Type 1 Diabetes we identified new potential disease genes. PMID:21738570

  3. Meta-Analysis of Genome-Wide Association Studies and Network Analysis-Based Integration with Gene Expression Data Identify New Suggestive Loci and Unravel a Wnt-Centric Network Associated with Dupuytren’s Disease

    PubMed Central

    Becker, Kerstin; Siegert, Sabine; Toliat, Mohammad Reza; Du, Juanjiangmeng; Casper, Ramona; Dolmans, Guido H.; Werker, Paul M.; Tinschert, Sigrid; Franke, Andre; Gieger, Christian; Strauch, Konstantin; Nothnagel, Michael; Nürnberg, Peter; Hennies, Hans Christian

    2016-01-01

    Dupuytren´s disease, a fibromatosis of the connective tissue in the palm, is a common complex disease with a strong genetic component. Up to date nine genetic loci have been found to be associated with the disease. Six of these loci contain genes that code for Wnt signalling proteins. In spite of this striking first insight into the genetic factors in Dupuytren´s disease, much of the inherited risk in Dupuytren´s disease still needs to be discovered. The already identified loci jointly explain ~1% of the heritability in this disease. To further elucidate the genetic basis of Dupuytren´s disease, we performed a genome-wide meta-analysis combining three genome-wide association study (GWAS) data sets, comprising 1,580 cases and 4,480 controls. We corroborated all nine previously identified loci, six of these with genome-wide significance (p-value < 5x10-8). In addition, we identified 14 new suggestive loci (p-value < 10−5). Intriguingly, several of these new loci contain genes associated with Wnt signalling and therefore represent excellent candidates for replication. Next, we compared whole-transcriptome data between patient- and control-derived tissue samples and found the Wnt/β-catenin pathway to be the top deregulated pathway in patient samples. We then conducted network and pathway analyses in order to identify protein networks that are enriched for genes highlighted in the GWAS meta-analysis and expression data sets. We found further evidence that the Wnt signalling pathways in conjunction with other pathways may play a critical role in Dupuytren´s disease. PMID:27467239

  4. A survey of FLS2 genes from multiple citrus species identifies candidates for enhancing disease resistance to Xanthomonas citri ssp. citri.

    PubMed

    Shi, Qingchun; Febres, Vicente J; Jones, Jeffrey B; Moore, Gloria A

    2016-01-01

    Pathogen-associated molecular patterns (PAMPs)-triggered immunity (PTI) is an important component of plant innate immunity. In a previous study, we showed that the PAMP flg22 from Xanthomonas citri ssp. citri (Xflg22), the causal agent of citrus canker, induced PTI in citrus, which correlated with the observed levels of canker resistance. Here, we identified and sequenced two bacterial flagellin/flg22 receptors (FLS2-1 and FLS2-2) from 'Duncan' grapefruit (Citrus paradisi, CpFLS2-1 and CpFLS2-2) and 'Sun Chu Sha' mandarin (C. reticulata, CrFLS2-1 and CrFLS2-2). We were able to isolate only one FLS2 from 'Nagami' kumquat (Fortunella margarita, FmFLS2-1) and gene flanking sequences suggest a rearrangement event that resulted in the deletion of FLS2-2 from the genome. Phylogenetic analysis, gene structure and presence of critical amino acid domains all indicate we identified the true FLS2 genes in citrus. FLS2-2 was more transcriptionally responsive to Xflg22 than FLS2-1, with induced expression levels higher in canker-resistant citrus than in susceptible ones. Interestingly, 'Nagami' kumquat showed the highest FLS2-1 steady-state expression levels, although it was not induced by Xflg22. We selected FmFLS2-1, CrFLS2-2 and CpFLS2-2 to further evaluate their capacity to enhance bacterial resistance using Agrobacterium-mediated transient expression assays. Both FmFLS2-1 and CrFLS2-2, the two proteins from canker-resistant species, conferred stronger Xflg22 responses and reduced canker symptoms in leaves of the susceptible grapefruit genotype. These two citrus genes will be useful resources to enhance PTI and achieve resistance against canker and possibly other bacterial pathogens in susceptible citrus types. PMID:27222722

  5. Gene mutations in Cushing's disease

    PubMed Central

    Xiong, Qi; Ge, Wei

    2016-01-01

    Cushing's disease (CD) is a severe (and potentially fatal) disease caused by adrenocorticotropic hormone (ACTH)-secreting adenomas of the pituitary gland (often termed pituitary adenomas). The majority of ACTH-secreting corticotroph tumors are sporadic and CD rarely appears as a familial disorder, thus, the genetic mechanisms underlying CD are poorly understood. Studies have reported that various mutated genes are associated with CD, such as those in menin 1, aryl hydrocarbon receptor-interacting protein and the nuclear receptor subfamily 3 group C member 1. Recently it was identified that ubiquitin-specific protease 8 mutations contribute to CD, which was significant towards elucidating the genetic mechanisms of CD. The present study reviews the associated gene mutations in CD patients. PMID:27588171

  6. Chapter 15: Disease Gene Prioritization

    PubMed Central

    Bromberg, Yana

    2013-01-01

    Disease-causing aberrations in the normal function of a gene define that gene as a disease gene. Proving a causal link between a gene and a disease experimentally is expensive and time-consuming. Comprehensive prioritization of candidate genes prior to experimental testing drastically reduces the associated costs. Computational gene prioritization is based on various pieces of correlative evidence that associate each gene with the given disease and suggest possible causal links. A fair amount of this evidence comes from high-throughput experimentation. Thus, well-developed methods are necessary to reliably deal with the quantity of information at hand. Existing gene prioritization techniques already significantly improve the outcomes of targeted experimental studies. Faster and more reliable techniques that account for novel data types are necessary for the development of new diagnostics, treatments, and cure for many diseases. PMID:23633938

  7. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease, and shows evidence for additional susceptibility genes

    PubMed Central

    Harold, Denise; Abraham, Richard; Hollingworth, Paul; Sims, Rebecca; Gerrish, Amy; Hamshere, Marian; Singh Pahwa, Jaspreet; Moskvina, Valentina; Dowzell, Kimberley; Williams, Amy; Jones, Nicola; Thomas, Charlene; Stretton, Alexandra; Morgan, Angharad; Lovestone, Simon; Powell, John; Proitsi, Petroula; Lupton, Michelle K; Brayne, Carol; Rubinsztein, David C.; Gill, Michael; Lawlor, Brian; Lynch, Aoibhinn; Morgan, Kevin; Brown, Kristelle; Passmore, Peter; Craig, David; McGuinness, Bernadette; Todd, Stephen; Holmes, Clive; Mann, David; Smith, A. David; Love, Seth; Kehoe, Patrick G.; Hardy, John; Mead, Simon; Fox, Nick; Rossor, Martin; Collinge, John; Maier, Wolfgang; Jessen, Frank; Schürmann, Britta; van den Bussche, Hendrik; Heuser, Isabella; Kornhuber, Johannes; Wiltfang, Jens; Dichgans, Martin; Frölich, Lutz; Hampel, Harald; Hüll, Michael; Rujescu, Dan; Goate, Alison; Kauwe, John S.K.; Cruchaga, Carlos; Nowotny, Petra; Morris, John C.; Mayo, Kevin; Sleegers, Kristel; Bettens, Karolien; Engelborghs, Sebastiaan; De Deyn, Peter; van Broeckhoven, Christine; Livingston, Gill; Bass, Nicholas J.; Gurling, Hugh; McQuillin, Andrew; Gwilliam, Rhian; Deloukas, Panagiotis; Al-Chalabi, Ammar; Shaw, Christopher E.; Tsolaki, Magda; Singleton, Andrew; Guerreiro, Rita; Mühleisen, Thomas W.; Nöthen, Markus M.; Moebus, Susanne; Jöckel, Karl-Heinz; Klopp, Norman; Wichmann, H-Erich; Carrasquillo, Minerva M.; Pankratz, V. Shane; Younkin, Steven G.; Holmans, Peter; O'Donovan, Michael; Owen, Michael J.; Williams, Julie

    2010-01-01

    We undertook a two-stage genome-wide association study of Alzheimer's disease involving over 16,000 individuals. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the APOE locus (most significant SNP: rs2075650, p= 1.8×10−157) and observed genome-wide significant association with SNPs at two novel loci: rs11136000 in the CLU or APOJ gene (p= 1.4×10−9) and rs3851179, a SNP 5′ to the PICALM gene (p= 1.9×10−8). Both novel associations were supported in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with AD in the combined dataset (rs11136000: p= 8.5×10−10, odds ratio= 0.86; rs3851179: p= 1.3×10−9, odds ratio= 0.86). We also observed more variants associated at p< 1×10−5 than expected by chance (p=7.5×10−6), including polymorphisms at the BIN1, DAB1 and CR1 loci. PMID:19734902

  8. Pyrosequencing-based profiling of archaeal and bacterial 16S rRNA genes identifies a novel archaeon associated with black band disease in corals.

    PubMed

    Sato, Yui; Willis, Bette L; Bourne, David G

    2013-11-01

    Black band disease (BBD) is a microbial consortium that creates anoxic, sulfide-rich microenvironments and kills underlying coral tissues as it rapidly migrates across colonies. Although bacterial communities associated with BBD have been studied extensively, the presence and roles of archaea are unexplored. Using amplicon-pyrosequencing of 16S ribosomal RNA genes, we investigated the community structure of both archaea and bacteria within microbial lesions of BBD and the less-virulent precursor stage, 'cyanobacterial patches' (CP), affecting the coral Montipora hispida. We detected characteristic shifts in microbial communities during the development of BBD from CP, reflecting microenvironmental changes within lesions. Archaeal profiles in CP suggested a diverse assemblage affiliated with the Thaumarchaeota and Euryarchaeota, similar to communities described for oxic marine environments. In contrast, a novel ribotype, distantly affiliated to the Euryarchaeota, dominated up to 94% of archaeal sequences retrieved from BBD. The physiological characteristics of this dominant archaeal ribotype are unknown because of the novelty of its 16S ribosomal RNA gene sequences; however, their prominent associations with BBD lesions suggest the ability to thrive in the organic- and sulfide-rich anoxic microenvironment characteristic of BBD lesions. Discovery of this novel archaeal ribotype provides new insights into the microbial ecology and aetiology of BBD. PMID:24112537

  9. Detection of disseminated tumor cells in the bone marrow of breast cancer patients using multiplex gene expression measurements identifies new therapeutic targets in patients at high risk for the development of metastatic disease

    PubMed Central

    Siddappa, Chidananda M.; Watson, Mark A.; Pillai, Sreeraj; Trinkaus, Kathryn; Fleming, Timothy; Aft, Rebecca

    2016-01-01

    Purpose Disseminated tumor cells (DTCs) detected in the bone marrow of breast cancer patients identifies women at high risk of recurrence. DTCs are traditionally detected by immunocytochemical staining for cytokeratins or single gene expression measurements, which limit both specificity and sensitivity. We evaluated the Nanostring nCounter™ (NC) platform for multi-marker, gene expression-based detection and classification of DTCs in the bone marrow of breast cancer patients. Experimental Design Candidate genes exhibiting tumor cell specific expression were identified from microarray data sets and validated by qRT-PCR analysis in non-malignant human BM and identical samples spiked with predefined numbers of molecularly diverse breast tumor cell lines. Thirty-eight validated transcripts were designed for the nCounter™ platform and a subset of these transcripts was technically validated against qRT-PCR measurements using identical spiked bone marrow controls. Bilateral iliac crest bone marrow aspirates were collected and analyzed from twenty breast cancer patients, prior to neoadjuvant therapy, using the full 38 gene nCounter™ code set. Results Tumor cell specific gene expression by nCounter™ was detected with a sensitivity of one cancer cell per 1×106 nucleated bone marrow cells after optimization. Measurements were quantitative, log linear over a twenty-fold range, and correlated with qRT-PCR measurements. Using the nCounter™ 38-gene panel, 6 of 8 patients (75%) who developed metastatic disease had detectable expression of at least one transcript. Notably, three of these patients had detectable expression of ERBB2 in their bone marrow, despite the fact that their corresponding primary tumors were HER2/ERBB2 negative and therefore did not receive trastuzumab therapy. Four of these patients also expressed the PTCH1 receptor, a newly recognized therapeutic target based on hedgehog signaling pathway inhibition. Conclusions The presumptive detection and

  10. A survey of FLS2 genes from multiple citrus species identifies candidates for enhancing disease resistance to Xanthomonas citri ssp. citri.

    PubMed Central

    Shi, Qingchun; Febres, Vicente J; Jones, Jeffrey B; Moore, Gloria A

    2016-01-01

    Pathogen-associated molecular patterns (PAMPs)-triggered immunity (PTI) is an important component of plant innate immunity. In a previous study, we showed that the PAMP flg22 from Xanthomonas citri ssp. citri (Xflg22), the causal agent of citrus canker, induced PTI in citrus, which correlated with the observed levels of canker resistance. Here, we identified and sequenced two bacterial flagellin/flg22 receptors (FLS2-1 and FLS2-2) from ‘Duncan’ grapefruit (Citrus paradisi, CpFLS2-1 and CpFLS2-2) and ‘Sun Chu Sha’ mandarin (C. reticulata, CrFLS2-1 and CrFLS2-2). We were able to isolate only one FLS2 from ‘Nagami’ kumquat (Fortunella margarita, FmFLS2-1) and gene flanking sequences suggest a rearrangement event that resulted in the deletion of FLS2-2 from the genome. Phylogenetic analysis, gene structure and presence of critical amino acid domains all indicate we identified the true FLS2 genes in citrus. FLS2-2 was more transcriptionally responsive to Xflg22 than FLS2-1, with induced expression levels higher in canker-resistant citrus than in susceptible ones. Interestingly, ‘Nagami’ kumquat showed the highest FLS2-1 steady-state expression levels, although it was not induced by Xflg22. We selected FmFLS2-1, CrFLS2-2 and CpFLS2-2 to further evaluate their capacity to enhance bacterial resistance using Agrobacterium-mediated transient expression assays. Both FmFLS2-1 and CrFLS2-2, the two proteins from canker-resistant species, conferred stronger Xflg22 responses and reduced canker symptoms in leaves of the susceptible grapefruit genotype. These two citrus genes will be useful resources to enhance PTI and achieve resistance against canker and possibly other bacterial pathogens in susceptible citrus types. PMID:27222722

  11. Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes.

    PubMed

    Edmunds, Richard C; Su, Baofeng; Balhoff, James P; Eames, B Frank; Dahdul, Wasila M; Lapp, Hilmar; Lundberg, John G; Vision, Todd J; Dunham, Rex A; Mabee, Paula M; Westerfield, Monte

    2016-01-01

    Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

  12. Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes

    PubMed Central

    Edmunds, Richard C.; Su, Baofeng; Balhoff, James P.; Eames, B. Frank; Dahdul, Wasila M.; Lapp, Hilmar; Lundberg, John G.; Vision, Todd J.; Dunham, Rex A.; Mabee, Paula M.; Westerfield, Monte

    2016-01-01

    Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

  13. Network motif-based method for identifying coronary artery disease

    PubMed Central

    LI, YIN; CONG, YAN; ZHAO, YUN

    2016-01-01

    The present study aimed to develop a more efficient method for identifying coronary artery disease (CAD) than the conventional method using individual differentially expressed genes (DEGs). GSE42148 gene microarray data were downloaded, preprocessed and screened for DEGs. Additionally, based on transcriptional regulation data obtained from ENCODE database and protein-protein interaction data from the HPRD, the common genes were downloaded and compared with genes annotated from gene microarrays to screen additional common genes in order to construct an integrated regulation network. FANMOD was then used to detect significant three-gene network motifs. Subsequently, GlobalAncova was used to screen differential three-gene network motifs between the CAD group and the normal control data from GSE42148. Genes involved in the differential network motifs were then subjected to functional annotation and pathway enrichment analysis. Finally, clustering analysis of the CAD and control samples was performed based on individual DEGs and the top 20 network motifs identified. In total, 9,008 significant three-node network motifs were detected from the integrated regulation network; these were categorized into 22 interaction modes, each containing a minimum of one transcription factor. Subsequently, 1,132 differential network motifs involving 697 genes were screened between the CAD and control group. The 697 genes were enriched in 154 gene ontology terms, including 119 biological processes, and 14 KEGG pathways. Identifying patients with CAD based on the top 20 network motifs provided increased accuracy compared with the conventional method based on individual DEGs. The results of the present study indicate that the network motif-based method is more efficient and accurate for identifying CAD patients than the conventional method based on individual DEGs. PMID:27347046

  14. Integrative Genomics Identifies Gene Signature Associated with Melanoma Ulceration

    PubMed Central

    Toth, Reka; Vizkeleti, Laura; Herandez-Vargas, Hector; Lazar, Viktoria; Emri, Gabriella; Szatmari, Istvan; Herceg, Zdenko; Adany, Roza; Balazs, Margit

    2013-01-01

    Background Despite the extensive research approaches applied to characterise malignant melanoma, no specific molecular markers are available that are clearly related to the progression of this disease. In this study, our aims were to define a gene expression signature associated with the clinical outcome of melanoma patients and to provide an integrative interpretation of the gene expression -, copy number alterations -, and promoter methylation patterns that contribute to clinically relevant molecular functional alterations. Methods Gene expression profiles were determined using the Affymetrix U133 Plus2.0 array. The NimbleGen Human CGH Whole-Genome Tiling array was used to define CNAs, and the Illumina GoldenGate Methylation platform was applied to characterise the methylation patterns of overlapping genes. Results We identified two subclasses of primary melanoma: one representing patients with better prognoses and the other being characteristic of patients with unfavourable outcomes. We assigned 1,080 genes as being significantly correlated with ulceration, 987 genes were downregulated and significantly enriched in the p53, Nf-kappaB, and WNT/beta-catenin pathways. Through integrated genome analysis, we defined 150 downregulated genes whose expression correlated with copy number losses in ulcerated samples. These genes were significantly enriched on chromosome 6q and 10q, which contained a total of 36 genes. Ten of these genes were downregulated and involved in cell-cell and cell-matrix adhesion or apoptosis. The expression and methylation patterns of additional genes exhibited an inverse correlation, suggesting that transcriptional silencing of these genes is driven by epigenetic events. Conclusion Using an integrative genomic approach, we were able to identify functionally relevant molecular hotspots characterised by copy number losses and promoter hypermethylation in distinct molecular subtypes of melanoma that contribute to specific transcriptomic silencing

  15. Characterizing the Molecular Basis of Attenuation of Marek's Disease Virus via In Vitro Serial Passage Identifies De Novo Mutations in the Helicase-Primase Subunit Gene UL5 and Other Candidates Associated with Reduced Virulence

    PubMed Central

    Hildebrandt, Evin; Dunn, John R.; Perumbakkam, Sudeep; Niikura, Masahiro

    2014-01-01

    culture until attenuated. To understand this process, we identified all the changes in the viral genome that occurred during repeated cell passage. We find that a single mutation in the UL5 gene, which encodes a viral protein necessary for DNA replication, reduces disease incidence by 90% or more. In addition, other candidate genes were identified. This information should lead to the development of more effective and rationally designed MD vaccines leading to improved animal health and welfare and lower costs to consumers. PMID:24648463

  16. Gene therapy for CNS diseases - Krabbe disease.

    PubMed

    Rafi, Mohammad A

    2016-01-01

    This is a brief report of the 19th Annual Meeting of the American Society of Gene and Cell Therapy that took place from May 4th through May 7th, 2016 in Washington, DC, USA. While the meeting provided many symposiums, lectures, and scientific sessions this report mainly focuses on one of the sessions on the "Gene Therapy for central nervous system (CNS) Diseases" and specifically on the "Gene Therapy for the globoid cell leukodystrophy or Krabbe disease. Two presentations focused on this subject utilizing two animal models of this disease: mice and dog models. Different serotypes of adeno-associate viral vectors (AAV) alone or in combination with bone marrow transplantations were used in these research projects. The Meeting of the ASGCT reflected continuous growth in the fields of gene and cell therapy and brighter forecast for efficient treatment options for variety of human diseases. PMID:27525222

  17. Network Topology Analysis of Post-Mortem Brain Microarrays Identifies More Alzheimer’s Related Genes and MicroRNAs and Points to Novel Routes for Fighting with the Disease

    PubMed Central

    Chandrasekaran, Sreedevi; Bonchev, Danail

    2016-01-01

    Network-based approaches are powerful and beneficial tools to study complex systems in their entirety, elucidating the essential factors that turn the multitude of individual elements into a functional system. In this study we used critical network topology descriptors and guilt-by-association rule to explore and understand the significant molecular players, drug targets and underlying biological mechanisms of Alzheimer’s disease. Analyzing two post-mortem brain gene microarrays (GSE4757 and GSE28146) with Pathway Studio software package we constructed and analyzed a set of protein-protein interaction, as well as miRNA-target networks. In a 4-step procedure the expression datasets were normalized using Robust Multi-array Average approach, while the modulation of gene expression by the disease was statistically evaluated by the empirical Bayes method from the limma Bioconductor package. Representative set of 214 seed-genes (p<0.01) common for the three brain sections of the two microarrays was thus created. The Pathway Studio analysis of the networks built identified 15 new potential AD-related genes and 17 novel AD-involved microRNAs. Using KEGG pathways relevant in Alzheimer’s disease we built an integrated mechanistic network from the interactions between the overlapping genes in these pathways. Routes of possible disease initiation process were thus revealed through the CD4, DCN, and IL8 extracellular ligands. DAVID and IPA enrichment analysis uncovered a number of deregulated biological processes and pathways including neuron projection/differentiation, aging, oxidative stress, chemokine/ neurotrophin signaling, long-term potentiation and others. The findings in this study offer information of interest for subsequent experimental studies. PMID:26784894

  18. Robust gene dysregulation in Alzheimer's disease brains.

    PubMed

    Feng, Xuemei; Bai, Zhouxian; Wang, Jiajia; Xie, Bin; Sun, Jiya; Han, Guangchun; Song, Fuhai; Crack, Peter J; Duan, Yong; Lei, Hongxing

    2014-01-01

    The brain transcriptome of Alzheimer's disease (AD) reflects the prevailing disease mechanism at the gene expression level. However, thousands of genes have been reported to be dysregulated in AD brains in existing studies, and the consistency or discrepancy among these studies has not been thoroughly examined. Toward this end, we conducted a comprehensive survey of the brain transcriptome datasets for AD and other neurological diseases. We first demonstrated that the frequency of observed dysregulation in AD was highly correlated with the reproducibility of the dysregulation. Based on this observation, we selected 100 genes with the highest frequency of dysregulation to illustrate the core perturbation in AD brains. The dysregulation of these genes was validated in several independent datasets for AD. We further identified 12 genes with strong correlation of gene expression with disease progression. The relevance of these genes to disease progression was also validated in an independent dataset. Interestingly, we found a transcriptional "cushion" for these 100 genes in the less vulnerable visual cortex region, which may be a critical component of the protection mechanism for less vulnerable brain regions. To facilitate the research in this field, we have provided the expression information of ~8000 relevant genes on a publicly accessible web server AlzBIG (http://alz.big.ac.cn). PMID:24662101

  19. Susceptibility Genes for Multiple Sclerosis Identified in a Gene-Based Genome-Wide Association Study

    PubMed Central

    Lin, Xiang; Deng, Fei-Yan; Lu, Xin

    2015-01-01

    Background and Purpose Multiple sclerosis (MS) is a demyelinating and inflammatory disease of the central nervous system. The aim of this study was to identify more genes associated with MS. Methods Based on the publicly available data of the single-nucleotide polymorphism-based genome-wide association study (GWAS) from the database of Genotypes and Phenotypes, we conducted a powerful gene-based GWAS in an initial sample with 931 family trios, and a replication study sample with 978 cases and 883 controls. For interesting genes, gene expression in MS-related cells between MS cases and controls was examined by using publicly available datasets. Results A total of 58 genes was identified, including 20 "novel" genes significantly associated with MS (p<1.40×10-4). In the replication study, 44 of the 58 identified genes had been genotyped and 35 replicated the association. In the gene-expression study, 21 of the 58 identified genes exhibited differential expressions in MS-related cells. Thus, 15 novel genes were supported by replicated association and/or differential expression. In particular, four of the novel genes, those encoding myelin oligodendrocyte glycoprotein (MOG), coiled-coil alpha-helical rod protein 1 (CCHCR1), human leukocyte antigen complex group 22 (HCG22), and major histocompatibility complex, class II, DM alpha (HLA-DMA), were supported by the evidence of both. Conclusions The results of this study emphasize the high power of gene-based GWAS in detecting the susceptibility genes of MS. The novel genes identified herein may provide new insights into the molecular genetic mechanisms underlying MS. PMID:26320842

  20. Advances in Identifying Beryllium Sensitization and Disease

    PubMed Central

    Middleton, Dan; Kowalski, Peter

    2010-01-01

    Beryllium is a lightweight metal with unique qualities related to stiffness, corrosion resistance, and conductivity. While there are many useful applications, researchers in the 1930s and l940s linked beryllium exposure to a progressive occupational lung disease. Acute beryllium disease is a pulmonary irritant response to high exposure levels, whereas chronic beryllium disease (CBD) typically results from a hypersensitivity response to lower exposure levels. A blood test, the beryllium lymphocyte proliferation test (BeLPT), was an important advance in identifying individuals who are sensitized to beryllium (BeS) and thus at risk for developing CBD. While there is no true “gold standard” for BeS, basic epidemiologic concepts have been used to advance our understanding of the different screening algorithms. PMID:20195436

  1. Identifying rare events in rare diseases.

    PubMed

    Attiyeh, Edward F; Maris, John M

    2015-04-15

    Utilizing genomic signatures from diagnostic tumor samples to forecast clinical behavior and response to therapy has long been a goal, and we are now poised to further refine how we can identify the relatively rare patients with aggressive neuroblastoma masquerading as patients with a more benign form of the disease. Clin Cancer Res; 21(8); 1782-5. ©2014 AACR. See related article by Oberthuer et al., p. 1904. PMID:25424848

  2. Gene therapy for Parkinson's disease.

    PubMed

    Lawlor, Patricia A; During, Matthew J

    2004-03-01

    Parkinson's disease (PD) is a debilitating neurodegenerative disorder arising from loss of dopaminergic neurons in the substantia nigra pars compacta and subsequent depletion of striatal dopamine levels, which results in distressing motor symptoms. The current standard pharmacological treatment for PD is direct replacement of dopamine by treatment with its precursor, levodopa (L-dopa). However, this does not significantly alter disease progression and might contribute to the ongoing pathology. Several features of PD make this disease one of the most promising targets for clinical gene therapy of any neurological disease. The confinement of the major pathology to a compact, localised neuronal population and the anatomy of the basal ganglia circuitry mean that global gene transfer is not required and there are well-defined sites for gene transfer. The multifactorial aetiology of idiopathic PD means that it is unlikely any single gene will cure the disease, and as a result at least three separate gene-transfer strategies are currently being pursued: transfer of genes for enzymes involved in dopamine production; transfer of genes for growth factors involved in dopaminergic cell survival and regeneration; and transfer of genes to reset neuronal circuitry by switching cellular phenotype. The merits of these strategies are discussed here, along with remaining hurdles that might impede transfer of gene therapy technology to the clinic as a treatment for PD. PMID:15000692

  3. Mining biological databases for candidate disease genes

    NASA Astrophysics Data System (ADS)

    Braun, Terry A.; Scheetz, Todd; Webster, Gregg L.; Casavant, Thomas L.

    2001-07-01

    The publicly-funded effort to sequence the complete nucleotide sequence of the human genome, the Human Genome Project (HGP), has currently produced more than 93% of the 3 billion nucleotides of the human genome into a preliminary `draft' format. In addition, several valuable sources of information have been developed as direct and indirect results of the HGP. These include the sequencing of model organisms (rat, mouse, fly, and others), gene discovery projects (ESTs and full-length), and new technologies such as expression analysis and resources (micro-arrays or gene chips). These resources are invaluable for the researchers identifying the functional genes of the genome that transcribe and translate into the transcriptome and proteome, both of which potentially contain orders of magnitude more complexity than the genome itself. Preliminary analyses of this data identified approximately 30,000 - 40,000 human `genes.' However, the bulk of the effort still remains -- to identify the functional and structural elements contained within the transcriptome and proteome, and to associate function in the transcriptome and proteome to genes. A fortuitous consequence of the HGP is the existence of hundreds of databases containing biological information that may contain relevant data pertaining to the identification of disease-causing genes. The task of mining these databases for information on candidate genes is a commercial application of enormous potential. We are developing a system to acquire and mine data from specific databases to aid our efforts to identify disease genes. A high speed cluster of Linux of workstations is used to analyze sequence and perform distributed sequence alignments as part of our data mining and processing. This system has been used to mine GeneMap99 sequences within specific genomic intervals to identify potential candidate disease genes associated with Bardet-Biedle Syndrome (BBS).

  4. Extended haplotype association study in Crohn’s disease identifies a novel, Ashkenazi Jewish-specific missense mutation in the NF-κB pathway gene, HEATR3

    PubMed Central

    Zhang, Wei; Hui, Ken Y.; Gusev, Alexander; Warner, Neil; Evelyn Ng, Sok Meng; Ferguson, John; Choi, Murim; Burberry, Aaron; Abraham, Clara; Mayer, Lloyd; Desnick, Robert J.; Cardinale, Christopher J.; Hakonarson, Hakon; Waterman, Matti; Chowers, Yehuda; Karban, Amir; Brant, Steven R.; Silverberg, Mark S.; Gregersen, Peter K.; Katz, Seymour; Lifton, Richard P.; Zhao, Hongyu; Nuñez, Gabriel; Pe’er, Itsik; Peter, Inga; Cho, Judy H.

