Science.gov

Sample records for identifying disease genes

  1. Identifying disease genes by integrating multiple data sources

    PubMed Central

    2014-01-01

    Background Now multiple types of data are available for identifying disease genes. Those data include gene-disease associations, disease phenotype similarities, protein-protein interactions, pathways, gene expression profiles, etc.. It is believed that integrating different kinds of biological data is an effective method to identify disease genes. Results In this paper, we propose a multiple data integration method based on the theory of Markov random field (MRF) and the method of Bayesian analysis for identifying human disease genes. The proposed method is not only flexible in easily incorporating different kinds of data, but also reliable in predicting candidate disease genes. Conclusions Numerical experiments are carried out by integrating known gene-disease associations, protein complexes, protein-protein interactions, pathways and gene expression profiles. Predictions are evaluated by the leave-one-out method. The proposed method achieves an AUC score of 0.743 when integrating all those biological data in our experiments. PMID:25350511

  2. Identifying Causal Genes and Dysregulated Pathways in Complex Diseases

    PubMed Central

    Kim, Yoo-Ah; Wuchty, Stefan; Przytycka, Teresa M.

    2011-01-01

    In complex diseases, various combinations of genomic perturbations often lead to the same phenotype. On a molecular level, combinations of genomic perturbations are assumed to dys-regulate the same cellular pathways. Such a pathway-centric perspective is fundamental to understanding the mechanisms of complex diseases and the identification of potential drug targets. In order to provide an integrated perspective on complex disease mechanisms, we developed a novel computational method to simultaneously identify causal genes and dys-regulated pathways. First, we identified a representative set of genes that are differentially expressed in cancer compared to non-tumor control cases. Assuming that disease-associated gene expression changes are caused by genomic alterations, we determined potential paths from such genomic causes to target genes through a network of molecular interactions. Applying our method to sets of genomic alterations and gene expression profiles of 158 Glioblastoma multiforme (GBM) patients we uncovered candidate causal genes and causal paths that are potentially responsible for the altered expression of disease genes. We discovered a set of putative causal genes that potentially play a role in the disease. Combining an expression Quantitative Trait Loci (eQTL) analysis with pathway information, our approach allowed us not only to identify potential causal genes but also to find intermediate nodes and pathways mediating the information flow between causal and target genes. Our results indicate that different genomic perturbations indeed dys-regulate the same functional pathways, supporting a pathway-centric perspective of cancer. While copy number alterations and gene expression data of glioblastoma patients provided opportunities to test our approach, our method can be applied to any disease system where genetic variations play a fundamental causal role. PMID:21390271

  3. 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 available as a stand-alone software package at http://wiki.chasmsoftware.org and is hosted by the CRAVAT web server at http://www.cravat.us PMID:23819870

  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. GeneFriends: An online co-expression analysis tool to identify novel gene targets for aging and complex diseases

    PubMed Central

    2012-01-01

    Background Although many diseases have been well characterized at the molecular level, the underlying mechanisms are often unknown. Nearly half of all human genes remain poorly studied, yet these genes may contribute to a number of disease processes. Genes involved in common biological processes and diseases are often co-expressed. Using known disease-associated genes in a co-expression analysis may help identify and prioritize novel candidate genes for further study. Results We have created an online tool, called GeneFriends, which identifies co-expressed genes in over 1,000 mouse microarray datasets. GeneFriends can be used to assign putative functions to poorly studied genes. Using a seed list of disease-associated genes and a guilt-by-association method, GeneFriends allows users to quickly identify novel genes and transcription factors associated with a disease or process. We tested GeneFriends using seed lists for aging, cancer, and mitochondrial complex I disease. We identified several candidate genes that have previously been predicted as relevant targets. Some of the genes identified are already being tested in clinical trials, indicating the effectiveness of this approach. Co-expressed transcription factors were investigated, identifying C/ebp genes as candidate regulators of aging. Furthermore, several novel candidate genes, that may be suitable for experimental or clinical follow-up, were identified. Two of the novel candidates of unknown function that were co-expressed with cancer-associated genes were selected for experimental validation. Knock-down of their human homologs (C1ORF112 and C12ORF48) in HeLa cells slowed growth, indicating that these genes of unknown function, identified by GeneFriends, may be involved in cancer. Conclusions GeneFriends is a resource for biologists to identify and prioritize novel candidate genes involved in biological processes and complex diseases. It is an intuitive online resource that will help drive experimentation. GeneFriends is available online at: http://genefriends.org/. PMID:23039964

  6. Identifying gene-disease associations using centrality on a literature mined gene-interaction network

    PubMed Central

    Özgür, Arzucan; Vu, Thuy; Erkan, Güneş; Radev, Dragomir R.

    2008-01-01

    Motivation: Understanding the role of genetics in diseases is one of the most important aims of the biological sciences. The completion of the Human Genome Project has led to a rapid increase in the number of publications in this area. However, the coverage of curated databases that provide information manually extracted from the literature is limited. Another challenge is that determining disease-related genes requires laborious experiments. Therefore, predicting good candidate genes before experimental analysis will save time and effort. We introduce an automatic approach based on text mining and network analysis to predict gene-disease associations. We collected an initial set of known disease-related genes and built an interaction network by automatic literature mining based on dependency parsing and support vector machines. Our hypothesis is that the central genes in this disease-specific network are likely to be related to the disease. We used the degree, eigenvector, betweenness and closeness centrality metrics to rank the genes in the network. Results: The proposed approach can be used to extract known and to infer unknown gene-disease associations. We evaluated the approach for prostate cancer. Eigenvector and degree centrality achieved high accuracy. A total of 95% of the top 20 genes ranked by these methods are confirmed to be related to prostate cancer. On the other hand, betweenness and closeness centrality predicted more genes whose relation to the disease is currently unknown and are candidates for experimental study. Availability: A web-based system for browsing the disease-specific gene-interaction networks is available at: http://gin.ncibi.org Contact: radev@umich.edu PMID:18586725

  7. IDENTIFYING DISEASE RESISTANCE GENES AND PATHWAYS THROUGH HOST-PATHOGEN PROTEIN INTERACTIONS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A major objective of both animal and plant genomics research is to identify disease resistance genes and pathways. Popular approaches to achieve this goal include candidate gene testing, genome-wide QTL screens, and DNA microarrays. We argue that the two-hybrid assay, which detects protein-protein...

  8. Genes that Affect Brain Structure and Function Identified by Rare Variant Analyses of Mendelian Neurologic Disease.

    PubMed

    Karaca, Ender; Harel, Tamar; Pehlivan, Davut; Jhangiani, Shalini N; Gambin, Tomasz; Coban Akdemir, Zeynep; Gonzaga-Jauregui, Claudia; Erdin, Serkan; Bayram, Yavuz; Campbell, Ian M; Hunter, Jill V; Atik, Mehmed M; Van Esch, Hilde; Yuan, Bo; Wiszniewski, Wojciech; Isikay, Sedat; Yesil, Gozde; Yuregir, Ozge O; Tug Bozdogan, Sevcan; Aslan, Huseyin; Aydin, Hatip; Tos, Tulay; Aksoy, Ayse; De Vivo, Darryl C; Jain, Preti; Geckinli, B Bilge; Sezer, Ozlem; Gul, Davut; Durmaz, Burak; Cogulu, Ozgur; Ozkinay, Ferda; Topcu, Vehap; Candan, Sukru; Cebi, Alper Han; Ikbal, Mevlit; Yilmaz Gulec, Elif; Gezdirici, Alper; Koparir, Erkan; Ekici, Fatma; Coskun, Salih; Cicek, Salih; Karaer, Kadri; Koparir, Asuman; Duz, Mehmet Bugrahan; Kirat, Emre; Fenercioglu, Elif; Ulucan, Hakan; Seven, Mehmet; Guran, Tulay; Elcioglu, Nursel; Yildirim, Mahmut Selman; Aktas, Dilek; Alikaşifoğlu, Mehmet; Ture, Mehmet; Yakut, Tahsin; Overton, John D; Yuksel, Adnan; Ozen, Mustafa; Muzny, Donna M; Adams, David R; Boerwinkle, Eric; Chung, Wendy K; Gibbs, Richard A; Lupski, James R

    2015-11-01

    Development of the human nervous system involves complex interactions among fundamental cellular processes and requires a multitude of genes, many of which remain to be associated with human disease. We applied whole exome sequencing to 128 mostly consanguineous families with neurogenetic disorders that often included brain malformations. Rare variant analyses for both single nucleotide variant (SNV) and copy number variant (CNV) alleles allowed for identification of 45 novel variants in 43 known disease genes, 41 candidate genes, and CNVs in 10 families, with an overall potential molecular cause identified in >85% of families studied. Among the candidate genes identified, we found PRUNE, VARS, and DHX37 in multiple families and homozygous loss-of-function variants in AGBL2, SLC18A2, SMARCA1, UBQLN1, and CPLX1. Neuroimaging and in silico analysis of functional and expression proximity between candidate and known disease genes allowed for further understanding of genetic networks underlying specific types of brain malformations. PMID:26539891

  9. A proposal of a novel experimental procedure to genetically identify disease gene loci in humans.

    PubMed

    Muto, Taro

    2011-01-01

    Forward genetics in humans is beneficial in terms of diagnosis and treatment of genetic diseases, and discovery of gene functions. However, experimental mating is not possible among humans. In order to overcome this problem, I propose a novel experimental procedure to genetically identify human disease gene loci. To accomplish this, somatic cells from patients or their parents are reprogrammed to the pluripotent state, oogenesis is induced, the oocytes are parthenogenetically activated in the presence of cytochalasin, and embryonic stem cells are established from the parthenogenetic blastocysts. This protocol produces a set of diploid pluripotent stem cell clones having maternal and paternal chromosomes in different manners to each other. The genetic loci for the disease genes are determined through the conventional processes of positional cloning. Thus, taking advantage of the strategy proposed here, if the abnormality is reproducible using patient-derived pluripotent stem cells, a single carrier of the genetic mutations would be adequate to identify the disease gene loci. PMID:21422742

  10. A proposal of a novel experimental procedure to genetically identify disease gene loci in humans

    PubMed Central

    MUTO, Taro

    2011-01-01

    Forward genetics in humans is beneficial in terms of diagnosis and treatment of genetic diseases, and discovery of gene functions. However, experimental mating is not possible among humans. In order to overcome this problem, I propose a novel experimental procedure to genetically identify human disease gene loci. To accomplish this, somatic cells from patients or their parents are reprogrammed to the pluripotent state, oogenesis is induced, the oocytes are parthenogenetically activated in the presence of cytochalasin, and embryonic stem cells are established from the parthenogenetic blastocysts. This protocol produces a set of diploid pluripotent stem cell clones having maternal and paternal chromosomes in different manners to each other. The genetic loci for the disease genes are determined through the conventional processes of positional cloning. Thus, taking advantage of the strategy proposed here, if the abnormality is reproducible using patient-derived pluripotent stem cells, a single carrier of the genetic mutations would be adequate to identify the disease gene loci. PMID:21422742

  11. 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

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

    PubMed

    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

  13. 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

  14. A network-based approach to identify disease-associated gene modules through integrating DNA methylation and gene expression.

    PubMed

    Zhang, Yuanyuan; Zhang, Junying; Liu, Zhaowen; Liu, Yajun; Tuo, Shouheng

    2015-09-25

    Formation and progression of complex diseases are generally the joint effect of genetic and epigenetic disorders, thus an integrative analysis of epigenetic and genetic data is essential for understanding mechanism of the diseases. In this study, we integrate Illuminate 450k DNA methylation and gene expression data to calculate the weights of gene network using Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA). The approach considers all methylation values of CpG sites in a gene, rather than averaging them which was used in other studies ignoring the variability of the methylation sites. Through comparing topological features of control network with those of case network, including global and local features, candidate disease-associated genes and gene modules are identified. We apply the approach to real data, breast invasive carcinoma (BRCA). It successfully identifies susceptibility breast cancer-related genes, such as TP53, BRCA1, EP300, CDK2, MCM7 and so forth, within which most are previously known to breast cancer. Also, GO and pathway enrichment analysis indicate that these genes enrich in cell apoptosis and regulation of cell death which are cancer-related biological processes. Importantly, through analyzing the functions and comparing expression and methylation values of these genes between cases and controls, we find some genes, such as VASN, SNRPD3, and gene modules, targeted by POLR2C, CHMP1B and TAF9, which might be novel breast cancer-related biomarkers. PMID:26282201

  15. 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

  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 previously defined, functionally relevant gene sets, the present study also identified two novel genes sets: a gene set associated with pulmonary fibrosis and a gene set associated with ROS, underlining the advantage of using a data-driven approach to identify novel, functionally related gene sets. The results can be used in future gene set enrichment analysis studies involving NMs or as features for clustering and classifying NMs of diverse properties. PMID:26885455

  19. Molecular profiling of experimental endometriosis identified gene expression patterns in common with human disease

    PubMed Central

    Flores, Idhaliz; Rivera, Elizabeth; Ruiz, Lynnette A.; Santiago, Olga I.; Vernon, Michael W.; Appleyard, Caroline B.

    2007-01-01

    OBJECTIVE To validate a rat model of endometriosis using cDNA microarrays by identifying common gene expression patterns beween experimental and natural disease. DESIGN Autotransplantation rat model. SETTING Medical school department. ANIMALS Female Sprague-Dawley rats. INTERVENTIONS Endometriosis was surgically-induced by suturing uterine horn implants next to the small intestine’s mesentery. Control rats received sutures with no implants. After 60 days, endometriotic implants and uterine horn were obtained. MAIN OUTCOME MEASURES Gene expression levels determined by cDNA microarrays and QRT-PCR. METHODS Cy5-labeled cDNA was synthesized from total RNA obtained from endometriotic implants. Cy3-labeled cDNA was synthesized using uterine RNA from a control rat. Gene expression levels were analyzed after hybridizing experimental and control labeled cDNA to PIQOR™ Toxicology Rat Microarrays (Miltenyi Biotec) containing 1,252 known genes. Cy5/Cy3 ratios were determined and genes with >2-fold higher or <0.5-fold lower expression levels were selected. Microarray results were validated by QRT-PCR. RESULTS We observed differential expression of genes previously shown to be upregulated in patients, including growth factors, inflammatory cytokines/receptors, tumor invasion/metastasis factors, adhesion molecules, and anti-apoptotic factors. CONCLUSIONS This study presents evidence in support of using this rat model to study the natural history of endometriosis and test novel therapeutics for this incurable disease. PMID:17478174

  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?gene of KBD. Our results provide novel clues for revealing the pathogenesis of KBD and the biological function of FGF12. PMID:26290467

  3. Comparative gene expression analysis in mouse models for multiple sclerosis, Alzheimer’s disease and stroke for identifying commonly regulated and disease-specific gene changes

    PubMed Central

    Tseveleki, Vivian; Rubio, Renee; Vamvakas, Sotiris-Spyros; White, Joseph; Taoufik, Era; Petit, Edwige; Quackenbush, John; Probert, Lesley

    2014-01-01

    The brain responds to injury and infection by activating innate defense and tissue repair mechanisms. Working upon the hypothesis that the brain defense response involves common genes and pathways across diverse pathologies, we analysed global gene expression in brain from mouse models representing three major central nervous system disorders, cerebral stroke, multiple sclerosis and Alzheimer’s disease compared to normal brain using DNA microarray expression profiling. A comparison of dysregulated genes across disease models revealed common genes and pathways including key components of estrogen and TGF-β signaling pathways that have been associated with neuroprotection as well as a neurodegeneration mediator, TRPM7. Further, for each disease model, we discovered collections of differentially expressed genes that provide novel insight into the individual pathology and its associated mechanisms. Our data provide a resource for exploring the complex molecular mechanisms that underlie brain neurodegeneration and a new approach for identifying generic and disease-specific targets for therapy. PMID:20435134

  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. Long-range DNA looping and gene expression analyses identify DEXI as an autoimmune disease candidate gene.

    PubMed

    Davison, Lucy J; Wallace, Chris; Cooper, Jason D; Cope, Nathan F; Wilson, Nicola K; Smyth, Deborah J; Howson, Joanna M M; Saleh, Nada; Al-Jeffery, Abdullah; Angus, Karen L; Stevens, Helen E; Nutland, Sarah; Duley, Simon; Coulson, Richard M R; Walker, Neil M; Burren, Oliver S; Rice, Catherine M; Cambien, Francois; Zeller, Tanja; Munzel, Thomas; Lackner, Karl; Blakenberg, Stefan; Fraser, Peter; Gottgens, Berthold; Todd, John A; Attwood, Tony; Belz, Stephanie; Braund, Peter; Cambien, François; Cooper, Jason; Crisp-Hihn, Abi; Diemert, Patrick; Deloukas, Panos; Foad, Nicola; Erdmann, Jeanette; Goodall, Alison H; Gracey, Jay; Gray, Emma; Williams, Rhian G; Heimerl, Susanne; Hengstenberg, Christian; Jolley, Jennifer; Krishnan, Unni; Lloyd-Jones, Heather; Lugauer, Ingrid; Lundmark, Per; Maouche, Seraya; Moore, Jasbir S; Muir, David; Murray, Elizabeth; Nelson, Chris P; Neudert, Jessica; Niblett, David; O'Leary, Karen; Ouwehand, Willem H; Pollard, Helen; Rankin, Angela; Rice, Catherine M; Sager, Hendrik; Samani, Nilesh J; Sambrook, Jennifer; Schmitz, Gerd; Scholz, Michael; Schroeder, Laura; Schunkert, Heribert; Syvannen, Ann-Christine; Tennstedt, Stefanie; Wallace, Chris

    2012-01-15

    The chromosome 16p13 region has been associated with several autoimmune diseases, including type 1 diabetes (T1D) and multiple sclerosis (MS). CLEC16A has been reported as the most likely candidate gene in the region, since it contains the most disease-associated single-nucleotide polymorphisms (SNPs), as well as an imunoreceptor tyrosine-based activation motif. However, here we report that intron 19 of CLEC16A, containing the most autoimmune disease-associated SNPs, appears to behave as a regulatory sequence, affecting the expression of a neighbouring gene, DEXI. The CLEC16A alleles that are protective from T1D and MS are associated with increased expression of DEXI, and no other genes in the region, in two independent monocyte gene expression data sets. Critically, using chromosome conformation capture (3C), we identified physical proximity between the DEXI promoter region and intron 19 of CLEC16A, separated by a loop of >150 kb. In reciprocal experiments, a 20 kb fragment of intron 19 of CLEC16A, containing SNPs associated with T1D and MS, as well as with DEXI expression, interacted with the promotor region of DEXI but not with candidate DNA fragments containing other potential causal genes in the region, including CLEC16A. Intron 19 of CLEC16A is highly enriched for transcription-factor-binding events and markers associated with enhancer activity. Taken together, these data indicate that although the causal variants in the 16p13 region lie within CLEC16A, DEXI is an unappreciated autoimmune disease candidate gene, and illustrate the power of the 3C approach in progressing from genome-wide association studies results to candidate causal genes. PMID:21989056

  6. Long-range DNA looping and gene expression analyses identify DEXI as an autoimmune disease candidate gene

    PubMed Central

    Davison, Lucy J.; Wallace, Chris; Cooper, Jason D.; Cope, Nathan F.; Wilson, Nicola K.; Smyth, Deborah J.; Howson, Joanna M.M.; Saleh, Nada; Al-Jeffery, Abdullah; Angus, Karen L.; Stevens, Helen E.; Nutland, Sarah; Duley, Simon; Coulson, Richard M.R.; Walker, Neil M.; Burren, Oliver S.; Rice, Catherine M.; Cambien, Francois; Zeller, Tanja; Munzel, Thomas; Lackner, Karl; Blankenberg, Stefan; Fraser, Peter; Gottgens, Berthold; Todd, John A.

    2012-01-01

    The chromosome 16p13 region has been associated with several autoimmune diseases, including type 1 diabetes (T1D) and multiple sclerosis (MS). CLEC16A has been reported as the most likely candidate gene in the region, since it contains the most disease-associated single-nucleotide polymorphisms (SNPs), as well as an imunoreceptor tyrosine-based activation motif. However, here we report that intron 19 of CLEC16A, containing the most autoimmune disease-associated SNPs, appears to behave as a regulatory sequence, affecting the expression of a neighbouring gene, DEXI. The CLEC16A alleles that are protective from T1D and MS are associated with increased expression of DEXI, and no other genes in the region, in two independent monocyte gene expression data sets. Critically, using chromosome conformation capture (3C), we identified physical proximity between the DEXI promoter region and intron 19 of CLEC16A, separated by a loop of >150 kb. In reciprocal experiments, a 20 kb fragment of intron 19 of CLEC16A, containing SNPs associated with T1D and MS, as well as with DEXI expression, interacted with the promotor region of DEXI but not with candidate DNA fragments containing other potential causal genes in the region, including CLEC16A. Intron 19 of CLEC16A is highly enriched for transcription-factor-binding events and markers associated with enhancer activity. Taken together, these data indicate that although the causal variants in the 16p13 region lie within CLEC16A, DEXI is an unappreciated autoimmune disease candidate gene, and illustrate the power of the 3C approach in progressing from genome-wide association studies results to candidate causal genes. PMID:21989056

  7. 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 clarified the literature with regard to many previously suggested genes. PMID:21966275

  8. 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 genome-wide or fine mapping can be pursued by choosing different sets of profiling primers. A protocol for next-generation profiling is provided and will form the basis for novel applications. Using the current overview of genomic targets, a rational choice can be made for profiling primers to be employed. PMID:24099459

  9. 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

  10. Real-Time qPCR Identifies Suitable Reference Genes for Borna Disease Virus-Infected Rat Cortical Neurons

    PubMed Central

    Zhang, Lujun; Liu, Siwen; Zhang, Liang; You, Hongmin; Huang, Rongzhong; Sun, Lin; He, Peng; Chen, Shigang; Zhang, Hong; Xie, Peng

    2014-01-01

    Quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR) is the most commonly-used technique to identify gene expression profiles. The selection of stably expressed reference genes is a prerequisite to properly evaluating gene expression. Here, the suitability of commonly-used reference genes in normalizing RT-qPCR assays of mRNA expression in cultured rat cortical neurons infected with Borna disease virus (BDV) was assessed. The expressions of eight commonly-used reference genes were comparatively analyzed in BDV-infected rat cortical neurons and non-infected control neurons mainly across 9 and 12 days post-infection. These reference genes were validated by RT-qPCR and separately ranked by four statistical algorithms: geNorm, NormFinder, BestKeeper and the comparative delta-Ct method. Then, the RankAggreg package was used to construct consensus rankings. ARBP was found to be the most stable internal control gene at Day 9, and ACTB at Day 12. As the assessment of the validity of the selected reference genes confirms the suitability of applying a combination of the two most stable references genes, combining the two most stable genes for normalization of RT-qPCR studies in BDV-infected rat cortical neurons is recommended at each time point. This study can contribute to improving BDV research by providing the means by which to obtain more reliable and accurate gene expression measurements. PMID:25431926

  11. Real-time qPCR identifies suitable reference genes for Borna disease virus-infected rat cortical neurons.

    PubMed

    Zhang, Lujun; Liu, Siwen; Zhang, Liang; You, Hongmin; Huang, Rongzhong; Sun, Lin; He, Peng; Chen, Shigang; Zhang, Hong; Xie, Peng

    2014-01-01

    Quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR) is the most commonly-used technique to identify gene expression profiles. The selection of stably expressed reference genes is a prerequisite to properly evaluating gene expression. Here, the suitability of commonly-used reference genes in normalizing RT-qPCR assays of mRNA expression in cultured rat cortical neurons infected with Borna disease virus (BDV) was assessed. The expressions of eight commonly-used reference genes were comparatively analyzed in BDV-infected rat cortical neurons and non-infected control neurons mainly across 9 and 12 days post-infection. These reference genes were validated by RT-qPCR and separately ranked by four statistical algorithms: geNorm, NormFinder, BestKeeper and the comparative delta-Ct method. Then, the RankAggreg package was used to construct consensus rankings. ARBP was found to be the most stable internal control gene at Day 9, and ACTB at Day 12. As the assessment of the validity of the selected reference genes confirms the suitability of applying a combination of the two most stable references genes, combining the two most stable genes for normalization of RT-qPCR studies in BDV-infected rat cortical neurons is recommended at each time point. This study can contribute to improving BDV research by providing the means by which to obtain more reliable and accurate gene expression measurements. PMID:25431926

  12. Transcriptional Profiling of Human Liver Identifies Sex-Biased Genes Associated with Polygenic Dyslipidemia and Coronary Artery Disease

    PubMed Central

    Zhang, Yijing; Klein, Kathrin; Sugathan, Aarathi; Nassery, Najlla; Dombkowski, Alan; Zanger, Ulrich M.; Waxman, David J.

    2011-01-01

    Sex-differences in human liver gene expression were characterized on a genome-wide scale using a large liver sample collection, allowing for detection of small expression differences with high statistical power. 1,249 sex-biased genes were identified, 70% showing higher expression in females. Chromosomal bias was apparent, with female-biased genes enriched on chrX and male-biased genes enriched on chrY and chr19, where 11 male-biased zinc-finger KRAB-repressor domain genes are distributed in six clusters. Top biological functions and diseases significantly enriched in sex-biased genes include transcription, chromatin organization and modification, sexual reproduction, lipid metabolism and cardiovascular disease. Notably, sex-biased genes are enriched at loci associated with polygenic dyslipidemia and coronary artery disease in genome-wide association studies. Moreover, of the 8 sex-biased genes at these loci, 4 have been directly linked to monogenic disorders of lipid metabolism and show an expression profile in females (elevated expression of ABCA1, APOA5 and LDLR; reduced expression of LIPC) that is consistent with the lower female risk of coronary artery disease. Female-biased expression was also observed for CYP7A1, which is activated by drugs used to treat hypercholesterolemia. Several sex-biased drug-metabolizing enzyme genes were identified, including members of the CYP, UGT, GPX and ALDH families. Half of 879 mouse orthologs, including many genes of lipid metabolism and homeostasis, show growth hormone-regulated sex-biased expression in mouse liver, suggesting growth hormone might play a similar regulatory role in human liver. Finally, the evolutionary rate of protein coding regions for human-mouse orthologs, revealed by dN/dS ratio, is significantly higher for genes showing the same sex-bias in both species than for non-sex-biased genes. These findings establish that human hepatic sex differences are widespread and affect diverse cell metabolic processes, and may help explain sex differences in lipid profiles associated with sex differential risk of coronary artery disease. PMID:21858147

  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. CARD15 gene polymorphisms in patients with spondyloarthropathies identify a specific phenotype previously related to Crohn's disease

    PubMed Central

    Laukens, D; Peeters, H; Marichal, D; Vander, C; Mielants, H; Elewaut, D; Demetter, P; Cuvelier, C; Van Den Berghe, M; Rottiers, P; Veys, E; Remaut, E; Steidler, L; De Keyser, F; De Vos, M

    2005-01-01

    Background: The association between spondyloarthropathy and Crohn's disease is well known. A risk for evolution to Crohn's disease has already been shown in the subgroup of patients with spondyloarthropathy associated with chronic gut inflammation. Objective: To investigate whether the reported polymorphisms in the CARD15 gene, a susceptibility gene for Crohn's disease, are associated with the presence of preclinical intestinal inflammation observed in spondyloarthropathies. Methods: 104 patients with spondyloarthropathies were studied. All underwent ileocolonoscopy with biopsies between 1983 and 2004. The prevalence of three single nucleotide polymorphisms in the CARD15 gene (R702W, G908R, and 1007fs) was assessed using restriction fragment length polymorphism–polymerase chain reaction (RFLP-PCR); the patients were compared with an ethnically matched Crohn's disease population and a control population. Results: The carrier frequency of R702W, G908R, or 1007fs variants in the spondyloarthropathy populations (20%) was similar to the control population (17%), but increased to 38% in the spondyloarthropathy subgroup with chronic gut inflammation. This frequency was significantly higher than in the other spondyloarthropathy subgroups (p = 0.001) or the control group (p = 0.006), but not different from the Crohn's disease group (49%) (NS). This indicates that CARD15 polymorphisms are associated with a higher risk for development of chronic gut inflammation. Conclusions: CARD15 gene polymorphisms clearly identify a subgroup of patients with spondyloarthropathies associated with chronic intestinal inflammation. PMID:15539413

  15. Rare copy number variations in congenital heart disease patients identify unique genes in left-right patterning

    PubMed Central

    Fakhro, Khalid A.; Choi, Murim; Ware, Stephanie M.; Belmont, John W.; Towbin, Jeffrey A.; Lifton, Richard P.; Khokha, Mustafa K.; Brueckner, Martina

    2011-01-01

    Dominant human genetic diseases that impair reproductive fitness and have high locus heterogeneity constitute a problem for gene discovery because the usual criterion of finding more mutations in specific genes than expected by chance may require extremely large populations. Heterotaxy (Htx), a congenital heart disease resulting from abnormalities in left-right (LR) body patterning, has features suggesting that many cases fall into this category. In this setting, appropriate model systems may provide a means to support implication of specific genes. By high-resolution genotyping of 262 Htx subjects and 991 controls, we identify a twofold excess of subjects with rare genic copy number variations in Htx (14.5% vs. 7.4%, P = 1.5 × 10−4). Although 7 of 45 Htx copy number variations were large chromosomal abnormalities, 38 smaller copy number variations altered a total of 61 genes, 22 of which had Xenopus orthologs. In situ hybridization identified 7 of these 22 genes with expression in the ciliated LR organizer (gastrocoel roof plate), a marked enrichment compared with 40 of 845 previously studied genes (sevenfold enrichment, P < 10−6). Morpholino knockdown in Xenopus of Htx candidates demonstrated that five (NEK2, ROCK2, TGFBR2, GALNT11, and NUP188) strongly disrupted both morphological LR development and expression of pitx2, a molecular marker of LR patterning. These effects were specific, because 0 of 13 control genes from rare Htx or control copy number variations produced significant LR abnormalities (P = 0.001). These findings identify genes not previously implicated in LR patterning. PMID:21282601

  16. 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...

  17. 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

  18. Exome Sequencing Identifies DLG1 as a Novel Gene for Potential Susceptibility to Crohn's Disease in a Chinese Family Study

    PubMed Central

    Song, Lu; NG, Siew Chien; Wang, Xiaobing; Chen, Liping; Yi, Fengming; Ran, Zhihua; Zhou, Rui; Xia, Bing

    2014-01-01

    Background Genetic variants make some contributions to inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC). More than 100 susceptibility loci were identified in Western IBD studies, but susceptibility gene has not been found in Chinese IBD patients till now. Sequencing of individuals with an IBD family history is a powerful approach toward our understanding of the genetics and pathogenesis of IBD. The aim of this study, which focuses on a Han Chinese CD family, is to identify high-risk variants and potentially novel loci using whole exome sequencing technique. Methods Exome sequence data from 4 individuals belonging to a same family were analyzed using bioinformatics methods to narrow down the variants associated with CD. The potential risk genes were further analyzed by genotyping and Sanger sequencing in family members, additional 401 healthy controls (HC), 278 sporadic CD patients, 123 UC cases, a pair of monozygotic CD twins and another Chinese CD family. Results From the CD family in which the father and daughter were affected, we identified a novel single nucleotide variant (SNV) c.374T>C (p.I125T) in exon 4 of discs large homolog 1 (DLG1), a gene has been reported to play mutiple roles in cell proliferation, T cell polarity and T cell receptor signaling. After genotyping among case and controls, a PLINK analysis showed the variant was of significance (P<0.05). 4 CD patients of the other Chinese family bore another non-synonymous variant c.833G>A (p.R278Q) in exon 9 of DLG1. Conclusions We have discovered novel genetic variants in the coding regions of DLG1 gene, the results support that DLG1 is a novel potential susceptibility gene for CD in Chinese patients. PMID:24937328

  19. Combined NGS Approaches Identify Mutations in the Intraflagellar Transport Gene IFT140 in Skeletal Ciliopathies with Early Progressive Kidney Disease

    PubMed Central

    Schmidts, Miriam; Frank, Valeska; Eisenberger, Tobias; al Turki, Saeed; Bizet, Albane A.; Antony, Dinu; Rix, Suzanne; Decker, Christian; Bachmann, Nadine; Bald, Martin; Vinke, Tobias; Toenshoff, Burkhard; Donato, Natalia Di; Neuhann, Theresa; Hartley, Jane L.; Maher, Eamonn R.; Bogdanović, Radovan; Peco-Antić, Amira; Mache, Christoph; Hurles, Matthew E.; Joksić, Ivana; Guć-Šćekić, Marija; Dobricic, Jelena; Brankovic-Magic, Mirjana; Bolz, Hanno J.; Pazour, Gregory J.; Beales, Philip L.; Scambler, Peter J.; Saunier, Sophie; Mitchison, Hannah M.; Bergmann, Carsten

    2014-01-01

    Ciliopathies are genetically heterogeneous disorders characterized by variable expressivity and overlaps between different disease entities. This is exemplified by the short rib-polydactyly syndromes, Jeune, Sensenbrenner, and Mainzer-Saldino chondrodysplasia syndromes. These three syndromes are frequently caused by mutations in intraflagellar transport (IFT) genes affecting the primary cilia, which play a crucial role in skeletal and chondral development. Here, we identified mutations in IFT140, an IFT complex A gene, in five Jeune asphyxiating thoracic dystrophy (JATD) and two Mainzer-Saldino syndrome (MSS) families, by screening a cohort of 66 JATD/MSS patients using whole exome sequencing and targeted resequencing of a customized ciliopathy gene panel. We also found an enrichment of rare IFT140 alleles in JATD compared with nonciliopathy diseases, implying putative modifier effects for certain alleles. IFT140 patients presented with mild chest narrowing, but all had end-stage renal failure under 13 years of age and retinal dystrophy when examined for ocular dysfunction. This is consistent with the severe cystic phenotype of Ift140 conditional knockout mice, and the higher level of Ift140 expression in kidney and retina compared with the skeleton at E15.5 in the mouse. IFT140 is therefore a major cause of cono-renal syndromes (JATD and MSS). The present study strengthens the rationale for IFT140 screening in skeletal ciliopathy spectrum patients that have kidney disease and/or retinal dystrophy. PMID:23418020

  20. 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...

  1. 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...

  2. Genome-Wide Gene-Environment Study Identifies Glutamate Receptor Gene GRIN2A as a Parkinson's Disease Modifier Gene via Interaction with Coffee

    PubMed Central

    Hamza, Taye H.; Chen, Honglei; Hill-Burns, Erin M.; Rhodes, Shannon L.; Montimurro, Jennifer; Kay, Denise M.; Tenesa, Albert; Kusel, Victoria I.; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W.; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M.; Kendler, Kenneth S.; Bacanu, Silviu-Alin; Scott, William K.; Ritz, Beate; Nutt, John; Factor, Stewart A.; Zabetian, Cyrus P.; Payami, Haydeh

    2011-01-01

    Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2df<5×10−8 in GWAIS, and OR = 0.41, P = 3×10−8 in heavy coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that are missed in GWAS. Both adenosine antagonists (caffeine-like) and glutamate antagonists (GRIN2A-related) are being tested in clinical trials for treatment of PD. GRIN2A may be a useful pharmacogenetic marker for subdividing individuals in clinical trials to determine which medications might work best for which patients. PMID:21876681

  3. 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

  4. 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

  5. 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

  6. Analysis of SNPs with an effect on gene expression identifies UBE2L3 and BCL3 as potential new risk genes for Crohn's disease.

    PubMed

    Fransen, Karin; Visschedijk, Marijn C; van Sommeren, Suzanne; Fu, Jinyuan Y; Franke, Lude; Festen, Eleonora A M; Stokkers, Pieter C F; van Bodegraven, Adriaan A; Crusius, J Bart A; Hommes, Daniel W; Zanen, Pieter; de Jong, Dirk J; Wijmenga, Cisca; van Diemen, Cleo C; Weersma, Rinse K

    2010-09-01

    Genome-wide association studies (GWAS) for Crohn's disease (CD) have identified loci explaining approximately 20% of the total genetic risk of CD. Part of the other genetic risk loci is probably partly hidden among signals discarded by the multiple testing correction needed in the analysis of GWAS data. Strategies for finding these hidden loci require large replication cohorts and are costly to perform. We adopted a strategy of selecting SNPs for follow-up that showed a correlation to gene expression [cis-expression quantitative trait loci (eQTLs)] since these have been shown more likely to be trait-associated. First we show that there is an overrepresentation of cis-eQTLs in the known CD-associated loci. Then SNPs were selected for follow-up by screening the top 500 SNP hits from a CD GWAS data set. We identified 10 cis-eQTL SNPs. These 10 SNPs were tested for association with CD in two independent cohorts of Dutch CD patients (1539) and healthy controls (2648). In a combined analysis, we identified two cis-eQTL SNPs that were associated with CD rs2298428 in UBE2L3 (P=5.22x10(-5)) and rs2927488 in BCL3 (P=2.94x10(-4)). After adding additional publicly available data from a previously reported meta-analysis, the association with rs2298428 almost reached genome-wide significance (P=2.40x10(-7)) and the association with rs2927488 was corroborated (P=6.46x10(-4)). We have identified UBE2L3 and BCL3 as likely novel risk genes for CD. UBE2L3 is also associated with other immune-mediated diseases. These results show that eQTL-based pre-selection for follow-up is a useful approach for identifying risk loci from a moderately sized GWAS. PMID:20601676

  7. Comparison of expression profiles in ovarian epithelium in vivo and ovarian cancer identifies novel candidate genes involved in disease pathogenesis.

    PubMed

    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 to the development of ovarian cancer. PMID:21423607

  8. Stratified gene expression analysis identifies major amyotrophic lateral sclerosis genes.

    PubMed

    Jones, Ashley R; Troakes, Claire; King, Andrew; Sahni, Vibhu; De Jong, Simone; Bossers, Koen; Papouli, Efterpi; Mirza, Muddassar; Al-Sarraj, Safa; Shaw, Christopher E; Shaw, Pamela J; Kirby, Janine; Veldink, Jan H; Macklis, Jeffrey D; Powell, John F; Al-Chalabi, Ammar

    2015-05-01

    Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of motor neurons resulting in progressive paralysis. Gene expression studies of ALS only rarely identify the same gene pathways as gene association studies. We hypothesized that analyzing tissues by matching on degree of disease severity would identify different patterns of gene expression from a traditional case-control comparison. We analyzed gene expression changes in 4 postmortem central nervous system regions, stratified by severity of motor neuron loss. An overall comparison of cases (n = 6) and controls (n = 3) identified known ALS gene, SOX5, as showing differential expression (log2 fold change = 0.09, p = 5.5 × 10(-5)). Analyses stratified by disease severity identified expression changes in C9orf72 (p = 2.77 × 10(-3)), MATR3 (p = 3.46 × 10(-3)), and VEGFA (p = 8.21 × 10(-4)), all implicated in ALS through genetic studies, and changes in other genes in pathways involving RNA processing and immune response. These findings suggest that analysis of gene expression stratified by disease severity can identify major ALS genes and may be more efficient than traditional case-control comparison. PMID:25801576

  9. Suppressors of the arabidopsis lsd5 cell death mutation identify genes involved in regulating disease resistance responses.

    PubMed Central

    Morel, J B; Dangl, J L

    1999-01-01

    Cell death is associated with the development of the plant disease resistance hypersensitive reaction (HR). Arabidopsis lsd mutants that spontaneously exhibit cell death reminiscent of the HR were identified previously. To study further the regulatory context in which cell death acts during disease resistance, one of these mutants, lsd5, was used to isolate new mutations that suppress its cell death phenotype. Using a simple lethal screen, nine lsd5 cell death suppressors, designated phx (for the mythological bird Phoenix that rises from its ashes), were isolated. These mutants were characterized with respect to their response to a bacterial pathogen and oomycete parasite. The strongest suppressors-phx2, 3, 6, and 11-1-showed complex, differential patterns of disease resistance modifications. These suppressors attenuated disease resistance to avirulent isolates of the biotrophic Peronospora parasitica pathogen, but only phx2 and phx3 altered disease resistance to avirulent strains of Pseudomonas syringae pv tomato. Therefore, some of these phx mutants define common regulators of cell death and disease resistance. In addition, phx2 and phx3 exhibited enhanced disease susceptibility to different virulent pathogens, confirming probable links between the disease resistance and susceptibility pathways. PMID:9872969

  10. 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

  11. Positively Selected Disease Response Orthologous Gene Sets in the Cereals Identified Using Sorghum bicolor L. Moench Expression Profiles and Comparative Genomics

    PubMed Central

    Zamora, Alejandro; Sun, Qi; Hamblin, Martha T.; Aquadro, Charles F.; Kresovich, Stephen

    2009-01-01

    Disease response genes (DRGs) diverge under recurrent positive selection as a result of a molecular arms race between hosts and pathogens. Most of these studies were conducted in animals, and few defense genes have been shown to evolve adaptively in plants. To test for adaptation in the molecules mediating disease resistance in the cereals, we first combined information from the expression pattern of Sorghum bicolor genes and from divergence to the full genome of rice to identify candidate DRGs. We then used evolutionary analyses of orthologous gene sets from several grass species, to determine whether the DRGs show signals of positive selection and the residues targeted. We found 140 divergent genes upregulated under biotic stress in S. bicolor by evaluating the relative abundance of expressed sequence tags in different libraries and comparing them with rice genes. For 10 of these genes, we found sets of orthologs including sequences from rice and three other cereals; six genes showed a pattern of substitution that was consistent with positive selection. Three of these genes, a thaumatin, a peroxidase, and a barley mlo homolog, are known antifungal proteins. The other three genes with evidence of positive selection were a MCM-1 agamous deficiens SRF- (MADS) box transcription factor, an eIF5 translation initiation factor, and a gene of unknown function but with evidence of expression during stress. Permutation analyses, using different ortholog and paralog sequences, consistently identified five positively selected codons in the peroxidase, a member of a cluster of genes and a large gene family. We mapped the positively selected residues onto the structure of the peroxidase and thaumatin and found that all sites are on the surface of these proteins and several are close to biochemically determined active sites. Identifying new positively selected plant disease resistance genes and the critical amino acid sites provides a basis for functional studies that may increase our understanding of their underlying molecular mechanisms of action. Additionally, it may lead to the identification of individuals having variation at functionally important sites, as well as eventually using this information in the rational design and engineering of proteins involved in plant disease resistance. PMID:19506000

  12. Genome-wide haplotype association study identify TNFRSF1A, CASP7, LRP1B, CDH1 and TG genes associated with Alzheimer's disease in Caribbean Hispanic individuals

    PubMed Central

    Shang, Zhenwei; Lv, Hongchao; Zhang, Mingming; Duan, Lian; Wang, Situo; Li, Jin; Liu, Guiyou; Ruijie, Zhang; Jiang, Yongshuai

    2015-01-01

    Alzheimer's disease (AD) is an acquired disorder of cognitive and behavioral impairment. It is considered to be caused by variety of factors, such as age, environment and genetic factors. In order to identify the genetic affect factors of AD, we carried out a bioinformatic approach which combined genome-wide haplotype-based association study with gene prioritization. The raw SNP genotypes data was downloaded from GEO database (GSE33528). It contains 615 AD patients and 560 controls of Caribbean Hispanic individuals. Firstly, we identified the linkage disequilibrium (LD) haplotype blocks and performed genome-wide haplotype association study to screen significant haplotypes that were associated with AD. Then we mapped these significant haplotypes to genes and obtained candidate genes set for AD. At last, we prioritized AD candidate genes based on their similarity with 36 known AD genes, so as to identify AD related genes. The results showed that 141 haplotypes on 134 LD blocks were significantly associated with AD (P<1E-4), and these significant haplotypes were mapped to 132 AD candidate genes. After prioritizing these candidate genes, we found seven AD related genes: APOE, APOC1, TNFRSF1A, LRP1B, CDH1, TG and CASP7. Among these genes, APOE and APOC1 are known AD risk genes. For the other five genes TNFRSF1A, CDH1, CASP7, LRP1B and TG, this is the first genetic association study which showed the significant association between these five genes and AD susceptibility in Caribbean Hispanic individuals. We believe that our findings can provide a new perspective to understand the genetic affect factors of AD. PMID:26621834

  13. 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

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

    PubMed

    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

  15. 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

  16. Identifying gene regulatory networks in schizophrenia.

    PubMed

    Potkin, Steven G; Macciardi, Fabio; Guffanti, Guia; Fallon, James H; Wang, Qi; Turner, Jessica A; Lakatos, Anita; Miles, Michael F; Lander, Arthur; Vawter, Marquis P; Xie, Xiaohui

    2010-11-15

    The imaging genetics approach to studying the genetic basis of disease leverages the individual strengths of both neuroimaging and genetic studies by visualizing and quantifying the brain activation patterns in the context of genetic background. Brain imaging as an intermediate phenotype can help clarify the functional link among genes, the molecular networks in which they participate, and brain circuitry and function. Integrating genetic data from a genome-wide association study (GWAS) with brain imaging as a quantitative trait (QT) phenotype can increase the statistical power to identify risk genes. A QT analysis using brain imaging (DLPFC activation during a working memory task) as a quantitative trait has identified unanticipated risk genes for schizophrenia. Several of these genes (RSRC1, ARHGAP18, ROBO1-ROBO2, GPC1, TNIK, and CTXN3-SLC12A2) have functions related to progenitor cell proliferation, migration, and differentiation, cytoskeleton reorganization, axonal connectivity, and development of forebrain structures. These genes, however, do not function in isolation but rather through gene regulatory networks. To obtain a deeper understanding how the GWAS-identified genes participate in larger gene regulatory networks, we measured correlations among transcript levels in the mouse and human postmortem tissue and performed a gene set enrichment analysis (GSEA) that identified several microRNA associated with schizophrenia (448, 218, 137). The results of such computational approaches can be further validated in animal experiments in which the networks are experimentally studied and perturbed with specific compounds. Glypican 1 and FGF17 mouse models for example, can be used to study such gene regulatory networks. The model demonstrates epistatic interactions between FGF and glypican on brain development and may be a useful model of negative symptom schizophrenia. PMID:20600988

  17. 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

  18. 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

  19. 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

  20. A module-based analytical strategy to identify novel disease-associated genes shows an inhibitory role for interleukin 7 Receptor in allergic inflammation

    PubMed Central

    Mobini, Reza; Andersson, Bengt A; Erjefält, Jonas; Hahn-Zoric, Mirjana; Langston, Michael A; Perkins, Andy D; Cardell, Lars Olaf; Benson, Mikael

    2009-01-01

    Background The identification of novel genes by high-throughput studies of complex diseases is complicated by the large number of potential genes. However, since disease-associated genes tend to interact, one solution is to arrange them in modules based on co-expression data and known gene interactions. The hypothesis of this study was that such a module could be a) found and validated in allergic disease and b) used to find and validate one ore more novel disease-associated genes. Results To test these hypotheses integrated analysis of a large number of gene expression microarray experiments from different forms of allergy was performed. This led to the identification of an experimentally validated reference gene that was used to construct a module of co-expressed and interacting genes. This module was validated in an independent material, by replicating the expression changes in allergen-challenged CD4+ cells. Moreover, the changes were reversed following treatment with corticosteroids. The module contained several novel disease-associated genes, of which the one with the highest number of interactions with known disease genes, IL7R, was selected for further validation. The expression levels of IL7R in allergen challenged CD4+ cells decreased following challenge but increased after treatment. This suggested an inhibitory role, which was confirmed by functional studies. Conclusion We propose that a module-based analytical strategy is generally applicable to find novel genes in complex diseases. PMID:19216740

  1. New Genes Tied to Alzheimer's Disease

    MedlinePlus

    ... Matters November 4, 2013 New Genes Tied to Alzheimer’s Disease Researchers identified 11 new genes that affect the risk for Alzheimer’s disease. The findings point to novel targets for preventing ...

