Comparative Transcriptional Profiling of the Axolotl Limb Identifies a Tripartite Regeneration-Specific Gene Program

PubMed Central

Knapp, Dunja; Schulz, Herbert; Rascon, Cynthia Alexander; Volkmer, Michael; Scholz, Juliane; Nacu, Eugen; Le, Mu; Novozhilov, Sergey; Tazaki, Akira; Protze, Stephanie; Jacob, Tina; Hubner, Norbert; Habermann, Bianca; Tanaka, Elly M.

2013-01-01

Understanding how the limb blastema is established after the initial wound healing response is an important aspect of regeneration research. Here we performed parallel expression profile time courses of healing lateral wounds versus amputated limbs in axolotl. This comparison between wound healing and regeneration allowed us to identify amputation-specific genes. By clustering the expression profiles of these samples, we could detect three distinguishable phases of gene expression – early wound healing followed by a transition-phase leading to establishment of the limb development program, which correspond to the three phases of limb regeneration that had been defined by morphological criteria. By focusing on the transition-phase, we identified 93 strictly amputation-associated genes many of which are implicated in oxidative-stress response, chromatin modification, epithelial development or limb development. We further classified the genes based on whether they were or were not significantly expressed in the developing limb bud. The specific localization of 53 selected candidates within the blastema was investigated by in situ hybridization. In summary, we identified a set of genes that are expressed specifically during regeneration and are therefore, likely candidates for the regulation of blastema formation. PMID:23658691

Comprehensive evaluation of disease- and trait-specific enrichment for eight functional elements among GWAS-identified variants.

PubMed

Markunas, Christina A; Johnson, Eric O; Hancock, Dana B

2017-07-01

Genome-wide association study (GWAS)-identified variants are enriched for functional elements. However, we have limited knowledge of how functional enrichment may differ by disease/trait and tissue type. We tested a broad set of eight functional elements for enrichment among GWAS-identified SNPs (p < 5×10 -8 ) from the NHGRI-EBI Catalog across seven disease/trait categories: cancer, cardiovascular disease, diabetes, autoimmune disease, psychiatric disease, neurological disease, and anthropometric traits. SNPs were annotated using HaploReg for the eight functional elements across any tissue: DNase sites, expression quantitative trait loci (eQTL), sequence conservation, enhancers, promoters, missense variants, sequence motifs, and protein binding sites. In addition, tissue-specific annotations were considered for brain vs. blood. Disease/trait SNPs were compared to a control set of 4809 SNPs matched to the GWAS SNPs (N = 1639) on allele frequency, gene density, distance to nearest gene, and linkage disequilibrium at ~3:1 ratio. Enrichment analyses were conducted using logistic regression, with Bonferroni correction. Overall, a significant enrichment was observed for all functional elements, except sequence motifs. Missense SNPs showed the strongest magnitude of enrichment. eQTLs were the only functional element significantly enriched across all diseases/traits. Magnitudes of enrichment were generally similar across diseases/traits, where enrichment was statistically significant. Blood vs. brain tissue effects on enrichment were dependent on disease/trait and functional element (e.g., cardiovascular disease: eQTLs P TissueDifference  = 1.28 × 10 -6 vs. enhancers P TissueDifference  = 0.94). Identifying disease/trait-relevant functional elements and tissue types could provide new insight into the underlying biology, by guiding a priori GWAS analyses (e.g., brain enhancer elements for psychiatric disease) or facilitating post hoc interpretation.

Disease gene prioritization by integrating tissue-specific molecular networks using a robust multi-network model.

PubMed

Ni, Jingchao; Koyuturk, Mehmet; Tong, Hanghang; Haines, Jonathan; Xu, Rong; Zhang, Xiang

2016-11-10

Accurately prioritizing candidate disease genes is an important and challenging problem. Various network-based methods have been developed to predict potential disease genes by utilizing the disease similarity network and molecular networks such as protein interaction or gene co-expression networks. Although successful, a common limitation of the existing methods is that they assume all diseases share the same molecular network and a single generic molecular network is used to predict candidate genes for all diseases. However, different diseases tend to manifest in different tissues, and the molecular networks in different tissues are usually different. An ideal method should be able to incorporate tissue-specific molecular networks for different diseases. In this paper, we develop a robust and flexible method to integrate tissue-specific molecular networks for disease gene prioritization. Our method allows each disease to have its own tissue-specific network(s). We formulate the problem of candidate gene prioritization as an optimization problem based on network propagation. When there are multiple tissue-specific networks available for a disease, our method can automatically infer the relative importance of each tissue-specific network. Thus it is robust to the noisy and incomplete network data. To solve the optimization problem, we develop fast algorithms which have linear time complexities in the number of nodes in the molecular networks. We also provide rigorous theoretical foundations for our algorithms in terms of their optimality and convergence properties. Extensive experimental results show that our method can significantly improve the accuracy of candidate gene prioritization compared with the state-of-the-art methods. In our experiments, we compare our methods with 7 popular network-based disease gene prioritization algorithms on diseases from Online Mendelian Inheritance in Man (OMIM) database. The experimental results demonstrate that our methods

Genome-wide Association Study Identifies African-Specific Susceptibility Loci in African Americans with Inflammatory Bowel Disease

PubMed Central

Brant, Steven R.; Okou, David T.; Simpson, Claire L.; Cutler, David J.; Haritunians, Talin; Bradfield, Jonathan P.; Chopra, Pankaj; Prince, Jarod; Begum, Ferdouse; Kumar, Archana; Huang, Chengrui; Venkateswaran, Suresh; Datta, Lisa W.; Wei, Zhi; Thomas, Kelly; Herrinton, Lisa J.; Klapproth, Jan-Micheal A.; Quiros, Antonio J.; Seminerio, Jenifer; Liu, Zhenqiu; Alexander, Jonathan S.; Baldassano, Robert N.; Dudley-Brown, Sharon; Cross, Raymond K.; Dassopoulos, Themistocles; Denson, Lee A.; Dhere, Tanvi A.; Dryden, Gerald W.; Hanson, John S.; Hou, Jason K.; Hussain, Sunny Z.; Hyams, Jeffrey S.; Isaacs, Kim L.; Kader, Howard; Kappelman, Michael D.; Katz, Jeffry; Kellermayer, Richard; Kirschner, Barbara S.; Kuemmerle, John F.; Kwon, John H.; Lazarev, Mark; Li, Ellen; Mack, David; Mannon, Peter; Moulton, Dedrick E.; Newberry, Rodney D.; Osuntokun, Bankole O.; Patel, Ashish S.; Saeed, Shehzad A.; Targan, Stephan R.; Valentine, John F.; Wang, Ming-Hsi; Zonca, Martin; Rioux, John D.; Duerr, Richard H.; Silverberg, Mark S.; Cho, Judy H.; Hakonarson, Hakon; Zwick, Michael E.; McGovern, Dermot P.B.; Kugathasan, Subra

2016-01-01

Background & Aims The inflammatory bowel diseases (IBD) ulcerative colitis (UC) and Crohn’s disease (CD) cause significant morbidity and are increasing in prevalence among all populations, including African Americans. More than 200 susceptibility loci have been identified in populations of predominantly European ancestry, but few loci have been associated with IBD in other ethnicities. Methods We performed 2 high-density, genome-wide scans comprising 2345 cases of African Americans with IBD (1646 with CD, 583 with UC, and 116 inflammatory bowel disease unclassified [IBD-U]) and 5002 individuals without IBD (controls, identified from the Health Retirement Study and Kaiser Permanente database). Single-nucleotide polymorphisms (SNPs) associated at P<5.0×10−8 in meta-analysis with a nominal evidence (P<.05) in each scan were considered to have genome-wide significance. Results We detected SNPs at HLA-DRB1, and African-specific SNPs at ZNF649 and LSAMP, with associations of genome-wide significance for UC. We detected SNPs at USP25 with associations of genome-wide significance associations for IBD. No associations of genome-wide significance were detected for CD. In addition, 9 genes previously associated with IBD contained SNPs with significant evidence for replication (P<1.6×10−6): ADCY3, CXCR6, HLA-DRB1 to HLA-DQA1 (genome-wide significance on conditioning), IL12B, PTGER4, and TNC for IBD; IL23R, PTGER4, and SNX20 (in strong linkage disequilibrium with NOD2) for CD; and KCNQ2 (near TNFRSF6B) for UC. Several of these genes, such as TNC (near TNFSF15), CXCR6, and genes associated with IBD at the HLA locus, contained SNPs with unique association patterns with African-specific alleles. Conclusions We performed a genome-wide association study of African Americans with IBD and identified loci associated with CD and UC in only this population; we also replicated loci identified in European populations. The detection of variants associated with IBD risk in only

Genome-Wide Association Study Identifies African-Specific Susceptibility Loci in African Americans With Inflammatory Bowel Disease.

PubMed

Brant, Steven R; Okou, David T; Simpson, Claire L; Cutler, David J; Haritunians, Talin; Bradfield, Jonathan P; Chopra, Pankaj; Prince, Jarod; Begum, Ferdouse; Kumar, Archana; Huang, Chengrui; Venkateswaran, Suresh; Datta, Lisa W; Wei, Zhi; Thomas, Kelly; Herrinton, Lisa J; Klapproth, Jan-Micheal A; Quiros, Antonio J; Seminerio, Jenifer; Liu, Zhenqiu; Alexander, Jonathan S; Baldassano, Robert N; Dudley-Brown, Sharon; Cross, Raymond K; Dassopoulos, Themistocles; Denson, Lee A; Dhere, Tanvi A; Dryden, Gerald W; Hanson, John S; Hou, Jason K; Hussain, Sunny Z; Hyams, Jeffrey S; Isaacs, Kim L; Kader, Howard; Kappelman, Michael D; Katz, Jeffry; Kellermayer, Richard; Kirschner, Barbara S; Kuemmerle, John F; Kwon, John H; Lazarev, Mark; Li, Ellen; Mack, David; Mannon, Peter; Moulton, Dedrick E; Newberry, Rodney D; Osuntokun, Bankole O; Patel, Ashish S; Saeed, Shehzad A; Targan, Stephan R; Valentine, John F; Wang, Ming-Hsi; Zonca, Martin; Rioux, John D; Duerr, Richard H; Silverberg, Mark S; Cho, Judy H; Hakonarson, Hakon; Zwick, Michael E; McGovern, Dermot P B; Kugathasan, Subra

2017-01-01

The inflammatory bowel diseases (IBD) ulcerative colitis (UC) and Crohn's disease (CD) cause significant morbidity and are increasing in prevalence among all populations, including African Americans. More than 200 susceptibility loci have been identified in populations of predominantly European ancestry, but few loci have been associated with IBD in other ethnicities. We performed 2 high-density, genome-wide scans comprising 2345 cases of African Americans with IBD (1646 with CD, 583 with UC, and 116 inflammatory bowel disease unclassified) and 5002 individuals without IBD (controls, identified from the Health Retirement Study and Kaiser Permanente database). Single-nucleotide polymorphisms (SNPs) associated at P < 5.0 × 10 -8 in meta-analysis with a nominal evidence (P < .05) in each scan were considered to have genome-wide significance. We detected SNPs at HLA-DRB1, and African-specific SNPs at ZNF649 and LSAMP, with associations of genome-wide significance for UC. We detected SNPs at USP25 with associations of genome-wide significance for IBD. No associations of genome-wide significance were detected for CD. In addition, 9 genes previously associated with IBD contained SNPs with significant evidence for replication (P < 1.6 × 10 -6 ): ADCY3, CXCR6, HLA-DRB1 to HLA-DQA1 (genome-wide significance on conditioning), IL12B,PTGER4, and TNC for IBD; IL23R, PTGER4, and SNX20 (in strong linkage disequilibrium with NOD2) for CD; and KCNQ2 (near TNFRSF6B) for UC. Several of these genes, such as TNC (near TNFSF15), CXCR6, and genes associated with IBD at the HLA locus, contained SNPs with unique association patterns with African-specific alleles. We performed a genome-wide association study of African Americans with IBD and identified loci associated with UC in only this population; we also replicated IBD, CD, and UC loci identified in European populations. The detection of variants associated with IBD risk in only people of African descent demonstrates the

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

PubMed Central

Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang

2011-01-01

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing

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

A meta-analysis of public microarray data identifies biological regulatory networks in Parkinson's disease.

PubMed

Su, Lining; Wang, Chunjie; Zheng, Chenqing; Wei, Huiping; Song, Xiaoqing

2018-04-13

Parkinson's disease (PD) is a long-term degenerative disease that is caused by environmental and genetic factors. The networks of genes and their regulators that control the progression and development of PD require further elucidation. We examine common differentially expressed genes (DEGs) from several PD blood and substantia nigra (SN) microarray datasets by meta-analysis. Further we screen the PD-specific genes from common DEGs using GCBI. Next, we used a series of bioinformatics software to analyze the miRNAs, lncRNAs and SNPs associated with the common PD-specific genes, and then identify the mTF-miRNA-gene-gTF network. Our results identified 36 common DEGs in PD blood studies and 17 common DEGs in PD SN studies, and five of the genes were previously known to be associated with PD. Further study of the regulatory miRNAs associated with the common PD-specific genes revealed 14 PD-specific miRNAs in our study. Analysis of the mTF-miRNA-gene-gTF network about PD-specific genes revealed two feed-forward loops: one involving the SPRK2 gene, hsa-miR-19a-3p and SPI1, and the second involving the SPRK2 gene, hsa-miR-17-3p and SPI. The long non-coding RNA (lncRNA)-mediated regulatory network identified lncRNAs associated with PD-specific genes and PD-specific miRNAs. Moreover, single nucleotide polymorphism (SNP) analysis of the PD-specific genes identified two significant SNPs, and SNP analysis of the neurodegenerative disease-specific genes identified seven significant SNPs. Most of these SNPs are present in the 3'-untranslated region of genes and are controlled by several miRNAs. Our study identified a total of 53 common DEGs in PD patients compared with healthy controls in blood and brain datasets and five of these genes were previously linked with PD. Regulatory network analysis identified PD-specific miRNAs, associated long non-coding RNA and feed-forward loops, which contribute to our understanding of the mechanisms underlying PD. The SNPs identified in our

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters.

PubMed

Javierre, Biola M; Burren, Oliver S; Wilder, Steven P; Kreuzhuber, Roman; Hill, Steven M; Sewitz, Sven; Cairns, Jonathan; Wingett, Steven W; Várnai, Csilla; Thiecke, Michiel J; Burden, Frances; Farrow, Samantha; Cutler, Antony J; Rehnström, Karola; Downes, Kate; Grassi, Luigi; Kostadima, Myrto; Freire-Pritchett, Paula; Wang, Fan; Stunnenberg, Hendrik G; Todd, John A; Zerbino, Daniel R; Stegle, Oliver; Ouwehand, Willem H; Frontini, Mattia; Wallace, Chris; Spivakov, Mikhail; Fraser, Peter

2016-11-17

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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

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

DOE PAGES

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

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

A systems-wide comparison of red rice (Oryza longistaminata) tissues identifies rhizome specific genes and proteins that are targets for cultivated rice improvement

PubMed Central

2014-01-01

Background The rhizome, the original stem of land plants, enables species to invade new territory and is a critical component of perenniality, especially in grasses. Red rice (Oryza longistaminata) is a perennial wild rice species with many valuable traits that could be used to improve cultivated rice cultivars, including rhizomatousness, disease resistance and drought tolerance. Despite these features, little is known about the molecular mechanisms that contribute to rhizome growth, development and function in this plant. Results We used an integrated approach to compare the transcriptome, proteome and metabolome of the rhizome to other tissues of red rice. 116 Gb of transcriptome sequence was obtained from various tissues and used to identify rhizome-specific and preferentially expressed genes, including transcription factors and hormone metabolism and stress response-related genes. Proteomics and metabolomics approaches identified 41 proteins and more than 100 primary metabolites and plant hormones with rhizome preferential accumulation. Of particular interest was the identification of a large number of gene transcripts from Magnaportha oryzae, the fungus that causes rice blast disease in cultivated rice, even though the red rice plants showed no sign of disease. Conclusions A significant set of genes, proteins and metabolites appear to be specifically or preferentially expressed in the rhizome of O. longistaminata. The presence of M. oryzae gene transcripts at a high level in apparently healthy plants suggests that red rice is resistant to this pathogen, and may be able to provide genes to cultivated rice that will enable resistance to rice blast disease. PMID:24521476

Whole exome sequencing identifies novel candidate genes that modify chronic obstructive pulmonary disease susceptibility.

PubMed

Bruse, Shannon; Moreau, Michael; Bromberg, Yana; Jang, Jun-Ho; Wang, Nan; Ha, Hongseok; Picchi, Maria; Lin, Yong; Langley, Raymond J; Qualls, Clifford; Klensney-Tait, Julia; Zabner, Joseph; Leng, Shuguang; Mao, Jenny; Belinsky, Steven A; Xing, Jinchuan; Nyunoya, Toru

2016-01-07

Chronic obstructive pulmonary disease (COPD) is characterized by an irreversible airflow limitation in response to inhalation of noxious stimuli, such as cigarette smoke. However, only 15-20 % smokers manifest COPD, suggesting a role for genetic predisposition. Although genome-wide association studies have identified common genetic variants that are associated with susceptibility to COPD, effect sizes of the identified variants are modest, as is the total heritability accounted for by these variants. In this study, an extreme phenotype exome sequencing study was combined with in vitro modeling to identify COPD candidate genes. We performed whole exome sequencing of 62 highly susceptible smokers and 30 exceptionally resistant smokers to identify rare variants that may contribute to disease risk or resistance to COPD. This was a cross-sectional case-control study without therapeutic intervention or longitudinal follow-up information. We identified candidate genes based on rare variant analyses and evaluated exonic variants to pinpoint individual genes whose function was computationally established to be significantly different between susceptible and resistant smokers. Top scoring candidate genes from these analyses were further filtered by requiring that each gene be expressed in human bronchial epithelial cells (HBECs). A total of 81 candidate genes were thus selected for in vitro functional testing in cigarette smoke extract (CSE)-exposed HBECs. Using small interfering RNA (siRNA)-mediated gene silencing experiments, we showed that silencing of several candidate genes augmented CSE-induced cytotoxicity in vitro. Our integrative analysis through both genetic and functional approaches identified two candidate genes (TACC2 and MYO1E) that augment cigarette smoke (CS)-induced cytotoxicity and, potentially, COPD susceptibility.

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

PubMed Central

Boldt, Karsten; van Reeuwijk, Jeroen; Lu, Qianhao; Koutroumpas, Konstantinos; Nguyen, Thanh-Minh T.; Texier, Yves; van Beersum, Sylvia E. C.; Horn, Nicola; Willer, Jason R.; Mans, Dorus A.; Dougherty, Gerard; Lamers, Ideke J. C.; Coene, Karlien L. M.; Arts, Heleen H.; Betts, Matthew J.; Beyer, Tina; Bolat, Emine; Gloeckner, Christian Johannes; Haidari, Khatera; Hetterschijt, Lisette; Iaconis, Daniela; Jenkins, Dagan; Klose, Franziska; Knapp, Barbara; Latour, Brooke; Letteboer, Stef J. F.; Marcelis, Carlo L.; Mitic, Dragana; Morleo, Manuela; Oud, Machteld M.; Riemersma, Moniek; Rix, Susan; Terhal, Paulien A.; Toedt, Grischa; van Dam, Teunis J. P.; de Vrieze, Erik; Wissinger, Yasmin; Wu, Ka Man; Apic, Gordana; Beales, Philip L.; Blacque, Oliver E.; Gibson, Toby J.; Huynen, Martijn A.; Katsanis, Nicholas; Kremer, Hannie; Omran, Heymut; van Wijk, Erwin; Wolfrum, Uwe; Kepes, François; Davis, Erica E.; Franco, Brunella; Giles, Rachel H.; Ueffing, Marius; Russell, Robert B.; Roepman, Ronald; Al-Turki, Saeed; Anderson, Carl; Antony, Dinu; Barroso, Inês; Bentham, Jamie; Bhattacharya, Shoumo; Carss, Keren; Chatterjee, Krishna; Cirak, Sebahattin; Cosgrove, Catherine; Danecek, Petr; Durbin, Richard; Fitzpatrick, David; Floyd, Jamie; Reghan Foley, A.; Franklin, Chris; Futema, Marta; Humphries, Steve E.; Hurles, Matt; Joyce, Chris; McCarthy, Shane; Mitchison, Hannah M.; Muddyman, Dawn; Muntoni, Francesco; O'Rahilly, Stephen; Onoufriadis, Alexandros; Payne, Felicity; Plagnol, Vincent; Raymond, Lucy; Savage, David B.; Scambler, Peter; Schmidts, Miriam; Schoenmakers, Nadia; Semple, Robert; Serra, Eva; Stalker, Jim; van Kogelenberg, Margriet; Vijayarangakannan, Parthiban; Walter, Klaudia; Whittall, Ros; Williamson, Kathy

2016-01-01

Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine. PMID:27173435

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.

Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.

PubMed

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result.

Gene Expression Profiling Combined with Bioinformatics Analysis Identify Biomarkers for Parkinson Disease

PubMed Central

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result. PMID:23284986

Omics of Brucella: Species-Specific sRNA-Mediated Gene Ontology Regulatory Networks Identified by Computational Biology.

PubMed

Vishnu, Udayakumar S; Sankarasubramanian, Jagadesan; Gunasekaran, Paramasamy; Sridhar, Jayavel; Rajendhran, Jeyaprakash

2016-06-01

Brucella is an intracellular bacterium that causes the zoonotic infectious disease, brucellosis. Brucella species are currently intensively studied with a view to developing novel global health diagnostics and therapeutics. In this context, small RNAs (sRNAs) are one of the emerging topical areas; they play significant roles in regulating gene expression and cellular processes in bacteria. In the present study, we forecast sRNAs in three Brucella species that infect humans, namely Brucella melitensis, Brucella abortus, and Brucella suis, using a computational biology analysis. We combined two bioinformatic algorithms, SIPHT and sRNAscanner. In B. melitensis 16M, 21 sRNA candidates were identified, of which 14 were novel. Similarly, 14 sRNAs were identified in B. abortus, of which four were novel. In B. suis, 16 sRNAs were identified, and five of them were novel. TargetRNA2 software predicted the putative target genes that could be regulated by the identified sRNAs. The identified mRNA targets are involved in carbohydrate, amino acid, lipid, nucleotide, and coenzyme metabolism and transport, energy production and conversion, replication, recombination, repair, and transcription. Additionally, the Gene Ontology (GO) network analysis revealed the species-specific, sRNA-based regulatory networks in B. melitensis, B. abortus, and B. suis. Taken together, although sRNAs are veritable modulators of gene expression in prokaryotes, there are few reports on the significance of sRNAs in Brucella. This report begins to address this literature gap by offering a series of initial observations based on computational biology to pave the way for future experimental analysis of sRNAs and their targets to explain the complex pathogenesis of Brucella.

Antioxidant Defense Enzyme Genes and Asthma Susceptibility: Gender-Specific Effects and Heterogeneity in Gene-Gene Interactions between Pathogenetic Variants of the Disease

PubMed Central

Polonikov, Alexey V.; Ivanov, Vladimir P.; Bogomazov, Alexey D.; Freidin, Maxim B.; Illig, Thomas; Solodilova, Maria A.

2014-01-01

Oxidative stress resulting from an increased amount of reactive oxygen species and an imbalance between oxidants and antioxidants plays an important role in the pathogenesis of asthma. The present study tested the hypothesis that genetic susceptibility to allergic and nonallergic variants of asthma is determined by complex interactions between genes encoding antioxidant defense enzymes (ADE). We carried out a comprehensive analysis of the associations between adult asthma and 46 single nucleotide polymorphisms of 34 ADE genes and 12 other candidate genes of asthma in Russian population using set association analysis and multifactor dimensionality reduction approaches. We found for the first time epistatic interactions between ADE genes underlying asthma susceptibility and the genetic heterogeneity between allergic and nonallergic variants of the disease. We identified GSR (glutathione reductase) and PON2 (paraoxonase 2) as novel candidate genes for asthma susceptibility. We observed gender-specific effects of ADE genes on the risk of asthma. The results of the study demonstrate complexity and diversity of interactions between genes involved in oxidative stress underlying susceptibility to allergic and nonallergic asthma. PMID:24895604

Leveraging network analytics to infer patient syndrome and identify causal genes in rare disease cases.

PubMed

Krämer, Andreas; Shah, Sohela; Rebres, Robert Anthony; Tang, Susan; Richards, Daniel Rene

2017-08-11

Next-generation sequencing is widely used to identify disease-causing variants in patients with rare genetic disorders. Identifying those variants from whole-genome or exome data can be both scientifically challenging and time consuming. A significant amount of time is spent on variant annotation, and interpretation. Fully or partly automated solutions are therefore needed to streamline and scale this process. We describe Phenotype Driven Ranking (PDR), an algorithm integrated into Ingenuity Variant Analysis, that uses observed patient phenotypes to prioritize diseases and genes in order to expedite causal-variant discovery. Our method is based on a network of phenotype-disease-gene relationships derived from the QIAGEN Knowledge Base, which allows for efficient computational association of phenotypes to implicated diseases, and also enables scoring and ranking. We have demonstrated the utility and performance of PDR by applying it to a number of clinical rare-disease cases, where the true causal gene was known beforehand. It is also shown that PDR compares favorably to a representative alternative tool.

A maize resistance gene functions against bacterial streak disease in rice.

PubMed

Zhao, Bingyu; Lin, Xinghua; Poland, Jesse; Trick, Harold; Leach, Jan; Hulbert, Scot

2005-10-25

Although cereal crops all belong to the grass family (Poacea), most of their diseases are specific to a particular species. Thus, a given cereal species is typically resistant to diseases of other grasses, and this nonhost resistance is generally stable. To determine the feasibility of transferring nonhost resistance genes (R genes) between distantly related grasses to control specific diseases, we identified a maize R gene that recognizes a rice pathogen, Xanthomonas oryzae pv. oryzicola, which causes bacterial streak disease. Bacterial streak is an important disease of rice in Asia, and no simply inherited sources of resistance have been identified in rice. Although X. o. pv. oryzicola does not cause disease on maize, we identified a maize gene, Rxo1, that conditions a resistance reaction to a diverse collection of pathogen strains. Surprisingly, Rxo1 also controls resistance to the unrelated pathogen Burkholderia andropogonis, which causes bacterial stripe of sorghum and maize. The same gene thus controls resistance reactions to both pathogens and nonpathogens of maize. Rxo1 has a nucleotide-binding site-leucine-rich repeat structure, similar to many previously identified R genes. Most importantly, Rxo1 functions after transfer as a transgene to rice, demonstrating the feasibility of nonhost R gene transfer between cereals and providing a valuable tool for controlling bacterial streak disease.