    2013-01-01

    The Ashkenazi Jewish population has a several-fold higher prevalence of Crohn’s disease compared to non-Jewish European ancestry populations and has a unique genetic history. Haplotype association is critical to Crohn’s disease etiology in this population, most notably at NOD2, in which three causal, uncommon, and conditionally independent NOD2 variants reside on a shared background haplotype. We present an analysis of extended haplotypes which showed significantly greater association to Crohn’s disease in the Ashkenazi Jewish population compared to a non-Jewish population (145 haplotypes and no haplotypes with P-value < 10−3, respectively). Two haplotype regions, one each on chromosomes 16 and 21, conferred increased disease risk within established Crohn’s disease loci. We performed exome sequencing of 55 Ashkenazi Jewish individuals and follow-up genotyping focused on variants in these two regions. We observed Ashkenazi Jewish-specific nominal association at R755C in TRPM2 on chromosome 21. Within the chromosome 16 region, R642S of HEATR3 and rs9922362 of BRD7 showed genome-wide significance. Expression studies of HEATR3 demonstrated a positive role in NOD2-mediated NF-κB signaling. The BRD7 signal showed conditional dependence with only the downstream rare Crohn’s disease-causal variants in NOD2, but not with the background haplotype; this elaborates NOD2 as a key illustration of synthetic association. PMID:23615072

  5. Gene Therapy for Retinal Diseases

    PubMed Central

    Samiy, Nasrollah

    2014-01-01

    Gene therapy has a growing research potential particularly in the field of ophthalmic and retinal diseases owing to three main characteristics of the eye; accessibility in terms of injections and surgical interventions, its immune-privileged status facilitating the accommodation to the antigenicity of a viral vector, and tight blood-ocular barriers which save other organs from unwanted contamination. Gene therapy has tremendous potential for different ocular diseases. In fact, the perspective of gene therapy in the field of eye research does not confine to exclusive monogenic ophthalmic problems and it has the potential to include gene based pharmacotherapies for non-monogenic problems such as age related macular disease and diabetic retinopathy. The present article has focused on how gene transfer into the eye has been developed and used to treat retinal disorders with no available therapy at present. PMID:25709778

  6. Gene Therapy for Cardiovascular Disease

    PubMed Central

    2003-01-01

    The last decade has seen substantial advances in the development of gene therapy strategies and vector technology for the treatment of a diverse number of diseases, with a view to translating the successes observed in animal models into the clinic. Perhaps the overwhelming drive for the increase in vascular gene transfer studies is the current lack of successful long-term pharmacological treatments for complex cardiovascular diseases. The increase in cardiovascular disease to epidemic proportions has also led many to conclude that drug therapy may have reached a plateau in its efficacy and that gene therapy may represent a realistic solution to a long-term problem. Here, we discuss gene delivery approaches and target diseases. PMID:12721517

  7. Identifying Specific Genes Controlling Complex Traits Through A Genome-Wide Screen For cis-Acting Regulatory Elements - An Example Using Marek's Disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The identification of specific genes underlying phenotypic variation of complex traits remains one of the greatest challenges in biology despite having genome sequences and more powerful tools. Most genome-wide screens lack sufficient resolving power as they typically depend on linkage. One altern...

  8. Virus induced gene silencing of Arabidopsis gene homologues in wheat identify genes conferring improved drought tolerance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In a non-model staple crop like wheat, functional validation of potential drought stress responsive genes identified in Arabidopsis could provide gene targets for wheat breeding. Virus induced gene silencing (VIGS) of genes of interest can overcome the inherent problems of polyploidy and limited tra...

  9. Collaborative science in the next-generation sequencing era: a viewpoint on how to combine exome sequencing data across sites to identify novel disease susceptibility genes.

    PubMed

    Hart, Steven N; Maxwell, Kara N; Thomas, Tinu; Ravichandran, Vignesh; Wubberhorst, Bradley; Klein, Robert J; Schrader, Kasmintan; Szabo, Csilla; Weitzel, Jeffrey N; Neuhausen, Susan L; Nathanson, Katherine; Offit, Kenneth; Couch, Fergus J; Vijai, Joseph

    2016-07-01

    The purpose of this article is to inform readers about technical challenges that we encountered when assembling exome sequencing data from the 'Simplifying Complex Exomes' (SIMPLEXO) consortium-whose mandate is the discovery of novel genes predisposing to breast and ovarian cancers. Our motivation is to share these obstacles-and our solutions to them-as a means of communicating important technical details that should be discussed early in projects involving massively parallel sequencing. PMID:26358132

  10. Differences in Pathogenesis for Salmonella enterica serovar Typhimurium in the Mouse Versus the Swine Model Identify Bacterial Gene Products Required for Systemic but not Gastrointestinal Disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the last several decades, the mouse model of Typhoid fever has been an extremely productive model to investigate Salmonella enterica serovar Typhimurium pathogenesis. The mouse is the paradigm for investigating systemic disease due to infection by Salmonella; however, the swine model of gastro...

  11. Network-Based Inference Framework for Identifying Cancer Genes from Gene Expression Data

    PubMed Central

    Yang, Bo; Zhang, Junying; Yin, Yaling; Zhang, Yuanyuan

    2013-01-01

    Great efforts have been devoted to alleviate uncertainty of detected cancer genes as accurate identification of oncogenes is of tremendous significance and helps unravel the biological behavior of tumors. In this paper, we present a differential network-based framework to detect biologically meaningful cancer-related genes. Firstly, a gene regulatory network construction algorithm is proposed, in which a boosting regression based on likelihood score and informative prior is employed for improving accuracy of identification. Secondly, with the algorithm, two gene regulatory networks are constructed from case and control samples independently. Thirdly, by subtracting the two networks, a differential-network model is obtained and then used to rank differentially expressed hub genes for identification of cancer biomarkers. Compared with two existing gene-based methods (t-test and lasso), the method has a significant improvement in accuracy both on synthetic datasets and two real breast cancer datasets. Furthermore, identified six genes (TSPYL5, CD55, CCNE2, DCK, BBC3, and MUC1) susceptible to breast cancer were verified through the literature mining, GO analysis, and pathway functional enrichment analysis. Among these oncogenes, TSPYL5 and CCNE2 have been already known as prognostic biomarkers in breast cancer, CD55 has been suspected of playing an important role in breast cancer prognosis from literature evidence, and other three genes are newly discovered breast cancer biomarkers. More generally, the differential-network schema can be extended to other complex diseases for detection of disease associated-genes. PMID:24073403

  12. Extended haplotype association study in Crohn's disease identifies a novel, Ashkenazi Jewish-specific missense mutation in the NF-κB pathway gene, HEATR3.

    PubMed

    Zhang, W; Hui, K Y; Gusev, A; Warner, N; Ng, S M E; Ferguson, J; Choi, M; Burberry, A; Abraham, C; Mayer, L; Desnick, R J; Cardinale, C J; Hakonarson, H; Waterman, M; Chowers, Y; Karban, A; Brant, S R; Silverberg, M S; Gregersen, P K; Katz, S; Lifton, R P; Zhao, H; Nuñez, G; Pe'er, I; Peter, I; Cho, J H

    2013-01-01

    The Ashkenazi Jewish population has a several-fold higher prevalence of Crohn's disease (CD) compared with non-Jewish European ancestry populations and has a unique genetic history. Haplotype association is critical to CD etiology in this population, most notably at NOD2, in which three causal, uncommon and conditionally independent NOD2 variants reside on a shared background haplotype. We present an analysis of extended haplotypes that showed significantly greater association to CD in the Ashkenazi Jewish population compared with a non-Jewish population (145 haplotypes and no haplotypes with P-value <10(-3), respectively). Two haplotype regions, one each on chromosomes 16 and 21, conferred increased disease risk within established CD loci. We performed exome sequencing of 55 Ashkenazi Jewish individuals and follow-up genotyping focused on variants in these two regions. We observed Ashkenazi Jewish-specific nominal association at R755C in TRPM2 on chromosome 21. Within the chromosome 16 region, R642S of HEATR3 and rs9922362 of BRD7 showed genome-wide significance. Expression studies of HEATR3 demonstrated a positive role in NOD2-mediated NF-κB signaling. The BRD7 signal showed conditional dependence with only the downstream rare CD-causal variants in NOD2, but not with the background haplotype; this elaborates NOD2 as a key illustration of synthetic association. PMID:23615072

  13. Disease Resistance Gene Analogs (RGAs) in Plants

    PubMed Central

    Sekhwal, Manoj Kumar; Li, Pingchuan; Lam, Irene; Wang, Xiue; Cloutier, Sylvie; You, Frank M.

    2015-01-01

    Plants have developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs), as resistance (R) gene candidates, have conserved domains and motifs that play specific roles in pathogens’ resistance. Well-known RGAs are nucleotide binding site leucine rich repeats, receptor like kinases, and receptor like proteins. Others include pentatricopeptide repeats and apoplastic peroxidases. RGAs can be detected using bioinformatics tools based on their conserved structural features. Thousands of RGAs have been identified from sequenced plant genomes. High-density genome-wide RGA genetic maps are useful for designing diagnostic markers and identifying quantitative trait loci (QTL) or markers associated with plant disease resistance. This review focuses on recent advances in structures and mechanisms of RGAs, and their identification from sequenced genomes using bioinformatics tools. Applications in enhancing fine mapping and cloning of plant disease resistance genes are also discussed. PMID:26287177

  14. Identifying and characterizing barley genes that protect against trichothecenes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Our overall goal is to identify genes that play a role in resistance to Fusarium Head Blight (FHB) and to develop and test transgenic wheat carrying these genes. In particular, we are interested in identifying genes that protect barley and wheat from the effects of trichothecenes. Previously, we con...

  15. Comparative Genomics in Identifying Aflatoxin Biosynthetic Genes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aspergillus flavus produces the most toxic and the most carcinogenic mycotoxins, aflatoxin B1 and B2. In order to solve aflatoxin contamination of food commodities, A. flavus genomics tools for identification of genes involved in aflatoxin biosynthesis have been employed. A. flavus Expressed Seque...

  16. Epigenome-wide scan identifies a treatment-responsive pattern of altered DNA methylation among cytoskeletal remodeling genes in monocytes and CD4+ T cells in Behçet’s disease

    PubMed Central

    Hughes, Travis; Ture-Ozdemir, Filiz; Alibaz-Oner, Fatma; Coit, Patrick; Direskeneli, Haner; Sawalha, Amr H

    2014-01-01

    Objective Behçet’s disease (BD) is an inflammatory disease characterized by multi-system involvement including recurrent oral and genital ulcers, cutaneous lesions, and uveitis. The pathogenesis of BD remains poorly understood. We performed a genome-wide DNA methylation study in BD before and after disease remission, and in healthy matched controls. Methods We examined genome-wide DNA methylation in monocytes and CD4+ T cells from a set of 16 untreated male BD patients and age, sex, and ethnicity-matched controls. Additional samples were collected from 12 of the same BD patients after treatment and disease remission. Genome-wide DNA methylation patterns were assessed using the HumanMethylation450 DNA Analysis BeadChip array which includes over 485,000 individual methylation sites across the genome. Results We identified 383 differentially methylated CpG sites between BD patients and controls in monocytes and 125 differentially methylated CpG sites in CD4+ T cells. Bioinformatic analysis revealed a pattern of aberrant DNA methylation among genes that regulate cytoskeletal dynamics suggesting that aberrant DNA methylation of multiple classes of structural and regulatory proteins of the cytoskeleton might contribute to the pathogenesis of BD. Further, DNA methylation changes associated with treatment act to restore methylation differences observed between patients and controls. Indeed, among CpG sites differentially methylated before and after disease remission, there was almost exclusive reversal of the direction of aberrant DNA methylation observed between patients and healthy controls. Conclusions We performed the first epigenome-wide study in BD and provide strong evidence that epigenetic modification of cytoskeletal dynamics underlies the pathogenesis and therapeutic response in BD. PMID:24574333

  17. Comparison of melanoblast expression patterns identifies distinct classes of genes

    PubMed Central

    Loftus, Stacie K.; Baxter, Laura L.; Buac, Kristina; Watkins-Chow, Dawn E.; Larson, Denise M.; Pavan, William J.

    2010-01-01

    Summary A full understanding of transcriptional regulation requires integration of information obtained from multiple experimental datasets. These include datasets annotating gene expression within the context of an entire organism under normal and genetically perturbed conditions. Here we describe an expression dataset annotating pigment cell-expressed genes of the developing melanocyte and RPE lineages. Expression images are annotated and available at http://research.nhgri.nih.gov/manuscripts/Loftus/March2009/. Data is also summarized in a standardized manner using a universal melanoblast scoring scale that accounts for the embryonic location of cells and regional cell density. This approach allowed us to classify 14 pigment genes into 4 groupings classified by cell lineage expression, temporal-spatial context, and differential alteration in response to altered MITF and SOX10 status. Significant differences in regional populations were also observed across inbred strain backgrounds highlighting the value of this approach to identify modifier allele influences on melanoblast number and distributions. This analysis revealed novel features of in vivo expression patterns that are not measurable by in vitro-based assays, providing data that in combination with genomic analyses will allow modeling of pigment cell gene expression in development and disease. PMID:19493314

  18. Identifying Driver Genes in Cancer by Triangulating Gene Expression, Gene Location, and Survival Data

    PubMed Central

    Rouam, Sigrid; Miller, Lance D; Karuturi, R Krishna Murthy

    2014-01-01

    Driver genes are directly responsible for oncogenesis and identifying them is essential in order to fully understand the mechanisms of cancer. However, it is difficult to delineate them from the larger pool of genes that are deregulated in cancer (ie, passenger genes). In order to address this problem, we developed an approach called TRIAngulating Gene Expression (TRIAGE through clinico-genomic intersects). Here, we present a refinement of this approach incorporating a new scoring methodology to identify putative driver genes that are deregulated in cancer. TRIAGE triangulates – or integrates – three levels of information: gene expression, gene location, and patient survival. First, TRIAGE identifies regions of deregulated expression (ie, expression footprints) by deriving a newly established measure called the Local Singular Value Decomposition (LSVD) score for each locus. Driver genes are then distinguished from passenger genes using dual survival analyses. Incorporating measurements of gene expression and weighting them according to the LSVD weight of each tumor, these analyses are performed using the genes located in significant expression footprints. Here, we first use simulated data to characterize the newly established LSVD score. We then present the results of our application of this refined version of TRIAGE to gene expression data from five cancer types. This refined version of TRIAGE not only allowed us to identify known prominent driver genes, such as MMP1, IL8, and COL1A2, but it also led us to identify several novel ones. These results illustrate that TRIAGE complements existing tools, allows for the identification of genes that drive cancer and could perhaps elucidate potential future targets of novel anticancer therapeutics. PMID:25949096

  19. Patching genes to fight disease

    SciTech Connect

    Holzman, D.

    1990-09-03

    The National Institutes of Health has approved the first gene therapy experiments, one of which will try to cure cancer by bolstering the immune system. The applications of such therapy are limited, but the potential aid to people with genetic diseases is great.

  20. Phenol sulfotransferases: Candidate genes for Batten disease

    SciTech Connect

    Dooley, T.P.; Probst, P.; Obermoeller, R.D.

    1995-06-05

    Batten disease (juvenile-onset neuronal ceroid lipofuscinosis; JNCL) is an autosomal recessive neurodegenerative disorder, characterized by the cytosomal accumulation of autofluorescent protolipopigments in neurons and other cell types. The Batten disease gene (CLN3) has not yet been identified, but has been mapped to a small region of human chromosome area 16p12.1-p11.2. We recently reported the fortuitous discovery that the cytosolic phenol sulfotransferase gene (STP) is located within this same interval of chromosome 16p. Since phenol sulfotransferase is expressed in neurons, can sulfate lipophilic phenolic compounds, and is mapped near CLN3, STP is considered as a candidate gene for Batten disease. YAC and cosmid cloning results have further substantiated the close proximity of STP and a highly related sulfotransferase (STM), encoding the catecholamine-preferring enzyme, to the CLN3 region of chromosome 16p. In this report, we summarize some of the recent progress in the identification of two phenol sulfotransferase genes (STP and STM) as positional candidate genes for Batten disease. 42 refs., 1 tab.

  1. mdv1-miR-M7-5p, located in the newly identified first intron of the latency-associated transcript of Marek's disease virus, targets the immediate-early genes ICP4 and ICP27.

    PubMed

    Strassheim, S; Stik, G; Rasschaert, D; Laurent, S

    2012-08-01

    Marek's disease virus serotype 1 (MDV-1) is an oncogenic alphaherpesvirus causing fatal T-cell lymphoma in chickens. MDV latency is characterized by the production of latency-associated transcripts (LATs), a family of non-protein-coding spliced RNAs. A cluster of four microRNAs (cluster mdv1-miR-M8-M10) was identified, but not formally mapped, at the predicted LAT 5' end. We established a LAT cDNA library from latently MDV-infected cell line MSB-1. We identified 22 highly variable LATs, which were due to the extensive alternative splicing of a total of 14 introns. RACE PCR confirmed the predicted 3' end and allowed identification of the 5' end, 400 nt upstream of the previously predicted LAT end. The LATs share their transcription start site with the microRNA-expressing transcript described previously, localizing the microRNAs to the first LAT intron and identifying the LATs as the primary transcripts of the microRNAs. We identified MDV immediate-early (IE) genes ICP4 and ICP27 as putative targets of mdv1-miR-M7-5p, the third microRNA of the cluster mdv1-miR-M8-M10. Endogenously expressed mdv1-miR-M7-5p in MSB-1 cells reduced luciferase activity significantly when microRNA-responsive elements from ICP4 or ICP27 were cloned in the 3' UTR of the firefly luciferase gene. ICP27 protein levels were decreased by 70 % when the mdv1-miR-M7-5p precursor was co-expressed with an ICP27 expression plasmid. Additionally, we showed a negative correlation between the decreased expression of mdv1-miR-M7-5p and an increase in ICP27 expression during virus reactivation. Our results suggest that, by targeting two IE genes, MDV microRNAs produced from LAT transcripts may contribute to establish and/or maintain latency. PMID:22513387

  2. Identifying Constraints to Potato System Sustainability: Diseases

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Four different potato cropping systems, designed to address specific management goals of soil conservation (SC), soil improvement (SI), disease suppression (DS), and a status quo (standard rotation) control (SQ), were evaluated for their effects on soilborne and foliar diseases of potato, as well as...

  3. Improved human disease candidate gene prioritization using mouse phenotype

    PubMed Central

    Chen, Jing; Xu, Huan; Aronow, Bruce J; Jegga, Anil G

    2007-01-01

    Background The majority of common diseases are multi-factorial and modified by genetically and mechanistically complex polygenic interactions and environmental factors. High-throughput genome-wide studies like linkage analysis and gene expression profiling, tend to be most useful for classification and characterization but do not provide sufficient information to identify or prioritize specific disease causal genes. Results Extending on an earlier hypothesis that the majority of genes that impact or cause disease share membership in any of several functional relationships we, for the first time, show the utility of mouse phenotype data in human disease gene prioritization. We study the effect of different data integration methods, and based on the validation studies, we show that our approach, ToppGene , outperforms two of the existing candidate gene prioritization methods, SUSPECTS and ENDEAVOUR. Conclusion The incorporation of phenotype information for mouse orthologs of human genes greatly improves the human disease candidate gene analysis and prioritization. PMID:17939863

  4. Activation tag screening to identify novel genes for trichothecene resistance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The goal of our research is to identify plant genes which enhance trichothecene resistance and, ultimately, Fusarium Head Blight resistance in wheat and barley. We are taking a two pronged approach using Arabidopsis to identify plant genes which confer resistance to trichothecenes. The first approac...

  5. Genes and environment in celiac disease.

    PubMed

    Sollid, L M; McAdam, S N; Molberg, O; Quarsten, H; Arentz-Hansen, H; Louka, A S; Lundin, K E

    2001-06-01

    Celiac disease is an intestinal disorder that develops as a result of interplay between genetic and environmental factors. HLA genes along with non-HLA genes predispose to the disease. Linkage studies have failed to identify chromosomal regions other than the HLA region which have major effects, indicating the existence of multiple non-HLA predisposing genes with modest effects. Association studies have shown that CTLA4 or a closely located gene is one of these genes. The primary HLA association in the majority of celiac disease patients is with DQ2 (DQA1*05/DQB1*02) and in the minority of patients with DQ8 (DQA1*0301/DQB1*0302). Gluten reactive CD4+ T cells can be isolated from small intestinal biopsies of celiac patients but not from controls. DQ2 or DQ8, but not other HLA molecules carried by patients, present peptides to these T cells. A number of distinct T cell gluten epitopes exist, most of them posttranslationally modified by deamidation. DQ2 and DQ8 bind the epitopes such that the glutamic acid residues created by deamidation are accommodated in pockets that have a preference for negatively charged side chains. There is evidence that deamidation in vivo is mediated by the enzyme tissue transglutaminase (tTG). Overall, the results point to control of the immune response to gluten by intestinal T cells restricted by the DQ2 or DQ8 molecules. This is likely to be a critical checkpoint for the development of celiac disease and could explain the dominant genetic role of HLA in this disorder. The products of the other predisposing genes may participate in pathway(s) that lead(s) to lesion formation. The minor genetic effects of the non-HLA genes could indicate a lack of critical checkpoints along these pathways, or that there are several pathways leading to the lesion formation. PMID:11501889

  6. Genes and Disease: Prader-Willi Syndrome

    MedlinePlus

    ... Medicine, National Institutes of Health. National Center for Biotechnology Information (US). Genes and Disease [Internet]. Bethesda (MD): National Center for Biotechnology Information (US); 1998-. Genes and Disease [Internet]. Show ...

  7. BLAT2DOLite: An Online System for Identifying Significant Relationships between Genetic Sequences and Diseases

    PubMed Central

    Cheng, Liang; Zhang, Shuo; Hu, Yang

    2016-01-01

    The significantly related diseases of sequences could play an important role in understanding the functions of these sequences. In this paper, we introduced BLAT2DOLite, an online system for annotating human genes and diseases and identifying the significant relationships between sequences and diseases. Currently, BLAT2DOLite integrates Entrez Gene database and Disease Ontology Lite (DOLite), which contain loci of gene and relationships between genes and diseases. It utilizes hypergeometric test to calculate P-values between genes and diseases of DOLite. The system can be accessed from: http://123.59.132.21:8080/BLAT2DOLite. The corresponding web service is described in: http://123.59.132.21:8080/BLAT2DOLite/BLAT2DOLiteIDMappingPort?wsdl. PMID:27315278

  8. Translation of disease associated gene signatures across tissues.

    PubMed

    Kasim, Adetayo; Shkedy, Ziv; Lin, Dan; Van Sanden, Suzy; Abrahantes, Josè Cortiñas; Göhlmann, Hinrich W H; Bijnens, Luc; Yekutieli, Dani; Camilleri, Michael; Aerssens, Jeroen; Talloen, Willem

    2015-01-01

    It has recently been shown that disease associated gene signatures can be identified by profiling tissue other than the disease related tissue. In this paper, we investigate gene signatures for Irritable Bowel Syndrome (IBS) using gene expression profiling of both disease related tissue (colon) and surrogate tissue (rectum). Gene specific joint ANOVA models were used to investigate differentially expressed genes between the IBS patients and the healthy controls taken into account both intra and inter tissue dependencies among expression levels of the same gene. Classification algorithms in combination with feature selection methods were used to investigate the predictive power of gene expression levels from the surrogate and the target tissues. We conclude based on the analyses that expression profiles of the colon and the rectum tissue could result in better predictive accuracy if the disease associated genes are known. PMID:26333264

  9. Blood Pressure Loci Identified with a Gene-Centric Array

    PubMed Central

    Johnson, Toby; Gaunt, Tom R.; Newhouse, Stephen J.; Padmanabhan, Sandosh; Tomaszewski, Maciej; Kumari, Meena; Morris, Richard W.; Tzoulaki, Ioanna; O'Brien, Eoin T.; Poulter, Neil R.; Sever, Peter; Shields, Denis C.; Thom, Simon; Wannamethee, Sasiwarang G.; Whincup, Peter H.; Brown, Morris J.; Connell, John M.; Dobson, Richard J.; Howard, Philip J.; Mein, Charles A.; Onipinla, Abiodun; Shaw-Hawkins, Sue; Zhang, Yun; Smith, George Davey; Day, Ian N.M.; Lawlor, Debbie A.; Goodall, Alison H.; Fowkes, F. Gerald; Abecasis, Gonçalo R.; Elliott, Paul; Gateva, Vesela; Braund, Peter S.; Burton, Paul R.; Nelson, Christopher P.; Tobin, Martin D.; van der Harst, Pim; Glorioso, Nicola; Neuvrith, Hani; Salvi, Erika; Staessen, Jan A.; Stucchi, Andrea; Devos, Nabila; Jeunemaitre, Xavier; Plouin, Pierre-François; Tichet, Jean; Juhanson, Peeter; Org, Elin; Putku, Margus; Sõber, Siim; Veldre, Gudrun; Viigimaa, Margus; Levinsson, Anna; Rosengren, Annika; Thelle, Dag S.; Hastie, Claire E.; Hedner, Thomas; Lee, Wai K.; Melander, Olle; Wahlstrand, Björn; Hardy, Rebecca; Wong, Andrew; Cooper, Jackie A.; Palmen, Jutta; Chen, Li; Stewart, Alexandre F.R.; Wells, George A.; Westra, Harm-Jan; Wolfs, Marcel G.M.; Clarke, Robert; Franzosi, Maria Grazia; Goel, Anuj; Hamsten, Anders; Lathrop, Mark; Peden, John F.; Seedorf, Udo; Watkins, Hugh; Ouwehand, Willem H.; Sambrook, Jennifer; Stephens, Jonathan; Casas, Juan-Pablo; Drenos, Fotios; Holmes, Michael V.; Kivimaki, Mika; Shah, Sonia; Shah, Tina; Talmud, Philippa J.; Whittaker, John; Wallace, Chris; Delles, Christian; Laan, Maris; Kuh, Diana; Humphries, Steve E.; Nyberg, Fredrik; Cusi, Daniele; Roberts, Robert; Newton-Cheh, Christopher; Franke, Lude; Stanton, Alice V.; Dominiczak, Anna F.; Farrall, Martin; Hingorani, Aroon D.; Samani, Nilesh J.; Caulfield, Mark J.; Munroe, Patricia B.

    2011-01-01

    Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10−7 study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r2 = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10−7 at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies. PMID:22100073

  10. Blood pressure loci identified with a gene-centric array.

    PubMed

    Johnson, Toby; Gaunt, Tom R; Newhouse, Stephen J; Padmanabhan, Sandosh; Tomaszewski, Maciej; Kumari, Meena; Morris, Richard W; Tzoulaki, Ioanna; O'Brien, Eoin T; Poulter, Neil R; Sever, Peter; Shields, Denis C; Thom, Simon; Wannamethee, Sasiwarang G; Whincup, Peter H; Brown, Morris J; Connell, John M; Dobson, Richard J; Howard, Philip J; Mein, Charles A; Onipinla, Abiodun; Shaw-Hawkins, Sue; Zhang, Yun; Davey Smith, George; Day, Ian N M; Lawlor, Debbie A; Goodall, Alison H; Fowkes, F Gerald; Abecasis, Gonçalo R; Elliott, Paul; Gateva, Vesela; Braund, Peter S; Burton, Paul R; Nelson, Christopher P; Tobin, Martin D; van der Harst, Pim; Glorioso, Nicola; Neuvrith, Hani; Salvi, Erika; Staessen, Jan A; Stucchi, Andrea; Devos, Nabila; Jeunemaitre, Xavier; Plouin, Pierre-François; Tichet, Jean; Juhanson, Peeter; Org, Elin; Putku, Margus; Sõber, Siim; Veldre, Gudrun; Viigimaa, Margus; Levinsson, Anna; Rosengren, Annika; Thelle, Dag S; Hastie, Claire E; Hedner, Thomas; Lee, Wai K; Melander, Olle; Wahlstrand, Björn; Hardy, Rebecca; Wong, Andrew; Cooper, Jackie A; Palmen, Jutta; Chen, Li; Stewart, Alexandre F R; Wells, George A; Westra, Harm-Jan; Wolfs, Marcel G M; Clarke, Robert; Franzosi, Maria Grazia; Goel, Anuj; Hamsten, Anders; Lathrop, Mark; Peden, John F; Seedorf, Udo; Watkins, Hugh; Ouwehand, Willem H; Sambrook, Jennifer; Stephens, Jonathan; Casas, Juan-Pablo; Drenos, Fotios; Holmes, Michael V; Kivimaki, Mika; Shah, Sonia; Shah, Tina; Talmud, Philippa J; Whittaker, John; Wallace, Chris; Delles, Christian; Laan, Maris; Kuh, Diana; Humphries, Steve E; Nyberg, Fredrik; Cusi, Daniele; Roberts, Robert; Newton-Cheh, Christopher; Franke, Lude; Stanton, Alice V; Dominiczak, Anna F; Farrall, Martin; Hingorani, Aroon D; Samani, Nilesh J; Caulfield, Mark J; Munroe, Patricia B

    2011-12-01

    Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies. PMID:22100073

  11. Microarray analysis identified Puccinia striiformis f. sp. tritici genes involved in infection and sporulation.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, one of the most important diseases of wheat worldwide. To identify Pst genes involved in infection and sporulation, a custom oligonucleotide Genechip was made using sequences of 442 genes selected from Pst cDNA libraries. Microarray analy...