  2. 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

  3. Human genes and diseases

    SciTech Connect

    Blasi, F.

    1986-01-01

    This book consists of 16 chapters. Some of the chapter titles are: Towards a complete linkage map of he X-chromosome; The role of HPRT genes in human disease; Human plasminogen activators. Genes and proteins structure; Metallothionein gene regulation in Menke's Disease; Molecular genetics of human B cell neoplasia, The erb-B related growth factors receptors, and Aldolase gene and protein families: structure, expression and molecular pathophysiology.

  4. A Parkinson's disease gene regulatory network identifies the signaling protein RGS2 as a modulator of LRRK2 activity and neuronal toxicity

    PubMed Central

    Dusonchet, Julien; Li, Hu; Guillily, Maria; Liu, Min; Stafa, Klodjan; Derada Troletti, Claudio; Boon, Joon Y.; Saha, Shamol; Glauser, Liliane; Mamais, Adamantios; Citro, Allison; Youmans, Katherine L.; Liu, LiQun; Schneider, Bernard L.; Aebischer, Patrick; Yue, Zhenyu; Bandopadhyay, Rina; Glicksman, Marcie A.; Moore, Darren J.; Collins, James J.; Wolozin, Benjamin

    2014-01-01

    Mutations in LRRK2 are one of the primary genetic causes of Parkinson's disease (PD). LRRK2 contains a kinase and a GTPase domain, and familial PD mutations affect both enzymatic activities. However, the signaling mechanisms regulating LRRK2 and the pathogenic effects of familial mutations remain unknown. Identifying the signaling proteins that regulate LRRK2 function and toxicity remains a critical goal for the development of effective therapeutic strategies. In this study, we apply systems biology tools to human PD brain and blood transcriptomes to reverse-engineer a LRRK2-centered gene regulatory network. This network identifies several putative master regulators of LRRK2 function. In particular, the signaling gene RGS2, which encodes for a GTPase-activating protein (GAP), is a key regulatory hub connecting the familial PD-associated genes DJ-1 and PINK1 with LRRK2 in the network. RGS2 expression levels are reduced in the striata of LRRK2 and sporadic PD patients. We identify RGS2 as a novel interacting partner of LRRK2 in vivo. RGS2 regulates both the GTPase and kinase activities of LRRK2. We show in mammalian neurons that RGS2 regulates LRRK2 function in the control of neuronal process length. RGS2 is also protective against neuronal toxicity of the most prevalent mutation in LRRK2, G2019S. We find that RGS2 regulates LRRK2 function and neuronal toxicity through its effects on kinase activity and independently of GTPase activity, which reveals a novel mode of action for GAP proteins. This work identifies RGS2 as a promising target for interfering with neurodegeneration due to LRRK2 mutations in PD patients. PMID:24794857

  5. 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- ...

  6. Genome-wide analysis of copy number variation identifies candidate gene loci associated with the progression of non-alcoholic fatty liver disease.

    PubMed

    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

  7. 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

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

    PubMed

    Cossard, Raynald; Esposito, Michela; Sellem, Carole H; Pitayu, Laras; Vasnier, Christelle; Delahodde, Agns; 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

  9. 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

  10. 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 ' ... 30, 2016 MONDAY, May 30, 2016 (HealthDay News) -- New gene screening methods may greatly improve doctors' ability ...

  11. Identifying Common Genes and Networks in Multi-Organ Fibrosis

    PubMed Central

    Wenzke, Kevin E.; Cantemir-Stone, Carmen; Zhang, Jie; Marsh, Clay B.; Huang, Kun

    2012-01-01

    Fibroproliferative diseases of organs are poorly understood and generally lack effective anti-fibrotic treatments. Our goal was to identify the key regulatory factors in pathologic fibrosis, common between organ-based fibrotic disease. We analyzed 9 microarray datasets publicly available in the GEO datasets from lung, heart, liver and kidney fibrotic disease tissue (489 microarrays total, disease and control). We identified a set of 90 genes differentially expressed in at least five microarray datasets. We used IPA and DAVID analysis to identify gene networks and their molecular functions. A mutual information based network work activity analysis showed that a connective tissue disorders network was the most active for all types of fibrosis included in this analysis. Conclusion: Our analysis indicates that despite different disease manifestation, organ fibrosis share a specific set of genes suggesting the potential for a common origin. PMID:22779061

  12. 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.

  13. Integrated Analyses of Genome-Wide DNA Occupancy and Expression Profiling Identify Key Genes and Pathways Involved in Cellular Transformation by a Marek's Disease Virus Oncoprotein, Meq

    PubMed Central

    Subramaniam, Sugalesini; Johnston, John; Preeyanon, Likit; Brown, C. Titus; Kung, Hsing-Jien

    2013-01-01

    Marek's disease (MD) is an economically significant disease in chickens that is caused by the highly oncogenic Marek's disease virus (MDV). A major unanswered question is the mechanism of MDV-induced tumor formation. Meq, a bZIP transcription factor discovered in the 1990s, is critically involved in viral oncogenicity, but only a few of its host target genes have been described, impeding our understanding of MDV-induced tumorigenesis. Using chromatin immunoprecipitation-sequencing (ChIP-seq) and microarray analysis, a high-confidence list of Meq binding sites in the chicken genome and a global transcriptome of Meq-responsive genes were generated. Meq binding sites were found to be enriched in the promoter regions of upregulated genes but not in those of downregulated genes. ChIP-seq was also performed for c-Jun, a known heterodimeric partner of Meq. The close location of binding sites of Meq and c-Jun was noted, suggesting cooperativity between these two factors in modulating transcription. Pathway analysis indicated that Meq transcriptionally regulates many genes that are part of several signaling pathways including the extracellular signal-regulated kinase /mitogen-activated protein kinase (ERK/MAPK), Jak-STAT, and ErbB pathways, which are critical for oncogenesis and/or include signaling mediators involved in apoptosis. Meq activates oncogenic signaling cascades by transcriptionally activating major kinases in the ERK/MAPK pathway and simultaneously repressing phosphatases, as verified using inhibitors of MEK and ERK1/2 in a cell proliferation assay. This study provides significant insights into the mechanistic basis of Meq-dependent cell transformation. PMID:23740999

  14. The Meaning of Clinical Remission in Polyarticular Juvenile Idiopathic Arthritis: Gene Expression Profiling in Peripheral Blood Mononuclear Cells Identifies Distinct Disease States

    PubMed Central

    Knowlton, Nicholas; Jiang, Kaiyu; Frank, Mark Barton; Aggarwal, Amita; Wallace, Carol; McKee, Ryan; Chaser, Brad; Tung, Catherine; Smith, Laura; Chen, Yanmin; Osban, Jeanette; O’Neil, Kathleen; Centola, Michael; McGhee, Julie L.; Jarvis, James N.

    2009-01-01

    Objective The development of biomarkers to predict response to therapy in polyarticular juvenile idiopathic arthritis (JIA) is an important issue in pediatric rheumatology. An critical step in this process is determining whether there is biological meaning to clinically derived terms such as “active disease” and “remission.” We used a systems biology approach to address this question. Methods We performed gene transcriptional profiling on children who fit criteria for specific disease states as defined by consensus criteria developed by Wallace et al. (J Rheumatol 2005). Children with active disease (AD, n=14), clinical remission on medication (CRM, n=9) and clinical remission off medication (CR, n=6) were studied, in addition to healthy control children (n=13). Transcriptional profiles in peripheral blood mononuclear cells (PBMC) were obtained using Affymetrix U133 Plus 2.0 Arrays. Results Hierarchical cluster analysis and predictive modeling demonstrated that the clinically-derived criteria represent biologically-distinct states. Minimal differences were seen between children with AD and those with CRM. Thus, underlying immune/inflammatory abnormalities persist despite response to therapy. The PBMC transcriptional profiles of children in remission did not return to normal, but revealed networks of pro- and anti-inflammatory genes suggesting that “remission” is a state of homeostasis, not a return to normal. Conclusions Gene transcriptional profiling of PBMC reveals that clinically-derived criteria for JIA disease states reflect underlying biology. We also demonstrate that neither CRM nor CR states result in resolution of the underlying inflammatory process, but are more likely to be states of balanced homeostasis between pro- and anti-inflammatory mechanisms. PMID:19248118

  15. 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

  16. Network Topology Reveals Key Cardiovascular Disease Genes

    PubMed Central

    Stojković, Neda; Radak, Djordje; Pržulj, Nataša

    2013-01-01

    The structure of protein-protein interaction (PPI) networks has already been successfully used as a source of new biological information. Even though cardiovascular diseases (CVDs) are a major global cause of death, many CVD genes still await discovery. We explore ways to utilize the structure of the human PPI network to find important genes for CVDs that should be targeted by drugs. The hope is to use the properties of such important genes to predict new ones, which would in turn improve a choice of therapy. We propose a methodology that examines the PPI network wiring around genes involved in CVDs. We use the methodology to identify a subset of CVD-related genes that are statistically significantly enriched in drug targets and “driver genes.” We seek such genes, since driver genes have been proposed to drive onset and progression of a disease. Our identified subset of CVD genes has a large overlap with the Core Diseasome, which has been postulated to be the key to disease formation and hence should be the primary object of therapeutic intervention. This indicates that our methodology identifies “key” genes responsible for CVDs. Thus, we use it to predict new CVD genes and we validate over 70% of our predictions in the literature. Finally, we show that our predicted genes are functionally similar to currently known CVD drug targets, which confirms a potential utility of our methodology towards improving therapy for CVDs. PMID:23977067

  17. 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

  18. 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

  19. 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

  20. Gene Therapy for Skin Diseases

    PubMed Central

    Gorell, Emily; Nguyen, Ngon; Lane, Alfred; Siprashvili, Zurab

    2014-01-01

    The skin possesses qualities that make it desirable for gene therapy, and studies have focused on gene therapy for multiple cutaneous diseases. Gene therapy uses a vector to introduce genetic material into cells to alter gene expression, negating a pathological process. This can be accomplished with a variety of viral vectors or nonviral administrations. Although results are promising, there are several potential pitfalls that must be addressed to improve the safety profile to make gene therapy widely available clinically. PMID:24692191

  1. 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

    ABSTRACT Marek's disease (MD) is a lymphoproliferative disease of chickens caused by the oncogenic Gallid herpesvirus 2, commonly known as Marek's disease virus (MDV). MD vaccines, the primary control method, are often generated by repeated in vitro serial passage of this highly cell-associated virus to attenuate virulent MDV strains. To understand the genetic basis of attenuation, we used experimental evolution by serially passing three virulent MDV replicates generated from an infectious bacterial artificial chromosome (BAC) clone. All replicates became completely or highly attenuated, indicating that de novo mutation, and not selection among quasispecies existing in a strain, is the primary driving force for the reduction in virulence. Sequence analysis of the attenuated replicates revealed 41 to 95 single-nucleotide variants (SNVs) at 2% or higher frequency in each population and several candidate genes containing high-frequency, nonsynonymous mutations. Five candidate mutations were incorporated into recombinant viruses to determine their in vivo effect. SNVs within UL42 (DNA polymerase auxiliary subunit) and UL46 (tegument) had no measurable influence, while two independent mutations in LORF2 (a gene of unknown function) improved survival time of birds but did not alter disease incidence. A fifth SNV located within UL5 (helicase-primase subunit) greatly reduced in vivo viral replication, increased survival time of birds, and resulted in only 0 to 11% disease incidence. This study shows that multiple genes, often within pathways involving DNA replication and transcriptional regulation, are involved in de novo attenuation of MDV and provides targets for the rational design of future MD vaccines. IMPORTANCE Marek's disease virus (MDV) is a very important pathogen in chickens that costs the worldwide poultry industry $1 billion to $2 billion annually. Marek's disease (MD) vaccines, the primary control method, are often produced by passing virulent strains in cell 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

  2. 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

  3. The Search for Autism Disease Genes

    ERIC Educational Resources Information Center

    Wassink, Thomas H.; Brzustowicz, Linda M.; Bartlett, Christopher W.; Szatmari, Peter

    2004-01-01

    Autism is a heritable disorder characterized by phenotypic and genetic complexity. This review begins by surveying current linkage, gene association, and cytogenetic studies performed with the goal of identifying autism disease susceptibility variants. Though numerous linkages and associations have been identified, they tend to diminish upon…

  4. Integrated analyses of genome-wide DNA occupancy and expression profiling identify key genes and pathways involved in cellular transformation by the Marek's disease virus oncoprotein Meq

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek’s disease (MD) is an economically significant disease in chickens caused by the highly oncogenic Marek’s disease virus (MDV). A major unanswered question is the mechanism of MDV-induced tumor formation. Meq, a bZIP transcription factor discovered in the 1990s, is largely attributed for viral o...

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

    PubMed Central

    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 low 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. PMID:25147748

  6. 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

  7. Gene therapy for neurodegenerative diseases.

    PubMed

    O'Connor, Deirdre M; Boulis, Nicholas M

    2015-08-01

    Gene therapy is, potentially, a powerful tool for treating neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy, Parkinson's disease (PD) and Alzheimer's disease (AD). To date, clinical trials have failed to show any improvement in outcome beyond the placebo effect. Efforts to improve outcomes are focusing on three main areas: vector design and the identification of new vector serotypes, mode of delivery of gene therapies, and identification of new therapeutic targets. These advances are being tested both individually and together to improve efficacy. These improvements may finally make gene therapy successful for these disorders. PMID:26122838

  8. 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).

  9. 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...

  10. 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...

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

    PubMed

    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

  12. 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

  13. 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...

  14. 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.

  15. 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

  16. [Gene therapy and Alzheimer's disease].

    PubMed

    Li, Jian; Li, Wenwen; Zhou, Jun

    2015-04-01

    Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the presence of extracellular β-amyloid in the senile plaques, intracellular aggregates of abnormal phosphorylation of tau protein in the neurofibrillary tangles, neuronal loss and cerebrovascular amyloidosis. The manifestations of clinical symptoms include memory impairment, cognitive decline, altered behavior and language deficit. Currently available drugs in AD therapy consist of acetylcholinesterase inhibitors, NMDA receptor antagonists, non-steroidal anti-inflammatory drugs, etc. These drugs can only alleviate the symptoms of AD. Gene therapy is achieved by vector-mediated gene transfer technology, which can delivery DNA or RNA into target cells to promote the expression of a protective or therapeutic protein and silence certain virulence genes. PMID:25931222

  17. Disease Gene Prioritization Using Network and Feature

    PubMed Central

    Agam, Gady; Balasubramanian, Sandhya; Xu, Jinbo; Gilliam, T. Conrad; Maltsev, Natalia; Börnigen, Daniela

    2015-01-01

    Abstract Identifying high-confidence candidate genes that are causative for disease phenotypes, from the large lists of variations produced by high-throughput genomics, can be both time-consuming and costly. The development of novel computational approaches, utilizing existing biological knowledge for the prioritization of such candidate genes, can improve the efficiency and accuracy of the biomedical data analysis. It can also reduce the cost of such studies by avoiding experimental validations of irrelevant candidates. In this study, we address this challenge by proposing a novel gene prioritization approach that ranks promising candidate genes that are likely to be involved in a disease or phenotype under study. This algorithm is based on the modified conditional random field (CRF) model that simultaneously makes use of both gene annotations and gene interactions, while preserving their original representation. We validated our approach on two independent disease benchmark studies by ranking candidate genes using network and feature information. Our results showed both high area under the curve (AUC) value (0.86), and more importantly high partial AUC (pAUC) value (0.1296), and revealed higher accuracy and precision at the top predictions as compared with other well-performed gene prioritization tools, such as Endeavour (AUC-0.82, pAUC-0.083) and PINTA (AUC-0.76, pAUC-0.066). We were able to detect more target genes (9/18/19/27) on top positions (1/5/10/20) compared to Endeavour (3/11/14/23) and PINTA (6/10/13/18). To demonstrate its usability, we applied our method to a case study for the prediction of molecular mechanisms contributing to intellectual disability and autism. Our approach was able to correctly recover genes related to both disorders and provide suggestions for possible additional candidates based on their rankings and functional annotations. PMID:25844670

  18. Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms

    PubMed Central

    2012-01-01

    Background Complex diseases are associated with altered interactions between thousands of genes. We developed a novel method to identify and prioritize disease genes, which was generally applicable to complex diseases. Results We identified modules of highly interconnected genes in disease-specific networks derived from integrating gene-expression and protein interaction data. We examined if those modules were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. First, we analyzed publicly available gene expression microarray and genome-wide association study (GWAS) data from 13, highly diverse, complex diseases. In each disease, highly interconnected genes formed modules, which were significantly enriched for genes harboring disease-associated SNPs. To test if such modules could be used to find novel genes for functional studies, we repeated the analyses using our own gene expression microarray and GWAS data from seasonal allergic rhinitis. We identified a novel gene, FGF2, whose relevance was supported by functional studies using combined small interfering RNA-mediated knock-down and gene expression microarrays. The modules in the 13 complex diseases analyzed here tended to overlap and were enriched for pathways related to oncological, metabolic and inflammatory diseases. This suggested that this union of the modules would be associated with a general increase in susceptibility for complex diseases. Indeed, we found that this union was enriched with GWAS genes for 145 other complex diseases. Conclusions Modules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. PMID:22703998

  19. Classification of Missense Mutations of Disease Genes

    PubMed Central

    Zhou, Xi; Iversen, Edwin S.; Parmigiani, Giovanni

    2008-01-01

    Clinical management of individuals found to harbor a mutation at a known disease-susceptibility gene depends on accurate assessment of mutation-specific disease risk. For missense mutations (MMs)mutations that lead to a single amino acid change in the protein coded by the genethis poses a particularly challenging problem. Because it is not possible to predict the structural and functional changes to the protein product for a given amino acid substitution, and because functional assays are often not available, disease association must be inferred from data on individuals with the mutation. Inference is complicated by small sample sizes and by sampling mechanisms that bias toward individuals at high familial risk of disease. We propose a Bayesian hierarchical model to classify the disease association of MMs given pedigree data collected in the high-risk setting. The models structure allows simultaneous characterization of multiple MMs. It uses a group of pedigrees identified through probands tested positive for known disease associated mutations and a group of test-negative pedigrees, both obtained from the same clinic, to calibrate classification and control for potential ascertainment bias. We apply this model to study MMs of breast-ovarian susceptibility genes BRCA1 and BRCA2, using data collected at the Duke University Medical Center in Durham, North Carolina. PMID:18418466

  20. Genes and Disease: Prader-Willi Syndrome

    MedlinePlus

    ... for Biotechnology Information (US); 1998-. Genes and Disease [Internet]. Show details National Center for Biotechnology Information (US). ... Center for Biotechnology Information (US). Genes and Disease [Internet]. Bethesda (MD): National Center for Biotechnology Information (US); ...

  1. 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...

  2. Gene Expression Signatures of Coronary Heart Disease

    PubMed Central

    Joehanes, Roby; Ying, Saixia; Huan, Tianxiao; Johnson, Andrew D.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Woodhouse, Kimberly A.; Sen, Shurjo K.; Tanriverdi, Kahraman; Courchesne, Paul; Freedman, Jane E.; O'Donnell, Christopher J.; Levy, Daniel; Munson, Peter J.

    2013-01-01

    Objective To identify transcriptomic biomarkers of coronary heart disease (CHD) in 188 CHD cases and 188 age- and sex-matched controls who were participants in the Framingham Heart Study. Approach and results A total of 35 genes were differentially expressed in CHD cases vs. controls at FDR<0.5 including GZMB, TMEM56 and GUK1. Cluster analysis revealed three gene clusters associated with CHD, two linked to increased erythrocyte production and a third to reduced natural killer (NK) and T cell activity in CHD cases. Exon-level results corroborated and extended the gene-level results. Alternative splicing analysis suggested that GUK1 and 38 other genes were differentially spliced in CHD cases vs. controls. Gene ontology analysis linked ubiquitination and T-cell-related pathways with CHD. Conclusion Two bioinformatically defined groups of genes show consistent associations with CHD. Our findings are consistent with the hypotheses that hematopoesis is up-regulated in CHD, possibly reflecting a compensatory mechanism, and that innate immune activity is disrupted in CHD or altered by its treatment. Transcriptomic signatures may be useful in identifying pathways associated with CHD and point toward novel therapeutic targets for its treatment and prevention. PMID:23539218

  3. Identifying multiple causative genes at a single GWAS locus.

    PubMed

    Flister, Michael J; Tsaih, Shirng-Wern; O'Meara, Caitlin C; Endres, Bradley; Hoffman, Matthew J; Geurts, Aron M; Dwinell, Melinda R; Lazar, Jozef; Jacob, Howard J; Moreno, Carol

    2013-12-01

    Genome-wide association studies (GWAS) are useful for nominating candidate genes, but typically are unable to establish disease causality or differentiate between the effects of variants in linkage disequilibrium (LD). Additionally, some GWAS loci might contain multiple causative variants or genes that contribute to the overall disease susceptibility at a single locus. However, the majority of current GWAS lack the statistical power to test whether multiple causative genes underlie the same locus, prompting us to adopt an alternative approach to testing multiple GWAS genes empirically. We used gene targeting in a disease-susceptible rat model of genetic hypertension to test all six genes at the Agtrap-Plod1 locus (Agtrap, Mthfr, Clcn6, Nppa, Nppb, and Plod1) for blood pressure (BP) and renal phenotypes. This revealed that the majority of genes at this locus (five out of six) can impact hypertension by modifying BP and renal phenotypes. Mutations of Nppa, Plod1, and Mthfr increased disease susceptibility, whereas Agtrap and Clcn6 mutations decreased hypertension risk. Reanalysis of the human AGTRAP-PLOD1 locus also implied that disease-associated haplotype blocks with polygenic effects were not only possible, but rather were highly plausible. Combined, these data demonstrate for the first time that multiple modifiers of hypertension can cosegregate at a single GWAS locus. PMID:24006081

  4. 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

  5. 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

  6. [Gene therapy for Parkinson's disease].

    PubMed

    Muramatsu, Shin-ichi

    2007-04-01

    Recombinant adeno-associated viral (rAAV) vectors are safer and more effective than other in vivo gene delivery methods. Stereotaxic injection of the vectors provides continuous and selective expression of therapeutic proteins throughout the target area in primate brains without toxicity. Three phase I clinical trials for gene therapy for Parkinson's disease (PD) using rAAV vectors are currently underway. One trial involves gene transfer of aromatic L-amino acid decarboxylase (AADC), an enzyme that converts L-dopa to dopamine, to restore therapeutic windows of orally administered L-dopa in advanced idiopathic PD. After AADC transduction, the daily required dose of L-dopa can be reduced and the duration of the ON period is prolonged. Another trial involves transduction of the subthalamic nucleus (STN) with rAAV vectors expressing glutamic acid decarboxylases, a rate-limiting enzyme for synthesizing inhibitory the neurotransmitter gamma-aminobutyric acid (GABA). This strategy, which is similar to deep brain stimulation, aims at modulating hyperactive STN neurons, thereby alter the resulting activity of down-stream targets, which influence movement. However, the mechanism of stimulation remains unknown, and there are some theoretical concerns of chemical alteration. The other trial involves delivery of rAAV vectors expressing neurturin, a natural analog of a glial cell line-derived neurotrophic factor, into the putamen to slow down the ongoing degeneration of nigral dopaminergic neurons. Positron emission tomography with various tracers has been used to monitor the effects of therapeutic gene expression in vivo. Although no serious adverse effects of gene transfer have been reported so far in these trials, vector systems that regulate transgene expression are necessary to increase safety, and the development of such systems is in progress. Gene therapy using rAAV vectors may be a promising option for treatment of PD in the near future. PMID:17447529

  7. 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...

  8. Proteomics Approach to Identify Biomarkers in Neurodegenerative Diseases.

    PubMed

    Nayak, Annapurna; Salt, Gregory; Verma, Sunil K; Kishore, Uday

    2015-01-01

    This chapter examines the use of proteomics in understanding pathogenesis and identifying possible biomarkers in a range of neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease, and prion diseases. We have attempted to look at the neuroproteomic approach from a biomarker discovery point of view. Novel biomarkers can pave the way for new therapeutic targets and lead us to a better understanding of the pathogenesis involved in the neurodegenerative diseases. PMID:26315762

  9. Evolutionary signatures amongst disease genes permit novel methods for gene prioritization and construction of informative gene-based networks.

    PubMed

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

    2015-02-01

    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

  10. 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

  11. 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

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

    PubMed Central

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

    2015-01-01

    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

  13. 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

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

    PubMed

    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

  15. 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.

  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. 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...

  19. A gene recommender algorithm to identify coexpressed genes in C. elegans.

    PubMed

    Owen, Art B; Stuart, Josh; Mach, Kathy; Villeneuve, Anne M; Kim, Stuart

    2003-08-01

    One of the most important uses of whole-genome expression data is for the discovery of new genes with similar function to a given list of genes (the query) already known to have closely related function. We have developed an algorithm, called the gene recommender, that ranks genes according to how strongly they correlate with a set of query genes in those experiments for which the query genes are most strongly coregulated. We used the gene recommender to find other genes coexpressed with several sets of query genes, including genes known to function in the retinoblastoma complex. Genetic experiments confirmed that one gene (JC8.6) identified by the gene recommender acts with lin-35 Rb to regulate vulval cell fates, and that another gene (wrm-1) acts antagonistically. We find that the gene recommender returns lists of genes with better precision, for fixed levels of recall, than lists generated using the C. elegans expression topomap. PMID:12902378

  20. Can We Identify Genes with Increased Phylogenetic Reliability?

    PubMed

    Doyle, Vinson P; Young, Randee E; Naylor, Gavin J P; Brown, Jeremy M

    2015-09-01

    Topological heterogeneity among gene trees is widely observed in phylogenomic analyses and some of this variation is likely caused by systematic error in gene tree estimation. Systematic error can be mitigated by improving models of sequence evolution to account for all evolutionary processes relevant to each gene or identifying those genes whose evolution best conforms to existing models. However, the best method for identifying such genes is not well established. Here, we ask if filtering genes according to their clock-likeness or posterior predictive effect size (PPES, an inference-based measure of model violation) improves phylogenetic reliability and congruence. We compared these approaches to each other, and to the common practice of filtering based on rate of evolution, using two different metrics. First, we compared gene-tree topologies to accepted reference topologies. Second, we examined topological similarity among gene trees in filtered sets. Our results suggest that filtering genes based on clock-likeness and PPES can yield a collection of genes with more reliable phylogenetic signal. For the two exemplar data sets we explored, from yeast and amniotes, clock-likeness and PPES outperformed rate-based filtering in both congruence and reliability. PMID:26099258

  1. GWAS as a Driver of Gene Discovery in Cardiometabolic Diseases.

    PubMed

    Atanasovska, Biljana; Kumar, Vinod; Fu, Jingyuan; Wijmenga, Cisca; Hofker, Marten H

    2015-12-01

    Cardiometabolic diseases represent a common complex disorder with a strong genetic component. Currently, genome-wide association studies (GWAS) have yielded some 755 single-nucleotide polymorphisms (SNPs) encompassing 366 independent loci that may help to decipher the molecular basis of cardiometabolic diseases. Going from a disease SNP to the underlying disease mechanisms is a huge challenge because the associated SNPs rarely disrupt protein function. Many disease SNPs are located in noncoding regions, and therefore attention is now focused on linking genetic SNP variation to effects on gene expression levels. By integrating genetic information with large-scale gene expression data, and with data from epigenetic roadmaps revealing gene regulatory regions, we expect to be able to identify candidate disease genes and the regulatory potential of disease SNPs. PMID:26596674

  2. 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

  3. 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

  4. The study of psychiatric disease genes and drugs in zebrafish

    PubMed Central

    Haesemeyer, Martin; Schier, Alexander F.

    2014-01-01

    Mutations associated with psychiatric disease are being identified, but it remains unclear how the affected genes contribute to disease. Zebrafish is an emerging model to study psychiatric disease genes with a rich repertoire of phenotyping tools. Recent zebrafish research has uncovered potential developmental phenotypes for genes associated with psychiatric disorders, while drug screens have behaviorally characterized small molecules and identified new classes of drugs. Behavioral studies have led to promising models for endophenotypes of psychiatric diseases. While further research is needed to firmly link these models to psychiatric disorders, they are valuable tools for phenotyping genetic mutations and drugs. Recently developed tools in genome editing and in vivo imaging promise additional insights into the processes disrupted by mutations in psychiatric disease genes. PMID:25523356

  5. 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

  6. 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

  7. 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

  8. Effect of gene polymorphisms on periodontal diseases

    PubMed Central

    Tarannum, Fouzia; Faizuddin, Mohamed

    2012-01-01

    Periodontal diseases are inflammatory diseases of supporting structures of the tooth. It results in the destruction of the supporting structures and most of the destructive processes involved are host derived. The processes leading to destruction and regeneration of the destroyed tissues are of great interest to both researchers and clinicians. The selective susceptibility of subjects for periodontitis has remained an enigma and wide varieties of risk factors have been implicated for the manifestation and progression of periodontitis. Genetic factors have been a new addition to the list of risk factors for periodontal diseases. With the availability of human genome sequence and the knowledge of the complement of the genes, it should be possible to identify the metabolic pathways involved in periodontal destruction and regeneration. Most forms of periodontitis represent a life-long account of interactions between the genome, behaviour, and environment. The current practical utility of genetic knowledge in periodontitis is limited. The information contained within the human genome can potentially lead to a better understanding of the control mechanisms modulating the production of inflammatory mediators as well as provides potential therapeutic targets for periodontal disease. Allelic variants at multiple gene loci probably influence periodontitis susceptibility. PMID:22754216

  9. Identifying functional links between genes by evolutionary transcriptomics.

    PubMed

    Silver, David H; Levin, Michal; Yanai, Itai

    2012-10-01

    The ability to determine gene expression profiles across distant species presents a unique opportunity to identify functional relationships between genes. In particular, transcriptome data may help to distinguish whether genes with similar expression profiles are functionally related or independent. Recent studies on the evolution of gene expression have revealed a striking amount of divergence across strains and species, a notion which has hitherto not been brought to bear on the problem of detecting functional relationships between genes. Here, we introduce evo-links, a method by which a pair of genes are linked if their expression profiles are consistently more similar within species, while their individual conservation across species is low. We show that genes connected through evo-links are more enriched in known functional interactions than genes linked by conventional correlation measures. The network of linked genes further allows the identification of gene communities which reflect distinct functional pathways. We classified communities into major cell-types and derived a temporal developmental map of tissue specification in the nematode C. elegans. This map shows the sequential activation of the endoderm, body wall muscle, and neuronal tissues, and later the pharynx. We propose that as comparative transcriptomics becomes increasingly feasible, evo-links offer a robust method to detect functional relationships and disentangle developmental pathways in data lacking spatial resolution. PMID:22772133

  10. 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

  11. Subclass Mapping: Identifying Common Subtypes in Independent Disease Data Sets

    PubMed Central

    Hoshida, Yujin; Brunet, Jean-Philippe; Tamayo, Pablo

    2007-01-01

    Whole genome expression profiles are widely used to discover molecular subtypes of diseases. A remaining challenge is to identify the correspondence or commonality of subtypes found in multiple, independent data sets generated on various platforms. While model-based supervised learning is often used to make these connections, the models can be biased to the training data set and thus miss inherent, relevant substructure in the test data. Here we describe an unsupervised subclass mapping method (SubMap), which reveals common subtypes between independent data sets. The subtypes within a data set can be determined by unsupervised clustering or given by predetermined phenotypes before applying SubMap. We define a measure of correspondence for subtypes and evaluate its significance building on our previous work on gene set enrichment analysis. The strength of the SubMap method is that it does not impose the structure of one data set upon another, but rather uses a bi-directional approach to highlight the common substructures in both. We show how this method can reveal the correspondence between several cancer-related data sets. Notably, it identifies common subtypes of breast cancer associated with estrogen receptor status, and a subgroup of lymphoma patients who share similar survival patterns, thus improving the accuracy of a clinical outcome predictor. PMID:18030330

  12. Gene Expression in Relation to Exhaled Nitric Oxide Identifies Novel Asthma Phenotypes with Unique Biomolecular Pathways

    PubMed Central

    Modena, Brian D.; Tedrow, John R.; Milosevic, Jadranka; Bleecker, Eugene R.; Meyers, Deborah A.; Wu, Wei; Bar-Joseph, Ziv; Erzurum, Serpil C.; Gaston, Benjamin M.; Busse, William W.; Jarjour, Nizar N.; Kaminski, Naftali

    2014-01-01

    Rationale Although asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly understood. Although genomic studies have successfully broadened our understanding in diseases such as cancer, they have not been widely used in asthma studies. Objectives To link gene expression patterns to clinical asthma phenotypes. Methods We used a microarray platform to analyze bronchial airway epithelial cell gene expression in relation to the asthma biomarker fractional exhaled nitric oxide (FeNO) in 155 subjects with asthma and healthy control subjects from the Severe Asthma Research Program (SARP). Measurements and Main Results We first identified a diverse set of 549 genes whose expression correlated with FeNO. We used k-means to cluster the patient samples according to the expression of these genes, identifying five asthma clusters/phenotypes with distinct clinical, physiological, cellular, and gene transcription characteristics—termed “subject clusters” (SCs). To then investigate differences in gene expression between SCs, a total of 1,384 genes were identified that highly differentiated the SCs at an unadjusted P value < 10−6. Hierarchical clustering of these 1,384 genes identified nine gene clusters or “biclusters,” whose coexpression suggested biological characteristics unique to each SC. Although genes related to type 2 inflammation were present, novel pathways, including those related to neuronal function, WNT pathways, and actin cytoskeleton, were noted. Conclusions These findings show that bronchial epithelial cell gene expression, as related to the asthma biomarker FeNO, can identify distinct asthma phenotypes, while also suggesting the presence of underlying novel gene pathways relevant to these phenotypes. PMID:25338189

  13. 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

  14. 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

  15. Using next-generation RNA sequencing to identify imprinted genes

    PubMed Central

    Wang, X; Clark, A G

    2014-01-01

    Genomic imprinting is manifested as differential allelic expression (DAE) depending on the parent-of-origin. The most direct way to identify imprinted genes is to directly score the DAE in a context where one can identify which parent transmitted each allele. Because many genes display DAE, simply scoring DAE in an individual is not sufficient to identify imprinted genes. In this paper, we outline many technical aspects of a scheme for identification of imprinted genes that makes use of RNA sequencing (RNA-seq) from tissues isolated from F1 offspring derived from the pair of reciprocal crosses. Ideally, the parental lines are from two inbred strains that are not closely related to each other. Aspects of tissue purity, RNA extraction, library preparation and bioinformatic inference of imprinting are all covered. These methods have already been applied in a number of organisms, and one of the most striking results is the evolutionary fluidity with which novel imprinted genes are gained and lost within genomes. The general methodology is also applicable to a wide range of other biological problems that require quantification of allele-specific expression using RNA-seq, such as cis-regulation of gene expression, X chromosome inactivation and random monoallelic expression. PMID:24619182

  16. Immunogenetic Mechanisms Leading to Thyroid Autoimmunity: Recent Advances in Identifying Susceptibility Genes and Regions

    PubMed Central

    Brand, Oliver J; Gough, Stephen C.L

    2011-01-01

    The autoimmune thyroid diseases (AITD) include Graves disease (GD) and Hashimotos thyroiditis (HT), which are characterised by a breakdown in immune tolerance to thyroid antigens. Unravelling the genetic architecture of AITD is vital to better understanding of AITD pathogenesis, required to advance therapeutic options in both disease management and prevention. The early whole-genome linkage and candidate gene association studies provided the first evidence that the HLA region and CTLA-4 represented AITD risk loci. Recent improvements in; high throughput genotyping technologies, collection of larger disease cohorts and cataloguing of genome-scale variation have facilitated genome-wide association studies and more thorough screening of candidate gene regions. This has allowed identification of many novel AITD risk genes and more detailed association mapping. The growing number of confirmed AITD susceptibility loci, implicates a number of putative disease mechanisms most of which are tightly linked with aspects of immune system function. The unprecedented advances in genetic study will allow future studies to identify further novel disease risk genes and to identify aetiological variants within specific gene regions, which will undoubtedly lead to a better understanding of AITD patho-physiology. PMID:22654554

  17. 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

  18. 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

  19. Computational disease gene prioritization: an appraisal.

    PubMed

    Gill, Nivit; Singh, Shailendra; Aseri, Trilok C

    2014-06-01

    Bioinformatics aids in the understanding of the biological processes of living beings and the genetic architecture of human diseases. The discovery of disease-related genes improves the diagnosis and therapy design for the disease. To save the cost and time involved in the experimental verification of the candidate genes, computational methods are employed for ranking the genes according to their likelihood of being associated with the disease. Only top-ranked genes are then verified experimentally. A variety of methods have been conceived by the researchers for the prioritization of the disease candidate genes, which differ in the data source being used or the scoring function used for ranking the genes. A review of various aspects of computational disease gene prioritization and its research issues is presented in this article. The aspects covered are gene prioritization process, data sources used, types of prioritization methods, and performance assessment methods. This article provides a brief overview and acts as a quick guide for disease gene prioritization. PMID:24665902

  20. Speeding disease gene discovery by sequence based candidate prioritization

    PubMed Central

    Adie, Euan A; Adams, Richard R; Evans, Kathryn L; Porteous, David J; Pickard, Ben S

    2005-01-01

    Background Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning. Results We examined a variety of sequence-based features and found that for many of them there are significant differences between the sets of genes known to be involved in human hereditary disease and those not known to be involved in disease. We have created an automatic classifier called PROSPECTR based on those features using the alternating decision tree algorithm which ranks genes in the order of likelihood of involvement in disease. On average, PROSPECTR enriches lists for disease genes two-fold 77% of the time, five-fold 37% of the time and twenty-fold 11% of the time. Conclusion PROSPECTR is a simple and effective way to identify genes involved in Mendelian and oligogenic disorders. It performs markedly better than the single existing sequence-based classifier on novel data. PROSPECTR could save investigators looking at large regions of interest time and effort by prioritizing positional candidate genes for mutation detection and case-control association studies. PMID:15766383

  1. Integrative genomics identifies APOE ε4 effectors in Alzheimer's disease.

    PubMed

    Rhinn, Herve; Fujita, Ryousuke; Qiang, Liang; Cheng, Rong; Lee, Joseph H; Abeliovich, Asa

    2013-08-01

    Late-onset Alzheimer's disease (LOAD) risk is strongly influenced by genetic factors such as the presence of the apolipoprotein E ε4 allele (referred to here as APOE4), as well as non-genetic determinants including ageing. To pursue mechanisms by which these affect human brain physiology and modify LOAD risk, we initially analysed whole-transcriptome cerebral cortex gene expression data in unaffected APOE4 carriers and LOAD patients. APOE4 carrier status was associated with a consistent transcriptomic shift that broadly resembled the LOAD profile. Differential co-expression correlation network analysis of the APOE4 and LOAD transcriptomic changes identified a set of candidate core regulatory mediators. Several of these--including APBA2, FYN, RNF219 and SV2A--encode known or novel modulators of LOAD associated amyloid beta A4 precursor protein (APP) endocytosis and metabolism. Furthermore, a genetic variant within RNF219 was found to affect amyloid deposition in human brain and LOAD age-of-onset. These data implicate an APOE4 associated molecular pathway that promotes LOAD. PMID:23883936

  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. Identifying candidate genes for blood pressure quantitative trait loci using differential gene expression and a panel of congenic strains.

    PubMed

    Cicila, G T; Lee, S J

    1998-12-01

    The most difficult step in dissecting the molecular basis of a quantitative trait is proceeding from chromosomal locations associated with this trait (i.e., quantitative trait locus, QTL) to determining what gene(s) in the QTL region is causative. Using standard positional cloning methodology to identify candidate genes for a particular QTL has three drawbacks: 1) it is labor intensive; 2) defining variants in genes causing quantitative variation from sequence information alone is difficult or impossible; and 3) many (or most) genes in a particular chromosomal interval will not be relevant for a specific disease/trait because they are not expressed in critical candidate organs. Instead of positional cloning, we propose using a panel of congenic strains, where each carries an allele for a different QTL on a similar genetic background, in conjunction with identification of differentially-expressed genes in target organs of inbred strains of contrasting phenotype. This will identify genes having altered expression in organs critical to regulating blood pressure and the development of hypertension. Radiation hybrid mapping of such genes will result in a transcription map of differentially-expressed genes in a target organ of a rat model of genetic hypertension. This approach could rapidly identify genes mapping to genomic regions near QTL, which will be strong candidates to explain, in part, the observed strain differences in blood pressure. This novel approach, which uses a panel of congenic strains to facilitate the mapping and subsequent identification of differentially-expressed and QTL-associated genes, should be applicable to any genetic model for identifying candidate genes located near QTL, given the availability of a panel of congenic strains. PMID:9877523

  4. Candidate olfaction genes identified within the Helicoverpa armigera Antennal Transcriptome.

    PubMed

    Liu, Yang; Gu, Shaohua; Zhang, Yongjun; Guo, Yuyuan; Wang, Guirong

    2012-01-01

    Antennal olfaction is extremely important for insect survival, mediating key behaviors such as host preference, mate choice, and oviposition site selection. Multiple antennal proteins are involved in olfactory signal transduction pathways. Of these, odorant receptors (ORs) and ionotropic receptors (IRs) confer specificity on olfactory sensory neuron responses. In this study, we identified the olfactory gene repertoire of the economically important agricultural pest moth, Helicoverpa armigera, by assembling the adult male and female antennal transcriptomes. Within the male and female antennal transcriptomes we identified a total of 47 OR candidate genes containing 6 pheromone receptor candidates. Additionally, 12 IR genes as well as 26 odorant-binding proteins and 12 chemosensory proteins were annotated. Our results allow a systematic functional analysis across much of conventional ORs repertoire and newly reported IRs mediating the key olfaction-mediated behaviors of H. armigera. PMID:23110222

  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. Quantifying cellular capacity identifies gene expression designs with reduced burden.

    PubMed

    Ceroni, Francesca; Algar, Rhys; Stan, Guy-Bart; Ellis, Tom

    2015-05-01

    Heterologous gene expression can be a significant burden for cells. Here we describe an in vivo monitor that tracks changes in the capacity of Escherichia coli in real time and can be used to assay the burden imposed by synthetic constructs and their parts. We identify construct designs with reduced burden that predictably outperformed less efficient designs, despite having equivalent output. PMID:25849635

  7. Recent gene therapy advancements for neurological diseases.

    PubMed

    Nagabhushan Kalburgi, Sahana; Khan, Nadia N; Gray, Steven J

    2013-02-01

    The past few years have seen rapid advancements in vector-mediated gene transfer to the nervous system and modest successes in human gene therapy trials. The purpose of this review is to describe commonly-used viral gene transfer vectors and recent advancements towards producing meaningful gene-based treatments for central nervous system (CNS) disorders. Gene therapy trials for Canavan disease, Batten disease, adrenoleukodystrophy, and Parkinson's disease are discussed to illustrate the current state of clinical gene transfer to the CNS. Preclinical studies are under way for a number of diseases, primarily lysosomal storage disorders, using a newer generation of vectors and delivery strategies. Relevant studies in animal models are highlighted for Mucopolysaccharidosis IIIB and Krabbe disease to provide a prelude for what can be expected in the coming years for human gene transfer trials, using recent advancements in gene transfer technology. In conclusion, recent improvements in CNS gene transfer technology are expected to significantly increase the degree of disease rescue in future CNS-directed clinical trials, exceeding the modest clinical successes that have been observed so far. PMID:23449113

  8. 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

  9. Systematic Analysis of New Drug Indications by Drug-Gene-Disease Coherent Subnetworks

    PubMed Central

    Wang, L; Wang, Y; Hu, Q; Li, S

    2014-01-01

    Drug targets and disease genes may work as driver factors at the transcriptional level, which propagate signals through gene regulatory network and cause the downstream genes' differential expression. How to analyze transcriptional response data to identify meaningful gene modules shared by both drugs and diseases is still a critical issue for drug-disease associations and molecular mechanism. In this article, we propose the drug-gene-disease coherent subnetwork concept to group the biological function related drugs, diseases, and genes. It was defined as the subnetwork with drug, gene, and disease as nodes and their interactions coherently crossing three data layers as edges. Integrating differential expression profiles of 418 drugs and 84 diseases, we develop a computational framework and identify 13 coherent subnetworks such as inflammatory bowel disease and melanoma relevant subnetwork. The results demonstrate that our coherent subnetwork approach is able to identify novel drug indications and highlight their molecular basis. PMID:25390685

  10. 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.

  11. Recombination-based in vivo expression technology identifies Helicobacter pylori genes important for host colonization.

    PubMed

    Castillo, Andrea R; Woodruff, Andrew J; Connolly, Lynn E; Sause, William E; Ottemann, Karen M

    2008-12-01

    Here we undertook to identify colonization and gastric disease-promoting factors of the human gastric pathogen Helicobacter pylori as genes that were induced in response to the stomach environment. Using recombination-based in vivo expression technology (RIVET), we identified six promoters induced in the host compared to laboratory conditions. Three of these promoters, designated Pivi10, Pivi66, and Pivi77, regulate genes that H. pylori may use to interact with other microbes or the host. Pivi10 likely regulates the mobA, mobB, and mobD genes, which have potential roles in horizontal gene transfer through plasmid mobilization. Pivi66 occurs in the cytotoxin-associated gene pathogenicity island, a genomic region known to be associated with more severe disease outcomes, and likely regulates cagZ, virB11, and virD4. Pivi77 likely regulates HP0289, an uncharacterized paralogue of the vacA cytotoxin gene. We assessed the roles of a subset of these genes in colonization by creating deletion mutants and analyzing them in single-strain and coinfection experiments. We found that a mobABD mutant was defective for murine host colonization and that a cagZ mutant outcompeted the wild-type strain in a coinfection analysis. Our work supports the conclusion that RIVET is a valuable tool for identifying H. pylori factors with roles in host colonization. PMID:18794279

  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. Using SCOPE to identify potential regulatory motifs in coregulated genes.