Genome Comparison of Human and Non-Human Malaria Parasites Reveals Species Subset-Specific Genes Potentially Linked to Human Disease

PubMed Central

Frech, Christian; Chen, Nansheng

2011-01-01

Genes underlying important phenotypic differences between Plasmodium species, the causative agents of malaria, are frequently found in only a subset of species and cluster at dynamically evolving subtelomeric regions of chromosomes. We hypothesized that chromosome-internal regions of Plasmodium genomes harbour additional species subset-specific genes that underlie differences in human pathogenicity, human-to-human transmissibility, and human virulence. We combined sequence similarity searches with synteny block analyses to identify species subset-specific genes in chromosome-internal regions of six published Plasmodium genomes, including Plasmodium falciparum, Plasmodium vivax, Plasmodium knowlesi, Plasmodium yoelii, Plasmodium berghei, and Plasmodium chabaudi. To improve comparative analysis, we first revised incorrectly annotated gene models using homology-based gene finders and examined putative subset-specific genes within syntenic contexts. Confirmed subset-specific genes were then analyzed for their role in biological pathways and examined for molecular functions using publicly available databases. We identified 16 genes that are well conserved in the three primate parasites but not found in rodent parasites, including three key enzymes of the thiamine (vitamin B1) biosynthesis pathway. Thirteen genes were found to be present in both human parasites but absent in the monkey parasite P. knowlesi, including genes specifically upregulated in sporozoites or gametocytes that could be linked to parasite transmission success between humans. Furthermore, we propose 15 chromosome-internal P. falciparum-specific genes as new candidate genes underlying increased human virulence and detected a currently uncharacterized cluster of P. vivax-specific genes on chromosome 6 likely involved in erythrocyte invasion. In conclusion, Plasmodium species harbour many chromosome-internal differences in the form of protein-coding genes, some of which are potentially linked to human

Common and specific signatures of gene expression and protein-protein interactions in autoimmune diseases.

PubMed

Tuller, T; Atar, S; Ruppin, E; Gurevich, M; Achiron, A

2013-03-01

The aim of this study is to understand intracellular regulatory mechanisms in peripheral blood mononuclear cells (PBMCs), which are either common to many autoimmune diseases or specific to some of them. We incorporated large-scale data such as protein-protein interactions, gene expression and demographical information of hundreds of patients and healthy subjects, related to six autoimmune diseases with available large-scale gene expression measurements: multiple sclerosis (MS), systemic lupus erythematosus (SLE), juvenile rheumatoid arthritis (JRA), Crohn's disease (CD), ulcerative colitis (UC) and type 1 diabetes (T1D). These data were analyzed concurrently by statistical and systems biology approaches tailored for this purpose. We found that chemokines such as CXCL1-3, 5, 6 and the interleukin (IL) IL8 tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In addition, the anti-apoptotic gene BCL3, interferon-γ (IFNG), and the vitamin D receptor (VDR) gene physically interact with significantly many genes that tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In general, similar cellular processes tend to be differentially expressed in PBMC in the analyzed autoimmune diseases. Specifically, the cellular processes related to cell proliferation (for example, epidermal growth factor, platelet-derived growth factor, nuclear factor-κB, Wnt/β-catenin signaling, stress-activated protein kinase c-Jun NH2-terminal kinase), inflammatory response (for example, interleukins IL2 and IL6, the cytokine granulocyte-macrophage colony-stimulating factor and the B-cell receptor), general signaling cascades (for example, mitogen-activated protein kinase, extracellular signal-regulated kinase, p38 and TRK) and apoptosis are activated in most of the analyzed autoimmune diseases. However, our results suggest that in each of the analyzed diseases, apoptosis and chemotaxis are activated via

A Penalized Robust Method for Identifying Gene-Environment Interactions

PubMed Central

Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

2015-01-01

In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model mis-specification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications. PMID:24616063

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).

Genome-wide identification and quantification of cis- and trans-regulated genes responding to Marek's disease virus infection via analysis of allele-specific expression

USDA-ARS?s Scientific Manuscript database

Background Marek’s disease (MD) is a commercially important neoplastic disease of chickens caused by the Marek’s disease virus (MDV), a naturally-occurring oncogenic alphaherpesvirus. We attempted to identify genes conferring MD resistance, by completing a genome-wide screen for allele-specific expr...

A maize resistance gene functions against bacterial streak disease in rice

PubMed Central

Zhao, Bingyu; Lin, Xinghua; Poland, Jesse; Trick, Harold; Leach, Jan; Hulbert, Scot

2005-01-01

Although cereal crops all belong to the grass family (Poacea), most of their diseases are specific to a particular species. Thus, a given cereal species is typically resistant to diseases of other grasses, and this nonhost resistance is generally stable. To determine the feasibility of transferring nonhost resistance genes (R genes) between distantly related grasses to control specific diseases, we identified a maize R gene that recognizes a rice pathogen, Xanthomonas oryzae pv. oryzicola, which causes bacterial streak disease. Bacterial streak is an important disease of rice in Asia, and no simply inherited sources of resistance have been identified in rice. Although X. o. pv. oryzicola does not cause disease on maize, we identified a maize gene, Rxo1, that conditions a resistance reaction to a diverse collection of pathogen strains. Surprisingly, Rxo1 also controls resistance to the unrelated pathogen Burkholderia andropogonis, which causes bacterial stripe of sorghum and maize. The same gene thus controls resistance reactions to both pathogens and nonpathogens of maize. Rxo1 has a nucleotide-binding site-leucine-rich repeat structure, similar to many previously identified R genes. Most importantly, Rxo1 functions after transfer as a transgene to rice, demonstrating the feasibility of nonhost R gene transfer between cereals and providing a valuable tool for controlling bacterial streak disease. PMID:16230639

Male specific genes from dioecious white campion identified by fluorescent differential display.

PubMed

Scutt, Charles P; Jenkins, Tom; Furuya, Masaki; Gilmartin, Philip M

2002-05-01

Fluorescent differential display (FDD) has been used to screen for cDNAs that are differentially up-regulated in male flowers of the dioecious plant Silene latifolia in which an X/Y chromosome system of sex determination operates. To adapt FDD to the cloning of large numbers of differential cDNAs, a novel method of confirming the differential expression of these has been devised. FDD gels were Southern electro-blotted and probed with mixtures of individual cDNA clones derived from different FDD product ligation reactions. These Southern blots were then stripped and re-probed with further mixtures of individual cloned FDD products to identify the maximum number of recombinant clones carrying the true differential amplification products. Of 135 differential bands identified by FDD, 56 differential amplification products were confirmed; these represent 23 unique differentially expressed genes as determined by virtual Northern analysis and two genes expressed at or below the level of detection by virtual Northern analysis. These two low expressed genes show bands of hybridization on genomic Southern blots that are specific to male plants, indicating that they are derived from, or closely related to, Y chromosome genes.

High-throughput identification of antigen-specific TCRs by TCR gene capture.

PubMed

Linnemann, Carsten; Heemskerk, Bianca; Kvistborg, Pia; Kluin, Roelof J C; Bolotin, Dmitriy A; Chen, Xiaojing; Bresser, Kaspar; Nieuwland, Marja; Schotte, Remko; Michels, Samira; Gomez-Eerland, Raquel; Jahn, Lorenz; Hombrink, Pleun; Legrand, Nicolas; Shu, Chengyi Jenny; Mamedov, Ilgar Z; Velds, Arno; Blank, Christian U; Haanen, John B A G; Turchaninova, Maria A; Kerkhoven, Ron M; Spits, Hergen; Hadrup, Sine Reker; Heemskerk, Mirjam H M; Blankenstein, Thomas; Chudakov, Dmitriy M; Bendle, Gavin M; Schumacher, Ton N M

2013-11-01

The transfer of T cell receptor (TCR) genes into patient T cells is a promising approach for the treatment of both viral infections and cancer. Although efficient methods exist to identify antibodies for the treatment of these diseases, comparable strategies to identify TCRs have been lacking. We have developed a high-throughput DNA-based strategy to identify TCR sequences by the capture and sequencing of genomic DNA fragments encoding the TCR genes. We establish the value of this approach by assembling a large library of cancer germline tumor antigen-reactive TCRs. Furthermore, by exploiting the quantitative nature of TCR gene capture, we show the feasibility of identifying antigen-specific TCRs in oligoclonal T cell populations from either human material or TCR-humanized mice. Finally, we demonstrate the ability to identify tumor-reactive TCRs within intratumoral T cell subsets without knowledge of antigen specificities, which may be the first step toward the development of autologous TCR gene therapy to target patient-specific neoantigens in human cancer.

Chamber Specific Gene Expression Landscape of the Zebrafish Heart

PubMed Central

Singh, Angom Ramcharan; Sivadas, Ambily; Sabharwal, Ankit; Vellarikal, Shamsudheen Karuthedath; Jayarajan, Rijith; Verma, Ankit; Kapoor, Shruti; Joshi, Adita; Scaria, Vinod; Sivasubbu, Sridhar

2016-01-01

The organization of structure and function of cardiac chambers in vertebrates is defined by chamber-specific distinct gene expression. This peculiarity and uniqueness of the genetic signatures demonstrates functional resolution attributed to the different chambers of the heart. Altered expression of the cardiac chamber genes can lead to individual chamber related dysfunctions and disease patho-physiologies. Information on transcriptional repertoire of cardiac compartments is important to understand the spectrum of chamber specific anomalies. We have carried out a genome wide transcriptome profiling study of the three cardiac chambers in the zebrafish heart using RNA sequencing. We have captured the gene expression patterns of 13,396 protein coding genes in the three cardiac chambers—atrium, ventricle and bulbus arteriosus. Of these, 7,260 known protein coding genes are highly expressed (≥10 FPKM) in the zebrafish heart. Thus, this study represents nearly an all-inclusive information on the zebrafish cardiac transcriptome. In this study, a total of 96 differentially expressed genes across the three cardiac chambers in zebrafish were identified. The atrium, ventricle and bulbus arteriosus displayed 20, 32 and 44 uniquely expressing genes respectively. We validated the expression of predicted chamber-restricted genes using independent semi-quantitative and qualitative experimental techniques. In addition, we identified 23 putative novel protein coding genes that are specifically restricted to the ventricle and not in the atrium or bulbus arteriosus. In our knowledge, these 23 novel genes have either not been investigated in detail or are sparsely studied. The transcriptome identified in this study includes 68 differentially expressing zebrafish cardiac chamber genes that have a human ortholog. We also carried out spatiotemporal gene expression profiling of the 96 differentially expressed genes throughout the three cardiac chambers in 11 developmental stages and 6

Defining the human macula transcriptome and candidate retinal disease genes using EyeSAGE.

PubMed

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

2006-06-01

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). 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. 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. 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.

Maternal Germline-Specific Genes in the Asian Malaria Mosquito Anopheles stephensi: Characterization and Application for Disease Control

PubMed Central

Biedler, James K.; Qi, Yumin; Pledger, David; Macias, Vanessa M.; James, Anthony A.; Tu, Zhijian

2014-01-01

Anopheles stephensi is a principal vector of urban malaria on the Indian subcontinent and an emerging model for molecular and genetic studies of mosquito biology. To enhance our understanding of female mosquito reproduction, and to develop new tools for basic research and for genetic strategies to control mosquito-borne infectious diseases, we identified 79 genes that displayed previtellogenic germline-specific expression based on RNA-Seq data generated from 11 life stage–specific and sex-specific samples. Analysis of this gene set provided insights into the biology and evolution of female reproduction. Promoters from two of these candidates, vitellogenin receptor and nanos, were used in independent transgenic cassettes for the expression of artificial microRNAs against suspected mosquito maternal-effect genes, discontinuous actin hexagon and myd88. We show these promoters have early germline-specific expression and demonstrate 73% and 42% knockdown of myd88 and discontinuous actin hexagon mRNA in ovaries 48 hr after blood meal, respectively. Additionally, we demonstrate maternal-specific delivery of mRNA and protein to progeny embryos. We discuss the application of this system of maternal delivery of mRNA/miRNA/protein in research on mosquito reproduction and embryonic development, and for the development of a gene drive system based on maternal-effect dominant embryonic arrest. PMID:25480960

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

PubMed Central

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

2009-01-01

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

Candidate genes for panhypopituitarism identified by gene expression profiling

PubMed Central

Mortensen, Amanda H.; MacDonald, James W.; Ghosh, Debashis

2011-01-01

Mutations in the transcription factors PROP1 and PIT1 (POU1F1) lead to pituitary hormone deficiency and hypopituitarism in mice and humans. The dysmorphology of developing Prop1 mutant pituitaries readily distinguishes them from those of Pit1 mutants and normal mice. This and other features suggest that Prop1 controls the expression of genes besides Pit1 that are important for pituitary cell migration, survival, and differentiation. To identify genes involved in these processes we used microarray analysis of gene expression to compare pituitary RNA from newborn Prop1 and Pit1 mutants and wild-type littermates. Significant differences in gene expression were noted between each mutant and their normal littermates, as well as between Prop1 and Pit1 mutants. Otx2, a gene critical for normal eye and pituitary development in humans and mice, exhibited elevated expression specifically in Prop1 mutant pituitaries. We report the spatial and temporal regulation of Otx2 in normal mice and Prop1 mutants, and the results suggest Otx2 could influence pituitary development by affecting signaling from the ventral diencephalon and regulation of gene expression in Rathke's pouch. The discovery that Otx2 expression is affected by Prop1 deficiency provides support for our hypothesis that identifying molecular differences in mutants will contribute to understanding the molecular mechanisms that control pituitary organogenesis and lead to human pituitary disease. PMID:21828248

The genetics of alcoholism: identifying specific genes through family studies.

PubMed

Edenberg, Howard J; Foroud, Tatiana

2006-09-01

Alcoholism is a complex disorder with both genetic and environmental risk factors. Studies in humans have begun to elucidate the genetic underpinnings of the risk for alcoholism. Here we briefly review strategies for identifying individual genes in which variations affect the risk for alcoholism and related phenotypes, in the context of one large study that has successfully identified such genes. The Collaborative Study on the Genetics of Alcoholism (COGA) is a family-based study that has collected detailed phenotypic data on individuals in families with multiple alcoholic members. A genome-wide linkage approach led to the identification of chromosomal regions containing genes that influenced alcoholism risk and related phenotypes. Subsequently, single nucleotide polymorphisms (SNPs) were genotyped in positional candidate genes located within the linked chromosomal regions, and analyzed for association with these phenotypes. Using this sequential approach, COGA has detected association with GABRA2, CHRM2 and ADH4; these associations have all been replicated by other researchers. COGA has detected association to additional genes including GABRG3, TAS2R16, SNCA, OPRK1 and PDYN, results that are awaiting confirmation. These successes demonstrate that genes contributing to the risk for alcoholism can be reliably identified using human subjects.

Type 2 diabetes mellitus disease risk genes identified by genome wide copy number variation scan in normal populations.

PubMed

Prabhanjan, Manasa; Suresh, Raviraj V; Murthy, Megha N; Ramachandra, Nallur B

2016-03-01

To identify the role of copy number variations (CNVs) on disease risk genes and its effect on disease phenotypes in type 2 diabetes mellitus (T2DM) in 12 random populations using high throughput arrays. CNV analysis was carried out on a total of 1715 individuals from 12 populations, from ArrayExpress Archive of the European Bioinformatics Institute along with our subjects using Affymetrix Genome Wide SNP 6.0 array. CNV effect on T2DM genes were analyzed using several bioinformatics tools and a molecular protein interaction network was constructed to identify the disease mechanism altered by the CNVs. Analysis showed 34.4% of the total population to be under CNV burden for T2DM, with 83 disease causal and associated genes being under CNV influence. Hotspots were identified on chromosomes 22, 12, 6, 19 and 11.Overlap studies with case cohorts revealed significant disease risk genes such as EGFR, E2F1, PPP1R3A, HLA and TSPAN8. CNVs play a significant role in predisposing T2DM in normal cohorts and contribute to the phenotypic effects. Thus, CNVs should be considered as one of the major contributors in predisposition of the disease. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

Allele-specific DNA methylation of disease susceptibility genes in Japanese patients with inflammatory bowel disease.

PubMed

Chiba, Hirofumi; Kakuta, Yoichi; Kinouchi, Yoshitaka; Kawai, Yosuke; Watanabe, Kazuhiro; Nagao, Munenori; Naito, Takeo; Onodera, Motoyuki; Moroi, Rintaro; Kuroha, Masatake; Kanazawa, Yoshitake; Kimura, Tomoya; Shiga, Hisashi; Endo, Katsuya; Negoro, Kenichi; Nagasaki, Masao; Unno, Michiaki; Shimosegawa, Tooru

2018-01-01

Inflammatory bowel disease (IBD) has an unknown etiology; however, accumulating evidence suggests that IBD is a multifactorial disease influenced by a combination of genetic and environmental factors. The influence of genetic variants on DNA methylation in cis and cis effects on expression have been demonstrated. We hypothesized that IBD susceptibility single-nucleotide polymorphisms (SNPs) regulate susceptibility gene expressions in cis by regulating DNA methylation around SNPs. For this, we determined cis-regulated allele-specific DNA methylation (ASM) around IBD susceptibility genes in CD4+ effector/memory T cells (Tem) in lamina propria mononuclear cells (LPMCs) in patients with IBD and examined the association between the ASM SNP genotype and neighboring susceptibility gene expressions. CD4+ effector/memory T cells (Tem) were isolated from LPMCs in 15 Japanese IBD patients (ten Crohn's disease [CD] and five ulcerative colitis [UC] patients). ASM analysis was performed by methylation-sensitive SNP array analysis. We defined ASM as a changing average relative allele score ([Formula: see text]) >0.1 after digestion by methylation-sensitive restriction enzymes. Among SNPs showing [Formula: see text] >0.1, we extracted the probes located on tag-SNPs of 200 IBD susceptibility loci and around IBD susceptibility genes as candidate ASM SNPs. To validate ASM, bisulfite-pyrosequencing was performed. Transcriptome analysis was examined in 11 IBD patients (seven CD and four UC patients). The relation between rs36221701 genotype and neighboring gene expressions were analyzed. We extracted six candidate ASM SNPs around IBD susceptibility genes. The top of [Formula: see text] (0.23) was rs1130368 located on HLA-DQB1. ASM around rs36221701 ([Formula: see text] = 0.14) located near SMAD3 was validated using bisulfite pyrosequencing. The SMAD3 expression was significantly associated with the rs36221701 genotype (p = 0.016). We confirmed the existence of cis-regulated ASM around

Allele-specific DNA methylation of disease susceptibility genes in Japanese patients with inflammatory bowel disease

PubMed Central

Chiba, Hirofumi; Kakuta, Yoichi; Kinouchi, Yoshitaka; Kawai, Yosuke; Watanabe, Kazuhiro; Nagao, Munenori; Naito, Takeo; Onodera, Motoyuki; Moroi, Rintaro; Kuroha, Masatake; Kanazawa, Yoshitake; Kimura, Tomoya; Shiga, Hisashi; Endo, Katsuya; Negoro, Kenichi; Nagasaki, Masao; Unno, Michiaki; Shimosegawa, Tooru

2018-01-01

Background Inflammatory bowel disease (IBD) has an unknown etiology; however, accumulating evidence suggests that IBD is a multifactorial disease influenced by a combination of genetic and environmental factors. The influence of genetic variants on DNA methylation in cis and cis effects on expression have been demonstrated. We hypothesized that IBD susceptibility single-nucleotide polymorphisms (SNPs) regulate susceptibility gene expressions in cis by regulating DNA methylation around SNPs. For this, we determined cis-regulated allele-specific DNA methylation (ASM) around IBD susceptibility genes in CD4+ effector/memory T cells (Tem) in lamina propria mononuclear cells (LPMCs) in patients with IBD and examined the association between the ASM SNP genotype and neighboring susceptibility gene expressions. Methods CD4+ effector/memory T cells (Tem) were isolated from LPMCs in 15 Japanese IBD patients (ten Crohn's disease [CD] and five ulcerative colitis [UC] patients). ASM analysis was performed by methylation-sensitive SNP array analysis. We defined ASM as a changing average relative allele score (ΔRAS¯) >0.1 after digestion by methylation-sensitive restriction enzymes. Among SNPs showing ΔRAS¯ >0.1, we extracted the probes located on tag-SNPs of 200 IBD susceptibility loci and around IBD susceptibility genes as candidate ASM SNPs. To validate ASM, bisulfite-pyrosequencing was performed. Transcriptome analysis was examined in 11 IBD patients (seven CD and four UC patients). The relation between rs36221701 genotype and neighboring gene expressions were analyzed. Results We extracted six candidate ASM SNPs around IBD susceptibility genes. The top of ΔRAS¯ (0.23) was rs1130368 located on HLA-DQB1. ASM around rs36221701 (ΔRAS¯ = 0.14) located near SMAD3 was validated using bisulfite pyrosequencing. The SMAD3 expression was significantly associated with the rs36221701 genotype (p = 0.016). Conclusions We confirmed the existence of cis-regulated ASM around IBD

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

The promise of discovering population-specific disease-associated genes in South Asia.

PubMed

Nakatsuka, Nathan; Moorjani, Priya; Rai, Niraj; Sarkar, Biswanath; Tandon, Arti; Patterson, Nick; Bhavani, Gandham SriLakshmi; Girisha, Katta Mohan; Mustak, Mohammed S; Srinivasan, Sudha; Kaushik, Amit; Vahab, Saadi Abdul; Jagadeesh, Sujatha M; Satyamoorthy, Kapaettu; Singh, Lalji; Reich, David; Thangaraj, Kumarasamy

2017-09-01

The more than 1.5 billion people who live in South Asia are correctly viewed not as a single large population but as many small endogamous groups. We assembled genome-wide data from over 2,800 individuals from over 260 distinct South Asian groups. We identified 81 unique groups, 14 of which had estimated census sizes of more than 1 million, that descend from founder events more extreme than those in Ashkenazi Jews and Finns, both of which have high rates of recessive disease due to founder events. We identified multiple examples of recessive diseases in South Asia that are the result of such founder events. This study highlights an underappreciated opportunity for decreasing disease burden among South Asians through discovery of and testing for recessive disease-associated genes.

Genomic convergence to identify candidate genes for Alzheimer disease on chromosome 10

PubMed Central

Liang, Xueying; Slifer, Michael; Martin, Eden R.; Schnetz-Boutaud, Nathalie; Bartlett, Jackie; Anderson, Brent; Züchner, Stephan; Gwirtsman, Harry; Gilbert, John R.; Pericak-Vance, Margaret A.; Haines, Jonathan L.

2009-01-01

A broad region of chromosome 10 (chr10) has engendered continued interest in the etiology of late-onset Alzheimer Disease (LOAD) from both linkage and candidate gene studies. However, there is a very extensive heterogeneity on chr10. We converged linkage analysis and gene expression data using the concept of genomic convergence that suggests that genes showing positive results across multiple different data types are more likely to be involved in AD. We identified and examined 28 genes on chr10 for association with AD in a Caucasian case-control dataset of 506 cases and 558 controls with substantial clinical information. The cases were all LOAD (minimum age at onset ≥ 60 years). Both single marker and haplotypic associations were tested in the overall dataset and 8 subsets defined by age, gender, ApoE and clinical status. PTPLA showed allelic, genotypic and haplotypic association in the overall dataset. SORCS1 was significant in the overall data sets (p=0.0025) and most significant in the female subset (allelic association p=0.00002, a 3-locus haplotype had p=0.0005). Odds Ratio of SORCS1 in the female subset was 1.7 (p<0.0001). SORCS1 is an interesting candidate gene involved in the Aβ pathway. Therefore, genetic variations in PTPLA and SORCS1 may be associated and have modest effect to the risk of AD by affecting Aβ pathway. The replication of the effect of these genes in different study populations and search for susceptible variants and functional studies of these genes are necessary to get a better understanding of the roles of the genes in Alzheimer disease. PMID:19241460

Increased Transcript Complexity in Genes Associated with Chronic Obstructive Pulmonary Disease

PubMed Central

Lackey, Lela; McArthur, Evonne; Laederach, Alain

2015-01-01

Genome-wide association studies aim to correlate genotype with phenotype. Many common diseases including Type II diabetes, Alzheimer’s, Parkinson’s and Chronic Obstructive Pulmonary Disease (COPD) are complex genetic traits with hundreds of different loci that are associated with varied disease risk. Identifying common features in the genes associated with each disease remains a challenge. Furthermore, the role of post-transcriptional regulation, and in particular alternative splicing, is still poorly understood in most multigenic diseases. We therefore compiled comprehensive lists of genes associated with Type II diabetes, Alzheimer’s, Parkinson’s and COPD in an attempt to identify common features of their corresponding mRNA transcripts within each gene set. The SERPINA1 gene is a well-recognized genetic risk factor of COPD and it produces 11 transcript variants, which is exceptional for a human gene. This led us to hypothesize that other genes associated with COPD, and complex disorders in general, are highly transcriptionally diverse. We found that COPD-associated genes have a statistically significant enrichment in transcript complexity stemming from a disproportionately high level of alternative splicing, however, Type II Diabetes, Alzheimer’s and Parkinson’s disease genes were not significantly enriched. We also identified a subset of transcriptionally complex COPD-associated genes (~40%) that are differentially expressed between mild, moderate and severe COPD. Although the genes associated with other lung diseases are not extensively documented, we found preliminary data that idiopathic pulmonary disease genes, but not cystic fibrosis modulators, are also more transcriptionally complex. Interestingly, complex COPD transcripts are more often the product of alternative acceptor site usage. To verify the biological importance of these alternative transcripts, we used RNA-sequencing analyses to determine that COPD-associated genes are frequently

MethylMix 2.0: an R package for identifying DNA methylation genes. | Office of Cancer Genomics

Cancer.gov

DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is a major mechanism of gene expression deregulation in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. We developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes.