  12. Using Text Analysis to Identify Functionally Coherent Gene Groups

    PubMed Central

    Raychaudhuri, Soumya; Schütze, Hinrich; Altman, Russ B.

    2002-01-01

    The analysis of large-scale genomic information (such as sequence data or expression patterns) frequently involves grouping genes on the basis of common experimental features. Often, as with gene expression clustering, there are too many groups to easily identify the functionally relevant ones. One valuable source of information about gene function is the published literature. We present a method, neighbor divergence, for assessing whether the genes within a group share a common biological function based on their associated scientific literature. The method uses statistical natural language processing techniques to interpret biological text. It requires only a corpus of documents relevant to the genes being studied (e.g., all genes in an organism) and an index connecting the documents to appropriate genes. Given a group of genes, neighbor divergence assigns a numerical score indicating how “functionally coherent” the gene group is from the perspective of the published literature. We evaluate our method by testing its ability to distinguish 19 known functional gene groups from 1900 randomly assembled groups. Neighbor divergence achieves 79% sensitivity at 100% specificity, comparing favorably to other tested methods. We also apply neighbor divergence to previously published gene expression clusters to assess its ability to recognize gene groups that had been manually identified as representative of a common function. PMID:12368251

  13. Evolutionary Signatures amongst Disease Genes Permit Novel Methods for Gene Prioritization and Construction of Informative Gene-Based Networks

    PubMed Central

    Priedigkeit, Nolan; Wolfe, Nicholas; Clark, Nathan L.

    2015-01-01

    Genes involved in the same function tend to have similar evolutionary histories, in that their rates of evolution covary over time. This coevolutionary signature, termed Evolutionary Rate Covariation (ERC), is calculated using only gene sequences from a set of closely related species and has demonstrated potential as a computational tool for inferring functional relationships between genes. To further define applications of ERC, we first established that roughly 55% of genetic diseases posses an ERC signature between their contributing genes. At a false discovery rate of 5% we report 40 such diseases including cancers, developmental disorders and mitochondrial diseases. Given these coevolutionary signatures between disease genes, we then assessed ERC's ability to prioritize known disease genes out of a list of unrelated candidates. We found that in the presence of an ERC signature, the true disease gene is effectively prioritized to the top 6% of candidates on average. We then apply this strategy to a melanoma-associated region on chromosome 1 and identify MCL1 as a potential causative gene. Furthermore, to gain global insight into disease mechanisms, we used ERC to predict molecular connections between 310 nominally distinct diseases. The resulting “disease map” network associates several diseases with related pathogenic mechanisms and unveils many novel relationships between clinically distinct diseases, such as between Hirschsprung's disease and melanoma. Taken together, these results demonstrate the utility of molecular evolution as a gene discovery platform and show that evolutionary signatures can be used to build informative gene-based networks. PMID:25679399

  14. Huntington's disease biomarker progression profile identified by transcriptome sequencing in peripheral blood.

    PubMed

    Mastrokolias, Anastasios; Ariyurek, Yavuz; Goeman, Jelle J; van Duijn, Erik; Roos, Raymund A C; van der Mast, Roos C; van Ommen, GertJan B; den Dunnen, Johan T; 't Hoen, Peter A C; van Roon-Mom, Willeke M C

    2015-10-01

    With several therapeutic approaches in development for Huntington's disease, there is a need for easily accessible biomarkers to monitor disease progression and therapy response. We performed next-generation sequencing-based transcriptome analysis of total RNA from peripheral blood of 91 mutation carriers (27 presymptomatic and, 64 symptomatic) and 33 controls. Transcriptome analysis by DeepSAGE identified 167 genes significantly associated with clinical total motor score in Huntington's disease patients. Relative to previous studies, this yielded novel genes and confirmed previously identified genes, such as H2AFY, an overlap in results that has proven difficult in the past. Pathway analysis showed enrichment of genes of the immune system and target genes of miRNAs, which are downregulated in Huntington's disease models. Using a highly parallelized microfluidics array chip (Fluidigm), we validated 12 of the top 20 significant genes in our discovery cohort and 7 in a second independent cohort. The five genes (PROK2, ZNF238, AQP9, CYSTM1 and ANXA3) that were validated independently in both cohorts present a candidate biomarker panel for stage determination and therapeutic readout in Huntington's disease. Finally we suggest a first empiric formula predicting total motor score from the expression levels of our biomarker panel. Our data support the view that peripheral blood is a useful source to identify biomarkers for Huntington's disease and monitor disease progression in future clinical trials. PMID:25626709

  15. Rice transcriptome analysis to identify possible herbicide quinclorac detoxification genes

    PubMed Central

    Xu, Wenying; Di, Chao; Zhou, Shaoxia; Liu, Jia; Li, Li; Liu, Fengxia; Yang, Xinling; Ling, Yun; Su, Zhen

    2015-01-01

    Quinclorac is a highly selective auxin-type herbicide and is widely used in the effective control of barnyard grass in paddy rice fields, improving the world's rice yield. The herbicide mode of action of quinclorac has been proposed, and hormone interactions affecting quinclorac signaling has been identified. Because of widespread use, quinclorac may be transported outside rice fields with the drainage waters, leading to soil and water pollution and other environmental health problems. In this study, we used 57K Affymetrix rice whole-genome array to identify quinclorac signaling response genes to study the molecular mechanisms of action and detoxification of quinclorac in rice plants. Overall, 637 probe sets were identified with differential expression levels under either 6 or 24 h of quinclorac treatment. Auxin-related genes such as GH3 and OsIAAs responded to quinclorac treatment. Gene Ontology analysis showed that genes of detoxification-related family genes were significantly enriched, including cytochrome P450, GST, UGT, and ABC and drug transporter genes. Moreover, real-time RT-PCR analysis showed that top candidate genes of P450 families such as CYP81, CYP709C, and CYP72A were universally induced by different herbicides. Some Arabidopsis genes of the same P450 family were up-regulated under quinclorac treatment. We conducted rice whole-genome GeneChip analysis and the first global identification of quinclorac response genes. This work may provide potential markers for detoxification of quinclorac and biomonitors of environmental chemical pollution. PMID:26483837

  16. Identifying Novel Candidate Genes Related to Apoptosis from a Protein-Protein Interaction Network

    PubMed Central

    Wang, Baoman; Yuan, Fei; Kong, Xiangyin; Hu, Lan-Dian; Cai, Yu-Dong

    2015-01-01

    Apoptosis is the process of programmed cell death (PCD) that occurs in multicellular organisms. This process of normal cell death is required to maintain the balance of homeostasis. In addition, some diseases, such as obesity, cancer, and neurodegenerative diseases, can be cured through apoptosis, which produces few side effects. An effective comprehension of the mechanisms underlying apoptosis will be helpful to prevent and treat some diseases. The identification of genes related to apoptosis is essential to uncover its underlying mechanisms. In this study, a computational method was proposed to identify novel candidate genes related to apoptosis. First, protein-protein interaction information was used to construct a weighted graph. Second, a shortest path algorithm was applied to the graph to search for new candidate genes. Finally, the obtained genes were filtered by a permutation test. As a result, 26 genes were obtained, and we discuss their likelihood of being novel apoptosis-related genes by collecting evidence from published literature. PMID:26543496

  17. Potential New Genes for Resistance to Mycosphaerella Graminicola Identified in Triticum Aestivum x Lophopyrum Elongatum Disomic Substitution Lines

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lophopyrum species carry many desirable agronomic traits, including disease resistance, which can be transferred to wheat by interspecific hybridizations. To identify potentially new genes for disease and insect resistance carried by individual Lophopyrum chromosomes, 19 of 21 possible wheat cultiv...

  18. The Wilson disease gene: Haplotypes and mutations

    SciTech Connect

    Thomas, G.R.; Roberts, E.A.; Cox, D.W.; Walshe, J.M.

    1994-09-01

    Wilson disease (WND) is an autosomal recessive defect of copper transport. The gene involved in WND, located on chromosome 13, has recently been shown to be a putative copper transporting P-type ATPase, designated ATP7B. The gene is highly similar to ATP7A, located on the X chromosome, which is defective in Menkes disease, another disorder of copper transport. We have available for study WND families from Canada (34 families), the United Kingdom (32 families), Japan (4 families), Iceland (3 families) and Hong Kong (2 families). We have utilized four highly polymorphic CA repeat markers (D13S296, D13S301, D13S314 and D13S316) surrounding the ATP7B locus to construct haplotypes in these families. Analysis indicates that there are many unique WND haplotypes not present on normal chromosomes and that there may be a large number of different WND mutations. We have screened the WND patients for mutations in the ATP7B gene. Fifty six patients, representing all of the identified haplotypes, have been screened using single strand conformational polymorphism (SSCP), followed by selective sequencing. To date, 19 mutations and 12 polymorphisms have been identified. All of the changes are nucleotide substitutions or small insertions/deletions and there is no evidence for larger deletions as seen in the similar gene on the X chromosome, ATP7A. Haplotypes of close markers and the ability to detect some of the mutations present in the gene allow for more reliable molecular diagnosis of presymptomatic sibs of WND patients. A reassessment of individuals previously diagnosed in the presymptomatic phase is now required, as we have have identified some heterozygotes who are biochemically indistinguishable from affected homozygotes. The identification of specific mutations will soon allow direct diagnosis of WND patients with a high level of certainty.

  19. GENE EXPRESSION PROFILING TO IDENTIFY BIOMARKERS OF REPRODUCTIVE TOXICITY

    EPA Science Inventory

    SOT 2005 SESSION ABSTRACT

    GENE EXPRESSION PROFILING TO IDENTIFY BIOMARKERS OF REPRODUCTIVE TOXICITY

    David J. Dix. National Health and Environmental Effects Research Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle...

  20. Strategies for Gene Mapping in Inherited Ophthalmic Diseases.

    PubMed

    Srilekha, Sundar; Rao, Bhavna; Rao, Divya M; Sudha, D; Chandrasekar, Sathya Priya; Pandian, A J; Soumittra, N; Sripriya, S

    2016-01-01

    Gene mapping of inherited ophthalmic diseases such as congenital cataracts, retinal degeneration, glaucoma, age-related macular degeneration, myopia, optic atrophy, and eye malformations has shed more light on the disease pathology, identified targets for research on therapeutics, earlier detection, and treatment options for disease management and patient care. This article details the different approaches to gene identification for both Mendelian and complex eye disorders. PMID:27488070

  1. How to identify essential genes from molecular networks?

    PubMed Central

    del Rio, Gabriel; Koschützki, Dirk; Coello, Gerardo

    2009-01-01

    Background The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion. Results By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for Saccharomyces cerevisiae, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined. Conclusion The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes. PMID:19822021

  2. Genes conserved for arbuscular mycorrhizal symbiosis identified through phylogenomics.

    PubMed

    Bravo, Armando; York, Thomas; Pumplin, Nathan; Mueller, Lukas A; Harrison, Maria J

    2016-01-01

    Arbuscular mycorrhizal symbiosis (AMS), a widespread mutualistic association of land plants and fungi(1), is predicted to have arisen once, early in the evolution of land plants(2-4). Consistent with this notion, several genes required for AMS have been conserved throughout evolution(5) and their symbiotic functions preserved, at least between monocot and dicot plants(6,7). Despite its significance, knowledge of the plants' genetic programme for AMS is limited. To date, most genes required for AMS have been found through commonalities with the evolutionarily younger nitrogen-fixing Rhizobium legume symbiosis (RLS)(8) or by reverse genetic analyses of differentially expressed candidate genes(9). Large sequence-indexed insertion mutant collections and recent genome editing technologies have vastly increased the power of reverse genetics but selection of candidate genes, from the thousands of genes that change expression during AMS, remains an arbitrary process. Here, we describe a phylogenomics approach to identify genes whose evolutionary history predicts conservation for AMS and we demonstrate the accuracy of the predictions through reverse genetics analysis. Phylogenomics analysis of 50 plant genomes resulted in 138 genes from Medicago truncatula predicted to function in AMS. This includes 15 genes with known roles in AMS. Additionally, we demonstrate that mutants in six previously uncharacterized AMS-conserved genes are all impaired in AMS. Our results demonstrate that phylogenomics is an effective strategy to identify a set of evolutionarily conserved genes required for AMS. PMID:27249190

  3. A Novel Prioritization Method in Identifying Recurrent Venous Thromboembolism-Related Genes

    PubMed Central

    Xie, Ruiqiang; Chen, Binbin; Huang, Hao; Li, Yiran; He, Yuehan; Lv, Junjie; He, Weiming; Chen, Lina

    2016-01-01

    Identifying the genes involved in venous thromboembolism (VTE) recurrence is important not only for understanding the pathogenesis but also for discovering the therapeutic targets. We proposed a novel prioritization method called Function-Interaction-Pearson (FIP) by creating gene-disease similarity scores to prioritize candidate genes underling VTE. The scores were calculated by integrating and optimizing three types of resources including gene expression, gene ontology and protein-protein interaction. As a result, 124 out of top 200 prioritized candidate genes had been confirmed in literature, among which there were 34 antithrombotic drug targets. Compared with two well-known gene prioritization tools Endeavour and ToppNet, FIP was shown to have better performance. The approach provides a valuable alternative for drug targets discovery and disease therapy. PMID:27050193

  4. A Novel Prioritization Method in Identifying Recurrent Venous Thromboembolism-Related Genes.

    PubMed

    Jiang, Jing; Li, Wan; Liang, Binhua; Xie, Ruiqiang; Chen, Binbin; Huang, Hao; Li, Yiran; He, Yuehan; Lv, Junjie; He, Weiming; Chen, Lina

    2016-01-01

    Identifying the genes involved in venous thromboembolism (VTE) recurrence is important not only for understanding the pathogenesis but also for discovering the therapeutic targets. We proposed a novel prioritization method called Function-Interaction-Pearson (FIP) by creating gene-disease similarity scores to prioritize candidate genes underling VTE. The scores were calculated by integrating and optimizing three types of resources including gene expression, gene ontology and protein-protein interaction. As a result, 124 out of top 200 prioritized candidate genes had been confirmed in literature, among which there were 34 antithrombotic drug targets. Compared with two well-known gene prioritization tools Endeavour and ToppNet, FIP was shown to have better performance. The approach provides a valuable alternative for drug targets discovery and disease therapy. PMID:27050193

  5. Differential Network Analyses of Alzheimer’s Disease Identify Early Events in Alzheimer’s Disease Pathology

    DOE PAGESBeta

    Xia, Jing; Rocke, David M.; Perry, George; Ray, Monika

    2014-01-01

    In late-onset Alzheimer’s disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with lowmore » topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases.« less

  6. Genetic risk factors for the development of allergic disease identified by genome-wide association

    PubMed Central

    Portelli, M A; Hodge, E; Sayers, I

    2015-01-01

    An increasing proportion of the worldwide population is affected by allergic diseases such as allergic rhinitis (AR), atopic dermatitis (AD) and allergic asthma and improved treatment options are needed particularly for severe, refractory disease. Allergic diseases are complex and development involves both environmental and genetic factors. Although the existence of a genetic component for allergy was first described almost 100 years ago, progress in gene identification has been hindered by lack of high throughput technologies to investigate genetic variation in large numbers of subjects. The development of Genome-Wide Association Studies (GWAS), a hypothesis-free method of interrogating large numbers of common variants spanning the entire genome in disease and non-disease subjects has revolutionised our understanding of the genetics of allergic disease. Susceptibility genes for asthma, AR and AD have now been identified with confidence, suggesting there are common and distinct genetic loci associated with these diseases, providing novel insights into potential disease pathways and mechanisms. Genes involved in both adaptive and innate immune mechanisms have been identified, notably including multiple genes involved in epithelial function/secretion, suggesting that the airway epithelium may be particularly important in asthma. Interestingly, concordance/discordance between the genetic factors driving allergic traits such as IgE levels and disease states such as asthma have further supported the accumulating evidence for heterogeneity in these diseases. While GWAS have been useful and continue to identify novel genes for allergic diseases through increased sample sizes and phenotype refinement, future approaches will integrate analyses of rare variants, epigenetic mechanisms and eQTL approaches, leading to greater insight into the genetic basis of these diseases. Gene identification will improve our understanding of disease mechanisms and generate potential

  7. A genomic approach to identify hybrid incompatibility genes

    PubMed Central

    Cooper, Jacob C.; Phadnis, Nitin

    2016-01-01

    ABSTRACT Uncovering the genetic and molecular basis of barriers to gene flow between populations is key to understanding how new species are born. Intrinsic postzygotic reproductive barriers such as hybrid sterility and hybrid inviability are caused by deleterious genetic interactions known as hybrid incompatibilities. The difficulty in identifying these hybrid incompatibility genes remains a rate-limiting step in our understanding of the molecular basis of speciation. We recently described how whole genome sequencing can be applied to identify hybrid incompatibility genes, even from genetically terminal hybrids. Using this approach, we discovered a new hybrid incompatibility gene, gfzf, between Drosophila melanogaster and Drosophila simulans, and found that it plays an essential role in cell cycle regulation. Here, we discuss the history of the hunt for incompatibility genes between these species, discuss the molecular roles of gfzf in cell cycle regulation, and explore how intragenomic conflict drives the evolution of fundamental cellular mechanisms that lead to the developmental arrest of hybrids. PMID:27230814

  8. Inferring Gene Family Histories in Yeast Identifies Lineage Specific Expansions

    PubMed Central

    Ames, Ryan M.; Money, Daniel; Lovell, Simon C.

    2014-01-01

    The complement of genes found in the genome is a balance between gene gain and gene loss. Knowledge of the specific genes that are gained and lost over evolutionary time allows an understanding of the evolution of biological functions. Here we use new evolutionary models to infer gene family histories across complete yeast genomes; these models allow us to estimate the relative genome-wide rates of gene birth, death, innovation and extinction (loss of an entire family) for the first time. We show that the rates of gene family evolution vary both between gene families and between species. We are also able to identify those families that have experienced rapid lineage specific expansion/contraction and show that these families are enriched for specific functions. Moreover, we find that families with specific functions are repeatedly expanded in multiple species, suggesting the presence of common adaptations and that these family expansions/contractions are not random. Additionally, we identify potential specialisations, unique to specific species, in the functions of lineage specific expanded families. These results suggest that an important mechanism in the evolution of genome content is the presence of lineage-specific gene family changes. PMID:24921666

  9. Functional epigenetic approach identifies frequently methylated genes in Ewing sarcoma.

    PubMed

    Alholle, Abdullah; Brini, Anna T; Gharanei, Seley; Vaiyapuri, Sumathi; Arrigoni, Elena; Dallol, Ashraf; Gentle, Dean; Kishida, Takeshi; Hiruma, Toru; Avigad, Smadar; Grimer, Robert; Maher, Eamonn R; Latif, Farida

    2013-11-01

    Using a candidate gene approach we recently identified frequent methylation of the RASSF2 gene associated with poor overall survival in Ewing sarcoma (ES). To identify effective biomarkers in ES on a genome-wide scale, we used a functionally proven epigenetic approach, in which gene expression was induced in ES cell lines by treatment with a demethylating agent followed by hybridization onto high density gene expression microarrays. After following a strict selection criterion, 34 genes were selected for expression and methylation analysis in ES cell lines and primary ES. Eight genes (CTHRC1, DNAJA4, ECHDC2, NEFH, NPTX2, PHF11, RARRES2, TSGA14) showed methylation frequencies of>20% in ES tumors (range 24-71%), these genes were expressed in human bone marrow derived mesenchymal stem cells (hBMSC) and hypermethylation was associated with transcriptional silencing. Methylation of NPTX2 or PHF11 was associated with poorer prognosis in ES. In addition, six of the above genes also showed methylation frequency of>20% (range 36-50%) in osteosarcomas. Identification of these genes may provide insights into bone cancer tumorigenesis and development of epigenetic biomarkers for prognosis and detection of these rare tumor types. PMID:24005033

  10. The Implicitome: A Resource for Rationalizing Gene-Disease Associations

    PubMed Central

    van der Horst, Eelke; Kaliyaperumal, Rajaram; Mina, Eleni; Tatum, Zuotian; Laros, Jeroen F. J.; van Mulligen, Erik M.; Schuemie, Martijn; Aten, Emmelien; Li, Tong Shu; Bruskiewich, Richard; Good, Benjamin M.; Su, Andrew I.; Kors, Jan A.; den Dunnen, Johan; van Ommen, Gert-Jan B.; Roos, Marco; ‘t Hoen, Peter A.C.; Mons, Barend; Schultes, Erik A.

    2016-01-01

    High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing biomedical knowledge for identification and interpretation of gene-disease associations. The implicitome can be used in conjunction with experimental data resources to rationalize both known and novel associations. We demonstrate the usefulness of the implicitome by rationalizing known and novel gene-disease associations, including those from GWAS. To facilitate the re-use of implicit gene-disease associations, we publish our data in compliance with FAIR Data Publishing recommendations [https://www.force11.org/group/fairgroup] using nanopublications. An online tool (http://knowledge.bio) is available to explore established and potential gene-disease associations in the context of other biomedical relations. PMID:26919047

  11. The Implicitome: A Resource for Rationalizing Gene-Disease Associations.

    PubMed

    Hettne, Kristina M; Thompson, Mark; van Haagen, Herman H H B M; van der Horst, Eelke; Kaliyaperumal, Rajaram; Mina, Eleni; Tatum, Zuotian; Laros, Jeroen F J; van Mulligen, Erik M; Schuemie, Martijn; Aten, Emmelien; Li, Tong Shu; Bruskiewich, Richard; Good, Benjamin M; Su, Andrew I; Kors, Jan A; den Dunnen, Johan; van Ommen, Gert-Jan B; Roos, Marco; 't Hoen, Peter A C; Mons, Barend; Schultes, Erik A

    2016-01-01

    High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing biomedical knowledge for identification and interpretation of gene-disease associations. The implicitome can be used in conjunction with experimental data resources to rationalize both known and novel associations. We demonstrate the usefulness of the implicitome by rationalizing known and novel gene-disease associations, including those from GWAS. To facilitate the re-use of implicit gene-disease associations, we publish our data in compliance with FAIR Data Publishing recommendations [https://www.force11.org/group/fairgroup] using nanopublications. An online tool (http://knowledge.bio) is available to explore established and potential gene-disease associations in the context of other biomedical relations. PMID:26919047

  12. Pathway Analysis Incorporating Protein-Protein Interaction Networks Identified Candidate Pathways for the Seven Common Diseases.

    PubMed

    Lin, Peng-Lin; Yu, Ya-Wen; Chung, Ren-Hua

    2016-01-01

    Pathway analysis has become popular as a secondary analysis strategy for genome-wide association studies (GWAS). Most of the current pathway analysis methods aggregate signals from the main effects of single nucleotide polymorphisms (SNPs) in genes within a pathway without considering the effects of gene-gene interactions. However, gene-gene interactions can also have critical effects on complex diseases. Protein-protein interaction (PPI) networks have been used to define gene pairs for the gene-gene interaction tests. Incorporating the PPI information to define gene pairs for interaction tests within pathways can increase the power for pathway-based association tests. We propose a pathway association test, which aggregates the interaction signals in PPI networks within a pathway, for GWAS with case-control samples. Gene size is properly considered in the test so that genes do not contribute more to the test statistic simply due to their size. Simulation studies were performed to verify that the method is a valid test and can have more power than other pathway association tests in the presence of gene-gene interactions within a pathway under different scenarios. We applied the test to the Wellcome Trust Case Control Consortium GWAS datasets for seven common diseases. The most significant pathway is the chaperones modulate interferon signaling pathway for Crohn's disease (p-value = 0.0003). The pathway modulates interferon gamma, which induces the JAK/STAT pathway that is involved in Crohn's disease. Several other pathways that have functional implications for the seven diseases were also identified. The proposed test based on gene-gene interaction signals in PPI networks can be used as a complementary tool to the current existing pathway analysis methods focusing on main effects of genes. An efficient software implementing the method is freely available at http://puppi.sourceforge.net. PMID:27622767

  13. [Gene therapy in lysosomal diseases].

    PubMed

    Moullier, P; Salvetti, A; Bohl, D; Danos, O; Heard, J M

    1996-01-01

    The study of the mechanisms of secretion and recapture of lysosomal enzymes has lead to the proposal of a treatment of lysosomal diseases by enzyme replacement. Autologous implants of genetically modified cells which secrete enzymes ensure systemic distribution of the lacking enzyme. A procedure which permits reimplantation of genetically modified fibroblasts is described. The stable secretion of human glucuronidase by autologous fibroblasts was thus obtained in animal species. This approach should by applicable to the treatment of Hurler's syndrome by obtaining the production and distribution of alpha-L-iduronidase in patients lacking this enzyme by retroviral transfer of the human alpha-L-iduronidase gene to cultured fibroblasts and by preparation of implants. PMID:8881268

  14. Deletions of recessive disease genes: CNV contribution to carrier states and disease-causing alleles

    PubMed Central

    Boone, Philip M.; Campbell, Ian M.; Baggett, Brett C.; Soens, Zachry T.; Rao, Mitchell M.; Hixson, Patricia M.; Patel, Ankita; Bi, Weimin; Cheung, Sau Wai; Lalani, Seema R.; Beaudet, Arthur L.; Stankiewicz, Pawel; Shaw, Chad A.; Lupski, James R.

    2013-01-01

    Over 1200 recessive disease genes have been described in humans. The prevalence, allelic architecture, and per-genome load of pathogenic alleles in these genes remain to be fully elucidated, as does the contribution of DNA copy-number variants (CNVs) to carrier status and recessive disease. We mined CNV data from 21,470 individuals obtained by array-comparative genomic hybridization in a clinical diagnostic setting to identify deletions encompassing or disrupting recessive disease genes. We identified 3212 heterozygous potential carrier deletions affecting 419 unique recessive disease genes. Deletion frequency of these genes ranged from one occurrence to 1.5%. When compared with recessive disease genes never deleted in our cohort, the 419 recessive disease genes affected by at least one carrier deletion were longer and located farther from known dominant disease genes, suggesting that the formation and/or prevalence of carrier CNVs may be affected by both local and adjacent genomic features and by selection. Some subjects had multiple carrier CNVs (307 subjects) and/or carrier deletions encompassing more than one recessive disease gene (206 deletions). Heterozygous deletions spanning multiple recessive disease genes may confer carrier status for multiple single-gene disorders, for complex syndromes resulting from the combination of two or more recessive conditions, or may potentially cause clinical phenotypes due to a multiply heterozygous state. In addition to carrier mutations, we identified homozygous and hemizygous deletions potentially causative for recessive disease. We provide further evidence that CNVs contribute to the allelic architecture of both carrier and recessive disease-causing mutations. Thus, a complete recessive carrier screening method or diagnostic test should detect CNV alleles. PMID:23685542

  15. Disease Risk Factors Identified through Shared Genetic Architecture and Electronic Medical Records

    PubMed Central

    Li, Li; Ruau, David J.; Patel, Chirag J.; Weber, Susan C.; Chen, Rong; Tatonetti, Nicholas P.; Dudley, Joel T.; Butte, Atul J.

    2015-01-01

    Genome-Wide Association Studies (GWAS) have identified genetic variants for thousands of diseases and traits. In this study, we evaluated the relationships between specific risk factors (for example, blood cholesterol level) and diseases on the basis of their shared genetic architecture in a comprehensive human disease-SNP association database (VARIMED), analyzing the findings from 8,962 published association studies. Similarity between traits and diseases was statistically evaluated based on their association with shared gene variants. We identified 120 disease-trait pairs that were statistically similar, and of these we tested and validated five previously unknown disease-trait associations by searching electronic medical records (EMR) from 3 independent medical centers for evidence of the trait appearing in patients within one year of first diagnosis of the disease. We validated that mean corpuscular volume is elevated before diagnosis of acute lymphoblastic leukemia; both have associated variants in the gene IKZF1. Platelet count is decreased before diagnosis of alcohol dependence; both are associated with variants in the gene C12orf51. Alkaline phosphatase level is elevated in patients with venous thromboembolism; both share variants in ABO. Similarly, we found prostate specific antigen and serum magnesium levels were altered before the diagnosis of lung cancer and gastric cancer, respectively. Disease-trait associations identifies traits that can potentially serve a prognostic function clinically; validating disease-trait associations through EMR can whether these candidates are risk factors for complex diseases. PMID:24786325

  16. Gene Regulatory Networks Elucidating Huanglongbing Disease Mechanisms

    PubMed Central

    Martinelli, Federico; Reagan, Russell L.; Uratsu, Sandra L.; Phu, My L.; Albrecht, Ute; Zhao, Weixiang; Davis, Cristina E.; Bowman, Kim D.; Dandekar, Abhaya M.