    PubMed

    Martyanov, Viktor; Gross, Robert H

    2011-01-01

    SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data. In this article, we utilize a web version of SCOPE to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs and has been used in other studies. The three algorithms that comprise SCOPE are BEAM, which finds non-degenerate motifs (ACCGGT), PRISM, which finds degenerate motifs (ASCGWT), and SPACER, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from a file. The output from SCOPE contains a list of all identified motifs with their scores, number of occurrences, fraction of genes containing the motif, and the algorithm used to identify the motif. For each motif, result details include a consensus representation of the motif, a sequence logo, a position weight matrix, and a list of instances for every motif occurrence (with exact positions and "strand" indicated). Results are returned in a browser window and also optionally by email. Previous papers describe the SCOPE algorithms in detail. PMID:21673638

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. Genes Necessary for Bacterial Magnetite Biomineralization Identified by Transposon Mutagenesis

    NASA Astrophysics Data System (ADS)

    Nash, C. Z.; Komeili, A.; Newman, D. K.; Kirschvink, J. L.

    2004-12-01

    Magnetic bacteria synthesize nanoscale crystals of magnetite in intracellular, membrane-bounded organelles (magnetosomes). These crystals are preserved in the fossil record at least as far back as the late Neoproterozoic and have been tentatively identified in much older rocks (1). This fossil record may provide deep time calibration points for molecular evolution studies once the genes involved in biologically controlled magnetic mineralization (BCMM) are known. Further, a genetic and biochemical understanding of BCMM will give insight into the depositional environment and biogeochemical cycles in which magnetic bacteria play a role. The BCMM process is not well understood, though proteins have been identified from the magnetosome membrane and genetic manipulation and biochemical characterization of these proteins are underway. Most of the proteins currently thought to be involved are encoded within the mam cluster, a large cluster of genes whose products localize to the magnetosome membrane and are conserved among magnetic bacteria (2). In an effort to identify all of the genes necessary for bacterial BCMM, we undertook a transposon mutagenesis of Magnetospirillum magneticum AMB-1. Non-magnetic mutants (MNMs) were identified by growth in liquid culture followed by a magnetic assay. The insertion site of the transposon was identified two ways. First MNMs were screened with a PCR assay to determine if the transposon had inserted into the mam cluster. Second, the transposon was rescued from the mutant DNA and cloned for sequencing. The majority insertion sites are located within the mam cluster. Insertion sites also occur in operons which have not previously been suspected to be involved in magnetite biomineralization. None of the insertion sites have occurred within genes reported from previous transposon mutagenesis studies of AMB-1 (3, 4). Two of the non-mam cluster insertion sites occur in operons containing genes conserved particularly between MS-1 and MC-1. We are undertaking a complementation strategy to demonstrate the necessity of these novel genes in BCMM as well as characterizing the phenotypes of the mutants. 1. S. B. R. Chang, J. F. Stolz, J. L. Kirschvink, S. M. Awramik, Precambrian Res. 43, 305-315 (1989). 2. K. Grünberg, C. Wawer, B. M. Tebo, D. Schüler, Appl. Environ. Microbiol. 67, 4573-4582 (2001). 3. A. T. Wahyudi, H. Takeyama, T. Matsunaga, Appl. Biochem. Biotechnol. 91-3, 147-154 (2001). 4. T. Matsunaga, C. Nakamura, J. G. Burgess, K. Sode, J. Bacteriol. 174, 2748-2753 (1992).

  1. 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

  2. Sleeping Beauty mouse models identify candidate genes involved in gliomagenesis.

    PubMed

    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. 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

  4. 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

  5. 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

  6. 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.

  7. Systematic tracking of dysregulated modules identifies novel genes in cancer.

    TOXLINE Toxicology Bibliographic Information

    Srihari S; Ragan MA

    2013-06-15

    MOTIVATION: Deciphering the modus operandi of dysregulated cellular mechanisms in cancer is critical to implicate novel cancer genes and develop effective anti-cancer therapies. Fundamental to this is meticulous tracking of the behavior of core modules, including complexes and pathways across specific conditions in cancer.RESULTS: Here, we performed a straightforward yet systematic identification and comparison of modules across pancreatic normal and cancer tissue conditions by integrating PPI, gene-expression and mutation data. Our analysis revealed interesting change-patterns in gene composition and expression correlation particularly affecting modules responsible for genome stability. Although in most cases these changes indicated impairment of essential functions (e.g., of DNA damage repair), in several other cases we noticed strengthening of modules possibly abetting cancer. Some of these compensatory modules showed switches in transcription regulation and recruitment of tumor inducers (e.g., SOX2 through overexpression). In-depth analysis revealed novel genes in pancreatic cancer, which showed susceptibility to copy-number alterations (e.g., for USP15 in 17 of 67 cases), supported by literature evidence for their involvement in other tumors (e.g., USP15 in glioblastoma). Two of the identified genes, YWHAE and DISC1, further supported the nexus between neural genes and pancreatic carcinogenesis. Extension of this assessment to BRCA1 and BRCA2 breast tumors showed specific differences even across the two sub-types and revealed novel genes involved therein (e.g., TRIM5 and NCOA6).AVAILABILITY: Our software CONTOURv1 is available at: http://bioinformatics.org.au/tools-data/

  8. DNA repeats identify novel virulence genes in Haemophilus influenzae.

    PubMed Central

    Hood, D W; Deadman, M E; Jennings, M P; Bisercic, M; Fleischmann, R D; Venter, J C; Moxon, E R

    1996-01-01

    The whole genome sequence (1.83 Mbp) of Haemophilus influenzae strain Rd was searched to identify tandem oligonucleotide repeat sequences. Loss or gain of one or more nucleotide repeats through a recombination-independent slippage mechanism is known to mediate phase variation of surface molecules of pathogenic bacteria, including H. influenzae. This facilitates evasion of host defenses and adaptation to the varying microenvironments of the host. We reasoned that iterative nucleotides could identify novel genes relevant to microbe-host interactions. Our search of the Rd genome sequence identified 9 novel loci with multiple (range 6-36, mean 22) tandem tetranucleotide repeats. All were found to be located within putative open reading frames and included homologues of hemoglobin-binding proteins of Neisseria, a glycosyltransferase (IgtC gene product) of Neisseria, and an adhesin of Yersinia. These tetranucleotide repeat sequences were also shown to be present in two other epidemiologically different H. influenzae type b strains, although the number and distribution of repeats was different. Further characterization of the IgtC gene showed that it was involved in phenotypic switching of a lipopolysaccharide epitope and that this variable expression was associated with changes in the number of tetranucleotide repeats. Mutation of IgtC resulted in attenuated virulence of H. influenzae in an infant rat model of invasive infection. These data indicate the rapidity, economy, and completeness with which whole genome sequences can be used to investigate the biology of pathogenic bacteria. Images Fig. 1 PMID:8855319

  9. 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

  10. Sheath blight disease screening methods to identify resistant Oryza spp. accessions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Oryza species, wild relatives of cultivated rice (O. sativa), may contain novel resistance genes to sheath blight, caused by Rhizoctonia solani Kühn, that could be used to enhance resistance to this important disease in commercial rice. Suitable greenhouse screening methods are needed to identify re...

  11. A Genome-wide screen identifies frequently methylated genes in haematological and epithelial cancers

    PubMed Central

    2010-01-01

    Background Genetic as well as epigenetic alterations are a hallmark of both epithelial and haematological malignancies. High throughput screens are required to identify epigenetic markers that can be useful for diagnostic and prognostic purposes across malignancies. Results Here we report for the first time the use of the MIRA assay (methylated CpG island recovery assay) in combination with genome-wide CpG island arrays to identify epigenetic molecular markers in childhood acute lymphoblastic leukemia (ALL) on a genome-wide scale. We identified 30 genes demonstrating methylation frequencies of ≥25% in childhood ALL, nine genes showed significantly different methylation frequencies in B vs T-ALL. For majority of the genes expression could be restored in methylated leukemia lines after treatment with 5-azaDC. Forty-four percent of the genes represent targets of the polycomb complex. In chronic myeloid leukemia (CML) two of the genes, (TFAP2A and EBF2), demonstrated increased methylation in blast crisis compared to chronic phase (P < 0.05). Furthermore hypermethylation of an autophagy related gene ATG16L2 was associated with poorer prognosis in terms of molecular response to Imatinib treatment. Lastly we demonstrated that ten of these genes were also frequently methylated in common epithelial cancers. Conclusion In summary we have identified a large number of genes showing frequent methylation in childhood ALL, methylation status of two of these genes is associated with advanced disease in CML and methylation status of another gene is associated with prognosis. In addition a subset of these genes may act as epigenetic markers across hematological malignancies as well as common epithelial cancers. PMID:20184741

  12. [TET2 gene in hematological diseases].

    PubMed

    Li, Shuang; Wang, Xiao-Qin

    2014-06-01

    The TET gene family has been found a few years ago. Recent studies indicated that TET2 (TET gene family 2) plays an important role in DNA demethylation, the epigenetic regulation and normal hematopoiesis. TET2 mutation has been discovered in a spectrum of myeloid malignancies, including myeloproliferative neoplasms (MPN), myelodysplastic syndrome (MDS) and leukemia, which suggest the role of TET2 as a tumor suppressor. In this review the recent results implicating TET2 in hematological malignancies are summarized, including regulatory functions of TET gene epigenetics, TET2 gene and hematopoietic regulation in bone marrow, TET2 gene and hematological disease(MPN, MDS, AML, CMML, lymphoma) and so on. PMID:24989305

  13. 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 ...

  14. [Fecal lactoferrin in identifying and management of inflammatory bowel disease].

    PubMed

    Pac-Kozuchowska, Elzbieta; Krawiec, Paulina; Mroczkowska-Juchkiewicz, Agnieszka

    2014-07-01

    Inflammatory bowel disease is a group of chronic inflammatory conditions of gastrointestinal tract, including ulcerative colitis and Crohn's disease. Diagnosis of inflammatory bowel disease is based on clinical symptoms, lower and/or upper gastrointestinal tract endoscopy with biopsies and histological results. These procedures are invasive for patients and highly expensive. Thus, efforts are underway to establish new noninvasive tests appropriate to diagnosis and management of inflammatory bowel disease. Commonly used, blood markers of inflammation or scales of inflammatory bowel disease activity has been demonstrated to be insufficient. Recently, there has been increasing interest in identifying biomarkers, i.e. calprotectin, lactoferrin, mieloperoxidasis or S100A12 protein in faeces. These proteins are produced by neutrophil granulocytes and clearly reflect inflammation directly in bowel. It should be highlighted that these tests are noninvasive and may be perform repetitiously. PMID:25154203

  15. Simulating gene-gene and gene-environment interactions in complex diseases: Gene-Environment iNteraction Simulator 2

    PubMed Central

    2012-01-01

    Background The analysis of complex diseases is an important problem in human genetics. Because multifactoriality is expected to play a pivotal role, many studies are currently focused on collecting information on the genetic and environmental factors that potentially influence these diseases. However, there is still a lack of efficient and thoroughly tested statistical models that can be used to identify implicated features and their interactions. Simulations using large biologically realistic data sets with known gene-gene and gene-environment interactions that influence the risk of a complex disease are a convenient and useful way to assess the performance of statistical methods. Results The Gene-Environment iNteraction Simulator 2 (GENS2) simulates interactions among two genetic and one environmental factor and also allows for epistatic interactions. GENS2 is based on data with realistic patterns of linkage disequilibrium, and imposes no limitations either on the number of individuals to be simulated or on number of non-predisposing genetic/environmental factors to be considered. The GENS2 tool is able to simulate gene-environment and gene-gene interactions. To make the Simulator more intuitive, the input parameters are expressed as standard epidemiological quantities. GENS2 is written in Python language and takes advantage of operators and modules provided by the simuPOP simulation environment. It can be used through a graphical or a command-line interface and is freely available from http://sourceforge.net/projects/gensim. The software is released under the GNU General Public License version 3.0. Conclusions Data produced by GENS2 can be used as a benchmark for evaluating statistical tools designed for the identification of gene-gene and gene-environment interactions. PMID:22698142

  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. NDRC: A Disease-Causing Genes Prioritized Method Based on Network Diffusion and Rank Concordance.

    PubMed

    Fang, Minghong; Hu, Xiaohua; Wang, Yan; Zhao, Junmin; Shen, Xianjun; He, Tingting

    2015-07-01

    Disease-causing genes prioritization is very important to understand disease mechanisms and biomedical applications, such as design of drugs. Previous studies have shown that promising candidate genes are mostly ranked according to their relatedness to known disease genes or closely related disease genes. Therefore, a dangling gene (isolated gene) with no edges in the network can not be effectively prioritized. These approaches tend to prioritize those genes that are highly connected in the PPI network while perform poorly when they are applied to loosely connected disease genes. To address these problems, we propose a new disease-causing genes prioritization method that based on network diffusion and rank concordance (NDRC). The method is evaluated by leave-one-out cross validation on 1931 diseases in which at least one gene is known to be involved, and it is able to rank the true causal gene first in 849 of all 2542 cases. The experimental results suggest that NDRC significantly outperforms other existing methods such as RWR, VAVIEN, DADA and PRINCE on identifying loosely connected disease genes and successfully put dangling genes as potential candidate disease genes. Furthermore, we apply NDRC method to study three representative diseases, Meckel syndrome 1, Protein C deficiency and Peroxisome biogenesis disorder 1A (Zellweger). Our study has also found that certain complex disease-causing genes can be divided into several modules that are closely associated with different disease phenotype. PMID:26080386

  18. Genome-wide association study for Crohn's disease in the Quebec Founder Population identifies multiple validated disease loci

    PubMed Central

    Raelson, John V.; Little, Randall D.; Ruether, Andreas; Fournier, Hélène; Paquin, Bruno; Van Eerdewegh, Paul; Bradley, W. E. C.; Croteau, Pascal; Nguyen-Huu, Quynh; Segal, Jonathan; Debrus, Sophie; Allard, René; Rosenstiel, Philip; Franke, Andre; Jacobs, Gunnar; Nikolaus, Susanna; Vidal, Jean-Michel; Szego, Peter; Laplante, Nathalie; Clark, Hilary F.; Paulussen, René J.; Hooper, John W.; Keith, Tim P.; Belouchi, Abdelmajid; Schreiber, Stefan

    2007-01-01

    Genome-wide association (GWA) studies offer a powerful unbiased method for the identification of multiple susceptibility genes for complex diseases. Here we report the results of a GWA study for Crohn's disease (CD) using family trios from the Quebec Founder Population (QFP). Haplotype-based association analyses identified multiple regions associated with the disease that met the criteria for genome-wide significance, with many containing a gene whose function appears relevant to CD. A proportion of these were replicated in two independent German Caucasian samples, including the established CD loci NOD2 and IBD5. The recently described IL23R locus was also identified and replicated. For this region, multiple individuals with all major haplotypes in the QFP were sequenced and extensive fine mapping performed to identify risk and protective alleles. Several additional loci, including a region on 3p21 containing several plausible candidate genes, a region near JAKMIP1 on 4p16.1, and two larger regions on chromosome 17 were replicated. Together with previously published loci, the spectrum of CD genes identified to date involves biochemical networks that affect epithelial defense mechanisms, innate and adaptive immune response, and the repair or remodeling of tissue. PMID:17804789

  19. 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. Furthermore, these genes have approximately equal contributions to all tissues, making them possible candidates to be used as non-invasive biomarkers in studying PBMCs instead of MLN and spleen during acute SIV infection experiments. We identified clusters of genes that co-vary together and studied their correlation with regard to other gene clusters. We also developed novel methods to faithfully visualize multi-gene correlations on two-dimensional polar plots, and to visualize tissue specificity of gene expression responses. PMID:25984721

  20. 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

  1. Identifying Francisella tularensis genes required for growth in host cells.

    PubMed

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

    2015-08-01

    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

  2. Identifying bacterial genes and endosymbiont DNA with Glimmer

    PubMed Central

    Delcher, Arthur L.; Bratke, Kirsten A.; Powers, Edwin C.; Salzberg, Steven L.

    2008-01-01

    Motivation: The Glimmer gene-finding software has been successfully used for finding genes in bacteria, archæa and viruses representing hundreds of species. We describe several major changes to the Glimmer system, including improved methods for identifying both coding regions and start codons. We also describe a new module of Glimmer that can distinguish host and endosymbiont DNA. This module was developed in response to the discovery that eukaryotic genome sequencing projects sometimes inadvertently capture the DNA of intracellular bacteria living in the host. Results: The new methods dramatically reduce the rate of false-positive predictions, while maintaining Glimmer's 99% sensitivity rate at detecting genes in most species, and they find substantially more correct start sites, as measured by comparisons to known and well-curated genes. We show that our interpolated Markov model (IMM) DNA discriminator correctly separated 99% of the sequences in a recent genome project that produced a mixture of sequences from the bacterium Prochloron didemni and its sea squirt host, Lissoclinum patella. PMID:17237039

  3. 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...

  4. 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 levels; in doing so, we highlight the value of studying expression variability for single cell RNA-seq data. PMID:26288249

  5. 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

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

    PubMed Central

    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.

    2014-01-01

    Copy number variants (CNVs) are associated with many neurocognitive disorders; however, these events are typically large and the underlying causative gene is unclear. We created an expanded CNV morbidity map from 29,085 children with developmental delay versus 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 ten genes enriched for putative loss of function. Patient follow-up on a subset identified new clinical subtypes of pediatric disease and the genes responsible for disease-associated CNVs. This includes haploinsufficiency of SETBP1 associated with intellectual disability and loss of expressive language and truncations of ZMYND11 in patients with autism, aggression and complex neuropsychiatric features. This combined CNV and SNV approach facilitates the rapid discovery of new syndromes and neuropsychiatric disease genes despite extensive genetic heterogeneity. PMID:25217958

  7. Gene expression in the Parkinson's disease brain

    PubMed Central

    Lewis, Patrick A.; Cookson, Mark R.

    2012-01-01

    The study of gene expression has undergone a transformation in the past decade as the benefits of the sequencing of the human genome have made themselves felt. Increasingly, genome wide approaches are being applied to the analysis of gene expression in human disease as a route to understanding the underlying pathogenic mechanisms. In this review, we will summarise current state of gene expression studies of the brain in Parkinson's disease, and examine how these techniques can be used to gain an insight into aetiology of this devastating disorder. PMID:22173063

  8. 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

  9. Screening for Noise in Gene Expression Identifies Drug Synergies

    PubMed Central

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

    2014-01-01

    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 over 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 strikingly they synergized with conventional transcriptional activators. Noise enhancers reactivated latent cells significantly better than existing best-in-class reactivation cocktails (and with reduced off-target cytotoxicity), while 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

  10. Identifying novel genes involved in both deer physiological and human pathological osteoporosis.

    PubMed

    Borsy, Adrienn; Podani, János; Stéger, Viktor; Balla, Bernadett; Horváth, Arnold; Kósa, János P; Gyurján, István; Molnár, Andrea; Szabolcsi, Zoltán; Szabó, László; Jakó, Eéna; Zomborszky, Zoltán; Nagy, János; Semsey, Szabolcs; Vellai, Tibor; Lakatos, Péter; Orosz, László

    2009-03-01

    Osteoporosis attacks 10% of the population worldwide. Humans or even the model animals of the disease cannot recover from porous bone. Regeneration in skeletal elements is the unique feature of our newly investigated osteoporosis model, the red deer (Cervus elaphus) stag. Cyclic physiological osteoporosis is a consequence of the annual antler cycle. This phenomenon raises the possibility to identify genes involved in the regulation of bone mineral density on the basis of comparative genomics between deer and human. We compare gene expression activity of osteoporotic and regenerating rib bone samples versus autumn dwell control in red deer by microarray hybridization. Identified genes were tested on human femoral bone tissue from non-osteoporotic controls and patients affected with age-related osteoporosis. Expression data were evaluated by Principal Components Analysis and Canonical Variates Analysis. Separation of patients into a normal and an affected group based on ten formerly known osteoporosis reference genes was significantly improved by expanding the data with newly identified genes. These genes include IGSF4, FABP3, FABP4, FKBP2, TIMP2, TMSB4X, TRIB, and members of the Wnt signaling. This study supports that extensive comparative genomic analyses, here deer and human, provide a novel approach to identify new targets for human diagnostics and therapy. PMID:19107525

  11. 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

  12. Viruses, autophagy genes, and Crohn's disease.

    PubMed

    Hubbard, Vanessa M; Cadwell, Ken

    2011-07-01

    The etiology of the intestinal disease Crohn's disease involves genetic factors as well as ill-defined environmental agents. Several genetic variants linked to this disease are associated with autophagy, a process that is critical for proper responses to viral infections. While a role for viruses in this disease remains speculative, accumulating evidence indicate that this possibility requires serious consideration. In this review, we will examine the three-way relationship between viruses, autophagy genes, and Crohn's disease and discuss how host-pathogen interactions can mediate complex inflammatory disorders. PMID:21994779

  13. Genetics of Sputum Gene Expression in Chronic Obstructive Pulmonary Disease

    PubMed Central

    Qiu, Weiliang; Cho, Michael H.; Riley, John H.; Anderson, Wayne H.; Singh, Dave; Bakke, Per; Gulsvik, Amund; Litonjua, Augusto A.; Lomas, David A.; Crapo, James D.; Beaty, Terri H.; Celli, Bartolome R.; Rennard, Stephen; Tal-Singer, Ruth; Fox, Steven M.; Silverman, Edwin K.; Hersh, Craig P.

    2011-01-01

    Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus. PMID:21949713

  14. Identifying critical transitions and their leading biomolecular networks in complex diseases

    NASA Astrophysics Data System (ADS)

    Liu, Rui; Li, Meiyi; Liu, Zhi-Ping; Wu, Jiarui; Chen, Luonan; Aihara, Kazuyuki

    2012-12-01

    Identifying a critical transition and its leading biomolecular network during the initiation and progression of a complex disease is a challenging task, but holds the key to early diagnosis and further elucidation of the essential mechanisms of disease deterioration at the network level. In this study, we developed a novel computational method for identifying early-warning signals of the critical transition and its leading network during a disease progression, based on high-throughput data using a small number of samples. The leading network makes the first move from the normal state toward the disease state during a transition, and thus is causally related with disease-driving genes or networks. Specifically, we first define a state-transition-based local network entropy (SNE), and prove that SNE can serve as a general early-warning indicator of any imminent transitions, regardless of specific differences among systems. The effectiveness of this method was validated by functional analysis and experimental data.

  15. An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis.

    PubMed

    Sweet-Cordero, Alejandro; Mukherjee, Sayan; Subramanian, Aravind; You, Han; Roix, Jeffrey J; Ladd-Acosta, Christine; Mesirov, Jill; Golub, Todd R; Jacks, Tyler

    2005-01-01

    Using advanced gene targeting methods, generating mouse models of cancer that accurately reproduce the genetic alterations present in human tumors is now relatively straightforward. The challenge is to determine to what extent such models faithfully mimic human disease with respect to the underlying molecular mechanisms that accompany tumor progression. Here we describe a method for comparing mouse models of cancer with human tumors using gene-expression profiling. We applied this method to the analysis of a model of Kras2-mediated lung cancer and found a good relationship to human lung adenocarcinoma, thereby validating the model. Furthermore, we found that whereas a gene-expression signature of KRAS2 activation was not identifiable when analyzing human tumors with known KRAS2 mutation status alone, integrating mouse and human data uncovered a gene-expression signature of KRAS2 mutation in human lung cancer. We confirmed the importance of this signature by gene-expression analysis of short hairpin RNA-mediated inhibition of oncogenic Kras2. These experiments identified both a pattern of gene expression indicative of KRAS2 mutation and potential effectors of oncogenic KRAS2 activity in human cancer. This approach provides a strategy for using genomic analysis of animal models to probe human disease. PMID:15608639

  16. Gene expression profiling as a window into idiopathic pulmonary fibrosis pathogenesis: can we identify the right target genes?

    PubMed

    Kaminski, Naftali; Rosas, Ivan O

    2006-06-01

    Expression microarrays that provide genome-level, transcriptional, high-resolution profiles have been applied successfully to multiple diseases. Although microarrays provide information regarding thousands of genes, many investigators prefer to focus on a single gene and validate its role, an approach often supported by grant and journal reviewers. Only a minority of investigators focus on global changes in gene expression. Here, we describe and contrast two general approaches to the use of microarray data: the reductionist "cherry picking" approach and the more global, quantitative "systems" approach. We describe microarray analysis experiments relevant to idiopathic pulmonary fibrosis (IPF) in the context of these two approaches. Although it seems that the cherry-picking approaches have been successful in identifying new relevant genes in IPF, we suggest that to fulfill the discovery potential of microarrays in IPF and to create a working model of IPF, unbiased integrative systems approaches are required. PMID:16738198

  17. 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

    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. PMID:21922596

  18. 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

  19. 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

  20. Genomics meets proteomics: identifying the culprits in disease.

    PubMed

    Stunnenberg, Hendrik G; Hubner, Nina C

    2014-06-01

    Genome-wide association studies (GWAS) revealed genomic risk loci that potentially have an impact on disease and phenotypic traits. This extensive resource holds great promise in providing novel directions for personalized medicine, including disease risk prediction, prevention and targeted medication. One of the major challenges that researchers face on the path between the initial identification of an association and precision treatment of patients is the comprehension of the biological mechanisms that underlie these associations. Currently, the focus to solve these questions lies on the integrative analysis of system-wide data on global genome variation, gene expression, transcription factor binding, epigenetic profiles and chromatin conformation. The generation of this data mainly relies on next-generation sequencing. However, due to multiple recent developments, mass spectrometry-based proteomics now offers additional, by the GWAS field so far hardly recognized possibilities for the identification of functional genome variants and, in particular, for the identification and characterization of (differentially) bound protein complexes as well as physiological target genes. In this review, we introduce these proteomics advances and suggest how they might be integrated in post-GWAS workflows. We argue that the combination of highly complementary techniques is powerful and can provide an unbiased, detailed picture of GWAS loci and their mechanistic involvement in disease. PMID:24135908

  1. 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

  2. An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association

    PubMed Central

    Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J

    2009-01-01

    Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929

  3. Integrative analysis of DNA methylation and gene expression data identifies EPAS1 as a key regulator of COPD.

    PubMed

    Yoo, Seungyeul; Takikawa, Sachiko; Geraghty, Patrick; Argmann, Carmen; Campbell, Joshua; Lin, Luan; Huang, Tao; Tu, Zhidong; Foronjy, Robert F; Feronjy, Robert; Spira, Avrum; Schadt, Eric E; Powell, Charles A; Zhu, Jun

    2015-01-01

    Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a 'causal' role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology. PMID:25569234

  4. Integrative Analysis of DNA Methylation and Gene Expression Data Identifies EPAS1 as a Key Regulator of COPD

    PubMed Central

    Yoo, Seungyeul; Takikawa, Sachiko; Geraghty, Patrick; Argmann, Carmen; Campbell, Joshua; Lin, Luan; Huang, Tao; Tu, Zhidong; Feronjy, Robert; Spira, Avrum; Schadt, Eric E.; Powell, Charles A.; Zhu, Jun

    2015-01-01

    Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a ‘causal’ role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology. PMID:25569234

  5. 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

  6. Identifying Genes Involved in Cyclic Processes by Combining Gene Expression Analysis and Prior Knowledge

    PubMed Central

    2009-01-01

    Based on time series gene expressions, cyclic genes can be recognized via spectral analysis and statistical periodicity detection tests. These cyclic genes are usually associated with cyclic biological processes, for example, cell cycle and circadian rhythm. The power of a scheme is practically measured by comparing the detected periodically expressed genes with experimentally verified genes participating in a cyclic process. However, in the above mentioned procedure the valuable prior knowledge only serves as an evaluation benchmark, and it is not fully exploited in the implementation of the algorithm. In addition, partial data sets are also disregarded due to their nonstationarity. This paper proposes a novel algorithm to identify cyclic-process-involved genes by integrating the prior knowledge with the gene expression analysis. The proposed algorithm is applied on data sets corresponding to Saccharomyces cerevisiae and Drosophila melanogaster, respectively. Biological evidences are found to validate the roles of the discovered genes in cell cycle and circadian rhythm. Dendrograms are presented to cluster the identified genes and to reveal expression patterns. It is corroborated that the proposed novel identification scheme provides a valuable technique for unveiling pathways related to cyclic processes. PMID:19390635

  7. 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

  8. Gene expression profiling identifies different sub-types of retinoblastoma

    PubMed Central

    Kapatai, G; Brundler, M-A; Jenkinson, H; Kearns, P; Parulekar, M; Peet, A C; McConville, C M

    2013-01-01

    Background: Mutation of the RB1 gene is necessary but not sufficient for the development of retinoblastoma. The nature of events occurring subsequent to RB1 mutation is unclear, as is the retinal cell-of-origin of this tumour. Methods: Gene expression profiling of 21 retinoblastomas was carried out to identify genetic events that contribute to tumorigenesis and to obtain information about tumour histogenesis. Results: Expression analysis showed a clear separation of retinoblastomas into two groups. Group 1 retinoblastomas express genes associated with a range of different retinal cell types, suggesting derivation from a retinal progenitor cell type. Recurrent chromosomal alterations typical of retinoblastoma, for example, chromosome 1q and 6p gain and 16q loss were also a feature of this group, and clinically they were characterised by an invasive pattern of tumour growth. In contrast, group 2 retinoblastomas were found to retain many characteristics of cone photoreceptor cells and appear to exploit the high metabolic capacity of this cell type in order to promote tumour proliferation. Conclusion: Retinoblastoma is a heterogeneous tumour with variable biology and clinical characteristics. PMID:23756868

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. A computational framework for the prioritization of disease-gene candidates

    PubMed Central

    2015-01-01

    Background The identification of genes and uncovering the role they play in diseases is an important and complex challenge. Genome-wide linkage and association studies have made advancements in identifying genetic variants that underpin human disease. An important challenge now is to identify meaningful disease-associated genes from a long list of candidate genes implicated by these analyses. The application of gene prioritization can enhance our understanding of disease mechanisms and aid in the discovery of drug targets. The integration of protein-protein interaction networks along with disease datasets and contextual information is an important tool in unraveling the molecular basis of diseases. Results In this paper we propose a computational pipeline for the prioritization of disease-gene candidates. Diverse heterogeneous data including: gene-expression, protein-protein interaction network, ontology-based similarity and topological measures and tissue-specific are integrated. The pipeline was applied to prioritize Alzheimer's Disease (AD) genes, whereby a list of 32 prioritized genes was generated. This approach correctly identified key AD susceptible genes: PSEN1 and TRAF1. Biological process enrichment analysis revealed the prioritized genes are modulated in AD pathogenesis including: regulation of neurogenesis and generation of neurons. Relatively high predictive performance (AUC: 0.70) was observed when classifying AD and normal gene expression profiles from individuals using leave-one-out cross validation. Conclusions This work provides a foundation for future investigation of diverse heterogeneous data integration for disease-gene prioritization. PMID:26330267

  15. 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

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

    PubMed

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

    2012-10-01

    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

  17. 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

  18. A polymorphic gene nested within an intron of the tau gene: Implications for Alzheimer's disease

    PubMed Central

    Conrad, Chris; Vianna, Cintia; Freeman, Melissa; Davies, Peter

    2002-01-01

    A previously undescribed gene, Saitohin (STH), has been discovered in the intron between exons 9 and 10 of the human tau gene. STH is an intronless gene that encodes a 128-aa protein with no clear homologs. The tissue expression of STH is similar to tau, a gene that is implicated in many neurodegenerative disorders. In humans, a single nucleotide polymorphism that results in an amino acid change (Q7R) has been identified in STH and was used in a case control study. The Q7R polymorphism appears to be over-represented in the homozygous state in late onset Alzheimer's disease subjects. PMID:12032355

  19. 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

  20. Integrated genomics identifies convergence of ankylosing spondylitis with global immune mediated disease pathways.

    PubMed

    Uddin, Mohammed; Codner, Dianne; Hasan, S M Mahmud; Scherer, Stephen W; O'Rielly, Darren D; Rahman, Proton

    2015-01-01

    Ankylosing spondylitis(AS), a highly heritable complex inflammatory arthritis. Although, a handful of non-HLA risk loci have been identified, capturing the unexplained genetic contribution to AS pathogenesis remains a challenge attributed to additive, pleiotropic and epistatic-interactions at the molecular level. Here, we developed multiple integrated genomic approaches to quantify molecular convergence of non-HLA loci with global immune mediated diseases. We show that non-HLA genes are significantly sensitive to deleterious mutation accumulation in the general population compared with tolerant genes. Human developmental proteomics (prenatal to adult) analysis revealed that proteins encoded by non-HLA AS risk loci are 2-fold more expressed in adult hematopoietic cells.Enrichment analysis revealed AS risk genes overlap with a significant number of immune related pathways (p < 0.0001 to 9.8 × 0(-12)). Protein-protein interaction analysis revealed non-shared AS risk genes are highly clustered seeds that significantly converge (empirical; p < 0.01 to 1.6 × 10(-4)) into networks of global immune mediated disease risk loci. We have also provided initial evidence for the involvement of STAT2/3 in AS pathogenesis. Collectively, these findings highlight molecular insight on non-HLA AS risk loci that are not exclusively connected with overlapping immune mediated diseases; rather a component of common pathophysiological pathways with other immune mediated diseases. This information will be pivotal to fully explain AS pathogenesis and identify new therapeutic targets. PMID:25980808

  1. Identifying progression related disease risk modules based on the human subcellular signaling networks.

    PubMed

    Xie, Ruiqiang; Huang, Hao; Li, Wan; Chen, Binbin; Jiang, Jing; He, Yuehan; Lv, Junjie; ma, Bo; Zhou, Yanyan; Feng, Chenchen; Chen, Lina; He, Weiming

    2014-12-01

    Many studies have shown that the structure and dynamics of the human signaling network are disturbed in complex diseases such as coronary artery disease, and gene expression profiles can distinguish variations in diseases since they can accurately reflect the status of cells. Integration of subcellular localization and the human signaling network holds promise for providing insight into human diseases. In this study, we performed a novel algorithm to identify progression-related-disease-risk modules (PRDRMs) among patients of different disease states within eleven subcellular sub-networks from a human signaling network. The functional annotation and literature retrieval showed that the PRDRMs were strongly associated with disease pathogenesis. The results indicated that the PRDRM expression values as classification features had a good classification performance to distinguish patients of different disease states. Our approach compared with the method PageRank had a better classification performance. The identification of the PRDRMs in response to the dynamic gene expression change could facilitate our understanding of the pathological basis of complex diseases. Our strategy could provide new insights into the potential use of prognostic biomarkers and the effective guidance of clinical therapy from the human subcellular signaling network perspective. PMID:25315201

  2. 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

  3. 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

  4. 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

  5. Identifying sarcomere gene mutations in hypertrophic cardiomyopathy: a personal history.

    PubMed

    Seidman, Christine E; Seidman, J G

    2011-03-18

    This review provides an historical and personal perspective on the discovery of genetic causes for hypertrophic cardiomyopathy (HCM). Extraordinary insights by 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

  6. 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

  7. 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

  8. Thick and thin filament gene mutations in striated muscle diseases.

    PubMed

    Tajsharghi, Homa

    2008-06-01

    The sarcomere is the fundamental unit of cardiac and skeletal muscle contraction. During the last ten years, there has been growing awareness of the etiology of skeletal and cardiac muscle diseases originating in the sarcomere, an important evolving field. Many sarcomeric diseases affect newborn children, i. e. are congenital myopathies. The discovery and characterization of several myopathies caused by mutations in myosin heavy chain genes, coding for the major component of skeletal muscle thick filaments, has led to the introduction of a new entity in the field of neuromuscular disorders: myosin myopathies. Recently, mutations in genes coding for skeletal muscle thin filaments, associated with various clinical features, have been identified. These mutations evoke distinct structural changes within the sarcomeric thin filament. Current knowledge regarding contractile protein dysfunction as it relates to disease pathogenesis has failed to decipher the mechanistic links between mutations identified in sarcomeric proteins and skeletal myopathies, which will no doubt require an integrated physiological approach. The discovery of additional genes associated with myopathies and the elucidation of the molecular mechanisms of pathogenesis will lead to improved and more accurate diagnosis, including prenatally, and to enhanced potential for prognosis, genetic counseling and developing possible treatments for these diseases. The goal of this review is to present recent progress in the identification of gene mutations from each of the major structural components of the sarcomere, the thick and thin filaments, related to skeletal muscle disease. The genetics and clinical manifestations of these disorders will be discussed. PMID:19325803

  9. Thick and Thin Filament Gene Mutations in Striated Muscle Diseases

    PubMed Central

    Tajsharghi, Homa

    2008-01-01

    The sarcomere is the fundamental unit of cardiac and skeletal muscle contraction. During the last ten years, there has been growing awareness of the etiology of skeletal and cardiac muscle diseases originating in the sarcomere, an important evolving field. Many sarcomeric diseases affect newborn children, i. e. are congenital myopathies. The discovery and characterization of several myopathies caused by mutations in myosin heavy chain genes, coding for the major component of skeletal muscle thick filaments, has led to the introduction of a new entity in the field of neuromuscular disorders: myosin myopathies. Recently, mutations in genes coding for skeletal muscle thin filaments, associated with various clinical features, have been identified. These mutations evoke distinct structural changes within the sarcomeric thin filament. Current knowledge regarding contractile protein dysfunction as it relates to disease pathogenesis has failed to decipher the mechanistic links between mutations identified in sarcomeric proteins and skeletal myopathies, which will no doubt require an integrated physiological approach. The discovery of additional genes associated with myopathies and the elucidation of the molecular mechanisms of pathogenesis will lead to improved and more accurate diagnosis, including prenatally, and to enhanced potential for prognosis, genetic counseling and developing possible treatments for these diseases. The goal of this review is to present recent progress in the identification of gene mutations from each of the major structural components of the sarcomere, the thick and thin filaments, related to skeletal muscle disease. The genetics and clinical manifestations of these disorders will be discussed. PMID:19325803

  10. 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

  11. 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

  12. TimeXNet: Identifying active gene sub-networks using time-course gene expression profiles

    PubMed Central

    2014-01-01

    Background Time-course gene expression profiles are frequently used to provide insight into the changes in cellular state over time and to infer the molecular pathways involved. When combined with large-scale molecular interaction networks, such data can provide information about the dynamics of cellular response to stimulus. However, few tools are currently available to predict a single active gene sub-network from time-course gene expression profiles. Results We introduce a tool, TimeXNet, which identifies active gene sub-networks with temporal paths using time-course gene expression profiles in the context of a weighted gene regulatory and protein-protein interaction network. TimeXNet uses a specialized form of the network flow optimization approach to identify the most probable paths connecting the genes with significant changes in expression at consecutive time intervals. TimeXNet has been extensively evaluated for its ability to predict novel regulators and their associated pathways within active gene sub-networks in the mouse innate immune response and the yeast osmotic stress response. Compared to other similar methods, TimeXNet identified up to 50% more novel regulators from independent experimental datasets. It predicted paths within a greater number of known pathways with longer overlaps (up to 7 consecutive edges) within these pathways. TimeXNet was also shown to be robust in the presence of varying amounts of noise in the molecular interaction network. Conclusions TimeXNet is a reliable tool that can be used to study cellular response to stimuli through the identification of time-dependent active gene sub-networks in diverse biological systems. It is significantly better than other similar tools. TimeXNet is implemented in Java as a stand-alone application and supported on Linux, MS Windows and Macintosh. The output of TimeXNet can be directly viewed in Cytoscape. TimeXNet is freely available for non-commercial users. PMID:25522063

  13. 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

  14. USE OF DNA MARKERS TO IDENTIFY BLASTS RESISTANCE GENES IN THE WILD RELATIVES OF RICE (ORYZA SP.)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Blast (Pyricularia grisea Cav.) is the major fungal disease affecting rice (Oryza sativa L.) in the USA. Wild species often have served as sources of new and unique disease resistance genes for crop plants. Research objectives were to 1) identify polymorphic microsatellite (DNA) markers, especiall...

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. Identifying concerted evolution and gene conversion in mammalian gene pairs lasting over 100 million years

    PubMed Central

    Carson, Andrew R; Scherer, Stephen W

    2009-01-01

    Background Concerted evolution occurs in multigene families and is characterized by stretches of homogeneity and higher sequence similarity between paralogues than between orthologues. Here we identify human gene pairs that have undergone concerted evolution, caused by ongoing gene conversion, since at least the human-mouse divergence. Our strategy involved the identification of duplicated genes with greater similarity within a species than between species. These genes were required to be present in multiple mammalian genomes, suggesting duplication early in mammalian divergence. To eliminate genes that have been conserved due to strong purifying selection, our analysis also required at least one intron to have retained high sequence similarity between paralogues. Results We identified three human gene pairs undergoing concerted evolution (BMP8A/B, DDX19A/B, and TUBG1/2). Phylogenetic investigations reveal that in each case the duplication appears to have occurred prior to eutherian mammalian radiation, with exactly two paralogues present in all examined species. This indicates that all three gene duplication events were established over 100 million years ago. Conclusion The extended duration of concerted evolution in multiple distant lineages suggests that there has been prolonged homogenization of specific segments within these gene pairs. Although we speculate that selection for homogenization could have been utilized in order to maintain crucial homo- or hetero- binding domains, it remains unclear why gene conversion has persisted for such extended periods of time. Through these analyses, our results demonstrate additional examples of a process that plays a definite, although unspecified, role in molecular evolution. PMID:19583854

  2. 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...

  3. 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

  4. 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 application of the bioinformatic tool here presented shows a neat way to achieve such molecular characterization of the diseases using genome-wide expression data. PMID:26040557

  5. 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

  6. 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

  7. 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

  8. Combining gene expression and genetic analyses to identify candidate genes involved in cold responses in pea.

    PubMed

    Legrand, Sylvain; Marque, Gilles; Blassiau, Christelle; Bluteau, Aurélie; Canoy, Anne-Sophie; Fontaine, Véronique; Jaminon, Odile; Bahrman, Nasser; Mautord, Julie; Morin, Julie; Petit, Aurélie; Baranger, Alain; Rivière, Nathalie; Wilmer, Jeroen; Delbreil, Bruno; Lejeune-Hénaut, Isabelle

    2013-09-01

    Cold stress affects plant growth and development. In order to better understand the responses to cold (chilling or freezing tolerance), we used two contrasted pea lines. Following a chilling period, the Champagne line becomes tolerant to frost whereas the Terese line remains sensitive. Four suppression subtractive hybridisation libraries were obtained using mRNAs isolated from pea genotypes Champagne and Terese. Using quantitative polymerase chain reaction (qPCR) performed on 159 genes, 43 and 54 genes were identified as differentially expressed at the initial time point and during the time course study, respectively. Molecular markers were developed from the differentially expressed genes and were genotyped on a population of 164 RILs derived from a cross between Champagne and Terese. We identified 5 candidate genes colocalizing with 3 different frost damage quantitative trait loci (QTL) intervals and a protein quantity locus (PQL) rich region previously reported. This investigation revealed the role of constitutive differences between both genotypes in the cold responses, in particular with genes related to glycine degradation pathway that could confer to Champagne a better frost tolerance. We showed that freezing tolerance involves a decrease of expression of genes related to photosynthesis and the expression of a gene involved in the production of cysteine and methionine that could act as cryoprotectant molecules. Although it remains to be confirmed, this study could also reveal the involvement of the jasmonate pathway in the cold responses, since we observed that two genes related to this pathway were mapped in a frost damage QTL interval and in a PQL rich region interval, respectively. PMID:23632303

  9. 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

  10. Identifying Unstable Regions of Proteins Involved in Misfolding Diseases

    NASA Astrophysics Data System (ADS)

    Guest, Will; Cashman, Neil; Plotkin, Steven

    2009-05-01

    Protein misfolding is a necessary step in the pathogenesis of many diseases, including Creutzfeldt-Jakob disease (CJD) and familial amyotrophic lateral sclerosis (fALS). Identifying unstable structural elements in their causative proteins elucidates the early events of misfolding and presents targets for inhibition of the disease process. An algorithm was developed to calculate the Gibbs free energy of unfolding for all sequence-contiguous regions of a protein using three methods to parameterize energy changes: a modified G=o model, changes in solvent-accessible surface area, and all-atoms molecular dynamics. The entropic effects of disulfide bonds and post-translational modifications are treated analytically. It incorporates a novel method for finding local dielectric constants inside a protein to accurately handle charge effects. We have predicted the unstable parts of prion protein and superoxide dismutase 1, the proteins involved in CJD and fALS respectively, and have used these regions as epitopes to prepare antibodies that are specific to the misfolded conformation and show promise as therapeutic agents.