Specific PCR primers directed to identify cryI and cryIII genes within a Bacillus thuringiensis strain collection.

PubMed Central

Cerón, J; Ortíz, A; Quintero, R; Güereca, L; Bravo, A

1995-01-01

In this paper we describe a PCR strategy that can be used to rapidly identify Bacillus thuringiensis strains that harbor any of the known cryI or cryIII genes. Four general PCR primers which amplify DNA fragments from the known cryI or cryIII genes were selected from conserved regions. Once a strain was identified as an organism that contains a particular type of cry gene, it could be easily characterized by performing additional PCR with specific cryI and cryIII primers selected from variable regions. The method described in this paper can be used to identify the 10 different cryI genes and the five different cryIII genes. One feature of this screening method is that each cry gene is expected to produce a PCR product having a precise molecular weight. The genes which produce PCR products having different sizes probably represent strains that harbor a potentially novel cry gene. Finally, we present evidence that novel crystal genes can be identified by the method described in this paper. PMID:8526493

Immunogenetic mechanisms leading to thyroid autoimmunity: recent advances in identifying susceptibility genes and regions.

PubMed

Brand, Oliver J; Gough, Stephen C L

2011-12-01

The autoimmune thyroid diseases (AITD) include Graves' disease (GD) and Hashimoto's 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.

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 Hashimoto’s 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

Locus-specific gene repositioning in prostate cancer

PubMed Central

Leshner, Marc; Devine, Michelle; Roloff, Gregory W.; True, Lawrence D.; Misteli, Tom; Meaburn, Karen J.

2016-01-01

Genes occupy preferred spatial positions within interphase cell nuclei. However, positioning patterns are not an innate feature of a locus, and genes can alter their localization in response to physiological and pathological changes. Here we screen the radial positioning patterns of 40 genes in normal, hyperplasic, and malignant human prostate tissues. We find that the overall spatial organization of the genome in prostate tissue is largely conserved among individuals. We identify three genes whose nuclear positions are robustly altered in neoplastic prostate tissues. FLI1 and MMP9 position differently in prostate cancer than in normal tissue and prostate hyperplasia, whereas MMP2 is repositioned in both prostate cancer and hyperplasia. Our data point to locus-specific reorganization of the genome during prostate disease. PMID:26564800

Gene expression profiling to identify the toxicities and potentially relevant human disease outcomes associated with environmental heavy metal exposure.

PubMed

Korashy, Hesham M; Attafi, Ibraheem M; Famulski, Konrad S; Bakheet, Saleh A; Hafez, Mohammed M; Alsaad, Abdulaziz M S; Al-Ghadeer, Abdul Rahman M

2017-02-01

Heavy metals are the most commonly encountered toxic substances that increase susceptibility to various diseases after prolonged exposure. We have previously shown that healthy volunteers living near a mining area had significant contamination with heavy metals associated with significant changes in the expression of some detoxifying genes, xenobiotic metabolizing enzymes, and DNA repair genes. However, alterations of most of the molecular target genes associated with diseases are still unknown. Thus, the aims of this study were to (a) evaluate the gene expression profile and (b) identify the toxicities and potentially relevant human disease outcomes associated with long-term human exposure to environmental heavy metals in mining area using microarray analysis. For this purpose, 40 healthy male volunteers who were residents of a heavy metal-polluted area (Mahd Al-Dhahab city, Saudi Arabia) and 20 healthy male volunteers who were residents of a non-heavy metal-polluted area were included in the study. Total RNA was isolated from whole blood using PAXgene Blood RNA tubes and then reversed transcribed and hybridized to the gene array using the Affymetrix U219 GeneChip. Microarray analysis showed about 2129 genes were identified and differentially altered, among which a shared set of 425 genes was differentially expressed in the heavy metal-exposed groups. Ingenuity pathway analysis revealed that the most altered gene-regulated diseases in heavy metal-exposed groups included hematological and developmental disorders and mostly renal and urological diseases. Quantitative real-time polymerase chain reaction closely matched the microarray data for some genes tested. Importantly, changes in gene-related diseases were attributed to alterations in the genes encoded for protein synthesis. Renal and urological diseases were the diseases that were most frequently associated with the heavy metal-exposed group. Therefore, there is a need for further studies to validate these

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

PubMed

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

2016-02-01

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

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

Joint genetic analysis of hippocampal size in mouse and human identifies a novel gene linked to neurodegenerative disease.

PubMed

Ashbrook, David G; Williams, Robert W; Lu, Lu; Stein, Jason L; Hibar, Derrek P; Nichols, Thomas E; Medland, Sarah E; Thompson, Paul M; Hager, Reinmar

2014-10-03

Variation in hippocampal volume has been linked to significant differences in memory, behavior, and cognition among individuals. To identify genetic variants underlying such differences and associated disease phenotypes, multinational consortia such as ENIGMA have used large magnetic resonance imaging (MRI) data sets in human GWAS studies. In addition, mapping studies in mouse model systems have identified genetic variants for brain structure variation with great power. A key challenge is to understand how genetically based differences in brain structure lead to the propensity to develop specific neurological disorders. We combine the largest human GWAS of brain structure with the largest mammalian model system, the BXD recombinant inbred mouse population, to identify novel genetic targets influencing brain structure variation that are linked to increased risk for neurological disorders. We first use a novel cross-species, comparative analysis using mouse and human genetic data to identify a candidate gene, MGST3, associated with adult hippocampus size in both systems. We then establish the coregulation and function of this gene in a comprehensive systems-analysis. We find that MGST3 is associated with hippocampus size and is linked to a group of neurodegenerative disorders, such as Alzheimer's.

Identification of the soybean HyPRP family and specific gene response to Asian soybean rust disease.

PubMed

Neto, Lauro Bücker; de Oliveira, Rafael Rodrigues; Wiebke-Strohm, Beatriz; Bencke, Marta; Weber, Ricardo Luís Mayer; Cabreira, Caroline; Abdelnoor, Ricardo Vilela; Marcelino, Francismar Correa; Zanettini, Maria Helena Bodanese; Passaglia, Luciane Maria Pereira

2013-07-01

Soybean [Glycine max (L.) Merril], one of the most important crop species in the world, is very susceptible to abiotic and biotic stress. Soybean plants have developed a variety of molecular mechanisms that help them survive stressful conditions. Hybrid proline-rich proteins (HyPRPs) constitute a family of cell-wall proteins with a variable N-terminal domain and conserved C-terminal domain that is phylogenetically related to non-specific lipid transfer proteins. Members of the HyPRP family are involved in basic cellular processes and their expression and activity are modulated by environmental factors. In this study, microarray analysis and real time RT-qPCR were used to identify putative HyPRP genes in the soybean genome and to assess their expression in different plant tissues. Some of the genes were also analyzed by time-course real time RT-qPCR in response to infection by Phakopsora pachyrhizi, the causal agent of Asian soybean rust disease. Our findings indicate that the time of induction of a defense pathway is crucial in triggering the soybean resistance response to P. pachyrhizi. This is the first study to identify the soybean HyPRP group B family and to analyze disease-responsive GmHyPRP during infection by P. pachyrhizi.

Next-generation sequencing to identify candidate genes and develop diagnostic markers for a novel Phytophthora resistance gene, RpsHC18, in soybean.

PubMed

Zhong, Chao; Sun, Suli; Li, Yinping; Duan, Canxing; Zhu, Zhendong

2018-03-01

A novel Phytophthora sojae resistance gene RpsHC18 was identified and finely mapped on soybean chromosome 3. Two NBS-LRR candidate genes were identified and two diagnostic markers of RpsHC18 were developed. Phytophthora root rot caused by Phytophthora sojae is a destructive disease of soybean. The most effective disease-control strategy is to deploy resistant cultivars carrying Phytophthora-resistant Rps genes. The soybean cultivar Huachun 18 has a broad and distinct resistance spectrum to 12 P. sojae isolates. Quantitative trait loci sequencing (QTL-seq), based on the whole-genome resequencing (WGRS) of two extreme resistant and susceptible phenotype bulks from an F 2:3 population, was performed, and one 767-kb genomic region with ΔSNP-index ≥ 0.9 on chromosome 3 was identified as the RpsHC18 candidate region in Huachun 18. The candidate region was reduced to a 146-kb region by fine mapping. Nonsynonymous SNP and haplotype analyses were carried out in the 146-kb region among ten soybean genotypes using WGRS. Four specific nonsynonymous SNPs were identified in two nucleotide-binding sites-leucine-rich repeat (NBS-LRR) genes, RpsHC18-NBL1 and RpsHC18-NBL2, which were considered to be the candidate genes. Finally, one specific SNP marker in each candidate gene was successfully developed using a tetra-primer ARMS-PCR assay, and the two markers were verified to be specific for RpsHC18 and to effectively distinguish other known Rps genes. In this study, we applied an integrated genomic-based strategy combining WGRS with traditional genetic mapping to identify RpsHC18 candidate genes and develop diagnostic markers. These results suggest that next-generation sequencing is a precise, rapid and cost-effective way to identify candidate genes and develop diagnostic markers, and it can accelerate Rps gene cloning and marker-assisted selection for breeding of P. sojae-resistant soybean cultivars.

Gene-Based Genome-Wide Association Analysis in European and Asian Populations Identified Novel Genes for Rheumatoid Arthritis.

PubMed

Zhu, Hong; Xia, Wei; Mo, Xing-Bo; Lin, Xiang; Qiu, Ying-Hua; Yi, Neng-Jun; Zhang, Yong-Hong; Deng, Fei-Yan; Lei, Shu-Feng

2016-01-01

Rheumatoid arthritis (RA) is a complex autoimmune disease. Using a gene-based association research strategy, the present study aims to detect unknown susceptibility to RA and to address the ethnic differences in genetic susceptibility to RA between European and Asian populations. Gene-based association analyses were performed with KGG 2.5 by using publicly available large RA datasets (14,361 RA cases and 43,923 controls of European subjects, 4,873 RA cases and 17,642 controls of Asian Subjects). For the newly identified RA-associated genes, gene set enrichment analyses and protein-protein interactions analyses were carried out with DAVID and STRING version 10.0, respectively. Differential expression verification was conducted using 4 GEO datasets. The expression levels of three selected 'highly verified' genes were measured by ELISA among our in-house RA cases and controls. A total of 221 RA-associated genes were newly identified by gene-based association study, including 71'overlapped', 76 'European-specific' and 74 'Asian-specific' genes. Among them, 105 genes had significant differential expressions between RA patients and health controls at least in one dataset, especially for 20 genes including 11 'overlapped' (ABCF1, FLOT1, HLA-F, IER3, TUBB, ZKSCAN4, BTN3A3, HSP90AB1, CUTA, BRD2, HLA-DMA), 5 'European-specific' (PHTF1, RPS18, BAK1, TNFRSF14, SUOX) and 4 'Asian-specific' (RNASET2, HFE, BTN2A2, MAPK13) genes whose differential expressions were significant at least in three datasets. The protein expressions of two selected genes FLOT1 (P value = 1.70E-02) and HLA-DMA (P value = 4.70E-02) in plasma were significantly different in our in-house samples. Our study identified 221 novel RA-associated genes and especially highlighted the importance of 20 candidate genes on RA. The results addressed ethnic genetic background differences for RA susceptibility between European and Asian populations and detected a long list of overlapped or ethnic specific RA genes. The

Identification of Genes Expressed in Premalignant Breast Disease by Microscopy-Directed Cloning

NASA Astrophysics Data System (ADS)

Jensen, Roy A.; Page, David L.; Holt, Jeffrey T.

1994-09-01

Histopathologic study of human breast biopsy samples has identified specific lesions which are associated with a high risk of development of invasive breast cancer. Presumably, these lesions (collectively termed premalignant breast disease) represent the earliest recognizable morphologic expression of fundamental molecular events that lead to the development of invasive breast cancer. To study molecular events underlying premalignant breast disease, we have developed a method for isolating RNA from histologically identified lesions from frozen human breast tissue. This method specifically obtains mRNA from breast epithelial cells and has identified three genes which are differentially expressed in premalignant breast epithelial lesions. One gene identified by this method is overexpressed in four of five noncomedo ductal carcinoma in situ lesions and appears to be the human homologue of the gene encoding the M2 subunit of ribonucleotide reductase, an enzyme involved in DNA synthesis.

Genome-wide histone state profiling of fibroblasts from the opossum, Monodelphis domestica, identifies the first marsupial-specific imprinted gene

PubMed Central

2014-01-01

Background Imprinted genes have been extensively documented in eutherian mammals and found to exhibit significant interspecific variation in the suites of genes that are imprinted and in their regulation between tissues and developmental stages. Much less is known about imprinted loci in metatherian (marsupial) mammals, wherein studies have been limited to a small number of genes previously known to be imprinted in eutherians. We describe the first ab initio search for imprinted marsupial genes, in fibroblasts from the opossum, Monodelphis domestica, based on a genome-wide ChIP-seq strategy to identify promoters that are simultaneously marked by mutually exclusive, transcriptionally opposing histone modifications. Results We identified a novel imprinted gene (Meis1) and two additional monoallelically expressed genes, one of which (Cstb) showed allele-specific, but non-imprinted expression. Imprinted vs. allele-specific expression could not be resolved for the third monoallelically expressed gene (Rpl17). Transcriptionally opposing histone modifications H3K4me3, H3K9Ac, and H3K9me3 were found at the promoters of all three genes, but differential DNA methylation was not detected at CpG islands at any of these promoters. Conclusions In generating the first genome-wide histone modification profiles for a marsupial, we identified the first gene that is imprinted in a marsupial but not in eutherian mammals. This outcome demonstrates the practicality of an ab initio discovery strategy and implicates histone modification, but not differential DNA methylation, as a conserved mechanism for marking imprinted genes in all therian mammals. Our findings suggest that marsupials use multiple epigenetic mechanisms for imprinting and support the concept that lineage-specific selective forces can produce sets of imprinted genes that differ between metatherian and eutherian lines. PMID:24484454

Distinct ontogenic and regional expressions of newly identified Cajal-Retzius cell-specific genes during neocorticogenesis.

PubMed

Yamazaki, Hiroshi; Sekiguchi, Mariko; Takamatsu, Masako; Tanabe, Yasuto; Nakanishi, Shigetada

2004-10-05

Cajal-Retzius (CR) cells are early-generated transient neurons and are important in the regulation of cortical neuronal migration and cortical laminar formation. Molecular entities characterizing the CR cell identity, however, remain largely elusive. We purified mouse cortical CR cells expressing GFP to homogeneity by fluorescence-activated cell sorting and examined a genome-wide expression profile of cortical CR cells at embryonic and postnatal periods. We identified 49 genes that exceeded hybridization signals by >10-fold in CR cells compared with non-CR cells at embryonic day 13.5, postnatal day 2, or both. Among these CR cell-specific genes, 25 genes, including the CR cell marker genes such as the reelin and calretinin genes, are selectively and highly expressed in both embryonic and postnatal CR cells. These genes, which encode generic properties of CR cell specificity, are eminently characterized as modulatory composites of voltage-dependent calcium channels and sets of functionally related cellular components involved in cell migration, adhesion, and neurite extension. Five genes are highly expressed in CR cells at the early embryonic period and are rapidly down-regulated thereafter. Furthermore, some of these genes have been shown to mark two distinctly different focal regions corresponding to the CR cell origins. At the late prenatal and postnatal periods, 19 genes are selectively up-regulated in CR cells. These genes include functional molecules implicated in synaptic transmission and modulation. CR cells thus strikingly change their cellular phenotypes during cortical development and play a pivotal role in both corticogenesis and cortical circuit maturation.

Joint-specific DNA methylation and transcriptome signatures in rheumatoid arthritis identify distinct pathogenic processes

PubMed Central

Ai, Rizi; Hammaker, Deepa; Boyle, David L.; Morgan, Rachel; Walsh, Alice M.; Fan, Shicai; Firestein, Gary S.; Wang, Wei

2016-01-01

Stratifying patients on the basis of molecular signatures could facilitate development of therapeutics that target pathways specific to a particular disease or tissue location. Previous studies suggest that pathogenesis of rheumatoid arthritis (RA) is similar in all affected joints. Here we show that distinct DNA methylation and transcriptome signatures not only discriminate RA fibroblast-like synoviocytes (FLS) from osteoarthritis FLS, but also distinguish RA FLS isolated from knees and hips. Using genome-wide methods, we show differences between RA knee and hip FLS in the methylation of genes encoding biological pathways, such as IL-6 signalling via JAK-STAT pathway. Furthermore, differentially expressed genes are identified between knee and hip FLS using RNA-sequencing. Double-evidenced genes that are both differentially methylated and expressed include multiple HOX genes. Joint-specific DNA signatures suggest that RA disease mechanisms might vary from joint to joint, thus potentially explaining some of the diversity of drug responses in RA patients. PMID:27282753

Whole genome co-expression analysis of soybean cytochrome P450 genes identifies nodulation-specific P450 monooxygenases

PubMed Central

2010-01-01

Background Cytochrome P450 monooxygenases (P450s) catalyze oxidation of various substrates using oxygen and NAD(P)H. Plant P450s are involved in the biosynthesis of primary and secondary metabolites performing diverse biological functions. The recent availability of the soybean genome sequence allows us to identify and analyze soybean putative P450s at a genome scale. Co-expression analysis using an available soybean microarray and Illumina sequencing data provides clues for functional annotation of these enzymes. This approach is based on the assumption that genes that have similar expression patterns across a set of conditions may have a functional relationship. Results We have identified a total number of 332 full-length P450 genes and 378 pseudogenes from the soybean genome. From the full-length sequences, 195 genes belong to A-type, which could be further divided into 20 families. The remaining 137 genes belong to non-A type P450s and are classified into 28 families. A total of 178 probe sets were found to correspond to P450 genes on the Affymetrix soybean array. Out of these probe sets, 108 represented single genes. Using the 28 publicly available microarray libraries that contain organ-specific information, some tissue-specific P450s were identified. Similarly, stress responsive soybean P450s were retrieved from 99 microarray soybean libraries. We also utilized Illumina transcriptome sequencing technology to analyze the expressions of all 332 soybean P450 genes. This dataset contains total RNAs isolated from nodules, roots, root tips, leaves, flowers, green pods, apical meristem, mock-inoculated and Bradyrhizobium japonicum-infected root hair cells. The tissue-specific expression patterns of these P450 genes were analyzed and the expression of a representative set of genes were confirmed by qRT-PCR. We performed the co-expression analysis on many of the 108 P450 genes on the Affymetrix arrays. First we confirmed that CYP93C5 (an isoflavone synthase gene) is

Vitiligo blood transcriptomics provides new insights into disease mechanisms and identifies potential novel therapeutic targets.

PubMed

Dey-Rao, Rama; Sinha, Animesh A

2017-01-28

Significant gaps remain regarding the pathomechanisms underlying the autoimmune response in vitiligo (VL), where the loss of self-tolerance leads to the targeted killing of melanocytes. Specifically, there is incomplete information regarding alterations in the systemic environment that are relevant to the disease state. We undertook a genome-wide profiling approach to examine gene expression in the peripheral blood of VL patients and healthy controls in the context of our previously published VL-skin gene expression profile. We used several in silico bioinformatics-based analyses to provide new insights into disease mechanisms and suggest novel targets for future therapy. Unsupervised clustering methods of the VL-blood dataset demonstrate a "disease-state"-specific set of co-expressed genes. Ontology enrichment analysis of 99 differentially expressed genes (DEGs) uncovers a down-regulated immune/inflammatory response, B-Cell antigen receptor (BCR) pathways, apoptosis and catabolic processes in VL-blood. There is evidence for both type I and II interferon (IFN) playing a role in VL pathogenesis. We used interactome analysis to identify several key blood associated transcriptional factors (TFs) from within (STAT1, STAT6 and NF-kB), as well as "hidden" (CREB1, MYC, IRF4, IRF1, and TP53) from the dataset that potentially affect disease pathogenesis. The TFs overlap with our reported lesional-skin transcriptional circuitry, underscoring their potential importance to the disease. We also identify a shared VL-blood and -skin transcriptional "hot spot" that maps to chromosome 6, and includes three VL-blood dysregulated genes (PSMB8, PSMB9 and TAP1) described as potential VL-associated genetic susceptibility loci. Finally, we provide bioinformatics-based support for prioritizing dysregulated genes in VL-blood or skin as potential therapeutic targets. We examined the VL-blood transcriptome in context with our (previously published) VL-skin transcriptional profile to address

Mining the Immune Cell Proteome to Identify Ovarian Cancer-Specific Biomarkers

DTIC Science & Technology

2012-03-01

data and are in the process of identifying gene signatures that can be used as biomarkers for the identification of ovarian cancer-specific biomarkers...groups. The groups showed significant difference in age as well as gestational age, which is expected when considering the disease process . Isolation of...MUC4 in intracellular signaling.32 Oligosaccharides attached to the extracellular domains of mucins have also been shown to interact with different

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. © 2011 Wiley-Liss, Inc.

Identifying genome-wide immune gene variation underlying infectious disease in wildlife populations - a next generation sequencing approach in the gopher tortoise.

PubMed

Elbers, Jean P; Brown, Mary B; Taylor, Sabrina S

2018-01-19

Infectious disease is the single greatest threat to taxa such as amphibians (chytrid fungus), bats (white nose syndrome), Tasmanian devils (devil facial tumor disease), and black-footed ferrets (canine distemper virus, plague). Although understanding the genetic basis to disease susceptibility is important for the long-term persistence of these groups, most research has been limited to major-histocompatibility and Toll-like receptor genes. To better understand the genetic basis of infectious disease susceptibility in a species of conservation concern, we sequenced all known/predicted immune response genes (i.e., the immunomes) in 16 Florida gopher tortoises, Gopherus polyphemus. All tortoises produced antibodies against Mycoplasma agassizii (an etiologic agent of infectious upper respiratory tract disease; URTD) and, at the time of sampling, either had (n = 10) or lacked (n = 6) clinical signs. We found several variants associated with URTD clinical status in complement and lectin genes, which may play a role in Mycoplasma immunity. Thirty-five genes deviated from neutrality according to Tajima's D. These genes were enriched in functions relating to macromolecule and protein modifications, which are vital to immune system functioning. These results are suggestive of genetic differences that might contribute to disease severity, a finding that is consistent with other mycoplasmal diseases. This has implications for management because tortoises across their range may possess genetic variation associated with a more severe response to URTD. More generally: 1) this approach demonstrates that a broader consideration of immune genes is better able to identify important variants, and; 2) this data pipeline can be adopted to identify alleles associated with disease susceptibility or resistance in other taxa, and therefore provide information on a population's risk of succumbing to disease, inform translocations to increase genetic variation for disease resistance

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

Defining the Role of Essential Genes in Human Disease

PubMed Central

Robertson, David L.; Hentges, Kathryn E.

2011-01-01

A greater understanding of the causes of human disease can come from identifying characteristics that are specific to disease genes. However, a full understanding of the contribution of essential genes to human disease is lacking, due to the premise that these genes tend to cause developmental abnormalities rather than adult disease. We tested the hypothesis that human orthologs of mouse essential genes are associated with a variety of human diseases, rather than only those related to miscarriage and birth defects. We segregated human disease genes according to whether the knockout phenotype of their mouse ortholog was lethal or viable, defining those with orthologs producing lethal knockouts as essential disease genes. We show that the human orthologs of mouse essential genes are associated with a wide spectrum of diseases affecting diverse physiological systems. Notably, human disease genes with essential mouse orthologs are over-represented among disease genes associated with cancer, suggesting links between adult cellular abnormalities and developmental functions. The proteins encoded by essential genes are highly connected in protein-protein interaction networks, which we find correlates with an over-representation of nuclear proteins amongst essential disease genes. Disease genes associated with essential orthologs also are more likely than those with non-essential orthologs to contribute to disease through an autosomal dominant inheritance pattern, suggesting that these diseases may actually result from semi-dominant mutant alleles. Overall, we have described attributes found in disease genes according to the essentiality status of their mouse orthologs. These findings demonstrate that disease genes do occupy highly connected positions in protein-protein interaction networks, and that due to the complexity of disease-associated alleles, essential genes cannot be ignored as candidates for causing diverse human diseases. PMID:22096564

Identification of regulatory targets of tissue-specific transcription factors: application to retina-specific gene regulation

PubMed Central

Qian, Jiang; Esumi, Noriko; Chen, Yangjian; Wang, Qingliang; Chowers, Itay; Zack, Donald J.

2005-01-01

Identification of tissue-specific gene regulatory networks can yield insights into the molecular basis of a tissue's development, function and pathology. Here, we present a computational approach designed to identify potential regulatory target genes of photoreceptor cell-specific transcription factors (TFs). The approach is based on the hypothesis that genes related to the retina in terms of expression, disease and/or function are more likely to be the targets of retina-specific TFs than other genes. A list of genes that are preferentially expressed in retina was obtained by integrating expressed sequence tag, SAGE and microarray datasets. The regulatory targets of retina-specific TFs are enriched in this set of retina-related genes. A Bayesian approach was employed to integrate information about binding site location relative to a gene's transcription start site. Our method was applied to three retina-specific TFs, CRX, NRL and NR2E3, and a number of potential targets were predicted. To experimentally assess the validity of the bioinformatic predictions, mobility shift, transient transfection and chromatin immunoprecipitation assays were performed with five predicted CRX targets, and the results were suggestive of CRX regulation in 5/5, 3/5 and 4/5 cases, respectively. Together, these experiments strongly suggest that RP1, GUCY2D, ABCA4 are novel targets of CRX. PMID:15967807

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

PubMed

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

2012-01-01

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.

A rapid method to identify Salmonella enterica serovar Gallinarum biovar Pullorum using a specific target gene ipaJ.