    2013-01-01

    Next-generation sequencing was exploited to gain deeper insight into the response to infection by Candidatus liberibacter asiaticus (CaLas), especially the immune disregulation and metabolic dysfunction caused by source-sink disruption. Previous fruit transcriptome data were compared with additional RNA-Seq data in three tissues: immature fruit, and young and mature leaves. Four categories of orchard trees were studied: symptomatic, asymptomatic, apparently healthy, and healthy. Principal component analysis found distinct expression patterns between immature and mature fruits and leaf samples for all four categories of trees. A predicted protein – protein interaction network identified HLB-regulated genes for sugar transporters playing key roles in the overall plant responses. Gene set and pathway enrichment analyses highlight the role of sucrose and starch metabolism in disease symptom development in all tissues. HLB-regulated genes (glucose-phosphate-transporter, invertase, starch-related genes) would likely determine the source-sink relationship disruption. In infected leaves, transcriptomic changes were observed for light reactions genes (downregulation), sucrose metabolism (upregulation), and starch biosynthesis (upregulation). In parallel, symptomatic fruits over-expressed genes involved in photosynthesis, sucrose and raffinose metabolism, and downregulated starch biosynthesis. We visualized gene networks between tissues inducing a source-sink shift. CaLas alters the hormone crosstalk, resulting in weak and ineffective tissue-specific plant immune responses necessary for bacterial clearance. Accordingly, expression of WRKYs (including WRKY70) was higher in fruits than in leaves. Systemic acquired responses were inadequately activated in young leaves, generally considered the sites where most new infections occur. PMID:24086326

  17. Candidate DNA repair susceptibility genes identified by exome sequencing in high-risk pancreatic cancer.

    PubMed

    Smith, Alyssa L; Alirezaie, Najmeh; Connor, Ashton; Chan-Seng-Yue, Michelle; Grant, Robert; Selander, Iris; Bascuñana, Claire; Borgida, Ayelet; Hall, Anita; Whelan, Thomas; Holter, Spring; McPherson, Treasa; Cleary, Sean; Petersen, Gloria M; Omeroglu, Atilla; Saloustros, Emmanouil; McPherson, John; Stein, Lincoln D; Foulkes, William D; Majewski, Jacek; Gallinger, Steven; Zogopoulos, George

    2016-01-28

    The genetic basis underlying the majority of hereditary pancreatic adenocarcinoma (PC) is unknown. Since DNA repair genes are widely implicated in gastrointestinal malignancies, including PC, we hypothesized that there are novel DNA repair PC susceptibility genes. As germline DNA repair gene mutations may lead to PC subtypes with selective therapeutic responses, we also hypothesized that there is an overall survival (OS) difference in mutation carriers versus non-carriers. We therefore interrogated the germline exomes of 109 high-risk PC cases for rare protein-truncating variants (PTVs) in 513 putative DNA repair genes. We identified PTVs in 41 novel genes among 36 kindred. Additional genetic evidence for causality was obtained for 17 genes, with FAN1, NEK1 and RHNO1 emerging as the strongest candidates. An OS difference was observed for carriers versus non-carriers of PTVs with early stage (≤IIB) disease. This adverse survival trend in carriers with early stage disease was also observed in an independent series of 130 PC cases. We identified candidate DNA repair PC susceptibility genes and suggest that carriers of a germline PTV in a DNA repair gene with early stage disease have worse survival. PMID:26546047

  18. Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype.

    PubMed

    Kanth, Priyanka; Bronner, Mary P; Boucher, Kenneth M; Burt, Randall W; Neklason, Deborah W; Hagedorn, Curt H; Delker, Don A

    2016-06-01

    Sessile serrated colon adenoma/polyps (SSA/P) are found during routine screening colonoscopy and may account for 20% to 30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. In addition, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing (RNA-Seq) was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon, and 20 control colon specimens. Differential expression and leave-one-out cross-validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1,422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n = 12) and sporadic SSA/Ps (n = 9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability. A smaller 7-gene panel showed high sensitivity and specificity in identifying BRAF-mutant, CpG island methylator phenotype high, and MLH1-silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. Cancer Prev Res; 9(6); 456-65. ©2016 AACR. PMID:27026680

  19. CNL Disease Resistance Genes in Soybean and Their Evolutionary Divergence

    PubMed Central

    Nepal, Madhav P; Benson, Benjamin V

    2015-01-01

    Disease resistance genes (R-genes) encode proteins involved in detecting pathogen attack and activating downstream defense molecules. Recent availability of soybean genome sequences makes it possible to examine the diversity of gene families including disease-resistant genes. The objectives of this study were to identify coiled-coil NBS-LRR (= CNL) R-genes in soybean, infer their evolutionary relationships, and assess structural as well as functional divergence of the R-genes. Profile hidden Markov models were used for sequence identification and model-based maximum likelihood was used for phylogenetic analysis, and variation in chromosomal positioning, gene clustering, and functional divergence were assessed. We identified 188 soybean CNL genes nested into four clades consistent to their orthologs in Arabidopsis. Gene clustering analysis revealed the presence of 41 gene clusters located on 13 different chromosomes. Analyses of the Ks-values and chromosomal positioning suggest duplication events occurring at varying timescales, and an extrapericentromeric positioning may have facilitated their rapid evolution. Each of the four CNL clades exhibited distinct patterns of gene expression. Phylogenetic analysis further supported the extrapericentromeric positioning effect on the divergence and retention of the CNL genes. The results are important for understanding the diversity and divergence of CNL genes in soybean, which would have implication in soybean crop improvement in future. PMID:25922568

  20. Gene-Environment Interactions in Human Disease: Nuisance or Opportunity?

    PubMed Central

    Ober, Carole; Vercelli, Donata

    2010-01-01

    Many environmental risk factors for common, complex human diseases have been revealed by epidemiologic studies, but how genotypes at specific loci modulate individual responses to environmental risk factors is largely unknown. Gene-environment interactions will be missed in genome-wide association studies and may account for some of the ‘missing heritability’ for these diseases. In this review, we focus on asthma as a model disease for studying gene-environment interactions because of relatively large numbers of candidate gene-environment interactions with asthma risk in the literature. Identifying these interactions using genome-wide approaches poses formidable methodological problems and elucidating molecular mechanisms for these interactions has been challenging. We suggest that studying gene-environment interactions in animal models, while more tractable, is not likely to shed light on the genetic architecture of human diseases. Lastly, we propose avenues for future studies to find gene-environment interactions. PMID:21216485

  1. Finding Genetic Overlaps Among Diseases Based on Ranked Gene Lists

    PubMed Central

    Chen, Quan; Zhou, Xianghong J.

    2015-01-01

    Abstract To understand disease relationships in terms of their genetic mechanisms, it is important to study the common genetic basis among different diseases. Although discoveries on pleiotropic genes related to multiple diseases abound, methods flexibly applicable to various types of datasets generated from different studies or experiments are needed to gain big pictures on the genetic relationships among a large number of diseases. We develop a set of genetic similarity measures to gauge the genetic overlap between diseases, as well as several estimators of the number of overlapping disease genes between diseases. These methods are based on ranked gene lists so that they could be flexibly applied to different types of data. We first investigate the performance of the genetic similarity measure for evaluating the similarity between human diseases in simulation studies. Then we apply the method to diseases in the OMIM database. We show that our proposed genetic measure achieves superior performance in explaining phenotype similarities between diseases compared to simpler methods. Furthermore, we identified common genes underlying the genetic overlap between disease pairs. With an example of five vision-related diseases, we demonstrate how our methods can provide insights into the relationships among diseases based on their shared genetic mechanisms. PMID:25684200

  2. Integrating Diverse Types of Genomic Data to Identify Genes that Underlie Adverse Pregnancy Phenotypes

    PubMed Central

    Hirbo, Jibril; Eidem, Haley; Rokas, Antonis; Abbot, Patrick

    2015-01-01

    Progress in understanding complex genetic diseases has been bolstered by synthetic approaches that overlay diverse data types and analyses to identify functionally important genes. Pre-term birth (PTB), a major complication of pregnancy, is a leading cause of infant mortality worldwide. A major obstacle in addressing PTB is that the mechanisms controlling parturition and birth timing remain poorly understood. Integrative approaches that overlay datasets derived from comparative genomics with function-derived ones have potential to advance our understanding of the genetics of birth timing, and thus provide insights into the genes that may contribute to PTB. We intersected data from fast evolving coding and non-coding gene regions in the human and primate lineage with data from genes expressed in the placenta, from genes that show enriched expression only in the placenta, as well as from genes that are differentially expressed in four distinct PTB clinical subtypes. A large fraction of genes that are expressed in placenta, and differentially expressed in PTB clinical subtypes (23–34%) are fast evolving, and are associated with functions that include adhesion neurodevelopmental and immune processes. Functional categories of genes that express fast evolution in coding regions differ from those linked to fast evolution in non-coding regions. Finally, there is a surprising lack of overlap between fast evolving genes that are differentially expressed in four PTB clinical subtypes. Integrative approaches, especially those that incorporate evolutionary perspectives, can be successful in identifying potential genetic contributions to complex genetic diseases, such as PTB. PMID:26641094

  3. Large-Scale Discovery of Disease-Disease and Disease-Gene Associations

    PubMed Central

    Gligorijevic, Djordje; Stojanovic, Jelena; Djuric, Nemanja; Radosavljevic, Vladan; Grbovic, Mihajlo; Kulathinal, Rob J.; Obradovic, Zoran

    2016-01-01

    Data-driven phenotype analyses on Electronic Health Record (EHR) data have recently drawn benefits across many areas of clinical practice, uncovering new links in the medical sciences that can potentially affect the well-being of millions of patients. In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients). A novel embedding model is designed to extract knowledge from disease comorbidities by learning from a large-scale EHR database comprising more than 35 million inpatient cases spanning nearly a decade, revealing significant improvements on disease phenotyping over current computational approaches. In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies. To evaluate our approach, its effectiveness is compared against a held-out set where, again, it revealed very compelling results. For selected diseases, we further identify candidate gene lists for which disease-gene associations were not studied previously. Thus, our approach provides biomedical researchers with new tools to filter genes of interest, thus, reducing costly lab studies. PMID:27578529

  4. Large-Scale Discovery of Disease-Disease and Disease-Gene Associations.

    PubMed

    Gligorijevic, Djordje; Stojanovic, Jelena; Djuric, Nemanja; Radosavljevic, Vladan; Grbovic, Mihajlo; Kulathinal, Rob J; Obradovic, Zoran

    2016-01-01

    Data-driven phenotype analyses on Electronic Health Record (EHR) data have recently drawn benefits across many areas of clinical practice, uncovering new links in the medical sciences that can potentially affect the well-being of millions of patients. In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients). A novel embedding model is designed to extract knowledge from disease comorbidities by learning from a large-scale EHR database comprising more than 35 million inpatient cases spanning nearly a decade, revealing significant improvements on disease phenotyping over current computational approaches. In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies. To evaluate our approach, its effectiveness is compared against a held-out set where, again, it revealed very compelling results. For selected diseases, we further identify candidate gene lists for which disease-gene associations were not studied previously. Thus, our approach provides biomedical researchers with new tools to filter genes of interest, thus, reducing costly lab studies. PMID:27578529

  5. GENE EXPRESSION PROFILING TO IDENTIFY MECHANISMS OF MALE REPRODUCTIVE TOXICITY

    EPA Science Inventory

    Gene Expression Profiling to Identify Mechanisms of Male Reproductive Toxicity
    David J. Dix
    National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA.
    Ab...

  6. Brain-specific genes have identifier sequences in their introns.

    PubMed Central

    Milner, R J; Bloom, F E; Lai, C; Lerner, R A; Sutcliffe, J G

    1984-01-01

    The 82-nucleotide identifier (ID) sequence is present in the rat genome in 1-1.5 X 10(5) copies and in cDNA clones of precursors of brain-specific mRNAs. One brain-specific gene contains more than one ID sequence in its introns. There is an excess of ID sequences to brain genes, and some ID sequences appear to have been inserted as mobile elements into other genetic locations. Therefore, brain genes contain ID sequences in their introns, but not all ID sequences are located in brain gene introns. A brain ID consensus sequence has been obtained by comparing 8 ID nucleotide sequences. Images PMID:6583673

  7. Identifying lipid metabolism genes in pig liver after clenbuterol administration.

    PubMed

    Liu, Qiuyue; Zhang, Jin; Guo, Wei; Zhao, Yiqiang; Hu, Xiaoxiang; Li, Ning

    2012-01-01

    Clenbuterol is a repartition agent (beta 2-adrenoceptor agonist) that can decrease fat deposition and increase skeletal muscle growth at manageable dose. To better understand the molecular mechanism of Clenbuterol's action, GeneChips and real-time PCR were used to compare the gene expression profiles of liver tissue in pigs with/without administration of Clenbuterol. Metabolism effects and the global gene expression profiles of liver tissue from Clenbuterol-treated and untreated pigs were conducted. Function enrichment tests showed that the differentially expressed genes are enriched in glycoprotein protein, plasma membrane, fatty acid and amino acid metabolic process, and cell differentiation and signal transduction groups. Pathway mining analysis revealed that physiological pathways such as MAPK, cell adhesion molecules, and the insulin signaling pathway, were remarkably regulated when Clenbuterol was administered. Gene prioritization algorithm was used to associate a number of important differentially expressed genes with lipid metabolism in response to Clenbuterol. Genes identified as differentially expressed in this study will be candidates for further investigation of the molecular mechanisms involved in Clenbuterol's effects on adipose and skeletal muscle tissue. PMID:22652664

  8. Common Marker Genes Identified from Various Sample Types for Systemic Lupus Erythematosus

    PubMed Central

    Wang, Lan; Zhang, Yong-Hong; Lei, Shu-Feng; Deng, Fei-Yan

    2016-01-01

    Objective Systemic lupus erythematosus (SLE) is a complex auto-immune disease. Gene expression studies have been conducted to identify SLE-related genes in various types of samples. It is unknown whether there are common marker genes significant for SLE but independent of sample types, which may have potentials for follow-up translational research. The aim of this study is to identify common marker genes across various sample types for SLE. Methods Based on four public microarray gene expression datasets for SLE covering three representative types of blood-born samples (monocyte; peripheral blood mononuclear cell, PBMC; whole blood), we utilized three statistics (fold-change, FC; t-test p value; false discovery rate adjusted p value) to scrutinize genes simultaneously regulated with SLE across various sample types. For common marker genes, we conducted the Gene Ontology enrichment analysis and Protein-Protein Interaction analysis to gain insights into their functions. Results We identified 10 common marker genes associated with SLE (IFI6, IFI27, IFI44L, OAS1, OAS2, EIF2AK2, PLSCR1, STAT1, RNASE2, and GSTO1). Significant up-regulation of IFI6, IFI27, and IFI44L with SLE was observed in all the studied sample types, though the FC was most striking in monocyte, compared with PBMC and whole blood (8.82–251.66 vs. 3.73–74.05 vs. 1.19–1.87). Eight of the above 10 genes, except RNASE2 and GSTO1, interact with each other and with known SLE susceptibility genes, participate in immune response, RNA and protein catabolism, and cell death. Conclusion Our data suggest that there exist common marker genes across various sample types for SLE. The 10 common marker genes, identified herein, deserve follow-up studies to dissert their potentials as diagnostic or therapeutic markers to predict SLE or treatment response. PMID:27257790

  9. A systematic screening to identify de novo mutations causing sporadic early-onset Parkinson's disease

    PubMed Central

    Kun-Rodrigues, Celia; Ganos, Christos; Guerreiro, Rita; Schneider, Susanne A.; Schulte, Claudia; Lesage, Suzanne; Darwent, Lee; Holmans, Peter; Singleton, Andrew; Bhatia, Kailash; Bras, Jose

    2015-01-01

    Despite the many advances in our understanding of the genetic basis of Mendelian forms of Parkinson's disease (PD), a large number of early-onset cases still remain to be explained. Many of these cases, present with a form of disease that is identical to that underlined by genetic causes, but do not have mutations in any of the currently known disease-causing genes. Here, we hypothesized that de novo mutations may account for a proportion of these early-onset, sporadic cases. We performed exome sequencing in full parent–child trios where the proband presents with typical PD to unequivocally identify de novo mutations. This approach allows us to test all genes in the genome in an unbiased manner. We have identified and confirmed 20 coding de novo mutations in 21 trios. We have used publicly available population genetic data to compare variant frequencies and our independent in-house dataset of exome sequencing in PD (with over 1200 cases) to identify additional variants in the same genes. Of the genes identified to carry de novo mutations, PTEN, VAPB and ASNA1 are supported by various sources of data to be involved in PD. We show that these genes are reported to be within a protein–protein interaction network with PD genes and that they contain additional rare, case-specific, mutations in our independent cohort of PD cases. Our results support the involvement of these three genes in PD and suggest that testing for de novo mutations in sporadic disease may aid in the identification of novel disease-causing genes. PMID:26362251

  10. A systematic screening to identify de novo mutations causing sporadic early-onset Parkinson's disease.

    PubMed

    Kun-Rodrigues, Celia; Ganos, Christos; Guerreiro, Rita; Schneider, Susanne A; Schulte, Claudia; Lesage, Suzanne; Darwent, Lee; Holmans, Peter; Singleton, Andrew; Bhatia, Kailash; Bras, Jose

    2015-12-01

    Despite the many advances in our understanding of the genetic basis of Mendelian forms of Parkinson's disease (PD), a large number of early-onset cases still remain to be explained. Many of these cases, present with a form of disease that is identical to that underlined by genetic causes, but do not have mutations in any of the currently known disease-causing genes. Here, we hypothesized that de novo mutations may account for a proportion of these early-onset, sporadic cases. We performed exome sequencing in full parent-child trios where the proband presents with typical PD to unequivocally identify de novo mutations. This approach allows us to test all genes in the genome in an unbiased manner. We have identified and confirmed 20 coding de novo mutations in 21 trios. We have used publicly available population genetic data to compare variant frequencies and our independent in-house dataset of exome sequencing in PD (with over 1200 cases) to identify additional variants in the same genes. Of the genes identified to carry de novo mutations, PTEN, VAPB and ASNA1 are supported by various sources of data to be involved in PD. We show that these genes are reported to be within a protein-protein interaction network with PD genes and that they contain additional rare, case-specific, mutations in our independent cohort of PD cases. Our results support the involvement of these three genes in PD and suggest that testing for de novo mutations in sporadic disease may aid in the identification of novel disease-causing genes. PMID:26362251

  11. 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns

    PubMed Central

    Hastie, Trevor; Tibshirani, Robert; Eisen, Michael B; Alizadeh, Ash; Levy, Ronald; Staudt, Louis; Chan, Wing C; Botstein, David; Brown, Patrick

    2000-01-01

    Background: Large gene expression studies, such as those conducted using DNA arrays, often provide millions of different pieces of data. To address the problem of analyzing such data, we describe a statistical method, which we have called 'gene shaving'. The method identifies subsets of genes with coherent expression patterns and large variation across conditions. Gene shaving differs from hierarchical clustering and other widely used methods for analyzing gene expression studies in that genes may belong to more than one cluster, and the clustering may be supervised by an outcome measure. The technique can be 'unsupervised', that is, the genes and samples are treated as unlabeled, or partially or fully supervised by using known properties of the genes or samples to assist in finding meaningful groupings. Results: We illustrate the use of the gene shaving method to analyze gene expression measurements made on samples from patients with diffuse large B-cell lymphoma. The method identifies a small cluster of genes whose expression is highly predictive of survival. Conclusions: The gene shaving method is a potentially useful tool for exploration of gene expression data and identification of interesting clusters of genes worth further investigation. PMID:11178228

  12. DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics

    PubMed Central

    2014-01-01

    Background De novo loss-of-function (dnLoF) mutations are found twofold more often in autism spectrum disorder (ASD) probands than their unaffected siblings. Multiple independent dnLoF mutations in the same gene implicate the gene in risk and hence provide a systematic, albeit arduous, path forward for ASD genetics. It is likely that using additional non-genetic data will enhance the ability to identify ASD genes. Methods To accelerate the search for ASD genes, we developed a novel algorithm, DAWN, to model two kinds of data: rare variations from exome sequencing and gene co-expression in the mid-fetal prefrontal and motor-somatosensory neocortex, a critical nexus for risk. The algorithm casts the ensemble data as a hidden Markov random field in which the graph structure is determined by gene co-expression and it combines these interrelationships with node-specific observations, namely gene identity, expression, genetic data and the estimated effect on risk. Results Using currently available genetic data and a specific developmental time period for gene co-expression, DAWN identified 127 genes that plausibly affect risk, and a set of likely ASD subnetworks. Validation experiments making use of published targeted resequencing results demonstrate its efficacy in reliably predicting ASD genes. DAWN also successfully predicts known ASD genes, not included in the genetic data used to create the model. Conclusions Validation studies demonstrate that DAWN is effective in predicting ASD genes and subnetworks by leveraging genetic and gene expression data. The findings reported here implicate neurite extension and neuronal arborization as risks for ASD. Using DAWN on emerging ASD sequence data and gene expression data from other brain regions and tissues would likely identify novel ASD genes. DAWN can also be used for other complex disorders to identify genes and subnetworks in those disorders. PMID:24602502

  13. Transposon tagging of disease resistance genes

    SciTech Connect

    Michelmore, R.W. . Dept. of Physics)

    1989-01-01

    We are developing a transposon mutagenesis system for lettuce to clone genes for resistance to the fungal pathogen, Bremia lactucae. Activity of heterologous transposons is being studied in transgenic plants. Southern analysis of T{sub 1} and T{sub 2} plants containing Tam3 from Antirrhinum provided ambiguous results. Multiple endonuclease digests indicated that transposition had occurred; however, in no plant were all endonuclease digests consistent with a simple excision event. Southern or PCR analysis of over 50 plans containing Ac from maize have also failed to reveal clear evidence of transposition; this is contrast to experiments by others with the same constructs who have observed high rates of Ac excision in other plant species. Nearly all of 65 T{sub 2} families containing Ac interrupting a chimeric streptomycin resistance gene (Courtesy J. Jones, Sainsbury Lab., UK) clearly segregated for streptomycin resistance. Southern analyses, however, showed no evidence of transposition, indicating restoration of a functional message by other mechanisms, possibly mRNA processing. Transgenic plants have also been generated containing CaMV 35S or hsp70 promoters fused to transposase coding sequences or a Ds element interrupting a chimeric GUS gene (Courtesy M. Lassner, UC Davis). F{sub 1} plants containing both constructs were analyzed for transposition. Only two plants containing both constructs were obtained from 48 progeny, far fewer than expected, and neither showed evidence of transposition in Southerns and GUS assays. We are currently constructing further chimeric transposase fusions. To test for the stability of the targeted disease resistance genes, 50,000 F{sub 1} plants heterozygous for three resistance genes were generated; no mutants have been identified in the 5000 so far screened.

  14. Microarray Analysis of Pneumococcal Gene Expression during Invasive Disease

    PubMed Central

    Orihuela, Carlos J.; Radin, Jana N.; Sublett, Jack E.; Gao, Geli; Kaushal, Deepak; Tuomanen, Elaine I.

    2004-01-01

    Streptococcus pneumoniae is a leading cause of invasive bacterial disease. This is the first study to examine the expression of S. pneumoniae genes in vivo by using whole-genome microarrays available from The Institute for Genomic Research. Total RNA was collected from pneumococci isolated from infected blood, infected cerebrospinal fluid, and bacteria attached to a pharyngeal epithelial cell line in vitro. Microarray analysis of pneumococcal genes expressed in these models identified body site-specific patterns of expression for virulence factors, transporters, transcription factors, translation-associated proteins, metabolism, and genes with unknown function. Contributions to virulence predicted for several unknown genes with enhanced expression in vivo were confirmed by insertion duplication mutagenesis and challenge of mice with the mutants. Finally, we cross-referenced our results with previous studies that used signature-tagged mutagenesis and differential fluorescence induction to identify genes that are potentially required by a broad range of pneumococcal strains for invasive disease. PMID:15385455

  15. Phage cluster relationships identified through single gene analysis

    PubMed Central

    2013-01-01

    Background Phylogenetic comparison of bacteriophages requires whole genome approaches such as dotplot analysis, genome pairwise maps, and gene content analysis. Currently mycobacteriophages, a highly studied phage group, are categorized into related clusters based on the comparative analysis of whole genome sequences. With the recent explosion of phage isolation, a simple method for phage cluster prediction would facilitate analysis of crude or complex samples without whole genome isolation and sequencing. The hypothesis of this study was that mycobacteriophage-cluster prediction is possible using comparison of a single, ubiquitous, semi-conserved gene. Tape Measure Protein (TMP) was selected to test the hypothesis because it is typically the longest gene in mycobacteriophage genomes and because regions within the TMP gene are conserved. Results A single gene, TMP, identified the known Mycobacteriophage clusters and subclusters using a Gepard dotplot comparison or a phylogenetic tree constructed from global alignment and maximum likelihood comparisons. Gepard analysis of 247 mycobacteriophage TMP sequences appropriately recovered 98.8% of the subcluster assignments that were made by whole-genome comparison. Subcluster-specific primers within TMP allow for PCR determination of the mycobacteriophage subcluster from DNA samples. Using the single-gene comparison approach for siphovirus coliphages, phage groupings by TMP comparison reflected relationships observed in a whole genome dotplot comparison and confirm the potential utility of this approach to another widely studied group of phages. Conclusions TMP sequence comparison and PCR results support the hypothesis that a single gene can be used for distinguishing phage cluster and subcluster assignments. TMP single-gene analysis can quickly and accurately aid in mycobacteriophage classification. PMID:23777341

  16. A Novel Approach for Identifying Causal Models of Complex Diseases from Family Data

    PubMed Central

    Park, Leeyoung; Kim, Ju H.

    2015-01-01

    Causal models including genetic factors are important for understanding the presentation mechanisms of complex diseases. Familial aggregation and segregation analyses based on polygenic threshold models have been the primary approach to fitting genetic models to the family data of complex diseases. In the current study, an advanced approach to obtaining appropriate causal models for complex diseases based on the sufficient component cause (SCC) model involving combinations of traditional genetics principles was proposed. The probabilities for the entire population, i.e., normal–normal, normal–disease, and disease–disease, were considered for each model for the appropriate handling of common complex diseases. The causal model in the current study included the genetic effects from single genes involving epistasis, complementary gene interactions, gene–environment interactions, and environmental effects. Bayesian inference using a Markov chain Monte Carlo algorithm (MCMC) was used to assess of the proportions of each component for a given population lifetime incidence. This approach is flexible, allowing both common and rare variants within a gene and across multiple genes. An application to schizophrenia data confirmed the complexity of the causal factors. An analysis of diabetes data demonstrated that environmental factors and gene–environment interactions are the main causal factors for type II diabetes. The proposed method is effective and useful for identifying causal models, which can accelerate the development of efficient strategies for identifying causal factors of complex diseases. PMID:25701286

  17. Integrative Approach to Pain Genetics Identifies Pain Sensitivity Loci across Diseases

    PubMed Central

    Ruau, David; Dudley, Joel T.; Chen, Rong; Phillips, Nicholas G.; Swan, Gary E.; Lazzeroni, Laura C.; Clark, J. David

    2012-01-01

    Identifying human genes relevant for the processing of pain requires difficult-to-conduct and expensive large-scale clinical trials. Here, we examine a novel integrative paradigm for data-driven discovery of pain gene candidates, taking advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories. First, thousands of diseases were ranked according to a disease-specific pain index (DSPI), derived from Medical Subject Heading (MESH) annotations in MEDLINE. Second, gene expression profiles of 121 of these human diseases were obtained from public sources. Third, genes with expression variation significantly correlated with DSPI across diseases were selected as candidate pain genes. Finally, selected candidate pain genes were genotyped in an independent human cohort and prospectively evaluated for significant association between variants and measures of pain sensitivity. The strongest signal was with rs4512126 (5q32, ABLIM3, P = 1.3×10−10) for the sensitivity to cold pressor pain in males, but not in females. Significant associations were also observed with rs12548828, rs7826700 and rs1075791 on 8q22.2 within NCALD (P = 1.7×10−4, 1.8×10−4, and 2.2×10−4 respectively). Our results demonstrate the utility of a novel paradigm that integrates publicly available disease-specific gene expression data with clinical data curated from MEDLINE to facilitate the discovery of pain-relevant genes. This data-derived list of pain gene candidates enables additional focused and efficient biological studies validating additional candidates. PMID:22685391

  18. Animal Models of GWAS-Identified Type 2 Diabetes Genes

    PubMed Central

    da Silva Xavier, Gabriela; Bellomo, Elisa A.; McGinty, James A.; French, Paul M.; Rutter, Guy A.