  11. 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

  12. Gene-Wide Analysis Detects Two New Susceptibility Genes for Alzheimer's Disease

    PubMed Central

    Harold, Denise; Jones, Lesley; Holmans, Peter; Gerrish, Amy; Vedernikov, Alexey; Richards, Alexander; DeStefano, Anita L.; Lambert, Jean-Charles; Ibrahim-Verbaas, Carla A.; Naj, Adam C.; Sims, Rebecca; Jun, Gyungah; Bis, Joshua C.; Beecham, Gary W.; Grenier-Boley, Benjamin; Russo, Giancarlo; Thornton-Wells, Tricia A.; Denning, Nicola; Smith, Albert V.; Chouraki, Vincent; Thomas, Charlene; Ikram, M. Arfan; Zelenika, Diana; Vardarajan, Badri N.; Kamatani, Yoichiro; Lin, Chiao-Feng; Schmidt, Helena; Kunkle, Brian; Dunstan, Melanie L.; Vronskaya, Maria; Johnson, Andrew D.; Ruiz, Agustin; Bihoreau, Marie-Thérèse; Reitz, Christiane; Pasquier, Florence; Hollingworth, Paul; Hanon, Olivier; Fitzpatrick, Annette L.; Buxbaum, Joseph D.; Campion, Dominique; Crane, Paul K.; Baldwin, Clinton; Becker, Tim; Gudnason, Vilmundur; Cruchaga, Carlos; Craig, David; Amin, Najaf; Berr, Claudine; Lopez, Oscar L.; De Jager, Philip L.; Deramecourt, Vincent; Johnston, Janet A.; Evans, Denis; Lovestone, Simon; Letenneur, Luc; Hernández, Isabel; Rubinsztein, David C.; Eiriksdottir, Gudny; Sleegers, Kristel; Goate, Alison M.; Fiévet, Nathalie; Huentelman, Matthew J.; Gill, Michael; Brown, Kristelle; Kamboh, M. Ilyas; Keller, Lina; Barberger-Gateau, Pascale; McGuinness, Bernadette; Larson, Eric B.; Myers, Amanda J.; Dufouil, Carole; Todd, Stephen; Wallon, David; Love, Seth; Rogaeva, Ekaterina; Gallacher, John; George-Hyslop, Peter St; Clarimon, Jordi; Lleo, Alberto; Bayer, Anthony; Tsuang, Debby W.; Yu, Lei; Tsolaki, Magda; Bossù, Paola; Spalletta, Gianfranco; Proitsi, Petra; Collinge, John; Sorbi, Sandro; Garcia, Florentino Sanchez; Fox, Nick C.; Hardy, John; Naranjo, Maria Candida Deniz; Bosco, Paolo; Clarke, Robert; Brayne, Carol; Galimberti, Daniela; Scarpini, Elio; Bonuccelli, Ubaldo; Mancuso, Michelangelo; Siciliano, Gabriele; Moebus, Susanne; Mecocci, Patrizia; Zompo, Maria Del; Maier, Wolfgang; Hampel, Harald; Pilotto, Alberto; Frank-García, Ana; Panza, Francesco; Solfrizzi, Vincenzo; Caffarra, Paolo; Nacmias, Benedetta; Perry, William; Mayhaus, Manuel; Lannfelt, Lars; Hakonarson, Hakon; Pichler, Sabrina; Carrasquillo, Minerva M.; Ingelsson, Martin; Beekly, Duane; Alvarez, Victoria; Zou, Fanggeng; Valladares, Otto; Younkin, Steven G.; Coto, Eliecer; Hamilton-Nelson, Kara L.; Gu, Wei; Razquin, Cristina; Pastor, Pau; Mateo, Ignacio; Owen, Michael J.; Faber, Kelley M.; Jonsson, Palmi V.; Combarros, Onofre; O'Donovan, Michael C.; Cantwell, Laura B.; Soininen, Hilkka; Blacker, Deborah; Mead, Simon; Mosley, Thomas H.; Bennett, David A.; Harris, Tamara B.; Fratiglioni, Laura; Holmes, Clive; de Bruijn, Renee F. A. G.; Passmore, Peter; Montine, Thomas J.; Bettens, Karolien; Rotter, Jerome I.; Brice, Alexis; Morgan, Kevin; Foroud, Tatiana M.; Kukull, Walter A.; Hannequin, Didier; Powell, John F.; Nalls, Michael A.; Ritchie, Karen; Lunetta, Kathryn L.; Kauwe, John S. K.; Boerwinkle, Eric; Riemenschneider, Matthias; Boada, Mercè; Hiltunen, Mikko; Martin, Eden R.; Schmidt, Reinhold; Rujescu, Dan; Dartigues, Jean-François; Mayeux, Richard; Tzourio, Christophe; Hofman, Albert; Nöthen, Markus M.; Graff, Caroline; Psaty, Bruce M.; Haines, Jonathan L.; Lathrop, Mark; Pericak-Vance, Margaret A.; Launer, Lenore J.; Van Broeckhoven, Christine; Farrer, Lindsay A.; van Duijn, Cornelia M.; Ramirez, Alfredo

    2014-01-01

    Background Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. Principal Findings In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10−6) and 14 (IGHV1-67 p = 7.9×10−8) which indexed novel susceptibility loci. Significance The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease. PMID:24922517

  13. Clinical Markers for Identifying Cholinergic Deficits in Parkinson's Disease

    PubMed Central

    Müller, Martijn L.T.M.; Bohnen, Nicolaas I.; Kotagal, Vikas; Scott, Peter J.H.; Koeppe, Robert A.; Frey, Kirk A.; Albin, Roger L.

    2014-01-01

    Background Cholinergic projection systems degeneration is associated with dopamine non-responsive features of Parkinson's disease (PD). Cholinergic deficits are variable in non-demented PD. Identification of cholinergic deficits in PD may help with selection of suitable patients for targeted cholinergic drug treatment in PD. The objective of this retrospective multivariate predictor analysis study was to identify clinical markers indicative of cholinergic deficits in PD patients, as assessed by acetylcholinesterase ([11C]PMP) positron emission tomography. Methods One hundred thirty-seven PD patients (34 female) participated; median modified Hoehn and Yahr score was 2.5 (range 1–4), average age of 65.6 ± 7.4 years, and average duration of motor disease symptoms of 6.0 ± 4.2 years. Subjects were dichotomized as “normocholinergic” or “hypocholinergic” based on a 5th percentile cutoff from normal for the basal forebrain-cortical and pedunculopontine nucleus-thalamic cholinergic projection systems. Previously identified clinical indices of cholinergic denervation were used for statistical prediction of cholinergic deficits. Logistic regression determined which risk factors predicted cholinergic deficits. Sensitivity, specificity, and accuracy were determined for the (combinations of) significant predictor variables. Results There were 49 (35.8%) hypocholinergic PD subjects. The combination of RBD symptoms and fall history showed highest diagnostic accuracy (81.1%) for predicting combined thalamic and cortical cholinergic deficits. A combined assessment of 8.5 meter walk time and lower score on the Montreal cognitive assessment scale provided diagnostic accuracy of 80.7 % for predicting isolated cortical cholinergic denervation. Conclusion Assessment of clinical indices of cholinergic denervation may be useful for identifying suitable subjects for trials of targeted cholinergic drug treatments in PD. PMID:25393613

  14. 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 Mta1 functions. PMID:21364872

  15. Brain expression genome-wide association study (eGWAS) identifies human disease-associated variants.

    PubMed

    Zou, Fanggeng; Chai, High Seng; Younkin, Curtis S; Allen, Mariet; Crook, Julia; Pankratz, V Shane; Carrasquillo, Minerva M; Rowley, Christopher N; Nair, Asha A; Middha, Sumit; Maharjan, Sooraj; Nguyen, Thuy; Ma, Li; Malphrus, Kimberly G; Palusak, Ryan; Lincoln, Sarah; Bisceglio, Gina; Georgescu, Constantin; Kouri, Naomi; Kolbert, Christopher P; Jen, Jin; Haines, Jonathan L; Mayeux, Richard; Pericak-Vance, Margaret A; Farrer, Lindsay A; Schellenberg, Gerard D; Petersen, Ronald C; Graff-Radford, Neill R; Dickson, Dennis W; Younkin, Steven G; Ertekin-Taner, Nilüfer

    2012-01-01

    Genetic variants that modify brain gene expression may also influence risk for human diseases. We measured expression levels of 24,526 transcripts in brain samples from the cerebellum and temporal cortex of autopsied subjects with Alzheimer's disease (AD, cerebellar n=197, temporal cortex n=202) and with other brain pathologies (non-AD, cerebellar n=177, temporal cortex n=197). We conducted an expression genome-wide association study (eGWAS) using 213,528 cisSNPs within ± 100 kb of the tested transcripts. We identified 2,980 cerebellar cisSNP/transcript level associations (2,596 unique cisSNPs) significant in both ADs and non-ADs (q<0.05, p=7.70 × 10(-5)-1.67 × 10(-82)). Of these, 2,089 were also significant in the temporal cortex (p=1.85 × 10(-5)-1.70 × 10(-141)). The top cerebellar cisSNPs had 2.4-fold enrichment for human disease-associated variants (p<10(-6)). We identified novel cisSNP/transcript associations for human disease-associated variants, including progressive supranuclear palsy SLCO1A2/rs11568563, Parkinson's disease (PD) MMRN1/rs6532197, Paget's disease OPTN/rs1561570; and we confirmed others, including PD MAPT/rs242557, systemic lupus erythematosus and ulcerative colitis IRF5/rs4728142, and type 1 diabetes mellitus RPS26/rs1701704. In our eGWAS, there was 2.9-3.3 fold enrichment (p<10(-6)) of significant cisSNPs with suggestive AD-risk association (p<10(-3)) in the Alzheimer's Disease Genetics Consortium GWAS. These results demonstrate the significant contributions of genetic factors to human brain gene expression, which are reliably detected across different brain regions and pathologies. The significant enrichment of brain cisSNPs among disease-associated variants advocates gene expression changes as a mechanism for many central nervous system (CNS) and non-CNS diseases. Combined assessment of expression and disease GWAS may provide complementary information in discovery of human disease variants with functional implications. Our findings have implications for the design and interpretation of eGWAS in general and the use of brain expression quantitative trait loci in the study of human disease genetics. PMID:22685416

  16. Brain Expression Genome-Wide Association Study (eGWAS) Identifies Human Disease-Associated Variants

    PubMed Central

    Crook, Julia; Pankratz, V. Shane; Carrasquillo, Minerva M.; Rowley, Christopher N.; Nair, Asha A.; Middha, Sumit; Maharjan, Sooraj; Nguyen, Thuy; Ma, Li; Malphrus, Kimberly G.; Palusak, Ryan; Lincoln, Sarah; Bisceglio, Gina; Georgescu, Constantin; Kouri, Naomi; Kolbert, Christopher P.; Jen, Jin; Haines, Jonathan L.; Mayeux, Richard; Pericak-Vance, Margaret A.; Farrer, Lindsay A.; Schellenberg, Gerard D.; Petersen, Ronald C.; Graff-Radford, Neill R.; Dickson, Dennis W.; Younkin, Steven G.; Ertekin-Taner, Nilüfer

    2012-01-01

    Genetic variants that modify brain gene expression may also influence risk for human diseases. We measured expression levels of 24,526 transcripts in brain samples from the cerebellum and temporal cortex of autopsied subjects with Alzheimer's disease (AD, cerebellar n = 197, temporal cortex n = 202) and with other brain pathologies (non–AD, cerebellar n = 177, temporal cortex n = 197). We conducted an expression genome-wide association study (eGWAS) using 213,528 cisSNPs within ±100 kb of the tested transcripts. We identified 2,980 cerebellar cisSNP/transcript level associations (2,596 unique cisSNPs) significant in both ADs and non–ADs (q<0.05, p = 7.70×10−5–1.67×10−82). Of these, 2,089 were also significant in the temporal cortex (p = 1.85×10−5–1.70×10−141). The top cerebellar cisSNPs had 2.4-fold enrichment for human disease-associated variants (p<10−6). We identified novel cisSNP/transcript associations for human disease-associated variants, including progressive supranuclear palsy SLCO1A2/rs11568563, Parkinson's disease (PD) MMRN1/rs6532197, Paget's disease OPTN/rs1561570; and we confirmed others, including PD MAPT/rs242557, systemic lupus erythematosus and ulcerative colitis IRF5/rs4728142, and type 1 diabetes mellitus RPS26/rs1701704. In our eGWAS, there was 2.9–3.3 fold enrichment (p<10−6) of significant cisSNPs with suggestive AD–risk association (p<10−3) in the Alzheimer's Disease Genetics Consortium GWAS. These results demonstrate the significant contributions of genetic factors to human brain gene expression, which are reliably detected across different brain regions and pathologies. The significant enrichment of brain cisSNPs among disease-associated variants advocates gene expression changes as a mechanism for many central nervous system (CNS) and non–CNS diseases. Combined assessment of expression and disease GWAS may provide complementary information in discovery of human disease variants with functional implications. Our findings have implications for the design and interpretation of eGWAS in general and the use of brain expression quantitative trait loci in the study of human disease genetics. PMID:22685416

  17. MouseFinder: candidate disease genes from mouse phenotype data

    PubMed Central

    Chen, Chao-Kung; Mungall, Christopher J; Gkoutos, Georgios V; Doelken, Sandra C; Köhler, Sebastian; Ruef, Barbara J; Smith, Cynthia; Westerfield, Monte; Robinson, Peter N; Lewis, Suzanna E; Schofield, Paul N; Smedley, Damian

    2012-01-01

    Mouse phenotype data represents a valuable resource for the identification of disease-associated genes, especially where the molecular basis is unknown and there is no clue to the candidate gene’s function, pathway involvement or expression pattern. However, until recently these data have not been systematically used due to difficulties in mapping between clinical features observed in humans and mouse phenotype annotations. Here, we describe a semantic approach to solve this problem and demonstrate highly significant recall of known disease-gene associations and orthology relationships. A web application (MouseFinder; www.mousemodels.org) has been developed to allow users to search the results of our whole-phenome comparison of human and mouse. We demonstrate its use in identifying ARTN as a strong candidate gene within the 1p34.1-p32 mapped locus for a hereditary form of ptosis. PMID:22331800

  18. Integrating genomic and epigenomic information: a promising strategy for identifying functional DNA variants of human disease.

    PubMed

    Zaina, S; Lund, G

    2012-04-01

    In a clinical setting diagnosis, heritability, risk and outcome of human disease rely heavily on the use of markers present in specific tissues. In the past decade, the development of genome-wide, non-hypothesis driven methods to identify molecular markers associated with disease have led to the discovery of numerous genetic variations associated with specific human diseases, the majority of which map within non-coding regions of the genome. In parallel, whole-genome studies focused on the role of gene regulatory epigenetic modifications such as DNA methylation and histone modifications are providing a conceptual framework for understanding the functional significance of sequence variation in human disease. This review highlights selected recent development in epigenetics and discusses their implications with respect to the identification of functional or novel single nucleotide polymorphisms. PMID:22292420

  19. Murine candidate bleomycin induced pulmonary fibrosis susceptibility genes identified by gene expression and sequence analysis of linkage regions

    PubMed Central

    Haston, C; Tomko, T; Godin, N; Kerckhoff, L; Hallett, M

    2005-01-01

    Background: Pulmonary fibrosis is a complex disease for which the predisposing genetic variants remain unknown. In a prior study, susceptibility to bleomycin induced pulmonary fibrosis was mapped to loci Blmpf1 and Blmpf2 on chromosomes 17 and 11, respectively, in a C57BL/6J (B6, susceptible) and C3Hf/KAM (C3H, resistant) mouse cross. Methods: Herein, the genetic basis of bleomycin induced pulmonary fibrosis was investigated in an approach combining gene expression and sequencing data with previously mapped linkage intervals. Results: In this study, gene expression analysis with microarrays revealed 1892 genes or ESTs (expressed sequence tags) to be differentially expressed between bleomycin treated B6 and C3H mice and 67 of these genetic elements map to Blmpf1 or Blmpf2. This group included genes involved in an oxidative stress response, in apoptosis, and in immune regulation. A comparison of the B6 and C3H sequence, for Blmpf1 and Blmpf2, made using the NCBI database and available C3H sequence, revealed approximately 35% of the genes in these regions contain non-synonymous coding sequence changes. An assessment of genotype/phenotype correlation among other inbred strains revealed 36% of these B6/C3H sequence variations predict for the known bleomycin induced fibrosis susceptibility of the DBA (susceptible) and A/J (resistant) mouse strains. Conclusions: Combining genomics approaches of differential gene expression and sequence variation potentially identifies approximately 5% the linked genes as fibrosis susceptibility candidate genes in this mouse cross. PMID:15937080

  20. Identifying dysregulated genes induced by Kaposi's sarcoma-associated herpesvirus (KSHV).

    PubMed

    Alcendor, Donald; Knobel, Susan

    2010-01-01

    Currently KS is the most predominant HIV/AIDS related malignancy in Southern Africa and hence the world. It is characterized as an angioproliferative tumor of vascular endothelial cells and produces rare B cell lymphoproliferative diseases in the form of pleural effusion lymphomas (PEL) and some forms of multicentric Castleman's disease. Only 1-5% of cells in KS lesions actively support lytic replication of Kaposi's sarcoma-associated herpesvirus (KSHV), the etiological agent associated with KS, and it is clear that cellular factors must interact with viral factors in the process of oncogenesis and tumor progression. Identifying novel host-factor determinants which contribute to KS pathology is essential for developing prognostic markers for tumor progression and metastasis as well as for developing novel therapeutics for the treatment of KS. The accompanying video details the methods we use to identify host cell gene expression programs altered in dermal microvascular endothelial cells (DMVEC) after KSHV infection and in KS tumor tissue. Once dysregulated genes are identified by microarray analysis, changes in protein expression are confirmed by immunoblot and dual labeled immunofluorescence. Changes in transcriptional expression of dysregulated genes are confirmed in vitro by quantitative real-time polymerase chain reaction (qRT-PCR). Validation of in vitro findings using archival KS tumor tissue is also performed by dual labeled immunochemistry and tissue microarrays. Our approach to identifying dysregulated genes in the KS tumor tissue microenvironment will allow the development of in vitro and subsequently in vivo model systems for discovery and evaluation of potential novel therapeutic for the treatment of KS. PMID:20864930

  1. Analysis of the robustness of network-based disease-gene prioritization methods reveals redundancy in the human interactome and functional diversity of disease-genes.

    PubMed

    Guney, Emre; Oliva, Baldo

    2014-01-01

    Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO) analysis highlighted the role of functional diversity for such diseases. PMID:24733074

  2. Connectivity mapping using a combined gene signature from multiple colorectal cancer datasets identified candidate drugs including existing chemotherapies

    PubMed Central

    2015-01-01

    Background While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease. Results We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations. PMID:26356760

  3. Analysis of the retinal gene expression profile after hypoxic preconditioning identifies candidate genes for neuroprotection

    PubMed Central

    Thiersch, Markus; Raffelsberger, Wolfgang; Frigg, Rico; Samardzija, Marijana; Wenzel, Andreas; Poch, Olivier; Grimm, Christian

    2008-01-01

    Background Retinal degeneration is a main cause of blindness in humans. Neuroprotective therapies may be used to rescue retinal cells and preserve vision. Hypoxic preconditioning stabilizes the transcription factor HIF-1? in the retina and strongly protects photoreceptors in an animal model of light-induced retinal degeneration. To address the molecular mechanisms of the protection, we analyzed the transcriptome of the hypoxic retina using microarrays and real-time PCR. Results Hypoxic exposure induced a marked alteration in the retinal transcriptome with significantly different expression levels of 431 genes immediately after hypoxic exposure. The normal expression profile was restored within 16 hours of reoxygenation. Among the differentially regulated genes, several candidates for neuroprotection were identified like metallothionein-1 and -2, the HIF-1 target gene adrenomedullin and the gene encoding the antioxidative and cytoprotective enzyme paraoxonase 1 which was previously not known to be a hypoxia responsive gene in the retina. The strongly upregulated cyclin dependent kinase inhibitor p21 was excluded from being essential for neuroprotection. Conclusion Our data suggest that neuroprotection after hypoxic preconditioning is the result of the differential expression of a multitude of genes which may act in concert to protect visual cells against a toxic insult. PMID:18261226

  4. Transcriptome profiling to identify genes involved in pathogenicity of Valsa mali on apple tree.

    PubMed

    Ke, Xiwang; Yin, Zhiyuan; Song, Na; Dai, Qingqing; Voegele, Ralf T; Liu, Yangyang; Wang, Haiying; Gao, Xiaoning; Kang, Zhensheng; Huang, Lili

    2014-07-01

    Apple Valsa canker, caused by the fungus Valsa mali (Vm), is one of the most destructive diseases of apple in China. A better understanding of this host-pathogen interaction is urgently needed to improve management strategies. In the current study we sequenced the transcriptomes of Vm during infection of apple bark and mycelium grown in axenic culture using Illumina RNA-Seq technology. We identified 437 genes that were differentially expressed during fungal infection compared to fungal mycelium grown in axenic culture. One hundred and thirty nine of these 437 genes showed more than two fold higher transcript abundance during infection. GO and KEGG enrichment analyses of the up-regulated genes suggest prevalence of genes associated with pectin catabolic, hydrolase activity and secondary metabolite biosynthesis during fungal infection. Some of the up-regulated genes associated with loss of pathogenicity and reduced virulence annotated by host-pathogen interaction databases may also be involved in cell wall hydrolysis and secondary metabolite transport, including a glycoside hydrolase family 28 protein, a peptidase and two major facilitator superfamily proteins. This highlights the importance of secondary metabolites and cell wall hydrolases during establishment of apple Valsa canker. Functional verification of the genes involved in pathogenicity of Vm will allow us to better understand how the fungus interferes with the host machinery and assists in apple canker establishment. PMID:24747070

  5. Whole-exome sequencing identifies rare pathogenic variants in new predisposition genes for familial colorectal cancer

    PubMed Central

    Esteban-Jurado, Clara; Vila-Casadesús, Maria; Garre, Pilar; Lozano, Juan José; Pristoupilova, Anna; Beltran, Sergi; Muñoz, Jenifer; Ocaña, Teresa; Balaguer, Francesc; López-Cerón, Maria; Cuatrecasas, Miriam; Franch-Expósito, Sebastià; Piqué, Josep M.; Castells, Antoni; Carracedo, Angel; Ruiz-Ponte, Clara; Abulí, Anna; Bessa, Xavier; Andreu, Montserrat; Bujanda, Luis; Caldés, Trinidad; Castellví-Bel, Sergi

    2015-01-01

    Purpose: Colorectal cancer is an important cause of mortality in the developed world. Hereditary forms are due to germ-line mutations in APC, MUTYH, and the mismatch repair genes, but many cases present familial aggregation but an unknown inherited cause. The hypothesis of rare high-penetrance mutations in new genes is a likely explanation for the underlying predisposition in some of these familial cases. Methods: Exome sequencing was performed in 43 patients with colorectal cancer from 29 families with strong disease aggregation without mutations in known hereditary colorectal cancer genes. Data analysis selected only very rare variants (0–0.1%), producing a putative loss of function and located in genes with a role compatible with cancer. Variants in genes previously involved in hereditary colorectal cancer or nearby previous colorectal cancer genome-wide association study hits were also chosen. Results: Twenty-eight final candidate variants were selected and validated by Sanger sequencing. Correct family segregation and somatic studies were used to categorize the most interesting variants in CDKN1B, XRCC4, EPHX1, NFKBIZ, SMARCA4, and BARD1. Conclusion: We identified new potential colorectal cancer predisposition variants in genes that have a role in cancer predisposition and are involved in DNA repair and the cell cycle, which supports their putative involvement in germ-line predisposition to this neoplasm. PMID:25058500

  6. GWAS identifies novel SLE susceptibility genes and explains the association of the HLA region.

    PubMed

    Armstrong, D L; Zidovetzki, R; Alarcón-Riquelme, M E; Tsao, B P; Criswell, L A; Kimberly, R P; Harley, J B; Sivils, K L; Vyse, T J; Gaffney, P M; Langefeld, C D; Jacob, C O

    2014-09-01

    In a genome-wide association study (GWAS) of individuals of European ancestry afflicted with systemic lupus erythematosus (SLE) the extensive utilization of imputation, step-wise multiple regression, lasso regularization and increasing study power by utilizing false discovery rate instead of a Bonferroni multiple test correction enabled us to identify 13 novel non-human leukocyte antigen (HLA) genes and confirmed the association of four genes previously reported to be associated. Novel genes associated with SLE susceptibility included two transcription factors (EHF and MED1), two components of the NF-κB pathway (RASSF2 and RNF114), one gene involved in adhesion and endothelial migration (CNTN6) and two genes involved in antigen presentation (BIN1 and SEC61G). In addition, the strongly significant association of multiple single-nucleotide polymorphisms (SNPs) in the HLA region was assigned to HLA alleles and serotypes and deconvoluted into four primary signals. The novel SLE-associated genes point to new directions for both the diagnosis and treatment of this debilitating autoimmune disease. PMID:24871463

  7. Network-based prediction and knowledge mining of disease genes

    PubMed Central

    2015-01-01

    Background In recent years, high-throughput protein interaction identification methods have generated a large amount of data. When combined with the results from other in vivo and in vitro experiments, a complex set of relationships between biological molecules emerges. The growing popularity of network analysis and data mining has allowed researchers to recognize indirect connections between these molecules. Due to the interdependent nature of network entities, evaluating proteins in this context can reveal relationships that may not otherwise be evident. Methods We examined the human protein interaction network as it relates to human illness using the Disease Ontology. After calculating several topological metrics, we trained an alternating decision tree (ADTree) classifier to identify disease-associated proteins. Using a bootstrapping method, we created a tree to highlight conserved characteristics shared by many of these proteins. Subsequently, we reviewed a set of non-disease-associated proteins that were misclassified by the algorithm with high confidence and searched for evidence of a disease relationship. Results Our classifier was able to predict disease-related genes with 79% area under the receiver operating characteristic (ROC) curve (AUC), which indicates the tradeoff between sensitivity and specificity and is a good predictor of how a classifier will perform on future data sets. We found that a combination of several network characteristics including degree centrality, disease neighbor ratio, eccentricity, and neighborhood connectivity help to distinguish between disease- and non-disease-related proteins. Furthermore, the ADTree allowed us to understand which combinations of strongly predictive attributes contributed most to protein-disease classification. In our post-processing evaluation, we found several examples of potential novel disease-related proteins and corresponding literature evidence. In addition, we showed that first- and second-order neighbors in the PPI network could be used to identify likely disease associations. Conclusions We analyzed the human protein interaction network and its relationship to disease and found that both the number of interactions with other proteins and the disease relationship of neighboring proteins helped to determine whether a protein had a relationship to disease. Our classifier predicted many proteins with no annotated disease association to be disease-related, which indicated that these proteins have network characteristics that are similar to disease-related proteins and may therefore have disease associations not previously identified. By performing a post-processing step after the prediction, we were able to identify evidence in literature supporting this possibility. This method could provide a useful filter for experimentalists searching for new candidate protein targets for drug repositioning and could also be extended to include other network and data types in order to refine these predictions. PMID:26043920

  8. Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci

    PubMed Central

    Miller, Clint; Pjanic, Milos; Castano, Victor G.; Kim, Juyong B.; Salfati, Elias L.; Kundaje, Anshul B.; Bejerano, Gill; Assimes, Themistocles; Yang, Xia; Quertermous, Thomas

    2015-01-01

    To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including “growth factor binding,” “matrix interaction,” and “smooth muscle contraction.” We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low P-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology. PMID:26020271

  9. Genetic Mapping and Exome Sequencing Identify Variants Associated with Five Novel Diseases

    PubMed Central

    Puffenberger, Erik G.; Jinks, Robert N.; Sougnez, Carrie; Cibulskis, Kristian; Willert, Rebecca A.; Achilly, Nathan P.; Cassidy, Ryan P.; Fiorentini, Christopher J.; Heiken, Kory F.; Lawrence, Johnny J.; Mahoney, Molly H.; Miller, Christopher J.; Nair, Devika T.; Politi, Kristin A.; Worcester, Kimberly N.; Setton, Roni A.; DiPiazza, Rosa; Sherman, Eric A.; Eastman, James T.; Francklyn, Christopher; Robey-Bond, Susan; Rider, Nicholas L.; Gabriel, Stacey; Morton, D. Holmes; Strauss, Kevin A.

    2012-01-01

    The Clinic for Special Children (CSC) has integrated biochemical and molecular methods into a rural pediatric practice serving Old Order Amish and Mennonite (Plain) children. Among the Plain people, we have used single nucleotide polymorphism (SNP) microarrays to genetically map recessive disorders to large autozygous haplotype blocks (mean = 4.4 Mb) that contain many genes (mean = 79). For some, uninformative mapping or large gene lists preclude disease-gene identification by Sanger sequencing. Seven such conditions were selected for exome sequencing at the Broad Institute; all had been previously mapped at the CSC using low density SNP microarrays coupled with autozygosity and linkage analyses. Using between 1 and 5 patient samples per disorder, we identified sequence variants in the known disease-causing genes SLC6A3 and FLVCR1, and present evidence to strongly support the pathogenicity of variants identified in TUBGCP6, BRAT1, SNIP1, CRADD, and HARS. Our results reveal the power of coupling new genotyping technologies to population-specific genetic knowledge and robust clinical data. PMID:22279524

  10. RNA interference for the identification of disease-associated genes.

    PubMed

    Nencioni, Alessio; Sandy, Peter; Dillon, Christopher; Kissler, Stephan; Blume-Jensen, Peter; Van Parijs, Luk

    2004-04-01

    RNA interference (RNAi) has emerged as a novel cellular mechanism regulating gene expression at the post-transcriptional level and as a powerful tool to control gene function experimentally. Recent advances in the biology and application of RNAi include the definition of improved criteria for selecting effective small interfering RNA (siRNA) sequences, and the generation of vectors for the delivery of siRNAs and stable silencing of genes in mammalian cells, tissues and animals. High-throughput screening projects based on RNAi have been initiated to search for genes involved in basic biological processes and in complex pathological conditions such as cancer, autoimmunity and degenerative disorders. This research is helping to identify novel therapeutic targets for a range of diseases and may translate into novel clinical applications for RNAi. PMID:15195924

  11. Integrating nutrigenomics data to identify cardiometabolic gene-environment interactions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nutrition is a key factor in health and in many age-related diseases. This is particularly the case for cardiometabolic diseases such as cardiovascular disease, type 2 diabetes and hypertension, and is often precluded by obesity, glucose impairment and metabolic syndrome. Our research objectives are...

  12. Identification of susceptibility genes and genetic modifiers of human diseases

    NASA Astrophysics Data System (ADS)

    Abel, Kenneth; Kammerer, Stefan; Hoyal, Carolyn; Reneland, Rikard; Marnellos, George; Nelson, Matthew R.; Braun, Andreas

    2005-03-01

    The completion of the human genome sequence enables the discovery of genes involved in common human disorders. The successful identification of these genes is dependent on the availability of informative sample sets, validated marker panels, a high-throughput scoring technology, and a strategy for combining these resources. We have developed a universal platform technology based on mass spectrometry (MassARRAY) for analyzing nucleic acids with high precision and accuracy. To fuel this technology, we generated more than 100,000 validated assays for single nucleotide polymorphisms (SNPs) covering virtually all known and predicted human genes. We also established a large DNA sample bank comprised of more than 50,000 consented healthy and diseased individuals. This combination of reagents and technology allows the execution of large-scale genome-wide association studies. Taking advantage of MassARRAY"s capability for quantitative analysis of nucleic acids, allele frequencies are estimated in sample pools containing large numbers of individual DNAs. To compare pools as a first-pass "filtering" step is a tremendous advantage in throughput and cost over individual genotyping. We employed this approach in numerous genome-wide, hypothesis-free searches to identify genes associated with common complex diseases, such as breast cancer, osteoporosis, and osteoarthritis, and genes involved in quantitative traits like high density lipoproteins cholesterol (HDL-c) levels and central fat. Access to additional well-characterized patient samples through collaborations allows us to conduct replication studies that validate true disease genes. These discoveries will expand our understanding of genetic disease predisposition, and our ability for early diagnosis and determination of specific disease subtype or progression stage.

  13. A functional screen for copper homeostasis genes identifies a pharmacologically tractable cellular system

    PubMed Central

    2014-01-01

    Background Copper is essential for the survival of aerobic organisms. If copper is not properly regulated in the body however, it can be extremely cytotoxic and genetic mutations that compromise copper homeostasis result in severe clinical phenotypes. Understanding how cells maintain optimal copper levels is therefore highly relevant to human health. Results We found that addition of copper (Cu) to culture medium leads to increased respiratory growth of yeast, a phenotype which we then systematically and quantitatively measured in 5050 homozygous diploid deletion strains. Cu’s positive effect on respiratory growth was quantitatively reduced in deletion strains representing 73 different genes, the function of which identify increased iron uptake as a cause of the increase in growth rate. Conversely, these effects were enhanced in strains representing 93 genes. Many of these strains exhibited respiratory defects that were specifically rescued by supplementing the growth medium with Cu. Among the genes identified are known and direct regulators of copper homeostasis, genes required to maintain low vacuolar pH, and genes where evidence supporting a functional link with Cu has been heretofore lacking. Roughly half of the genes are conserved in man, and several of these are associated with Mendelian disorders, including the Cu-imbalance syndromes Menkes and Wilson’s disease. We additionally demonstrate that pharmacological agents, including the approved drug disulfiram, can rescue Cu-deficiencies of both environmental and genetic origin. Conclusions A functional screen in yeast has expanded the list of genes required for Cu-dependent fitness, revealing a complex cellular system with implications for human health. Respiratory fitness defects arising from perturbations in this system can be corrected with pharmacological agents that increase intracellular copper concentrations. PMID:24708151

  14. Large-scale association study identifies ICAM gene region as breast and prostate cancer susceptibility locus.

    PubMed

    Kammerer, Stefan; Roth, Richard B; Reneland, Richard; Marnellos, George; Hoyal, Carolyn R; Markward, Nathan J; Ebner, Florian; Kiechle, Marion; Schwarz-Boeger, Ulrike; Griffiths, Lyn R; Ulbrich, Christian; Chrobok, Korbinian; Forster, Gerhard; Praetorius, Georg M; Meyer, Peter; Rehbock, Joachim; Cantor, Charles R; Nelson, Matthew R; Braun, Andreas

    2004-12-15

    We conducted a large-scale association study to identify genes that influence nonfamilial breast cancer risk using a collection of German cases and matched controls and >25,000 single nucleotide polymorphisms located within 16,000 genes. One of the candidate loci identified was located on chromosome 19p13.2 [odds ratio (OR) = 1.5, P = 0.001]. The effect was substantially stronger in the subset of cases with reported family history of breast cancer (OR = 3.4, P = 0.001). The finding was subsequently replicated in two independent collections (combined OR = 1.4, P < 0.001) and was also associated with predisposition to prostate cancer in an independent sample set of prostate cancer cases and matched controls (OR = 1.4, P = 0.002). High-density single nucleotide polymorphism mapping showed that the extent of association spans 20 kb and includes the intercellular adhesion molecule genes ICAM1, ICAM4, and ICAM5. Although genetic variants in ICAM5 showed the strongest association with disease status, ICAM1 is expressed at highest levels in normal and tumor breast tissue. A variant in ICAM5 was also associated with disease progression and prognosis. Because ICAMs are suitable targets for antibodies and small molecules, these findings may not only provide diagnostic and prognostic markers but also new therapeutic opportunities in breast and prostate cancer. PMID:15604251

  15. Dissecting the Gene Network of Dietary Restriction to Identify Evolutionarily Conserved Pathways and New Functional Genes

    PubMed Central

    Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

    2012-01-01

    Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR–essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR–essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR–essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR–essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR–induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple organisms led us to suggest that DR commonly suppresses translation, while stimulating an ancient reproduction-related process. PMID:22912585

  16. Human Disease Insight: An integrated knowledge-based platform for disease-gene-drug information.

    PubMed

    Tasleem, Munazzah; Ishrat, Romana; Islam, Asimul; Ahmad, Faizan; Hassan, Md Imtaiyaz

    2016-01-01

    The scope of the Human Disease Insight (HDI) database is not limited to researchers or physicians as it also provides basic information to non-professionals and creates disease awareness, thereby reducing the chances of patient suffering due to ignorance. HDI is a knowledge-based resource providing information on human diseases to both scientists and the general public. Here, our mission is to provide a comprehensive human disease database containing most of the available useful information, with extensive cross-referencing. HDI is a knowledge management system that acts as a central hub to access information about human diseases and associated drugs and genes. In addition, HDI contains well-classified bioinformatics tools with helpful descriptions. These integrated bioinformatics tools enable researchers to annotate disease-specific genes and perform protein analysis, search for biomarkers and identify potential vaccine candidates. Eventually, these tools will facilitate the analysis of disease-associated data. The HDI provides two types of search capabilities and includes provisions for downloading, uploading and searching disease/gene/drug-related information. The logistical design of the HDI allows for regular updating. The database is designed to work best with Mozilla Firefox and Google Chrome and is freely accessible at http://humandiseaseinsight.com. PMID:26631432

  17. Fluid Mechanics, Arterial Disease, and Gene Expression

    PubMed Central

    Tarbell, John M.; Shi, Zhong-Dong; Dunn, Jessilyn; Jo, Hanjoong

    2014-01-01

    This review places modern research developments in vascular mechanobiology in the context of hemodynamic phenomena in the cardiovascular system and the discrete localization of vascular disease. The modern origins of this field are traced, beginning in the 1960s when associations between flow characteristics, particularly blood flow–induced wall shear stress, and the localization of atherosclerotic plaques were uncovered, and continuing to fluid shear stress effects on the vascular lining endothelial) cells (ECs), including their effects on EC morphology, biochemical production, and gene expression. The earliest single-gene studies and genome-wide analyses are considered. The final section moves from the ECs lining the vessel wall to the smooth muscle cells and fibroblasts within the wall that are fluid me chanically activated by interstitial flow that imposes shear stresses on their surfaces comparable with those of flowing blood on EC surfaces. Interstitial flow stimulates biochemical production and gene expression, much like blood flow on ECs. PMID:25360054

  18. Gene Expression in Human Hippocampus from Cocaine Abusers Identifies Genes which Regulate Extracellular Matrix Remodeling

    PubMed Central

    Mash, Deborah C.; ffrench-Mullen, Jarlath; Adi, Nikhil; Qin, Yujing; Buck, Andrew; Pablo, John

    2007-01-01

    The chronic effects of cocaine abuse on brain structure and function are blamed for the inability of most addicts to remain abstinent. Part of the difficulty in preventing relapse is the persisting memory of the intense euphoria or cocaine “rush”. Most abused drugs and alcohol induce neuroplastic changes in brain pathways subserving emotion and cognition. Such changes may account for the consolidation and structural reconfiguration of synaptic connections with exposure to cocaine. Adaptive hippocampal plasticity could be related to specific patterns of gene expression with chronic cocaine abuse. Here, we compare gene expression profiles in the human hippocampus from cocaine addicts and age-matched drug-free control subjects. Cocaine abusers had 151 gene transcripts upregulated, while 91 gene transcripts were downregulated. Topping the list of cocaine-regulated transcripts was RECK in the human hippocampus (FC = 2.0; p<0.05). RECK is a membrane-anchored MMP inhibitor that is implicated in the coordinated regulation of extracellular matrix integrity and angiogenesis. In keeping with elevated RECK expression, active MMP9 protein levels were decreased in the hippocampus from cocaine abusers. Pathway analysis identified other genes regulated by cocaine that code for proteins involved in the remodeling of the cytomatrix and synaptic connections and the inhibition of blood vessel proliferation (PCDH8, LAMB1, ITGB6, CTGF and EphB4). The observed microarray phenotype in the human hippocampus identified RECK and other region-specific genes that may promote long-lasting structural changes with repeated cocaine abuse. Extracellular matrix remodeling in the hippocampus may be a persisting effect of chronic abuse that contributes to the compulsive and relapsing nature of cocaine addiction. PMID:18000554

  19. Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

    PubMed

    Davis, Allan Peter; Wiegers, Thomas C; King, Benjamin L; Wiegers, Jolene; Grondin, Cynthia J; Sciaky, Daniela; Johnson, Robin J; Mattingly, Carolyn J

    2016-01-01

    Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO) file from NCBI Gene. By integrating these GO-gene annotations with CTD's gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil) and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis) as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and pharmaceutical drug makers in finding commonalities in disease mechanisms, which in turn could help identify new therapeutics, new indications for existing pharmaceuticals, potential disease comorbidities, and alerts for side effects. PMID:27171405

  20. Integrated Genomics Identifies Convergence of Ankylosing Spondylitis with Global Immune Mediated Disease Pathways

    PubMed Central

    Uddin, Mohammed; Codner, Dianne; Mahmud Hasan, S M; Scherer, Stephen W; O’Rielly, Darren D; Rahman, Proton

    2015-01-01

    Ankylosing spondylitis(AS), a highly heritable complex inflammatory arthritis. Although, a handful of non-HLA risk loci have been identified, capturing the unexplained genetic contribution to AS pathogenesis remains a challenge attributed to additive, pleiotropic and epistatic-interactions at the molecular level. Here, we developed multiple integrated genomic approaches to quantify molecular convergence of non-HLA loci with global immune mediated diseases. We show that non-HLA genes are significantly sensitive to deleterious mutation accumulation in the general population compared with tolerant genes. Human developmental proteomics (prenatal to adult) analysis revealed that proteins encoded by non-HLA AS risk loci are 2-fold more expressed in adult hematopoietic cells.Enrichment analysis revealed AS risk genes overlap with a significant number of immune related pathways (p < 0.0001 to 9.8 × 10-12). Protein-protein interaction analysis revealed non-shared AS risk genes are highly clustered seeds that significantly converge (empirical; p < 0.01 to 1.6 × 10-4) into networks of global immune mediated disease risk loci. We have also provided initial evidence for the involvement of STAT2/3 in AS pathogenesis. Collectively, these findings highlight molecular insight on non-HLA AS risk loci that are not exclusively connected with overlapping immune mediated diseases; rather a component of common pathophysiological pathways with other immune mediated diseases. This information will be pivotal to fully explain AS pathogenesis and identify new therapeutic targets. PMID:25980808

  1. Comparative and Functional Genomics in Identifying Aflatoxin Biosynthetic Genes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Identification of genes involved in aflatoxin biosynthesis through Aspergillus flavus genomics has been actively pursued. A. flavus Expressed Sequence Tags (EST’s) and whole genome sequencing have been completed. Groups of genes that are potentially involved in aflatoxin production have been profi...

  2. Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases.

    PubMed

    Arakelyan, Arsen; Nersisyan, Lilit; Petrek, Martin; Löffler-Wirth, Henry; Binder, Hans

    2016-01-01

    Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases at molecular level, no systematic approach has been developed so far. Here we have applied a methodology for pathway-centered mining of high throughput gene expression data to describe a wide range of lung diseases in the light of shared and specific pathway activity profiles. We have applied an algorithm combining a Pathway Signal Flow (PSF) algorithm for estimation of pathway activity deregulation states in lung diseases and malignancies, and a Self Organizing Maps algorithm for classification and clustering of the pathway activity profiles. The analysis results allowed clearly distinguish between cancer and non-cancer lung diseases. Lung cancers were characterized by pathways implicated in cell proliferation, metabolism, while non-malignant lung diseases were characterized by deregulations in pathways involved in immune/inflammatory response and fibrotic tissue remodeling. In contrast to lung malignancies, chronic lung diseases had relatively heterogeneous pathway deregulation profiles. We identified three groups of interstitial lung diseases and showed that the development of characteristic pathological processes, such as fibrosis, can be initiated by deregulations in different signaling pathways. In conclusion, this paper describes the pathobiology of lung diseases from systems viewpoint using pathway centered high-dimensional data mining approach. Our results contribute largely to current understanding of pathological events in lung cancers and non-malignant lung diseases. Moreover, this paper provides new insight into molecular mechanisms of a number of interstitial lung diseases that have been studied to a lesser extent. PMID:27200087

  3. Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases

    PubMed Central

    Arakelyan, Arsen; Nersisyan, Lilit; Petrek, Martin; Löffler-Wirth, Henry; Binder, Hans

    2016-01-01

    Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases at molecular level, no systematic approach has been developed so far. Here we have applied a methodology for pathway-centered mining of high throughput gene expression data to describe a wide range of lung diseases in the light of shared and specific pathway activity profiles. We have applied an algorithm combining a Pathway Signal Flow (PSF) algorithm for estimation of pathway activity deregulation states in lung diseases and malignancies, and a Self Organizing Maps algorithm for classification and clustering of the pathway activity profiles. The analysis results allowed clearly distinguish between cancer and non-cancer lung diseases. Lung cancers were characterized by pathways implicated in cell proliferation, metabolism, while non-malignant lung diseases were characterized by deregulations in pathways involved in immune/inflammatory response and fibrotic tissue remodeling. In contrast to lung malignancies, chronic lung diseases had relatively heterogeneous pathway deregulation profiles. We identified three groups of interstitial lung diseases and showed that the development of characteristic pathological processes, such as fibrosis, can be initiated by deregulations in different signaling pathways. In conclusion, this paper describes the pathobiology of lung diseases from systems viewpoint using pathway centered high-dimensional data mining approach. Our results contribute largely to current understanding of pathological events in lung cancers and non-malignant lung diseases. Moreover, this paper provides new insight into molecular mechanisms of a number of interstitial lung diseases that have been studied to a lesser extent. PMID:27200087

  4. Genetic Susceptibility to Vitiligo: GWAS Approaches for Identifying Vitiligo Susceptibility Genes and Loci

    PubMed Central

    Shen, Changbing; Gao, Jing; Sheng, Yujun; Dou, Jinfa; Zhou, Fusheng; Zheng, Xiaodong; Ko, Randy; Tang, Xianfa; Zhu, Caihong; Yin, Xianyong; Sun, Liangdan; Cui, Yong; Zhang, Xuejun

    2016-01-01

    Vitiligo is an autoimmune disease with a strong genetic component, characterized by areas of depigmented skin resulting from loss of epidermal melanocytes. Genetic factors are known to play key roles in vitiligo through discoveries in association studies and family studies. Previously, vitiligo susceptibility genes were mainly revealed through linkage analysis and candidate gene studies. Recently, our understanding of the genetic basis of vitiligo has been rapidly advancing through genome-wide association study (GWAS). More than 40 robust susceptible loci have been identified and confirmed to be associated with vitiligo by using GWAS. Most of these associated genes participate in important pathways involved in the pathogenesis of vitiligo. Many susceptible loci with unknown functions in the pathogenesis of vitiligo have also been identified, indicating that additional molecular mechanisms may contribute to the risk of developing vitiligo. In this review, we summarize the key loci that are of genome-wide significance, which have been shown to influence vitiligo risk. These genetic loci may help build the foundation for genetic diagnosis and personalize treatment for patients with vitiligo in the future. However, substantial additional studies, including gene-targeted and functional studies, are required to confirm the causality of the genetic variants and their biological relevance in the development of vitiligo. PMID:26870082

  5. Genetic Susceptibility to Vitiligo: GWAS Approaches for Identifying Vitiligo Susceptibility Genes and Loci.

    PubMed

    Shen, Changbing; Gao, Jing; Sheng, Yujun; Dou, Jinfa; Zhou, Fusheng; Zheng, Xiaodong; Ko, Randy; Tang, Xianfa; Zhu, Caihong; Yin, Xianyong; Sun, Liangdan; Cui, Yong; Zhang, Xuejun

    2016-01-01

    Vitiligo is an autoimmune disease with a strong genetic component, characterized by areas of depigmented skin resulting from loss of epidermal melanocytes. Genetic factors are known to play key roles in vitiligo through discoveries in association studies and family studies. Previously, vitiligo susceptibility genes were mainly revealed through linkage analysis and candidate gene studies. Recently, our understanding of the genetic basis of vitiligo has been rapidly advancing through genome-wide association study (GWAS). More than 40 robust susceptible loci have been identified and confirmed to be associated with vitiligo by using GWAS. Most of these associated genes participate in important pathways involved in the pathogenesis of vitiligo. Many susceptible loci with unknown functions in the pathogenesis of vitiligo have also been identified, indicating that additional molecular mechanisms may contribute to the risk of developing vitiligo. In this review, we summarize the key loci that are of genome-wide significance, which have been shown to influence vitiligo risk. These genetic loci may help build the foundation for genetic diagnosis and personalize treatment for patients with vitiligo in the future. However, substantial additional studies, including gene-targeted and functional studies, are required to confirm the causality of the genetic variants and their biological relevance in the development of vitiligo. PMID:26870082

  6. Mutation skew in genes identified by genome-wide association study of hypertriglyceridemia

    PubMed Central

    Johansen, Christopher T.; Wang, Jian; Lanktree, Matthew B.; Cao, Henian; McIntyre, Adam D.; Ban, Matthew R.; Martins, Rebecca A.; Kennedy, Brooke A.; Hassell, Reina G.; Visser, Maartje E.; Schwartz, Stephen M.; Voight, Benjamin F.; Elosua, Roberto; Salomaa, Veikko; O'Donnell, Christopher J.; Dallinga-Thie, Geesje M.; Anand, Sonia S.; Yusuf, Salim; Huff, Murray W.; Kathiresan, Sekar; Hegele, Robert A.