PubMed

Xu, Lijuan; Liu, Zijian; Li, Yang; Yin, Chao; Hu, Yachen; Xie, Xiaolei; Li, Qiuchun; Jiao, Xinan

2018-06-01

Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum) is the pathogen of pullorum disease, which leads to severe economic losses in many developing countries. Traditional methods to identify S. enterica have relied on biochemical reactions and serotyping, which are time-consuming with accurate identification if properly carried out. In this study, we developed a rapid polymerase chain reaction (PCR) method targeting the specific gene ipaJ to detect S. Pullorum. Among the 650 S. Pullorum strains isolated from 1962 to 2016 all over China, 644 strains were identified to harbour ipaJ gene in the plasmid pSPI12, accounting for a detection rate of 99.08%. Six strains were ipaJ negative because pSPI12 was not found in these strains according to whole genome sequencing results. There was no cross-reaction with other Salmonella serotypes, including Salmonella enterica serovar Gallinarum biovar Gallinarum (S. Gallinarum), which show a close genetic relationship with S. Pullorum. This shows that the PCR method could distinguish S. Gallinarum from S. Pullorum in one-step PCR without complicated biochemical identification. The limit of detection of this PCR method was as low as 90 fg/μl or 10 2 CFU, which shows a high sensitivity. Moreover, this method was applied to identify Salmonella isolated from the chicken farm and the results were consistent with what we obtained from biochemical reactions and serotyping. Together, all the results demonstrated that this one-step PCR method is simple and feasible to efficiently identify S. Pullorum.

Compendium of Immune Signatures Identifies Conserved and Species-Specific Biology in Response to Inflammation.

PubMed

Godec, Jernej; Tan, Yan; Liberzon, Arthur; Tamayo, Pablo; Bhattacharya, Sanchita; Butte, Atul J; Mesirov, Jill P; Haining, W Nicholas

2016-01-19

Gene-expression profiling has become a mainstay in immunology, but subtle changes in gene networks related to biological processes are hard to discern when comparing various datasets. For instance, conservation of the transcriptional response to sepsis in mouse models and human disease remains controversial. To improve transcriptional analysis in immunology, we created ImmuneSigDB: a manually annotated compendium of ∼5,000 gene-sets from diverse cell states, experimental manipulations, and genetic perturbations in immunology. Analysis using ImmuneSigDB identified signatures induced in activated myeloid cells and differentiating lymphocytes that were highly conserved between humans and mice. Sepsis triggered conserved patterns of gene expression in humans and mouse models. However, we also identified species-specific biological processes in the sepsis transcriptional response: although both species upregulated phagocytosis-related genes, a mitosis signature was specific to humans. ImmuneSigDB enables granular analysis of transcriptomic data to improve biological understanding of immune processes of the human and mouse immune systems. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

2015-01-01

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

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

PubMed Central

2015-01-01

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

Gene correction in patient-specific iPSCs for therapy development and disease modeling

PubMed Central

Jang, Yoon-Young

2018-01-01

The discovery that mature cells can be reprogrammed to become pluripotent and the development of engineered endonucleases for enhancing genome editing are two of the most exciting and impactful technology advances in modern medicine and science. Human pluripotent stem cells have the potential to establish new model systems for studying human developmental biology and disease mechanisms. Gene correction in patient-specific iPSCs can also provide a novel source for autologous cell therapy. Although historically challenging, precise genome editing in human iPSCs is becoming more feasible with the development of new genome-editing tools, including ZFNs, TALENs, and CRISPR. iPSCs derived from patients of a variety of diseases have been edited to correct disease-associated mutations and to generate isogenic cell lines. After directed differentiation, many of the corrected iPSCs showed restored functionality and demonstrated their potential in cell replacement therapy. Genome-wide analyses of gene-corrected iPSCs have collectively demonstrated a high fidelity of the engineered endonucleases. Remaining challenges in clinical translation of these technologies include maintaining genome integrity of the iPSC clones and the differentiated cells. Given the rapid advances in genome-editing technologies, gene correction is no longer the bottleneck in developing iPSC-based gene and cell therapies; generating functional and transplantable cell types from iPSCs remains the biggest challenge needing to be addressed by the research field. PMID:27256364

Specific c-Jun target genes in malignant melanoma.

PubMed

Schummer, Patrick; Kuphal, Silke; Vardimon, Lily; Bosserhoff, Anja K; Kappelmann, Melanie

2016-05-03

A fundamental event in the development and progression of malignant melanoma is the de-regulation of cancer-relevant transcription factors. We recently showed that c-Jun is a main regulator of melanoma progression and, thus, is the most important member of the AP-1 transcription factor family in this disease. Surprisingly, no cancer-related specific c-Jun target genes in melanoma were described in the literature, so far. Therefore, we focused on pre-existing ChIP-Seq data (Encyclopedia of DNA Elements) of 3 different non-melanoma cell lines to screen direct c-Jun target genes. Here, a specific c-Jun antibody to immunoprecipitate the associated promoter DNA was used. Consequently, we identified 44 direct c-Jun targets and a detailed analysis of 6 selected genes confirmed their deregulation in malignant melanoma. The identified genes were differentially regulated comparing 4 melanoma cell lines and normal human melanocytes and we confirmed their c-Jun dependency. Direct interaction between c-Jun and the promoter/enhancer regions of the identified genes was confirmed by us via ChIP experiments. Interestingly, we revealed that the direct regulation of target gene expression via c-Jun can be independent of the existence of the classical AP-1 (5´-TGA(C/G)TCA-3´) consensus sequence allowing for the subsequent down- or up-regulation of the expression of these cancer-relevant genes. In summary, the results of this study indicate that c-Jun plays a crucial role in the development and progression of malignant melanoma via direct regulation of cancer-relevant target genes and that inhibition of direct c-Jun targets through inhibition of c-Jun is a potential novel therapeutic option for treatment of malignant melanoma.

Large-Scale Gene-Centric Analysis Identifies Novel Variants for Coronary Artery Disease

PubMed Central

2011-01-01

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

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

Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia.

PubMed

Badea, Liviu; Herlea, Vlad; Dima, Simona Olimpia; Dumitrascu, Traian; Popescu, Irinel

2008-01-01

The precise details of pancreatic ductal adenocarcinoma (PDAC) pathogenesis are still insufficiently known, requiring the use of high-throughput methods. However, PDAC is especially difficult to study using microarrays due to its strong desmoplastic reaction, which involves a hyperproliferating stroma that effectively "masks" the contribution of the minoritary neoplastic epithelial cells. Thus it is not clear which of the genes that have been found differentially expressed between normal and whole tumor tissues are due to the tumor epithelia and which simply reflect the differences in cellular composition. To address this problem, laser microdissection studies have been performed, but these have to deal with much smaller tissue sample quantities and therefore have significantly higher experimental noise. In this paper we combine our own large sample whole-tissue study with a previously published smaller sample microdissection study by Grützmann et al. to identify the genes that are specifically overexpressed in PDAC tumor epithelia. The overlap of this list of genes with other microarray studies of pancreatic cancer as well as with the published literature is impressive. Moreover, we find a number of genes whose over-expression appears to be inversely correlated with patient survival: keratin 7, laminin gamma 2, stratifin, platelet phosphofructokinase, annexin A2, MAP4K4 and OACT2 (MBOAT2), which are all specifically upregulated in the neoplastic epithelia, rather than the tumor stroma. We improve on other microarray studies of PDAC by putting together the higher statistical power due to a larger number of samples with information about cell-type specific expression and patient survival.

Transcriptome profiling of two maize inbreds with distinct responses to Gibberella ear rot disease to identify candidate resistance genes.

PubMed

Kebede, Aida Z; Johnston, Anne; Schneiderman, Danielle; Bosnich, Whynn; Harris, Linda J

2018-02-09

Gibberella ear rot (GER) is one of the most economically important fungal diseases of maize in the temperate zone due to moldy grain contaminated with health threatening mycotoxins. To develop resistant genotypes and control the disease, understanding the host-pathogen interaction is essential. RNA-Seq-derived transcriptome profiles of fungal- and mock-inoculated developing kernel tissues of two maize inbred lines were used to identify differentially expressed transcripts and propose candidate genes mapping within GER resistance quantitative trait loci (QTL). A total of 1255 transcripts were significantly (P ≤ 0.05) up regulated due to fungal infection in both susceptible and resistant inbreds. A greater number of transcripts were up regulated in the former (1174) than the latter (497) and increased as the infection progressed from 1 to 2 days after inoculation. Focusing on differentially expressed genes located within QTL regions for GER resistance, we identified 81 genes involved in membrane transport, hormone regulation, cell wall modification, cell detoxification, and biosynthesis of pathogenesis related proteins and phytoalexins as candidate genes contributing to resistance. Applying droplet digital PCR, we validated the expression profiles of a subset of these candidate genes from QTL regions contributed by the resistant inbred on chromosomes 1, 2 and 9. By screening global gene expression profiles for differentially expressed genes mapping within resistance QTL regions, we have identified candidate genes for gibberella ear rot resistance on several maize chromosomes which could potentially lead to a better understanding of Fusarium resistance mechanisms.

Gene therapy for sickle cell disease.

PubMed

Olowoyeye, Abiola; Okwundu, Charles I

2014-10-10

Sickle cell disease encompasses a group of genetic disorders characterized by the presence of at least one hemoglobin S (Hb S) allele, and a second abnormal allele that could allow abnormal hemoglobin polymerisation leading to a symptomatic disorder.Autosomal recessive disorders (such as sickle cell disease) are good candidates for gene therapy because a normal phenotype can be restored in diseased cells with only a single normal copy of the mutant gene. The objectives of this review are:- to determine whether gene therapy can improve survival and prevent symptoms and complications associated with sickle cell disease;- to examine the risks of gene therapy against the potential long-term gain for people with sickle cell disease. We searched the Cochrane Cystic Fibrosis and Genetic Disorders Group Haemoglobinopathies Trials Register, which comprises of references identified from comprehensive electronic database searches and searching relevant journals and abstract books of conference proceedings.Date of the most recent search of the Group's Haemoglobinopathies Trials Register: 21 July 2014. All randomised or quasi-randomised clinical trials (including any relevant phase 1, 2 or 3 trials) of gene therapy for all individuals with sickle cell disease, regardless of age or setting. No trials of gene therapy for sickle cell disease were found. No trials of gene therapy for sickle cell disease were reported. No randomised or quasi-randomised clinical trials of gene therapy for sickle cell disease were reported. Thus, no objective conclusions or recommendations in practice can be made on gene therapy for sickle cell disease. This systematic review has identified the need for well-designed, randomised controlled trials to assess the benefits and risks of gene therapy for sickle cell disease.

m6A-Driver: Identifying Context-Specific mRNA m6A Methylation-Driven Gene Interaction Networks

PubMed Central

Zhang, Song-Yao; Zhang, Shao-Wu; Liu, Lian; Huang, Yufei

2016-01-01

As the most prevalent mammalian mRNA epigenetic modification, N6-methyladenosine (m6A) has been shown to possess important post-transcriptional regulatory functions. However, the regulatory mechanisms and functional circuits of m6A are still largely elusive. To help unveil the regulatory circuitry mediated by mRNA m6A methylation, we develop here m6A-Driver, an algorithm for predicting m6A-driven genes and associated networks, whose functional interactions are likely to be actively modulated by m6A methylation under a specific condition. Specifically, m6A-Driver integrates the PPI network and the predicted differential m6A methylation sites from methylated RNA immunoprecipitation sequencing (MeRIP-Seq) data using a Random Walk with Restart (RWR) algorithm and then builds a consensus m6A-driven network of m6A-driven genes. To evaluate the performance, we applied m6A-Driver to build the context-specific m6A-driven networks for 4 known m6A (de)methylases, i.e., FTO, METTL3, METTL14 and WTAP. Our results suggest that m6A-Driver can robustly and efficiently identify m6A-driven genes that are functionally more enriched and associated with higher degree of differential expression than differential m6A methylated genes. Pathway analysis of the constructed context-specific m6A-driven gene networks further revealed the regulatory circuitry underlying the dynamic interplays between the methyltransferases and demethylase at the epitranscriptomic layer of gene regulation. PMID:28027310

Computational deconvolution of genome wide expression data from Parkinson's and Huntington's disease brain tissues using population-specific expression analysis

PubMed Central

Capurro, Alberto; Bodea, Liviu-Gabriel; Schaefer, Patrick; Luthi-Carter, Ruth; Perreau, Victoria M.

2015-01-01

The characterization of molecular changes in diseased tissues gives insight into pathophysiological mechanisms and is important for therapeutic development. Genome-wide gene expression analysis has proven valuable for identifying biological processes in neurodegenerative diseases using post mortem human brain tissue and numerous datasets are publically available. However, many studies utilize heterogeneous tissue samples consisting of multiple cell types, all of which contribute to global gene expression values, confounding biological interpretation of the data. In particular, changes in numbers of neuronal and glial cells occurring in neurodegeneration confound transcriptomic analyses, particularly in human brain tissues where sample availability and controls are limited. To identify cell specific gene expression changes in neurodegenerative disease, we have applied our recently published computational deconvolution method, population specific expression analysis (PSEA). PSEA estimates cell-type-specific expression values using reference expression measures, which in the case of brain tissue comprises mRNAs with cell-type-specific expression in neurons, astrocytes, oligodendrocytes and microglia. As an exercise in PSEA implementation and hypothesis development regarding neurodegenerative diseases, we applied PSEA to Parkinson's and Huntington's disease (PD, HD) datasets. Genes identified as differentially expressed in substantia nigra pars compacta neurons by PSEA were validated using external laser capture microdissection data. Network analysis and Annotation Clustering (DAVID) identified molecular processes implicated by differential gene expression in specific cell types. The results of these analyses provided new insights into the implementation of PSEA in brain tissues and additional refinement of molecular signatures in human HD and PD. PMID:25620908

Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

PubMed

Johnston, Iain G; Williams, Ben P

2016-02-24

Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.

Hypoxia as a target for tissue specific gene therapy.

PubMed

Rhim, Taiyoun; Lee, Dong Yun; Lee, Minhyung

2013-12-10

Hypoxia is a hallmark of various ischemic diseases such as ischemic heart disease, ischemic limb, ischemic stroke, and solid tumors. Gene therapies for these diseases have been developed with various therapeutic genes including growth factors, anti-apoptotic genes, and toxins. However, non-specific expression of these therapeutic genes may induce dangerous side effects in the normal tissues. To avoid the side effects, gene expression should be tightly regulated in an oxygen concentration dependent manner. The hypoxia inducible promoters and enhancers have been evaluated as a transcriptional regulation tool for hypoxia inducible gene therapy. The hypoxia inducible UTRs were also used in gene therapy for spinal cord injury as a translational regulation strategy. In addition to transcriptional and translational regulations, post-translational regulation strategies have been developed using the HIF-1α ODD domain. Hypoxia inducible transcriptional, translational, and post-translational regulations are useful for tissue specific gene therapy of ischemic diseases. In this review, hypoxia inducible gene expression systems are discussed and their applications are introduced. Copyright © 2013 Elsevier B.V. All rights reserved.

Positive-unlabeled learning for disease gene identification

PubMed Central

Yang, Peng; Li, Xiao-Li; Mei, Jian-Ping; Kwoh, Chee-Keong; Ng, See-Kiong

2012-01-01

Background: Identifying disease genes from human genome is an important but challenging task in biomedical research. Machine learning methods can be applied to discover new disease genes based on the known ones. Existing machine learning methods typically use the known disease genes as the positive training set P and the unknown genes as the negative training set N (non-disease gene set does not exist) to build classifiers to identify new disease genes from the unknown genes. However, such kind of classifiers is actually built from a noisy negative set N as there can be unknown disease genes in N itself. As a result, the classifiers do not perform as well as they could be. Result: Instead of treating the unknown genes as negative examples in N, we treat them as an unlabeled set U. We design a novel positive-unlabeled (PU) learning algorithm PUDI (PU learning for disease gene identification) to build a classifier using P and U. We first partition U into four sets, namely, reliable negative set RN, likely positive set LP, likely negative set LN and weak negative set WN. The weighted support vector machines are then used to build a multi-level classifier based on the four training sets and positive training set P to identify disease genes. Our experimental results demonstrate that our proposed PUDI algorithm outperformed the existing methods significantly. Conclusion: The proposed PUDI algorithm is able to identify disease genes more accurately by treating the unknown data more appropriately as unlabeled set U instead of negative set N. Given that many machine learning problems in biomedical research do involve positive and unlabeled data instead of negative data, it is possible that the machine learning methods for these problems can be further improved by adopting PU learning methods, as we have done here for disease gene identification. Availability and implementation: The executable program and data are available at http://www1.i2r

Regulatory systems for hypoxia-inducible gene expression in ischemic heart disease gene therapy.

PubMed

Kim, Hyun Ah; Rhim, Taiyoun; Lee, Minhyung

2011-07-18

Ischemic heart diseases are caused by narrowed coronary arteries that decrease the blood supply to the myocardium. In the ischemic myocardium, hypoxia-responsive genes are up-regulated by hypoxia-inducible factor-1 (HIF-1). Gene therapy for ischemic heart diseases uses genes encoding angiogenic growth factors and anti-apoptotic proteins as therapeutic genes. These genes increase blood supply into the myocardium by angiogenesis and protect cardiomyocytes from cell death. However, non-specific expression of these genes in normal tissues may be harmful, since growth factors and anti-apoptotic proteins may induce tumor growth. Therefore, tight gene regulation is required to limit gene expression to ischemic tissues, to avoid unwanted side effects. For this purpose, various gene expression strategies have been developed for ischemic-specific gene expression. Transcriptional, post-transcriptional, and post-translational regulatory strategies have been developed and evaluated in ischemic heart disease animal models. The regulatory systems can limit therapeutic gene expression to ischemic tissues and increase the efficiency of gene therapy. In this review, recent progresses in ischemic-specific gene expression systems are presented, and their applications to ischemic heart diseases are discussed. Copyright © 2011 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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

Gene therapy for sickle cell disease.

PubMed

Olowoyeye, Abiola; Okwundu, Charles I

2016-11-14

Sickle cell disease encompasses a group of genetic disorders characterized by the presence of at least one hemoglobin S (Hb S) allele, and a second abnormal allele that could allow abnormal hemoglobin polymerisation leading to a symptomatic disorder.Autosomal recessive disorders (such as sickle cell disease) are good candidates for gene therapy because a normal phenotype can be restored in diseased cells with only a single normal copy of the mutant gene. This is an update of a previously published Cochrane Review. The objectives of this review are:to determine whether gene therapy can improve survival and prevent symptoms and complications associated with sickle cell disease;to examine the risks of gene therapy against the potential long-term gain for people with sickle cell disease. We searched the Cochrane Cystic Fibrosis and Genetic Disorders Group Haemoglobinopathies Trials Register, which comprises of references identified from comprehensive electronic database searches and searching relevant journals and abstract books of conference proceedings.Date of the most recent search of the Group's Haemoglobinopathies Trials Register: 15 August 2016. All randomised or quasi-randomised clinical trials (including any relevant phase 1, 2 or 3 trials) of gene therapy for all individuals with sickle cell disease, regardless of age or setting. No trials of gene therapy for sickle cell disease were found. No trials of gene therapy for sickle cell disease were reported. No randomised or quasi-randomised clinical trials of gene therapy for sickle cell disease were reported. Thus, no objective conclusions or recommendations in practice can be made on gene therapy for sickle cell disease. This systematic review has identified the need for well-designed, randomised controlled trials to assess the benefits and risks of gene therapy for sickle cell disease.

Specific reduction of calcium-binding protein (28-kilodalton calbindin-D) gene expression in aging and neurodegenerative diseases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iacopino, A.M.; Christakos, S.

1990-06-01

The present studies establish that there are specific, significant decreases in the neuronal calcium-binding protein (28-kDa calbindin-D) gene expression in aging and in neurodegenerative diseases. The specificity of the changes observed in calbindin mRNA levels was tested by reprobing blots with calmodulin, cyclophilin, and B-actin cDNAs. Gross brain regions of the aging rat exhibited specific, significant decreases in calbindin{center dot}mRNA and protein levels in the cerebellum, corpus striatum, and brain-stem region but not in the cerebral cortex or hippocampus. Discrete areas of the aging human brain exhibited significant decreases in calbindin protein and mRNA in the cerebellum, corpus striatum, andmore » nucleus basalis but not in the neocortex, hippocampus, amygdala, locus ceruleus, or nucleus raphe dorsalis. Comparison of diseased human brain tissue with age- and sex-matched controls yielded significant decreases calbindin protein and mRNA in the substantia nigra (Parkinson disease), in the corpus striatum (Huntington disease), in the nucleus basalis (Alzheimer disease), and in the hippocampus and nucleus raphe dorsalis (Parkinson, Huntington, and Alzheimer diseases) but not in the cerebellum, neocortex, amygdala, or locus ceruleus. These findings suggest that decreased calbindin gene expression may lead to a failure of calcium buffering or intraneuronal calcium homeostasis, which contributes to calcium-mediated cytotoxic events during aging and in the pathogenesis of neurodegenerative diseases.« less

Pediatric Crohn disease patients exhibit specific ileal transcriptome and microbiome signature.

PubMed

Haberman, Yael; Tickle, Timothy L; Dexheimer, Phillip J; Kim, Mi-Ok; Tang, Dora; Karns, Rebekah; Baldassano, Robert N; Noe, Joshua D; Rosh, Joel; Markowitz, James; Heyman, Melvin B; Griffiths, Anne M; Crandall, Wallace V; Mack, David R; Baker, Susan S; Huttenhower, Curtis; Keljo, David J; Hyams, Jeffrey S; Kugathasan, Subra; Walters, Thomas D; Aronow, Bruce; Xavier, Ramnik J; Gevers, Dirk; Denson, Lee A

2014-08-01

Interactions between the host and gut microbial community likely contribute to Crohn disease (CD) pathogenesis; however, direct evidence for these interactions at the onset of disease is lacking. Here, we characterized the global pattern of ileal gene expression and the ileal microbial community in 359 treatment-naive pediatric patients with CD, patients with ulcerative colitis (UC), and control individuals. We identified core gene expression profiles and microbial communities in the affected CD ilea that are preserved in the unaffected ilea of patients with colon-only CD but not present in those with UC or control individuals; therefore, this signature is specific to CD and independent of clinical inflammation. An abnormal increase of antimicrobial dual oxidase (DUOX2) expression was detected in association with an expansion of Proteobacteria in both UC and CD, while expression of lipoprotein APOA1 gene was downregulated and associated with CD-specific alterations in Firmicutes. The increased DUOX2 and decreased APOA1 gene expression signature favored oxidative stress and Th1 polarization and was maximally altered in patients with more severe mucosal injury. A regression model that included APOA1 gene expression and microbial abundance more accurately predicted month 6 steroid-free remission than a model using clinical factors alone. These CD-specific host and microbe profiles identify the ileum as the primary inductive site for all forms of CD and may direct prognostic and therapeutic approaches.

Evidence for somatic gene conversion and deletion in bipolar disorder, Crohn's disease, coronary artery disease, hypertension, rheumatoid arthritis, type-1 diabetes, and type-2 diabetes.

PubMed

Ross, Kenneth Andrew

2011-02-03

During gene conversion, genetic information is transferred unidirectionally between highly homologous but non-allelic regions of DNA. While germ-line gene conversion has been implicated in the pathogenesis of some diseases, somatic gene conversion has remained technically difficult to investigate on a large scale. A novel analysis technique is proposed for detecting the signature of somatic gene conversion from SNP microarray data. The Wellcome Trust Case Control Consortium has gathered SNP microarray data for two control populations and cohorts for bipolar disorder (BD), cardiovascular disease (CAD), Crohn's disease (CD), hypertension (HT), rheumatoid arthritis (RA), type-1 diabetes (T1D) and type-2 diabetes (T2D). Using the new analysis technique, the seven disease cohorts are analyzed to identify cohort-specific SNPs at which conversion is predicted. The quality of the predictions is assessed by identifying known disease associations for genes in the homologous duplicons, and comparing the frequency of such associations with background rates. Of 28 disease/locus pairs meeting stringent conditions, 22 show various degrees of disease association, compared with only 8 of 70 in a mock study designed to measure the background association rate (P < 10-9). Additional candidate genes are identified using less stringent filtering conditions. In some cases, somatic deletions appear likely. RA has a distinctive pattern of events relative to other diseases. Similarities in patterns are apparent between BD and HT. The associations derived represent the first evidence that somatic gene conversion could be a significant causative factor in each of the seven diseases. The specific genes provide potential insights about disease mechanisms, and are strong candidates for further study.

Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

PubMed

Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

2017-08-01

This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

Shared and organism-specific host responses to childhood diarrheal diseases revealed by whole blood transcript profiling.

PubMed

DeBerg, Hannah A; Zaidi, Mussaret B; Altman, Matthew C; Khaenam, Prasong; Gersuk, Vivian H; Campos, Freddy D; Perez-Martinez, Iza; Meza-Segura, Mario; Chaussabel, Damien; Banchereau, Jacques; Estrada-Garcia, Teresa; Linsley, Peter S

2018-01-01

Globally, diarrheal diseases are a leading cause of death in children under five and disproportionately affect children in developing countries. Children who contract diarrheal diseases are rarely screened to identify the etiologic agent due to time and cost considerations associated with pathogen-specific screening and hence pathogen-directed therapy is uncommon. The development of biomarkers to rapidly identify underlying pathogens could improve treatment options and clinical outcomes in childhood diarrheal diseases. Here, we perform RNA sequencing on blood samples collected from children evaluated in an emergency room setting with diarrheal disease where the pathogen(s) present are known. We determine host response gene signatures specific to Salmonella, Shigella and rotavirus, but not E. coli, infections that distinguish them from each other and from healthy controls. Specifically, we observed differential expression of genes related to chemokine receptors or inflammasome signaling in Shigella cases, such as CCR3, CXCR8, and NLRC4, and interferon response genes, such as IFI44 and OASL, in rotavirus cases. Our findings add insight into the host peripheral immune response to these pathogens, and suggest strategies and limitations for the use host response transcript signatures for diagnosing the etiologic agent of childhood diarrheal diseases.

NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities.