    2013-01-01

    More than 65 loci, encoding up to 500 different genes, have been implicated by genome-wide association studies (GWAS) as conferring an increased risk of developing type 2 diabetes (T2D). Whilst mouse models have in the past been central to understanding the mechanisms through which more penetrant risk genes for T2D, for example, those responsible for neonatal or maturity-onset diabetes of the young, only a few of those identified by GWAS, notably TCF7L2 and ZnT8/SLC30A8, have to date been examined in mouse models. We discuss here the animal models available for the latter genes and provide perspectives for future, higher throughput approaches towards efficiently mining the information provided by human genetics. PMID:23710470

  19. Disease-specific classification using deconvoluted whole blood gene expression

    PubMed Central

    Wang, Li; Oh, William K.; Zhu, Jun

    2016-01-01

    Blood-based biomarker assays have an advantage in being minimally invasive. Diagnostic and prognostic models built on peripheral blood gene expression have been reported for various types of disease. However, most of these studies focused on only one disease type, and failed to address whether the identified gene expression signature is disease-specific or more widely applicable across diseases. We conducted a meta-analysis of 46 whole blood gene expression datasets covering a wide range of diseases and physiological conditions. Our analysis uncovered a striking overlap of signature genes shared by multiple diseases, driven by an underlying common pattern of cell component change, specifically an increase in myeloid cells and decrease in lymphocytes. These observations reveal the necessity of building disease-specific classifiers that can distinguish different disease types as well as normal controls, and highlight the importance of cell component change in deriving blood gene expression based models. We developed a new strategy to develop blood-based disease-specific models by leveraging both cell component changes and cell molecular state changes, and demonstrate its superiority using independent datasets. PMID:27596246

  20. Disease-specific classification using deconvoluted whole blood gene expression.

    PubMed

    Wang, Li; Oh, William K; Zhu, Jun

    2016-01-01

    Blood-based biomarker assays have an advantage in being minimally invasive. Diagnostic and prognostic models built on peripheral blood gene expression have been reported for various types of disease. However, most of these studies focused on only one disease type, and failed to address whether the identified gene expression signature is disease-specific or more widely applicable across diseases. We conducted a meta-analysis of 46 whole blood gene expression datasets covering a wide range of diseases and physiological conditions. Our analysis uncovered a striking overlap of signature genes shared by multiple diseases, driven by an underlying common pattern of cell component change, specifically an increase in myeloid cells and decrease in lymphocytes. These observations reveal the necessity of building disease-specific classifiers that can distinguish different disease types as well as normal controls, and highlight the importance of cell component change in deriving blood gene expression based models. We developed a new strategy to develop blood-based disease-specific models by leveraging both cell component changes and cell molecular state changes, and demonstrate its superiority using independent datasets. PMID:27596246

  1. An Effective Method to Identify Shared Pathways and Common Factors among Neurodegenerative Diseases

    PubMed Central

    Li, Ping; Nie, Yaling; Yu, Jingkai

    2015-01-01

    Groups of distinct but related diseases often share common symptoms, which suggest likely overlaps in underlying pathogenic mechanisms. Identifying the shared pathways and common factors among those disorders can be expected to deepen our understanding for them and help designing new treatment strategies effected on those diseases. Neurodegeneration diseases, including Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD), were taken as a case study in this research. Reported susceptibility genes for AD, PD and HD were collected and human protein-protein interaction network (hPPIN) was used to identify biological pathways related to neurodegeneration. 81 KEGG pathways were found to be correlated with neurodegenerative disorders. 36 out of the 81 are human disease pathways, and the remaining ones are involved in miscellaneous human functional pathways. Cancers and infectious diseases are two major subclasses within the disease group. Apoptosis is one of the most significant functional pathways. Most of those pathways found here are actually consistent with prior knowledge of neurodegenerative diseases except two cell communication pathways: adherens and tight junctions. Gene expression analysis showed a high probability that the two pathways were related to neurodegenerative diseases. A combination of common susceptibility genes and hPPIN is an effective method to study shared pathways involved in a group of closely related disorders. Common modules, which might play a bridging role in linking neurodegenerative disorders and the enriched pathways, were identified by clustering analysis. The identified shared pathways and common modules can be expected to yield clues for effective target discovery efforts on neurodegeneration. PMID:26575483

  2. Sleeping Beauty Mouse Models Identify Candidate Genes Involved in Gliomagenesis

    PubMed Central

    Vyazunova, Irina; Maklakova, Vilena I.; Berman, Samuel; De, Ishani; Steffen, Megan D.; Hong, Won; Lincoln, Hayley; Morrissy, A. Sorana; Taylor, Michael D.; Akagi, Keiko; Brennan, Cameron W.; Rodriguez, Fausto J.; Collier, Lara S.

    2014-01-01

    Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP) compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma. PMID:25423036

  3. Methods for identifying an essential gene in a prokaryotic microorganism

    DOEpatents

    Shizuya, Hiroaki

    2006-01-31

    Methods are provided for the rapid identification of essential or conditionally essential DNA segments in any species of haploid cell (one copy chromosome per cell) that is capable of being transformed by artificial means and is capable of undergoing DNA recombination. This system offers an enhanced means of identifying essential function genes in diploid pathogens, such as gram-negative and gram-positive bacteria.

  4. Heterozygous screen in Saccharomyces cerevisiae identifies dosage-sensitive genes that affect chromosome stability.

    PubMed

    Strome, Erin D; Wu, Xiaowei; Kimmel, Marek; Plon, Sharon E

    2008-03-01

    Current techniques for identifying mutations that convey a small increased cancer risk or those that modify cancer risk in carriers of highly penetrant mutations are limited by the statistical power of epidemiologic studies, which require screening of large populations and candidate genes. To identify dosage-sensitive genes that mediate genomic stability, we performed a genomewide screen in Saccharomyces cerevisiae for heterozygous mutations that increase chromosome instability in a checkpoint-deficient diploid strain. We used two genome stability assays sensitive enough to detect the impact of heterozygous mutations and identified 172 heterozygous gene disruptions that affected chromosome fragment (CF) loss, 45% of which also conferred modest but statistically significant instability of endogenous chromosomes. Analysis of heterozygous deletion of 65 of these genes demonstrated that the majority increased genomic instability in both checkpoint-deficient and wild-type backgrounds. Strains heterozygous for COMA kinetochore complex genes were particularly unstable. Over 50% of the genes identified in this screen have putative human homologs, including CHEK2, ERCC4, and TOPBP1, which are already associated with inherited cancer susceptibility. These findings encourage the incorporation of this orthologous gene list into cancer epidemiology studies and suggest further analysis of heterozygous phenotypes in yeast as models of human disease resulting from haplo-insufficiency. PMID:18245329

  5. Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes

    PubMed Central

    Lieberman, Tami D.; Michel, Jean-Baptiste; Aingaran, Mythili; Potter-Bynoe, Gail; Roux, Damien; Davis, Michael R.; Skurnik, David; Leiby, Nicholas; LiPuma, John J.; Goldberg, Joanna B.; McAdam, Alexander J.; Priebe, Gregory P.; Kishony, Roy

    2011-01-01

    Bacterial pathogens evolve during the infection of their human hosts1-8, but separating adaptive and neutral mutations remains challenging9-11. Here, we identify bacterial genes under adaptive evolution by tracking recurrent patterns of mutations in the same pathogenic strain during the infection of multiple patients. We conducted a retrospective study of a Burkholderia dolosa outbreak among people with cystic fibrosis, sequencing the genomes of 112 isolates collected from 14 individuals over 16 years. We find that 17 bacterial genes acquired non-synonymous mutations in multiple individuals, which indicates parallel adaptive evolution. Mutations in these genes illuminate the genetic basis of important pathogenic phenotypes, including antibiotic resistance and bacterial membrane composition, and implicate oxygen-dependent gene regulation as paramount in lung infections. Several genes have not been previously implicated in pathogenesis, suggesting new therapeutic targets. The identification of parallel molecular evolution suggests key selection forces acting on pathogens within humans and can help predict and prepare for their future evolutionary course. PMID:22081229

  6. Gene expression endophenotypes: a novel approach for gene discovery in Alzheimer's disease.

    PubMed

    Ertekin-Taner, Nilüfer

    2011-01-01

    Uncovering the underlying genetic component of any disease is key to the understanding of its pathophysiology and may open new avenues for development of therapeutic strategies and biomarkers. In the past several years, there has been an explosion of genome-wide association studies (GWAS) resulting in the discovery of novel candidate genes conferring risk for complex diseases, including neurodegenerative diseases. Despite this success, there still remains a substantial genetic component for many complex traits and conditions that is unexplained by the GWAS findings. Additionally, in many cases, the mechanism of action of the newly discovered disease risk variants is not inherently obvious. Furthermore, a genetic region with multiple genes may be identified via GWAS, making it difficult to discern the true disease risk gene. Several alternative approaches are proposed to overcome these potential shortcomings of GWAS, including the use of quantitative, biologically relevant phenotypes. Gene expression levels represent an important class of endophenotypes. Genetic linkage and association studies that utilize gene expression levels as endophenotypes determined that the expression levels of many genes are under genetic influence. This led to the postulate that there may exist many genetic variants that confer disease risk via modifying gene expression levels. Results from the handful of genetic studies which assess gene expression level endophenotypes in conjunction with disease risk suggest that this combined phenotype approach may both increase the power for gene discovery and lead to an enhanced understanding of their mode of action. This review summarizes the evidence in support of gene expression levels as promising endophenotypes in the discovery and characterization of novel candidate genes for complex diseases, which may also represent a novel approach in the genetic studies of Alzheimer's and other neurodegenerative diseases. PMID:21569597

  7. Molecular markers for tolerance of European ash (Fraxinus excelsior) to dieback disease identified using Associative Transcriptomics.

    PubMed

    Harper, Andrea L; McKinney, Lea Vig; Nielsen, Lene Rostgaard; Havlickova, Lenka; Li, Yi; Trick, Martin; Fraser, Fiona; Wang, Lihong; Fellgett, Alison; Sollars, Elizabeth S A; Janacek, Sophie H; Downie, J Allan; Buggs, Richard J A; Kjær, Erik Dahl; Bancroft, Ian

    2016-01-01

    Tree disease epidemics are a global problem, impacting food security, biodiversity and national economies. The potential for conservation and breeding in trees is hampered by complex genomes and long lifecycles, with most species lacking genomic resources. The European Ash tree Fraxinus excelsior is being devastated by the fungal pathogen Hymenoscyphus fraxineus, which causes ash dieback disease. Taking this system as an example and utilizing Associative Transcriptomics for the first time in a plant pathology study, we discovered gene sequence and gene expression variants across a genetic diversity panel scored for disease symptoms and identified markers strongly associated with canopy damage in infected trees. Using these markers we predicted phenotypes in a test panel of unrelated trees, successfully identifying individuals with a low level of susceptibility to the disease. Co-expression analysis suggested that pre-priming of defence responses may underlie reduced susceptibility to ash dieback. PMID:26757823

  8. Molecular markers for tolerance of European ash (Fraxinus excelsior) to dieback disease identified using Associative Transcriptomics

    PubMed Central

    Harper, Andrea L.; McKinney, Lea Vig; Nielsen, Lene Rostgaard; Havlickova, Lenka; Li, Yi; Trick, Martin; Fraser, Fiona; Wang, Lihong; Fellgett, Alison; Sollars, Elizabeth S. A.; Janacek, Sophie H.; Downie, J. Allan; Buggs, Richard. J. A.; Kjær, Erik Dahl; Bancroft, Ian

    2016-01-01

    Tree disease epidemics are a global problem, impacting food security, biodiversity and national economies. The potential for conservation and breeding in trees is hampered by complex genomes and long lifecycles, with most species lacking genomic resources. The European Ash tree Fraxinus excelsior is being devastated by the fungal pathogen Hymenoscyphus fraxineus, which causes ash dieback disease. Taking this system as an example and utilizing Associative Transcriptomics for the first time in a plant pathology study, we discovered gene sequence and gene expression variants across a genetic diversity panel scored for disease symptoms and identified markers strongly associated with canopy damage in infected trees. Using these markers we predicted phenotypes in a test panel of unrelated trees, successfully identifying individuals with a low level of susceptibility to the disease. Co-expression analysis suggested that pre-priming of defence responses may underlie reduced susceptibility to ash dieback. PMID:26757823

  9. An extended set of yeast-based functional assays accurately identifies human disease mutations.

    PubMed

    Sun, Song; Yang, Fan; Tan, Guihong; Costanzo, Michael; Oughtred, Rose; Hirschman, Jodi; Theesfeld, Chandra L; Bansal, Pritpal; Sahni, Nidhi; Yi, Song; Yu, Analyn; Tyagi, Tanya; Tie, Cathy; Hill, David E; Vidal, Marc; Andrews, Brenda J; Boone, Charles; Dolinski, Kara; Roth, Frederick P

    2016-05-01

    We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods. PMID:26975778

  10. An extended set of yeast-based functional assays accurately identifies human disease mutations

    PubMed Central

    Sun, Song; Yang, Fan; Tan, Guihong; Costanzo, Michael; Oughtred, Rose; Hirschman, Jodi; Theesfeld, Chandra L.; Bansal, Pritpal; Sahni, Nidhi; Yi, Song; Yu, Analyn; Tyagi, Tanya; Tie, Cathy; Hill, David E.; Vidal, Marc; Andrews, Brenda J.; Boone, Charles; Dolinski, Kara; Roth, Frederick P.

    2016-01-01

    We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods. PMID:26975778

  11. AKAP2 identified as a novel gene mutated in a Chinese family with adolescent idiopathic scoliosis

    PubMed Central

    Li, Wei; Li, YaWei; Zhang, Lusi; Guo, Hui; Tian, Di; Li, Ying; Peng, Yu; Zheng, Yu; Dai, Yuliang; Xia, Kun; Lan, Xinqiang; Wang, Bing; Hu, Zhengmao

    2016-01-01

    Background Adolescent idiopathic scoliosis exhibits high heritability and is one of the most common spinal deformities found in adolescent populations. However, little is known about the disease-causing genes in families with adolescent idiopathic scoliosis exhibiting Mendelian inheritance. Objective The aim of this study was to identify the causative gene in a family with adolescent idiopathic scoliosis. Methods Whole-exome sequencing was performed on this family to identify the candidate gene. Sanger sequencing was conducted to validate the candidate mutations and familial segregation. Real-time QPCR was used to measure the expression level of the possible causative gene. Results We identified the mutation c.2645A>C (p.E882A) within the AKAP2 gene, which cosegregated with the adolescent idiopathic scoliosis phenotypes. AKAP2 is located in a previously reported linkage locus (IS4) on chromosome 9q31.2–q34.2 and has been implicated in skeletal development. The mutation was absent in dbSNP144, ESP6500 and 503 ethnicity-matched controls. Real-time QPCR revealed that the mRNA expression level in the patients was increased significantly compared with the family controls (p<0.0001). Conclusions AKAP2 was therefore implicated as a novel gene mutated in a Chinese family with adolescent idiopathic scoliosis. Further studies should be conducted to validate the results from the perspective of both the genetics and pathogenesis of this disease. PMID:26989089

  12. DDA: A Novel Network-Based Scoring Method to Identify Disease–Disease Associations

    PubMed Central

    Suratanee, Apichat; Plaimas, Kitiporn

    2015-01-01

    Categorizing human diseases provides higher efficiency and accuracy for disease diagnosis, prognosis, and treatment. Disease–disease association (DDA) is a precious information that indicates the large-scale structure of complex relationships of diseases. However, the number of known and reliable associations is very small. Therefore, identification of DDAs is a challenging task in systems biology and medicine. Here, we developed a novel network-based scoring algorithm called DDA to identify the relationships between diseases in a large-scale study. Our method is developed based on a random walk prioritization in a protein–protein interaction network. This approach considers not only whether two diseases directly share associated genes but also the statistical relationships between two different diseases using known disease-related genes. Predicted associations were validated by known DDAs from a database and literature supports. The method yielded a good performance with an area under the curve of 71% and outperformed other standard association indices. Furthermore, novel DDAs and relationships among diseases from the clusters analysis were reported. This method is efficient to identify disease–disease relationships on an interaction network and can also be generalized to other association studies to further enhance knowledge in medical studies. PMID:26673408

  13. Gene therapy for CNS diseases – Krabbe disease

    PubMed Central

    Rafi, Mohammad A.

    2016-01-01

    Summary This is a brief report of the 19th Annual Meeting of the American Society of Gene and Cell Therapy that took place from May 4th through May 7th, 2016 in Washington, DC, USA. While the meeting provided many symposiums, lectures, and scientific sessions this report mainly focuses on one of the sessions on the "Gene Therapy for central nervous system (CNS) Diseases" and specifically on the "Gene Therapy for the globoid cell leukodystrophy or Krabbe disease. Two presentations focused on this subject utilizing two animal models of this disease: mice and dog models. Different serotypes of adeno-associate viral vectors (AAV) alone or in combination with bone marrow transplantations were used in these research projects. The Meeting of the ASGCT reflected continuous growth in the fields of gene and cell therapy and brighter forecast for efficient treatment options for variety of human diseases. PMID:27525222

  14. Gene Therapy for Diseases and Genetic Disorders

    MedlinePlus

    ... notable advancements are the following: Gene Therapy for Genetic Disorders Severe Combined Immune Deficiency (ADA-SCID) ADA- ... in preclinical animal models of this disease. Other genetic disorders After many years of laboratory and preclinical ...

  15. Multiplexed Component Analysis to Identify Genes Contributing to the Immune Response during Acute SIV Infection

    PubMed Central

    Hosseini, Iraj; Gama, Lucio; Mac Gabhann, Feilim

    2015-01-01

    Immune response genes play an important role during acute HIV and SIV infection. Using an SIV macaque model of AIDS and CNS disease, our overall goal was to assess how the expression of genes associated with immune and inflammatory responses are longitudinally changed in different organs or cells during SIV infection. To compare RNA expression of a panel of 88 immune-related genes across time points and among three tissues – spleen, mesenteric lymph nodes (MLN) and peripheral blood mononuclear cells (PBMC) – we designed a set of Nanostring probes. To identify significant genes during acute SIV infection and to investigate whether these genes are tissue-specific or have global roles, we introduce a novel multiplexed component analysis (MCA) method. This combines multivariate analysis methods with multiple preprocessing methods to create a set of 12 “judges”; each judge emphasizes particular types of change in gene expression to which cells could respond, for example, the absolute or relative size of expression change from baseline. Compared to bivariate analysis methods, our MCA method improved classification rates. This analysis allows us to identify three categories of genes: (a) consensus genes likely to contribute highly to the immune response; (b) genes that would contribute highly to the immune response only if certain assumptions are met – e.g. that the cell responds to relative expression change rather than absolute expression change; and (c) genes whose contribution to immune response appears to be modest. We then compared the results across the three tissues of interest; some genes are consistently highly-contributing in all tissues, while others are specific for certain tissues. Our analysis identified CCL8, CXCL10, CXCL11, MxA, OAS2, and OAS1 as top contributing genes, all of which are stimulated by type I interferon. This suggests that the cytokine storm during acute SIV infection is a systemic innate immune response against viral replication

  16. Gene Conversion in Human Genetic Disease

    PubMed Central

    Chen, Jian-Min; Férec, Claude; Cooper, David N.

    2010-01-01

    Gene conversion is a specific type of homologous recombination that involves the unidirectional transfer of genetic material from a ‘donor’ sequence to a highly homologous ‘acceptor’. We have recently reviewed the molecular mechanisms underlying gene conversion, explored the key part that this process has played in fashioning extant human genes, and performed a meta-analysis of gene-conversion events known to have caused human genetic disease. Here we shall briefly summarize some of the latest developments in the study of pathogenic gene conversion events, including (i) the emerging idea of minimal efficient sequence homology (MESH) for homologous recombination, (ii) the local DNA sequence features that appear to predispose to gene conversion, (iii) a mechanistic comparison of gene conversion and transient hypermutability, and (iv) recently reported examples of pathogenic gene conversion events. PMID:24710102

  17. Isolated populations and complex disease gene identification

    PubMed Central

    Kristiansson, Kati; Naukkarinen, Jussi; Peltonen, Leena

    2008-01-01

    The utility of genetically isolated populations (population isolates) in the mapping and identification of genes is not only limited to the study of rare diseases; isolated populations also provide a useful resource for studies aimed at improved understanding of the biology underlying common diseases and their component traits. Well characterized human populations provide excellent study samples for many different genetic investigations, ranging from genome-wide association studies to the characterization of interactions between genes and the environment. PMID:18771588

  18. A recellularized human colon model identifies cancer driver genes.

    PubMed

    Chen, Huanhuan Joyce; Wei, Zhubo; Sun, Jian; Bhattacharya, Asmita; Savage, David J; Serda, Rita; Mackeyev, Yuri; Curley, Steven A; Bu, Pengcheng; Wang, Lihua; Chen, Shuibing; Cohen-Gould, Leona; Huang, Emina; Shen, Xiling; Lipkin, Steven M; Copeland, Neal G; Jenkins, Nancy A; Shuler, Michael L

    2016-08-01

    Refined cancer models are needed to bridge the gaps between cell line, animal and clinical research. Here we describe the engineering of an organotypic colon cancer model by recellularization of a native human matrix that contains cell-populated mucosa and an intact muscularis mucosa layer. This ex vivo system recapitulates the pathophysiological progression from APC-mutant neoplasia to submucosal invasive tumor. We used it to perform a Sleeping Beauty transposon mutagenesis screen to identify genes that cooperate with mutant APC in driving invasive neoplasia. We identified 38 candidate invasion-driver genes, 17 of which, including TCF7L2, TWIST2, MSH2, DCC, EPHB1 and EPHB2 have been previously implicated in colorectal cancer progression. Six invasion-driver genes that have not, to our knowledge, been previously described were validated in vitro using cell proliferation, migration and invasion assays and ex vivo using recellularized human colon. These results demonstrate the utility of our organoid model for studying cancer biology. PMID:27398792

  19. Identifying Francisella tularensis Genes Required for Growth in Host Cells

    PubMed Central

    Brunton, J.; Steele, S.; Miller, C.; Lovullo, E.; Taft-Benz, S.

    2015-01-01

    Francisella tularensis is a highly virulent Gram-negative intracellular pathogen capable of infecting a vast diversity of hosts, ranging from amoebae to humans. A hallmark of F. tularensis virulence is its ability to quickly grow to high densities within a diverse set of host cells, including, but not limited to, macrophages and epithelial cells. We developed a luminescence reporter system to facilitate a large-scale transposon mutagenesis screen to identify genes required for growth in macrophage and epithelial cell lines. We screened 7,454 individual mutants, 269 of which exhibited reduced intracellular growth. Transposon insertions in the 269 growth-defective strains mapped to 68 different genes. FTT_0924, a gene of unknown function but highly conserved among Francisella species, was identified in this screen to be defective for intracellular growth within both macrophage and epithelial cell lines. FTT_0924 was required for full Schu S4 virulence in a murine pulmonary infection model. The ΔFTT_0924 mutant bacterial membrane is permeable when replicating in hypotonic solution and within macrophages, resulting in strongly reduced viability. The permeability and reduced viability were rescued when the mutant was grown in a hypertonic solution, indicating that FTT_0924 is required for resisting osmotic stress. The ΔFTT_0924 mutant was also significantly more sensitive to β-lactam antibiotics than Schu S4. Taken together, the data strongly suggest that FTT_0924 is required for maintaining peptidoglycan integrity and virulence. PMID:25987704

  20. Linking Genes to Cardiovascular Diseases: Gene Action and Gene-Environment Interactions.

    PubMed

    Pasipoularides, Ares

    2015-12-01

    A unique myocardial characteristic is its ability to grow/remodel in order to adapt; this is determined partly by genes and partly by the environment and the milieu intérieur. In the "post-genomic" era, a need is emerging to elucidate the physiologic functions of myocardial genes, as well as potential adaptive and maladaptive modulations induced by environmental/epigenetic factors. Genome sequencing and analysis advances have become exponential lately, with escalation of our knowledge concerning sometimes controversial genetic underpinnings of cardiovascular diseases. Current technologies can identify candidate genes variously involved in diverse normal/abnormal morphomechanical phenotypes, and offer insights into multiple genetic factors implicated in complex cardiovascular syndromes. The expression profiles of thousands of genes are regularly ascertained under diverse conditions. Global analyses of gene expression levels are useful for cataloging genes and correlated phenotypes, and for elucidating the role of genes in maladies. Comparative expression of gene networks coupled to complex disorders can contribute insights as to how "modifier genes" influence the expressed phenotypes. Increasingly, a more comprehensive and detailed systematic understanding of genetic abnormalities underlying, for example, various genetic cardiomyopathies is emerging. Implementing genomic findings in cardiology practice may well lead directly to better diagnosing and therapeutics. There is currently evolving a strong appreciation for the value of studying gene anomalies, and doing so in a non-disjointed, cohesive manner. However, it is challenging for many-practitioners and investigators-to comprehend, interpret, and utilize the clinically increasingly accessible and affordable cardiovascular genomics studies. This survey addresses the need for fundamental understanding in this vital area. PMID:26545598

  1. Variability of Gene Expression Identifies Transcriptional Regulators of Early Human Embryonic Development

    PubMed Central

    Hasegawa, Yu; Taylor, Deanne; Ovchinnikov, Dmitry A.; Wolvetang, Ernst J.; de Torrenté, Laurence; Mar, Jessica C.

    2015-01-01

    An analysis of gene expression variability can provide an insightful window into how regulatory control is distributed across the transcriptome. In a single cell analysis, the inter-cellular variability of gene expression measures the consistency of transcript copy numbers observed between cells in the same population. Application of these ideas to the study of early human embryonic development may reveal important insights into the transcriptional programs controlling this process, based on which components are most tightly regulated. Using a published single cell RNA-seq data set of human embryos collected at four-cell, eight-cell, morula and blastocyst stages, we identified genes with the most stable, invariant expression across all four developmental stages. Stably-expressed genes were found to be enriched for those sharing indispensable features, including essentiality, haploinsufficiency, and ubiquitous expression. The stable genes were less likely to be associated with loss-of-function variant genes or human recessive disease genes affected by a DNA copy number variant deletion, suggesting that stable genes have a functional impact on the regulation of some of the basic cellular processes. Genes with low expression variability at early stages of development are involved in regulation of DNA methylation, responses to hypoxia and telomerase activity, whereas by the blastocyst stage, low-variability genes are enriched for metabolic processes as well as telomerase signaling. Based on changes in expression variability, we identified a putative set of gene expression markers of morulae and blastocyst stages. Experimental validation of a blastocyst-expressed variability marker demonstrated that HDDC2 plays a role in the maintenance of pluripotency in human ES and iPS cells. Collectively our analyses identified new regulators involved in human embryonic development that would have otherwise been missed using methods that focus on assessment of the average expression

  2. Refining analyses of copy number variation identifies specific genes associated with developmental delay.

    PubMed

    Coe, Bradley P; Witherspoon, Kali; Rosenfeld, Jill A; van Bon, Bregje W M; Vulto-van Silfhout, Anneke T; Bosco, Paolo; Friend, Kathryn L; Baker, Carl; Buono, Serafino; Vissers, Lisenka E L M; Schuurs-Hoeijmakers, Janneke H; Hoischen, Alex; Pfundt, Rolph; Krumm, Nik; Carvill, Gemma L; Li, Deana; Amaral, David; Brown, Natasha; Lockhart, Paul J; Scheffer, Ingrid E; Alberti, Antonino; Shaw, Marie; Pettinato, Rosa; Tervo, Raymond; de Leeuw, Nicole; Reijnders, Margot R F; Torchia, Beth S; Peeters, Hilde; O'Roak, Brian J; Fichera, Marco; Hehir-Kwa, Jayne Y; Shendure, Jay; Mefford, Heather C; Haan, Eric; Gécz, Jozef; de Vries, Bert B A; Romano, Corrado; Eichler, Evan E

    2014-10-01

    Copy number variants (CNVs) are associated with many neurocognitive disorders; however, these events are typically large, and the underlying causative genes are unclear. We created an expanded CNV morbidity map from 29,085 children with developmental delay in comparison to 19,584 healthy controls, identifying 70 significant CNVs. We resequenced 26 candidate genes in 4,716 additional cases with developmental delay or autism and 2,193 controls. An integrated analysis of CNV and single-nucleotide variant (SNV) data pinpointed 10 genes enriched for putative loss of function. Follow-up of a subset of affected individuals identified new clinical subtypes of pediatric disease and the genes responsible for disease-associated CNVs. These genetic changes include haploinsufficiency of SETBP1 associated with intellectual disability and loss of expressive language and truncations of ZMYND11 in individuals with autism, aggression and complex neuropsychiatric features. This combined CNV and SNV approach facilitates the rapid discovery of new syndromes and genes involved in neuropsychiatric disease despite extensive genetic heterogeneity. PMID:25217958

  3. Identifying the genes regulated by IDH1 via gene-chip in glioma cell U87

    PubMed Central

    Ren, Jie; Lou, Meiqing; Shi, Jinlong; Xue, Yajun; Cui, Daming

    2015-01-01

    Glioma is the most common form of primary brain tumor. Increasing evidence show that IDH1 gene mutation is implicated in glioma. However, the mechanism involved in the progression of glioma remains unclear until now. In the study reported here, we used gene chip to identifying the genes regulated with IDH mutanted at R132. The results showed that IDH1-mutant leads to 1255 up-regulated genes and 1862 down-regulated genes in U87 cell lines. Meanwhile, GO and gene-network was performed and shown IDH1-mutant mainly affect small molecule metabolic process, mitotic cell cycle and apoptosis. This result will lay a foundation for further study of IDH1 gene function in the future. PMID:26770405

  4. Screening for noise in gene expression identifies drug synergies.

    PubMed

    Dar, Roy D; Hosmane, Nina N; Arkin, Michelle R; Siliciano, Robert F; Weinberger, Leor S

    2014-06-20

    Stochastic fluctuations are inherent to gene expression and can drive cell-fate specification. We used such fluctuations to modulate reactivation of HIV from latency-a quiescent state that is a major barrier to an HIV cure. By screening a diverse library of bioactive small molecules, we identified more than 80 compounds that modulated HIV gene-expression fluctuations (i.e., "noise"), without changing mean expression. These noise-modulating compounds would be neglected in conventional screens, and yet, they synergized with conventional transcriptional activators. Noise enhancers reactivated latent cells significantly better than existing best-in-class reactivation drug combinations (and with reduced off-target cytotoxicity), whereas noise suppressors stabilized latency. Noise-modulating chemicals may provide novel probes for the physiological consequences of noise and an unexplored axis for drug discovery, allowing enhanced control over diverse cell-fate decisions. PMID:24903562

  5. Identifying genes that mediate anthracyline toxicity in immune cells

    PubMed Central

    Frick, Amber; Suzuki, Oscar T.; Benton, Cristina; Parks, Bethany; Fedoriw, Yuri; Richards, Kristy L.; Thomas, Russell S.; Wiltshire, Tim

    2015-01-01

    The role of the immune system in response to chemotherapeutic agents remains elusive. The interpatient variability observed in immune and chemotherapeutic cytotoxic responses is likely, at least in part, due to complex genetic differences. Through the use of a panel of genetically diverse mouse inbred strains, we developed a drug screening platform aimed at identifying genes underlying these chemotherapeutic cytotoxic effects on immune cells. Using genome-wide association studies (GWAS), we identified four genome-wide significant quantitative trait loci (QTL) that contributed to the sensitivity of doxorubicin and idarubicin in immune cells. Of particular interest, a locus on chromosome 16 was significantly associated with cell viability following idarubicin administration (p = 5.01 × 10−8). Within this QTL lies App, which encodes amyloid beta precursor protein. Comparison of dose-response curves verified that T-cells in App knockout mice were more sensitive to idarubicin than those of C57BL/6J control mice (p < 0.05). In conclusion, the cellular screening approach coupled with GWAS led to the identification and subsequent validation of a gene involved in T-cell viability after idarubicin treatment. Previous studies have suggested a role for App in in vitro and in vivo cytotoxicity to anticancer agents; the overexpression of App enhances resistance, while the knockdown of this gene is deleterious to cell viability. Further investigations should include performing mechanistic studies, validating additional genes from the GWAS, including Ppfia1 and Ppfibp1, and ultimately translating the findings to in vivo and human studies. PMID:25926793

  6. New Viruses Identified in Fig Trees Exhibiting Fig Mosaic Disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fig mosaic disease has been known for decades, but the causal agent has been elusive. Here we present data on the incidence of at least four new viruses isolated from fig trees exhibiting mosaic symptoms. One of the viruses is closely related to the recently identified European mountain ash ringspo...