    2010-01-01

    Genome-wide association studies (GWAS) have replicably identified multiple loci associated with population-based plasma lipid concentrations1-5. Common genetic variants at these loci together explain <10% of the total variation of each lipid trait4,5. Rare variants of individually large effect may contribute additionally to the missing heritability of lipid traits6,7, however it remains to be shown to what extent rare variants will affect lipid phenotypes. Here, we demonstrate a significant accumulation of rare variants in GWAS-identified genes in patients with an extreme phenotype of abnormal plasma triglyceride (TG) metabolism. A GWAS of hypertriglyceridemia (HTG) patients revealed that common variants in APOA5, GCKR, LPL and APOB genes were associated with the HTG phenotype at genome-wide significance. We subsequently resequenced protein coding regions of these genes and found a significant burden of 154 rare missense or nonsense variants in 438 HTG patients, in contrast to 53 variants in 327 controls (P=6.2X10-8); this corresponds to a carrier frequency of 28.1% of HTG patients and 15.3% of controls (P=2.6X10-5). Many rare variants were predicted in silico to have compromised function; additionally some had previously demonstrated dysfunctionality in vitro. Rare variants in these 4 genes explained 1.1% of total variation in HTG diagnoses. Our study demonstrates a marked mutation skew that likely contributes to disease pathophysiology in patients with HTG. PMID:20657596

  7. Elevating crop disease resistance with cloned genes

    PubMed Central

    Jones, Jonathan D. G.; Witek, Kamil; Verweij, Walter; Jupe, Florian; Cooke, David; Dorling, Stephen; Tomlinson, Laurence; Smoker, Matthew; Perkins, Sara; Foster, Simon

    2014-01-01

    Essentially all plant species exhibit heritable genetic variation for resistance to a variety of plant diseases caused by fungi, bacteria, oomycetes or viruses. Disease losses in crop monocultures are already significant, and would be greater but for applications of disease-controlling agrichemicals. For sustainable intensification of crop production, we argue that disease control should as far as possible be achieved using genetics rather than using costly recurrent chemical sprays. The latter imply CO2 emissions from diesel fuel and potential soil compaction from tractor journeys. Great progress has been made in the past 25 years in our understanding of the molecular basis of plant disease resistance mechanisms, and of how pathogens circumvent them. These insights can inform more sophisticated approaches to elevating disease resistance in crops that help us tip the evolutionary balance in favour of the crop and away from the pathogen. We illustrate this theme with an account of a genetically modified (GM) blight-resistant potato trial in Norwich, using the Rpi-vnt1.1 gene isolated from a wild relative of potato, Solanum venturii, and introduced by GM methods into the potato variety Desiree. PMID:24535396

  8. Elevating crop disease resistance with cloned genes.

    PubMed

    Jones, Jonathan D G; Witek, Kamil; Verweij, Walter; Jupe, Florian; Cooke, David; Dorling, Stephen; Tomlinson, Laurence; Smoker, Matthew; Perkins, Sara; Foster, Simon

    2014-04-01

    Essentially all plant species exhibit heritable genetic variation for resistance to a variety of plant diseases caused by fungi, bacteria, oomycetes or viruses. Disease losses in crop monocultures are already significant, and would be greater but for applications of disease-controlling agrichemicals. For sustainable intensification of crop production, we argue that disease control should as far as possible be achieved using genetics rather than using costly recurrent chemical sprays. The latter imply CO₂ emissions from diesel fuel and potential soil compaction from tractor journeys. Great progress has been made in the past 25 years in our understanding of the molecular basis of plant disease resistance mechanisms, and of how pathogens circumvent them. These insights can inform more sophisticated approaches to elevating disease resistance in crops that help us tip the evolutionary balance in favour of the crop and away from the pathogen. We illustrate this theme with an account of a genetically modified (GM) blight-resistant potato trial in Norwich, using the Rpi-vnt1.1 gene isolated from a wild relative of potato, Solanum venturii, and introduced by GM methods into the potato variety Desiree. PMID:24535396

  9. Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease.

    PubMed

    Trynka, Gosia; Hunt, Karen A; Bockett, Nicholas A; Romanos, Jihane; Mistry, Vanisha; Szperl, Agata; Bakker, Sjoerd F; Bardella, Maria Teresa; Bhaw-Rosun, Leena; Castillejo, Gemma; de la Concha, Emilio G; de Almeida, Rodrigo Coutinho; Dias, Kerith-Rae M; van Diemen, Cleo C; Dubois, Patrick C A; Duerr, Richard H; Edkins, Sarah; Franke, Lude; Fransen, Karin; Gutierrez, Javier; Heap, Graham A R; Hrdlickova, Barbara; Hunt, Sarah; Plaza Izurieta, Leticia; Izzo, Valentina; Joosten, Leo A B; Langford, Cordelia; Mazzilli, Maria Cristina; Mein, Charles A; Midah, Vandana; Mitrovic, Mitja; Mora, Barbara; Morelli, Marinita; Nutland, Sarah; Núñez, Concepción; Onengut-Gumuscu, Suna; Pearce, Kerra; Platteel, Mathieu; Polanco, Isabel; Potter, Simon; Ribes-Koninckx, Carmen; Ricaño-Ponce, Isis; Rich, Stephen S; Rybak, Anna; Santiago, José Luis; Senapati, Sabyasachi; Sood, Ajit; Szajewska, Hania; Troncone, Riccardo; Varadé, Jezabel; Wallace, Chris; Wolters, Victorien M; Zhernakova, Alexandra; Thelma, B K; Cukrowska, Bozena; Urcelay, Elena; Bilbao, Jose Ramon; Mearin, M Luisa; Barisani, Donatella; Barrett, Jeffrey C; Plagnol, Vincent; Deloukas, Panos; Wijmenga, Cisca; van Heel, David A

    2011-12-01

    Using variants from the 1000 Genomes Project pilot European CEU dataset and data from additional resequencing studies, we densely genotyped 183 non-HLA risk loci previously associated with immune-mediated diseases in 12,041 individuals with celiac disease (cases) and 12,228 controls. We identified 13 new celiac disease risk loci reaching genome-wide significance, bringing the number of known loci (including the HLA locus) to 40. We found multiple independent association signals at over one-third of these loci, a finding that is attributable to a combination of common, low-frequency and rare genetic variants. Compared to previously available data such as those from HapMap3, our dense genotyping in a large sample collection provided a higher resolution of the pattern of linkage disequilibrium and suggested localization of many signals to finer scale regions. In particular, 29 of the 54 fine-mapped signals seemed to be localized to single genes and, in some instances, to gene regulatory elements. Altogether, we define the complex genetic architecture of the risk regions of and refine the risk signals for celiac disease, providing the next step toward uncovering the causal mechanisms of the disease. PMID:22057235

  10. Development and Utilization of InDel Markers to Identify Peanut (Arachis hypogaea) Disease Resistance.

    PubMed

    Liu, Lifeng; Dang, Phat M; Chen, Charles Y

    2015-01-01

    Peanut diseases, such as leaf spot and spotted wilt caused by Tomato Spotted Wilt Virus, can significantly reduce yield and quality. Application of marker assisted plant breeding requires the development and validation of different types of DNA molecular markers. Nearly 10,000 SSR-based molecular markers have been identified by various research groups around the world, but less than 14.5% showed polymorphism in peanut and only 6.4% have been mapped. Low levels of polymorphism limit the application of marker assisted selection (MAS) in peanut breeding programs. Insertion/deletion (InDel) markers have been reported to be more polymorphic than SSRs in some crops. The goals of this study were to identify novel InDel markers and to evaluate the potential use in peanut breeding. Forty-eight InDel markers were developed from conserved sequences of functional genes and tested in a diverse panel of 118 accessions covering six botanical types of cultivated peanut, of which 104 were from the U.S. mini-core. Results showed that 16 InDel markers were polymorphic with polymorphic information content (PIC) among InDels ranged from 0.017 to 0.660. With respect to botanical types, PICs varied from 0.176 for fastigiata var., 0.181 for hypogaea var., 0.306 for vulgaris var., 0.534 for aequatoriana var., 0.556 for peruviana var., to 0.660 for hirsuta var., implying that aequatoriana var., peruviana var., and hirsuta var. have higher genetic diversity than the other types and provide a basis for gene functional studies. Single marker analysis was conducted to associate specific marker to disease resistant traits. Five InDels from functional genes were identified to be significantly correlated to tomato spotted wilt virus (TSWV) infection and leaf spot, and these novel markers will be utilized to identify disease resistant genotype in breeding populations. PMID:26617627

  11. Development and Utilization of InDel Markers to Identify Peanut (Arachis hypogaea) Disease Resistance

    PubMed Central

    Liu, Lifeng; Dang, Phat M.; Chen, Charles Y.

    2015-01-01

    Peanut diseases, such as leaf spot and spotted wilt caused by Tomato Spotted Wilt Virus, can significantly reduce yield and quality. Application of marker assisted plant breeding requires the development and validation of different types of DNA molecular markers. Nearly 10,000 SSR-based molecular markers have been identified by various research groups around the world, but less than 14.5% showed polymorphism in peanut and only 6.4% have been mapped. Low levels of polymorphism limit the application of marker assisted selection (MAS) in peanut breeding programs. Insertion/deletion (InDel) markers have been reported to be more polymorphic than SSRs in some crops. The goals of this study were to identify novel InDel markers and to evaluate the potential use in peanut breeding. Forty-eight InDel markers were developed from conserved sequences of functional genes and tested in a diverse panel of 118 accessions covering six botanical types of cultivated peanut, of which 104 were from the U.S. mini-core. Results showed that 16 InDel markers were polymorphic with polymorphic information content (PIC) among InDels ranged from 0.017 to 0.660. With respect to botanical types, PICs varied from 0.176 for fastigiata var., 0.181 for hypogaea var., 0.306 for vulgaris var., 0.534 for aequatoriana var., 0.556 for peruviana var., to 0.660 for hirsuta var., implying that aequatoriana var., peruviana var., and hirsuta var. have higher genetic diversity than the other types and provide a basis for gene functional studies. Single marker analysis was conducted to associate specific marker to disease resistant traits. Five InDels from functional genes were identified to be significantly correlated to tomato spotted wilt virus (TSWV) infection and leaf spot, and these novel markers will be utilized to identify disease resistant genotype in breeding populations. PMID:26617627

  12. Antioxidant Enzyme Gene Transfer for Ischemic Diseases

    PubMed Central

    Wu, Jian; Hecker, James G.; Chiamvimonvat, Nipavan

    2009-01-01

    The balance of redox is pivotal for normal function and integrity of tissues. Ischemic insults occur as results of a variety of conditions, leading to an accumulation of reactive oxygen species (ROS) and an imbalanced redox status in the tissues. The oxidant stress may activate signaling mechanisms provoking more toxic events, and eventually cause tissue damage. Therefore, treatments with antioxidants, free radical scavengers and their mimetics, as well as gene transfer approaches to overexpress antioxidant genes represent potential therapeutic options to correct the redox imbalance. Among them, antioxidant gene transfer may enhance the production of antioxidant scavengers, and has been employed to experimentally prevent or treat ischemic injury in cardiovascular, pulmonary, hepatic, intestinal, central nervous or other systems in animal models. With improvements in vector systems and delivery approaches, innovative antioxidant gene therapy has conferred better outcomes for myocardial infarction, reduced restenosis after coronary angioplasty, improved the quality and function of liver grafts, as well as outcome of intestinal and cerebral ischemic attacks. However, it is crucial to be mindful that like other therapeutic armentarium, the efficacy of antioxidant gene transfer requires extensive preclinical investigation before it can be used in patients, and that it may have unanticipated short- or long-term adverse effects. Thus, it is critical to balance between the therapeutic benefits and potential risks, to develop disease-specific antioxidant gene transfer strategies, to deliver the therapy with an optimal time window and in a safe manner. This review attempts to provide the rationale, the most effective approaches and the potential hurdles of available antioxidant gene transfer approaches for ischemic injury in various organs, as well as the possible directions of future preclinical and clinical investigations of this highly promising therapeutic modality. PMID:19233238

  13. BEYOND COMPARING MEANS: THE USEFULNESS OF ANALYZING INTERINDIVIDUAL VARIATION IN GENE EXPRESSION FOR IDENTIFYING GENES ASSOCIATED WITH CANCER DEVELOPMENT

    PubMed Central

    GORLOV, IVAN P.; BYUN, JINYOUNG; ZHAO, HONGYA; LOGOTHETIS, CHRISTOPHER J.; GORLOVA, OLGA Y.

    2013-01-01

    Identifying genes associated with cancer development is typically accomplished by comparing mean expression values in normal and tumor tissues, which identifies differentially expressed (DE) genes. Interindividual variation (IV) in gene expression is indirectly included in DE gene identification because given the same absolute differences in means, genes with lower variance tend to have lower P values. We explored the direct use of IV in gene expression to identify candidate genes associated with cancer development. We focused on prostate (PCa) and lung (LC) cancers and compared IV in the expression level of genes shown to be cancer related with that in all other genes in the human genome. Compared with all those other genes, cancer-related genes tended to have greater IV in normal tissues and a greater increase in IV during the transition from normal to tumorous tissue. Genes without significantly different mean expression values between tumor and normal tissues but with greater IV in tumor than in normal tissue (note: the DE-based approach completely ignores those genes) had stronger associations with clinically important features like Gleason score in PCa or tumor histology in LC than all other genes were. Our results suggest that analyzing IV in gene expression level is useful in identifying novel candidate genes associated with cancer development. PMID:22809348

  14. Inflammatory bowel disease gene discovery. CRADA final report

    SciTech Connect

    1997-09-09

    The ultimate goal of this project is to identify the human gene(s) responsible for the disorder known as IBD. The work was planned in two phases. The desired products resulting from Phase 1 were BAC clone(s) containing the genetic marker(s) identified by gene/Networks, Inc. as potentially linked to IBD, plasmid subclones of those BAC(s), and new genetic markers developed from these plasmid subclones. The newly developed markers would be genotyped by gene/Networks, Inc. to ascertain evidence for linkage or non-linkage of IBD to this region. If non-linkage was indicated, the project would move to investigation of other candidate chromosomal regions. Where linkage was indicated, the project would move to Phase 2, in which a physical map of the candidate region(s) would be developed. The products of this phase would be contig(s) of BAC clones in the region exhibiting linkage to IBD, as well as plasmic subclones of the BACs and further genetic marker development. There would also be continued genotyping with new polymorphic markers during this phase. It was anticipated that clones identified and developed during these two phases would provide the physical resources for eventual disease gene discovery.

  15. Methods to identify and analyze gene products involved in neuronal intracellular transport using Drosophila.

    PubMed

    Neisch, Amanda L; Avery, Adam W; Machamer, James B; Li, Min-Gang; Hays, Thomas S

    2016-01-01

    Proper neuronal function critically depends on efficient intracellular transport and disruption of transport leads to neurodegeneration. Molecular pathways that support or regulate neuronal transport are not fully understood. A greater understanding of these pathways will help reveal the pathological mechanisms underlying disease. Drosophila melanogaster is the premier model system for performing large-scale genetic functional screens. Here we describe methods to carry out primary and secondary genetic screens in Drosophila aimed at identifying novel gene products and pathways that impact neuronal intracellular transport. These screens are performed using whole animal or live cell imaging of intact neural tissue to ensure integrity of neurons and their cellular environment. The primary screen is used to identify gross defects in neuronal function indicative of a disruption in microtubule-based transport. The secondary screens, conducted in both motoneurons and dendritic arborization neurons, will confirm the function of candidate gene products in intracellular transport. Together, the methodologies described here will support labs interested in identifying and characterizing gene products that alter intracellular transport in Drosophila. PMID:26794520

  16. Identifying autism loci and genes by tracing recent shared ancestry.

    PubMed

    Morrow, Eric M; Yoo, Seung-Yun; Flavell, Steven W; Kim, Tae-Kyung; Lin, Yingxi; Hill, Robert Sean; Mukaddes, Nahit M; Balkhy, Soher; Gascon, Generoso; Hashmi, Asif; Al-Saad, Samira; Ware, Janice; Joseph, Robert M; Greenblatt, Rachel; Gleason, Danielle; Ertelt, Julia A; Apse, Kira A; Bodell, Adria; Partlow, Jennifer N; Barry, Brenda; Yao, Hui; Markianos, Kyriacos; Ferland, Russell J; Greenberg, Michael E; Walsh, Christopher A

    2008-07-11

    To find inherited causes of autism-spectrum disorders, we studied families in which parents share ancestors, enhancing the role of inherited factors. We mapped several loci, some containing large, inherited, homozygous deletions that are likely mutations. The largest deletions implicated genes, including PCDH10 (protocadherin 10) and DIA1 (deleted in autism1, or c3orf58), whose level of expression changes in response to neuronal activity, a marker of genes involved in synaptic changes that underlie learning. A subset of genes, including NHE9 (Na+/H+ exchanger 9), showed additional potential mutations in patients with unrelated parents. Our findings highlight the utility of "homozygosity mapping" in heterogeneous disorders like autism but also suggest that defective regulation of gene expression after neural activity may be a mechanism common to seemingly diverse autism mutations. PMID:18621663

  17. Identifying Autism Loci and Genes by Tracing Recent Shared Ancestry

    PubMed Central

    Morrow, Eric M.; Yoo, Seung-Yun; Flavell, Steven W.; Kim, Tae-Kyung; Lin, Yingxi; Hill, Robert Sean; Mukaddes, Nahit M.; Balkhy, Soher; Gascon, Generoso; Hashmi, Asif; Al-Saad, Samira; Ware, Janice; Joseph, Robert M.; Greenblatt, Rachel; Gleason, Danielle; Ertelt, Julia A.; Apse, Kira A.; Bodell, Adria; Partlow, Jennifer N.; Barry, Brenda; Yao, Hui; Markianos, Kyriacos; Ferland, Russell J.; Greenberg, Michael E.; Walsh, Christopher A.

    2008-01-01

    To find inherited causes of autism-spectrum disorders, we studied families in which parents share ancestors, enhancing the role of inherited factors. We mapped several loci, some containing large, inherited, homozygous deletions that are likely mutations. The largest deletions implicated genes, including PCDH10 (protocadherin 10) and DIA1 (deleted in autism1, or c3orf58), whose level of expression changes in response to neuronal activity, a marker of genes involved in synaptic changes that underlie learning. A subset of genes, including NHE9 (Na+/H+ exchanger 9), showed additional potential mutations in patients with unrelated parents. Our findings highlight the utility of “homozygosity mapping” in heterogeneous disorders like autism but also suggest that defective regulation of gene expression after neural activity may be a mechanism common to seemingly diverse autism mutations. PMID:18621663

  18. Genome-Wide Expression Profiles Identify Potential Targets for Gene by Environment Interactions in Asthma Severity

    PubMed Central

    Sordillo, Joanne E; Kelly, Roxanne; Bunyavanich, Supinda; McGeachie, Michael; Qiu, Weiliang; Croteau-Chonka, Damien C.; Soto-Quiros, Manuel; Avila, Lydiana; Celedón, Juan C.; Brehm, John M.; Weiss, Scott T; Gold, Diane R; Litonjua, Augusto A

    2015-01-01

    Background Gene by environment interaction (G × E) studies utilizing GWAS data are often underpowered after adjustment for multiple comparisons. Differential gene expression, in response to the exposure of interest, may capture the most biologically relevant genes at the genome-wide level. Methods We used differential genome-wide expression profiles from the Home Allergens and Asthma Birth cohort in response to Der f 1 allergen (sensitized vs. non-sensitized) to inform a G × E study of dust mite exposure and asthma severity. Polymorphisms in differentially expressed genes were identified in GWAS data from CAMP, a clinical trial in childhood asthmatics. Home dust mite allergen (< or ≥ 10µg/g dust) was assessed at baseline, and (≥ 1) severe asthma exacerbation (emergency room (ER) visit or hospitalization for asthma in the first trial year) served as the disease severity outcome. The Genetics of Asthma in Costa Rica (GACRS) study, and a Puerto Rico/Connecticut asthma cohortwere used for replication. Results IL-9, IL-5 and PRG2 expression was up-regulated in Der f 1 stimulated PBMCs from dust mite sensitized individuals (adj. p value <0.04). IL-9 polymorphisms (rs11741137, rs2069885, rs1859430) showed evidence for interaction with dust mite in CAMP (p=0.02 to 0.03), with replication in GACRS (p=0.04). Subjects with the dominant genotype for these IL-9 polymorphisms were more likely to report a severe asthma exacerbation if exposed to elevated dust mite. Conclusions Genome-wide differential gene expression in response to dust mite allergen identified IL-9, a biologically plausible gene target that may interact with environmental dust mite to increase severe asthma exacerbations in children. PMID:25913104

  19. Mutational analysis of PKD1 gene in a Chinese family with autosomal dominant polycystic kidney disease

    PubMed Central

    Liu, Jingyan; Li, Lanrong; Liu, Qingmin

    2015-01-01

    Autosomal dominant polycystic kidney disease (ADPKD) is a hereditary disease and common renal disease. Mutations of PKD genes are responsible for this disease. We analyzed a large Chinese family with ADPKD using Sanger sequencing to identify the mutation responsible for this disease. The family comprised 27 individuals including 10 ADPKD patients. These ADPKD patients had severe renal disease and most of them died very young. We analyzed 6 survival patients gene and found they all had C10529T mutation in exon 35 of PKD1 gene. We did not found gene mutation in any unaffected relatives or 300 unrelated controls. These findings suggested that the C10529T mutation in PKD1 gene might be the pathogenic mutation responsible for the disease in this family. PMID:26722532

  20. Identifying novel resistance genes in rice wild relatives

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rice blast and sheath blight are major fungal diseases of cultivated rice (Oryza sativa L. ) that limit Arkansas rough rice yields and market potential. Resistance to these diseases has been found in rice wild relatives (Oryza spp.) A collection of these wild relatives originating from outside the U...

  1. Knowledge-based compact disease models identify new molecular players contributing to early-stage Alzheimers disease

    PubMed Central

    2013-01-01

    Background High-throughput profiling of human tissues typically yield as results the gene lists comprised of a mix of relevant molecular entities with multiple false positives that obstruct the translation of such results into mechanistic hypotheses. From general probabilistic considerations, gene lists distilled for the mechanistically relevant components can be far more useful for subsequent experimental design or data interpretation. Results The input candidate gene lists were processed into different tiers of evidence consistency established by enrichment analysis across subsets of the same experiments and across different experiments and platforms. The cut-offs were established empirically through ontological and semantic enrichment; resultant shortened gene list was re-expanded by Ingenuity Pathway Assistant tool. The resulting sub-networks provided the basis for generating mechanistic hypotheses that were partially validated by literature search. This approach differs from previous consistency-based studies in that the cut-off on the Receiver Operating Characteristic of the true-false separation process is optimized by flexible selection of the consistency building procedure. The gene list distilled by this analytic technique and its network representation were termed Compact Disease Model (CDM). Here we present the CDM signature for the study of early-stage Alzheimers disease. The integrated analysis of this gene signature allowed us to identify the protein traffic vesicles as prominent players in the pathogenesis of Alzheimers. Considering the distances and complexity of protein trafficking in neurons, it is plausible that spontaneous protein misfolding along with a shortage of growth stimulation result in neurodegeneration. Several potentially overlapping scenarios of early-stage Alzheimer pathogenesis have been discussed, with an emphasis on the protective effects of AT-1 mediated antihypertensive response on cytoskeleton remodeling, along with neuronal activation of oncogenes, luteinizing hormone signaling and insulin-related growth regulation, forming a pleiotropic model of its early stages. Alignment with emerging literature confirmed many predictions derived from early-stage Alzheimers disease CDM. Conclusions A flexible approach for high-throughput data analysis, the Compact Disease Model generation, allows extraction of meaningful, mechanism-centered gene sets compatible with instant translation of the results into testable hypotheses. PMID:24196233

  2. Mapping Gene Associations in Human Mitochondria using Clinical Disease Phenotypes

    PubMed Central

    Scharfe, Curt; Lu, Henry Horng-Shing; Neuenburg, Jutta K.; Allen, Edward A.; Li, Guan-Cheng; Klopstock, Thomas; Cowan, Tina M.; Enns, Gregory M.; Davis, Ronald W.

    2009-01-01

    Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes. PMID:19390613

  3. Use of recombinase gene fusions to identify Vibrio cholerae genes induced during infection

    PubMed Central

    Camilli, Andrew; Mekalanos, John J.

    2016-01-01

    Summary A complete understanding of host-parasite interactions must necessarily include the identification and characterization of gene products expressed by both parties during the infectious process. We have developed a new screen to identify bacterial genes that are transcriptionally induced during infection of a host animal. The method is based on pre-selection of strains carrying tnpR operon fusions (encoding resolvase, a site-specific DNA recombinase) which are not expressed in vitro, followed by screening for a subset of these strains that subsequently express resolvase within the host environment. The latter subset was recognized as recombinants that had deleted a resolvase-specific reporter construct. Thirteen transcription units of Vibrio cholerae were identified that were induced during infection in an infant mouse model of cholera. Five of these were predicted to encode polypeptides with diverse functions in metabolism, biosynthesis and motility; one encoded a secreted lipase; two appear to be antisense to genes involved in motility; and five are predicted to encode polypeptides of unknown function. Three of the transcripts were shown to be required for full virulence in infant mice, as assessed by competition experiments. PMID:8817490

  4. Evaluation of an efficient approach for identifying genetic disease loci

    SciTech Connect

    Sheffield, V.C.; Kwitek-Black, A.E.; Rokhlina, T.

    1994-09-01

    Identification of disease loci by genetic linkage analysis has been enhanced by the availability of highly polymorphic short tandem repeat polymorphic markers (STRPs). The development of high quality tri- and tetranucleotide STRPs allows new strategies to increase the efficiency of genotyping resulting in streamlined linkage studies. We have tested a strategy using pooled DNA samples from affected individuals from large Bedouin pedigrees segregating recessive disorders. Equal molar amounts of DNA from affected individuals are pooled and used as a template for PCR of STRPs. Pooled DNA from unaffected siblings are used as controls. STRPS linked to the disorder show a shift in allele frequency in the affected compared to the control pool, whereas unlinked markers show an identical allele distribution in affected and control pools. We have demonstrated the sensitivity of this approach for identifying STRPs giving positive lod scores in recessive kindreds. We have also modelled this approach with dominant pedigrees. Application of this approach to polygenic disorders should be possible by using methods to quantitate allele frequencies in pooled samples. The high quality tri- and tetranucleotide repeat markers developed by the Cooperative Human Linkage Center (CHLC) facilitate the use of this method.

  5. Protein networks identify novel symbiogenetic genes resulting from plastid endosymbiosis.

    PubMed

    Méheust, Raphaël; Zelzion, Ehud; Bhattacharya, Debashish; Lopez, Philippe; Bapteste, Eric

    2016-03-29

    The integration of foreign genetic information is central to the evolution of eukaryotes, as has been demonstrated for the origin of the Calvin cycle and of the heme and carotenoid biosynthesis pathways in algae and plants. For photosynthetic lineages, this coordination involved three genomes of divergent phylogenetic origins (the nucleus, plastid, and mitochondrion). Major hurdles overcome by the ancestor of these lineages were harnessing the oxygen-evolving organelle, optimizing the use of light, and stabilizing the partnership between the plastid endosymbiont and host through retargeting of proteins to the nascent organelle. Here we used protein similarity networks that can disentangle reticulate gene histories to explore how these significant challenges were met. We discovered a previously hidden component of algal and plant nuclear genomes that originated from the plastid endosymbiont: symbiogenetic genes (S genes). These composite proteins, exclusive to photosynthetic eukaryotes, encode a cyanobacterium-derived domain fused to one of cyanobacterial or another prokaryotic origin and have emerged multiple, independent times during evolution. Transcriptome data demonstrate the existence and expression of S genes across a wide swath of algae and plants, and functional data indicate their involvement in tolerance to oxidative stress, phototropism, and adaptation to nitrogen limitation. Our research demonstrates the "recycling" of genetic information by photosynthetic eukaryotes to generate novel composite genes, many of which function in plastid maintenance. PMID:26976593

  6. Protein networks identify novel symbiogenetic genes resulting from plastid endosymbiosis

    PubMed Central

    Méheust, Raphaël; Zelzion, Ehud; Bhattacharya, Debashish; Lopez, Philippe; Bapteste, Eric

    2016-01-01

    The integration of foreign genetic information is central to the evolution of eukaryotes, as has been demonstrated for the origin of the Calvin cycle and of the heme and carotenoid biosynthesis pathways in algae and plants. For photosynthetic lineages, this coordination involved three genomes of divergent phylogenetic origins (the nucleus, plastid, and mitochondrion). Major hurdles overcome by the ancestor of these lineages were harnessing the oxygen-evolving organelle, optimizing the use of light, and stabilizing the partnership between the plastid endosymbiont and host through retargeting of proteins to the nascent organelle. Here we used protein similarity networks that can disentangle reticulate gene histories to explore how these significant challenges were met. We discovered a previously hidden component of algal and plant nuclear genomes that originated from the plastid endosymbiont: symbiogenetic genes (S genes). These composite proteins, exclusive to photosynthetic eukaryotes, encode a cyanobacterium-derived domain fused to one of cyanobacterial or another prokaryotic origin and have emerged multiple, independent times during evolution. Transcriptome data demonstrate the existence and expression of S genes across a wide swath of algae and plants, and functional data indicate their involvement in tolerance to oxidative stress, phototropism, and adaptation to nitrogen limitation. Our research demonstrates the “recycling” of genetic information by photosynthetic eukaryotes to generate novel composite genes, many of which function in plastid maintenance. PMID:26976593

  7. Microglial genes regulating neuroinflammation in the progression of Alzheimer's disease.

    PubMed

    Villegas-Llerena, Claudio; Phillips, Alexandra; Garcia-Reitboeck, Pablo; Hardy, John; Pocock, Jennifer M

    2016-02-01

    Neuroinflammation is a pathological hallmark of Alzheimer's disease (AD), and microglia, the brain's resident phagocyte, are pivotal for the immune response observed in AD. Microglia act as sentinel and protective cells, but may become inappropriately reactive in AD to drive neuropathology. Recent Genome Wide Association Studies (GWAS) have identified more than 20 gene variants associated with an increased risk of late-onset AD (LOAD), the most prevalent form of AD [1]. The findings strongly implicate genes related to the immune response (CR1, CD33, MS4A, CLU, ABCA7, EPHA1 and HLA-DRB5-HLA-DRB1), endocytosis (BIN1, PICALM, CD2AP, EPHA1 and SORL1) and lipid biology (CLU, ABCA7 and SORL1) [2-8], and many encode proteins which are highly expressed in microglia [1]. Furthermore, recent identification of a low frequency mutation in the gene encoding the triggering receptor expressed in myeloid cells 2 protein (TREM2) confers increased risk of AD in LOAD cohorts with an effect size similar to that for APOE, until recently the only identified genetic risk factor associated with LOAD [9,10(••)] (Figure 1). The present review summarises our current understanding of the probable roles of microglial genes in the regulation of neuroinflammatory processes in AD and their relation to other processes affecting the disease's progression. PMID:26517285

  8. Gene Expression Profiling Identifies Molecular Pathways Associated with Collagen VI Deficiency and Provides Novel Therapeutic Targets

    PubMed Central

    Paco, Sonia; Kalko, Susana G.; Jou, Cristina; Rodríguez, María A.; Corbera, Joan; Muntoni, Francesco; Feng, Lucy; Rivas, Eloy; Torner, Ferran; Gualandi, Francesca; Gomez-Foix, Anna M.; Ferrer, Anna; Ortez, Carlos; Nascimento, Andrés; Colomer, Jaume; Jimenez-Mallebrera, Cecilia

    2013-01-01

    Ullrich congenital muscular dystrophy (UCMD), caused by collagen VI deficiency, is a common congenital muscular dystrophy. At present, the role of collagen VI in muscle and the mechanism of disease are not fully understood. To address this we have applied microarrays to analyse the transcriptome of UCMD muscle and compare it to healthy muscle and other muscular dystrophies. We identified 389 genes which are differentially regulated in UCMD relative to controls. In addition, there were 718 genes differentially expressed between UCMD and dystrophin deficient muscle. In contrast, only 29 genes were altered relative to other congenital muscular dystrophies. Changes in gene expression were confirmed by real-time PCR. The set of regulated genes was analysed by Gene Ontology, KEGG pathways and Ingenuity Pathway analysis to reveal the molecular functions and gene networks associated with collagen VI defects. The most significantly regulated pathways were those involved in muscle regeneration, extracellular matrix remodelling and inflammation. We characterised the immune response in UCMD biopsies as being mainly mediated via M2 macrophages and the complement pathway indicating that anti-inflammatory treatment may be beneficial to UCMD as for other dystrophies. We studied the immunolocalisation of ECM components and found that biglycan, a collagen VI interacting proteoglycan, was reduced in the basal lamina of UCMD patients. We propose that biglycan reduction is secondary to collagen VI loss and that it may be contributing towards UCMD pathophysiology. Consequently, strategies aimed at over-expressing biglycan and restore the link between the muscle cell surface and the extracellular matrix should be considered. PMID:24223098

  9. CFTR gene mutations in isolated chronic obstructive pulmonary disease

    SciTech Connect

    Pignatti, P.F.; Bombien, C.; Marigo, C.

    1994-09-01

    In order to identify a possible hereditary predisposition to the development of chronic obstructive pulmonary disease (COPD), we have looked for the presence of cystic fibrosis transmembrane regulator (CFTR) gene DNA sequence modifications in 28 unrelated patients with no signs of cystic fibrosis. The known mutations in Italian CF patients, as well as the most frequent worldwide CF mutations, were investigated. In addition, a denaturing gradient gel electrophoresis analysis of about half of the coding sequence of the gene in 56 chromosomes from the patients and in 102 chromosomes from control individuals affected by other pulmonary diseases and from normal controls was performed. Nine different CFTR gene mutations and polymorphisms were found in seven patients, a highly significant increase over controls. Two of the patients were compound heterozygotes. Two frequent CF mutations were detected: deletion F508 and R117H; two rare CF mutations: R1066C and 3667ins4; and five CF sequence variants: R75Q (which was also described as a disease-causing mutation in male sterility cases due to the absence of the vasa deferentia), G576A, 2736 A{r_arrow}G, L997F, and 3271+18C{r_arrow}T. Seven (78%) of the mutations are localized in transmembrane domains. Six (86%) of the patients with defined mutations and polymorphisms had bronchiectasis. These results indicate that CFTR gene mutations and sequence alterations may be involved in the etiopathogenesis of some cases of COPD.

  10. Chromatin Signature Identifies Monoallelic Gene Expression Across Mammalian Cell Types

    PubMed Central

    Nag, Anwesha; Vigneau, Sébastien; Savova, Virginia; Zwemer, Lillian M.; Gimelbrant, Alexander A.

    2015-01-01

    Monoallelic expression of autosomal genes (MAE) is a widespread epigenetic phenomenon which is poorly understood, due in part to current limitations of genome-wide approaches for assessing it. Recently, we reported that a specific histone modification signature is strongly associated with MAE and demonstrated that it can serve as a proxy of MAE in human lymphoblastoid cells. Here, we use murine cells to establish that this chromatin signature is conserved between mouse and human and is associated with MAE in multiple cell types. Our analyses reveal extensive conservation in the identity of MAE genes between the two species. By analyzing MAE chromatin signature in a large number of cell and tissue types, we show that it remains consistent during terminal cell differentiation and is predominant among cell-type specific genes, suggesting a link between MAE and specification of cell identity. PMID:26092837

  11. Identifying genetic determinants of host resistance to Marek's disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek's disease (MD) is a contagious disease of poultry induced by an alpha-herpesvirus known as Marek's disease virus (MDV). MD has been controlled by vaccination since the 1970s but it remains a serious potential threat to the world poultry industry since: 1) commercial poultry populations at larg...

  12. Low variance RNAs identify Parkinson’s disease molecular signature in blood

    PubMed Central

    Chikina, Maria D.; Gerald, Christophe P.; Li, Xianting; Ge, Yongchao; Pincas, Hanna; Nair, Venugopalan D.; Wong, Aaron K.; Krishnan, Arjun; Troyanskaya, Olga G.; Raymond, Deborah; Saunders-Pullman, Rachel; Bressman, Susan B.; Yue, Zhenyu; Sealfon, Stuart C.

    2015-01-01

    Background The diagnosis of Parkinson’s disease (PD) is usually not established until advanced neurodegeneration leads to clinically detectable symptoms. Previous blood PD transcriptome studies show low concordance, possibly due to the use of microarray technology, which has high measurement variation. The Leucine-rich repeat kinase 2 (LRRK2) G2019S mutation predisposes to PD. Using preclinical and clinical studies, we sought to develop a novel statistically motivated transcriptomic-based approach to identify a molecular signature in the blood of Ashkenazi Jewish PD patients including LRRK2 mutation carriers. Methods Using a digital gene expression platform to quantify 175 mRNA markers with low coefficients of variation (CV), we first compared whole blood transcript levels in mouse models 1) over-expressing wild-type (WT) LRRK2, 2) overexpressing G2019S LRRK2, 3) lacking LRRK2 (knockout), 4) and in WT controls. We then studied an Ashkenazi Jewish cohort of 34 symptomatic PD patients (both WT LRRK2 and G2019S LRRK2) and 32 asymptomatic controls. Results The expression profiles distinguished the 4 mouse groups with different genetic background. In patients, we detected significant differences in blood transcript levels both between individuals differing in LRRK2 genotype and between PD patients and controls. Discriminatory PD markers included genes associated with innate and adaptive immunity and inflammatory disease. Notably, gene expression patterns in L-DOPA-treated PD patients were significantly closer to those of healthy controls in a dose-dependent manner. Conclusions We identify whole blood mRNA signatures correlating with LRRK2 genotype and with PD disease state. This approach may provide insight into pathogenesis and a route to early disease detection. PMID:25786808

  13. Gene expression profiling in autoimmune non-infectious uveitis disease

    PubMed Central

    Li, Zhuqing; Liu, Baoying; Arvydas, Maminishkis; Mahesh, Sankaranarayana P.; Yeh, Steven; Lew, Julie; Lim, Wee Kiak; Sen, H. Nida; Clarke, Grace; Buggage, Ronald; Miller, Sheldon S.; Nussenblatt., Robert B.

    2008-01-01

    Non-infectious uveitis is a predominantly T cell mediated autoimmune, intraocular inflammatory disease. To characterize the gene expression profile from patients with non-infectious uveitis, peripheral blood mononuclear cells (PBMCs) were isolated from 50 patients with clinically characterized non-infectious uveitis syndrome. A pathway-specific cDNA microarray was used for gene expression profiling and real time PCR array for further confirmation. Sixty-seven inflammation and autoimmune associated genes were found differentially expressed in uveitis patients with twenty-eight of those genes being validated by real-time PCR. Several genes previously unknown for autoimmune uveitis, including IL-22, IL-19, IL-20 and IL-25/IL-17E, were found to be highly expressed among uveitis patients compared to the normal subjects with IL-22 expression highly variable among the patients. Furthermore, we show that IL-22 can affect primary human retinal pigment epithelial cells by decreasing total tissue resistance and inducing apoptosis possibly by decreasing phospho-Bad level. In addition, the microarray data identified a possible uveitis-associated gene expression pattern, showed distinct gene expression profiles in patients during periods of clinical activity and quiescence, and demonstrated similar expression patterns in related patients with similar clinical phenotypes. Our data provides the first evidence that a sub-set of IL-10 family genes are implicated in non-infectious uveitis and that IL-22 can affect human retinal pigment epithelial cells. The results may facilitate further understanding of the molecular mechanisms of autoimmune uveitis and other autoimmune originated inflammatory diseases. PMID:18802119

  14. Discovering New Genes in the Pathways of Common Sporadic Neurodegenerative Diseases: A Bioinformatics Approach.

    PubMed

    Kim, Yong Hwan; Beak, Seung Han; Charidimou, Andreas; Song, Min

    2016-01-13

    Late onset Alzheimer's disease (AD) and Parkinson's disease (PD) are mostly "sporadic" age-related neurodegenerative disorders, but with a clear genetic component. However, their genetic architecture is complex and heterogeneous, largely remaining a conundrum, with only a handful of well-established genetic risk factors consistently associated with these diseases. It is possible that numerous, yet undiscovered, AD and PD related genes might exist. We focused on the 'gene' as a mediator to find new potential genes that might have a relationship with both disorders using bio-literature mining techniques. Based on Entrez Gene, we extracted the genes and directional gene-gene relation in the entire MEDLINE records and then constructed a directional gene-gene network. We identified common genes associated with two different but related diseases by performing shortest path analysis on the network. With our approach, we were able to identify and map already known genes that have a direct relationship with PD and AD. In addition, we identified 7 genes previously unknown to be a bridge between these two disorders. We confirmed 4 genes, ROS1, FMN1, ATP8A2, and SNORD12C, by biomedical literature and further checked 3 genes, ERVK-10, PRS, and C7orf49, that might have a high possibility to be related with both diseases. Additional experiments were performed to demonstrate the effectiveness of our proposed method. Comparing to the co-occurrence approach, our approach detected 25% more candidate genes and verified 10% more genes that have the relationship between both diseases than the co-occurrence approach did. PMID:26836166

  15. Genes and non-mendelian diseases: dealing with complexity.

    PubMed

    Jordan, Bertrand

    2014-01-01

    The first decades of the new medical genetics (1980 to 2000) were marked by resounding successes, with the identification of the genes responsible (when defective) for muscular dystrophy, cystic fibrosis, or Huntington's disease, to name justa few of the several thousand Mendelian genetic conditions whose causes are now known. In contrast, the search for genes involved in common disorders such as diabetes,hypertension, schizophrenia, or autism failed miserably in the 1990s, with inconsistent and conflicting results--although the strong genetic component of these diseases (that also involve environmental factors) was (and still is) beyond doubt. From 2000 on,thanks to huge progress in genomic knowledge, technology, and analytical methods, it became possible to reliably identify genes influencing the risk of complex conditions,using the so-called GWAS (Genome-Wide Association Study) approach. Yet many problems remain, such as the vexing question of the "missing heritability," or the difficulty of translating these scientific results into genetic tests with real clinical validity and utility. Autism is one of the cases in which a strong genetic component has been demonstrated, but where the search for causative genes remains difficult and attempts at developing valid genetic tests have failed, because of the many genes involved and possibly of the heterogeneity of the condition. PMID:25345706

  16. Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease

    PubMed Central

    Trynka, Gosia; Hunt, Karen A; Bockett, Nicholas A; Romanos, Jihane; Mistry, Vanisha; Szperl, Agata; Bakker, Sjoerd F; Bardella, Maria Teresa; Bhaw-Rosun, Leena; Castillejo, Gemma; de la Concha, Emilio G.; de Almeida, Rodrigo Coutinho; Dias, Kerith-Rae M; van Diemen, Cleo C.; Dubois, Patrick CA; Duerr, Richard H.; Edkins, Sarah; Franke, Lude; Fransen, Karin; Gutierrez, Javier; Heap, Graham AR; Hrdlickova, Barbara; Hunt, Sarah; Izurieta, Leticia Plaza; Izzo, Valentina; Joosten, Leo AB; Langford, Cordelia; Mazzilli, Maria Cristina; Mein, Charles A; Midah, Vandana; Mitrovic, Mitja; Mora, Barbara; Morelli, Marinita; Nutland, Sarah; Núñez, Concepción; Onengut-Gumuscu, Suna; Pearce, Kerra; Platteel, Mathieu; Polanco, Isabel; Potter, Simon; Ribes-Koninckx, Carmen; Ricaño-Ponce, Isis; Rich, Stephen S.; Rybak, Anna; Santiago, José Luis; Senapati, Sabyasachi; Sood, Ajit; Szajewska, Hania; Troncone, Riccardo; Varadé, Jezabel; Wallace, Chris; Wolters, Victorien M; Zhernakova, Alexandra; Thelma, B.K.; Cukrowska, Bozena; Urcelay, Elena; Bilbao, Jose Ramon; Mearin, M Luisa; Barisani, Donatella; Barrett, Jeffrey C; Plagnol, Vincent; Deloukas, Panos; Wijmenga, Cisca; van Heel, David A

    2011-01-01

    We densely genotyped, using 1000 Genomes Project pilot CEU and additional re-sequencing study variants, 183 reported immune-mediated disease non-HLA risk loci in 12,041 celiac disease cases and 12,228 controls. We identified 13 new celiac disease risk loci at genome wide significance, bringing the total number of known loci (including HLA) to 40. Multiple independent association signals are found at over a third of these loci, attributable to a combination of common, low frequency, and rare genetic variants. In comparison with previously available data such as HapMap3, our dense genotyping in a large sample size provided increased resolution of the pattern of linkage disequilibrium, and suggested localization of many signals to finer scale regions. In particular, 29 of 54 fine-mapped signals appeared localized to specific single genes - and in some instances to gene regulatory elements. We define a complex genetic architecture of risk regions, and refine risk signals, providing a next step towards elucidating causal disease mechanisms. PMID:22057235