PubMed

da Rocha, Edroaldo Lummertz; Ung, Choong Yong; McGehee, Cordelia D; Correia, Cristina; Li, Hu

2016-06-02

The sequential chain of interactions altering the binary state of a biomolecule represents the 'information flow' within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein-protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes-network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code (http://www.NetDecoder.org) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of Non-HLA Genes Associated with Celiac Disease and Country-Specific Differences in a Large, International Pediatric Cohort

PubMed Central

Sharma, Ashok; Liu, Xiang; Hadley, David; Hagopian, William; Liu, Edwin; Chen, Wei-Min; Onengut-Gumuscu, Suna; Simell, Ville; Rewers, Marian; Ziegler, Anette-G.; Lernmark, Åke; Simell, Olli; Toppari, Jorma; Krischer, Jeffrey P.; Akolkar, Beena; Rich, Stephen S.; Agardh, Daniel; She, Jin-Xiong

2016-01-01

Objectives There are significant geographical differences in the prevalence and incidence of celiac disease that cannot be explained by HLA alone. More than 40 loci outside of the HLA region have been associated with celiac disease. We investigated the roles of these non-HLA genes in the development of tissue transglutaminase autoantibodies (tTGA) and celiac disease in a large international prospective cohort study. Methods A total of 424,788 newborns from the US and European general populations and first-degree relatives with type 1 diabetes were screened for specific HLA genotypes. Of these, 21,589 carried 1 of the 9 HLA genotypes associated with increased risk for type 1 diabetes and celiac disease; we followed 8676 of the children in a 15 y prospective follow-up study. Genotype analyses were performed on 6010 children using the Illumina ImmunoChip. Levels of tTGA were measured in serum samples using radio-ligand binding assays; diagnoses of celiac disease were made based on persistent detection of tTGA and biopsy analysis. Data were analyzed using Cox proportional hazards analyses. Results We found 54 single-nucleotide polymorphisms (SNPs) in 5 genes associated with celiac disease (TAGAP, IL18R1, RGS21, PLEK, and CCR9) in time to celiac disease analyses (10−4>P>5.8x10−6). The hazard ratios (HR) for the SNPs with the smallest P values in each region were 1.59, 1.45, 2.23, 2.64, and 1.40, respectively. Outside of regions previously associated with celiac disease, we identified 10 SNPs in 8 regions that could also be associated with the disease (P<10−4). A SNP near PKIA (rs117128341, P = 6.5x10−8, HR = 2.8) and a SNP near PFKFB3 (rs117139146, P<2.8x10−7, HR = 4.9) reached the genome-wide association threshold in subjects from Sweden. Analyses of time to detection of tTGA identified 29 SNPs in 2 regions previously associated with celiac disease (CTLA4, P = 1.3x10−6, HR = 0.76 and LPP, P = 2.8x10−5, HR = .80) and 6 SNPs in 5 regions not previously

Identification of Non-HLA Genes Associated with Celiac Disease and Country-Specific Differences in a Large, International Pediatric Cohort.

PubMed

Sharma, Ashok; Liu, Xiang; Hadley, David; Hagopian, William; Liu, Edwin; Chen, Wei-Min; Onengut-Gumuscu, Suna; Simell, Ville; Rewers, Marian; Ziegler, Anette-G; Lernmark, Åke; Simell, Olli; Toppari, Jorma; Krischer, Jeffrey P; Akolkar, Beena; Rich, Stephen S; Agardh, Daniel; She, Jin-Xiong

2016-01-01

There are significant geographical differences in the prevalence and incidence of celiac disease that cannot be explained by HLA alone. More than 40 loci outside of the HLA region have been associated with celiac disease. We investigated the roles of these non-HLA genes in the development of tissue transglutaminase autoantibodies (tTGA) and celiac disease in a large international prospective cohort study. A total of 424,788 newborns from the US and European general populations and first-degree relatives with type 1 diabetes were screened for specific HLA genotypes. Of these, 21,589 carried 1 of the 9 HLA genotypes associated with increased risk for type 1 diabetes and celiac disease; we followed 8676 of the children in a 15 y prospective follow-up study. Genotype analyses were performed on 6010 children using the Illumina ImmunoChip. Levels of tTGA were measured in serum samples using radio-ligand binding assays; diagnoses of celiac disease were made based on persistent detection of tTGA and biopsy analysis. Data were analyzed using Cox proportional hazards analyses. We found 54 single-nucleotide polymorphisms (SNPs) in 5 genes associated with celiac disease (TAGAP, IL18R1, RGS21, PLEK, and CCR9) in time to celiac disease analyses (10-4>P>5.8x10-6). The hazard ratios (HR) for the SNPs with the smallest P values in each region were 1.59, 1.45, 2.23, 2.64, and 1.40, respectively. Outside of regions previously associated with celiac disease, we identified 10 SNPs in 8 regions that could also be associated with the disease (P<10-4). A SNP near PKIA (rs117128341, P = 6.5x10-8, HR = 2.8) and a SNP near PFKFB3 (rs117139146, P<2.8x10-7, HR = 4.9) reached the genome-wide association threshold in subjects from Sweden. Analyses of time to detection of tTGA identified 29 SNPs in 2 regions previously associated with celiac disease (CTLA4, P = 1.3x10-6, HR = 0.76 and LPP, P = 2.8x10-5, HR = .80) and 6 SNPs in 5 regions not previously associated with celiac disease (P<10-4); non

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. Copyright © 2015, American Association for the Advancement of Science.

Expression screening of cancer/testis genes in prostate cancer identifies NR6A1 as a novel marker of disease progression and aggressiveness.

PubMed

Mathieu, Romain; Evrard, Bertrand; Fromont, Gaëlle; Rioux-Leclercq, Nathalie; Godet, Julie; Cathelineau, Xavier; Guillé, François; Primig, Michael; Chalmel, Frédéric

2013-07-01

Cancer/Testis (CT) genes are expressed in male gonads, repressed in most healthy somatic tissues and de-repressed in various somatic malignancies including prostate cancers (PCa). Because of their specific expression signature and their associations with tumor aggressiveness and poor outcomes, CT genes are considered to be useful biomarkers and they are also targets for the development of new anti-cancer immunotherapies. The aim of this study was to identify novel CT genes associated with hormone-sensitive prostate cancer (HSPC), and castration-resistant prostate cancer (CRPC). To identify novel CT genes we screened genes for which transcripts were detected by RNA profiling specifically in normal testis and in either HSPC or CRPC as compared to normal prostate and 44 other healthy tissues using GeneChips. The expression and clinicopathological significance of a promising candidate--NR6A1--was examined in HSPC, CRPC, and metastatic site samples using tissue microarrays. We report the identification of 98 genes detected in CRPC, HSPC and testicular samples but not in the normal controls. Among them, cellular levels of NR6A1 were found to be higher in HSPC compared to normal prostate and further increased in metastatic lesions and CRPC. Furthermore, increased NR6A1 immunoreactivity was significantly associated with a high Gleason score, advanced pT stage and cancer cell proliferation. Our results show that cellular levels of NR6A1 are correlated with disease progression in PCa. We suggest that this essential orphan nuclear receptor is a potential therapeutic target as well as a biomarker of PCa aggressiveness. Copyright © 2013 Wiley Periodicals, Inc.

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

Elucidating the genotype-phenotype relationships and network perturbations of human shared and specific disease genes from an evolutionary perspective.

PubMed

Begum, Tina; Ghosh, Tapash Chandra

2014-10-05

To date, numerous studies have been attempted to determine the extent of variation in evolutionary rates between human disease and nondisease (ND) genes. In our present study, we have considered human autosomal monogenic (Mendelian) disease genes, which were classified into two groups according to the number of phenotypic defects, that is, specific disease (SPD) gene (one gene: one defect) and shared disease (SHD) gene (one gene: multiple defects). Here, we have compared the evolutionary rates of these two groups of genes, that is, SPD genes and SHD genes with respect to ND genes. We observed that the average evolutionary rates are slow in SHD group, intermediate in SPD group, and fast in ND group. Group-to-group evolutionary rate differences remain statistically significant regardless of their gene expression levels and number of defects. We demonstrated that disease genes are under strong selective constraint if they emerge through edgetic perturbation or drug-induced perturbation of the interactome network, show tissue-restricted expression, and are involved in transmembrane transport. Among all the factors, our regression analyses interestingly suggest the independent effects of 1) drug-induced perturbation and 2) the interaction term of expression breadth and transmembrane transport on protein evolutionary rates. We reasoned that the drug-induced network disruption is a combination of several edgetic perturbations and, thus, has more severe effect on gene phenotypes. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Gene therapy for ocular diseases.

PubMed

Liu, Melissa M; Tuo, Jingsheng; Chan, Chi-Chao

2011-05-01

The eye is an easily accessible, highly compartmentalised and immune-privileged organ that offers unique advantages as a gene therapy target. Significant advancements have been made in understanding the genetic pathogenesis of ocular diseases, and gene replacement and gene silencing have been implicated as potentially efficacious therapies. Recent improvements have been made in the safety and specificity of vector-based ocular gene transfer methods. Proof-of-concept for vector-based gene therapies has also been established in several experimental models of human ocular diseases. After nearly two decades of ocular gene therapy research, preliminary successes are now being reported in phase 1 clinical trials for the treatment of Leber congenital amaurosis. This review describes current developments and future prospects for ocular gene therapy. Novel methods are being developed to enhance the performance and regulation of recombinant adeno-associated virus- and lentivirus-mediated ocular gene transfer. Gene therapy prospects have advanced for a variety of retinal disorders, including retinitis pigmentosa, retinoschisis, Stargardt disease and age-related macular degeneration. Advances have also been made using experimental models for non-retinal diseases, such as uveitis and glaucoma. These methodological advancements are critical for the implementation of additional gene-based therapies for human ocular diseases in the near future.

A vector space model approach to identify genetically related diseases.

PubMed

Sarkar, Indra Neil

2012-01-01

The relationship between diseases and their causative genes can be complex, especially in the case of polygenic diseases. Further exacerbating the challenges in their study is that many genes may be causally related to multiple diseases. This study explored the relationship between diseases through the adaptation of an approach pioneered in the context of information retrieval: vector space models. A vector space model approach was developed that bridges gene disease knowledge inferred across three knowledge bases: Online Mendelian Inheritance in Man, GenBank, and Medline. The approach was then used to identify potentially related diseases for two target diseases: Alzheimer disease and Prader-Willi Syndrome. In the case of both Alzheimer Disease and Prader-Willi Syndrome, a set of plausible diseases were identified that may warrant further exploration. This study furthers seminal work by Swanson, et al. that demonstrated the potential for mining literature for putative correlations. Using a vector space modeling approach, information from both biomedical literature and genomic resources (like GenBank) can be combined towards identification of putative correlations of interest. To this end, the relevance of the predicted diseases of interest in this study using the vector space modeling approach were validated based on supporting literature. The results of this study suggest that a vector space model approach may be a useful means to identify potential relationships between complex diseases, and thereby enable the coordination of gene-based findings across multiple complex diseases.

Evidence for somatic gene conversion and deletion in bipolar disorder, Crohn's disease, coronary artery disease, hypertension, rheumatoid arthritis, type-1 diabetes, and type-2 diabetes

PubMed Central

2011-01-01

Background During gene conversion, genetic information is transferred unidirectionally between highly homologous but non-allelic regions of DNA. While germ-line gene conversion has been implicated in the pathogenesis of some diseases, somatic gene conversion has remained technically difficult to investigate on a large scale. Methods A novel analysis technique is proposed for detecting the signature of somatic gene conversion from SNP microarray data. The Wellcome Trust Case Control Consortium has gathered SNP microarray data for two control populations and cohorts for bipolar disorder (BD), cardiovascular disease (CAD), Crohn's disease (CD), hypertension (HT), rheumatoid arthritis (RA), type-1 diabetes (T1D) and type-2 diabetes (T2D). Using the new analysis technique, the seven disease cohorts are analyzed to identify cohort-specific SNPs at which conversion is predicted. The quality of the predictions is assessed by identifying known disease associations for genes in the homologous duplicons, and comparing the frequency of such associations with background rates. Results Of 28 disease/locus pairs meeting stringent conditions, 22 show various degrees of disease association, compared with only 8 of 70 in a mock study designed to measure the background association rate (P < 10-9). Additional candidate genes are identified using less stringent filtering conditions. In some cases, somatic deletions appear likely. RA has a distinctive pattern of events relative to other diseases. Similarities in patterns are apparent between BD and HT. Conclusions The associations derived represent the first evidence that somatic gene conversion could be a significant causative factor in each of the seven diseases. The specific genes provide potential insights about disease mechanisms, and are strong candidates for further study. Please see Commentary: http://www.biomedcentral.com/1741-7015/9/13/abstract. PMID:21291537

Common variants in Mendelian kidney disease genes and their association with renal function.

PubMed

Parsa, Afshin; Fuchsberger, Christian; Köttgen, Anna; O'Seaghdha, Conall M; Pattaro, Cristian; de Andrade, Mariza; Chasman, Daniel I; Teumer, Alexander; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Kim, Young J; Taliun, Daniel; Li, Man; Feitosa, Mary; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C; Glazer, Nicole; Isaacs, Aaron; Rao, Madhumathi; Smith, Albert V; O'Connell, Jeffrey R; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Hwang, Shih-Jen; Atkinson, Elizabeth J; Lohman, Kurt; Cornelis, Marilyn C; Johansson, Asa; Tönjes, Anke; Dehghan, Abbas; Couraki, Vincent; Holliday, Elizabeth G; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y; Murgia, Federico; Trompet, Stella; Imboden, Medea; Kollerits, Barbara; Pistis, Giorgio; Harris, Tamara B; Launer, Lenore J; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D; Boerwinkle, Eric; Schmidt, Helena; Hofer, Edith; Hu, Frank; Demirkan, Ayse; Oostra, Ben A; Turner, Stephen T; Ding, Jingzhong; Andrews, Jeanette S; Freedman, Barry I; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Döring, Angela; Wichmann, H-Erich; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H; Wright, Alan F; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G; Rivadeneira, Fernando; Aulchenko, Yurii S; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K; Portas, Laura; Ford, Ian; Buckley, Brendan M; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J Wouter; Probst-Hensch, Nicole M; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; van Duijn, Cornelia M; Borecki, Ingrid; Kardia, Sharon L R; Liu, Yongmei; Curhan, Gary C; Rudan, Igor; Gyllensten, Ulf; Wilson, James F; Franke, Andre; Pramstaller, Peter P; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M; Bochud, Murielle; Heid, Iris M; Siscovick, David S; Fox, Caroline S; Kao, W Linda; Böger, Carsten A

2013-12-01

Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.

Common Variants in Mendelian Kidney Disease Genes and Their Association with Renal Function

PubMed Central

Fuchsberger, Christian; Köttgen, Anna; O’Seaghdha, Conall M.; Pattaro, Cristian; de Andrade, Mariza; Chasman, Daniel I.; Teumer, Alexander; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Kim, Young J.; Taliun, Daniel; Li, Man; Feitosa, Mary; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C.; Glazer, Nicole; Isaacs, Aaron; Rao, Madhumathi; Smith, Albert V.; O’Connell, Jeffrey R.; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Hwang, Shih-Jen; Atkinson, Elizabeth J.; Lohman, Kurt; Cornelis, Marilyn C.; Johansson, Åsa; Tönjes, Anke; Dehghan, Abbas; Couraki, Vincent; Holliday, Elizabeth G.; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y.; Murgia, Federico; Trompet, Stella; Imboden, Medea; Kollerits, Barbara; Pistis, Giorgio; Harris, Tamara B.; Launer, Lenore J.; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D.; Boerwinkle, Eric; Schmidt, Helena; Hofer, Edith; Hu, Frank; Demirkan, Ayse; Oostra, Ben A.; Turner, Stephen T.; Ding, Jingzhong; Andrews, Jeanette S.; Freedman, Barry I.; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Döring, Angela; Wichmann, H.-Erich; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E.; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H.; Wright, Alan F.; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K.; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G.; Rivadeneira, Fernando; Aulchenko, Yurii S.; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K.; Portas, Laura; Ford, Ian; Buckley, Brendan M.; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J. Wouter; Probst-Hensch, Nicole M.; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R.; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; van Duijn, Cornelia M.; Borecki, Ingrid; Kardia, Sharon L.R.; Liu, Yongmei; Curhan, Gary C.; Rudan, Igor; Gyllensten, Ulf; Wilson, James F.; Franke, Andre; Pramstaller, Peter P.; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M.; Bochud, Murielle; Heid, Iris M.; Siscovick, David S.; Fox, Caroline S.; Kao, W. Linda; Böger, Carsten A.

2013-01-01

Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research. PMID:24029420

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni

PubMed Central

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-01-01

Background Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. Results We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni.

PubMed

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-12-29

Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1, cytoplasmic intermediate

Exome chip meta-analysis identifies novel loci and East Asian-specific coding variants contributing to lipid levels and coronary artery disease

PubMed Central

Lu, Xiangfeng; Peloso, Gina M; Liu, Dajiang J.; Wu, Ying; Zhang, He; Zhou, Wei; Li, Jun; Tang, Clara Sze-man; Dorajoo, Rajkumar; Li, Huaixing; Long, Jirong; Guo, Xiuqing; Xu, Ming; Spracklen, Cassandra N.; Chen, Yang; Liu, Xuezhen; Zhang, Yan; Khor, Chiea Chuen; Liu, Jianjun; Sun, Liang; Wang, Laiyuan; Gao, Yu-Tang; Hu, Yao; Yu, Kuai; Wang, Yiqin; Cheung, Chloe Yu Yan; Wang, Feijie; Huang, Jianfeng; Fan, Qiao; Cai, Qiuyin; Chen, Shufeng; Shi, Jinxiu; Yang, Xueli; Zhao, Wanting; Sheu, Wayne H.-H.; Cherny, Stacey Shawn; He, Meian; Feranil, Alan B.; Adair, Linda S.; Gordon-Larsen, Penny; Du, Shufa; Varma, Rohit; da Chen, Yii-Der I; Shu, XiaoOu; Lam, Karen Siu Ling; Wong, Tien Yin; Ganesh, Santhi K.; Mo, Zengnan; Hveem, Kristian; Fritsche, Lars; Nielsen, Jonas Bille; Tse, Hung-fat; Huo, Yong; Cheng, Ching-Yu; Chen, Y. Eugene; Zheng, Wei; Tai, E Shyong; Gao, Wei; Lin, Xu; Huang, Wei; Abecasis, Goncalo; Consortium, GLGC; Kathiresan, Sekar; Mohlke, Karen L.; Wu, Tangchun; Sham, Pak Chung; Gu, Dongfeng; Willer, Cristen J

2017-01-01

Most genome-wide association studies have been conducted in European individuals, even though most genetic variation in humans is seen only in non-European samples. To search for novel loci associated with blood lipid levels and clarify the mechanism of action at previously identified lipid loci, we examined protein-coding genetic variants in 47,532 East Asian individuals using an exome array. We identified 255 variants at 41 loci reaching chip-wide significance, including 3 novel loci and 14 East Asian-specific coding variant associations. After meta-analysis with > 300,000 European samples, we identified an additional 9 novel loci. The same 16 genes were identified by the protein-altering variants in both East Asians and Europeans, likely pointing to the functional genes. Our data demonstrate that most of the low-frequency or rare coding variants associated with lipids are population-specific, and that examining genomic data across diverse ancestries may facilitate the identification of functional genes at associated loci. PMID:29083407

Parallel gene analysis with allele-specific padlock probes and tag microarrays

PubMed Central

Banér, Johan; Isaksson, Anders; Waldenström, Erik; Jarvius, Jonas; Landegren, Ulf; Nilsson, Mats

2003-01-01

Parallel, highly specific analysis methods are required to take advantage of the extensive information about DNA sequence variation and of expressed sequences. We present a scalable laboratory technique suitable to analyze numerous target sequences in multiplexed assays. Sets of padlock probes were applied to analyze single nucleotide variation directly in total genomic DNA or cDNA for parallel genotyping or gene expression analysis. All reacted probes were then co-amplified and identified by hybridization to a standard tag oligonucleotide array. The technique was illustrated by analyzing normal and pathogenic variation within the Wilson disease-related ATP7B gene, both at the level of DNA and RNA, using allele-specific padlock probes. PMID:12930977

Loss of RNA expression and allele-specific expression associated with congenital heart disease

PubMed Central

McKean, David M.; Homsy, Jason; Wakimoto, Hiroko; Patel, Neil; Gorham, Joshua; DePalma, Steven R.; Ware, James S.; Zaidi, Samir; Ma, Wenji; Patel, Nihir; Lifton, Richard P.; Chung, Wendy K.; Kim, Richard; Shen, Yufeng; Brueckner, Martina; Goldmuntz, Elizabeth; Sharp, Andrew J.; Seidman, Christine E.; Gelb, Bruce D.; Seidman, J. G.

2016-01-01

Congenital heart disease (CHD), a prevalent birth defect occurring in 1% of newborns, likely results from aberrant expression of cardiac developmental genes. Mutations in a variety of cardiac transcription factors, developmental signalling molecules and molecules that modify chromatin cause at least 20% of disease, but most CHD remains unexplained. We employ RNAseq analyses to assess allele-specific expression (ASE) and biallelic loss-of-expression (LOE) in 172 tissue samples from 144 surgically repaired CHD subjects. Here we show that only 5% of known imprinted genes with paternal allele silencing are monoallelic versus 56% with paternal allele expression—this cardiac-specific phenomenon seems unrelated to CHD. Further, compared with control subjects, CHD subjects have a significant burden of both LOE genes and ASE events associated with altered gene expression. These studies identify FGFBP2, LBH, RBFOX2, SGSM1 and ZBTB16 as candidate CHD genes because of significantly altered transcriptional expression. PMID:27670201

Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients.

PubMed

Rapin, Nicolas; Bagger, Frederik Otzen; Jendholm, Johan; Mora-Jensen, Helena; Krogh, Anders; Kohlmann, Alexander; Thiede, Christian; Borregaard, Niels; Bullinger, Lars; Winther, Ole; Theilgaard-Mönch, Kim; Porse, Bo T

2014-02-06

Gene expression profiling has been used extensively to characterize cancer, identify novel subtypes, and improve patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in identifying expression changes fundamental to disease etiology. Here we present a method that facilitates the comparison of any cancer sample to its nearest normal cellular counterpart, using acute myeloid leukemia (AML) as a model. We first generated a gene expression-based landscape of the normal hematopoietic hierarchy, using expression profiles from normal stem/progenitor cells, and next mapped the AML patient samples to this landscape. This allowed us to identify the closest normal counterpart of individual AML samples and determine gene expression changes between cancer and normal. We find the cancer vs normal method (CvN method) to be superior to conventional methods in stratifying AML patients with aberrant karyotype and in identifying common aberrant transcriptional programs with potential importance for AML etiology. Moreover, the CvN method uncovered a novel poor-outcome subtype of normal-karyotype AML, which allowed for the generation of a highly prognostic survival signature. Collectively, our CvN method holds great potential as a tool for the analysis of gene expression profiles of cancer patients.

Implication of common and disease specific variants in CLU, CR1, and PICALM.

PubMed

Ferrari, Raffaele; Moreno, Jorge H; Minhajuddin, Abu T; O'Bryant, Sid E; Reisch, Joan S; Barber, Robert C; Momeni, Parastoo

2012-08-01

Two recent genome-wide association studies (GWAS) for late onset Alzheimer's disease (LOAD) revealed 3 new genes: clusterin (CLU), phosphatidylinositol binding clathrin assembly protein (PICALM), and complement receptor 1 (CR1). In order to evaluate association with these genome-wide association study-identified genes and to isolate the variants contributing to the pathogenesis of LOAD, we genotyped the top single nucleotide polymorphisms (SNPs), rs11136000 (CLU), rs3818361 (CR1), and rs3851179 (PICALM), and sequenced the entire coding regions of these genes in our cohort of 342 LOAD patients and 277 control subjects. We confirmed the association of rs3851179 (PICALM) (p = 7.4 × 10(-3)) with the disease status. Through sequencing we identified 18 variants in CLU, 3 of which were found exclusively in patients; 8 variants (out of 65) in CR1 gene were only found in patients and the 16 variants identified in PICALM gene were present in both patients and controls. In silico analysis of the variants in PICALM did not predict any damaging effect on the protein. The haplotype analysis of the variants in each gene predicted a common haplotype when the 3 single nucleotide polymorphisms rs11136000 (CLU), rs3818361 (CR1), and rs3851179 (PICALM), respectively, were included. For each gene the haplotype structure and size differed between patients and controls. In conclusion, we confirmed association of CLU, CR1, and PICALM genes with the disease status in our cohort through identification of a number of disease-specific variants among patients through the sequencing of the coding region of these genes. Published by Elsevier Inc.

Genome-Wide association study identifies candidate genes for Parkinson's disease in an Ashkenazi Jewish population

PubMed Central

2011-01-01

Background To date, nine Parkinson disease (PD) genome-wide association studies in North American, European and Asian populations have been published. The majority of studies have confirmed the association of the previously identified genetic risk factors, SNCA and MAPT, and two studies have identified three new PD susceptibility loci/genes (PARK16, BST1 and HLA-DRB5). In a recent meta-analysis of datasets from five of the published PD GWAS an additional 6 novel candidate genes (SYT11, ACMSD, STK39, MCCC1/LAMP3, GAK and CCDC62/HIP1R) were identified. Collectively the associations identified in these GWAS account for only a small proportion of the estimated total heritability of PD suggesting that an 'unknown' component of the genetic architecture of PD remains to be identified. Methods We applied a GWAS approach to a relatively homogeneous Ashkenazi Jewish (AJ) population from New York to search for both 'rare' and 'common' genetic variants that confer risk of PD by examining any SNPs with allele frequencies exceeding 2%. We have focused on a genetic isolate, the AJ population, as a discovery dataset since this cohort has a higher sharing of genetic background and historically experienced a significant bottleneck. We also conducted a replication study using two publicly available datasets from dbGaP. The joint analysis dataset had a combined sample size of 2,050 cases and 1,836 controls. Results We identified the top 57 SNPs showing the strongest evidence of association in the AJ dataset (p < 9.9 × 10-5). Six SNPs located within gene regions had positive signals in at least one other independent dbGaP dataset: LOC100505836 (Chr3p24), LOC153328/SLC25A48 (Chr5q31.1), UNC13B (9p13.3), SLCO3A1(15q26.1), WNT3(17q21.3) and NSF (17q21.3). We also replicated published associations for the gene regions SNCA (Chr4q21; rs3775442, p = 0.037), PARK16 (Chr1q32.1; rs823114 (NUCKS1), p = 6.12 × 10-4), BST1 (Chr4p15; rs12502586, p = 0.027), STK39 (Chr2q24.3; rs3754775, p = 0

Transcriptomic meta-analysis identifies gene expression characteristics in various samples of HIV-infected patients with nonprogressive disease.