  7. Enrichment Analysis Identifies Functional MicroRNA-Disease Associations in Humans

    PubMed Central

    Yuan, Dandan; Cui, Xiaomeng; Wang, Yang; Zhao, Yilei; Li, Huiying; Hu, Suangjiu; Chu, Xiaodan; Li, Yan; Li, Qiang; Liu, Qian; Zhu, Wenliang

    2015-01-01

    Substantial evidence has shown that microRNAs (miRNAs) may be causally linked to the occurrence and progression of human diseases. Herein, we conducted an enrichment analysis to identify potential functional miRNA-disease associations (MDAs) in humans by integrating currently known biological data: miRNA-target interactions (MTIs), protein-protein interactions, and gene-disease associations. Two contributing factors to functional miRNA-disease associations were quantitatively considered: the direct effects of miRNA that target disease-related genes, and indirect effects triggered by protein-protein interactions. Ninety-nine miRNAs were scanned for possible functional association with 2223 MeSH-defined human diseases. Each miRNA was experimentally validated to target ≥ 10 mRNA genes. Putative MDAs were identified when at least one MTI was confidently validated for a disease. Overall, 19648 putative MDAs were found, of which 10.0% was experimentally validated. Further results suggest that filtering for miRNAs that target a greater number of disease-related genes (n ≥ 8) can significantly enrich for true MDAs from the set of putative associations (enrichment rate = 60.7%, adjusted hypergeometric p = 2.41×10−91). Considering the indirect effects of miRNAs further elevated the enrichment rate to 72.6%. By using this method, a novel MDA between miR-24 and ovarian cancer was found. Compared with scramble miRNA overexpression of miR-24 was validated to remarkably induce ovarian cancer cells apoptosis. Our study provides novel insight into factors contributing to functional MDAs by integrating large quantities of previously generated biological data, and establishes a feasible method to identify plausible associations with high confidence. PMID:26296081

  8. Enrichment Analysis Identifies Functional MicroRNA-Disease Associations in Humans.

    PubMed

    Yuan, Dandan; Cui, Xiaomeng; Wang, Yang; Zhao, Yilei; Li, Huiying; Hu, Suangjiu; Chu, Xiaodan; Li, Yan; Li, Qiang; Liu, Qian; Zhu, Wenliang

    2015-01-01

    Substantial evidence has shown that microRNAs (miRNAs) may be causally linked to the occurrence and progression of human diseases. Herein, we conducted an enrichment analysis to identify potential functional miRNA-disease associations (MDAs) in humans by integrating currently known biological data: miRNA-target interactions (MTIs), protein-protein interactions, and gene-disease associations. Two contributing factors to functional miRNA-disease associations were quantitatively considered: the direct effects of miRNA that target disease-related genes, and indirect effects triggered by protein-protein interactions. Ninety-nine miRNAs were scanned for possible functional association with 2223 MeSH-defined human diseases. Each miRNA was experimentally validated to target ≥ 10 mRNA genes. Putative MDAs were identified when at least one MTI was confidently validated for a disease. Overall, 19648 putative MDAs were found, of which 10.0% was experimentally validated. Further results suggest that filtering for miRNAs that target a greater number of disease-related genes (n ≥ 8) can significantly enrich for true MDAs from the set of putative associations (enrichment rate = 60.7%, adjusted hypergeometric p = 2.41×10-91). Considering the indirect effects of miRNAs further elevated the enrichment rate to 72.6%. By using this method, a novel MDA between miR-24 and ovarian cancer was found. Compared with scramble miRNA overexpression of miR-24 was validated to remarkably induce ovarian cancer cells apoptosis. Our study provides novel insight into factors contributing to functional MDAs by integrating large quantities of previously generated biological data, and establishes a feasible method to identify plausible associations with high confidence. PMID:26296081

  9. Patient Identified Disease Burden in Facioscapulohumeral Muscular Dystrophy

    PubMed Central

    Johnson, Nicholas E; Quinn, Christine; Eastwood, Eileen; Tawil, Rabi; Heatwole, Chad R

    2013-01-01

    Introduction The multitude of symptoms associated with facioscapulohumeral muscular dystrophy (FSHD) disease burden are of varying importance. The extent of these symptoms and their cumulative effect on the FSHD population is unknown. Methods We conducted interviews with adult FSHD patients to identify which symptoms have the greatest effect on their lives. Each interview was recorded, transcribed, coded, and analyzed using a qualitative framework technique, triangulation, and 3-investigator consensus approach. Results 1375 quotes were obtained through 20 patient interviews. 251 symptoms of importance were identified representing 14 themes of FSHD disease burden. Symptoms associated with mobility impairment, activity limitation, and social role limitation were most frequently mentioned by participants. Conclusions There are multiple themes and symptoms, some previously under-recognized, that play a key role in FSHD disease burden. PMID:23225386

  10. Gene Therapy For Ischemic Heart Disease

    PubMed Central

    Lavu, Madhav; Gundewar, Susheel; Lefer, David J.

    2010-01-01

    Current pharmacologic therapy for ischemic heart disease suffers multiple limitations such as compliance issues and side effects of medications. Revascularization procedures often end with need for repeat procedures. Patients remain symptomatic despite maximal medical therapy. Gene therapy offers an attractive alternative to current pharmacologic therapies and may be beneficial in refractory disease. Gene therapy with isoforms of growth factors such as VEGF, FGF and HGF induces angiogenesis, decreases apoptosis and leads to protection in the ischemic heart. Stem cell therapy augmented with gene therapy used for myogenesis has proven to be beneficial in numerous animal models of myocardial ischemia. Gene therapy coding for antioxidants, eNOS, HSP, mitogen-activated protein kinase and numerous other anti apoptotic proteins have demonstrated significant cardioprotection in animal models. Clinical trials have demonstrated safety in humans apart from symptomatic and objective improvements in cardiac function. Current research efforts are aimed at refining various gene transfection techniques and regulation of gene expression in vivo in the heart and circulation to improve clinical outcomes in patients that suffer from ischemic heart disease. In this review article we will attempt to summarize the current state of both preclinical and clinical studies of gene therapy to combat myocardial ischemic disease. PMID:20600100

  11. Utilizing Gene Tree Variation to Identify Candidate Effector Genes in Zymoseptoria tritici

    PubMed Central

    McDonald, Megan C.; McGinness, Lachlan; Hane, James K.; Williams, Angela H.; Milgate, Andrew; Solomon, Peter S.

    2016-01-01

    Zymoseptoria tritici is a host-specific, necrotrophic pathogen of wheat. Infection by Z. tritici is characterized by its extended latent period, which typically lasts 2 wks, and is followed by extensive host cell death, and rapid proliferation of fungal biomass. This work characterizes the level of genomic variation in 13 isolates, for which we have measured virulence on 11 wheat cultivars with differential resistance genes. Between the reference isolate, IPO323, and the 13 Australian isolates we identified over 800,000 single nucleotide polymorphisms, of which ∼10% had an effect on the coding regions of the genome. Furthermore, we identified over 1700 probable presence/absence polymorphisms in genes across the Australian isolates using de novo assembly. Finally, we developed a gene tree sorting method that quickly identifies groups of isolates within a single gene alignment whose sequence haplotypes correspond with virulence scores on a single wheat cultivar. Using this method, we have identified < 100 candidate effector genes whose gene sequence correlates with virulence toward a wheat cultivar carrying a major resistance gene. PMID:26837952

  12. Pseudoachondroplasia and Multiple Epiphyseal Dysplasia: A 7-Year Comprehensive Analysis of the Known Disease Genes Identify Novel and Recurrent Mutations and Provides an Accurate Assessment of Their Relative Contribution

    PubMed Central

    Jackson, Gail C; Mittaz-Crettol, Laureane; Taylor, Jacqueline A; Mortier, Geert R; Spranger, Juergen; Zabel, Bernhard; Le Merrer, Martine; Cormier-Daire, Valerie; Hall, Christine M; Offiah, Amaka; Wright, Michael J; Savarirayan, Ravi; Nishimura, Gen; Ramsden, Simon C; Elles, Rob; Bonafe, Luisa; Superti-Furga, Andrea; Unger, Sheila; Zankl, Andreas; Briggs, Michael D

    2012-01-01

    Pseudoachondroplasia (PSACH) and multiple epiphyseal dysplasia (MED) are relatively common skeletal dysplasias resulting in short-limbed dwarfism, joint pain, and stiffness. PSACH and the largest proportion of autosomal dominant MED (AD-MED) results from mutations in cartilage oligomeric matrix protein (COMP); however, AD-MED is genetically heterogenous and can also result from mutations in matrilin-3 (MATN3) and type IX collagen (COL9A1, COL9A2, and COL9A3). In contrast, autosomal recessive MED (rMED) appears to result exclusively from mutations in sulphate transporter solute carrier family 26 (SLC26A2). The diagnosis of PSACH and MED can be difficult for the nonexpert due to various complications and similarities with other related diseases and often mutation analysis is requested to either confirm or exclude the diagnosis. Since 2003, the European Skeletal Dysplasia Network (ESDN) has used an on-line review system to efficiently diagnose cases referred to the network prior to mutation analysis. In this study, we present the molecular findings in 130 patients referred to ESDN, which includes the identification of novel and recurrent mutations in over 100 patients. Furthermore, this study provides the first indication of the relative contribution of each gene and confirms that they account for the majority of PSACH and MED. Hum Mutat 33:144–157, 2012. © 2011 Wiley Periodicals, Inc. PMID:21922596

  13. Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation.

    PubMed

    Sharma, Ankit; Ghatge, Madankumar; Mundkur, Lakshmi; Vangala, Rajani Kanth

    2016-05-01

    Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD‑gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)‑induced genes were identified from the literature and the CAD‑associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identified in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ‑glutamyl transferase (GGT)‑5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV‑neutralizing antibody (CMV‑NA) titers. The C‑statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction. PMID:27035874

  14. Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

    PubMed Central

    2015-01-01

    Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

  15. GeneValidator: identify problems with protein-coding gene predictions

    PubMed Central

    Drăgan, Monica-Andreea; Moghul, Ismail; Priyam, Anurag; Bustos, Claudio; Wurm, Yannick

    2016-01-01

    Summary: Genomes of emerging model organisms are now being sequenced at very low cost. However, obtaining accurate gene predictions remains challenging: even the best gene prediction algorithms make substantial errors and can jeopardize subsequent analyses. Therefore, many predicted genes must be time-consumingly visually inspected and manually curated. We developed GeneValidator (GV) to automatically identify problematic gene predictions and to aid manual curation. For each gene, GV performs multiple analyses based on comparisons to gene sequences from large databases. The resulting report identifies problematic gene predictions and includes extensive statistics and graphs for each prediction to guide manual curation efforts. GV thus accelerates and enhances the work of biocurators and researchers who need accurate gene predictions from newly sequenced genomes. Availability and implementation: GV can be used through a web interface or in the command-line. GV is open-source (AGPL), available at https://wurmlab.github.io/tools/genevalidator. Contact: y.wurm@qmul.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26787666

  16. Enhancing Plant Disease Resistance without R Genes.

    PubMed

    Sarma, Birinchi Kumar; Singh, Harikesh Bahadur; Fernando, Dilantha; Silva, Roberto Nascimento; Gupta, Vijai Kumar

    2016-07-01

    Crop plants encounter constant biotic challenges, and these challenges have historically been best managed with resistance (R) genes. However, the rapid evolution of new pathogenic strains along with the nonavailability or nonidentification of R genes in cultivated crop species against a large number of plant pathogens have led researchers to think beyond R genes. Biotechnological tools have shown promise in dealing with such challenges. Technologies such as transgenerational plant immunity, interspecies transfer of pattern recognition receptors (PRRs), pathogen-derived resistance (PDR), gene regulation, and expression of antimicrobial peptides (AMPs) in host plants from other plant species have led to enhanced disease resistance and increased food security. PMID:27113633

  17. Transcriptional Profile Analysis of RPGRORF15 Frameshift Mutation Identifies Novel Genes Associated with Retinal Degeneration

    PubMed Central

    Genini, Sem; Zangerl, Barbara; Slavik, Julianna; Acland, Gregory M.; Beltran, William A.

    2010-01-01

    Purpose. To identify genes and molecular mechanisms associated with photoreceptor degeneration in a canine model of XLRP caused by an RPGR exon ORF15 microdeletion. Methods. Expression profiles of mutant and normal retinas were compared by using canine retinal custom cDNA microarrays. qRT-PCR, Western blot analysis, and immunohistochemistry (IHC) were applied to selected genes, to confirm and expand the microarray results. Results. At 7 and 16 weeks, respectively, 56 and 18 transcripts were downregulated in the mutant retinas, but none were differentially expressed (DE) at both ages, suggesting the involvement of temporally distinct pathways. Downregulated genes included the known retina-relevant genes PAX6, CHML, and RDH11 at 7 weeks and CRX and SAG at 16 weeks. Genes directly or indirectly active in apoptotic processes were altered at 7 weeks (CAMK2G, NTRK2, PRKCB, RALA, RBBP6, RNF41, SMYD3, SPP1, and TUBB2C) and 16 weeks (SLC25A5 and NKAP). Furthermore, the DE genes at 7 weeks (ELOVL6, GLOD4, NDUFS4, and REEP1) and 16 weeks (SLC25A5 and TARS2) are related to mitochondrial functions. qRT-PCR of 18 genes confirmed the microarray results and showed DE of additional genes not on the array. Only GFAP was DE at 3 weeks of age. Western blot and IHC analyses also confirmed the high reliability of the transcriptomic data. Conclusions. Several DE genes were identified in mutant retinas. At 7 weeks, a combination of nonclassic anti- and proapoptosis genes appear to be involved in photoreceptor degeneration, whereas at both 7 and 16 weeks, the expression of mitochondria-related genes indicates that they may play a relevant role in the disease process. PMID:20574030

  18. DRUMS: a human disease related unique gene mutation search engine.

    PubMed

    Li, Zuofeng; Liu, Xingnan; Wen, Jingran; Xu, Ye; Zhao, Xin; Li, Xuan; Liu, Lei; Zhang, Xiaoyan

    2011-10-01

    With the completion of the human genome project and the development of new methods for gene variant detection, the integration of mutation data and its phenotypic consequences has become more important than ever. Among all available resources, locus-specific databases (LSDBs) curate one or more specific genes' mutation data along with high-quality phenotypes. Although some genotype-phenotype data from LSDB have been integrated into central databases little effort has been made to integrate all these data by a search engine approach. In this work, we have developed disease related unique gene mutation search engine (DRUMS), a search engine for human disease related unique gene mutation as a convenient tool for biologists or physicians to retrieve gene variant and related phenotype information. Gene variant and phenotype information were stored in a gene-centred relational database. Moreover, the relationships between mutations and diseases were indexed by the uniform resource identifier from LSDB, or another central database. By querying DRUMS, users can access the most popular mutation databases under one interface. DRUMS could be treated as a domain specific search engine. By using web crawling, indexing, and searching technologies, it provides a competitively efficient interface for searching and retrieving mutation data and their relationships to diseases. The present system is freely accessible at http://www.scbit.org/glif/new/drums/index.html. PMID:21913285

  19. Copy number variation analysis identifies novel CAKUT candidate genes in children with a solitary functioning kidney

    PubMed Central

    Westland, Rik; Verbitsky, Miguel; Vukojevic, Katarina; Perry, Brittany J.; Fasel, David A.; Zwijnenburg, Petra J.G.; Bökenkamp, Arend; Gille, Johan J.P.; Saraga-Babic, Mirna; Ghiggeri, Gian Marco; D’Agati, Vivette D.; Schreuder, Michiel F.; Gharavi, Ali G.; van Wijk, Joanna A.E.; Sanna-Cherchi, Simone

    2016-01-01

    Copy number variations associate with different developmental phenotypes and represent a major cause of congenital anomalies of the kidney and urinary tract (CAKUT). Because rare pathogenic copy number variations are often large and contain multiple genes, identification of the underlying genetic drivers has proven to be difficult. Here we studied the role of rare copy number variations in 80 patients from the KIMONO-study cohort for which pathogenic mutations in three genes commonly implicated in CAKUT were excluded. In total, 13 known or novel genomic imbalances in 11 of 80 patients were absent or extremely rare in 23,362 population controls. To identify the most likely genetic drivers for the CAKUT phenotype underlying these rare copy number variations, we used a systematic in silico approach based on frequency in a large dataset of controls, annotation with publicly available databases for developmental diseases, tolerance and haploinsufficiency scores, and gene expression profile in the developing kidney and urinary tract. Five novel candidate genes for CAKUT were identified that showed specific expression in the human and mouse developing urinary tract. Among these genes, DLG1 and KIF12 are likely novel susceptibility genes for CAKUT in humans. Thus, there is a significant role of genomic imbalance in the determination of kidney developmental phenotypes. Additionally, we defined a systematic strategy to identify genetic drivers underlying rare copy number variations. PMID:26352300

  20. Identifying sexual differentiation genes that affect Drosophila life span

    PubMed Central

    2009-01-01

    Background Sexual differentiation often has significant effects on life span and aging phenotypes. For example, males and females of several species have different life spans, and genetic and environmental manipulations that affect life span often have different magnitude of effect in males versus females. Moreover, the presence of a differentiated germ-line has been shown to affect life span in several species, including Drosophila and C. elegans. Methods Experiments were conducted to determine how alterations in sexual differentiation gene activity might affect the life span of Drosophila melanogaster. Drosophila females heterozygous for the tudor[1] mutation produce normal offspring, while their homozygous sisters produce offspring that lack a germ line. To identify additional sexual differentiation genes that might affect life span, the conditional transgenic system Geneswitch was employed, whereby feeding adult flies or developing larvae the drug RU486 causes the over-expression of selected UAS-transgenes. Results In this study germ-line ablation caused by the maternal tudor[1] mutation was examined in a long-lived genetic background, and was found to increase life span in males but not in females, consistent with previous reports. Fitting the data to a Gompertz-Makeham model indicated that the maternal tudor[1] mutation increases the life span of male progeny by decreasing age-independent mortality. The Geneswitch system was used to screen through several UAS-type and EP-type P element mutations in genes that regulate sexual differentiation, to determine if additional sex-specific effects on life span would be obtained. Conditional over-expression of transformer female isoform (traF) during development produced male adults with inhibited sexual differentiation, however this caused no significant change in life span. Over-expression of doublesex female isoform (dsxF) during development was lethal to males, and produced a limited number of female escapers

  1. Prioritization of Retinal Disease Genes: An Integrative Approach

    PubMed Central

    Wagner, Alex H.; Taylor, Kyle R.; DeLuca, Adam P.; Casavant, Thomas L.; Mullins, Robert F.; Stone, Edwin M.; Scheetz, Todd E.; Braun, Terry A.

    2015-01-01

    The discovery of novel disease-associated variations in genes is often a daunting task in highly heterogeneous disease classes. We seek a generalizable algorithm that integrates multiple publicly available genomic data sources in a machine-learning model for the prioritization of candidates identified in patients with retinal disease. To approach this problem, we generate a set of feature vectors from publicly available microarray, RNA-seq, and ChIP-seq datasets of biological relevance to retinal disease, to observe patterns in gene expression specificity among tissues of the body and the eye, in addition to photoreceptor-specific signals by the CRX transcription factor. Using these features, we describe a novel algorithm, positive and unlabeled learning for prioritization (PULP). This article compares several popular supervised learning techniques as the regression function for PULP. The results demonstrate a highly significant enrichment for previously characterized disease genes using a logistic regression method. Finally, a comparison of PULP with the popular gene prioritization tool ENDEAVOUR shows superior prioritization of retinal disease genes from previous studies. PMID:23508994

  2. Interference, heterogeneity and disease gene mapping

    SciTech Connect

    Keats, B.

    1996-12-31

    The Human Genome Project has had a major impact on genetic research over the past five years. The number of mapped genes is now over 3,000 compared with approximately 1,600 in 1989 and only about 260 ten years before that. The realization that extensive variation could be detected in anonymous DNA segments greatly enhanced the potential for mapping by linkage analysis. Previously, linkage studies had depended on polymorphisms that could be detected in red blood cell antigens, proteins (revealed by electrophoresis and isoelectric focusing), and cytogenetic heteromorphisms. The identification of thousands of polymorphic DNA markers throughout the human genome has led to the construction of high density genetic linkage maps. These maps provide the data necessary to test hypotheses concerning differences in recombination rates and levels of interference. They are also important for disease gene mapping because the existence of these genes must be inferred from the phenotype. Showing linkage of a disease gene to a DNA marker is the first step towards isolating the disease gene, determining its protein product, and developing effective therapies. However, interpretation of results is not always straightforward. Factors such as etiological heterogeneity and undetected irregular segregation can lead to confusing linkage results and incorrect conclusions about the locations of disease genes. This paper will discuss these phenomena and present examples that illustrate the problems, as well as approaches to dealing with them. 23 refs., 3 figs., 3 tabs.

  3. Gene therapy: prospects for glycolipid storage diseases.

    PubMed Central

    Gieselmann, Volkmar; Matzner, Ulrich; Klein, Diana; Mansson, Jan Eric; D'Hooge, Rudi; DeDeyn, Peter D; Lüllmann Rauch, Renate; Hartmann, Dieter; Harzer, Klaus

    2003-01-01

    Lysosomal storage diseases comprise a group of about 40 disorders, which in most cases are due to the deficiency of a lysosomal enzyme. Since lysosomal enzymes are involved in the degradation of various compounds, the diseases can be further subdivided according to which pathway is affected. Thus, enzyme deficiencies in the degradation pathway of glycosaminoglycans cause mucopolysaccharidosis, and deficiencies affecting glycopeptides cause glycoproteinosis. In glycolipid storage diseases enzymes are deficient that are involved in the degradation of sphingolipids. Mouse models are available for most of these diseases, and some of these mouse models have been used to study the applicability of in vivo gene therapy. We review the rationale for gene therapy in lysosomal disorders and present data, in particular, about trials in an animal model of metachromatic leukodystrophy. The data of these trials are compared with those obtained with animal models of other lysosomal diseases. PMID:12803926

  4. Gene therapy: prospects for glycolipid storage diseases.

    PubMed

    Gieselmann, Volkmar; Matzner, Ulrich; Klein, Diana; Mansson, Jan Eric; D'Hooge, Rudi; DeDeyn, Peter D; Lüllmann Rauch, Renate; Hartmann, Dieter; Harzer, Klaus

    2003-05-29

    Lysosomal storage diseases comprise a group of about 40 disorders, which in most cases are due to the deficiency of a lysosomal enzyme. Since lysosomal enzymes are involved in the degradation of various compounds, the diseases can be further subdivided according to which pathway is affected. Thus, enzyme deficiencies in the degradation pathway of glycosaminoglycans cause mucopolysaccharidosis, and deficiencies affecting glycopeptides cause glycoproteinosis. In glycolipid storage diseases enzymes are deficient that are involved in the degradation of sphingolipids. Mouse models are available for most of these diseases, and some of these mouse models have been used to study the applicability of in vivo gene therapy. We review the rationale for gene therapy in lysosomal disorders and present data, in particular, about trials in an animal model of metachromatic leukodystrophy. The data of these trials are compared with those obtained with animal models of other lysosomal diseases. PMID:12803926

  5. A cross-study gene set enrichment analysis identifies critical pathways in endometriosis

    PubMed Central

    Zhao, Hongbo; Wang, Qishan; Bai, Chunyan; He, Kan; Pan, Yuchun

    2009-01-01

    Background Endometriosis is an enigmatic disease. Gene expression profiling of endometriosis has been used in several studies, but few studies went further to classify subtypes of endometriosis based on expression patterns and to identify possible pathways involved in endometriosis. Some of the observed pathways are more inconsistent between the studies, and these candidate pathways presumably only represent a fraction of the pathways involved in endometriosis. Methods We applied a standardised microarray preprocessing and gene set enrichment analysis to six independent studies, and demonstrated increased concordance between these gene datasets. Results We find 16 up-regulated and 19 down-regulated pathways common in ovarian endometriosis data sets, 22 up-regulated and one down-regulated pathway common in peritoneal endometriosis data sets. Among them, 12 up-regulated and 1 down-regulated were found consistent between ovarian and peritoneal endometriosis. The main canonical pathways identified are related to immunological and inflammatory disease. Early secretory phase has the most over-represented pathways in the three uterine cycle phases. There are no overlapping significant pathways between the dataset from human endometrial endothelial cells and the datasets from ovarian endometriosis which used whole tissues. Conclusion The study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. By standardised microarray preprocessing and GSEA, we have increased the concordance in identifying many biological mechanisms involved in endometriosis. The identified gene pathways will shed light on the understanding of endometriosis and promote the development of novel therapies. PMID:19735579

  6. A genetic screen identifies genes essential for development of myelinated axons in zebrafish.

    PubMed

    Pogoda, Hans-Martin; Sternheim, Nitzan; Lyons, David A; Diamond, Brianne; Hawkins, Thomas A; Woods, Ian G; Bhatt, Dimple H; Franzini-Armstrong, Clara; Dominguez, Claudia; Arana, Naomi; Jacobs, Jennifer; Nix, Rebecca; Fetcho, Joseph R; Talbot, William S

    2006-10-01

    The myelin sheath insulates axons in the vertebrate nervous system, allowing rapid propagation of action potentials via saltatory conduction. Specialized glial cells, termed Schwann cells in the PNS and oligodendrocytes in the CNS, wrap axons to form myelin, a compacted, multilayered sheath comprising specific proteins and lipids. Disruption of myelinated axons causes human diseases, including multiple sclerosis and Charcot-Marie-Tooth peripheral neuropathies. Despite the progress in identifying human disease genes and other mutations disrupting glial development and myelination, many important unanswered questions remain about the mechanisms that coordinate the development of myelinated axons. To address these questions, we began a genetic dissection of myelination in zebrafish. Here we report a genetic screen that identified 13 mutations, which define 10 genes, disrupting the development of myelinated axons. We present the initial characterization of seven of these mutations, defining six different genes, along with additional characterization of mutations that we have described previously. The different mutations affect the PNS, the CNS, or both, and phenotypic analyses indicate that the genes affect a wide range of steps in glial development, from fate specification through terminal differentiation. The analysis of these mutations will advance our understanding of myelination, and the mutants will serve as models of human diseases of myelin. PMID:16875686

  7. Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways

    PubMed Central

    Cirulli, Elizabeth T.; Lasseigne, Brittany N.; Petrovski, Slavé; Sapp, Peter C.; Dion, Patrick A.; Leblond, Claire S.; Couthouis, Julien; Lu, Yi-Fan; Wang, Quanli; Krueger, Brian J.; Ren, Zhong; Keebler, Jonathan; Han, Yujun; Levy, Shawn E.; Boone, Braden E.; Wimbish, Jack R.; Waite, Lindsay L.; Jones, Angela L.; Carulli, John P.; Day-Williams, Aaron G.; Staropoli, John F.; Xin, Winnie W.; Chesi, Alessandra; Raphael, Alya R.; McKenna-Yasek, Diane; Cady, Janet; de Jong, J.M.B. Vianney; Kenna, Kevin P.; Smith, Bradley N.; Topp, Simon; Miller, Jack; Gkazi, Athina; Al-Chalabi, Ammar; van den Berg, Leonard H.; Veldink, Jan; Silani, Vincenzo; Ticozzi, Nicola; Shaw, Christopher E.; Baloh, Robert H.; Appel, Stanley; Simpson, Ericka; Lagier-Tourenne, Clotilde; Pulst, Stefan M.; Gibson, Summer; Trojanowski, John Q.; Elman, Lauren; McCluskey, Leo; Grossman, Murray; Shneider, Neil A.; Chung, Wendy K.; Ravits, John M.; Glass, Jonathan D.; Sims, Katherine B.; Van Deerlin, Vivianna M.; Maniatis, Tom; Hayes, Sebastian D.; Ordureau, Alban; Swarup, Sharan; Landers, John; Baas, Frank; Allen, Andrew S.; Bedlack, Richard S.; Harper, J. Wade; Gitler, Aaron D.; Rouleau, Guy A.; Brown, Robert; Harms, Matthew B.; Cooper, Gregory M.; Harris, Tim; Myers, Richard M.; Goldstein, David B.