  17. Inherited neuropathies: from gene to disease.

    PubMed

    Keller, M P; Chance, P F

    1999-04-01

    Inherited disorders of peripheral nerves represent a common group of neurologic diseases. Charcot-Marie-Tooth neuropathy type 1 (CMT1) is a genetically heterogeneous group of chronic demyelinating polyneuropathies with loci mapping to chromosome 17 (CMT1A), chromosome 1 (CMT1B) and to another unknown autosome (CMT1C). CMT1A is most often associated with a tandem 1.5-megabase (Mb) duplication in chromosome 17p11.2-12, or in rare patients may result from a point mutation in the peripheral myelin protein-22 (PMP22) gene. CMT1B is associated with point mutations in the myelin protein zero (P0 or MPZ) gene. The molecular defect in CMT1C is unknown. X-linked Charcot-Marie-Tooth neuropathy (CMTX), which has clinical features similar to CMT1, is associated with mutations in the connexin32 gene. Charcot-Marie-Tooth neuropathy type 2 (CMT2) is an axonal neuropathy, also of undetermined cause. One form of CMT2 maps to chromosome 1p36 (CMT2A), another to chromosome 3p (CMT2B) and another to 7p (CMT2D). Dejerine-Sottas disease (DSD), also called hereditary motor and sensory neuropathy type III (HMSNIII), is a severe, infantile-onset demyelinating polyneuropathy syndrome that may be associated with point mutations in either the PMP22 gene or the P0 gene and shares considerable clinical and pathological features with CMT1. Hereditary neuropathy with liability to pressure palsies (HNPP) is an autosomal dominant disorder that results in a recurrent, episodic demyelinating neuropathy. HNPP is associated with a 1.5-Mb deletion in chromosome 17p11.2-12 and results from reduced expression of the PMP22 gene. CMT1A and HNPP are reciprocal duplication/deletion syndromes originating from unequal crossover during germ cell meiosis. Other rare forms of demyelinating peripheral neuropathies map to chromosome 8q, 10q and 11q. Hereditary neuralgic amyotrophy (familial brachial plexus neuropathy) is an autosomal dominant disorder causing painful, recurrent brachial plexopathies and maps to chromosome 17q25. PMID:10219749

  18. Integrated genomic approaches identify major pathways and upstream regulators in late onset Alzheimers disease

    PubMed Central

    Li, Xinzhong; Long, Jintao; He, Taigang; Belshaw, Robert; Scott, James

    2015-01-01

    Previous studies have evaluated gene expression in Alzheimers disease (AD) brains to identify mechanistic processes, but have been limited by the size of the datasets studied. Here we have implemented a novel meta-analysis approach to identify differentially expressed genes (DEGs) in published datasets comprising 450 late onset AD (LOAD) brains and 212 controls. We found 3124 DEGs, many of which were highly correlated with Braak stage and cerebral atrophy. Pathway Analysis revealed the most perturbed pathways to be (a) nitric oxide and reactive oxygen species in macrophages (NOROS), (b) NFkB and (c) mitochondrial dysfunction. NOROS was also up-regulated, and mitochondrial dysfunction down-regulated, in healthy ageing subjects. Upstream regulator analysis predicted the TLR4 ligands, STAT3 and NFKBIA, for activated pathways and RICTOR for mitochondrial genes. Protein-protein interaction network analysis emphasised the role of NFKB; identified a key interaction of CLU with complement; and linked TYROBP, TREM2 and DOK3 to modulation of LPS signalling through TLR4 and to phosphatidylinositol metabolism. We suggest that NEUROD6, ZCCHC17, PPEF1 and MANBAL are potentially implicated in LOAD, with predicted links to calcium signalling and protein mannosylation. Our study demonstrates a highly injurious combination of TLR4-mediated NFKB signalling, NOROS inflammatory pathway activation, and mitochondrial dysfunction in LOAD. PMID:26202100

  19. Kinome siRNA screen identifies novel cell-type specific dengue host target genes.

    PubMed

    Kwon, Yong-Jun; Heo, Jinyeong; Wong, Hazel E E; Cruz, Deu John M; Velumani, Sumathy; da Silva, Camila T; Mosimann, Ana Luiza P; Duarte Dos Santos, Claudia N; Freitas-Junior, Lucio H; Fink, Katja

    2014-10-01

    Dengue is a global emerging infectious disease, with no specific treatment available. To identify novel human host cell targets important for dengue virus infection and replication, an image-based high-throughput siRNA assay screening of a human kinome siRNA library was conducted using human hepatocyte cell line Huh7 infected with a recent dengue serotype 2 virus isolate BR DEN2 01-01. In the primary siRNA screening of 779 kinase-related genes, knockdown of 22 genes showed a reduction in DENV-2 infection. Conversely, knockdown of 8 genes enhanced viral infection. To assess host cell specificity, the confirmed hits were tested in the DENV-infected monocytic cell line U937. While the expression of EIF2AK3, ETNK2 and SMAD7 was regulated in both cell lines after infection, most kinases were hepatocyte-specific. Monocytic cells represent initial targets of infection and an antiviral treatment targeting these cells is probably most effective to reduce initial viral load. In turn, infection of the liver could contribute to pathogenesis, and the novel hepatocyte-specific human targets identified here could be important for dengue infection and pathogenesis. PMID:25046486

  20. Gene Expression Analysis Identifies Potential Biomarkers of Neurofibromatosis Type 1 Including Adrenomedullin

    PubMed Central

    Hummel, Trent R.; Jessen, Walter J.; Miller, Shyra J.; Kluwe, Lan; Mautner, Victor F.; Wallace, Margaret R.; Lázaro, Conxi; Page, Grier P.; Worley, Paul F.; Aronow, Bruce J.; Schorry, Elizabeth K.; Ratner, Nancy

    2016-01-01

    Purpose Plexiform neurofibromas (pNF) are Schwann cell tumors found in a third of individuals with neurofibromatosis type 1 (NF1). pNF can undergo transformation to malignant peripheral nerve sheath tumors (MPNST). There are no identified serum biomarkers of pNF tumor burden or transformation to MPNST. Serum biomarkers would be useful to verify NF1 diagnosis, monitor tumor burden, and/or detect transformation. Experimental Design We used microarray gene expression analysis to define 92 genes that encode putative secreted proteins in neurofibroma Schwann cells, neurofibromas, and MPNST. We validated differential expression by quantitative reverse transcription-PCR, Western blotting, and ELISA assays in cell conditioned medium and control and NF1 patient sera. Results Of 13 candidate genes evaluated, only adrenomedullin (ADM) was confirmed as differentially expressed and elevated in serum of NF1 patients. ADM protein concentrati on was further elevated in serum of a small sampling of NF1 patients with MPNST. MPNST cell conditioned medium, containing ADM and hepatocyte growth factor, stimulated MPNST migration and endothelial cell proliferation. Conclusions Thus, microarray analysis identifies potential serum biomarkers for disease, and ADM is a serum biomarker of NF1. ADM serum levels do not seem to correlate with the presence of pNFs but may be a biomarker of transformation to MPNST. PMID:20739432

  1. Stratified Pathway Analysis to Identify Gene Sets Associated with Oral Contraceptive Use and Breast Cancer

    PubMed Central

    Pang, Herbert; Zhao, Hongyu

    2014-01-01

    Cancer biomarker discovery can facilitate drug development, improve staging of patients, and predict patient prognosis. Because cancer is the result of many interacting genes, analysis based on a set of genes with related biological functions or pathways may be more informative than single gene-based analysis for cancer biomarker discovery. The relevant pathways thus identified may help characterize different aspects of molecular phenotypes related to the tumor. Although it is well known that cancer patients may respond to the same treatment differently because of clinical variables and variation of molecular phenotypes, this patient heterogeneity has not been explicitly considered in pathway analysis in the literature. We hypothesize that combining pathway and patient clinical information can more effectively identify relevant pathways pertinent to specific patient subgroups, leading to better diagnosis and treatment. In this article, we propose to perform stratified pathway analysis based on clinical information from patients. In contrast to analysis using all the patients, this more focused analysis has the potential to reveal subgroup-specific pathways that may lead to more biological insights into disease etiology and treatment response. As an illustration, the power of our approach is demonstrated through its application to a breast cancer dataset in which the patients are stratified according to their oral contraceptive use. PMID:25574128

  2. Candidate genes and functional noncoding variants identified in a canine model of obsessive-compulsive disorder

    PubMed Central

    2014-01-01

    Background Obsessive-compulsive disorder (OCD), a severe mental disease manifested in time-consuming repetition of behaviors, affects 1 to 3% of the human population. While highly heritable, complex genetics has hampered attempts to elucidate OCD etiology. Dogs suffer from naturally occurring compulsive disorders that closely model human OCD, manifested as an excessive repetition of normal canine behaviors that only partially responds to drug therapy. The limited diversity within dog breeds makes identifying underlying genetic factors easier. Results We use genome-wide association of 87 Doberman Pinscher cases and 63 controls to identify genomic loci associated with OCD and sequence these regions in 8 affected dogs from high-risk breeds and 8 breed-matched controls. We find 119 variants in evolutionarily conserved sites that are specific to dogs with OCD. These case-only variants are significantly more common in high OCD risk breeds compared to breeds with no known psychiatric problems. Four genes, all with synaptic function, have the most case-only variation: neuronal cadherin (CDH2), catenin alpha2 (CTNNA2), ataxin-1 (ATXN1), and plasma glutamate carboxypeptidase (PGCP). In the 2 Mb gene desert between the cadherin genes CDH2 and DSC3, we find two different variants found only in dogs with OCD that disrupt the same highly conserved regulatory element. These variants cause significant changes in gene expression in a human neuroblastoma cell line, likely due to disrupted transcription factor binding. Conclusions The limited genetic diversity of dog breeds facilitates identification of genes, functional variants and regulatory pathways underlying complex psychiatric disorders that are mechanistically similar in dogs and humans. PMID:24995881

  3. Dorothy Hodgkin Lecture 2014. Understanding genes identified by genome-wide association studies for type 2 diabetes.

    PubMed

    Rutter, G A

    2014-12-01

    Whilst the heritable nature of Type 2 diabetes has been recognized for many years, only in the past two decades have linkage analyses in families and genome-wide association studies in large populations begun to reveal the genetic landscape of the disease in detail. Whilst the former have provided a powerful means of identifying the genes responsible for monogenic forms of the disease, the latter highlight relatively large genomic regions. These often harbour multiple genes, whose relative contribution to exaggerated disease risk is uncertain. In the present study, the approaches that have been used to dissect the role of just a few (TCF7L2, SLC30A8, ADCY5, MTNR1B and CDKAL1) of the ~ 500 genes identified at dozens of implicated loci are described. These are usually selected based on the strength of their effect on disease risk, and predictions as to their likely biological role. Direct determination of the effects of identified polymorphisms on gene expression in disease-relevant tissues, notably the pancreatic islet, are then performed to identify genes whose expression is affected by a particular polymorphism. Subsequent functional analyses then involve perturbing gene expression in vitro in β-cell lines or isolated islets and in vivo in animal models. Although the majority of polymorphisms affect insulin production rather than action, and mainly affect the β cell, effects via other tissues may also contribute, requiring careful consideration in the design and interpretation of experiments in model systems. These considerations illustrate the scale of the task needed to exploit genome-wide association study data for the development of new therapeutic strategies. PMID:25186316

  4. A set-based association test identifies sex-specific gene sets associated with type 2 diabetes

    PubMed Central

    He, Tao; Zhong, Ping-Shou; Cui, Yuehua

    2014-01-01

    Single variant analysis in genome-wide association studies (GWAS) has been proven to be successful in identifying thousands of genetic variants associated with hundreds of complex diseases. However, these identified variants only explain a small fraction of inheritable variability in many diseases, suggesting that other resources, such as multilevel genetic variations, may contribute to disease susceptibility. In this work, we proposed to combine genetic variants that belong to a gene set, such as at gene- and pathway-level to form an integrated signal aimed to identify major players that function in a coordinated manner conferring disease risk. The integrated analysis provides novel insight into disease etiology while individual signals could be easily missed by single variant analysis. We applied our approach to a genome-wide association study of type 2 diabetes (T2D) with male and female data analyzed separately. Novel sex-specific genes and pathways were identified to increase the risk of T2D. We also demonstrated the performance of signal integration through simulation studies. PMID:25429300

  5. Analysis of genomic aberrations and gene expression profiling identifies novel lesions and pathways in myeloproliferative neoplasms.

    PubMed

    Rice, K L; Lin, X; Wolniak, K; Ebert, B L; Berkofsky-Fessler, W; Buzzai, M; Sun, Y; Xi, C; Elkin, P; Levine, R; Golub, T; Gilliland, D G; Crispino, J D; Licht, J D; Zhang, W

    2011-11-01

    Polycythemia vera (PV), essential thrombocythemia and primary myelofibrosis, are myeloproliferative neoplasms (MPNs) with distinct clinical features and are associated with the JAK2V617F mutation. To identify genomic anomalies involved in the pathogenesis of these disorders, we profiled 87 MPN patients using Affymetrix 250K single-nucleotide polymorphism (SNP) arrays. Aberrations affecting chr9 were the most frequently observed and included 9pLOH (n=16), trisomy 9 (n=6) and amplifications of 9p13.3-23.3 (n=1), 9q33.1-34.13 (n=1) and 9q34.13 (n=6). Patients with trisomy 9 were associated with elevated JAK2V617F mutant allele burden, suggesting that gain of chr9 represents an alternative mechanism for increasing JAK2V617F dosage. Gene expression profiling of patients with and without chr9 abnormalities (+9, 9pLOH), identified genes potentially involved in disease pathogenesis including JAK2, STAT5B and MAPK14. We also observed recurrent gains of 1p36.31-36.33 (n=6), 17q21.2-q21.31 (n=5) and 17q25.1-25.3 (n=5) and deletions affecting 18p11.31-11.32 (n=8). Combined SNP and gene expression analysis identified aberrations affecting components of a non-canonical PRC2 complex (EZH1, SUZ12 and JARID2) and genes comprising a 'HSC signature' (MLLT3, SMARCA2 and PBX1). We show that NFIB, which is amplified in 7/87 MPN patients and upregulated in PV CD34+ cells, protects cells from apoptosis induced by cytokine withdrawal. PMID:22829077

  6. Gene expression reveals overlap between normal aging and Alzheimer’s disease genes

    PubMed Central

    Avramopoulos, Dimitrios; Szymanski, Megan; Wang, Ruihua; Bassett, Susan

    2010-01-01

    Alzheimer’s disease (AD) is a common cause of dementia with a strong genetic component and risk sharply increasing with age. We performed two parallel microarray experiments to independently identify genes involved in normal aging and genes involved in AD using RNA extracted from the temporal lobe of 22 late onset AD and 23 control brain donors. We found that AD is accompanied by significant changes in the expression of many genes with up-regulation of genes involved in inflammation and in transcription regulation and down-regulation of genes involved in neuronal functions. The changes with healthy aging involved multiple genes but were not as strong. Replicating and strengthening previous reports we find a highly significant overlap between genes changing expression with age and those changing in AD and we observe that those changes are most often in the same direction. This result supports an overlap between the biological processes of normal aging and susceptibility to AD and suggests that age related genes expression changes might increase the risk to develop AD. PMID:20570407

  7. Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas

    PubMed Central

    ZHOU, RUIGANG; MAN, YIGANG

    2016-01-01

    The present study performed an integral analysis of the gene expression and DNA methylation profile of pilocytic astrocytomas (PAs). Weighted gene co-expression network analysis (WGCNA) was also performed to examine and identify the genes correlated to PAs, to identify candidate therapeutic targets for the treatment of PAs. The DNA methylation profile and gene expression profile were downloaded from the Gene Expression Omnibus database. Following screening of the differentially expressed genes (DEGs) and differentially methylated regions (DMRs), respectively, integrated analysis of the DEGs and DMRs was performed to detect their correlation. Subsequently, the WGCNA algorithm was applied to identify the significant modules and construct the co-expression network associated with PAs. Furthermore, Gene Ontology enrichment analysis of the associated genes was performed using the Database for Annotation, Visualization and Integrated Discovery. A total number of 2,259 DEGs and 235 DMRs were screened out. Integrated analysis revealed that 30 DEGs were DMRs with prominent negative correlation (cor=−0.82; P=0.02). Based on the DEGs, the gene co-expression network was constructed, and nine network modules associated with PAs were identified. The functional analysis results showed that genes relevant to PAs were closely associated with cell differentiation modulation. The screened PA-associated genes were significantly different at the expression and methylation levels. These genes may be used as reliable candidate target genes for the treatment of PAs. PMID:26934913

  8. Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas.

    PubMed

    Zhou, Ruigang; Man, Yigang

    2016-04-01

    The present study performed an integral analysis of the gene expression and DNA methylation profile of pilocytic astrocytomas (PAs). Weighted gene co-expression network analysis (WGCNA) was also performed to examine and identify the genes correlated to PAs, to identify candidate therapeutic targets for the treatment of PAs. The DNA methylation profile and gene expression profile were downloaded from the Gene Expression Omnibus database. Following screening of the differentially expressed genes (DEGs) and differentially methylated regions (DMRs), respectively, integrated analysis of the DEGs and DMRs was performed to detect their correlation. Subsequently, the WGCNA algorithm was applied to identify the significant modules and construct the co‑expression network associated with PAs. Furthermore, Gene Ontology enrichment analysis of the associated genes was performed using the Database for Annotation, Visualization and Integrated Discovery. A total number of 2,259 DEGs and 235 DMRs were screened out. Integrated analysis revealed that 30 DEGs were DMRs with prominent negative correlation (cor=‑0.82; P=0.02). Based on the DEGs, the gene co‑expression network was constructed, and nine network modules associated with PAs were identified. The functional analysis results showed that genes relevant to PAs were closely associated with cell differentiation modulation. The screened PA-associated genes were significantly different at the expression and methylation levels. These genes may be used as reliable candidate target genes for the treatment of PAs. PMID:26934913

  9. A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

    PubMed

    Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

    2015-01-01

    In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

  10. A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

    PubMed Central

    Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

    2015-01-01

    In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

  11. Identifying and characterizing barley genes that protect against trichothecene mycotoxins

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fusarium head blight of wheat and barley, caused by the fungal pathogen Fusarium graminearum, is a major disease problem around the world. During infection, trichothecene mycotoxins are produced and act as virulence factors, resulting in reduced grain yield and quality. There are two types of tricho...

  12. Identifying mechanistic indicators of childhood asthma from blood gene expression

    EPA Science Inventory

    Asthmatic individuals have been identified as a susceptible subpopulation for air pollutants. However, asthma represents a syndrome with multiple probable etiologies, and the identification of these asthma endotypes is critical to accurately define the most susceptible subpopula...

  13. DIFFERENTIALLY EXPRESSED GENES IN RESPONSES TO LATE LEAF SPOT DISEASE CAUSED BY CERCOSPORIDIUM PERSONATUM IN PEANUT USING MICROARRAY ANALYSIS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Late leaf spot disease caused by Cercosporidium personatum is one of the most destructive foliar diseases of peanut worldwide. This research was to identify resistance genes in response to leaf spot disease using miccroarray and real-time PCR. To identify transcripts involved in disease resistance, ...

  14. Novel Association Strategy with Copy Number Variation for Identifying New Risk Loci of Human Diseases

    PubMed Central

    Chen, Xianfeng; Li, Xinlei; Wang, Ping; Liu, Yang; Zhang, Zhenguo; Zhao, Guoping; Xu, Haiming; Zhu, Jun; Qin, Xueying; Chen, Suchao; Hu, Landian; Kong, Xiangyin

    2010-01-01

    Background Copy number variations (CNV) are important causal genetic variations for human disease; however, the lack of a statistical model has impeded the systematic testing of CNVs associated with disease in large-scale cohort. Methodology/Principal Findings Here, we developed a novel integrated strategy to test CNV-association in genome-wide case-control studies. We converted the single-nucleotide polymorphism (SNP) signal to copy number states using a well-trained hidden Markov model. We mapped the susceptible CNV-loci through SNP site-specific testing to cope with the physiological complexity of CNVs. We also ensured the credibility of the associated CNVs through further window-based CNV-pattern clustering. Genome-wide data with seven diseases were used to test our strategy and, in total, we identified 36 new susceptible loci that are associated with CNVs for the seven diseases: 5 with bipolar disorder, 4 with coronary artery disease, 1 with Crohn's disease, 7 with hypertension, 9 with rheumatoid arthritis, 7 with type 1 diabetes and 3 with type 2 diabetes. Fifteen of these identified loci were validated through genotype-association and physiological function from previous studies, which provide further confidence for our results. Notably, the genes associated with bipolar disorder converged in the phosphoinositide/calcium signaling, a well-known affected pathway in bipolar disorder, which further supports that CNVs have impact on bipolar disorder. Conclusions/Significance Our results demonstrated the effectiveness and robustness of our CNV-association analysis and provided an alternative avenue for discovering new associated loci of human diseases. PMID:20808825

  15. Gene Prospector: An evidence gateway for evaluating potential susceptibility genes and interacting risk factors for human diseases

    PubMed Central

    Yu, Wei; Wulf, Anja; Liu, Tiebin; Khoury, Muin J; Gwinn, Marta

    2008-01-01

    Background Millions of single nucleotide polymorphisms have been identified as a result of the human genome project and the rapid advance of high throughput genotyping technology. Genetic association studies, such as recent genome-wide association studies (GWAS), have provided a springboard for exploring the contribution of inherited genetic variation and gene/environment interactions in relation to disease. Given the capacity of such studies to produce a plethora of information that may then be described in a number of publications, selecting possible disease susceptibility genes and identifying related modifiable risk factors is a major challenge. A Web-based application for finding evidence of such relationships is key to the development of follow-up studies and evidence for translational research. We developed a Web-based application that selects and prioritizes potential disease-related genes by using a highly curated and updated literature database of genetic association studies. The application, called Gene Prospector, also provides a comprehensive set of links to additional data sources. Results We compared Gene Prospector results for the query "Parkinson" with a list of 13 leading candidate genes (Top Results) from a curated, specialty database for genetic associations with Parkinson disease (PDGene). Nine of the thirteen leading candidate genes from PDGene were in the top 10th percentile of the ranked list from Gene Prospector. In fact, Gene Prospector included more published genetic association studies for the 13 leading candidate genes than PDGene did. Conclusion Gene Prospector provides an online gateway for searching for evidence about human genes in relation to diseases, other phenotypes, and risk factors, and provides links to published literature and other online data sources. Gene Prospector can be accessed via . PMID:19063745

  16. Candidate genes for limiting cholestatic intestinal injury identified by gene expression profiling

    PubMed Central

    Alaish, Samuel M; Timmons, Jennifer; Smith, Alexis; Buzza, Marguerite S; Murphy, Ebony; Zhao, Aiping; Sun, Yezhou; Turner, Douglas J; Shea-Donahue, Terez; Antalis, Toni M; Cross, Alan; Dorsey, Susan G

    2013-01-01

    The lack of bile flow from the liver into the intestine can have devastating complications including hepatic failure, sepsis, and even death. This pathologic condition known as cholestasis can result from etiologies as diverse as total parenteral nutrition (TPN), hepatitis, and pancreatic cancer. The intestinal injury associated with cholestasis has been shown to result in decreased intestinal resistance, increased bacterial translocation, and increased endotoxemia. Anecdotal clinical evidence suggests a genetic predisposition to exaggerated injury. Recent animal research on two different strains of inbred mice demonstrating different rates of bacterial translocation with different mortality rates supports this premise. In this study, a microarray analysis of intestinal tissue following common bile duct ligation (CBDL) performed under general anesthesia on these same two strains of inbred mice was done with the goal of identifying the potential molecular mechanistic pathways responsible. Over 500 genes were increased more than 2.0-fold following CBDL. The most promising candidate genes included major urinary proteins (MUPs), serine protease-1-inhibitor (Serpina1a), and lipocalin-2 (LCN-2). Quantitative polymerase chain reaction (qPCR) validated the microarray results for these candidate genes. In an in vitro experiment using differentiated intestinal epithelial cells, inhibition of MUP-1 by siRNA resulted in increased intestinal epithelial cell permeability. Diverse novel mechanisms involving the growth hormone pathway, the acute phase response, and the innate immune response are thus potential avenues for limiting cholestatic intestinal injury. Changes in gene expression were at times found to be not only due to the CBDL but also due to the murine strain. Should further studies in cholestatic patients demonstrate interindividual variability similar to what we have shown in mice, then a “personalized medicine” approach to cholestatic patients may become possible. PMID:24179676

  17. Synthetic lethal screening in the mammalian central nervous system identifies Gpx6 as a modulator of Huntingtons disease

    PubMed Central

    Shema, Reut; Kulicke, Ruth; Cowley, Glenn S.; Stein, Rachael; Root, David E.; Heiman, Myriam

    2015-01-01

    Huntingtons disease, the most common inherited neurodegenerative disease, is characterized by a dramatic loss of deep-layer cortical and striatal neurons, as well as morbidity in midlife. Human genetic studies led to the identification of the causative gene, huntingtin. Recent genomic advances have also led to the identification of hundreds of potential interacting partners for huntingtin protein and many hypotheses as to the molecular mechanisms whereby mutant huntingtin leads to cellular dysfunction and death. However, the multitude of possible interacting partners and cellular pathways affected by mutant huntingtin has complicated efforts to understand the etiology of this disease, and to date no curative therapeutic exists. To address the general problem of identifying the disease-phenotype contributing genes from a large number of correlative studies, here we develop a synthetic lethal screening methodology for the mammalian central nervous system, called SLIC, for synthetic lethal in the central nervous system. Applying SLIC to the study of Huntingtons disease, we identify the age-regulated glutathione peroxidase 6 (Gpx6) gene as a modulator of mutant huntingtin toxicity and show that overexpression of Gpx6 can dramatically alleviate both behavioral and molecular phenotypes associated with a mouse model of Huntingtons disease. SLIC can, in principle, be used in the study of any neurodegenerative disease for which a mouse model exists, promising to reveal modulators of neurodegenerative disease in an unbiased fashion, akin to screens in simpler model organisms. PMID:25535386

  18. Identifying Foodborne Disease Hazards in Food Service Establishments

    ERIC Educational Resources Information Center

    Bryan, Frank L.

    1974-01-01

    Describes procedures used to evaluate foodborne disease hazards that exist in food service establishments, lists the factors that have contributed to foodborne disease outbreaks in the United States, and presents a form that has been devised to facilitate the evaluation of these factors. (JR)

  19. Identifying the genetic basis of attenuation in Marek's disease virus

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek’s disease virus (MDV) is an oncogenic alphaherpesvirus of chickens that induces lymphoid tumors in susceptible birds. This agronomically-important disease is controlled primarily through vaccines that prevent tumor formation but are non-sterilizing. Currently most efficacious vaccines consist ...

  20. Uncover disease genes by maximizing information flow in the phenome–interactome network

    PubMed Central

    Chen, Yong; Jiang, Tao; Jiang, Rui

    2011-01-01

    Motivation: Pinpointing genes that underlie human inherited diseases among candidate genes in susceptibility genetic regions is the primary step towards the understanding of pathogenesis of diseases. Although several probabilistic models have been proposed to prioritize candidate genes using phenotype similarities and protein–protein interactions, no combinatorial approaches have been proposed in the literature. Results: We propose the first combinatorial approach for prioritizing candidate genes. We first construct a phenome–interactome network by integrating the given phenotype similarity profile, protein–protein interaction network and associations between diseases and genes. Then, we introduce a computational method called MAXIF to maximize the information flow in this network for uncovering genes that underlie diseases. We demonstrate the effectiveness of this method in prioritizing candidate genes through a series of cross-validation experiments, and we show the possibility of using this method to identify diseases with which a query gene may be associated. We demonstrate the competitive performance of our method through a comparison with two existing state-of-the-art methods, and we analyze the robustness of our method with respect to the parameters involved. As an example application, we apply our method to predict driver genes in 50 copy number aberration regions of melanoma. Our method is not only able to identify several driver genes that have been reported in the literature, it also shed some new biological insights on the understanding of the modular property and transcriptional regulation scheme of these driver genes. Contact: ruijiang@tsinghua.edu.cn PMID:21685067

  1. Seven newly identified loci for autoimmune thyroid disease.

    PubMed

    Cooper, Jason D; Simmonds, Matthew J; Walker, Neil M; Burren, Oliver; Brand, Oliver J; Guo, Hui; Wallace, Chris; Stevens, Helen; Coleman, Gillian; Franklyn, Jayne A; Todd, John A; Gough, Stephen C L

    2012-12-01

    Autoimmune thyroid disease (AITD), including Graves' disease (GD) and Hashimoto's thyroiditis (HT), is one of the most common of the immune-mediated diseases. To further investigate the genetic determinants of AITD, we conducted an association study using a custom-made single-nucleotide polymorphism (SNP) array, the ImmunoChip. The SNP array contains all known and genotype-able SNPs across 186 distinct susceptibility loci associated with one or more immune-mediated diseases. After stringent quality control, we analysed 103 875 common SNPs (minor allele frequency >0.05) in 2285 GD and 462 HT patients and 9364 controls. We found evidence for seven new AITD risk loci (P < 1.12 × 10(-6); a permutation test derived significance threshold), five at locations previously associated and two at locations awaiting confirmation, with other immune-mediated diseases. PMID:22922229

  2. Analysis of antigen receptor genes in Hodgkin's disease.

    PubMed Central

    Angel, C A; Pringle, J H; Naylor, J; West, K P; Lauder, I

    1993-01-01

    AIM--To analyse the configuration of the antigen receptor genes in Hodgkin's disease. METHODS--DNA extracted from 45 samples of Hodgkin's disease was analysed using Southern blotting and DNA hybridisation, using probes to the joining region of the immunoglobulin heavy chain gene, the constant region of kappa immunoglobulin light chain gene, and the constant region of the beta chain of the T cell receptor gene. RESULTS--A single case of nodular sclerosing disease showed clonal rearrangement of the immunoglobulin heavy and light chain genes, all other samples having germline immunoglobulin genes. The nature of the clonal population in the diseased tissue is uncertain, because the intensity of the rearranged bands did not correlate with the percentage of Reed-Sternberg cells present. The T cell receptor genes were in germline configuration in all the samples. CONCLUSIONS--Antigen receptor gene rearrangement is a rare finding in unselected cases of Hodgkin's disease. Images PMID:8388407

  3. Exome Sequencing Identifies a Novel Gene, WNK1, for Susceptibility to Pelvic Organ Prolapse (POP)

    PubMed Central

    Rao, Shuquan; Lang, Jinghe; Zhu, Lan; Chen, Juan

    2015-01-01

    Pelvic organ prolapse (POP) is a common gynecological disorder; however, the genetic components remain largely unidentified. Exome sequencing has been widely used to identify pathogenic gene mutations of several diseases because of its high chromosomal coverage and accuracy. In this study, we performed whole exome sequencing (WES), for the first time, on 8 peripheral blood DNA samples from representative POP cases. After filtering the sequencing data from the dbSNP database (build 138) and the 1000 Genomes Project, 2 missense variants in WNK1, c.2668G > A (p.G890R) and c.6761C> T (p.P2254L), were identified and further validated via Sanger sequencing. In validation stage, the c.2668G > A (p.G890R) variant and 8 additional variants were detected in 11 out of 161 POP patients. All these variants were absent in 231 healthy controls. Functional experiments showed that fibroblasts from the utero-sacral ligaments of POP with WNK1 mutations exhibited loose and irregular alignment compared with fibroblasts from healthy controls. In sum, our study identified a novel gene, WNK1, for POP susceptibility, expanded the causal mutation spectrums of POP, and provided evidence for the genetic diagnosis and medical management of POP in the future. PMID:25739019

  4. Gene expression profiles in the rat streptococcal cell wall-induced arthritis model identified using microarray analysis

    PubMed Central

    Rioja, Inmaculada; Clayton, Chris L; Graham, Simon J; Life, Paul F; Dickson, Marion C

    2005-01-01

    Experimental arthritis models are considered valuable tools for delineating mechanisms of inflammation and autoimmune phenomena. Use of microarray-based methods represents a new and challenging approach that allows molecular dissection of complex autoimmune diseases such as arthritis. In order to characterize the temporal gene expression profile in joints from the reactivation model of streptococcal cell wall (SCW)-induced arthritis in Lewis (LEW/N) rats, total RNA was extracted from ankle joints from naïve, SCW injected, or phosphate buffered saline injected animals (time course study) and gene expression was analyzed using Affymetrix oligonucleotide microarray technology (RAE230A). After normalization and statistical analysis of data, 631 differentially expressed genes were sorted into clusters based on their levels and kinetics of expression using Spotfire® profile search and K-mean cluster analysis. Microarray-based data for a subset of genes were validated using real-time PCR TaqMan® analysis. Analysis of the microarray data identified 631 genes (441 upregulated and 190 downregulated) that were differentially expressed (Delta > 1.8, P < 0.01), showing specific levels and patterns of gene expression. The genes exhibiting the highest fold increase in expression on days -13.8, -13, or 3 were involved in chemotaxis, inflammatory response, cell adhesion and extracellular matrix remodelling. Transcriptome analysis identified 10 upregulated genes (Delta > 5), which have not previously been associated with arthritis pathology and are located in genomic regions associated with autoimmune disease. The majority of the downregulated genes were associated with metabolism, transport and regulation of muscle development. In conclusion, the present study describes the temporal expression of multiple disease-associated genes with potential pathophysiological roles in the reactivation model of SCW-induced arthritis in Lewis (LEW/N) rat. These findings improve our understanding of the molecular events that underlie the pathology in this animal model, which is potentially a valuable comparator to human rheumatoid arthritis (RA). PMID:15642130

  5. Identifying microRNA targets in different gene regions

    PubMed Central

    2014-01-01

    Background Currently available microRNA (miRNA) target prediction algorithms require the presence of a conserved seed match to the 5' end of the miRNA and limit the target sites to the 3' untranslated regions of mRNAs. However, it has been noted that these requirements may be too stringent, leading to a substantial number of missing targets. Results We have developed TargetS, a novel computational approach for predicting miRNA targets with the target sites located along entire gene sequences, which permits finding additional targets that are not located in the 3' un-translated regions. Our model is based on both canonical seed matching and non-canonical seed pairing, which discovers targets that allow one bit GU wobble. It does not rely on evolutionary conservation, so it allows the detection of species-specific miRNA-mRNA interactions and makes it suitable for analyzing un-conserved gene sequences. To test the performance of our approach, we have imported the widely used benchmark dataset revealing fold-changes in protein production corresponding to each of the five selected microRNAs. Compared to well-known miRNA target prediction tools, including TargetScanS, PicTar and MicroT_CDS, our method yields the highest sensitivity, while achieving a comparable level of accuracy. Human miRNA target predictions using our computational approach are available online at http://liubioinfolab.org/targetS/mirna.html Conclusions A simple but powerful computational miRNA target prediction method is developed that is solely based on canonical and non-canonical seed matches without requiring evolutionary conservation of the target sites. Our method also expands the target search space to different gene regions, rather than limiting to 3'UTR only. This improves the sensitivity of miRNA target identification, while achieving a comparable accuracy with existing methods. PMID:25077573

  6. Gene expression profiling predicts pathways and genes associated with Parkinson's disease.

    PubMed

    Liu, Shuang; Zhang, Yong; Bian, Hong; Li, Xiaohong

    2016-01-01

    This study was aimed to explore the molecular mechanism of Parkinson's disease (PD) development and discover underlying pathways and genes associated with PD. The microarray data of GSE22491 containing 10 samples from PD patients and 8 samples from healthy controls (HC) were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by paired t-test. Then the DEGs were performed cluster and principal component analyses followed by Gene Ontology (GO) and pathway enrichment analyses and protein-protein interaction (PPI) network construction. Total 176 up-regulated DEGs and 49 down-regulated DEGs were identified. Totally, 39 GO terms and 72 pathways were closely related to PD. Pathway of neuronal system was enriched by 10 DEGs such as synapsin I (SYN1), glutamate receptor, ionotropic, N-methyl-D-aspartate 1 (GRIN1) and GRIN2D. In the PPI networks, 18 hub genes were obtained, such as GRIN2D and discs, large (Drosophila) homolog-associated protein 3 (DLGAP3). The pathway of neuronal system and its enriched DEGs may play important roles in PD progression. The DEGs such as SYN1, GRIN1, GRIN2D and DLGAP3 may become promising candidate genes for PD. PMID:26269422

  7. Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach

    PubMed Central

    Yuan, Fei; Zhou, You; Wang, Meng; Yang, Jing; Wu, Kai; Lu, Changhong; Kong, Xiangyin; Cai, Yu-Dong

    2015-01-01

    Prostate cancer is a type of cancer that occurs in the male prostate, a gland in the male reproductive system. Because prostate cancer cells may spread to other parts of the body and can influence human reproduction, understanding the mechanisms underlying this disease is critical for designing effective treatments. The identification of as many genes and chemicals related to prostate cancer as possible will enhance our understanding of this disease. In this study, we proposed a computational method to identify new candidate genes and chemicals based on currently known genes and chemicals related to prostate cancer by applying a shortest path approach in a hybrid network. The hybrid network was constructed according to information concerning chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions. Many of the obtained genes and chemicals are associated with prostate cancer. PMID:26504486

  8. Using Epidemiological Models and Genetic Selection to Identify Theoretical Opportunities to Reduce Disease Impact

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Selection for disease resistance is a contemporary topic with developing approaches for genetic improvement. Merging the sciences of genetic selection and epidemiology is essential to identify selection schemes to enhance disease resistance. Epidemiological models can identify theoretical opportuni...

  9. Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis.

    PubMed

    Kazmi, Nabila; Gaunt, Tom R

    2016-01-01

    Cardiovascular disease (including coronary artery disease and myocardial infarction) is one of the leading causes of death in Europe, and is influenced by both environmental and genetic factors. With the recent advances in genomic tools and technologies there is potential to predict and diagnose heart disease using molecular data from analysis of blood cells. We analyzed gene expression data from blood samples taken from normal people (n = 21), non-significant coronary artery disease (n = 93), patients with unstable angina (n = 16), stable coronary artery disease (n = 14) and myocardial infarction (MI; n = 207). We used a feature selection approach to identify a set of gene expression variables which successfully differentiate different cardiovascular diseases. The initial features were discovered by fitting a linear model for each probe set across all arrays of normal individuals and patients with myocardial infarction. Three different feature optimisation algorithms were devised which identified two discriminating sets of genes, one using MI and normal controls (total genes = 6) and another one using MI and unstable angina patients (total genes = 7). In all our classification approaches we used a non-parametric k-nearest neighbour (KNN) classification method (k = 3). The results proved the diagnostic robustness of the final feature sets in discriminating patients with myocardial infarction from healthy controls. Interestingly it also showed efficacy in discriminating myocardial infarction patients from patients with clinical symptoms of cardiac ischemia but no myocardial necrosis or stable coronary artery disease, despite the influence of batch effects and different microarray gene chips and platforms. PMID:26930047

  10. Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis

    PubMed Central

    Kazmi, Nabila; Gaunt, Tom R.

    2016-01-01

    Cardiovascular disease (including coronary artery disease and myocardial infarction) is one of the leading causes of death in Europe, and is influenced by both environmental and genetic factors. With the recent advances in genomic tools and technologies there is potential to predict and diagnose heart disease using molecular data from analysis of blood cells. We analyzed gene expression data from blood samples taken from normal people (n = 21), non-significant coronary artery disease (n = 93), patients with unstable angina (n = 16), stable coronary artery disease (n = 14) and myocardial infarction (MI; n = 207). We used a feature selection approach to identify a set of gene expression variables which successfully differentiate different cardiovascular diseases. The initial features were discovered by fitting a linear model for each probe set across all arrays of normal individuals and patients with myocardial infarction. Three different feature optimisation algorithms were devised which identified two discriminating sets of genes, one using MI and normal controls (total genes = 6) and another one using MI and unstable angina patients (total genes = 7). In all our classification approaches we used a non-parametric k-nearest neighbour (KNN) classification method (k = 3). The results proved the diagnostic robustness of the final feature sets in discriminating patients with myocardial infarction from healthy controls. Interestingly it also showed efficacy in discriminating myocardial infarction patients from patients with clinical symptoms of cardiac ischemia but no myocardial necrosis or stable coronary artery disease, despite the influence of batch effects and different microarray gene chips and platforms. PMID:26930047

  11. Shared Genetic Etiology between Type 2 Diabetes and Alzheimer's Disease Identified by Bioinformatics Analysis.

    PubMed

    Gao, Lei; Cui, Zhen; Shen, Liang; Ji, Hong-Fang

    2015-11-28

    Type 2 diabetes (T2D) and Alzheimer's disease (AD) are two major health issues, and increasing evidence in recent years supports the close connection between these two diseases. The present study aimed to explore the shared genetic etiology underlying T2D and AD based on the available genome wide association studies (GWAS) data collected through August 2014. We performed bioinformatics analyses based on GWAS data of T2D and AD on single nucleotide polymorphisms (SNPs), gene, and pathway levels, respectively. Six SNPs (rs111789331, rs12721046, rs12721051, rs4420638, rs56131196, and rs66626994) were identified for the first time to be shared genetic factors between T2D and AD. Further functional enrichment analysis found lipid metabolism related pathways to be common between these two disorders. The findings may have important implications for future mechanistic and interventional studies for T2D and AD. PMID:26639962

  12. EvoTol: a protein-sequence based evolutionary intolerance framework for disease-gene prioritization

    PubMed Central

    Rackham, Owen J. L.; Shihab, Hashem A.; Johnson, Michael R.; Petretto, Enrico

    2015-01-01

    Methods to interpret personal genome sequences are increasingly required. Here, we report a novel framework (EvoTol) to identify disease-causing genes using patient sequence data from within protein coding-regions. EvoTol quantifies a gene's intolerance to mutation using evolutionary conservation of protein sequences and can incorporate tissue-specific gene expression data. We apply this framework to the analysis of whole-exome sequence data in epilepsy and congenital heart disease, and demonstrate EvoTol's ability to identify known disease-causing genes is unmatched by competing methods. Application of EvoTol to the human interactome revealed networks enriched for genes intolerant to protein sequence variation, informing novel polygenic contributions to human disease. PMID:25550428

  13. Genetic association of sirtuin genes and Parkinson's disease.

    PubMed

    Jesús, Silvia; Gómez-Garre, Pilar; Carrillo, Fátima; Cáceres-Redondo, María T; Huertas-Fernández, Ismael; Bernal-Bernal, Inmaculada; Bonilla-Toribio, Marta; Vargas-González, Laura; Carballo, Manuel; Mir, Pablo

    2013-09-01

    Parkinson's disease (PD) is a neurodegenerative disease caused by both genetic and environmental factors. Sirtuins are highly-conserved, NAD-dependent class III deacetylases that regulate a variety of cellular functions. Most of the known sirtuins have been involved in animal models of neurodegenerative disorders, such as PD. Although seven sirtuin family members have been identified (SIRT1-SIRT7) the relationship between sirtuins and PD in humans has not been established. Our aim was to investigate the association between sirtuin genes and risk of PD. We included 326 PD patients and 371 controls from southern Spain. Forty-one single nucleotide polymorphisms (SNPs) in sirtuin genes were genotyped in order to determine whether they were related to the risk of PD. These SNPs included Tag-SNPs, coding non-synonymous SNPs and SNPs affecting activity of microRNA binding sites. No relationship was found between these SNPs in sirtuin genes and PD. Our data indicate that variations in sirtuin genes do not affect the risk for PD, at least in our population. PMID:23719790

  14. Identifying genes affectng stress response in rainbow trout

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genomic analyses have the potential to impact aquaculture production traits by identifying markers as proxies for traits which are expensive or difficult to measure and characterizing genetic variation and biochemical mechanisms underlying phenotypic variation. One such set of traits are the respon...

  15. Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease

    PubMed Central

    Rivas, Manuel A.; Beaudoin, Melissa; Gardet, Agnes; Stevens, Christine; Sharma, Yashoda; Zhang, Clarence K.; Boucher, Gabrielle; Ripke, Stephan; Ellinghaus, David; Burtt, Noel; Fennell, Tim; Kirby, Andrew; Latiano, Anna; Goyette, Philippe; Green, Todd; Halfvarson, Jonas; Haritunians, Talin; Korn, Joshua M.; Kuruvilla, Finny; Lagacé, Caroline; Neale, Benjamin; Lo, Ken Sin; Schumm, Phil; Törkvist, Leif; Dubinsky, Marla; Brant, Steven R.; Silverberg, Mark; Duerr, Richard H.; Altshuler, David; Gabriel, Stacey; Lettre, Guillaume; Franke, Andre; D’Amato, Mauro; McGovern, Dermot P.B.; Cho, Judy H.; Rioux, John D.; Xavier, Ramnik J.; Daly, Mark J.

    2012-01-01

    More than a thousand disease susceptibility loci have been identified via genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings generally remain to be defined. We utilize pooled next-generation sequencing to study 56 genes in regions associated to Crohn’s Disease in 350 cases and 350 controls. Follow up genotyping of 70 rare and low-frequency protein-altering variants (MAF ~ .001-.05) in nine independent case-control series (16054 CD patients, 12153 UC patients, 17575 healthy controls) identifies four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association to a novel, protective splice variant in CARD9 (p < 1e-16, OR ~ 0.29), as well as additional associations to coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by providing novel, rare, and likely functional variants that will empower functional experiments and predictive models. PMID:21983784

  16. Can Raman spectroscopy identify the origin of Paget disease?

    NASA Astrophysics Data System (ADS)

    Martin, A. A.; Marcelo, Moreno; Bitar, R.; Martinho, H., .; Santos, E. A. P.; Arisawa, E. A. L.

    2008-02-01

    The histogenesis of the breast Paget's disease was investigated by the optical diagnosis technique using Raman spectroscopy. A total of 15 spectra of the associated breast lesion, 21 spectra of the eczematoid skin lesion and 396 spectra of invasive breast cancer not otherwise specified were compared by clustering the spectral data between 800 - 1800 cm -1 at level of similarity of 95%, using a correlation distance measurement by computing the covariance matrix. The Raman spectral-biochemical characterization of invasive breast cancer and breast Paget's disease with eczematoid skin lesion associated with underlying invasive breast lesion tissues enabled one concludes that the parenchymal disease had similar characteristics to the skin's Paget lesion. This could indicate a similar histogenesis for both. Thus, the findings of the present work adds a relevant experimental evidence that agrees with the epidermotropic theory of Paget's disease, that states that the cells originate in the breast ducts and migrate to the nipple's skin.