PubMed

Zhang, Le-Le; Zhang, Zi-Ning; Wu, Xian; Jiang, Yong-Jun; Fu, Ya-Jing; Shang, Hong

2017-09-12

A small proportion of HIV-infected patients remain clinically and/or immunologically stable for years, including elite controllers (ECs) who have undetectable viremia (<50 copies/ml) and long-term nonprogressors (LTNPs) who maintain normal CD4 + T cell counts for prolonged periods (>10 years). However, the mechanism of nonprogression needs to be further resolved. In this study, a transcriptome meta-analysis was performed on nonprogressor and progressor microarray data to identify differential transcriptome pathways and potential biomarkers. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed genes (DEGs) in nonprogressors and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DEGs identified in the meta-analysis. Five microarray datasets (81 cases and 98 controls in total), including whole blood, CD4 + and CD8 + T cells, were collected for meta-analysis. We determined that nonprogressors have reduced expression of important interferon-stimulated genes (ISGs), CD38, lymphocyte activation gene 3 (LAG-3) in whole blood, CD4 + and CD8 + T cells. Gene ontology (GO) analysis showed a significant enrichment in DEGs that function in the type I interferon signaling pathway. Upregulated pathways, including the PI3K-Akt signaling pathway in whole blood, cytokine-cytokine receptor interaction in CD4 + T cells and the MAPK signaling pathway in CD8 + T cells, were identified in nonprogressors compared with progressors. In each metabolic functional category, the number of downregulated DEGs was more than the upregulated DEGs, and almost all genes were downregulated DEGs in the oxidative phosphorylation (OXPHOS) and tricarboxylic acid (TCA) cycle in the three types of samples. Our transcriptomic meta-analysis provides a comprehensive evaluation of the gene expression profiles in major blood types of nonprogressors, providing new

Coalitional game theory as a promising approach to identify candidate autism genes.

PubMed

Gupta, Anika; Sun, Min Woo; Paskov, Kelley Marie; Stockham, Nate Tyler; Jung, Jae-Yoon; Wall, Dennis Paul

2018-01-01

Despite mounting evidence for the strong role of genetics in the phenotypic manifestation of Autism Spectrum Disorder (ASD), the specific genes responsible for the variable forms of ASD remain undefined. ASD may be best explained by a combinatorial genetic model with varying epistatic interactions across many small effect mutations. Coalitional or cooperative game theory is a technique that studies the combined effects of groups of players, known as coalitions, seeking to identify players who tend to improve the performance--the relationship to a specific disease phenotype--of any coalition they join. This method has been previously shown to boost biologically informative signal in gene expression data but to-date has not been applied to the search for cooperative mutations among putative ASD genes. We describe our approach to highlight genes relevant to ASD using coalitional game theory on alteration data of 1,965 fully sequenced genomes from 756 multiplex families. Alterations were encoded into binary matrices for ASD (case) and unaffected (control) samples, indicating likely gene-disrupting, inherited mutations in altered genes. To determine individual gene contributions given an ASD phenotype, a "player" metric, referred to as the Shapley value, was calculated for each gene in the case and control cohorts. Sixty seven genes were found to have significantly elevated player scores and likely represent significant contributors to the genetic coordination underlying ASD. Using network and cross-study analysis, we found that these genes are involved in biological pathways known to be affected in the autism cases and that a subset directly interact with several genes known to have strong associations to autism. These findings suggest that coalitional game theory can be applied to large-scale genomic data to identify hidden yet influential players in complex polygenic disorders such as autism.

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

PubMed Central

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

2016-01-01

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

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

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

PubMed Central

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

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. Copyright © 2015 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.

Omics analysis of human bone to identify genes and molecular networks regulating skeletal remodeling in health and disease.

PubMed

Reppe, Sjur; Datta, Harish K; Gautvik, Kaare M

2017-08-01

The skeleton is a metabolically active organ throughout life where specific bone cell activity and paracrine/endocrine factors regulate its morphogenesis and remodeling. In recent years, an increasing number of reports have used multi-omics technologies to characterize subsets of bone biological molecular networks. The skeleton is affected by primary and secondary disease, lifestyle and many drugs. Therefore, to obtain relevant and reliable data from well characterized patient and control cohorts are vital. Here we provide a brief overview of omics studies performed on human bone, of which our own studies performed on trans-iliacal bone biopsies from postmenopausal women with osteoporosis (OP) and healthy controls are among the first and largest. Most other studies have been performed on smaller groups of patients, undergoing hip replacement for osteoarthritis (OA) or fracture, and without healthy controls. The major findings emerging from the combined studies are: 1. Unstressed and stressed bone show profoundly different gene expression reflecting differences in bone turnover and remodeling and 2. Omics analyses comparing healthy/OP and control/OA cohorts reveal characteristic changes in transcriptomics, epigenomics (DNA methylation), proteomics and metabolomics. These studies, together with genome-wide association studies, in vitro observations and transgenic animal models have identified a number of genes and gene products that act via Wnt and other signaling systems and are highly associated to bone density and fracture. Future challenge is to understand the functional interactions between bone-related molecular networks and their significance in OP and OA pathogenesis, and also how the genomic architecture is affected in health and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2016-01-01

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. © 2015 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

Ancestry-based stratified analysis of Immunochip data identifies novel associations with celiac disease.

PubMed

Garcia-Etxebarria, Koldo; Jauregi-Miguel, Amaia; Romero-Garmendia, Irati; Plaza-Izurieta, Leticia; Legarda, Maria; Irastorza, Iñaki; Bilbao, Jose Ramon

2016-12-01

To identify candidate genes in celiac disease (CD), we reanalyzed the whole Immunochip CD cohort using a different approach that clusters individuals based on immunoancestry prior to disease association analysis, rather than by geographical origin. We detected 636 new associated SNPs (P<7.02 × 10 -07 ) and identified 5 novel genomic regions, extended 8 others previously identified and also detected 18 isolated signals defined by one or very few significant SNPs. To test whether we could identify putative candidate genes, we performed expression analyses of several genes from the top novel region (chr2:134533564-136169524), from a previously identified locus that is now extended, and a gene marked by an isolated SNP, in duodenum biopsies of active and treated CD patients, and non-celiac controls. In the largest novel region, CCNT2 and R3HDM1 were constitutively underexpressed in disease, even after gluten removal. Moreover, several genes within this region were coexpressed in patients, but not in controls. Other novel genes like KIF21B, REL and SORD also showed altered expression in active disease. Apart from the identification of novel CD loci, these results suggest that ancestry-based stratified analysis is an efficient strategy for association studies in complex diseases.

Prenatal Exposure to Arsenic and Cadmium Impacts Infectious Disease-Related Genes within the Glucocorticoid Receptor Signal Transduction Pathway

PubMed Central

Rager, Julia E.; Yosim, Andrew; Fry, Rebecca C.

2014-01-01

There is increasing evidence that environmental agents mediate susceptibility to infectious disease. Studies support the impact of prenatal/early life exposure to the environmental metals inorganic arsenic (iAs) and cadmium (Cd) on increased risk for susceptibility to infection. The specific biological mechanisms that underlie such exposure-mediated effects remain understudied. This research aimed to identify key genes/signal transduction pathways that associate prenatal exposure to these toxic metals with changes in infectious disease susceptibility using a Comparative Genomic Enrichment Method (CGEM). Using CGEM an infectious disease gene (IDG) database was developed comprising 1085 genes with known roles in viral, bacterial, and parasitic disease pathways. Subsequently, datasets collected from human pregnancy cohorts exposed to iAs or Cd were examined in relationship to the IDGs, specifically focusing on data representing epigenetic modifications (5-methyl cytosine), genomic perturbations (mRNA expression), and proteomic shifts (protein expression). A set of 82 infection and exposure-related genes was identified and found to be enriched for their role in the glucocorticoid receptor signal transduction pathway. Given their common identification across numerous human cohorts and their known toxicological role in disease, the identified genes within the glucocorticoid signal transduction pathway may underlie altered infectious disease susceptibility associated with prenatal exposures to the toxic metals iAs and Cd in humans. PMID:25479081

Exome chip meta-analysis identifies novel loci and East Asian-specific coding variants that contribute to lipid levels and coronary artery disease.

PubMed

Lu, Xiangfeng; Peloso, Gina M; Liu, Dajiang J; Wu, Ying; Zhang, He; Zhou, Wei; Li, Jun; Tang, Clara Sze-Man; Dorajoo, Rajkumar; Li, Huaixing; Long, Jirong; Guo, Xiuqing; Xu, Ming; Spracklen, Cassandra N; Chen, Yang; Liu, Xuezhen; Zhang, Yan; Khor, Chiea Chuen; Liu, Jianjun; Sun, Liang; Wang, Laiyuan; Gao, Yu-Tang; Hu, Yao; Yu, Kuai; Wang, Yiqin; Cheung, Chloe Yu Yan; Wang, Feijie; Huang, Jianfeng; Fan, Qiao; Cai, Qiuyin; Chen, Shufeng; Shi, Jinxiu; Yang, Xueli; Zhao, Wanting; Sheu, Wayne H-H; Cherny, Stacey Shawn; He, Meian; Feranil, Alan B; Adair, Linda S; Gordon-Larsen, Penny; Du, Shufa; Varma, Rohit; Chen, Yii-Der Ida; Shu, Xiao-Ou; Lam, Karen Siu Ling; Wong, Tien Yin; Ganesh, Santhi K; Mo, Zengnan; Hveem, Kristian; Fritsche, Lars G; Nielsen, Jonas Bille; Tse, Hung-Fat; Huo, Yong; Cheng, Ching-Yu; Chen, Y Eugene; Zheng, Wei; Tai, E Shyong; Gao, Wei; Lin, Xu; Huang, Wei; Abecasis, Goncalo; Kathiresan, Sekar; Mohlke, Karen L; Wu, Tangchun; Sham, Pak Chung; Gu, Dongfeng; Willer, Cristen J

2017-12-01

Most genome-wide association studies have been of European individuals, even though most genetic variation in humans is seen only in non-European samples. To search for novel loci associated with blood lipid levels and clarify the mechanism of action at previously identified lipid loci, we used an exome array to examine protein-coding genetic variants in 47,532 East Asian individuals. We identified 255 variants at 41 loci that reached chip-wide significance, including 3 novel loci and 14 East Asian-specific coding variant associations. After a meta-analysis including >300,000 European samples, we identified an additional nine novel loci. Sixteen genes were identified by protein-altering variants in both East Asians and Europeans, and thus are likely to be functional genes. Our data demonstrate that most of the low-frequency or rare coding variants associated with lipids are population specific, and that examining genomic data across diverse ancestries may facilitate the identification of functional genes at associated loci.

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

Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types.

PubMed

Cornish, Alex J; Filippis, Ioannis; David, Alessia; Sternberg, Michael J E

2015-09-01

Each cell type found within the human body performs a diverse and unique set of functions, the disruption of which can lead to disease. However, there currently exists no systematic mapping between cell types and the diseases they can cause. In this study, we integrate protein-protein interaction data with high-quality cell-type-specific gene expression data from the FANTOM5 project to build the largest collection of cell-type-specific interactomes created to date. We develop a novel method, called gene set compactness (GSC), that contrasts the relative positions of disease-associated genes across 73 cell-type-specific interactomes to map genes associated with 196 diseases to the cell types they affect. We conduct text-mining of the PubMed database to produce an independent resource of disease-associated cell types, which we use to validate our method. The GSC method successfully identifies known disease-cell-type associations, as well as highlighting associations that warrant further study. This includes mast cells and multiple sclerosis, a cell population currently being targeted in a multiple sclerosis phase 2 clinical trial. Furthermore, we build a cell-type-based diseasome using the cell types identified as manifesting each disease, offering insight into diseases linked through etiology. The data set produced in this study represents the first large-scale mapping of diseases to the cell types in which they are manifested and will therefore be useful in the study of disease systems. Overall, we demonstrate that our approach links disease-associated genes to the phenotypes they produce, a key goal within systems medicine.

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

Inductive matrix completion for predicting gene-disease associations.

PubMed

Natarajan, Nagarajan; Dhillon, Inderjit S

2014-06-15

Most existing methods for predicting causal disease genes rely on specific type of evidence, and are therefore limited in terms of applicability. More often than not, the type of evidence available for diseases varies-for example, we may know linked genes, keywords associated with the disease obtained by mining text, or co-occurrence of disease symptoms in patients. Similarly, the type of evidence available for genes varies-for example, specific microarray probes convey information only for certain sets of genes. In this article, we apply a novel matrix-completion method called Inductive Matrix Completion to the problem of predicting gene-disease associations; it combines multiple types of evidence (features) for diseases and genes to learn latent factors that explain the observed gene-disease associations. We construct features from different biological sources such as microarray expression data and disease-related textual data. A crucial advantage of the method is that it is inductive; it can be applied to diseases not seen at training time, unlike traditional matrix-completion approaches and network-based inference methods that are transductive. Comparison with state-of-the-art methods on diseases from the Online Mendelian Inheritance in Man (OMIM) database shows that the proposed approach is substantially better-it has close to one-in-four chance of recovering a true association in the top 100 predictions, compared to the recently proposed Catapult method (second best) that has <15% chance. We demonstrate that the inductive method is particularly effective for a query disease with no previously known gene associations, and for predicting novel genes, i.e. genes that are previously not linked to diseases. Thus the method is capable of predicting novel genes even for well-characterized diseases. We also validate the novelty of predictions by evaluating the method on recently reported OMIM associations and on associations recently reported in the literature

Zinc-finger protein-targeted gene regulation: Genomewide single-gene specificity

PubMed Central

Tan, Siyuan; Guschin, Dmitry; Davalos, Albert; Lee, Ya-Li; Snowden, Andrew W.; Jouvenot, Yann; Zhang, H. Steven; Howes, Katherine; McNamara, Andrew R.; Lai, Albert; Ullman, Chris; Reynolds, Lindsey; Moore, Michael; Isalan, Mark; Berg, Lutz-Peter; Campos, Bradley; Qi, Hong; Spratt, S. Kaye; Case, Casey C.; Pabo, Carl O.; Campisi, Judith; Gregory, Philip D.

2003-01-01

Zinc-finger protein transcription factors (ZFP TFs) can be designed to control the expression of any desired target gene, and thus provide potential therapeutic tools for the study and treatment of disease. Here we report that a ZFP TF can repress target gene expression with single-gene specificity within the human genome. A ZFP TF repressor that binds an 18-bp recognition sequence within the promoter of the endogenous CHK2 gene gives a >10-fold reduction in CHK2 mRNA and protein. This level of repression was sufficient to generate a functional phenotype, as demonstrated by the loss of DNA damage-induced CHK2-dependent p53 phosphorylation. We determined the specificity of repression by using DNA microarrays and found that the ZFP TF repressed a single gene (CHK2) within the monitored genome in two different cell types. These data demonstrate the utility of ZFP TFs as precise tools for target validation, and highlight their potential as clinical therapeutics. PMID:14514889

Identification of susceptible genes for complex chronic diseases based on disease risk functional SNPs and interaction networks.

PubMed

Li, Wan; Zhu, Lina; Huang, Hao; He, Yuehan; Lv, Junjie; Li, Weimin; Chen, Lina; He, Weiming

2017-10-01

Complex chronic diseases are caused by the effects of genetic and environmental factors. Single nucleotide polymorphisms (SNPs), one common type of genetic variations, played vital roles in diseases. We hypothesized that disease risk functional SNPs in coding regions and protein interaction network modules were more likely to contribute to the identification of disease susceptible genes for complex chronic diseases. This could help to further reveal the pathogenesis of complex chronic diseases. Disease risk SNPs were first recognized from public SNP data for coronary heart disease (CHD), hypertension (HT) and type 2 diabetes (T2D). SNPs in coding regions that were classified into nonsense and missense by integrating several SNP functional annotation databases were treated as functional SNPs. Then, regions significantly associated with each disease were screened using random permutations for disease risk functional SNPs. Corresponding to these regions, 155, 169 and 173 potential disease susceptible genes were identified for CHD, HT and T2D, respectively. A disease-related gene product interaction network in environmental context was constructed for interacting gene products of both disease genes and potential disease susceptible genes for these diseases. After functional enrichment analysis for disease associated modules, 5 CHD susceptible genes, 7 HT susceptible genes and 3 T2D susceptible genes were finally identified, some of which had pleiotropic effects. Most of these genes were verified to be related to these diseases in literature. This was similar for disease genes identified from another method proposed by Lee et al. from a different aspect. This research could provide novel perspectives for diagnosis and treatment of complex chronic diseases and susceptible genes identification for other diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Allele specific expression analysis identifies regulatory variation associated with stress-related genes in the Mexican highland maize landrace Palomero Toluqueño

PubMed Central

González-Segovia, Eric; Ross-Ibarra, Jeffrey; Simpson, June K.

2017-01-01

Background Gene regulatory variation has been proposed to play an important role in the adaptation of plants to environmental stress. In the central highlands of Mexico, farmer selection has generated a unique group of maize landraces adapted to the challenges of the highland niche. In this study, gene expression in Mexican highland maize and a reference maize breeding line were compared to identify evidence of regulatory variation in stress-related genes. It was hypothesised that local adaptation in Mexican highland maize would be associated with a transcriptional signature observable even under benign conditions. Methods Allele specific expression analysis was performed using the seedling-leaf transcriptome of an F1 individual generated from the cross between the highland adapted Mexican landrace Palomero Toluqueño and the reference line B73, grown under benign conditions. Results were compared with a published dataset describing the transcriptional response of B73 seedlings to cold, heat, salt and UV treatments. Results A total of 2,386 genes were identified to show allele specific expression. Of these, 277 showed an expression difference between Palomero Toluqueño and B73 alleles under benign conditions that anticipated the response of B73 cold, heat, salt and/or UV treatments, and, as such, were considered to display a prior stress response. Prior stress response candidates included genes associated with plant hormone signaling and a number of transcription factors. Construction of a gene co-expression network revealed further signaling and stress-related genes to be among the potential targets of the transcription factors candidates. Discussion Prior activation of responses may represent the best strategy when stresses are severe but predictable. Expression differences observed here between Palomero Toluqueño and B73 alleles indicate the presence of cis-acting regulatory variation linked to stress-related genes in Palomero Toluqueño. Considered alongside

Gene regulation mediates host specificity of a bacterial pathogen.

PubMed

Killiny, Nabil; Almeida, Rodrigo P P

2011-12-01

Many bacterial plant pathogens have a gene-for-gene relationship that determines host specificity. However, there are pathogens such as the xylem-limited bacterium Xylella fastidiosa that do not carry genes considered essential for the gene-for-gene model, such as those coding for a type III secretion system and effector molecules. Nevertheless, X. fastidiosa subspecies are host specific. A comparison of symptom development and host colonization after infection of plants with several mutant strains in two hosts, grapevines and almonds, indicated that X. fastidiosa virulence mechanisms are similar in those plants. Thus, we tested if modification of gene regulation patterns, by affecting the production of a cell-cell signalling molecule (DSF), impacted host specificity in X. fastidiosa. Results show that disruption of the rpfF locus, required for DSF synthesis, in a strain incapable of causing disease in grapevines, leads to symptom development in that host. These data are indicative that the core machinery required for the colonization of grapevines is present in that strain, and that changes in gene regulation alone can lead X. fastidiosa to exploit a novel host. The study of the evolution and mechanisms of host specificity mediated by gene regulation at the genome level could lead to important insights on the emergence of new diseases. © 2011 Society for Applied Microbiology and Blackwell Publishing Ltd.

Current Status and Challenges in Identifying Disease Resistance Genes in Brassica napus

PubMed Central

Neik, Ting Xiang; Barbetti, Martin J.; Batley, Jacqueline

2017-01-01

Brassica napus is an economically important crop across different continents including temperate and subtropical regions in Europe, Canada, South Asia, China and Australia. Its widespread cultivation also brings setbacks as it plays host to fungal, oomycete and chytrid pathogens that can lead to serious yield loss. For sustainable crop production, identification of resistance (R) genes in B. napus has become of critical importance. In this review, we discuss four key pathogens affecting Brassica crops: Clubroot (Plasmodiophora brassicae), Blackleg (Leptosphaeria maculans and L. biglobosa), Sclerotinia Stem Rot (Sclerotinia sclerotiorum), and Downy Mildew (Hyaloperonospora parasitica). We first review current studies covering prevalence of these pathogens on Brassica crops and highlight the R genes and QTL that have been identified from Brassica species against these pathogens. Insights into the relationships between the pathogen and its Brassica host, the unique host resistance mechanisms and how these affect resistance outcomes is also presented. We discuss challenges in identification and deployment of R genes in B. napus in relation to highly specific genetic interactions between host subpopulations and pathogen pathotypes and emphasize the need for common or shared techniques and research materials or tighter collaboration between researchers to reconcile the inconsistencies in the research outcomes. Using current genomics tools, we provide examples of how characterization and cloning of R genes in B. napus can be carried out more effectively. Lastly, we put forward strategies to breed resistant cultivars through introgressions supported by genomic approaches and suggest prospects that can be implemented in the future for a better, pathogen-resistant B. napus. PMID:29163558

Identifying Disease Associated miRNAs Based on Protein Domains.

PubMed

Qin, Gui-Min; Li, Rui-Yi; Zhao, Xing-Ming

2016-01-01

MicroRNAs (miRNAs) are a class of small endogenous non-coding genes, acting as regulators in the post-transcriptional processes. Recently, the miRNAs are found to be widely involved in different types of diseases. Therefore, the identification of disease associated miRNAs can help understand the mechanisms that underlie the disease and identify new biomarkers. However, it is not easy to identify the miRNAs related to diseases due to its extensive involvements in various biological processes. In this work, we present a new approach to identify disease associated miRNAs based on domains, the functional and structural blocks of proteins. The results on real datasets demonstrate that our method can effectively identify disease related miRNAs with high precision.

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. Copyright © 2016 Elsevier Inc. All rights reserved.

Generation of Healthy Mice from Gene-Corrected Disease-Specific Induced Pluripotent Stem Cells

PubMed Central

Rittelmeyer, Ina; Sharma, Amar Deep; Sgodda, Malte; Zaehres, Holm; Bleidißel, Martina; Greber, Boris; Gentile, Luca; Han, Dong Wook; Rudolph, Cornelia; Steinemann, Doris; Schambach, Axel; Ott, Michael; Schöler, Hans R.; Cantz, Tobias

2011-01-01

Using the murine model of tyrosinemia type 1 (fumarylacetoacetate hydrolase [FAH] deficiency; FAH −/− mice) as a paradigm for orphan disorders, such as hereditary metabolic liver diseases, we evaluated fibroblast-derived FAH −/−-induced pluripotent stem cells (iPS cells) as targets for gene correction in combination with the tetraploid embryo complementation method. First, after characterizing the FAH −/− iPS cell lines, we aggregated FAH −/−-iPS cells with tetraploid embryos and obtained entirely FAH −/−-iPS cell–derived mice that were viable and exhibited the phenotype of the founding FAH −/− mice. Then, we transduced FAH cDNA into the FAH −/−-iPS cells using a third-generation lentiviral vector to generate gene-corrected iPS cells. We could not detect any chromosomal alterations in these cells by high-resolution array CGH analysis, and after their aggregation with tetraploid embryos, we obtained fully iPS cell–derived healthy mice with an astonishing high efficiency for full-term development of up to 63.3%. The gene correction was validated functionally by the long-term survival and expansion of FAH-positive cells of these mice after withdrawal of the rescuing drug NTBC (2-(2-nitro-4-fluoromethylbenzoyl)-1,3-cyclohexanedione). Furthermore, our results demonstrate that both a liver-specific promoter (transthyretin, TTR)-driven FAH transgene and a strong viral promoter (from spleen focus-forming virus, SFFV)-driven FAH transgene rescued the FAH-deficiency phenotypes in the mice derived from the respective gene-corrected iPS cells. In conclusion, our data demonstrate that a lentiviral gene repair strategy does not abrogate the full pluripotent potential of fibroblast-derived iPS cells, and genetic manipulation of iPS cells in combination with tetraploid embryo aggregation provides a practical and rapid approach to evaluate the efficacy of gene correction of human diseases in mouse models. PMID:21765802

Gene Therapy for Infectious Diseases

PubMed Central

Bunnell, Bruce A.; Morgan, Richard A.

1998-01-01

Gene therapy is being investigated as an alternative treatment for a wide range of infectious diseases that are not amenable to standard clinical management. Approaches to gene therapy for infectious diseases can be divided into three broad categories: (i) gene therapies based on nucleic acid moieties, including antisense DNA or RNA, RNA decoys, and catalytic RNA moieties (ribozymes); (ii) protein approaches such as transdominant negative proteins and single-chain antibodies; and (iii) immunotherapeutic approaches involving genetic vaccines or pathogen-specific lymphocytes. It is further possible that combinations of the aforementioned approaches will be used simultaneously to inhibit multiple stages of the life cycle of the infectious agent. PMID:9457428

Computation and application of tissue-specific gene set weights.

PubMed

Frost, H Robert

2018-04-06

Gene set testing, or pathway analysis, has become a critical tool for the analysis of highdimensional genomic data. Although the function and activity of many genes and higher-level processes is tissue-specific, gene set testing is typically performed in a tissue agnostic fashion, which impacts statistical power and the interpretation and replication of results. To address this challenge, we have developed a bioinformatics approach to compute tissuespecific weights for individual gene sets using information on tissue-specific gene activity from the Human Protein Atlas (HPA). We used this approach to create a public repository of tissue-specific gene set weights for 37 different human tissue types from the HPA and all collections in the Molecular Signatures Database (MSigDB). To demonstrate the validity and utility of these weights, we explored three different applications: the functional characterization of human tissues, multi-tissue analysis for systemic diseases and tissue-specific gene set testing. All data used in the reported analyses is publicly available. An R implementation of the method and tissue-specific weights for MSigDB gene set collections can be downloaded at http://www.dartmouth.edu/∼hrfrost/TissueSpecificGeneSets. rob.frost@dartmouth.edu.

Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

PubMed Central

Xu, Pingzhen

2018-01-01

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

PubMed

Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

2016-09-01

Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

Transcriptomic analysis reveals tomato genes whose expression is induced specifically during effector-triggered immunity and identifies the Epk1 protein kinase which is required for the host response to three bacterial effector proteins.

PubMed

Pombo, Marina A; Zheng, Yi; Fernandez-Pozo, Noe; Dunham, Diane M; Fei, Zhangjun; Martin, Gregory B

2014-01-01

Plants have two related immune systems to defend themselves against pathogen attack. Initially,pattern-triggered immunity is activated upon recognition of microbe-associated molecular patterns by pattern recognition receptors. Pathogenic bacteria deliver effector proteins into the plant cell that interfere with this immune response and promote disease. However, some plants express resistance proteins that detect the presence of specific effectors leading to a robust defense response referred to as effector-triggered immunity. The interaction of tomato with Pseudomonas syringae pv. tomato is an established model system for understanding the molecular basis of these plant immune responses. We apply high-throughput RNA sequencing to this pathosystem to identify genes whose expression changes specifically during pattern-triggered or effector-triggered immunity. We then develop reporter genes for each of these responses that will enable characterization of the host response to the large collection of P. s. pv. tomato strains that express different combinations of effectors. Virus-induced gene silencing of 30 of the effector-triggered immunity-specific genes identifies Epk1 which encodes a predicted protein kinase from a family previously unknown to be involved in immunity. Knocked-down expression of Epk1 compromises effector-triggered immunity triggered by three bacterial effectors but not by effectors from non-bacterial pathogens. Epistasis experiments indicate that Epk1 acts upstream of effector-triggered immunity-associated MAP kinase signaling. Using RNA-seq technology we identify genes involved in specific immune responses. A functional genomics screen led to the discovery of Epk1, a novel predicted protein kinase required for plant defense activation upon recognition of three different bacterial effectors.

Inheritance-mode specific pathogenicity prioritization (ISPP) for human protein coding genes.

PubMed

Hsu, Jacob Shujui; Kwan, Johnny S H; Pan, Zhicheng; Garcia-Barcelo, Maria-Mercè; Sham, Pak Chung; Li, Miaoxin

2016-10-15

Exome sequencing studies have facilitated the detection of causal genetic variants in yet-unsolved Mendelian diseases. However, the identification of disease causal genes among a list of candidates in an exome sequencing study is still not fully settled, and it is often difficult to prioritize candidate genes for follow-up studies. The inheritance mode provides crucial information for understanding Mendelian diseases, but none of the existing gene prioritization tools fully utilize this information. We examined the characteristics of Mendelian disease genes under different inheritance modes. The results suggest that Mendelian disease genes with autosomal dominant (AD) inheritance mode are more haploinsufficiency and de novo mutation sensitive, whereas those autosomal recessive (AR) genes have significantly more non-synonymous variants and regulatory transcript isoforms. In addition, the X-linked (XL) Mendelian disease genes have fewer non-synonymous and synonymous variants. As a result, we derived a new scoring system for prioritizing candidate genes for Mendelian diseases according to the inheritance mode. Our scoring system assigned to each annotated protein-coding gene (N = 18 859) three pathogenic scores according to the inheritance mode (AD, AR and XL). This inheritance mode-specific framework achieved higher accuracy (area under curve  = 0.84) in XL mode. The inheritance-mode specific pathogenicity prioritization (ISPP) outperformed other well-known methods including Haploinsufficiency, Recessive, Network centrality, Genic Intolerance, Gene Damage Index and Gene Constraint scores. This systematic study suggests that genes manifesting disease inheritance modes tend to have unique characteristics. ISPP is included in KGGSeq v1.0 (http://grass.cgs.hku.hk/limx/kggseq/), and source code is available from (https://github.com/jacobhsu35/ISPP.git). mxli@hku.hkSupplementary information: Supplementary data are available at Bioinformatics online. © The Author

LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network.

PubMed

Wei, Pi-Jing; Zhang, Di; Xia, Junfeng; Zheng, Chun-Hou

2016-12-23

Cancer is a complex disease which is characterized by the accumulation of genetic alterations during the patient's lifetime. With the development of the next-generation sequencing technology, multiple omics data, such as cancer genomic, epigenomic and transcriptomic data etc., can be measured from each individual. Correspondingly, one of the key challenges is to pinpoint functional driver mutations or pathways, which contributes to tumorigenesis, from millions of functional neutral passenger mutations. In this paper, in order to identify driver genes effectively, we applied a generalized additive model to mutation profiles to filter genes with long length and constructed a new gene-gene interaction network. Then we integrated the mutation data and expression data into the gene-gene interaction network. Lastly, greedy algorithm was used to prioritize candidate driver genes from the integrated data. We named the proposed method Length-Net-Driver (LNDriver). Experiments on three TCGA datasets, i.e., head and neck squamous cell carcinoma, kidney renal clear cell carcinoma and thyroid carcinoma, demonstrated that the proposed method was effective. Also, it can identify not only frequently mutated drivers, but also rare candidate driver genes.

Analyzing the most frequent disease loci in targeted patient categories optimizes disease gene identification and test accuracy worldwide.

PubMed

Lebo, Roger V; Tonk, Vijay S

2015-01-21

Our genomewide studies support targeted testing the most frequent genetic diseases by patient category: (1) pregnant patients, (2) at-risk conceptuses, (3) affected children, and (4) abnormal adults. This approach not only identifies most reported disease causing sequences accurately, but also minimizes incorrectly identified additional disease causing loci. Diseases were grouped in descending order of occurrence from four data sets: (1) GeneTests 534 listed population prevalences, (2) 4129 high risk prenatal karyotypes, (3) 1265 affected patient microarrays, and (4) reanalysis of 25,452 asymptomatic patient results screened prenatally for 108 genetic diseases. These most frequent diseases are categorized by transmission: (A) autosomal recessive, (B) X-linked, (C) autosomal dominant, (D) microscopic chromosome rearrangements, (E) submicroscopic copy number changes, and (F) frequent ethnic diseases. Among affected and carrier patients worldwide, most reported mutant genes would be identified correctly according to one of four patient categories from at-risk couples with <64 tested genes to affected adults with 314 tested loci. Three clinically reported patient series confirmed this approach. First, only 54 targeted chromosomal sites would have detected all 938 microscopically visible unbalanced karyotypes among 4129 karyotyped POC, CVS, and amniocentesis samples. Second, 37 of 48 reported aneuploid regions were found among our 1265 clinical microarrays confirming the locations of 8 schizophrenia loci and 20 aneuploidies altering intellectual ability, while also identifying 9 of the most frequent deletion syndromes. Third, testing 15 frequent genes would have identified 124 couples with a 1 in 4 risk of a fetus with a recessive disease compared to the 127 couples identified by testing all 108 genes, while testing all mutations in 15 genes could have identified more couples. Testing the most frequent disease causing abnormalities in 1 of 8 reported disease loci [~1 of

Disease-specific molecular events in cortical multiple sclerosis lesions

PubMed Central

Wimmer, Isabella; Höftberger, Romana; Gerlach, Susanna; Haider, Lukas; Zrzavy, Tobias; Hametner, Simon; Mahad, Don; Binder, Christoph J.; Krumbholz, Markus; Bauer, Jan; Bradl, Monika

2013-01-01

Cortical lesions constitute an important part of multiple sclerosis pathology. Although inflammation appears to play a role in their formation, the mechanisms leading to demyelination and neurodegeneration are poorly understood. We aimed to identify some of these mechanisms by combining gene expression studies with neuropathological analysis. In our study, we showed that the combination of inflammation, plaque-like primary demyelination and neurodegeneration in the cortex is specific for multiple sclerosis and is not seen in other chronic inflammatory diseases mediated by CD8-positive T cells (Rasmussen’s encephalitis), B cells (B cell lymphoma) or complex chronic inflammation (tuberculous meningitis, luetic meningitis or chronic purulent meningitis). In addition, we performed genome-wide microarray analysis comparing micro-dissected active cortical multiple sclerosis lesions with those of tuberculous meningitis (inflammatory control), Alzheimer’s disease (neurodegenerative control) and with cortices of age-matched controls. More than 80% of the identified multiple sclerosis-specific genes were related to T cell-mediated inflammation, microglia activation, oxidative injury, DNA damage and repair, remyelination and regenerative processes. Finally, we confirmed by immunohistochemistry that oxidative damage in cortical multiple sclerosis lesions is associated with oligodendrocyte and neuronal injury, the latter also affecting axons and dendrites. Our study provides new insights into the complex mechanisms of neurodegeneration and regeneration in the cortex of patients with multiple sclerosis. PMID:23687122

Extended exome sequencing identifies BACH2 as a novel major risk locus for Addison's disease.

PubMed

Eriksson, D; Bianchi, M; Landegren, N; Nordin, J; Dalin, F; Mathioudaki, A; Eriksson, G N; Hultin-Rosenberg, L; Dahlqvist, J; Zetterqvist, H; Karlsson, Å; Hallgren, Å; Farias, F H G; Murén, E; Ahlgren, K M; Lobell, A; Andersson, G; Tandre, K; Dahlqvist, S R; Söderkvist, P; Rönnblom, L; Hulting, A-L; Wahlberg, J; Ekwall, O; Dahlqvist, P; Meadows, J R S; Bensing, S; Lindblad-Toh, K; Kämpe, O; Pielberg, G R

2016-12-01

Autoimmune disease is one of the leading causes of morbidity and mortality worldwide. In Addison's disease, the adrenal glands are targeted by destructive autoimmunity. Despite being the most common cause of primary adrenal failure, little is known about its aetiology. To understand the genetic background of Addison's disease, we utilized the extensively characterized patients of the Swedish Addison Registry. We developed an extended exome capture array comprising a selected set of 1853 genes and their potential regulatory elements, for the purpose of sequencing 479 patients with Addison's disease and 1394 controls. We identified BACH2 (rs62408233-A, OR = 2.01 (1.71-2.37), P = 1.66 × 10 -15 , MAF 0.46/0.29 in cases/controls) as a novel gene associated with Addison's disease development. We also confirmed the previously known associations with the HLA complex. Whilst BACH2 has been previously reported to associate with organ-specific autoimmune diseases co-inherited with Addison's disease, we have identified BACH2 as a major risk locus in Addison's disease, independent of concomitant autoimmune diseases. Our results may enable future research towards preventive disease treatment. © 2016 The Authors. Journal of Internal Medicine published by John Wiley & Sons Ltd on behalf of Association for Publication of The Journal of Internal Medicine.

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

USDA-ARS?s Scientific Manuscript database

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

Genetic variants in the PIWI-piRNA pathway gene DCP1A predict melanoma disease-specific survival.

PubMed

Zhang, Weikang; Liu, Hongliang; Yin, Jieyun; Wu, Wenting; Zhu, Dakai; Amos, Christopher I; Fang, Shenying; Lee, Jeffrey E; Li, Yi; Han, Jiali; Wei, Qingyi

2016-12-15

The Piwi-piRNA pathway is important for germ cell maintenance, genome integrity, DNA methylation and retrotransposon control and thus may be involved in cancer development. In this study, we comprehensively analyzed prognostic roles of 3,116 common SNPs in PIWI-piRNA pathway genes in melanoma disease-specific survival. A published genome-wide association study (GWAS) by The University of Texas M.D. Anderson Cancer Center was used to identify associated SNPs, which were later validated by another GWAS from the Harvard Nurses' Health Study and Health Professionals Follow-up Study. After multiple testing correction, we found that there were 27 common SNPs in two genes (PIWIL4 and DCP1A) with false discovery rate < 0.2 in the discovery dataset. Three tagSNPs (i.e., rs7933369 and rs508485 in PIWIL4; rs11551405 in DCP1A) were replicated. The rs11551405 A allele, located at the 3' UTR microRNA binding site of DCP1A, was associated with an increased risk of melanoma disease-specific death in both discovery dataset [adjusted Hazards ratio (HR) = 1.66, 95% confidence interval (CI) = 1.21-2.27, p =1.50 × 10 -3 ] and validation dataset (HR = 1.55, 95% CI = 1.03-2.34, p = 0.038), compared with the C allele, and their meta-analysis showed an HR of 1.62 (95% CI, 1.26-2.08, p =1.55 × 10 -4 ). Using RNA-seq data from the 1000 Genomes Project, we found that DCP1A mRNA expression levels increased significantly with the A allele number of rs11551405. Additional large, prospective studies are needed to validate these findings. © 2016 UICC.

Identifying Candidate Reprogramming Genes in Mouse Induced Pluripotent Stem Cells.

PubMed

Gao, Fang; Li, Jingyu; Zhang, Heng; Yang, Xu; An, Tiezhu

2017-08-01

Factor-based induced reprogramming approaches have tremendous potential for human regenerative medicine, but the efficiencies of these approaches are still low. In this study, we analyzed the global transcriptional profiles of mouse induced pluripotent stem cells (miPSCs) and mouse embryonic stem cells (mESCs) from seven different labs and present here the first successful clustering according to cell type, not by lab of origin. We identified 2131 different expression genes (DEs) as candidate pluripotency-associated genes by comparing mESCs/miPSCs with somatic cells and 720 DEs between miPSCs and mESCs. Interestingly, there was a significant overlap between the two DE sets. Therefore, we defined the overlap DEs as "consensus DEs" including 313 miPSC-specific genes expressed at a higher level in miPSCs versus mESCs and 184 mESC-specific genes in total and reasoned that these may contribute to the differences in pluripotency between mESCs and miPSCs. A classification of "consensus DEs" according to their different expression levels between somatic cells and mESCs/miPSCs shows that 86% of the miPSC-specific genes are more highly expressed in somatic cells, while 73% of mESC-specific genes are highly expressed in mESCs/miPSCs, indicating that the miPSCs have not efficiently silenced the expression pattern of the somatic cells from which they are derived and failed to completely induce the genes with high expression levels in mESCs. We further revealed a strong correlation between oocyte-enriched factors and insufficiently induced mESC-specific genes and identified 11 hub genes via network analysis. In light of these findings, we postulated that these key hub genes might not only drive somatic cell nuclear transfer (SCNT) reprogramming but also augment the efficiency and quality of miPSC reprogramming.

A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders.

PubMed

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

2015-05-05

Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel 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 that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A Heterogeneous Network Based Method for Identifying GBM-Related Genes by Integrating Multi-Dimensional Data.

PubMed

Chen Peng; Ao Li

2017-01-01

The emergence of multi-dimensional data offers opportunities for more comprehensive analysis of the molecular characteristics of human diseases and therefore improving diagnosis, treatment, and prevention. In this study, we proposed a heterogeneous network based method by integrating multi-dimensional data (HNMD) to identify GBM-related genes. The novelty of the method lies in that the multi-dimensional data of GBM from TCGA dataset that provide comprehensive information of genes, are combined with protein-protein interactions to construct a weighted heterogeneous network, which reflects both the general and disease-specific relationships between genes. In addition, a propagation algorithm with resistance is introduced to precisely score and rank GBM-related genes. The results of comprehensive performance evaluation show that the proposed method significantly outperforms the network based methods with single-dimensional data and other existing approaches. Subsequent analysis of the top ranked genes suggests they may be functionally implicated in GBM, which further corroborates the superiority of the proposed method. The source code and the results of HNMD can be downloaded from the following URL: http://bioinformatics.ustc.edu.cn/hnmd/ .

RNA-Seq analysis and annotation of a draft blueberry genome assembly identifies candidate genes involved in fruit ripening, biosynthesis of bioactive compounds, and stage-specific alternative splicing.

PubMed

Gupta, Vikas; Estrada, April D; Blakley, Ivory; Reid, Rob; Patel, Ketan; Meyer, Mason D; Andersen, Stig Uggerhøj; Brown, Allan F; Lila, Mary Ann; Loraine, Ann E

2015-01-01

Blueberries are a rich source of antioxidants and other beneficial compounds that can protect against disease. Identifying genes involved in synthesis of bioactive compounds could enable the breeding of berry varieties with enhanced health benefits. Toward this end, we annotated a previously sequenced draft blueberry genome assembly using RNA-Seq data from five stages of berry fruit development and ripening. Genome-guided assembly of RNA-Seq read alignments combined with output from ab initio gene finders produced around 60,000 gene models, of which more than half were similar to proteins from other species, typically the grape Vitis vinifera. Comparison of gene models to the PlantCyc database of metabolic pathway enzymes identified candidate genes involved in synthesis of bioactive compounds, including bixin, an apocarotenoid with potential disease-fighting properties, and defense-related cyanogenic glycosides, which are toxic. Cyanogenic glycoside (CG) biosynthetic enzymes were highly expressed in green fruit, and a candidate CG detoxification enzyme was up-regulated during fruit ripening. Candidate genes for ethylene, anthocyanin, and 400 other biosynthetic pathways were also identified. Homology-based annotation using Blast2GO and InterPro assigned Gene Ontology terms to around 15,000 genes. RNA-Seq expression profiling showed that blueberry growth, maturation, and ripening involve dynamic gene expression changes, including coordinated up- and down-regulation of metabolic pathway enzymes and transcriptional regulators. Analysis of RNA-seq alignments identified developmentally regulated alternative splicing, promoter use, and 3' end formation. We report genome sequence, gene models, functional annotations, and RNA-Seq expression data that provide an important new resource enabling high throughput studies in blueberry.

Gene editing for skin diseases: designer nucleases as tools for gene therapy of skin fragility disorders.

PubMed

March, Oliver P; Reichelt, Julia; Koller, Ulrich

2018-04-01

What is the topic of this review? This review concerns current gene editing strategies for blistering skin diseases with respect to individual genetic constellations and distinct conditions. What advances does it highlight? Specificity and safety dominate the discussion of gene editing applications for gene therapy, where a number of tools are implemented. Recent developments in this rapidly progressing field pose further questions regarding which tool is best suited for each particular use. The current treatment of inherited blistering skin diseases, such as epidermolysis bullosa (EB), is largely restricted to wound care and pain management. More effective therapeutic strategies are urgently required, and targeting the genetic basis of these severe diseases is now within reach. Here, we describe current gene editing tools and their potential to correct gene function in monogenetic blistering skin diseases. We present the features of the most frequently used gene editing techniques, transcription activator-like effector nuclease (TALEN) and clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9), determining their preferential application for specific genetic conditions, including the type of mutational inheritance, the targeting site within the gene or the possibility to target the mutation specifically. Both tools have traits beneficial in specific situations. Promising developments in the field engender gene editing as a potentially powerful therapeutic option for future clinical applications. © 2017 The Authors. Experimental Physiology © 2017 The Physiological Society.

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

PubMed Central

2010-01-01

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

Comparative analyses of Legionella species identifies genetic features of strains causing Legionnaires' disease.

PubMed

Gomez-Valero, Laura; Rusniok, Christophe; Rolando, Monica; Neou, Mario; Dervins-Ravault, Delphine; Demirtas, Jasmin; Rouy, Zoe; Moore, Robert J; Chen, Honglei; Petty, Nicola K; Jarraud, Sophie; Etienne, Jerome; Steinert, Michael; Heuner, Klaus; Gribaldo, Simonetta; Médigue, Claudine; Glöckner, Gernot; Hartland, Elizabeth L; Buchrieser, Carmen

2014-01-01

The genus Legionella comprises over 60 species. However, L. pneumophila and L. longbeachae alone cause over 95% of Legionnaires’ disease. To identify the genetic bases underlying the different capacities to cause disease we sequenced and compared the genomes of L. micdadei, L. hackeliae and L. fallonii (LLAP10), which are all rarely isolated from humans. We show that these Legionella species possess different virulence capacities in amoeba and macrophages, correlating with their occurrence in humans. Our comparative analysis of 11 Legionella genomes belonging to five species reveals highly heterogeneous genome content with over 60% representing species-specific genes; these comprise a complete prophage in L. micdadei, the first ever identified in a Legionella genome. Mobile elements are abundant in Legionella genomes; many encode type IV secretion systems for conjugative transfer, pointing to their importance for adaptation of the genus. The Dot/Icm secretion system is conserved, although the core set of substrates is small, as only 24 out of over 300 described Dot/Icm effector genes are present in all Legionella species. We also identified new eukaryotic motifs including thaumatin, synaptobrevin or clathrin/coatomer adaptine like domains. Legionella genomes are highly dynamic due to a large mobilome mainly comprising type IV secretion systems, while a minority of core substrates is shared among the diverse species. Eukaryotic like proteins and motifs remain a hallmark of the genus Legionella. Key factors such as proteins involved in oxygen binding, iron storage, host membrane transport and certain Dot/Icm substrates are specific features of disease-related strains.

Homophila: human disease gene cognates in Drosophila

PubMed Central

Chien, Samson; Reiter, Lawrence T.; Bier, Ethan; Gribskov, Michael

2002-01-01

Although many human genes have been associated with genetic diseases, knowing which mutations result in disease phenotypes often does not explain the etiology of a specific disease. Drosophila melanogaster provides a powerful system in which to use genetic and molecular approaches to investigate human genetic diseases. Homophila is an intergenomic resource linking the human and fly genomes in order to stimulate functional genomic investigations in Drosophila that address questions about genetic disease in humans. Homophila provides a comprehensive linkage between the disease genes compiled in Online Mendelian Inheritance in Man (OMIM) and the complete Drosophila genomic sequence. Homophila is a relational database that allows searching based on human disease descriptions, OMIM number, human or fly gene names, and sequence similarity, and can be accessed at http://homophila.sdsc.edu. PMID:11752278

Ocular findings associated with a Cys39Arg mutation in the Norrie disease gene.

PubMed

Joos, K M; Kimura, A E; Vandenburgh, K; Bartley, J A; Stone, E M

1994-12-01

To diagnose the carriers and noncarriers in a family affected with Norrie disease based on molecular analysis. Family members from three generations, including one affected patient, two obligate carriers, one carrier identified with linkage analysis, one noncarrier identified with linkage analysis, and one female family member with indeterminate carrier status, were examined clinically and electrophysiologically. Linkage analysis had previously failed to determine the carrier status of one female family member in the third generation. Blood samples were screened for mutations in the Norrie disease gene with single-strand conformation polymorphism analysis. The mutation was characterized by dideoxy-termination sequencing. Ophthalmoscopy and electroretinographic examination failed to detect the carrier state. The affected individuals and carriers in this family were found to have a transition from thymidine to cytosine in the first nucleotide of codon 39 of the Norrie disease gene, causing a cysteine-to-arginine mutation. Single-strand conformation polymorphism analysis identified a patient of indeterminate status (by linkage) to be a noncarrier of Norrie disease. Ophthalmoscopy and electroretinography could not identify carriers of this Norrie disease mutation. Single-strand conformation polymorphism analysis was more sensitive and specific than linkage analysis in identifying carriers in this family.

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

PubMed

Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

2017-04-27

Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By

Genetic and molecular risk factors within the newly identified primate-specific exon of the SAP97/DLG1 gene in the 3q29 schizophrenia-associated locus.

PubMed

Uezato, Akihito; Yamamoto, Naoki; Jitoku, Daisuke; Haramo, Emiko; Hiraaki, Eri; Iwayama, Yoshimi; Toyota, Tomoko; Umino, Masakazu; Umino, Asami; Iwata, Yasuhide; Suzuki, Katsuaki; Kikuchi, Mitsuru; Hashimoto, Tasuku; Kanahara, Nobuhisa; Kurumaji, Akeo; Yoshikawa, Takeo; Nishikawa, Toru

2017-12-01

The synapse-associated protein 97/discs, large homolog 1 of Drosophila (DLG1) gene encodes synaptic scaffold PDZ proteins interacting with ionotropic glutamate receptors including the N-methyl-D-aspartate type glutamate receptor (NMDAR) that is presumed to be hypoactive in brains of patients with schizophrenia. The DLG1 gene resides in the chromosomal position 3q29, the microdeletion of which confers a 40-fold increase in the risk for schizophrenia. In the present study, we performed genetic association analyses for DLG1 gene using a Japanese cohort with 1808 schizophrenia patients and 2170 controls. We detected an association which remained significant after multiple comparison testing between schizophrenia and the single nucleotide polymorphism (SNP) rs3915512 that is located within the newly identified primate-specific exon (exon 3b) of the DLG1 gene and constitutes the exonic splicing enhancer sequence. When stratified by onset age, although it did not survive multiple comparisons, the association was observed in non-early onset schizophrenia, whose onset-age selectivity is consistent with our recent postmortem study demonstrating a decrease in the expression of the DLG1 variant in early-onset schizophrenia. Although the present study did not demonstrate the previously reported association of the SNP rs9843659 by itself, a meta-analysis revealed a significant association between DLG1 gene and schizophrenia. These findings provide a valuable clue for molecular mechanisms on how genetic variations in the primate-specific exon of the gene in the schizophrenia-associated 3q29 locus affect its regulation in the glutamate system and lead to the disease onset around a specific stage of brain development. © 2017 Wiley Periodicals, Inc.

Republished review: Gene therapy for ocular diseases.

PubMed

Liu, Melissa M; Tuo, Jingsheng; Chan, Chi-Chao

2011-07-01

The eye is an easily accessible, highly compartmentalised and immune-privileged organ that offers unique advantages as a gene therapy target. Significant advancements have been made in understanding the genetic pathogenesis of ocular diseases, and gene replacement and gene silencing have been implicated as potentially efficacious therapies. Recent improvements have been made in the safety and specificity of vector-based ocular gene transfer methods. Proof-of-concept for vector-based gene therapies has also been established in several experimental models of human ocular diseases. After nearly two decades of ocular gene therapy research, preliminary successes are now being reported in phase 1 clinical trials for the treatment of Leber congenital amaurosis. This review describes current developments and future prospects for ocular gene therapy. Novel methods are being developed to enhance the performance and regulation of recombinant adeno-associated virus- and lentivirus-mediated ocular gene transfer. Gene therapy prospects have advanced for a variety of retinal disorders, including retinitis pigmentosa, retinoschisis, Stargardt disease and age-related macular degeneration. Advances have also been made using experimental models for non-retinal diseases, such as uveitis and glaucoma. These methodological advancements are critical for the implementation of additional gene-based therapies for human ocular diseases in the near future.