    2015-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating neurological disease with no effective treatment. Here we report the results of a moderate-scale sequencing study aimed at identifying new genes contributing to predisposition for ALS. We performed whole exome sequencing of 2,874 ALS patients and compared them to 6,405 controls. Several known ALS genes were found to be associated, and the non-canonical IκB kinase family TANK-Binding Kinase 1 (TBK1) was identified as an ALS gene. TBK1 is known to bind to and phosphorylate a number of proteins involved in innate immunity and autophagy, including optineurin (OPTN) and p62 (SQSTM1/sequestosome), both of which have also been implicated in ALS. These observations reveal a key role of the autophagic pathway in ALS and suggest specific targets for therapeutic intervention. PMID:25700176

  8. Phenolyzer: phenotype-based prioritization of candidate genes for human diseases.

    PubMed

    Yang, Hui; Robinson, Peter N; Wang, Kai

    2015-09-01

    Prior biological knowledge and phenotype information may help to identify disease genes from human whole-genome and whole-exome sequencing studies. We developed Phenolyzer (http://phenolyzer.usc.edu), a tool that uses prior information to implicate genes involved in diseases. Phenolyzer exhibits superior performance over competing methods for prioritizing Mendelian and complex disease genes, based on disease or phenotype terms entered as free text. PMID:26192085

  9. Co-clustering phenome–genome for phenotype classification and disease gene discovery

    PubMed Central

    Hwang, TaeHyun; Atluri, Gowtham; Xie, MaoQiang; Dey, Sanjoy; Hong, Changjin; Kumar, Vipin; Kuang, Rui

    2012-01-01

    Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped >2000 phenotype–gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype–gene association matrix under the prior knowledge from phenotype similarity network and protein–protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype–gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein–protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways. PMID:22735708

  10. Network Analysis Identifies SOD2 mRNA as a Potential Biomarker for Parkinson's Disease

    PubMed Central

    Santiago, Jose A.; Scherzer, Clemens R.; Potashkin, Judith A.

    2014-01-01

    Increasing evidence indicates that Parkinson's disease (PD) and type 2 diabetes (T2DM) share dysregulated molecular networks. We identified 84 genes shared between PD and T2DM from curated disease-gene databases. Nitric oxide biosynthesis, lipid and carbohydrate metabolism, insulin secretion and inflammation were identified as common dysregulated pathways. A network prioritization approach was implemented to rank genes according to their distance to seed genes and their involvement in common biological pathways. Quantitative polymerase chain reaction assays revealed that a highly ranked gene, superoxide dismutase 2 (SOD2), is upregulated in PD patients compared to healthy controls in 192 whole blood samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Diagnostic and Prognostic Biomarkers in Parkinson's disease (PROBE). The results from this study reinforce the idea that shared molecular networks between PD and T2DM provides an additional source of biologically meaningful biomarkers. Evaluation of this biomarker in de novo PD patients and in a larger prospective longitudinal study is warranted. PMID:25279756

  11. Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways.

    PubMed

    Cirulli, Elizabeth T; Lasseigne, Brittany N; Petrovski, Slavé; Sapp, Peter C; Dion, Patrick A; Leblond, Claire S; Couthouis, Julien; Lu, Yi-Fan; Wang, Quanli; Krueger, Brian J; Ren, Zhong; Keebler, Jonathan; Han, Yujun; Levy, Shawn E; Boone, Braden E; Wimbish, Jack R; Waite, Lindsay L; Jones, Angela L; Carulli, John P; Day-Williams, Aaron G; Staropoli, John F; Xin, Winnie W; Chesi, Alessandra; Raphael, Alya R; McKenna-Yasek, Diane; Cady, Janet; Vianney de Jong, J M B; Kenna, Kevin P; Smith, Bradley N; Topp, Simon; Miller, Jack; Gkazi, Athina; Al-Chalabi, Ammar; van den Berg, Leonard H; Veldink, Jan; Silani, Vincenzo; Ticozzi, Nicola; Shaw, Christopher E; Baloh, Robert H; Appel, Stanley; Simpson, Ericka; Lagier-Tourenne, Clotilde; Pulst, Stefan M; Gibson, Summer; Trojanowski, John Q; Elman, Lauren; McCluskey, Leo; Grossman, Murray; Shneider, Neil A; Chung, Wendy K; Ravits, John M; Glass, Jonathan D; Sims, Katherine B; Van Deerlin, Vivianna M; Maniatis, Tom; Hayes, Sebastian D; Ordureau, Alban; Swarup, Sharan; Landers, John; Baas, Frank; Allen, Andrew S; Bedlack, Richard S; Harper, J Wade; Gitler, Aaron D; Rouleau, Guy A; Brown, Robert; Harms, Matthew B; Cooper, Gregory M; Harris, Tim; Myers, Richard M; Goldstein, David B

    2015-03-27

    Amyotrophic lateral sclerosis (ALS) is a devastating neurological disease with no effective treatment. We report the results of a moderate-scale sequencing study aimed at increasing the number of genes known to contribute to predisposition for ALS. We performed whole-exome sequencing of 2869 ALS patients and 6405 controls. Several known ALS genes were found to be associated, and TBK1 (the gene encoding TANK-binding kinase 1) was identified as an ALS gene. TBK1 is known to bind to and phosphorylate a number of proteins involved in innate immunity and autophagy, including optineurin (OPTN) and p62 (SQSTM1/sequestosome), both of which have also been implicated in ALS. These observations reveal a key role of the autophagic pathway in ALS and suggest specific targets for therapeutic intervention. PMID:25700176

  12. Harnessing genomics to identify environmental determinants of heritable disease

    PubMed Central

    Yauk, Carole Lyn; Argueso, J. Lucas; Auerbach, Scott S.; Awadalla, Philip; Davis, Sean R.; DeMarini, David M.; Douglas, George R.; Dubrova, Yuri E.; Elespuru, Rosalie K.; Glover, Thomas W.; Hales, Barbara F.; Hurles, Matthew E.; Klein, Catherine B.; Lupski, James R.; Manchester, David K.; Marchetti, Francesco; Montpetit, Alexandre; Mulvihill, John J.; Robaire, Bernard; Robbins, Wendie A.; Rouleau, Guy A.; Shaughnessy, Daniel T.; Somers, Christopher M.; Taylor, James G.; Trasler, Jacquetta; Waters, Michael D.; Wilson, Thomas E.; Witt, Kristine L.; Bishop, Jack B.

    2012-01-01

    Next-generation sequencing technologies can now be used to directly measure heritable de novo DNA sequence mutations in humans. However, these techniques have not been used to examine environmental factors that induce such mutations and their associated diseases. To address this issue, a working group on environmentally induced germline mutation analysis (ENIGMA) met in October 2011 to propose the necessary foundational studies, which include sequencing of parent–offspring trios from highly exposed human populations, and controlled dose–response experiments in animals. These studies will establish background levels of variability in germline mutation rates and identify environmental agents that influence these rates and heritable disease. Guidance for the types of exposures to examine come from rodent studies that have identified agents such as cancer chemotherapeutic drugs, ionizing radiation, cigarette smoke, and air pollution as germ-cell mutagens. Research is urgently needed to establish the health consequences of parental exposures on subsequent generations. PMID:22935230

  13. Exome Sequencing Identifies Three Novel Candidate Genes Implicated in Intellectual Disability

    PubMed Central

    Azam, Maleeha; Ayub, Humaira; Vissers, Lisenka E. L. M.; Gilissen, Christian; Ali, Syeda Hafiza Benish; Riaz, Moeen; Veltman, Joris A.; Pfundt, Rolph; van Bokhoven, Hans; Qamar, Raheel

    2014-01-01

    Intellectual disability (ID) is a major health problem mostly with an unknown etiology. Recently exome sequencing of individuals with ID identified novel genes implicated in the disease. Therefore the purpose of the present study was to identify the genetic cause of ID in one syndromic and two non-syndromic Pakistani families. Whole exome of three ID probands was sequenced. Missense variations in two plausible novel genes implicated in autosomal recessive ID were identified: lysine (K)-specific methyltransferase 2B (KMT2B), zinc finger protein 589 (ZNF589), as well as hedgehog acyltransferase (HHAT) with a de novo mutation with autosomal dominant mode of inheritance. The KMT2B recessive variant is the first report of recessive Kleefstra syndrome-like phenotype. Identification of plausible causative mutations for two recessive and a dominant type of ID, in genes not previously implicated in disease, underscores the large genetic heterogeneity of ID. These results also support the viewpoint that large number of ID genes converge on limited number of common networks i.e. ZNF589 belongs to KRAB-domain zinc-finger proteins previously implicated in ID, HHAT is predicted to affect sonic hedgehog, which is involved in several disorders with ID, KMT2B associated with syndromic ID fits the epigenetic module underlying the Kleefstra syndromic spectrum. The association of these novel genes in three different Pakistani ID families highlights the importance of screening these genes in more families with similar phenotypes from different populations to confirm the involvement of these genes in pathogenesis of ID. PMID:25405613

  14. Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

    PubMed Central

    SHARMA, ANKIT; GHATGE, MADANKUMAR; MUNDKUR, LAKSHMI; VANGALA, RAJANI KANTH

    2016-01-01

    Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD-gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)-induced genes were identified from the literature and the CAD-associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identifed in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ-glutamyl transferase (GGT)-5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV-neutralizing antibody (CMV-NA) titers. The C-statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction. PMID:27035874

  15. Identifying Sarcomere Gene Mutations in HCM: A Personal History

    PubMed Central

    Seidman, Christine E.; Seidman, J.G.

    2011-01-01

    This article provides an historical and personal perspective on the discovery of genetic causes for hypertrophic cardiomyopathy (HCM). Extraordinary insights of physicians who initially detailed remarkable and varied manifestations of the disorder, collaboration among multidisciplinary teams with skills in clinical diagnostics and molecular genetics, and hard work by scores of trainees, solved the etiologic riddle of HCM, and unexpectedly demonstrated mutations in sarcomere protein genes as the cause of disease. In addition to celebrating 20 years of genetic research in HCM, this article serves as an introductory overview to a thematic review series that will present contemporary advances in the field of hypertrophic heart disease. Through the continued application of advances in genetic methodologies, combined with biochemical and biophysical analyses of the consequences of human mutations, fundamental knowledge about HCM and sarcomere biology has emerged. Expanding research to elucidate the mechanisms by which subtle genetic variation in contractile proteins remodel the human heart remains an exciting opportunity, one with considerable promise to provide new strategies to limit or even prevent HCM pathogenesis. PMID:21415408

  16. Gene and splicing therapies for neuromuscular diseases.

    PubMed

    Benchaouir, Rachid; Robin, Valerie; Goyenvalle, Aurelie

    2015-01-01

    Neuromuscular disorders (NMD) are heterogeneous group of genetic diseases characterized by muscle weakness and wasting. Duchenne Muscular dystrophy (DMD) and Spinal muscular atrophy (SMA) are two of the most common and severe forms in humans and although the molecular mechanisms of these diseases have been extensively investigated, there is currently no effective treatment. However, new gene-based therapies have recently emerged with particular noted advances in using conventional gene replacement strategies and RNA-based technology. Whilst proof of principle have been demonstrated in animal models, several clinical trials have recently been undertaken to investigate the feasibility of these strategies in patients. In particular, antisense mediated exon skipping has shown encouraging results and hold promise for the treatment of dystrophic muscle. In this review, we summarize the recent progress of therapeutic approaches to neuromuscular diseases, with an emphasis on gene therapy and splicing modulation for DMD and SMA, focusing on the advantages offered by these technologies but also their challenges. PMID:25961553

  17. Analysis of pan-genome to identify the core genes and essential genes of Brucella spp.

    PubMed

    Yang, Xiaowen; Li, Yajie; Zang, Juan; Li, Yexia; Bie, Pengfei; Lu, Yanli; Wu, Qingmin

    2016-04-01

    Brucella spp. are facultative intracellular pathogens, that cause a contagious zoonotic disease, that can result in such outcomes as abortion or sterility in susceptible animal hosts and grave, debilitating illness in humans. For deciphering the survival mechanism of Brucella spp. in vivo, 42 Brucella complete genomes from NCBI were analyzed for the pan-genome and core genome by identification of their composition and function of Brucella genomes. The results showed that the total 132,143 protein-coding genes in these genomes were divided into 5369 clusters. Among these, 1710 clusters were associated with the core genome, 1182 clusters with strain-specific genes and 2477 clusters with dispensable genomes. COG analysis indicated that 44 % of the core genes were devoted to metabolism, which were mainly responsible for energy production and conversion (COG category C), and amino acid transport and metabolism (COG category E). Meanwhile, approximately 35 % of the core genes were in positive selection. In addition, 1252 potential essential genes were predicted in the core genome by comparison with a prokaryote database of essential genes. The results suggested that the core genes in Brucella genomes are relatively conservation, and the energy and amino acid metabolism play a more important role in the process of growth and reproduction in Brucella spp. This study might help us to better understand the mechanisms of Brucella persistent infection and provide some clues for further exploring the gene modules of the intracellular survival in Brucella spp. PMID:26724943

  18. Transcriptome analysis reveals mucin 4 to be highly associated with periodontitis and identifies pleckstrin as a link to systemic diseases.

    PubMed

    Lundmark, Anna; Davanian, Haleh; Båge, Tove; Johannsen, Gunnar; Koro, Catalin; Lundeberg, Joakim; Yucel-Lindberg, Tülay

    2015-01-01

    The multifactorial chronic inflammatory disease periodontitis, which is characterized by destruction of tooth-supporting tissues, has also been implicated as a risk factor for various systemic diseases. Although periodontitis has been studied extensively, neither disease-specific biomarkers nor therapeutic targets have been identified, nor its link with systemic diseases. Here, we analyzed the global transcriptome of periodontitis and compared its gene expression profile with those of other inflammatory conditions, including cardiovascular disease (CVD), rheumatoid arthritis (RA), and ulcerative colitis (UC). Gingival biopsies from 62 patients with periodontitis and 62 healthy subjects were subjected to RNA sequencing. The up-regulated genes in periodontitis were related to inflammation, wounding and defense response, and apoptosis, whereas down-regulated genes were related to extracellular matrix organization and structural support. The most highly up-regulated gene was mucin 4 (MUC4), and its protein product was confirmed to be over-expressed in periodontitis. When comparing the expression profile of periodontitis with other inflammatory diseases, several gene ontology categories, including inflammatory response, cell death, cell motion, and homeostatic processes, were identified as common to all diseases. Only one gene, pleckstrin (PLEK), was significantly overexpressed in periodontitis, CVD, RA, and UC, implicating this gene as an important networking link between these chronic inflammatory diseases. PMID:26686060

  19. Transcriptome analysis reveals mucin 4 to be highly associated with periodontitis and identifies pleckstrin as a link to systemic diseases

    PubMed Central

    Lundmark, Anna; Davanian, Haleh; Båge, Tove; Johannsen, Gunnar; Koro, Catalin; Lundeberg, Joakim; Yucel-Lindberg, Tülay

    2015-01-01

    The multifactorial chronic inflammatory disease periodontitis, which is characterized by destruction of tooth-supporting tissues, has also been implicated as a risk factor for various systemic diseases. Although periodontitis has been studied extensively, neither disease-specific biomarkers nor therapeutic targets have been identified, nor its link with systemic diseases. Here, we analyzed the global transcriptome of periodontitis and compared its gene expression profile with those of other inflammatory conditions, including cardiovascular disease (CVD), rheumatoid arthritis (RA), and ulcerative colitis (UC). Gingival biopsies from 62 patients with periodontitis and 62 healthy subjects were subjected to RNA sequencing. The up-regulated genes in periodontitis were related to inflammation, wounding and defense response, and apoptosis, whereas down-regulated genes were related to extracellular matrix organization and structural support. The most highly up-regulated gene was mucin 4 (MUC4), and its protein product was confirmed to be over-expressed in periodontitis. When comparing the expression profile of periodontitis with other inflammatory diseases, several gene ontology categories, including inflammatory response, cell death, cell motion, and homeostatic processes, were identified as common to all diseases. Only one gene, pleckstrin (PLEK), was significantly overexpressed in periodontitis, CVD, RA, and UC, implicating this gene as an important networking link between these chronic inflammatory diseases. PMID:26686060

  20. Parkinson's disease candidate gene prioritization based on expression profile of midbrain dopaminergic neurons

    PubMed Central

    2010-01-01

    Background Parkinson's disease is the second most common neurodegenerative disorder. The pathological hallmark of the disease is degeneration of midbrain dopaminergic neurons. Genetic association studies have linked 13 human chromosomal loci to Parkinson's disease. Identification of gene(s), as part of the etiology of Parkinson's disease, within the large number of genes residing in these loci can be achieved through several approaches, including screening methods, and considering appropriate criteria. Since several of the indentified Parkinson's disease genes are expressed in substantia nigra pars compact of the midbrain, expression within the neurons of this area could be a suitable criterion to limit the number of candidates and identify PD genes. Methods In this work we have used the combination of findings from six rodent transcriptome analysis studies on the gene expression profile of midbrain dopaminergic neurons and the PARK loci in OMIM (Online Mendelian Inheritance in Man) database, to identify new candidate genes for Parkinson's disease. Results Merging the two datasets, we identified 20 genes within PARK loci, 7 of which are located in an orphan Parkinson's disease locus and one, which had been identified as a disease gene. In addition to identifying a set of candidates for further genetic association studies, these results show that the criteria of expression in midbrain dopaminergic neurons may be used to narrow down the number of genes in PARK loci for such studies. PMID:20716345

  1. Genome-Wide Architecture of Disease Resistance Genes in Lettuce.

    PubMed

    Christopoulou, Marilena; Wo, Sebastian Reyes-Chin; Kozik, Alex; McHale, Leah K; Truco, Maria-Jose; Wroblewski, Tadeusz; Michelmore, Richard W

    2015-12-01

    Genome-wide motif searches identified 1134 genes in the lettuce reference genome of cv. Salinas that are potentially involved in pathogen recognition, of which 385 were predicted to encode nucleotide binding-leucine rich repeat receptor (NLR) proteins. Using a maximum-likelihood approach, we grouped the NLRs into 25 multigene families and 17 singletons. Forty-one percent of these NLR-encoding genes belong to three families, the largest being RGC16 with 62 genes in cv. Salinas. The majority of NLR-encoding genes are located in five major resistance clusters (MRCs) on chromosomes 1, 2, 3, 4, and 8 and cosegregate with multiple disease resistance phenotypes. Most MRCs contain primarily members of a single NLR gene family but a few are more complex. MRC2 spans 73 Mb and contains 61 NLRs of six different gene families that cosegregate with nine disease resistance phenotypes. MRC3, which is 25 Mb, contains 22 RGC21 genes and colocates with Dm13. A library of 33 transgenic RNA interference tester stocks was generated for functional analysis of NLR-encoding genes that cosegregated with disease resistance phenotypes in each of the MRCs. Members of four NLR-encoding families, RGC1, RGC2, RGC21, and RGC12 were shown to be required for 16 disease resistance phenotypes in lettuce. The general composition of MRCs is conserved across different genotypes; however, the specific repertoire of NLR-encoding genes varied particularly of the rapidly evolving Type I genes. These tester stocks are valuable resources for future analyses of additional resistance phenotypes. PMID:26449254

  2. Genome-Wide Architecture of Disease Resistance Genes in Lettuce

    PubMed Central

    Christopoulou, Marilena; Wo, Sebastian Reyes-Chin; Kozik, Alex; McHale, Leah K.; Truco, Maria-Jose; Wroblewski, Tadeusz; Michelmore, Richard W.

    2015-01-01

    Genome-wide motif searches identified 1134 genes in the lettuce reference genome of cv. Salinas that are potentially involved in pathogen recognition, of which 385 were predicted to encode nucleotide binding-leucine rich repeat receptor (NLR) proteins. Using a maximum-likelihood approach, we grouped the NLRs into 25 multigene families and 17 singletons. Forty-one percent of these NLR-encoding genes belong to three families, the largest being RGC16 with 62 genes in cv. Salinas. The majority of NLR-encoding genes are located in five major resistance clusters (MRCs) on chromosomes 1, 2, 3, 4, and 8 and cosegregate with multiple disease resistance phenotypes. Most MRCs contain primarily members of a single NLR gene family but a few are more complex. MRC2 spans 73 Mb and contains 61 NLRs of six different gene families that cosegregate with nine disease resistance phenotypes. MRC3, which is 25 Mb, contains 22 RGC21 genes and colocates with Dm13. A library of 33 transgenic RNA interference tester stocks was generated for functional analysis of NLR-encoding genes that cosegregated with disease resistance phenotypes in each of the MRCs. Members of four NLR-encoding families, RGC1, RGC2, RGC21, and RGC12 were shown to be required for 16 disease resistance phenotypes in lettuce. The general composition of MRCs is conserved across different genotypes; however, the specific repertoire of NLR-encoding genes varied particularly of the rapidly evolving Type I genes. These tester stocks are valuable resources for future analyses of additional resistance phenotypes. PMID:26449254

  3. Mitigating false-positive associations in rare disease gene discovery.

    PubMed

    Akle, Sebastian; Chun, Sung; Jordan, Daniel M; Cassa, Christopher A

    2015-10-01

    Clinical sequencing is expanding, but causal variants are still not identified in the majority of cases. These unsolved cases can aid in gene discovery when individuals with similar phenotypes are identified in systems such as the Matchmaker Exchange. We describe risks for gene discovery in this growing set of unsolved cases. In a set of rare disease cases with the same phenotype, it is not difficult to find two individuals with the same phenotype that carry variants in the same gene. We quantify the risk of false-positive association in a cohort of individuals with the same phenotype, using the prior probability of observing a variant in each gene from over 60,000 individuals (Exome Aggregation Consortium). Based on the number of individuals with a genic variant, cohort size, specific gene, and mode of inheritance, we calculate a P value that the match represents a true association. A match in two of 10 patients in MECP2 is statistically significant (P = 0.0014), whereas a match in TTN would not reach significance, as expected (P > 0.999). Finally, we analyze the probability of matching in clinical exome cases to estimate the number of cases needed to identify genes related to different disorders. We offer Rare Disease Match, an online tool to mitigate the uncertainty of false-positive associations. PMID:26378430

  4. Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes.

    PubMed

    Saunders, Colleen J; Jalali Sefid Dashti, Mahjoubeh; Gamieldien, Junaid

    2016-01-01

    Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening, and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in mouse and rat are central concepts mapped to ontology terms. The BORG was used to screen all human genes for potential links to tendinopathy. Following further prioritisation, four strong candidate genes (COL11A2, ELN, ITGB3, LOX) were identified. These genes are differentially expressed in tendinopathy, functionally linked to features of tendinopathy and previously implicated in other connective tissue diseases. In conclusion, cross-domain semantic integration of multiple sources of biomedical knowledge, and interrogation of phenotypes and gene functions associated with disease, may significantly increase the probability of identifying strong and unobvious candidate genes in genetic association studies. PMID:26804977

  5. Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes

    PubMed Central

    Saunders, Colleen J.; Jalali Sefid Dashti, Mahjoubeh; Gamieldien, Junaid

    2016-01-01

    Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening, and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in mouse and rat are central concepts mapped to ontology terms. The BORG was used to screen all human genes for potential links to tendinopathy. Following further prioritisation, four strong candidate genes (COL11A2, ELN, ITGB3, LOX) were identified. These genes are differentially expressed in tendinopathy, functionally linked to features of tendinopathy and previously implicated in other connective tissue diseases. In conclusion, cross-domain semantic integration of multiple sources of biomedical knowledge, and interrogation of phenotypes and gene functions associated with disease, may significantly increase the probability of identifying strong and unobvious candidate genes in genetic association studies. PMID:26804977

  6. Hippocampal Gene Expression Meta-Analysis Identifies Aging and Age-Associated Spatial Learning Impairment (ASLI) Genes and Pathways

    PubMed Central

    Uddin, Raihan K.; Singh, Shiva M.

    2013-01-01

    A number of gene expression microarray studies have been carried out in the past, which studied aging and age-associated spatial learning impairment (ASLI) in the hippocampus in animal models, with varying results. Data from such studies were never integrated to identify the most significant ASLI genes and to understand their effect. In this study we integrated these data involving rats using meta-analysis. Our results show that proper removal of batch effects from microarray data generated from different laboratories is necessary before integrating them for meta-analysis. Our meta-analysis has identified a number of significant differentially expressed genes across age or across ASLI. These genes affect many key functions in the aged compared to the young rats, which include viability of neurons, cell-to-cell signalling and interaction, migration of cells, neuronal growth, and synaptic plasticity. These functional changes due to the altered gene expression may manifest into various neurodegenerative diseases and disorders, some of which leading into syndromic memory impairments. While other aging related molecular changes can result into altered synaptic plasticity simply causing normal aging related non-syndromic learning or spatial learning impairments such as ASLI. PMID:23874995

  7. Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases.