  17. Inferring novel gene-disease associations using Medical Subject Heading Over-representation Profiles

    PubMed Central

    2012-01-01

    Background MEDLINE®/PubMed® currently indexes over 18 million biomedical articles, providing unprecedented opportunities and challenges for text analysis. Using Medical Subject Heading Over-representation Profiles (MeSHOPs), an entity of interest can be robustly summarized, quantitatively identifying associated biomedical terms and predicting novel indirect associations. Methods A procedure is introduced for quantitative comparison of MeSHOPs derived from a group of MEDLINE® articles for a biomedical topic (for example, articles for a specific gene or disease). Similarity scores are computed to compare MeSHOPs of genes and diseases. Results Similarity scores successfully infer novel associations between diseases and genes. The number of papers addressing a gene or disease has a strong influence on predicted associations, revealing an important bias for gene-disease relationship prediction. Predictions derived from comparisons of MeSHOPs achieves a mean 8% AUC improvement in the identification of gene-disease relationships compared to gene-independent baseline properties. Conclusions MeSHOP comparisons are demonstrated to provide predictive capacity for novel relationships between genes and human diseases. We demonstrate the impact of literature bias on the performance of gene-disease prediction methods. MeSHOPs provide a rich source of annotation to facilitate relationship discovery in biomedical informatics. PMID:23021552

  18. Genome Wide Transcriptome Analysis of Dendritic Cells Identifies Genes with Altered Expression in Psoriasis

    PubMed Central

    Szász, András; Tubak, Vilmos; Kemény, Lajos; Kondorosi, Éva; Nagy, István

    2013-01-01

    Activation of dendritic cells by different pathogens induces the secretion of proinflammatory mediators resulting in local inflammation. Importantly, innate immunity must be properly controlled, as its continuous activation leads to the development of chronic inflammatory diseases such as psoriasis. Lipopolysaccharide (LPS) or peptidoglycan (PGN) induced tolerance, a phenomenon of transient unresponsiveness of cells to repeated or prolonged stimulation, proved valuable model for the study of chronic inflammation. Thus, the aim of this study was the identification of the transcriptional diversity of primary human immature dendritic cells (iDCs) upon PGN induced tolerance. Using SAGE-Seq approach, a tag-based transcriptome sequencing method, we investigated gene expression changes of primary human iDCs upon stimulation or restimulation with Staphylococcus aureus derived PGN, a widely used TLR2 ligand. Based on the expression pattern of the altered genes, we identified non-tolerizeable and tolerizeable genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (Kegg) analysis showed marked enrichment of immune-, cell cycle- and apoptosis related genes. In parallel to the marked induction of proinflammatory mediators, negative feedback regulators of innate immunity, such as TNFAIP3, TNFAIP8, Tyro3 and Mer are markedly downregulated in tolerant cells. We also demonstrate, that the expression pattern of TNFAIP3 and TNFAIP8 is altered in both lesional, and non-lesional skin of psoriatic patients. Finally, we show that pretreatment of immature dendritic cells with anti-TNF-α inhibits the expression of IL-6 and CCL1 in tolerant iDCs and partially releases the suppression of TNFAIP8. Our findings suggest that after PGN stimulation/restimulation the host cell utilizes different mechanisms in order to maintain critical balance between inflammation and tolerance. Importantly, the transcriptome sequencing of stimulated/restimulated iDCs identified numerous genes with altered expression to date not associated with role in chronic inflammation, underlying the relevance of our in vitro model for further characterization of IFN-primed iDCs. PMID:24039940

  19. Global Analysis of the Human Pathophenotypic Similarity Gene Network Merges Disease Module Components

    PubMed Central

    Reyes-Palomares, Armando; Rodríguez-López, Rocío; Ranea, Juan A. G.; Jiménez, Francisca Sánchez; Medina, Miguel Angel

    2013-01-01

    The molecular complexity of genetic diseases requires novel approaches to break it down into coherent biological modules. For this purpose, many disease network models have been created and analyzed. We highlight two of them, “the human diseases networks” (HDN) and “the orphan disease networks” (ODN). However, in these models, each single node represents one disease or an ambiguous group of diseases. In these cases, the notion of diseases as unique entities reduces the usefulness of network-based methods. We hypothesize that using the clinical features (pathophenotypes) to define pathophenotypic connections between disease-causing genes improve our understanding of the molecular events originated by genetic disturbances. For this, we have built a pathophenotypic similarity gene network (PSGN) and compared it with the unipartite projections (based on gene-to-gene edges) similar to those used in previous network models (HDN and ODN). Unlike these disease network models, the PSGN uses semantic similarities. This pathophenotypic similarity has been calculated by comparing pathophenotypic annotations of genes (human abnormalities of HPO terms) in the “Human Phenotype Ontology”. The resulting network contains 1075 genes (nodes) and 26197 significant pathophenotypic similarities (edges). A global analysis of this network reveals: unnoticed pairs of genes showing significant pathophenotypic similarity, a biological meaningful re-arrangement of the pathological relationships between genes, correlations of biochemical interactions with higher similarity scores and functional biases in metabolic and essential genes toward the pathophenotypic specificity and the pleiotropy, respectively. Additionally, pathophenotypic similarities and metabolic interactions of genes associated with maple syrup urine disease (MSUD) have been used to merge into a coherent pathological module. Our results indicate that pathophenotypes contribute to identify underlying co-dependencies among disease-causing genes that are useful to describe disease modularity. PMID:23437198

  20. Global analysis of the human pathophenotypic similarity gene network merges disease module components.

    PubMed

    Reyes-Palomares, Armando; Rodríguez-López, Rocío; Ranea, Juan A G; Sánchez Jiménez, Francisca; Medina, Miguel Angel

    2013-01-01

    The molecular complexity of genetic diseases requires novel approaches to break it down into coherent biological modules. For this purpose, many disease network models have been created and analyzed. We highlight two of them, "the human diseases networks" (HDN) and "the orphan disease networks" (ODN). However, in these models, each single node represents one disease or an ambiguous group of diseases. In these cases, the notion of diseases as unique entities reduces the usefulness of network-based methods. We hypothesize that using the clinical features (pathophenotypes) to define pathophenotypic connections between disease-causing genes improve our understanding of the molecular events originated by genetic disturbances. For this, we have built a pathophenotypic similarity gene network (PSGN) and compared it with the unipartite projections (based on gene-to-gene edges) similar to those used in previous network models (HDN and ODN). Unlike these disease network models, the PSGN uses semantic similarities. This pathophenotypic similarity has been calculated by comparing pathophenotypic annotations of genes (human abnormalities of HPO terms) in the "Human Phenotype Ontology". The resulting network contains 1075 genes (nodes) and 26197 significant pathophenotypic similarities (edges). A global analysis of this network reveals: unnoticed pairs of genes showing significant pathophenotypic similarity, a biological meaningful re-arrangement of the pathological relationships between genes, correlations of biochemical interactions with higher similarity scores and functional biases in metabolic and essential genes toward the pathophenotypic specificity and the pleiotropy, respectively. Additionally, pathophenotypic similarities and metabolic interactions of genes associated with maple syrup urine disease (MSUD) have been used to merge into a coherent pathological module.Our results indicate that pathophenotypes contribute to identify underlying co-dependencies among disease-causing genes that are useful to describe disease modularity. PMID:23437198

  1. Integrated Analyses of Gene Expression Profiles Digs out Common Markers for Rheumatic Diseases

    PubMed Central

    Wang, Lan; Wu, Long-Fei; Lu, Xin; Mo, Xing-Bo; Tang, Zai-Xiang; Lei, Shu-Feng; Deng, Fei-Yan

    2015-01-01

    Objective Rheumatic diseases have some common symptoms. Extensive gene expression studies, accumulated thus far, have successfully identified signature molecules for each rheumatic disease, individually. However, whether there exist shared factors across rheumatic diseases has yet to be tested. Methods We collected and utilized 6 public microarray datasets covering 4 types of representative rheumatic diseases including rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, and osteoarthritis. Then we detected overlaps of differentially expressed genes across datasets and performed a meta-analysis aiming at identifying common differentially expressed genes that discriminate between pathological cases and normal controls. To further gain insights into the functions of the identified common differentially expressed genes, we conducted gene ontology enrichment analysis and protein-protein interaction analysis. Results We identified a total of eight differentially expressed genes (TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, PRF1), each associated with at least 3 of the 4 studied rheumatic diseases. Meta-analysis warranted the significance of the eight genes and highlighted the general significance of four genes (CX3CR1, LY96, TLR5, and PRF1). Protein-protein interaction and gene ontology enrichment analyses indicated that the eight genes interact with each other to exert functions related to immune response and immune regulation. Conclusion The findings support that there exist common factors underlying rheumatic diseases. For rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and osteoarthritis diseases, those common factors include TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, and PRF1. In-depth studies on these common factors may provide keys to understanding the pathogenesis and developing intervention strategies for rheumatic diseases. PMID:26352601

  2. New Genes and New Insights from Old Genes: Update on Alzheimer Disease

    PubMed Central

    Ringman, John M.; Coppola, Giovanni

    2013-01-01

    Purpose of Review: This article discusses the current status of knowledge regarding the genetic basis of Alzheimer disease (AD) with a focus on clinically relevant aspects. Recent Findings: The genetic architecture of AD is complex, as it includes multiple susceptibility genes and likely nongenetic factors. Rare but highly penetrant autosomal dominant mutations explain a small minority of the cases but have allowed tremendous advances in understanding disease pathogenesis. The identification of a strong genetic risk factor, APOE, reshaped the field and introduced the notion of genetic risk for AD. More recently, large-scale genome-wide association studies are adding to the picture a number of common variants with very small effect sizes. Large-scale resequencing studies are expected to identify additional risk factors, including rare susceptibility variants and structural variation. Summary: Genetic assessment is currently of limited utility in clinical practice because of the low frequency (Mendelian mutations) or small effect size (common risk factors) of the currently known susceptibility genes. However, genetic studies are identifying with confidence a number of novel risk genes, and this will further our understanding of disease biology and possibly the identification of therapeutic targets. PMID:23558482

  3. Identifying Host Genetic Risk Factors in the Context of Public Health Surveillance for Invasive Pneumococcal Disease

    PubMed Central

    Zimmer, Shanta M.; Lynfield, Ruth; McNicholl, Janet M.; Messonnier, Nancy E.; Whitney, Cynthia G.; Crawford, Dana C.

    2011-01-01

    Host genetic factors that modify risk of pneumococcal disease may help target future public health interventions to individuals at highest risk of disease. We linked data from population-based surveillance for invasive pneumococcal disease (IPD) with state-based newborn dried bloodspot repositories to identify biological samples from individuals who developed invasive pneumococcal disease. Genomic DNA was extracted from 366 case and 732 anonymous control samples. TagSNPs were selected in 34 candidate genes thought to be associated with host response to invasive pneumococcal disease, and a total of 326 variants were successfully genotyped. Among 543 European Americans (EA) (182 cases and 361 controls), and 166 African Americans (AA) (53 cases and 113 controls), common variants in surfactant protein D (SFTPD) are consistently underrepresented in IPD. SFTPD variants with the strongest association for IPD are intronic rs17886286 (allelic OR 0.45, 95% confidence interval (CI) [0.25, 0.82], with p?=?0.007) in EA and 5? flanking rs12219080 (allelic OR 0.32, 95%CI [0.13, 0.78], with p?=?0.009) in AA. Variants in CD46 and IL1R1 are also associated with IPD in both EA and AA, but with effects in different directions; FAS, IL1B, IL4, IL10, IL12B, SFTPA1, SFTPB, and PTAFR variants are associated (p?0.05) with IPD in EA or AA. We conclude that variants in SFTPD may protect against IPD in EA and AA and genetic variation in other host response pathways may also contribute to risk of IPD. While our associations are not corrected for multiple comparisons and therefore must be replicated in additional cohorts, this pilot study underscores the feasibility of integrating public health surveillance with existing, prospectively collected, newborn dried blood spot repositories to identify host genetic factors associated with infectious diseases. PMID:21858107

  4. Validating GWAS-Identified Risk Loci for Alzheimer's Disease in Han Chinese Populations.

    PubMed

    Wang, Hui-Zhen; Bi, Rui; Hu, Qiu-Xiang; Xiang, Qun; Zhang, Chen; Zhang, Deng-Feng; Zhang, Wen; Ma, Xiaohong; Guo, Wanjun; Deng, Wei; Zhao, Liansheng; Ni, Peiyan; Li, Mingli; Fang, Yiru; Li, Tao; Yao, Yong-Gang

    2016-01-01

    In recent years, genome-wide association studies (GWASs) have identified many novel susceptible genes/loci for Alzheimer's disease (AD). However, most of these studies were conducted in European and populations of European origin, and limited studies have been performed in Han Chinese. In this study, we genotyped 14 single-nucleotide polymorphisms (SNPs) in eight GWAS-reported AD risk genes in 1509 individuals comprising two independent Han Chinese case-control cohorts. Four SNPs (rs11234495, rs592297, rs676733, and rs3851179) in the PICALM gene were significantly associated with late-onset (LO)-AD in populations from Southwest China, whereas SNPs rs744373 (BIN1), rs9331942 (CLU), and rs670139 (MS4A4E) were linked to LO-AD in populations from East China. In the combined Han Chinese population, positive associations were observed between PICALM, CLU, MS4A4E genes, and LO-AD. The association between rs3851179 (PICALM), rs744373 (BIN1), and AD was further confirmed by meta-analysis of Asian populations. Our study verified the association between PICALM, BIN1, CLU, and MS4A4E variants and AD susceptibility in Han Chinese populations. We also discerned some regional differences concerning AD susceptibility SNPs. PMID:25452228

  5. A multistep screening method to identify genes using evolutionary transcriptome of plants.

    PubMed

    Kim, Chang-Kug; Lim, Hye-Min; Na, Jong-Kuk; Choi, Ji-Weon; Sohn, Seong-Han; Park, Soo-Chul; Kim, Young-Hwan; Kim, Yong-Kab; Kim, Dool-Yi

    2014-01-01

    We introduced a multistep screening method to identify the genes in plants using microarrays and ribonucleic acid (RNA)-seq transcriptome data. Our method describes the process for identifying genes using the salt-tolerance response pathways of the potato (Solanum tuberosum) plant. Gene expression was analyzed using microarrays and RNA-seq experiments that examined three potato lines (high, intermediate, and low salt tolerance) under conditions of salt stress. We screened the orthologous genes and pathway genes involved in salinity-related biosynthetic pathways, and identified nine potato genes that were candidates for salinity-tolerance pathways. The nine genes were selected to characterize their phylogenetic reconstruction with homologous genes of Arabidopsis thaliana, and a Circos diagram was generated to understand the relationships among the selected genes. The involvement of the selected genes in salt-tolerance pathways was verified by reverse transcription polymerase chain reaction analysis. One candidate potato gene was selected for physiological validation by generating dehydration-responsive element-binding 1 (DREB1)-overexpressing transgenic potato plants. The DREB1 overexpression lines exhibited increased salt tolerance and plant growth when compared to that of the control. Although the nine genes identified by our multistep screening method require further characterization and validation, this study demonstrates the power of our screening strategy after the initial identification of genes using microarrays and RNA-seq experiments. PMID:24812480

  6. A search engine to identify pathway genes from expression data on multiple organisms

    PubMed Central

    Chen, Chunnuan; Weirauch, Matthew T; Powell, Corey C; Zambon, Alexander C; Stuart, Joshua M

    2007-01-01

    Background The completion of several genome projects showed that most genes have not yet been characterized, especially in multicellular organisms. Although most genes have unknown functions, a large collection of data is available describing their transcriptional activities under many different experimental conditions. In many cases, the coregulatation of a set of genes across a set of conditions can be used to infer roles for genes of unknown function. Results We developed a search engine, the Multiple-Species Gene Recommender (MSGR), which scans gene expression datasets from multiple organisms to identify genes that participate in a genetic pathway. The MSGR takes a query consisting of a list of genes that function together in a genetic pathway from one of six organisms: Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Arabidopsis thaliana, and Helicobacter pylori. Using a probabilistic method to merge searches, the MSGR identifies genes that are significantly coregulated with the query genes in one or more of those organisms. The MSGR achieves its highest accuracy for many human pathways when searches are combined across species. We describe specific examples in which new genes were identified to be involved in a neuromuscular signaling pathway and a cell-adhesion pathway. Conclusion The search engine can scan large collections of gene expression data for new genes that are significantly coregulated with a pathway of interest. By integrating searches across organisms, the MSGR can identify pathway members whose coregulation is either ancient or newly evolved. PMID:17477880

  7. Gene transcription abnormalities in canine atopic dermatitis and related human eosinophilic allergic diseases.

    PubMed

    Plager, Douglas A; Torres, Sheila M F; Koch, Sandra N; Kita, Hirohito

    2012-09-15

    Canine atopic dermatitis (AD) is clinically similar to human AD, implicating it as a useful model of human eosinophilic allergic disease. To identify cutaneous gene transcription changes in relatively early inflammation of canine AD, microarrays were used to monitor transcription in normal skin (n=13) and in acute lesional AD (ALAD) and nearby visibly nonlesional AD (NLAD) skin (n=13) from dogs. Scanning the putative abnormally transcribed genes, several potentially relevant genes, some abnormally transcribed in both NLAD and ALAD (e.g. IL6, NFAM1, MSRA, and SYK), were observed. Comparison for abnormally transcribed genes common to two related human diseases, human AD and asthmatic chronic rhinosinusitis with nasal polyps (aCRSwNP), further identified genes or gene sets likely relevant to eosinophilic allergic inflammation. These included: (1) genes associated with alternatively activated monocyte-derived cells, including members of the monocyte chemotactic protein (MCP) gene cluster, (2) members of the IL1 family gene cluster, (3) eosinophil-associated seven transmembrane receptor EMR1 and EMR3 genes, (4) interferon-inducible genes, and (5) keratin genes associated with hair and nail formation. Overall, numerous abnormally transcribed genes were observed only in canine AD; however, many others are common to related human eosinophilic allergic diseases and represent therapeutic targets testable in dogs with AD. PMID:22749291

  8. Exploiting CpG hypermutability to identify phenotypically significant variation within human protein-coding genes.

    PubMed

    Ying, Hua; Huttley, Gavin

    2011-01-01

    The CpG dinucleotide is disproportionately represented in human genetic variation due to the hypermutability of 5-methyl-cytosine (5mC). We exploit this hypermutability and a novel codon substitution model to identify candidate functionally important exonic nucleotides. Population genetic theory suggests that codon positions with high cross-species CpG frequency will derive from stronger purifying selection. Using the phylogeny-based maximum likelihood inference framework, we applied codon substitution models with context-dependent parameters to measure the mutagenic and selective processes affecting CpG dinucleotides within exonic sequence. The suitability of these models was validated on >2,000 protein coding genes from a naturally occurring biological control, four yeast species that do not methylate their DNA. As expected, our analyses of yeast revealed no evidence for an elevated CpG transition rate or for substitution suppression affecting CpG-containing codons. Our analyses of >12,000 protein-coding genes from four primate lineages confirm the systemic influence of 5mC hypermutability on the divergence of these genes. After adjusting for confounding influences of mutation and the properties of the encoded amino acids, we confirmed that CpG-containing codons are under greater purifying selection in primates. Genes with significant evidence of enhanced suppression of nonsynonymous CpG changes were also shown to be significantly enriched in Online Mendelian Inheritance in Man. We developed a method for ranking candidate phenotypically influential CpG positions in human genes. Application of this method indicates that of the ∼1 million exonic CpG dinucleotides within humans, ∼20% are strong candidates for both hypermutability and disease association. PMID:21398426

  9. Allelic Variants of Complement Genes Associated with Dense Deposit Disease

    PubMed Central

    Abrera-Abeleda, Maria Asuncion; Nishimura, Carla; Frees, Kathy; Jones, Michael; Maga, Tara; Katz, Louis M.; Zhang, Yuzhou

    2011-01-01

    The alternative pathway of the complement cascade plays a role in the pathogenesis of dense deposit disease (DDD). Deficiency of complement factor H and mutations in CFH associate with the development of DDD, but it is unknown whether allelic variants in other complement genes also associate with this disease. We studied patients with DDD and identified previously unreported sequence alterations in several genes in addition to allelic variants and haplotypes common to patients with DDD. We found that the likelihood of developing DDD increases with the presence of two or more risk alleles in CFH and C3. To determine the functional consequence of this finding, we measured the activity of the alternative pathway in serum samples from phenotypically normal controls genotyped for variants in CFH and C3. Alternative pathway activity was higher in the presence of variants associated with DDD. Taken together, these data confirm that DDD is a complex genetic disease and may provide targets for the development of disease-specific therapies. PMID:21784901

  10. Defining the Human Macula Transcriptome and Candidate Retinal Disease Genes UsingEyeSAGE

    PubMed Central

    Rickman, Catherine Bowes; Ebright, Jessica N.; Zavodni, Zachary J.; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P.; Wistow, Graeme; Boon, Kathy; Hauser, Michael A.

    2009-01-01

    Purpose To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Methods Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Results Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. Conclusions The EyeSAGE database, combining three different gene-profiling platforms including the authors’ multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions. PMID:16723438

  11. Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium.

    PubMed

    Hohman, Timothy J; Bush, William S; Jiang, Lan; Brown-Gentry, Kristin D; Torstenson, Eric S; Dudek, Scott M; Mukherjee, Shubhabrata; Naj, Adam; Kunkle, Brian W; Ritchie, Marylyn D; Martin, Eden R; Schellenberg, Gerard D; Mayeux, Richard; Farrer, Lindsay A; Pericak-Vance, Margaret A; Haines, Jonathan L; Thornton-Wells, Tricia A

    2016-02-01

    Late-onset Alzheimer disease (AD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance, and gene-gene interactions; however, the investigation of interactions in recent genome-wide association studies has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across 13 data sets from the Alzheimer Disease Genetics Consortium. Fifteen single nucleotide polymorphism (SNP)-SNP pairs within 3 gene-gene combinations were identified: SIRT1 × ABCB1, PSAP × PEBP4, and GRIN2B × ADRA1A. In addition, we extend a previously identified interaction from an endophenotype analysis between RYR3 × CACNA1C. Finally, post hoc gene expression analyses of the implicated SNPs further implicate SIRT1 and ABCB1, and implicate CDH23 which was most recently identified as an AD risk locus in an epigenetic analysis of AD. The observed interactions in this article highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis. PMID:26827652

  12. Identifying the Association Between Alzheimer's Disease and Parkinson's Disease Using Genome-Wide Association Studies and Protein-Protein Interaction Network.

    PubMed

    Liu, Guiyou; Bao, Xinjie; Jiang, Yongshuai; Liao, Mingzhi; Jiang, Qinghua; Feng, Rennan; Zhang, Liangcai; Ma, Guoda; Chen, Zugen; Wang, Guangyu; Wang, Renzhi; Zhao, Bin; Li, Keshen

    2015-12-01

    Alzheimer's disease (AD) and Parkinson's disease (PD) are the first and second most common neurodegenerative diseases in the elderly. Shared clinical and pathological features have been reported. Recent large-scale genome-wide association studies (GWAS) have been conducted and reported a number of AD and PD variants. Until now, the underlying genetic mechanisms for all these newly identified PD variants as well as the association between AD and PD are still unclear exactly. We think that PD variants may contribute to AD and PD by influence on brain gene expression. Here, we conducted a systems analysis using (1) AD and PD variants (P?identified by the published GWAS; (2) four brain expression GWAS datasets using expression quantitative trait loci from the cerebellum and temporal cortex; (3) large-scale AD GWAS from the Alzheimer Disease Genetics Consortium (ADGC); (4) a protein-protein interaction network. Our results indicated that PD variants around the 17q21 were associated with gene expression and suggestive AD risk. We also identified significant interaction among AD and PD susceptibility genes. We believe that our findings may explain the underlying genetic mechanisms for newly identified PD variants in PD and AD, as well as the association between AD and PD, which may be very useful for future genetic studies for both diseases. PMID:25370933

  13. Novel variants identified in methyl-CpG-binding domain genes in autistic individuals.

    PubMed

    Cukier, Holly N; Rabionet, Raquel; Konidari, Ioanna; Rayner-Evans, Melissa Y; Baltos, Mary L; Wright, Harry H; Abramson, Ruth K; Martin, Eden R; Cuccaro, Michael L; Pericak-Vance, Margaret A; Gilbert, John R

    2010-07-01

    Misregulation of the methyl-CpG-binding protein 2 (MECP2) gene has been found to cause a myriad of neurological disorders including autism, mental retardation, seizures, learning disabilities, and Rett syndrome. We hypothesized that mutations in other members of the methyl-CpG-binding domain (MBD) family may also cause autistic features in individuals. We evaluated 226 autistic individuals for alterations in the four genes most homologous to MECP2: MBD1, MBD2, MBD3, and MBD4. A total of 46 alterations were identified in the four genes, including ten missense changes and two deletions that alter coding sequence. Several are either unique to our autistic population or cosegregate with affected individuals within a family, suggesting a possible relation of these variations to disease etiology. Variants include a R23M alteration in two affected half brothers which falls within the MBD domain of the MBD3 protein, as well as a frameshift in MBD4 that is predicted to truncate almost half of the protein. These results suggest that rare cases of autism may be influenced by mutations in members of the dynamic MBD protein family. PMID:19921286

  14. Identifying rhesus macaque gene orthologs using heterospecific human CNV probes

    PubMed Central

    Ng, Jillian; Fass, Joseph N.; Durbin-Johnson, Blythe; Smith, David Glenn; Kanthaswamy, Sree

    2015-01-01

    We used the Affymetrix® Genome-Wide Human SNP Array 6.0 to identify heterospecific markers and compare copy number and structural genomic variation between humans and rhesus macaques. Over 200,000 human copy number variation (CNV) probes were mapped to a Chinese and an Indian rhesus macaque sample. Observed genomic rearrangements and synteny were in agreement with the results of a previously published genomic comparison between humans and rhesus macaques. Comparisons between each of the two rhesus macaques and humans yielded 206 regions with copy numbers that differed by at least two fold in the Indian rhesus macaque and human, 32 in the Chinese rhesus macaque and human, and 147 in both rhesus macaques. The detailed genomic map and preliminary CNV data are useful for better understanding genetic variation in rhesus macaques, identifying derived changes in human CNVs that may have evolved by selection, and determining the suitability of rhesus macaques as human models for particular biomedical studies. PMID:26697375

  15. Identifying rhesus macaque gene orthologs using heterospecific human CNV probes.

    PubMed

    Ng, Jillian; Fass, Joseph N; Durbin-Johnson, Blythe; Smith, David Glenn; Kanthaswamy, Sree

    2015-12-01

    We used the Affymetrix(®) Genome-Wide Human SNP Array 6.0 to identify heterospecific markers and compare copy number and structural genomic variation between humans and rhesus macaques. Over 200,000 human copy number variation (CNV) probes were mapped to a Chinese and an Indian rhesus macaque sample. Observed genomic rearrangements and synteny were in agreement with the results of a previously published genomic comparison between humans and rhesus macaques. Comparisons between each of the two rhesus macaques and humans yielded 206 regions with copy numbers that differed by at least two fold in the Indian rhesus macaque and human, 32 in the Chinese rhesus macaque and human, and 147 in both rhesus macaques. The detailed genomic map and preliminary CNV data are useful for better understanding genetic variation in rhesus macaques, identifying derived changes in human CNVs that may have evolved by selection, and determining the suitability of rhesus macaques as human models for particular biomedical studies. PMID:26697375

  16. With current gene markers, presymptomatic diagnosis of heritable disease is still a family affair

    SciTech Connect

    Not Available

    1987-09-04

    In the last four years, genes or genetic markers have been identified for a host of disorders including Huntington's disease, cystic fibrosis, Duchenne muscular dystrophy, polycystic kidney disease, bipolar depressive disorder, retinoblastoma, Alzheimer's disease, and schizophrenia. Such discoveries have made it possible to diagnose in utero some 30 genetic diseases during the first trimester of pregnancy. Yet, while these newly discovered gene markers may be revolutionizing prenatal and presymptomatic diagnosis, they are in many respects halfway technology. Such was the opinion of several speakers at a conference sponsored by the American Medical Association in Washington, DC. At the conference, entitled DNA Probes in the Practice of Medicine, geneticists emphasized that gene markers - stretches of DNA that are usually inherited in tandem with a disease gene - are usually not sufficient for presymptomatic diagnosis of genetic disease in an individual.

  17. Differences in Gene-Gene Interactions in Graves’ Disease Patients Stratified by Age of Onset

    PubMed Central

    Jurecka-Lubieniecka, Beata; Bednarczuk, Tomasz; Ploski, Rafal; Krajewska, Jolanta; Kula, Dorota; Kowalska, Malgorzata; Tukiendorf, Andrzej; Kolosza, Zofia; Jarzab, Barbara

    2016-01-01

    Background Graves’ disease (GD) is a complex disease in which genetic predisposition is modified by environmental factors. Each gene exerts limited effects on the development of autoimmune disease (OR = 1.2–1.5). An epidemiological study revealed that nearly 70% of the risk of developing inherited autoimmunological thyroid diseases (AITD) is the result of gene interactions. In the present study, we analyzed the effects of the interactions of multiple loci on the genetic predisposition to GD. The aim of our analyses was to identify pairs of genes that exhibit a multiplicative interaction effect. Material and Methods A total of 709 patients with GD were included in the study. The patients were stratified into more homogeneous groups depending on the age at time of GD onset: younger patients less than 30 years of age and older patients greater than 30 years of age. Association analyses were performed for genes that influence the development of GD: HLADRB1, PTPN22, CTLA4 and TSHR. The interactions among polymorphisms were analyzed using the multiple logistic regression and multifactor dimensionality reduction (MDR) methods. Results GD patients stratified by the age of onset differed in the allele frequencies of the HLADRB1*03 and 1858T polymorphisms of the PTPN22 gene (OR = 1.7, p = 0.003; OR = 1.49, p = 0.01, respectively). We evaluated the genetic interactions of four SNPs in a pairwise fashion with regard to disease risk. The coexistence of HLADRB1 with CTLA4 or HLADRB1 with PTPN22 exhibited interactions on more than additive levels (OR = 3.64, p = 0.002; OR = 4.20, p < 0.001, respectively). These results suggest that interactions between these pairs of genes contribute to the development of GD. MDR analysis confirmed these interactions. Conclusion In contrast to a single gene effect, we observed that interactions between the HLADRB1/PTPN22 and HLADRB1/CTLA4 genes more closely predicted the risk of GD onset in young patients. PMID:26943356

  18. Metabolic disruption identified in the Huntington's disease transgenic sheep model.

    PubMed

    Handley, Renee R; Reid, Suzanne J; Patassini, Stefano; Rudiger, Skye R; Obolonkin, Vladimir; McLaughlan, Clive J; Jacobsen, Jessie C; Gusella, James F; MacDonald, Marcy E; Waldvogel, Henry J; Bawden, C Simon; Faull, Richard L M; Snell, Russell G

    2016-01-01

    Huntington's disease (HD) is a dominantly inherited, progressive neurodegenerative disorder caused by a CAG repeat expansion within exon 1 of HTT, encoding huntingtin. There are no therapies that can delay the progression of this devastating disease. One feature of HD that may play a critical role in its pathogenesis is metabolic disruption. Consequently, we undertook a comparative study of metabolites in our transgenic sheep model of HD (OVT73). This model does not display overt symptoms of HD but has circadian rhythm alterations and molecular changes characteristic of the early phase disease. Quantitative metabolite profiles were generated from the motor cortex, hippocampus, cerebellum and liver tissue of 5 year old transgenic sheep and matched controls by gas chromatography-mass spectrometry. Differentially abundant metabolites were evident in the cerebellum and liver. There was striking tissue-specificity, with predominantly amino acids affected in the transgenic cerebellum and fatty acids in the transgenic liver, which together may indicate a hyper-metabolic state. Furthermore, there were more strong pair-wise correlations of metabolite abundance in transgenic than in wild-type cerebellum and liver, suggesting altered metabolic constraints. Together these differences indicate a metabolic disruption in the sheep model of HD and could provide insight into the presymptomatic human disease. PMID:26864449

  19. Harnessing genomics to identify environmental determinants of heritable disease

    EPA Science Inventory

    De novo mutation is increasingly being recognized as the cause for a range of human genetic diseases and disorders. Important examples of this include inherited genetic disorders such as autism, schizophrenia, mental retardation, epilepsy, and a broad range of adverse reproductiv...

  20. The use of Random Homozygous Gene Perturbation to identify novel host-oriented targets for influenza.

    PubMed

    Sui, Baoquan; Bamba, Douty; Weng, Ke; Ung, Huong; Chang, Shaojing; Van Dyke, Jessica; Goldblatt, Michael; Duan, Roxanne; Kinch, Michael S; Li, Wu-Bo

    2009-05-10

    Conventional approaches for therapeutic targeting of viral pathogens have consistently faced obstacles arising from the development of resistant strains and a lack of broad-spectrum application. Influenza represents a particularly problematic therapeutic challenge since high viral mutation rates have often confounded many conventional antivirals. Newly emerging or engineered strains of influenza represent an even greater threat as typified by recent interest in avian subtypes of influenza. Based on the limitations associated with targeting virally-encoded molecules, we have taken an orthogonal approach of targeting host pathways in a manner that prevents viral propagation or spares the host from virus-mediated pathogenicity. To this end, we report herein the application of an improved technology for target discovery, Random Homozygous Gene Perturbation (RHGP), to identify host-oriented targets that are well-tolerated in normal cells but that prevent influenza-mediated killing of host cells. Improvements in RHGP facilitated a thorough screening of the entire genome, both for overexpression or loss of expression, to identify targets that render host cells resistant to influenza infection. We identify a set of host-oriented targets that prevent influenza killing of host cells and validate these targets using multiple approaches. These studies provide further support for a new paradigm to combat viral disease and demonstrate the power of RHGP to identify novel targets and mechanisms. PMID:19327807

  1. Rapid-Throughput Skeletal Phenotyping of 100 Knockout Mice Identifies 9 New Genes That Determine Bone Strength

    PubMed Central

    Gogakos, Apostolos; White, Jacqueline K.; Evans, Holly; Jacques, Richard M.; van der Spek, Anne H.; Ramirez-Solis, Ramiro; Ryder, Edward; Sunter, David; Boyde, Alan; Campbell, Michael J.

    2012-01-01

    Osteoporosis is a common polygenic disease and global healthcare priority but its genetic basis remains largely unknown. We report a high-throughput multi-parameter phenotype screen to identify functionally significant skeletal phenotypes in mice generated by the Wellcome Trust Sanger Institute Mouse Genetics Project and discover novel genes that may be involved in the pathogenesis of osteoporosis. The integrated use of primary phenotype data with quantitative x-ray microradiography, micro-computed tomography, statistical approaches and biomechanical testing in 100 unselected knockout mouse strains identified nine new genetic determinants of bone mass and strength. These nine new genes include five whose deletion results in low bone mass and four whose deletion results in high bone mass. None of the nine genes have been implicated previously in skeletal disorders and detailed analysis of the biomechanical consequences of their deletion revealed a novel functional classification of bone structure and strength. The organ-specific and disease-focused strategy described in this study can be applied to any biological system or tractable polygenic disease, thus providing a general basis to define gene function in a system-specific manner. Application of the approach to diseases affecting other physiological systems will help to realize the full potential of the International Mouse Phenotyping Consortium. PMID:22876197

  2. Rhesus monkey model of liver disease reflecting clinical disease progression and hepatic gene expression analysis

    PubMed Central

    Wang, Hong; Tan, Tao; Wang, Junfeng; Niu, Yuyu; Yan, Yaping; Guo, Xiangyu; Kang, Yu; Duan, Yanchao; Chang, Shaohui; Liao, Jianpeng; Si, Chenyang; Ji, Weizhi; Si, Wei

    2015-01-01

    Alcoholic liver disease (ALD) is a significant public health issue with heavy medical and economic burdens. The aetiology of ALD is not yet completely understood. The development of drugs and therapies for ALD is hampered by a lack of suitable animal models that replicate both the histological and metabolic features of human ALD. Here, we characterize a rhesus monkey model of alcohol-induced liver steatosis and hepatic fibrosis that is compatible with the clinical progression of the biochemistry and pathology in humans with ALD. Microarray analysis of hepatic gene expression was conducted to identify potential molecular signatures of ALD progression. The up-regulation of expression of hepatic genes related to liver steatosis (CPT1A, FASN, LEPR, RXRA, IGFBP1, PPARGC1A and SLC2A4) was detected in our rhesus model, as was the down-regulation of such genes (CYP7A1, HMGCR, GCK and PNPLA3) and the up-regulation of expression of hepatic genes related to liver cancer (E2F1, OPCML, FZD7, IGFBP1 and LEF1). Our results demonstrate that this ALD model reflects the clinical disease progression and hepatic gene expression observed in humans. These findings will be useful for increasing the understanding of ALD pathogenesis and will benefit the development of new therapeutic procedures and pharmacological reagents for treating ALD. PMID:26442469

  3. Expression of coordinately regulated defense response genes and analysis of their role in disease resistance in Medicago truncatula

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarray technology was used to identify genes associated with disease defense responses in the model legume Medicago truncatula. Transcript profiles from leaves inoculated with Colletotrichum trifolii and Erysiphe pisi and roots infected with Phytophthora medicaginis were compared to identify gen...

  4. Gene Therapy May Offer Hope for 'Bubble Boy' Disease

    MedlinePlus

    ... html Gene Therapy May Offer Hope for 'Bubble Boy' Disease Preliminary research tries new approach to rebuild ... therapy shows preliminary promise against so-called "Bubble Boy" disease, researchers report. A small, early-stage trial ...

  5. Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases.

    PubMed

    Greene, Daniel; Richardson, Sylvia; Turro, Ernest

    2016-03-01

    Rare genetic disorders, which can now be studied systematically with affordable genome sequencing, are often caused by high-penetrance rare variants. Such disorders are often heterogeneous and characterized by abnormalities spanning multiple organ systems ascertained with variable clinical precision. Existing methods for identifying genes with variants responsible for rare diseases summarize phenotypes with unstructured binary or quantitative variables. The Human Phenotype Ontology (HPO) allows composite phenotypes to be represented systematically but association methods accounting for the ontological relationship between HPO terms do not exist. We present a Bayesian method to model the association between an HPO-coded patient phenotype and genotype. Our method estimates the probability of an association together with an HPO-coded phenotype characteristic of the disease. We thus formalize a clinical approach to phenotyping that is lacking in standard regression techniques for rare disease research. We demonstrate the power of our method by uncovering a number of true associations in a large collection of genome-sequenced and HPO-coded cases with rare diseases. PMID:26924528

  6. Gene therapy for cardiovascular manifestations of lysosomal storage diseases

    PubMed Central

    Sleeper, Meg M.; Haskins, Mark E.; Ponder, Katherine P.

    2012-01-01

    Cardiac disease causes morbidity in several lysosomal storage diseases, which are the result of deficient activity of lysosomal enzymes. Mucopolysaccharidosis (MPS) causes aortic and valvular disease, Pompe disease causes cardiac muscle weakness, and Fabry disease causes left ventricular hypertrophy. Enzyme replacement therapy involves intravenous injection of enzyme modified with mannose 6-phosphate, which can be taken up by cells, and is currently approved for some lysosomal storage diseases. Gene therapy can result in secretion of mannose 6-phosphate-modified enzyme into blood, from where it can; similarly, be taken up by cells. Gene therapy has been effective in animal models of lysosomal storage disease, and holds great promise. PMID:26937225

  7. Family-based analysis identified CD2 as a susceptibility gene for primary open angle glaucoma in Chinese Han population

    PubMed Central

    Liu, Ting; Xie, Lin; Ye, Jian; He, Xiangge

    2014-01-01

    Primary open angle glaucoma (POAG) is characterized by optic disc cupping and irreversible loss of retinal ganglion cells. Few genes have been detected that influence POAG susceptibility and little is known about its genetic architecture. In this study, we employed exome sequencing on three members from a high frequency POAG family to identify the risk factors of POAG in Chinese population. Text-mining method was applied to identify genes associated with glaucoma in literature, and protein–protein interaction networks were constructed. Furthermore, reverse transcription PCR and Western blot were performed to confirm the differential gene expression. Six genes, baculoviral inhibitors of apoptosis protein repeat containing 6 (BIRC6), CD2, luteinizing hormone/choriogonadotropin receptor (LHCGR), polycystic kidney and hepatic disease gene 1 (PKHD1), phenylalanine hydroxylase (PAH) and fucosyltransferase 7 (FUT7), which might be associated with POAG, were identified. Both the mRNA expression levels and protein expression levels of HSP27 were increased in astrocytes from POAG patients compared with those from normal control, suggesting that mutation in CD2 might pose a risk for POAG in Chinese population. In conclusion, novel rare variants detected by exome sequencing may hold the key to unravelling the remaining contribution of genetics to complex diseases such as POAG. PMID:24597656

  8. Identifying Essential Streptococcus sanguinis Genes Using Genome-Wide Deletion Mutation

    PubMed Central

    Chen, Lei; Ge, Xiuchun; Xu, Ping

    2016-01-01

    Essential genes in pathogens are important for the development of antibacterial drugs. In this report, we described a protocol to identify essential genes in the Streptococcus sanguinis SK36 strain using genome-wide deletion mutation. A fusion PCR-based method is used to construct gene deletion fragments, which contain kanamycin resistance cassettes with two flanking arms of DNA upstream and downstream of the target gene. The linear fused PCR amplicons were transformed into S. sanguinis SK36 cells. No kanamycin-resistant transformants suggested the gene essentiality because the deletion of the essential gene renders a lethal phenotype of the transformants. The putative essential genes were further confirmed by independent transformations up to five attempts. The false nonessential genes were also identified by removing double-band mutants. PMID:25636610

  9. AN MHC class I immune evasion gene of Marek's disease virus

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek's disease virus (MDV) is a widespread a-herpesvirus of chickens that causes T cell tumors. Acute, but not latent, MDV infection has previously been shown to lead to downregulation of cell-surface MHC class I (Virology 282:198–205 (2001)), but the gene(s) involved have not been identified. Here...

  10. Identification of genes conferring genetic resistance to Marek’s disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic resistance to Marek’s disease (MD) is complex and controlled by many genes with the majority having small effect making them difficult to detect. Thus, to identify specific genes, we have been employing and integrating a variety of genomic and functional genomic approaches that capitalize on...

  11. Identification of Candidate Genes in Rice for Resistance to Sheath Blight Disease by Whole Genome Sequencing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent advances in whole genome sequencing have allowed identification of genes for disease susceptibility in humans. The objective of our research was to exploit whole genome sequences of 13 rice (Oryza sativa L.) inbred lines to identify non-synonymous SNPs (nsSNPs) and candidate genes for resista...

  12. Using registries to identify adverse events in rheumatic diseases.

    PubMed

    Lionetti, Geraldina; Kimura, Yukiko; Schanberg, Laura E; Beukelman, Timothy; Wallace, Carol A; Ilowite, Norman T; Winsor, Jane; Fox, Kathleen; Natter, Marc; Sundy, John S; Brodsky, Eric; Curtis, Jeffrey R; Del Gaizo, Vincent; Iyasu, Solomon; Jahreis, Angelika; Meeker-O'Connell, Ann; Mittleman, Barbara B; Murphy, Bernard M; Peterson, Eric D; Raymond, Sandra C; Setoguchi, Soko; Siegel, Jeffrey N; Sobel, Rachel E; Solomon, Daniel; Southwood, Taunton R; Vesely, Richard; White, Patience H; Wulffraat, Nico M; Sandborg, Christy I

    2013-11-01

    The proven effectiveness of biologics and other immunomodulatory products in inflammatory rheumatic diseases has resulted in their widespread use as well as reports of potential short- and long-term complications such as infection and malignancy. These complications are especially worrisome in children who often have serial exposures to multiple immunomodulatory products. Post-marketing surveillance of immunomodulatory products in juvenile idiopathic arthritis (JIA) and pediatric systemic lupus erythematosus is currently based on product-specific registries and passive surveillance, which may not accurately reflect the safety risks for children owing to low numbers, poor long-term retention, and inadequate comparators. In collaboration with the US Food and Drug Administration (FDA), patient and family advocacy groups, biopharmaceutical industry representatives and other stakeholders, the Childhood Arthritis and Rheumatology Research Alliance (CARRA) and the Duke Clinical Research Institute (DCRI) have developed a novel pharmacosurveillance model (CARRA Consolidated Safety Registry [CoRe]) based on a multicenter longitudinal pediatric rheumatic diseases registry with over 8000 participants. The existing CARRA infrastructure provides access to much larger numbers of subjects than is feasible in single-product registries. Enrollment regardless of medication exposure allows more accurate detection and evaluation of safety signals. Flexibility built into the model allows the addition of specific data elements and safety outcomes, and designation of appropriate disease comparator groups relevant to each product, fulfilling post-marketing requirements and commitments. The proposed model can be applied to other pediatric and adult diseases, potentially transforming the paradigm of pharmacosurveillance in response to the growing public mandate for rigorous post-marketing safety monitoring. PMID:24144710

  13. Using Registries to Identify Adverse Events in Rheumatic Diseases

    PubMed Central

    Lionetti, Geraldina; Kimura, Yukiko; Schanberg, Laura E.; Beukelman, Timothy; Wallace, Carol A.; Ilowite, Norman T.; Winsor, Jane; Fox, Kathleen; Natter, Marc; Sundy, John S.; Brodsky, Eric; Curtis, Jeffrey R.; Del Gaizo, Vincent; Iyasu, Solomon; Jahreis, Angelika; Meeker-O’Connell, Ann; Mittleman, Barbara B.; Murphy, Bernard M.; Peterson, Eric D.; Raymond, Sandra C.; Setoguchi, Soko; Siegel, Jeffrey N.; Sobel, Rachel E.; Solomon, Daniel; Southwood, Taunton R.; Vesely, Richard; White, Patience H.; Wulffraat, Nico M.; Sandborg, Christy I.

    2013-01-01

    The proven effectiveness of biologics and other immunomodulatory products in inflammatory rheumatic diseases has resulted in their widespread use as well as reports of potential short- and long-term complications such as infection and malignancy. These complications are especially worrisome in children who often have serial exposures to multiple immunomodulatory products. Post-marketing surveillance of immunomodulatory products in juvenile idiopathic arthritis (JIA) and pediatric systemic lupus erythematosus is currently based on product-specific registries and passive surveillance, which may not accurately reflect the safety risks for children owing to low numbers, poor long-term retention, and inadequate comparators. In collaboration with the US Food and Drug Administration (FDA), patient and family advocacy groups, biopharmaceutical industry representatives and other stakeholders, the Childhood Arthritis and Rheumatology Research Alliance (CARRA) and the Duke Clinical Research Institute (DCRI) have developed a novel pharmacosurveillance model (CARRA Consolidated Safety Registry [CoRe]) based on a multicenter longitudinal pediatric rheumatic diseases registry with over 8000 participants. The existing CARRA infrastructure provides access to much larger numbers of subjects than is feasible in single-product registries. Enrollment regardless of medication exposure allows more accurate detection and evaluation of safety signals. Flexibility built into the model allows the addition of specific data elements and safety outcomes, and designation of appropriate disease comparator groups relevant to each product, fulfilling post-marketing requirements and commitments. The proposed model can be applied to other pediatric and adult diseases, potentially transforming the paradigm of pharmacosurveillance in response to the growing public mandate for rigorous post-marketing safety monitoring. PMID:24144710

  14. Loci influencing blood pressure identified using a cardiovascular gene-centric array.

    PubMed

    Ganesh, Santhi K; Tragante, Vinicius; Guo, Wei; Guo, Yiran; Lanktree, Matthew B; Smith, Erin N; Johnson, Toby; Castillo, Berta Almoguera; Barnard, John; Baumert, Jens; Chang, Yen-Pei Christy; Elbers, Clara C; Farrall, Martin; Fischer, Mary E; Franceschini, Nora; Gaunt, Tom R; Gho, Johannes M I H; Gieger, Christian; Gong, Yan; Isaacs, Aaron; Kleber, Marcus E; Mateo Leach, Irene; McDonough, Caitrin W; Meijs, Matthijs F L; Mellander, Olle; Molony, Cliona M; Nolte, Ilja M; Padmanabhan, Sandosh; Price, Tom S; Rajagopalan, Ramakrishnan; Shaffer, Jonathan; Shah, Sonia; Shen, Haiqing; Soranzo, Nicole; van der Most, Peter J; Van Iperen, Erik P A; Van Setten, Jessica; Van Setten, Jessic A; Vonk, Judith M; Zhang, Li; Beitelshees, Amber L; Berenson, Gerald S; Bhatt, Deepak L; Boer, Jolanda M A; Boerwinkle, Eric; Burkley, Ben; Burt, Amber; Chakravarti, Aravinda; Chen, Wei; Cooper-Dehoff, Rhonda M; Curtis, Sean P; Dreisbach, Albert; Duggan, David; Ehret, Georg B; Fabsitz, Richard R; Fornage, Myriam; Fox, Ervin; Furlong, Clement E; Gansevoort, Ron T; Hofker, Marten H; Hovingh, G Kees; Kirkland, Susan A; Kottke-Marchant, Kandice; Kutlar, Abdullah; Lacroix, Andrea Z; Langaee, Taimour Y; Li, Yun R; Lin, Honghuang; Liu, Kiang; Maiwald, Steffi; Malik, Rainer; Murugesan, Gurunathan; Newton-Cheh, Christopher; O'Connell, Jeffery R; Onland-Moret, N Charlotte; Ouwehand, Willem H; Palmas, Walter; Penninx, Brenda W; Pepine, Carl J; Pettinger, Mary; Polak, Joseph F; Ramachandran, Vasan S; Ranchalis, Jane; Redline, Susan; Ridker, Paul M; Rose, Lynda M; Scharnag, Hubert; Schork, Nicholas J; Shimbo, Daichi; Shuldiner, Alan R; Srinivasan, Sathanur R; Stolk, Ronald P; Taylor, Herman A; Thorand, Barbara; Trip, Mieke D; van Duijn, Cornelia M; Verschuren, W Monique; Wijmenga, Cisca; Winkelmann, Bernhard R; Wyatt, Sharon; Young, J Hunter; Boehm, Bernhard O; Caulfield, Mark J; Chasman, Daniel I; Davidson, Karina W; Doevendans, Pieter A; Fitzgerald, Garret A; Gums, John G; Hakonarson, Hakon; Hillege, Hans L; Illig, Thomas; Jarvik, Gail P; Johnson, Julie A; Kastelein, John J P; Koenig, Wolfgang; März, Winfried; Mitchell, Braxton D; Murray, Sarah S; Oldehinkel, Albertine J; Rader, Daniel J; Reilly, Muredach P; Reiner, Alex P; Schadt, Eric E; Silverstein, Roy L; Snieder, Harold; Stanton, Alice V; Uitterlinden, André G; van der Harst, Pim; van der Schouw, Yvonne T; Samani, Nilesh J; Johnson, Andrew D; Munroe, Patricia B; de Bakker, Paul I W; Zhu, Xiaofeng; Levy, Daniel; Keating, Brendan J; Asselbergs, Folkert W

    2013-04-15

    Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10(-6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention. PMID:23303523

  15. Loci influencing blood pressure identified using a cardiovascular gene-centric array

    PubMed Central

    Ganesh, Santhi K.; Tragante, Vinicius; Guo, Wei; Guo, Yiran; Lanktree, Matthew B.; Smith, Erin N.; Johnson, Toby; Castillo, Berta Almoguera; Barnard, John; Baumert, Jens; Chang, Yen-Pei Christy; Elbers, Clara C.; Farrall, Martin; Fischer, Mary E.; Franceschini, Nora; Gaunt, Tom R.; Gho, Johannes M.I.H.; Gieger, Christian; Gong, Yan; Isaacs, Aaron; Kleber, Marcus E.; Leach, Irene Mateo; McDonough, Caitrin W.; Meijs, Matthijs F.L.; Mellander, Olle; Molony, Cliona M.; Nolte, Ilja M.; Padmanabhan, Sandosh; Price, Tom S.; Rajagopalan, Ramakrishnan; Shaffer, Jonathan; Shah, Sonia; Shen, Haiqing; Soranzo, Nicole; van der Most, Peter J.; Van Iperen, Erik P.A.; Van Setten, Jessic A.; Vonk, Judith M.; Zhang, Li; Beitelshees, Amber L.; Berenson, Gerald S.; Bhatt, Deepak L.; Boer, Jolanda M.A.; Boerwinkle, Eric; Burkley, Ben; Burt, Amber; Chakravarti, Aravinda; Chen, Wei; Cooper-DeHoff, Rhonda M.; Curtis, Sean P.; Dreisbach, Albert; Duggan, David; Ehret, Georg B.; Fabsitz, Richard R.; Fornage, Myriam; Fox, Ervin; Furlong, Clement E.; Gansevoort, Ron T.; Hofker, Marten H.; Hovingh, G. Kees; Kirkland, Susan A.; Kottke-Marchant, Kandice; Kutlar, Abdullah; LaCroix, Andrea Z.; Langaee, Taimour Y.; Li, Yun R.; Lin, Honghuang; Liu, Kiang; Maiwald, Steffi; Malik, Rainer; Murugesan, Gurunathan; Newton-Cheh, Christopher; O'Connell, Jeffery R.; Onland-Moret, N. Charlotte; Ouwehand, Willem H.; Palmas, Walter; Penninx, Brenda W.; Pepine, Carl J.; Pettinger, Mary; Polak, Joseph F.; Ramachandran, Vasan S.; Ranchalis, Jane; Redline, Susan; Ridker, Paul M.; Rose, Lynda M.; Scharnag, Hubert; Schork, Nicholas J.; Shimbo, Daichi; Shuldiner, Alan R.; Srinivasan, Sathanur R.; Stolk, Ronald P.; Taylor, Herman A.; Thorand, Barbara; Trip, Mieke D.; van Duijn, Cornelia M.; Verschuren, W. Monique; Wijmenga, Cisca; Winkelmann, Bernhard R.; Wyatt, Sharon; Young, J. Hunter; Boehm, Bernhard O.; Caulfield, Mark J.; Chasman, Daniel I.; Davidson, Karina W.; Doevendans, Pieter A.; FitzGerald, Garret A.; Gums, John G.; Hakonarson, Hakon; Hillege, Hans L.; Illig, Thomas; Jarvik, Gail P.; Johnson, Julie A.; Kastelein, John J.P.; Koenig, Wolfgang; März, Winfried; Mitchell, Braxton D.; Murray, Sarah S.; Oldehinkel, Albertine J.; Rader, Daniel J.; Reilly, Muredach P.; Reiner, Alex P.; Schadt, Eric E.; Silverstein, Roy L.; Snieder, Harold; Stanton, Alice V.; Uitterlinden, André G.; van der Harst, Pim; van der Schouw, Yvonne T.; Samani, Nilesh J.; Johnson, Andrew D.; Munroe, Patricia B.; de Bakker, Paul I.W.; Zhu, Xiaofeng; Levy, Daniel; Keating, Brendan J.; Asselbergs, Folkert W.

    2013-01-01

    Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10−6). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention. PMID:23303523

  16. Identifying subspace gene clusters from microarray data using low-rank representation.

    PubMed

    Cui, Yan; Zheng, Chun-Hou; Yang, Jian

    2013-01-01

    Identifying subspace gene clusters from the gene expression data is useful for discovering novel functional gene interactions. In this paper, we propose to use low-rank representation (LRR) to identify the subspace gene clusters from microarray data. LRR seeks the lowest-rank representation among all the candidates that can represent the genes as linear combinations of the bases in the dataset. The clusters can be extracted based on the block diagonal representation matrix obtained using LRR, and they can well capture the intrinsic patterns of genes with similar functions. Meanwhile, the parameter of LRR can balance the effect of noise so that the method is capable of extracting useful information from the data with high level of background noise. Compared with traditional methods, our approach can identify genes with similar functions yet without similar expression profiles. Also, it could assign one gene into different clusters. Moreover, our method is robust to the noise and can identify more biologically relevant gene clusters. When applied to three public datasets, the results show that the LRR based method is superior to existing methods for identifying subspace gene clusters. PMID:23527177

  17. Genetic association study identifies HSPB7 as a risk gene for idiopathic dilated cardiomyopathy.

    PubMed

    Stark, Klaus; Esslinger, Ulrike B; Reinhard, Wibke; Petrov, George; Winkler, Thomas; Komajda, Michel; Isnard, Richard; Charron, Philippe; Villard, Eric; Cambien, François; Tiret, Laurence; Aumont, Marie-Claude; Dubourg, Olivier; Trochu, Jean-Noël; Fauchier, Laurent; Degroote, Pascal; Richter, Anette; Maisch, Bernhard; Wichter, Thomas; Zollbrecht, Christa; Grassl, Martina; Schunkert, Heribert; Linsel-Nitschke, Patrick; Erdmann, Jeanette; Baumert, Jens; Illig, Thomas; Klopp, Norman; Wichmann, H-Erich; Meisinger, Christa; Koenig, Wolfgang; Lichtner, Peter; Meitinger, Thomas; Schillert, Arne; König, Inke R; Hetzer, Roland; Heid, Iris M; Regitz-Zagrosek, Vera; Hengstenberg, Christian

    2010-10-01

    Dilated cardiomyopathy (DCM) is a structural heart disease with strong genetic background. Monogenic forms of DCM are observed in families with mutations located mostly in genes encoding structural and sarcomeric proteins. However, strong evidence suggests that genetic factors also affect the susceptibility to idiopathic DCM. To identify risk alleles for non-familial forms of DCM, we carried out a case-control association study, genotyping 664 DCM cases and 1,874 population-based healthy controls from Germany using a 50K human cardiovascular disease bead chip covering more than 2,000 genes pre-selected for cardiovascular relevance. After quality control, 30,920 single nucleotide polymorphisms (SNP) were tested for association with the disease by logistic regression adjusted for gender, and results were genomic-control corrected. The analysis revealed a significant association between a SNP in HSPB7 gene (rs1739843, minor allele frequency 39%) and idiopathic DCM (p = 1.06 × 10⁻⁶, OR  = 0.67 [95% CI 0.57-0.79] for the minor allele T). Three more SNPs showed p < 2.21 × 10⁻⁵. De novo genotyping of these four SNPs was done in three independent case-control studies of idiopathic DCM. Association between SNP rs1739843 and DCM was significant in all replication samples: Germany (n =564, n = 981 controls, p = 2.07 × 10⁻³, OR = 0.79 [95% CI 0.67-0.92]), France 1 (n = 433 cases, n = 395 controls, p =3.73 × 10⁻³, OR  = 0.74 [95% CI 0.60-0.91]), and France 2 (n = 249 cases, n = 380 controls, p = 2.26 × 10⁻⁴, OR  = 0.63 [95% CI 0.50-0.81]). The combined analysis of all four studies including a total of n = 1,910 cases and n = 3,630 controls showed highly significant evidence for association between rs1739843 and idiopathic DCM (p = 5.28 × 10⁻¹³, OR= 0.72 [95% CI 0.65-0.78]). None of the other three SNPs showed significant results in the replication stage.This finding of the HSPB7 gene from a genetic search for idiopathic DCM using a large SNP panel underscores the influence of common polymorphisms on DCM susceptibility. PMID:20975947

  18. Genetic Association Study Identifies HSPB7 as a Risk Gene for Idiopathic Dilated Cardiomyopathy

    PubMed Central

    Stark, Klaus; Esslinger, Ulrike B.; Reinhard, Wibke; Petrov, George; Winkler, Thomas; Komajda, Michel; Isnard, Richard; Charron, Philippe; Villard, Eric; Cambien, François; Tiret, Laurence; Aumont, Marie-Claude; Dubourg, Olivier; Trochu, Jean-Noël; Fauchier, Laurent; DeGroote, Pascal; Richter, Anette; Maisch, Bernhard; Wichter, Thomas; Zollbrecht, Christa; Grassl, Martina; Schunkert, Heribert; Linsel-Nitschke, Patrick; Erdmann, Jeanette; Baumert, Jens; Illig, Thomas; Klopp, Norman; Wichmann, H.-Erich; Meisinger, Christa; Koenig, Wolfgang; Lichtner, Peter; Meitinger, Thomas; Schillert, Arne; König, Inke R.; Hetzer, Roland; Heid, Iris M.; Regitz-Zagrosek, Vera; Hengstenberg, Christian

    2010-01-01

    Dilated cardiomyopathy (DCM) is a structural heart disease with strong genetic background. Monogenic forms of DCM are observed in families with mutations located mostly in genes encoding structural and sarcomeric proteins. However, strong evidence suggests that genetic factors also affect the susceptibility to idiopathic DCM. To identify risk alleles for non-familial forms of DCM, we carried out a case-control association study, genotyping 664 DCM cases and 1,874 population-based healthy controls from Germany using a 50K human cardiovascular disease bead chip covering more than 2,000 genes pre-selected for cardiovascular relevance. After quality control, 30,920 single nucleotide polymorphisms (SNP) were tested for association with the disease by logistic regression adjusted for gender, and results were genomic-control corrected. The analysis revealed a significant association between a SNP in HSPB7 gene (rs1739843, minor allele frequency 39%) and idiopathic DCM (p = 1.06×10−6, OR = 0.67 [95% CI 0.57–0.79] for the minor allele T). Three more SNPs showed p < 2.21×10−5. De novo genotyping of these four SNPs was done in three independent case-control studies of idiopathic DCM. Association between SNP rs1739843 and DCM was significant in all replication samples: Germany (n = 564, n = 981 controls, p = 2.07×10−3, OR = 0.79 [95% CI 0.67–0.92]), France 1 (n = 433 cases, n = 395 controls, p = 3.73×10−3, OR = 0.74 [95% CI 0.60–0.91]), and France 2 (n = 249 cases, n = 380 controls, p = 2.26×10−4, OR = 0.63 [95% CI 0.50–0.81]). The combined analysis of all four studies including a total of n = 1,910 cases and n = 3,630 controls showed highly significant evidence for association between rs1739843 and idiopathic DCM (p = 5.28×10−13, OR = 0.72 [95% CI 0.65–0.78]). None of the other three SNPs showed significant results in the replication stage. This finding of the HSPB7 gene from a genetic search for idiopathic DCM using a large SNP panel underscores the influence of common polymorphisms on DCM susceptibility. PMID:20975947

  19. A GABBR2 gene variant modifies pathophysiology in Huntington's disease.

    PubMed

    Philpott, April L; Fitzgerald, Paul B; Bailey, Neil W; Churchyard, Andrew; Georgiou-Karistianis, Nellie; Cummins, Tarrant D R

    2016-05-01

    Striatal degeneration in Huntington's disease (HD) causes changes in cortico-subcortical pathways. Transcranial magnetic stimulation (TMS) is a valuable tool for assessing pathophysiology within these pathways, yet has had limited application in HD. As cortico-subcortical pathways are largely mediated by GABA and dopamine receptor genes, understanding how these genes modulate neurophysiology in HD may provide new insights into how underlying pathology maps onto clinical phenotype. Twenty-nine participants with HD underwent motor cortex stimulation, while corticospinal excitability, cortical inhibition and intracortical facilitation were indexed via peripheral electromyography. Single-nucleotide polymorphism mapping was performed across six genes that are known to modulate cortico-subcortical pathways (GABRA2, GABBR1, GABBR2, DRD1, DRD2, DRD4). Genetic associations with six TMS measures and age at onset were investigated. Our hierarchical multiple regression analysis, controlling for CAG and age, revealed that a GABBR2 variant, predicted to be disease-causative, was significantly associated with corticospinal excitability at corrected levels. A subsequent uncorrected exploratory analysis revealed associations between GABBR2, GABRA2 and DRD2 variants with TMS measures of corticospinal excitability and cortical inhibition in HD, as well as with age at onset. Our findings support the notion that uncovering genetic associations with pathophysiological measures and age at onset is an important way forward in terms of generating meaningful biomarkers with diagnostic and prognostic sensitivity, and identifying novel human-validated targets for future clinical trials. PMID:27033668

  20. Candidate gene associated with a mutation causing recessive polycystic kidney disease in mice

    SciTech Connect

    Moyer, J.H.; Lee-Tischler, M.J.; Kwon, H.Y.; Schrick, J.J. ); Avner, E.D.; Sweeney, W.E. ); Godfrey, V.L.; Cacheiro, N.L.A.; Woychik, R.P. ); Wilkinson, J.E. )

    1994-05-27

    A line of transgenic mice was generated that contains an insertional mutation causing a phenotype similar to human autosomal recessive polycystic kidney disease. Homozygotes displayed a complex phenotype that included bilateral polycystic kidneys and an unusual liver lesion. The mutant locus was cloned and characterized through use of the transgene as a molecular marker. Additionally, a candidate polycystic kidney disease (PKD) gene was identified whose structure and expression are directly associated with the mutant locus. A complementary DNA derived from this gene predicted a peptide containing a motif that was originally identified in several genes involved in cell cycle control.

  1. Human beta-galactosidase gene mutations in morquio B disease.

    PubMed Central

    Oshima, A; Yoshida, K; Shimmoto, M; Fukuhara, Y; Sakuraba, H; Suzuki, Y

    1991-01-01

    Three different beta-galactosidase gene mutations--a 273Trp----Leu (mutation F) in both families, 482Arg----His (mutation G) in one family, and 509Trp----Cys (mutation H) in the other family--were identified in three patients with Morquio B disease who were from two unrelated families. Restriction-site analysis using StuI, Nsp(7524)I or RsaI confirmed these mutations. In human fibroblasts, mutation F expressed as much as 8% of the normal allele's enzyme activity, but the other mutations expressed no detectable enzyme activity. We conclude that the unique clinical manifestations are specifically associated with mutation F, a common two-base substitution, in this disease. Images Figure 1 PMID:1928092

  2. Integrating microarrays into disease-gene identification strategies.

    PubMed

    Dobrin, Seth E; Stephan, Dietrich A

    2003-05-01

    Positional cloning represents one of the most successful paradigm shifts in identifying the underlying patho-mechanisms in human disease. While traditional discovery tools focused on identifying defects at the tissue or cellular level, positional cloning identifies the damaged region of the genome as the preliminary step. While a large number of inherited single gene disorders have been mapped using this approach, a bottleneck still exists in combing through the genomic interval, often millions of nucleotides in length, to identify the nucleotide changes which result in a defective protein and subsequent disease. Along with the recent unravelling of the human genetic code, the development of massively parallel tools, such as microarrays, represent an equally important step forward in unraveling pathogenic genome dysfunctions. There are many emerging variants on microarray technology, such as expression arrays, exon arrays, array-based comparative genomic hybridization and sequencing arrays. Several of these platforms, if used properly, can accelerate the positional cloning process. The proper use of the platform is driven by knowledge of the underlying molecular defect being searched for and the operating characteristics of the array. The resultant insight forms the basis for improved molecular diagnostics and novel therapeutic targets. PMID:12779011

  3. Differential Expression of Vitamin E and Selenium-Responsive Genes by Disease Severity in Chronic Obstructive Pulmonary Disease

    PubMed Central

    Agler, AH; Crystal, RG; Mezey, JG; Fuller, J; Gao, C; Hansen, JG; Cassano, PA

    2014-01-01

    Antioxidant nutritional status is hypothesized to influence chronic obstructive pulmonary disease (COPD) susceptibility and progression. Although past studies relate antioxidants to gene expression, there are no data in patients with COPD. This study investigated the hypothesis that antioxidant status is compromised in patients with COPD, and antioxidant-responsive genes differentially express in a similar pattern. Lung tissue samples from patients with COPD were assayed for vitamin E and gene expression. Selenium and vitamin E were assayed in corresponding plasma samples. Discovery based genome-wide expression analysis compared moderate, severe, and very severe COPD (GOLD II-IV) patients to mild and at-risk/normal (GOLD 0-I). Hypotheses-driven analyses assessed differential gene expression by disease severity for vitamin E-responsive and selenium-responsive genes. GOLD II-IV COPD patients had 30% lower lung tissue vitamin E levels compared to GOLD 0-I participants (p = 0.0082). No statistically significant genome-wide differences in expression by disease severity were identified. Hypothesis-driven analyses of 109 genes found 16 genes differentially expressed (padjusted<0.05) by disease severity including 6 selenium-responsive genes (range in fold-change -1.39 to 2.25), 6 vitamin E-responsive genes (fold-change -2.30 to 1.51), and 4 COPD-associated genes. Lung tissue vitamin E in patients with COPD was associated with disease severity and vitamin E-responsive genes were differentially expressed by disease severity. While nutritional status is hypothesized to contribute to COPD risk, and is of therapeutic interest, evidence to date is mainly observational. The findings reported herein are novel, and support a role of vitamin E in COPD progression. PMID:23875740

  4. Evolutionary dynamics of human autoimmune disease genes and malfunctioned immunological genes

    PubMed Central

    2012-01-01

    Background One of the main issues of molecular evolution is to divulge the principles in dictating the evolutionary rate differences among various gene classes. Immunological genes have received considerable attention in evolutionary biology as candidates for local adaptation and for studying functionally important polymorphisms. The normal structure and function of immunological genes will be distorted when they experience mutations leading to immunological dysfunctions. Results Here, we examined the fundamental differences between the genes which on mutation give rise to autoimmune or other immune system related diseases and the immunological genes that do not cause any disease phenotypes. Although the disease genes examined are analogous to non-disease genes in product, expression, function, and pathway affiliation, a statistically significant decrease in evolutionary rate has been found in autoimmune disease genes relative to all other immune related diseases and non-disease genes. Possible ways of accumulation of mutation in the three steps of the central dogma (DNA-mRNA-Protein) have been studied to trace the mutational effects predisposed to disease consequence and acquiring higher selection pressure. Principal Component Analysis and Multivariate Regression Analysis have established the predominant role of single nucleotide polymorphisms in guiding the evolutionary rate of immunological disease and non-disease genes followed by m-RNA abundance, paralogs number, fraction of phosphorylation residue, alternatively spliced exon, protein residue burial and protein disorder. Conclusions Our study provides an empirical insight into the etiology of autoimmune disease genes and other immunological diseases. The immediate utility of our study is to help in disease gene identification and may also help in medicinal improvement of immune related disease. PMID:22276655

  5. Mapping eQTLs in the Norfolk Island Genetic Isolate Identifies Candidate Genes for CVD Risk Traits

    PubMed Central

    Benton, Miles C.; Lea, Rod A.; Macartney-Coxson, Donia; Carless, Melanie A.; Göring, Harald H.; Bellis, Claire; Hanna, Michelle; Eccles, David; Chambers, Geoffrey K.; Curran, Joanne E.; Harper, Jacquie L.; Blangero, John; Griffiths, Lyn R.

    2013-01-01

    Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10−7) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations. PMID:24314549

  6. The influence of disease categories on gene candidate predictions from model organism phenotypes

    PubMed Central

    2014-01-01

    Background The molecular etiology is still to be identified for about half of the currently described Mendelian diseases in humans, thereby hindering efforts to find treatments or preventive measures. Advances, such as new sequencing technologies, have led to increasing amounts of data becoming available with which to address the problem of identifying disease genes. Therefore, automated methods are needed that reliably predict disease gene candidates based on available data. We have recently developed Exomiser as a tool for identifying causative variants from exome analysis results by filtering and prioritising using a number of criteria including the phenotype similarity between the disease and mouse mutants involving the gene candidates. Initial investigations revealed a variation in performance for different medical categories of disease, due in part to a varying contribution of the phenotype scoring component. Results In this study, we further analyse the performance of our cross-species phenotype matching algorithm, and examine in more detail the reasons why disease gene filtering based on phenotype data works better for certain disease categories than others. We found that in addition to misleading phenotype alignments between species, some disease categories are still more amenable to automated predictions than others, and that this often ties in with community perceptions on how well the organism works as model. Conclusions In conclusion, our automated disease gene candidate predictions are highly dependent on the organism used for the predictions and the disease category being studied. Future work on computational disease gene prediction using phenotype data would benefit from methods that take into account the disease category and the source of model organism data. PMID:25093073

  7. How well do HapMap haplotypes identify common haplotypes of genes? A comparison with haplotypes of 334 genes resequenced in the environmental genome project.

    PubMed

    Taylor, Jack A; Xu, Zong-Li; Kaplan, Norman L; Morris, Richard W

    2006-01-01

    One of the goals of the International HapMap Project is the identification of common haplotypes in genes. However, HapMap uses an incomplete catalogue of single nucleotide polymorphisms (SNPs) and might miss some common haplotypes. We examined this issue using data from the Environmental Genome Project (EGP) which resequenced 335 genes in 90 people, and thus, has a nearly complete catalogue of gene SNPs. The EGP identified a total of 45,243 SNPs, of which 10,780 were common SNPs (minor allele frequency >or=0.1). Using EGP common SNP genotype data, we identified 1,459 haplotypes with frequency >or=0.05 and we use these as "benchmark" haplotypes. HapMap release 16 had genotype information for 1,573 of 10,780 (15%) EGP common SNPs. Using these SNPs, we identified common HapMap haplotypes (frequency >or=0.05) in each of the four HapMap ethnic groups. To compare common HapMap haplotypes to EGP benchmark haplotypes, we collapsed benchmark haplotypes to the set of 1,573 SNPs. Ninety-eight percent of the collapsed benchmark haplotypes could be found as common HapMap haplotypes in one or more of the four HapMap ethnic groups. However, collapsing benchmark haplotypes to the set of SNPs available in HapMap resulted in a loss of haplotype information: 545 of 1,459 (37%) benchmark haplotypes were uniquely identified, and only 25% of genes had all their benchmark haplotypes uniquely identified. We resampled the EGP data to examine the effect of increasing the number of HapMap SNPs to 5 million, and estimate that approximately 40% of common SNPs in genes will be sampled and that half of the genes will have sufficient SNPs to identify all common haplotypes. This inability to distinguish common haplotypes of genes may result in loss of power when examining haplotype-disease association. PMID:16434598

  8. A Microarray-Based Gene Expression Analysis to Identify Diagnostic Biomarkers for Unknown Primary Cancer

    PubMed Central

    Kurahashi, Issei; Fujita, Yoshihiko; Arao, Tokuzo; Kurata, Takayasu; Koh, Yasuhiro; Sakai, Kazuko; Matsumoto, Koji; Tanioka, Maki; Takeda, Koji; Takiguchi, Yuichi; Yamamoto, Nobuyuki; Tsuya, Asuka; Matsubara, Nobuaki; Mukai, Hirofumi; Minami, Hironobu; Chayahara, Naoko; Yamanaka, Yasuhiro; Miwa, Keisuke; Takahashi, Shin; Takahashi, Shunji; Nakagawa, Kazuhiko; Nishio, Kazuto

    2013-01-01

    Background The biological basis for cancer of unknown primary (CUP) at the molecular level remains largely unknown, with no evidence of whether a common biological entity exists. Here, we assessed the possibility of identifying a common diagnostic biomarker for CUP using a microarray gene expression analysis. Methods Tumor mRNA samples from 60 patients with CUP were analyzed using the Affymetrix U133A Plus 2.0 GeneChip and were normalized by asinh (hyperbolic arc sine) transformation to construct a mean gene-expression profile specific to CUP. A gene-expression profile specific to non-CUP group was constructed using publicly available raw microarray datasets. The t-tests were performed to compare the CUP with non-CUP groups and the top 59 CUP specific genes with the highest fold change were selected (p-value<0.001). Results Among the 44 genes that were up-regulated in the CUP group, 6 genes for ribosomal proteins were identified. Two of these genes (RPS7 and RPL11) are known to be involved in the Mdm2–p53 pathway. We also identified several genes related to metastasis and apoptosis, suggesting a biological attribute of CUP. Conclusions The protein products of the up-regulated and down-regulated genes identified in this study may be clinically useful as unique biomarkers for CUP. PMID:23671674

  9. An Orthologous Epigenetic Gene Expression Signature Derived from Differentiating Embryonic Stem Cells Identifies Regulators of Cardiogenesis

    PubMed Central

    Busser, Brian W.; Lin, Yongshun; Yang, Yanqin; Zhu, Jun; Chen, Guokai; Michelson, Alan M.

    2015-01-01

    Here we used predictive gene expression signatures within a multi-species framework to identify the genes that underlie cardiac cell fate decisions in differentiating embryonic stem cells. We show that the overlapping orthologous mouse and human genes are the most accurate candidate cardiogenic genes as these genes identified the most conserved developmental pathways that characterize the cardiac lineage. An RNAi-based screen of the candidate genes in Drosophila uncovered numerous novel cardiogenic genes. shRNA knockdown combined with transcriptome profiling of the newly-identified transcription factors zinc finger protein 503 and zinc finger E-box binding homeobox 2 and the well-known cardiac regulatory factor NK2 homeobox 5 revealed that zinc finger E-box binding homeobox 2 activates terminal differentiation genes required for cardiomyocyte structure and function whereas zinc finger protein 503 and NK2 homeobox 5 are required for specification of the cardiac lineage. We further demonstrated that an essential role of NK2 homeobox 5 and zinc finger protein 503 in specification of the cardiac lineage is the repression of gene expression programs characteristic of alternative cell fates. Collectively, these results show that orthologous gene expression signatures can be used to identify conserved cardiogenic pathways. PMID:26485529

  10. Whole-exome sequencing identifies MST1R as a genetic susceptibility gene in nasopharyngeal carcinoma.

    PubMed

    Dai, Wei; Zheng, Hong; Cheung, Arthur Kwok Leung; Tang, Clara Sze-Man; Ko, Josephine Mun Yee; Wong, Bonnie Wing Yan; Leong, Merrin Man Long; Sham, Pak Chung; Cheung, Florence; Kwong, Dora Lai-Wan; Ngan, Roger Kai Cheong; Ng, Wai Tong; Yau, Chun Chung; Pan, Jianji; Peng, Xun; Tung, Stewart; Zhang, Zengfeng; Ji, Mingfang; Chiang, Alan Kwok-Shing; Lee, Anne Wing-Mui; Lee, Victor Ho-Fun; Lam, Ka-On; Au, Kwok Hung; Cheng, Hoi Ching; Yiu, Harry Ho-Yin; Lung, Maria Li

    2016-03-22

    Multiple factors, including host genetics, environmental factors, and Epstein-Barr virus (EBV) infection, contribute to nasopharyngeal carcinoma (NPC) development. To identify genetic susceptibility genes for NPC, a whole-exome sequencing (WES) study was performed in 161 NPC cases and 895 controls of Southern Chinese descent. The gene-based burden test discovered an association between macrophage-stimulating 1 receptor (MST1R) and NPC. We identified 13 independent cases carrying theMST1Rpathogenic heterozygous germ-line variants, and 53.8% of these cases were diagnosed with NPC aged at or even younger than 20 y, indicating thatMST1Rgerm-line variants are relevant to disease early-age onset (EAO) (age of ≤20 y). In total, fiveMST1Rmissense variants were found in EAO cases but were rare in controls (EAO vs. control, 17.9% vs. 1.2%,P= 7.94 × 10(-12)). The validation study, including 2,160 cases and 2,433 controls, showed that theMST1Rvariant c.G917A:p.R306H is highly associated with NPC (odds ratio of 9.0).MST1Ris predominantly expressed in the tissue-resident macrophages and is critical for innate immunity that protects organs from tissue damage and inflammation. Importantly, MST1R expression is detected in the ciliated epithelial cells in normal nasopharyngeal mucosa and plays a role in the cilia motility important for host defense. Although no somatic mutation ofMST1Rwas identified in the sporadic NPC tumors, copy number alterations and promoter hypermethylation atMST1Rwere often observed. Our findings provide new insights into the pathogenesis of NPC by highlighting the involvement of the MST1R-mediated signaling pathways. PMID:26951679

  11. Large-scale association analysis identifies new risk loci for coronary artery disease.

    PubMed

    Deloukas, Panos; Kanoni, Stavroula; Willenborg, Christina; Farrall, Martin; Assimes, Themistocles L; Thompson, John R; Ingelsson, Erik; Saleheen, Danish; Erdmann, Jeanette; Goldstein, Benjamin A; Stirrups, Kathleen; König, Inke R; Cazier, Jean-Baptiste; Johansson, Asa; Hall, Alistair S; Lee, Jong-Young; Willer, Cristen J; Chambers, John C; Esko, Tõnu; Folkersen, Lasse; Goel, Anuj; Grundberg, Elin; Havulinna, Aki S; Ho, Weang K; Hopewell, Jemma C; Eriksson, Niclas; Kleber, Marcus E; Kristiansson, Kati; Lundmark, Per; Lyytikäinen, Leo-Pekka; Rafelt, Suzanne; Shungin, Dmitry; Strawbridge, Rona J; Thorleifsson, Gudmar; Tikkanen, Emmi; Van Zuydam, Natalie; Voight, Benjamin F; Waite, Lindsay L; Zhang, Weihua; Ziegler, Andreas; Absher, Devin; Altshuler, David; Balmforth, Anthony J; Barroso, Inês; Braund, Peter S; Burgdorf, Christof; Claudi-Boehm, Simone; Cox, David; Dimitriou, Maria; Do, Ron; Doney, Alex S F; El Mokhtari, NourEddine; Eriksson, Per; Fischer, Krista; Fontanillas, Pierre; Franco-Cereceda, Anders; Gigante, Bruna; Groop, Leif; Gustafsson, Stefan; Hager, Jörg; Hallmans, Göran; Han, Bok-Ghee; Hunt, Sarah E; Kang, Hyun M; Illig, Thomas; Kessler, Thorsten; Knowles, Joshua W; Kolovou, Genovefa; Kuusisto, Johanna; Langenberg, Claudia; Langford, Cordelia; Leander, Karin; Lokki, Marja-Liisa; Lundmark, Anders; McCarthy, Mark I; Meisinger, Christa; Melander, Olle; Mihailov, Evelin; Maouche, Seraya; Morris, Andrew D; Müller-Nurasyid, Martina; Nikus, Kjell; Peden, John F; Rayner, N William; Rasheed, Asif; Rosinger, Silke; Rubin, Diana; Rumpf, Moritz P; Schäfer, Arne; Sivananthan, Mohan; Song, Ci; Stewart, Alexandre F R; Tan, Sian-Tsung; Thorgeirsson, Gudmundur; van der Schoot, C Ellen; Wagner, Peter J; Wells, George A; Wild, Philipp S; Yang, Tsun-Po; Amouyel, Philippe; Arveiler, Dominique; Basart, Hanneke; Boehnke, Michael; Boerwinkle, Eric; Brambilla, Paolo; Cambien, Francois; Cupples, Adrienne L; de Faire, Ulf; Dehghan, Abbas; Diemert, Patrick; Epstein, Stephen E; Evans, Alun; Ferrario, Marco M; Ferrières, Jean; Gauguier, Dominique; Go, Alan S; Goodall, Alison H; Gudnason, Villi; Hazen, Stanley L; Holm, Hilma; Iribarren, Carlos; Jang, Yangsoo; Kähönen, Mika; Kee, Frank; Kim, Hyo-Soo; Klopp, Norman; Koenig, Wolfgang; Kratzer, Wolfgang; Kuulasmaa, Kari; Laakso, Markku; Laaksonen, Reijo; Lee, Ji-Young; Lind, Lars; Ouwehand, Willem H; Parish, Sarah; Park, Jeong E; Pedersen, Nancy L; Peters, Annette; Quertermous, Thomas; Rader, Daniel J; Salomaa, Veikko; Schadt, Eric; Shah, Svati H; Sinisalo, Juha; Stark, Klaus; Stefansson, Kari; Trégouët, David-Alexandre; Virtamo, Jarmo; Wallentin, Lars; Wareham, Nicholas; Zimmermann, Martina E; Nieminen, Markku S; Hengstenberg, Christian; Sandhu, Manjinder S; Pastinen, Tomi; Syvänen, Ann-Christine; Hovingh, G Kees; Dedoussis, George; Franks, Paul W; Lehtimäki, Terho; Metspalu, Andres; Zalloua, Pierre A; Siegbahn, Agneta; Schreiber, Stefan; Ripatti, Samuli; Blankenberg, Stefan S; Perola, Markus; Clarke, Robert; Boehm, Bernhard O; O'Donnell, Christopher; Reilly, Muredach P; März, Winfried; Collins, Rory; Kathiresan, Sekar; Hamsten, Anders; Kooner, Jaspal S; Thorsteinsdottir, Unnur; Danesh, John; Palmer, Colin N A; Roberts, Robert; Watkins, Hugh; Schunkert, Heribert; Samani, Nilesh J

    2013-01-01

    Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2) < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways. PMID:23202125

  12. Renal cystic disease in tuberous sclerosis: role of the polycystic kidney disease 1 gene.

    PubMed Central

    Sampson, J R; Maheshwar, M M; Aspinwall, R; Thompson, P; Cheadle, J P; Ravine, D; Roy, S; Haan, E; Bernstein, J; Harris, P C

    1997-01-01

    Tuberous sclerosis is an autosomal dominant trait characterized by the development of hamartomatous growths in many organs. Renal cysts are also a frequent manifestation. Major genes for tuberous sclerosis and autosomal dominant polycystic kidney disease, TSC2 and PKD1, respectively, lie adjacent to each other at chromosome 16p13.3, suggesting a role for PKD1 in the etiology of renal cystic disease in tuberous sclerosis. We studied 27 unrelated patients with tuberous sclerosis and renal cystic disease. Clinical histories and radiographic features were reviewed, and renal function was assessed. We sought mutations at the TSC2 and PKD1 loci, using pulsed field- and conventional-gel electrophoresis and FISH. Twenty-two patients had contiguous deletions of TSC2 and PKD1. In 17 patients with constitutional deletions, cystic disease was severe, with early renal insufficiency. One patient with deletion of TSC2 and of only the 3' UTR of PKD1 had few cysts. Four patients were somatic mosaics; the severity of their cystic disease varied considerably. Mosaicism and mild cystic disease also were demonstrated in parents of 3 of the constitutionally deleted patients. Five patients without contiguous deletions had relatively mild cystic disease, 3 of whom had gross rearrangements of TSC2 and 2 in whom no mutation was identified. Significant renal cystic disease in tuberous sclerosis usually reflects mutational involvement of the PKD1 gene, and mosaicism for large deletions of TSC2 and PKD1 is a frequent phenomenon. Images Figure 1 Figure 2 Figure 3 Figure 5 PMID:9382094

  13. Pinpointing disease genes through phenomic and genomic data fusion

    PubMed Central

    2015-01-01

    Background Pinpointing genes involved in inherited human diseases remains a great challenge in the post-genomics era. Although approaches have been proposed either based on the guilt-by-association principle or making use of disease phenotype similarities, the low coverage of both diseases and genes in existing methods has been preventing the scan of causative genes for a significant proportion of diseases at the whole-genome level. Results To overcome this limitation, we proposed a rigorous statistical method called pgFusion to prioritize candidate genes by integrating one type of disease phenotype similarity derived from the Unified Medical Language System (UMLS) and seven types of gene functional similarities calculated from gene expression, gene ontology, pathway membership, protein sequence, protein domain, protein-protein interaction and regulation pattern, respectively. Our method covered a total of 7,719 diseases and 20,327 genes, achieving the highest coverage thus far for both diseases and genes. We performed leave-one-out cross-validation experiments to demonstrate the superior performance of our method and applied it to a real exome sequencing dataset of epileptic encephalopathies, showing the capability of this approach in finding causative genes for complex diseases. We further provided the standalone software and online services of pgFusion at http://bioinfo.au.tsinghua.edu.cn/jianglab/pgfusion. Conclusions pgFusion not only provided an effective way for prioritizing candidate genes, but also demonstrated feasible solutions to two fundamental questions in the analysis of big genomic data: the comparability of heterogeneous data and the integration of multiple types of data. Applications of this method in exome or whole genome sequencing studies would accelerate the finding of causative genes for human diseases. Other research fields in genomics could also benefit from the incorporation of our data fusion methodology. PMID:25708473

  14. Omics Approach to Identify Factors Involved in Brassica Disease Resistance.

    PubMed

    Francisco, Marta; Soengas, Pilar; Velasco, Pablo; Bhadauria, Vijai; Cartea, Maria E; Rodríguez, Victor M

    2016-01-01

    Understanding plant's defense mechanisms and their response to biotic stresses is of fundamental meaning for the development of resistant crop varieties and more productive agriculture. The Brassica genus involves a large variety of economically important species and cultivars used as vegetable source, oilseeds, forage and ornamental. Damage caused by pathogens attack affects negatively various aspects of plant growth, development, and crop productivity. Over the last few decades, advances in plant physiology, genetics, and molecular biology have greatly improved our understanding of plant responses to biotic stress conditions. In this regard, various 'omics' technologies enable qualitative and quantitative monitoring of the abundance of various biological molecules in a high-throughput manner, and thus allow determination of their variation between different biological states on a genomic scale. In this review, we have described advances in 'omic' tools (genomics, transcriptomics, proteomics and metabolomics) in the view of conventional and modern approaches being used to elucidate the molecular mechanisms that underlie Brassica disease resistance. PMID:26363709

  15. Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database

    PubMed Central

    Davis, Allan Peter; Wiegers, Thomas C.; King, Benjamin L.; Wiegers, Jolene; Grondin, Cynthia J.; Sciaky, Daniela; Johnson, Robin J.; Mattingly, Carolyn J.

    2016-01-01

    Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO) file from NCBI Gene. By integrating these GO-gene annotations with CTD’s gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil) and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis) as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and pharmaceutical drug makers in finding commonalities in disease mechanisms, which in turn could help identify new therapeutics, new indications for existing pharmaceuticals, potential disease comorbidities, and alerts for side effects. PMID:27171405

  16. Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

    PubMed Central

    Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

    2008-01-01

    Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

  17. Rapid in vivo forward genetic approach for identifying axon death genes in Drosophila

    PubMed Central

    Neukomm, Lukas J.; Burdett, Thomas C.; Gonzalez, Michael A.; Züchner, Stephan; Freeman, Marc R.

    2014-01-01

    Axons damaged by acute injury, toxic insults, or neurodegenerative diseases execute a poorly defined autodestruction signaling pathway leading to widespread fragmentation and functional loss. Here, we describe an approach to study Wallerian degeneration in the Drosophila L1 wing vein that allows for analysis of axon degenerative phenotypes with single-axon resolution in vivo. This method allows for the axotomy of specific subsets of axons followed by examination of progressive axonal degeneration and debris clearance alongside uninjured control axons. We developed new Flippase (FLP) reagents using proneural gene promoters to drive FLP expression very early in neural lineages. These tools allow for the production of mosaic clone populations with high efficiency in sensory neurons in the wing. We describe a collection of lines optimized for forward genetic mosaic screens using MARCM (mosaic analysis with a repressible cell marker; i.e., GFP-labeled, homozygous mutant) on all major autosomal arms (∼95% of the fly genome). Finally, as a proof of principle we screened the X chromosome and identified a collection eight recessive and two dominant alleles of highwire, a ubiquitin E3 ligase required for axon degeneration. Similar unbiased forward genetic screens should help rapidly delineate axon death genes, thereby providing novel potential drug targets for therapeutic intervention to prevent axonal and synaptic loss. PMID:24958874

  18. Standardized Plant Disease Evaluations will Enhance Resistance Gene Discovery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Gene discovery and marker development using DNA based tools require plant populations with well-documented phenotypes. Related crops such as apples and pears may share a number of genes, for example resistance to common diseases, and data mining in one crop may reveal genes for the other. However, u...

  19. A Drosophila model identifies a critical role for zinc in mineralization for kidney stone disease.

    PubMed

    Chi, Thomas; Kim, Man Su; Lang, Sven; Bose, Neelanjan; Kahn, Arnold; Flechner, Lawrence; Blaschko, Sarah D; Zee, Tiffany; Muteliefu, Gulinuer; Bond, Nichole; Kolipinski, Marysia; Fakra, Sirine C; Mandel, Neil; Miller, Joe; Ramanathan, Arvind; Killilea, David W; Brückner, Katja; Kapahi, Pankaj; Stoller, Marshall L

    2015-01-01

    Ectopic calcification is a driving force for a variety of diseases, including kidney stones and atherosclerosis, but initiating factors remain largely unknown. Given its importance in seemingly divergent disease processes, identifying fundamental principal actors for ectopic calcification may have broad translational significance. Here we establish a Drosophila melanogaster model for ectopic calcification by inhibiting xanthine dehydrogenase whose deficiency leads to kidney stones in humans and dogs. Micro X-ray absorption near edge spectroscopy (μXANES) synchrotron analyses revealed high enrichment of zinc in the Drosophila equivalent of kidney stones, which was also observed in human kidney stones and Randall's plaques (early calcifications seen in human kidneys thought to be the precursor for renal stones). To further test the role of zinc in driving mineralization, we inhibited zinc transporter genes in the ZnT family and observed suppression of Drosophila stone formation. Taken together, genetic, dietary, and pharmacologic interventions to lower zinc confirm a critical role for zinc in driving the process of heterogeneous nucleation that eventually leads to stone formation. Our findings open a novel perspective on the etiology of urinary stones and related diseases, which may lead to the identification of new preventive and therapeutic approaches. PMID:25970330

  20. A Drosophila Model Identifies a Critical Role for Zinc in Mineralization for Kidney Stone Disease

    PubMed Central

    Lang, Sven; Bose, Neelanjan; Kahn, Arnold; Flechner, Lawrence; Blaschko, Sarah D.; Zee, Tiffany; Muteliefu, Gulinuer; Bond, Nichole; Kolipinski, Marysia; Fakra, Sirine C.; Mandel, Neil; Miller, Joe; Ramanathan, Arvind; Killilea, David W.; Brückner, Katja; Kapahi, Pankaj; Stoller, Marshall L.

    2015-01-01

    Ectopic calcification is a driving force for a variety of diseases, including kidney stones and atherosclerosis, but initiating factors remain largely unknown. Given its importance in seemingly divergent disease processes, identifying fundamental principal actors for ectopic calcification may have broad translational significance. Here we establish a Drosophila melanogaster model for ectopic calcification by inhibiting xanthine dehydrogenase whose deficiency leads to kidney stones in humans and dogs. Micro X-ray absorption near edge spectroscopy (μXANES) synchrotron analyses revealed high enrichment of zinc in the Drosophila equivalent of kidney stones, which was also observed in human kidney stones and Randall’s plaques (early calcifications seen in human kidneys thought to be the precursor for renal stones). To further test the role of zinc in driving mineralization, we inhibited zinc transporter genes in the ZnT family and observed suppression of Drosophila stone formation. Taken together, genetic, dietary, and pharmacologic interventions to lower zinc confirm a critical role for zinc in driving the process of heterogeneous nucleation that eventually l