    PubMed

    Chen, Rong; Shi, Lisong; Hakenberg, Jörg; Naughton, Brian; Sklar, Pamela; Zhang, Jianguo; Zhou, Hanlin; Tian, Lifeng; Prakash, Om; Lemire, Mathieu; Sleiman, Patrick; Cheng, Wei-Yi; Chen, Wanting; Shah, Hardik; Shen, Yulan; Fromer, Menachem; Omberg, Larsson; Deardorff, Matthew A; Zackai, Elaine; Bobe, Jason R; Levin, Elissa; Hudson, Thomas J; Groop, Leif; Wang, Jun; Hakonarson, Hakon; Wojcicki, Anne; Diaz, George A; Edelmann, Lisa; Schadt, Eric E; Friend, Stephen H

    2016-05-01

    Genetic studies of human disease have traditionally focused on the detection of disease-causing mutations in afflicted individuals. Here we describe a complementary approach that seeks to identify healthy individuals resilient to highly penetrant forms of genetic childhood disorders. A comprehensive screen of 874 genes in 589,306 genomes led to the identification of 13 adults harboring mutations for 8 severe Mendelian conditions, with no reported clinical manifestation of the indicated disease. Our findings demonstrate the promise of broadening genetic studies to systematically search for well individuals who are buffering the effects of rare, highly penetrant, deleterious mutations. They also indicate that incomplete penetrance for Mendelian diseases is likely more common than previously believed. The identification of resilient individuals may provide a first step toward uncovering protective genetic variants that could help elucidate the mechanisms of Mendelian diseases and new therapeutic strategies. PMID:27065010

  8. Multiple gene mutations identified in patients infected with influenza A (H7N9) virus

    PubMed Central

    Chen, Cuicui; Wang, Mingbang; Zhu, Zhaoqin; Qu, Jieming; Xi, Xiuhong; Tang, Xinjun; Lao, Xiangda; Seeley, Eric; Li, Tao; Fan, Xiaomei; Du, Chunling; Wang, Qin; Yang, Lin; Hu, Yunwen; Bai, Chunxue; Zhang, Zhiyong; Lu, Shuihua; Song, Yuanlin; Zhou, Wenhao

    2016-01-01

    Influenza A (H7N9) virus induced high mortality since 2013. It is important to elucidate the potential genetic variations that contribute to virus infection susceptibilities. In order to identify genetic mutations that might increase host susceptibility to infection, we performed exon sequencing and validated the SNPS by Sanger sequencing on 18 H7N9 patients. Blood samples were collected from 18 confirmed H7N9 patients. The genomic DNA was captured with the Agilent SureSelect Human All Exon kit, sequenced on the Illumina Hiseq 2000, and the resulting data processed and annotated with Genome analysis Tool. SNPs were verified by independent Sanger sequencing. The DAVID database and the DAPPLE database were used to do bioinformatics analysis. Through exon sequencing and Sanger sequencing, we identified 21 genes that were highly associated with H7N9 influenza infection. Protein-protein interaction analysis showed that direct interactions among genetic products were significantly higher than expected (p = 0.004), and DAVID analysis confirmed the defense-related functions of these genes. Gene mutation profiles of survived and non-survived patients were similar, suggesting some of genes identified in this study may be associated with H7N9 influenza susceptibility. Host specific genetic determinants of disease severity identified by this approach may provide new targets for the treatment of H7N9 influenza. PMID:27156515

  9. Multiple gene mutations identified in patients infected with influenza A (H7N9) virus.

    PubMed

    Chen, Cuicui; Wang, Mingbang; Zhu, Zhaoqin; Qu, Jieming; Xi, Xiuhong; Tang, Xinjun; Lao, Xiangda; Seeley, Eric; Li, Tao; Fan, Xiaomei; Du, Chunling; Wang, Qin; Yang, Lin; Hu, Yunwen; Bai, Chunxue; Zhang, Zhiyong; Lu, Shuihua; Song, Yuanlin; Zhou, Wenhao

    2016-01-01

    Influenza A (H7N9) virus induced high mortality since 2013. It is important to elucidate the potential genetic variations that contribute to virus infection susceptibilities. In order to identify genetic mutations that might increase host susceptibility to infection, we performed exon sequencing and validated the SNPS by Sanger sequencing on 18 H7N9 patients. Blood samples were collected from 18 confirmed H7N9 patients. The genomic DNA was captured with the Agilent SureSelect Human All Exon kit, sequenced on the Illumina Hiseq 2000, and the resulting data processed and annotated with Genome analysis Tool. SNPs were verified by independent Sanger sequencing. The DAVID database and the DAPPLE database were used to do bioinformatics analysis. Through exon sequencing and Sanger sequencing, we identified 21 genes that were highly associated with H7N9 influenza infection. Protein-protein interaction analysis showed that direct interactions among genetic products were significantly higher than expected (p = 0.004), and DAVID analysis confirmed the defense-related functions of these genes. Gene mutation profiles of survived and non-survived patients were similar, suggesting some of genes identified in this study may be associated with H7N9 influenza susceptibility. Host specific genetic determinants of disease severity identified by this approach may provide new targets for the treatment of H7N9 influenza. PMID:27156515

  10. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

    PubMed Central

    He, Xin; Sanders, Stephan J.; Liu, Li; De Rubeis, Silvia; Lim, Elaine T.; Sutcliffe, James S.; Schellenberg, Gerard D.; Gibbs, Richard A.; Daly, Mark J.; Buxbaum, Joseph D.; State, Matthew W.; Devlin, Bernie; Roeder, Kathryn

    2013-01-01

    De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based on independent de novo loss-of-function (LoF) mutations falling in the same gene, and found that de novo LoF mutations occurred at a twofold higher rate than expected by chance. However successful these studies were, they used only a small fraction of the data, excluding other types of de novo mutations and inherited rare variants. Moreover, such analyses cannot readily incorporate data from case-control studies. An important research challenge in gene discovery, therefore, is to develop statistical methods that accommodate a broader class of rare variation. We develop methods that can incorporate WES data regarding de novo mutations, inherited variants present, and variants identified within cases and controls. TADA, for Transmission And De novo Association, integrates these data by a gene-based likelihood model involving parameters for allele frequencies and gene-specific penetrances. Inference is based on a Hierarchical Bayes strategy that borrows information across all genes to infer parameters that would be difficult to estimate for individual genes. In addition to theoretical development we validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis. Thus TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes. Indeed, application of TADA to WES data from subjects with ASD and their families, as well as from a study of ASD subjects and controls, revealed several novel and promising ASD candidate genes with strong statistical support. PMID:23966865

  11. COPD subtypes identified by network-based clustering of blood gene expression.

    PubMed

    Chang, Yale; Glass, Kimberly; Liu, Yang-Yu; Silverman, Edwin K; Crapo, James D; Tal-Singer, Ruth; Bowler, Russ; Dy, Jennifer; Cho, Michael; Castaldi, Peter

    2016-03-01

    One of the most common smoking-related diseases, chronic obstructive pulmonary disease (COPD), results from a dysregulated, multi-tissue inflammatory response to cigarette smoke. We hypothesized that systemic inflammatory signals in genome-wide blood gene expression can identify clinically important COPD-related disease subtypes, and we leveraged pre-existing gene interaction networks to guide unsupervised clustering of blood microarray expression data. Using network-informed non-negative matrix factorization, we analyzed genome-wide blood gene expression from 229 former smokers in the ECLIPSE Study, and we identified novel, clinically relevant molecular subtypes of COPD. These network-informed clusters were more stable and more strongly associated with measures of lung structure and function than clusters derived from a network-naïve approach, and they were associated with subtype-specific enrichment for inflammatory and protein catabolic pathways. These clusters were successfully reproduced in an independent sample of 135 smokers from the COPDGene Study. PMID:26773458

  12. Molecular Characterization of Potato Disease Resistance Genes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A key long-term management strategy for combating potato diseases is to develop cultivars with high levels of resistance through identification and integration of major resistance (R) genes. This talk will summarize our results of cloning and characterizing major late blight and Verticillium wilt R...

  13. [From gene to disease; cutaneous leiomyomatosis].

    PubMed

    Badeloe, S; van Geel, M; van Steensel, M A M; Steijlen, P M; Poblete-Gutiérrez, P; Frank, J A

    2007-02-01

    Multiple cutaneous and uterine leiomyomatosis (MCUL; OMIM 150800) is an autosomal dominantly inherited disease characterized by leiomyomas of the skin and uterine leiomyomas. MCUL can be associated with various types of renal cancer. This syndrome is known as hereditary leiomyomatosis and renal cell cancer (HLRCC; OMIM 605839). Both disorders result from heterozygous germline mutations in the fumarate hydratase (FH) gene. PMID:17326474

  14. Gene Therapy for "Bubble Boy" Disease.

    PubMed

    Hoggatt, Jonathan

    2016-07-14

    Adenosine deaminase (ADA) deficiency results in the accumulation of toxic metabolites that destroy the immune system, causing severe combined immunodeficiency (ADA-SCID), often referred to as the "bubble boy" disease. Strimvelis is a European Medicines Agency approved gene therapy for ADA-SCID patients without a suitable bone marrow donor. PMID:27419862

  15. Comparative prion disease gene expression profiling using the prion disease mimetic, cuprizone

    PubMed Central

    Moody, Laura R; Herbst, Allen J; Yoo, Han Sang; Vanderloo, Joshua P

    2009-01-01

    Identification of genes expressed in response to prion infection may elucidate biomarkers for disease, identify factors involved in agent replication, mechanisms of neuropathology and therapeutic targets. Although several groups have sought to identify gene expression changes specific to prion disease, expression profiles rife with cell population changes have consistently been identified. Cuprizone, a neurotoxicant, qualitatively mimics the cell population changes observed in prion disease, resulting in both spongiform change and astrocytosis. The use of cuprizone-treated animals as an experimental control during comparative expression profiling allows for the identification of transcripts whose expression increases during prion disease and remains unchanged during cuprizone-triggered neuropathology. In this study, expression profiles from the brains of mice preclinically and clinically infected with Rocky Mountain Laboratory (RML) mouse-adapted scrapie agent and age-matched controls were profiled using Affymetrix gene arrays. In total, 164 genes were differentially regulated during prion infection. Eighty-three of these transcripts have been previously undescribed as differentially regulated during prion disease. A 0.4% cuprizone diet was utilized as a control for comparative expression profiling. Cuprizone treatment induced spongiosis and astrocyte proliferation as indicated by glial fibrillary acidic protein (Gfap) transcriptional activation and immunohistochemistry. Gene expression profiles from brain tissue obtained from cuprizone-treated mice identified 307 differentially regulated transcript changes. After comparative analysis, 17 transcripts unaffected by cuprizone treatment but increasing in expression from preclinical to clinical prion infection were identified. Here we describe the novel use of the prion disease mimetic, cuprizone, to control for cell population changes in the brain during prion infection. PMID:19535908

  16. Analyse multiple disease subtypes and build associated gene networks using genome-wide expression profiles

    PubMed Central

    2015-01-01

    Background Despite the large increase of transcriptomic studies that look for gene signatures on diseases, there is still a need for integrative approaches that obtain separation of multiple pathological states providing robust selection of gene markers for each disease subtype and information about the possible links or relations between those genes. Results We present a network-oriented and data-driven bioinformatic approach that searches for association of genes and diseases based on the analysis of genome-wide expression data derived from microarrays or RNA-Seq studies. The approach aims to (i) identify gene sets associated to different pathological states analysed together; (ii) identify a minimum subset within these genes that unequivocally differentiates and classifies the compared disease subtypes; (iii) provide a measurement of the discriminant power of these genes and (iv) identify links between the genes that characterise each of the disease subtypes. This bioinformatic approach is implemented in an R package, named geNetClassifier, available as an open access tool in Bioconductor. To illustrate the performance of the tool, we applied it to two independent datasets: 250 samples from patients with four major leukemia subtypes analysed using expression arrays; another leukemia dataset analysed with RNA-Seq that includes a subtype also present in the previous set. The results show the selection of key deregulated genes recently reported in the literature and assigned to the leukemia subtypes studied. We also show, using these independent datasets, the selection of similar genes in a network built for the same disease subtype. Conclusions The construction of gene networks related to specific disease subtypes that include parameters such as gene-to-gene association, gene disease specificity and gene discriminant power can be very useful to draw gene-disease maps and to unravel the molecular features that characterize specific pathological states. The

  17. Gene-Trap Mutagenesis Identifies Mammalian Genes Contributing to Intoxication by Clostridium perfringens ε-Toxin

    PubMed Central

    Ivie, Susan E.; Fennessey, Christine M.; Sheng, Jinsong; Rubin, Donald H.; McClain, Mark S.

    2011-01-01

    The Clostridium perfringens ε-toxin is an extremely potent toxin associated with lethal toxemias in domesticated ruminants and may be toxic to humans. Intoxication results in fluid accumulation in various tissues, most notably in the brain and kidneys. Previous studies suggest that the toxin is a pore-forming toxin, leading to dysregulated ion homeostasis and ultimately cell death. However, mammalian host factors that likely contribute to ε-toxin-induced cytotoxicity are poorly understood. A library of insertional mutant Madin Darby canine kidney (MDCK) cells, which are highly susceptible to the lethal affects of ε-toxin, was used to select clones of cells resistant to ε-toxin-induced cytotoxicity. The genes mutated in 9 surviving resistant cell clones were identified. We focused additional experiments on one of the identified genes as a means of validating the experimental approach. Gene expression microarray analysis revealed that one of the identified genes, hepatitis A virus cellular receptor 1 (HAVCR1, KIM-1, TIM1), is more abundantly expressed in human kidney cell lines than it is expressed in human cells known to be resistant to ε-toxin. One human kidney cell line, ACHN, was found to be sensitive to the toxin and expresses a larger isoform of the HAVCR1 protein than the HAVCR1 protein expressed by other, toxin-resistant human kidney cell lines. RNA interference studies in MDCK and in ACHN cells confirmed that HAVCR1 contributes to ε-toxin-induced cytotoxicity. Additionally, ε-toxin was shown to bind to HAVCR1 in vitro. The results of this study indicate that HAVCR1 and the other genes identified through the use of gene-trap mutagenesis and RNA interference strategies represent important targets for investigation of the process by which ε-toxin induces cell death and new targets for potential therapeutic intervention. PMID:21412435

  18. Relationship between TBX20 gene polymorphism and congenital heart disease.

    PubMed

    Yang, X F; Zhang, Y F; Zhao, C F; Liu, M M; Si, J P; Fang, Y F; Xing, W W; Wang, F L

    2016-01-01

    Congenital heart disease in children is a type of birth defect. Previous studies have suggested that the transcription factor, TBX20, is involved in the occurrence and development of congenital heart disease in children; however, the specific regulatory mechanisms are yet to be evaluated. Hence, this study aimed to evaluate the relationship between the TBX20 polymorphism and the occurrence and development of congenital heart disease. The TBX20 gene sequence was obtained from the NCBI database and the polymorphic locus candidate was predicted. Thereafter, the specific gene primers were designed for the restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR) of DNA extracted from the blood of 80 patients with congenital heart disease and 80 controls. The results of the PCR were subjected to correlation analysis to identify the differences between the amplicons and to determine the relationship between the TBX20 gene polymorphism and congenital heart disease. One of the single nucleotide polymorphic locus was found to be rs3999950: c.774T>C (Ala265Ala). The TC genotype frequency in the patients was higher than that in the controls, similar to that for the C locus. The odds ratio of the TC genotypes was above 1, indicating that the presence of the TC genotype increases the incidence of congenital heart diseases. Thus, rs3999950 may be associated with congenital heart disease, and TBX20 may predispose children to the defect. PMID:27323105

  19. A Systems Approach Identifies Networks and Genes Linking Sleep and Stress: Implications for Neuropsychiatric Disorders

    PubMed Central

    Jiang, Peng; Scarpa, Joseph R.; Fitzpatrick, Karrie; Losic, Bojan; Gao, Vance D.; Hao, Ke; Summa, Keith C.; Yang, He S.; Zhang, Bin; Allada, Ravi; Vitaterna, Martha H.; Turek, Fred W.; Kasarskis, Andrew

    2016-01-01

    SUMMARY Sleep dysfunction and stress susceptibility are co-morbid complex traits, which often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multi-level organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J×A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests the interplay between sleep, stress, and neuropathology emerge from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework to interrogate the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders. PMID:25921536

  20. Genomic analysis of primordial dwarfism reveals novel disease genes.

    PubMed

    Shaheen, Ranad; Faqeih, Eissa; Ansari, Shinu; Abdel-Salam, Ghada; Al-Hassnan, Zuhair N; Al-Shidi, Tarfa; Alomar, Rana; Sogaty, Sameera; Alkuraya, Fowzan S

    2014-02-01

    Primordial dwarfism (PD) is a disease in which severely impaired fetal growth persists throughout postnatal development and results in stunted adult size. The condition is highly heterogeneous clinically, but the use of certain phenotypic aspects such as head circumference and facial appearance has proven helpful in defining clinical subgroups. In this study, we present the results of clinical and genomic characterization of 16 new patients in whom a broad definition of PD was used (e.g., 3M syndrome was included). We report a novel PD syndrome with distinct facies in two unrelated patients, each with a different homozygous truncating mutation in CRIPT. Our analysis also reveals, in addition to mutations in known PD disease genes, the first instance of biallelic truncating BRCA2 mutation causing PD with normal bone marrow analysis. In addition, we have identified a novel locus for Seckel syndrome based on a consanguineous multiplex family and identified a homozygous truncating mutation in DNA2 as the likely cause. An additional novel PD disease candidate gene XRCC4 was identified by autozygome/exome analysis, and the knockout mouse phenotype is highly compatible with PD. Thus, we add a number of novel genes to the growing list of PD-linked genes, including one which we show to be linked to a novel PD syndrome with a distinct facial appearance. PD is extremely heterogeneous genetically and clinically, and genomic tools are often required to reach a molecular diagnosis. PMID:24389050

  1. Identifying Symptom Patterns in People Living With HIV Disease.

    PubMed

    Wilson, Natalie L; Azuero, Andres; Vance, David E; Richman, Joshua S; Moneyham, Linda D; Raper, James L; Heath, Sonya L; Kempf, Mirjam-Colette

    2016-01-01

    Symptoms guide disease management, and patients frequently report HIV-related symptoms, but HIV symptom patterns reported by patients have not been described in the era of improved antiretroviral treatment. The objectives of our study were to investigate the prevalence and burden of symptoms in people living with HIV and attending an outpatient clinic. The prevalence, burden, and bothersomeness of symptoms reported by patients in routine clinic visits during 2011 were assessed using the 20-item HIV Symptom Index. Principal component analysis was used to identify symptom clusters and relationships between groups using appropriate statistic techniques. Two main clusters were identified. The most prevalent and bothersome symptoms were muscle aches/joint pain, fatigue, and poor sleep. A third of patients had seven or more symptoms, including the most burdensome symptoms. Even with improved antiretroviral drug side-effect profiles, symptom prevalence and burden, independent of HIV viral load and CD4+ T cell count, are high. PMID:26790340

  2. Identifying glycoside hydrolase family 18 genes in the mycoparasitic fungal species Clonostachys rosea.

    PubMed

    Tzelepis, Georgios; Dubey, Mukesh; Jensen, Dan Funck; Karlsson, Magnus

    2015-07-01

    Clonostachysrosea is a mycoparasitic fungal species that is an efficient biocontrol agent against many plant diseases. During mycoparasitic interactions, one of the most crucial steps is the hydrolysis of the prey's fungal cell wall, which mainly consists of glucans, glycoproteins and chitin. Chitinases are hydrolytic enzymes responsible for chitin degradation and it is suggested that they play an important role in fungal-fungal interactions. Fungal chitinases belong exclusively to the glycoside hydrolase (GH) family 18.These GH18 proteins are categorized into three distinct phylogenetic groups (A, B and C), subdivided into several subgroups. In this study, we identified 14 GH18 genes in the C. rosea genome, which is remarkably low compared with the high numbers found in mycoparasitic Trichoderma species. Phylogenetic analysis revealed that C. rosea contains eight genes in group A, two genes in group B, two genes in group C, one gene encoding a putative ENGase (endo-β-N-acetylglucosaminidase) and the ech37 gene, which is of bacterial origin. Gene expression analysis showed that only two genes had higher transcription levels during fungal-fungal interactions, while eight out of 14 GH18 genes were triggered by chitin. Furthermore, deletion of the C group chiC2 gene decreased the growth inhibitory activity of C. rosea culture filtrates against Botrytis cinerea and Rhizoctonia solani, although the biocontrol ability of C. rosea against B. cinerea was not affected. In addition, a potential role of the CHIC2 chitinase in the sporulation process was revealed. These results provide new information about the role of GH18 proteins in mycoparasitic interactions. PMID:25881898

  3. Species-wide Genetic Incompatibility Analysis Identifies Immune Genes as Hotspots of Deleterious Epistasis

    PubMed Central

    Chae, Eunyoung; Bomblies, Kirsten; Kim, Sang-Tae; Karelina, Darya; Zaidem, Maricris; Ossowski, Stephan; Martín-Pizarro, Carmen; Laitinen, Roosa A. E.; Rowan, Beth A.; Tenenboim, Hezi; Lechner, Sarah; Demar, Monika; Habring-Müller, Anette; Lanz, Christa; Rätsch, Gunnar; Weigel, Detlef

    2014-01-01

    Summary Intraspecific genetic incompatibilities prevent the assembly of specific alleles into single genotypes and influence genome- and species-wide patterns of sequence variation. A common incompatibility in plants is hybrid necrosis, characterized by autoimmune responses due to epistatic interactions between natural genetic variants. By systematically testing thousands of F1 hybrids of Arabidopsis thaliana strains, we identified a small number of incompatibility hotspots in the genome, often in regions densely populated by NLR immune receptor genes. In several cases, these immune receptor loci interact with each other, suggestive of conflict within the immune system. A particularly dangerous locus is a highly variable cluster of NLR genes, DANGEROUS MIX2 (DM2), which causes multiple, independent incompatibilities with genes that encode a range of biochemical functions, including NLRs. Our findings suggest that deleterious interactions of immune receptors at the front lines of host-pathogen co-evolution limit the combinations of favorable disease resistance alleles accessible to plant genomes. PMID:25467443

  4. On the Identifiability of Transmission Dynamic Models for Infectious Diseases.

    PubMed

    Lintusaari, Jarno; Gutmann, Michael U; Kaski, Samuel; Corander, Jukka

    2016-03-01

    Understanding the transmission dynamics of infectious diseases is important for both biological research and public health applications. It has been widely demonstrated that statistical modeling provides a firm basis for inferring relevant epidemiological quantities from incidence and molecular data. However, the complexity of transmission dynamic models presents two challenges: (1) the likelihood function of the models is generally not computable, and computationally intensive simulation-based inference methods need to be employed, and (2) the model may not be fully identifiable from the available data. While the first difficulty can be tackled by computational and algorithmic advances, the second obstacle is more fundamental. Identifiability issues may lead to inferences that are driven more by prior assumptions than by the data themselves. We consider a popular and relatively simple yet analytically intractable model for the spread of tuberculosis based on classical IS6110 fingerprinting data. We report on the identifiability of the model, also presenting some methodological advances regarding the inference. Using likelihood approximations, we show that the reproductive value cannot be identified from the data available and that the posterior distributions obtained in previous work have likely been substantially dominated by the assumed prior distribution. Further, we show that the inferences are influenced by the assumed infectious population size, which generally has been kept fixed in previous work. We demonstrate that the infectious population size can be inferred if the remaining epidemiological parameters are already known with sufficient precision. PMID:26739450

  5. Gene polymorphisms and chronic obstructive pulmonary disease

    PubMed Central

    Wu, Xiaodan; Yuan, Bowei; López, Elena; Bai, Chunxue; Wang, Xiangdong

    2014-01-01

    The genetic component was suggested to contribute to the development of chronic obstructive pulmonary disease (COPD), a major and growing public health burden. The present review aims to characterize the evidence that gene polymorphisms contribute to the aetiology of COPD and related traits, and explore the potential relationship between certain gene polymorphisms and COPD susceptibility, severity, lung function, phenotypes, or drug effects, even though limited results from related studies lacked consistency. Most of these studies were association studies, rather than confirmatory studies. More large-sized and strictly controlled studies are needed to prove the relationship between gene polymorphisms and the reviewed traits. More importantly, prospective confirmatory studies beyond initial association studies will be necessary to evaluate true relationships between gene polymorphisms and COPD and help individualized treatment for patients with COPD. PMID:24256364

  6. Genome-Wide Scan Informed by Age-Related Disease Identifies Loci for Exceptional Human Longevity

    PubMed Central

    Fortney, Kristen; Dobriban, Edgar; Garagnani, Paolo; Pirazzini, Chiara; Monti, Daniela; Mari, Daniela; Atzmon, Gil; Barzilai, Nir; Franceschi, Claudio; Owen, Art B.; Kim, Stuart K.

    2015-01-01

    We developed a new statistical framework to find genetic variants associated with extreme longevity. The method, informed GWAS (iGWAS), takes advantage of knowledge from large studies of age-related disease in order to narrow the search for SNPs associated with longevity. To gain support for our approach, we first show there is an overlap between loci involved in disease and loci associated with extreme longevity. These results indicate that several disease variants may be depleted in centenarians versus the general population. Next, we used iGWAS to harness information from 14 meta-analyses of disease and trait GWAS to identify longevity loci in two studies of long-lived humans. In a standard GWAS analysis, only one locus in these studies is significant (APOE/TOMM40) when controlling the false discovery rate (FDR) at 10%. With iGWAS, we identify eight genetic loci to associate significantly with exceptional human longevity at FDR < 10%. We followed up the eight lead SNPs in independent cohorts, and found replication evidence of four loci and suggestive evidence for one more with exceptional longevity. The loci that replicated (FDR < 5%) included APOE/TOMM40 (associated with Alzheimer’s disease), CDKN2B/ANRIL (implicated in the regulation of cellular senescence), ABO (tags the O blood group), and SH2B3/ATXN2 (a signaling gene that extends lifespan in Drosophila and a gene involved in neurological disease). Our results implicate new loci in longevity and reveal a genetic overlap between longevity and age-related diseases and traits, including coronary artery disease and Alzheimer’s disease. iGWAS provides a new analytical strategy for uncovering SNPs that influence extreme longevity, and can be applied more broadly to boost power in other studies of complex phenotypes. PMID:26677855

  7. A Systematic Analysis of Human Disease-Associated Gene Sequences In Drosophila melanogaster

    PubMed Central

    Reiter, Lawrence T.; Potocki, Lorraine; Chien, Sam; Gribskov, Michael; Bier, Ethan

    2001-01-01

    We performed a systematic BLAST analysis of 929 human disease gene entries associated with at least one mutant allele in the Online Mendelian Inheritance in Man (OMIM) database against the recently completed genome sequence of Drosophila melanogaster. The results of this search have been formatted as an updateable and searchable on-line database called Homophila. Our analysis identified 714 distinct human disease genes (77% of disease genes searched) matching 548 unique Drosophila sequences, which we have summarized by disease category. This breakdown into disease classes creates a picture of disease genes that are amenable to study using Drosophila as the model organism. Of the 548 Drosophila genes related to human disease genes, 153 are associated with known mutant alleles and 56 more are tagged by P-element insertions in or near the gene. Examples of how to use the database to identify Drosophila genes related to human disease genes are presented. We anticipate that cross-genomic analysis of human disease genes using the power of Drosophila second-site modifier screens will promote interaction between human and Drosophila research groups, accelerating the understanding of the pathogenesis of human genetic disease. The Homophila database is available at http://homophila.sdsc.edu. PMID:11381037

  8. A Genome-Wide Methylation Approach Identifies a New Hypermethylated Gene Panel in Ulcerative Colitis

    PubMed Central

    Kang, Keunsoo; Bae, Jin-Han; Han, Kyudong; Kim, Eun Soo; Kim, Tae-Oh; Yi, Joo Mi

    2016-01-01

    The cause of inflammatory bowel disease (IBD) is still unknown, but there is growing evidence that environmental factors such as epigenetic changes can contribute to the disease etiology. The aim of this study was to identify newly hypermethylated genes in ulcerative colitis (UC) using a genome-wide DNA methylation approach. Using an Infinium HumanMethylation450 BeadChip array, we screened the DNA methylation changes in three normal colon controls and eight UC patients. Using these methylation profiles, 48 probes associated with CpG promoter methylation showed differential hypermethylation between UC patients and normal controls. Technical validations for methylation analyses in a larger series of UC patients (n = 79) were performed by methylation-specific PCR (MSP) and bisulfite sequencing analysis. We finally found that three genes (FAM217B, KIAA1614 and RIBC2) that were significantly elevating the promoter methylation levels in UC compared to normal controls. Interestingly, we confirmed that three genes were transcriptionally silenced in UC patient samples by qRT-PCR, suggesting that their silencing is correlated with the promoter hypermethylation. Pathway analyses were performed using GO and KEGG databases with differentially hypermethylated genes in UC. Our results highlight that aberrant hypermethylation was identified in UC patients which can be a potential biomarker for detecting UC. Moreover, pathway-enriched hypermethylated genes are possibly implicating important cellular function in the pathogenesis of UC. Overall, this study describes a newly hypermethylated gene panel in UC patients and provides new clinical information that can be used for the diagnosis and therapeutic treatment of IBD. PMID:27517910

  9. A Genome-Wide Methylation Approach Identifies a New Hypermethylated Gene Panel in Ulcerative Colitis.

    PubMed

    Kang, Keunsoo; Bae, Jin-Han; Han, Kyudong; Kim, Eun Soo; Kim, Tae-Oh; Yi, Joo Mi

    2016-01-01

    The cause of inflammatory bowel disease (IBD) is still unknown, but there is growing evidence that environmental factors such as epigenetic changes can contribute to the disease etiology. The aim of this study was to identify newly hypermethylated genes in ulcerative colitis (UC) using a genome-wide DNA methylation approach. Using an Infinium HumanMethylation450 BeadChip array, we screened the DNA methylation changes in three normal colon controls and eight UC patients. Using these methylation profiles, 48 probes associated with CpG promoter methylation showed differential hypermethylation between UC patients and normal controls. Technical validations for methylation analyses in a larger series of UC patients (n = 79) were performed by methylation-specific PCR (MSP) and bisulfite sequencing analysis. We finally found that three genes (FAM217B, KIAA1614 and RIBC2) that were significantly elevating the promoter methylation levels in UC compared to normal controls. Interestingly, we confirmed that three genes were transcriptionally silenced in UC patient samples by qRT-PCR, suggesting that their silencing is correlated with the promoter hypermethylation. Pathway analyses were performed using GO and KEGG databases with differentially hypermethylated genes in UC. Our results highlight that aberrant hypermethylation was identified in UC patients which can be a potential biomarker for detecting UC. Moreover, pathway-enriched hypermethylated genes are possibly implicating important cellular function in the pathogenesis of UC. Overall, this study describes a newly hypermethylated gene panel in UC patients and provides new clinical information that can be used for the diagnosis and therapeutic treatment of IBD. PMID:27517910

  10. Gene Profiling of Mta1 Identifies Novel Gene Targets and Functions

    PubMed Central

    Eswaran, Jeyanthy; Kumar, Rakesh

    2011-01-01

    Background Metastasis-associated protein 1 (MTA1), a master dual co-regulatory protein is found to be an integral part of NuRD (Nucleosome Remodeling and Histone Deacetylation) complex, which has indispensable transcriptional regulatory functions via histone deacetylation and chromatin remodeling. Emerging literature establishes MTA1 to be a valid DNA-damage responsive protein with a significant role in maintaining the optimum DNA-repair activity in mammalian cells exposed to genotoxic stress. This DNA-damage responsive function of MTA1 was reported to be a P53-dependent and independent function. Here, we investigate the influence of P53 on gene regulation function of Mta1 to identify novel gene targets and functions of Mta1. Methods Gene expression analysis was performed on five different mouse embryonic fibroblasts (MEFs) samples (i) the Mta1 wild type, (ii) Mta1 knock out (iii) Mta1 knock out in which Mta1 was reintroduced (iv) P53 knock out (v) P53 knock out in which Mta1 was over expressed using Affymetrix Mouse Exon 1.0 ST arrays. Further Hierarchical Clustering, Gene Ontology analysis with GO terms satisfying corrected p-value<0.1, and the Ingenuity Pathway Analysis were performed. Finally, RT-qPCR was carried out on selective candidate genes. Significance/Conclusion This study represents a complete genome wide screen for possible target genes of a coregulator, Mta1. The comparative gene profiling of Mta1 wild type, Mta1 knockout and Mta1 re-expression in the Mta1 knockout conditions define “bona fide” Mta1 target genes. Further extensive analyses of the data highlights the influence of P53 on Mta1 gene regulation. In the presence of P53 majority of the genes regulated by Mta1 are related to inflammatory and anti-microbial responses whereas in the absence of P53 the predominant target genes are involved in cancer signaling. Thus, the presented data emphasizes the known functions of Mta1 and serves as a rich resource which could help us identify novel Mta