Genes involved in muscle contractility and nutrient signaling pathways within celiac disease risk loci show differential mRNA expression.

PubMed

Montén, Caroline; Gudjonsdottir, Audur H; Browaldh, Lars; Arnell, Henrik; Nilsson, Staffan; Agardh, Daniel; Naluai, Åsa Torinsson

2015-06-30

Risk gene variants for celiac disease, identified in genome-wide linkage and association studies, might influence molecular pathways important for disease development. The aim was to examine expression levels of potential risk genes close to these variants in the small intestine and peripheral blood and also to test if the non-coding variants affect nearby gene expression levels in children with celiac disease. Intestinal biopsy and peripheral blood RNA was isolated from 167 children with celiac disease, 61 with potential celiac disease and 174 disease controls. Transcript levels for 88 target genes, selected from celiac disease risk loci, were analyzed in biopsies of a smaller sample subset by qPCR. Differentially expressed genes (3 from the pilot and 8 previously identified) were further validated in the larger sample collection (n = 402) of both tissues and correlated to nearby celiac disease risk variants. All genes were significantly down- or up-regulated in the intestinal mucosa of celiac disease children, NTS being most down-regulated (Fold change 3.6, p < 0.001). In contrast, PPP1R12B isoform C was up-regulated in the celiac disease mucosa (Fold change 1.9, p < 0.001). Allele specific expression of GLS (rs6741418, p = 0.009), INSR (rs7254060, p = 0.003) and NCALD (rs652008, p = 0.005) was also detected in the biopsies. Two genes (APPL2 and NCALD) were differentially expressed in peripheral blood but no allele specific expression was observed in this tissue. The differential expression of NTS and PPP1R12B indicate a potential role for smooth muscle contractility and cell proliferation in celiac disease, whereas other genes like GLS, NCALD and INSR suggests involvement of nutrient signaling and energy homeostasis in celiac disease pathogenesis. A disturbance in any of these pathways might contribute to development of childhood celiac disease.

Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.

PubMed

Mei, Hao; Li, Lianna; Liu, Shijian; Jiang, Fan; Griswold, Michael; Mosley, Thomas

2017-01-21

We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

Identifying a gene expression signature of cluster headache in blood

PubMed Central

Eising, Else; Pelzer, Nadine; Vijfhuizen, Lisanne S.; Vries, Boukje de; Ferrari, Michel D.; ‘t Hoen, Peter A. C.; Terwindt, Gisela M.; van den Maagdenberg, Arn M. J. M.

2017-01-01

Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20). Gene expression data were analysed by gene and by module of co-expressed genes with particular attention to previously implicated disease pathways including hypocretin dysregulation. Only moderate gene expression differences were identified and no associations were found with previously reported pathogenic mechanisms. At the level of functional gene sets, associations were observed for genes involved in several brain-related mechanisms such as GABA receptor function and voltage-gated channels. In addition, genes and modules of co-expressed genes showed a role for intracellular signalling cascades, mitochondria and inflammation. Although larger study samples may be required to identify the full range of involved pathways, these results indicate a role for mitochondria, intracellular signalling and inflammation in cluster headache. PMID:28074859

Identifying key genes in glaucoma based on a benchmarked dataset and the gene regulatory network.

PubMed

Chen, Xi; Wang, Qiao-Ling; Zhang, Meng-Hui

2017-10-01

The current study aimed to identify key genes in glaucoma based on a benchmarked dataset and gene regulatory network (GRN). Local and global noise was added to the gene expression dataset to produce a benchmarked dataset. Differentially-expressed genes (DEGs) between patients with glaucoma and normal controls were identified utilizing the Linear Models for Microarray Data (Limma) package based on benchmarked dataset. A total of 5 GRN inference methods, including Zscore, GeneNet, context likelihood of relatedness (CLR) algorithm, Partial Correlation coefficient with Information Theory (PCIT) and GEne Network Inference with Ensemble of Trees (Genie3) were evaluated using receiver operating characteristic (ROC) and precision and recall (PR) curves. The interference method with the best performance was selected to construct the GRN. Subsequently, topological centrality (degree, closeness and betweenness) was conducted to identify key genes in the GRN of glaucoma. Finally, the key genes were validated by performing reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A total of 176 DEGs were detected from the benchmarked dataset. The ROC and PR curves of the 5 methods were analyzed and it was determined that Genie3 had a clear advantage over the other methods; thus, Genie3 was used to construct the GRN. Following topological centrality analysis, 14 key genes for glaucoma were identified, including IL6 , EPHA2 and GSTT1 and 5 of these 14 key genes were validated by RT-qPCR. Therefore, the current study identified 14 key genes in glaucoma, which may be potential biomarkers to use in the diagnosis of glaucoma and aid in identifying the molecular mechanism of this disease.

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

Analysis of the Human Prostate-Specific Proteome Defined by Transcriptomics and Antibody-Based Profiling Identifies TMEM79 and ACOXL as Two Putative, Diagnostic Markers in Prostate Cancer

PubMed Central

O'Hurley, Gillian; Busch, Christer; Fagerberg, Linn; Hallström, Björn M.; Stadler, Charlotte; Tolf, Anna; Lundberg, Emma; Schwenk, Jochen M.; Jirström, Karin; Bjartell, Anders; Gallagher, William M.; Uhlén, Mathias; Pontén, Fredrik

2015-01-01

To better understand prostate function and disease, it is important to define and explore the molecular constituents that signify the prostate gland. The aim of this study was to define the prostate specific transcriptome and proteome, in comparison to 26 other human tissues. Deep sequencing of mRNA (RNA-seq) and immunohistochemistry-based protein profiling were combined to identify prostate specific gene expression patterns and to explore tissue biomarkers for potential clinical use in prostate cancer diagnostics. We identified 203 genes with elevated expression in the prostate, 22 of which showed more than five-fold higher expression levels compared to all other tissue types. In addition to previously well-known proteins we identified two poorly characterized proteins, TMEM79 and ACOXL, with potential to differentiate between benign and cancerous prostatic glands in tissue biopsies. In conclusion, we have applied a genome-wide analysis to identify the prostate specific proteome using transcriptomics and antibody-based protein profiling to identify genes with elevated expression in the prostate. Our data provides a starting point for further functional studies to explore the molecular repertoire of normal and diseased prostate including potential prostate cancer markers such as TMEM79 and ACOXL. PMID:26237329

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

PubMed

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

2007-09-11

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.

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

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

Alterations in cholesterol metabolism-related genes in sporadic Alzheimer's disease.

PubMed

Picard, Cynthia; Julien, Cédric; Frappier, Josée; Miron, Justin; Théroux, Louise; Dea, Doris; Breitner, John C S; Poirier, Judes

2018-06-01

Genome-wide association studies have identified several cholesterol metabolism-related genes as top risk factors for late-onset Alzheimer's disease (LOAD). We hypothesized that specific genetic variants could act as disease-modifying factors by altering the expression of those genes. Targeted association studies were conducted with available genomic, transcriptomic, proteomic, and histopathological data from 3 independent cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Quebec Founder Population (QFP), and the United Kingdom Brain Expression Consortium (UKBEC). First, a total of 273 polymorphisms located in 17 cholesterol metabolism-related loci were screened for associations with cerebrospinal fluid LOAD biomarkers beta amyloid, phosphorylated tau, and tau (from the ADNI) and with amyloid plaque and tangle densities (from the QFP). Top polymorphisms were then contrasted with gene expression levels measured in 134 autopsied healthy brains (from the UKBEC). In the end, only SREBF2 polymorphism rs2269657 showed significant dual associations with LOAD pathological biomarkers and gene expression levels. Furthermore, SREBF2 expression levels measured in LOAD frontal cortices inversely correlated with age at death; suggesting a possible influence on survival rate. Copyright © 2018 Elsevier Inc. All rights reserved.

Global transcriptome analysis of formalin-fixed prostate cancer specimens identifies biomarkers of disease recurrence.

PubMed

Long, Qi; Xu, Jianpeng; Osunkoya, Adeboye O; Sannigrahi, Soma; Johnson, Brent A; Zhou, Wei; Gillespie, Theresa; Park, Jong Y; Nam, Robert K; Sugar, Linda; Stanimirovic, Aleksandra; Seth, Arun K; Petros, John A; Moreno, Carlos S

2014-06-15

Prostate cancer remains the second leading cause of cancer death in American men and there is an unmet need for biomarkers to identify patients with aggressive disease. In an effort to identify biomarkers of recurrence, we performed global RNA sequencing on 106 formalin-fixed, paraffin-embedded prostatectomy samples from 100 patients at three independent sites, defining a 24-gene signature panel. The 24 genes in this panel function in cell-cycle progression, angiogenesis, hypoxia, apoptosis, PI3K signaling, steroid metabolism, translation, chromatin modification, and transcription. Sixteen genes have been associated with cancer, with five specifically associated with prostate cancer (BTG2, IGFBP3, SIRT1, MXI1, and FDPS). Validation was performed on an independent publicly available dataset of 140 patients, where the new signature panel outperformed markers published previously in terms of predicting biochemical recurrence. Our work also identified differences in gene expression between Gleason pattern 4 + 3 and 3 + 4 tumors, including several genes involved in the epithelial-to-mesenchymal transition and developmental pathways. Overall, this study defines a novel biomarker panel that has the potential to improve the clinical management of prostate cancer. ©2014 American Association for Cancer Research.

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further

Gene Expression Correlated with Severe Asthma Characteristics Reveals Heterogeneous Mechanisms of Severe Disease.

PubMed

Modena, Brian D; Bleecker, Eugene R; Busse, William W; Erzurum, Serpil C; Gaston, Benjamin M; Jarjour, Nizar N; Meyers, Deborah A; Milosevic, Jadranka; Tedrow, John R; Wu, Wei; Kaminski, Naftali; Wenzel, Sally E

2017-06-01

Severe asthma (SA) is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of bronchial epithelial cells in individuals with asthma have provided biological insight and underscored possible mechanistic differences between individuals. Identify networks of genes reflective of underlying biological processes that define SA. Airway epithelial cell gene expression from 155 subjects with asthma and healthy control subjects in the Severe Asthma Research Program was analyzed by weighted gene coexpression network analysis to identify gene networks and profiles associated with SA and its specific characteristics (i.e., pulmonary function tests, quality of life scores, urgent healthcare use, and steroid use), which potentially identified underlying biological processes. A linear model analysis confirmed these findings while adjusting for potential confounders. Weighted gene coexpression network analysis constructed 64 gene network modules, including modules corresponding to T1 and T2 inflammation, neuronal function, cilia, epithelial growth, and repair mechanisms. Although no network selectively identified SA, genes in modules linked to epithelial growth and repair and neuronal function were markedly decreased in SA. Several hub genes of the epithelial growth and repair module were found located at the 17q12-21 locus, near a well-known asthma susceptibility locus. T2 genes increased with severity in those treated with corticosteroids but were also elevated in untreated, mild-to-moderate disease compared with healthy control subjects. T1 inflammation, especially when associated with increased T2 gene expression, was elevated in a subgroup of younger patients with SA. In this hypothesis-generating analysis, gene expression networks in relation to asthma severity provided potentially new insight into biological mechanisms associated with the development of SA and its phenotypes.

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.

Disease-aging network reveals significant roles of aging genes in connecting genetic diseases.

PubMed

Wang, Jiguang; Zhang, Shihua; Wang, Yong; Chen, Luonan; Zhang, Xiang-Sun

2009-09-01

One of the challenging problems in biology and medicine is exploring the underlying mechanisms of genetic diseases. Recent studies suggest that the relationship between genetic diseases and the aging process is important in understanding the molecular mechanisms of complex diseases. Although some intricate associations have been investigated for a long time, the studies are still in their early stages. In this paper, we construct a human disease-aging network to study the relationship among aging genes and genetic disease genes. Specifically, we integrate human protein-protein interactions (PPIs), disease-gene associations, aging-gene associations, and physiological system-based genetic disease classification information in a single graph-theoretic framework and find that (1) human disease genes are much closer to aging genes than expected by chance; and (2) diseases can be categorized into two types according to their relationships with aging. Type I diseases have their genes significantly close to aging genes, while type II diseases do not. Furthermore, we examine the topological characters of the disease-aging network from a systems perspective. Theoretical results reveal that the genes of type I diseases are in a central position of a PPI network while type II are not; (3) more importantly, we define an asymmetric closeness based on the PPI network to describe relationships between diseases, and find that aging genes make a significant contribution to associations among diseases, especially among type I diseases. In conclusion, the network-based study provides not only evidence for the intricate relationship between the aging process and genetic diseases, but also biological implications for prying into the nature of human diseases.

Microarray analysis to identify the similarities and differences of pathogenesis between aortic occlusive disease and abdominal aortic aneurysm.

PubMed

Wang, Guofu; Bi, Lechang; Wang, Gaofeng; Huang, Feilai; Lu, Mingjing; Zhu, Kai

2018-06-01

Objectives Expression profile of GSE57691 was analyzed to identify the similarities and differences between aortic occlusive disease and abdominal aortic aneurysm. Methods The expression profile of GSE57691 was downloaded from Gene Expression Omnibus database, including 20 small abdominal aortic aneurysm samples, 29 large abdominal aortic aneurysm samples, 9 aortic occlusive disease samples, and 10 control samples. Using the limma package in R, the differentially expressed genes were screened. Followed by enrichment analysis was performed for the differentially expressed genes using database for annotation, visualization, and integrated discovery online tool. Based on string online tool and Cytoscape software, protein-protein interaction network and module analyses were carried out. Moreover, integrated TF platform database and Cytoscape software were used for constructing transcriptional regulatory networks. Results As a result, 1757, 354, and 396 differentially expressed genes separately were identified in aortic occlusive disease, large abdominal aortic aneurysm, and small abdominal aortic aneurysm samples. UBB was significantly enriched in proteolysis related pathways with a high degree in three groups. SPARCL1 was another gene shared by these groups and regulated by NFIA, which had a high degree in transcriptional regulatory network. ACTB, a significant upregulated gene in abdominal aortic aneurysm samples, could be regulated by CLIC4, which was significantly enriched in cell motions. ACLY and NFIB were separately identified in aortic occlusive disease and small abdominal aortic aneurysm samples, and separately enriched in lipid metabolism and negative regulation of cell proliferation. Conclusions The downregulated UBB, NFIA, and SPARCL1 might play key roles in both aortic occlusive disease and abdominal aortic aneurysm, while the upregulated ACTB might only involve in abdominal aortic aneurysm. ACLY and NFIB were specifically involved in aortic occlusive

Virus-Plus-Susceptibility Gene Interaction Determines Crohn’s Disease Gene Atg16L1 Phenotypes in Intestine

PubMed Central

Cadwell, Ken; Patel, Khushbu K.; Maloney, Nicole S.; Liu, Ta-Chiang; Ng, Aylwin C.Y.; Storer, Chad E.; Head, Richard D.; Xavier, Ramnik; Stappenbeck, Thaddeus S.; Virgin, Herbert W.

2010-01-01

SUMMARY It is unclear why disease occurs in only a small proportion of persons carrying common risk alleles of disease susceptibility genes. Here we demonstrate that an interaction between a specific virus infection and a mutation in the Crohn’s disease susceptibility gene Atg16L1 induces intestinal pathologies in mice. This virus-plus-susceptibility gene interaction generated abnormalities in granule packaging and unique patterns of gene expression in Paneth cells. Further, the response to injury induced by the toxic substance dextran sodium sulfate was fundamentally altered to include pathologies resembling aspects of Crohn’s disease. These pathologies triggered by virus-plus-susceptibility gene interaction were dependent on TNFα and IFNγ and were prevented by treatment with broad spectrum antibiotics. Thus, we provide a specific example of how a virus-plus-susceptibility gene interaction can, in combination with additional environmental factors and commensal bacteria, determine the phenotype of hosts carrying common risk alleles for inflammatory disease. PMID:20602997

Powerful Identification of Cis-regulatory SNPs in Human Primary Monocytes Using Allele-Specific Gene Expression

PubMed Central

Almlöf, Jonas Carlsson; Lundmark, Per; Lundmark, Anders; Ge, Bing; Maouche, Seraya; Göring, Harald H. H.; Liljedahl, Ulrika; Enström, Camilla; Brocheton, Jessy; Proust, Carole; Godefroy, Tiphaine; Sambrook, Jennifer G.; Jolley, Jennifer; Crisp-Hihn, Abigail; Foad, Nicola; Lloyd-Jones, Heather; Stephens, Jonathan; Gwilliam, Rhian; Rice, Catherine M.; Hengstenberg, Christian; Samani, Nilesh J.; Erdmann, Jeanette; Schunkert, Heribert; Pastinen, Tomi; Deloukas, Panos; Goodall, Alison H.; Ouwehand, Willem H.; Cambien, François; Syvänen, Ann-Christine

2012-01-01

A large number of genome-wide association studies have been performed during the past five years to identify associations between SNPs and human complex diseases and traits. The assignment of a functional role for the identified disease-associated SNP is not straight-forward. Genome-wide expression quantitative trait locus (eQTL) analysis is frequently used as the initial step to define a function while allele-specific gene expression (ASE) analysis has not yet gained a wide-spread use in disease mapping studies. We compared the power to identify cis-acting regulatory SNPs (cis-rSNPs) by genome-wide allele-specific gene expression (ASE) analysis with that of traditional expression quantitative trait locus (eQTL) mapping. Our study included 395 healthy blood donors for whom global gene expression profiles in circulating monocytes were determined by Illumina BeadArrays. ASE was assessed in a subset of these monocytes from 188 donors by quantitative genotyping of mRNA using a genome-wide panel of SNP markers. The performance of the two methods for detecting cis-rSNPs was evaluated by comparing associations between SNP genotypes and gene expression levels in sample sets of varying size. We found that up to 8-fold more samples are required for eQTL mapping to reach the same statistical power as that obtained by ASE analysis for the same rSNPs. The performance of ASE is insensitive to SNPs with low minor allele frequencies and detects a larger number of significantly associated rSNPs using the same sample size as eQTL mapping. An unequivocal conclusion from our comparison is that ASE analysis is more sensitive for detecting cis-rSNPs than standard eQTL mapping. Our study shows the potential of ASE mapping in tissue samples and primary cells which are difficult to obtain in large numbers. PMID:23300628

Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits.

PubMed

Mancuso, Nicholas; Shi, Huwenbo; Goddard, Pagé; Kichaev, Gleb; Gusev, Alexander; Pasaniuc, Bogdan

2017-03-02

Although genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. Here, we introduce a method for estimating the local genetic correlation between gene expression and a complex trait and utilize it to estimate the genetic correlation due to predicted expression between pairs of traits. We integrated gene expression measurements from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide association studies (TWASs). We identified 1,196 genes whose expression is associated with these traits; of these, 168 reside more than 0.5 Mb away from any previously reported GWAS significant variant. We then used our approach to find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, eight were not found through genetic correlation at the SNP level. Finally, we used bi-directional regression to find evidence that BMI causally influences triglyceride levels and that triglyceride levels causally influence low-density lipoprotein. Together, our results provide insight into the role of gene expression in the susceptibility of complex traits and diseases. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

A 6-gene signature identifies four molecular subgroups of neuroblastoma

PubMed Central

2011-01-01

Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p < 0.05, Fisher's exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics. PMID:21492432

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

PubMed

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Sex and tissue specific gene expression patterns identified following de novo transcriptomic analysis of the Norway lobster, Nephrops norvegicus.

PubMed

Rotllant, Guiomar; Nguyen, Tuan Viet; Sbragaglia, Valerio; Rahi, Lifat; Dudley, Kevin J; Hurwood, David; Ventura, Tomer; Company, Joan B; Chand, Vincent; Aguzzi, Jacopo; Mather, Peter B

2017-08-16

The Norway lobster, Nephrops norvegicus, is economically important in European fisheries and is a key organism in local marine ecosystems. Despite multi-faceted scientific interest in this species, our current knowledge of genetic resources in this species remains very limited. Here, we generated a reference de novo transcriptome for N. norvegicus from multiple tissues in both sexes. Bioinformatic analyses were conducted to detect transcripts that were expressed exclusively in either males or females. Patterns were validated via RT-PCR. Sixteen N. norvegicus libraries were sequenced from immature and mature ovary, testis and vas deferens (including the masculinizing androgenic gland). In addition, eyestalk, brain, thoracic ganglia and hepatopancreas tissues were screened in males and both immature and mature females. RNA-Sequencing resulted in >600 million reads. De novo assembly that combined the current dataset with two previously published libraries from eyestalk tissue, yielded a reference transcriptome of 333,225 transcripts with an average size of 708 base pairs (bp), with an N50 of 1272 bp. Sex-specific transcripts were detected primarily in gonads followed by hepatopancreas, brain, thoracic ganglia, and eyestalk, respectively. Candidate transcripts that were expressed exclusively either in males or females were highlighted and the 10 most abundant ones were validated via RT-PCR. Among the most highly expressed genes were Serine threonine protein kinase in testis and Vitellogenin in female hepatopancreas. These results align closely with gene annotation results. Moreover, a differential expression heatmap showed that the majority of differentially expressed transcripts were identified in gonad and eyestalk tissues. Results indicate that sex-specific gene expression patterns in Norway lobster are controlled by differences in gene regulation pattern between males and females in somatic tissues. The current study presents the first multi-tissue reference

Gene expression profiling following NRF2 and KEAP1 siRNA knockdown in human lung fibroblasts identifies CCL11/Eotaxin-1 as a novel NRF2 regulated gene.

PubMed

Fourtounis, Jimmy; Wang, I-Ming; Mathieu, Marie-Claude; Claveau, David; Loo, Tenneille; Jackson, Aimee L; Peters, Mette A; Therien, Alex G; Boie, Yves; Crackower, Michael A

2012-10-12

Oxidative Stress contributes to the pathogenesis of many diseases. The NRF2/KEAP1 axis is a key transcriptional regulator of the anti-oxidant response in cells. Nrf2 knockout mice have implicated this pathway in regulating inflammatory airway diseases such as asthma and COPD. To better understand the role the NRF2 pathway has on respiratory disease we have taken a novel approach to define NRF2 dependent gene expression in a relevant lung system. Normal human lung fibroblasts were transfected with siRNA specific for NRF2 or KEAP1. Gene expression changes were measured at 30 and 48 hours using a custom Affymetrix Gene array. Changes in Eotaxin-1 gene expression and protein secretion were further measured under various inflammatory conditions with siRNAs and pharmacological tools. An anti-correlated gene set (inversely regulated by NRF2 and KEAP1 RNAi) that reflects specific NRF2 regulated genes was identified. Gene annotations show that NRF2-mediated oxidative stress response is the most significantly regulated pathway, followed by heme metabolism, metabolism of xenobiotics by Cytochrome P450 and O-glycan biosynthesis. Unexpectedly the key eosinophil chemokine Eotaxin-1/CCL11 was found to be up-regulated when NRF2 was inhibited and down-regulated when KEAP1 was inhibited. This transcriptional regulation leads to modulation of Eotaxin-1 secretion from human lung fibroblasts under basal and inflammatory conditions, and is specific to Eotaxin-1 as NRF2 or KEAP1 knockdown had no effect on the secretion of a set of other chemokines and cytokines. Furthermore, the known NRF2 small molecule activators CDDO and Sulphoraphane can also dose dependently inhibit Eotaxin-1 release from human lung fibroblasts. These data uncover a previously unknown role for NRF2 in regulating Eotaxin-1 expression and further the mechanistic understanding of this pathway in modulating inflammatory lung disease.

Hypocretin neuron-specific transcriptome profiling identifies the sleep modulator Kcnh4a.

PubMed

Yelin-Bekerman, Laura; Elbaz, Idan; Diber, Alex; Dahary, Dvir; Gibbs-Bar, Liron; Alon, Shahar; Lerer-Goldshtein, Tali; Appelbaum, Lior

2015-10-01

Sleep has been conserved throughout evolution; however, the molecular and neuronal mechanisms of sleep are largely unknown. The hypothalamic hypocretin/orexin (Hcrt) neurons regulate sleep\\wake states, feeding, stress, and reward. To elucidate the mechanism that enables these various functions and to identify sleep regulators, we combined fluorescence cell sorting and RNA-seq in hcrt:EGFP zebrafish. Dozens of Hcrt-neuron-specific transcripts were identified and comprehensive high-resolution imaging revealed gene-specific localization in all or subsets of Hcrt neurons. Clusters of Hcrt-neuron-specific genes are predicted to be regulated by shared transcription factors. These findings show that Hcrt neurons are heterogeneous and that integrative molecular mechanisms orchestrate their diverse functions. The voltage-gated potassium channel Kcnh4a, which is expressed in all Hcrt neurons, was silenced by the CRISPR-mediated gene inactivation system. The mutant kcnh4a (kcnh4a(-/-)) larvae showed reduced sleep time and consolidation, specifically during the night, suggesting that Kcnh4a regulates sleep.

Prioritizing causal disease genes using unbiased genomic features.

PubMed

Deo, Rahul C; Musso, Gabriel; Tasan, Murat; Tang, Paul; Poon, Annie; Yuan, Christiana; Felix, Janine F; Vasan, Ramachandran S; Beroukhim, Rameen; De Marco, Teresa; Kwok, Pui-Yan; MacRae, Calum A; Roth, Frederick P

2014-12-03

Cardiovascular disease (CVD) is the leading cause of death in the developed world. Human genetic studies, including genome-wide sequencing and SNP-array approaches, promise to reveal disease genes and mechanisms representing new therapeutic targets. In practice, however, identification of the actual genes contributing to disease pathogenesis has lagged behind identification of associated loci, thus limiting the clinical benefits. To aid in localizing causal genes, we develop a machine learning approach, Objective Prioritization for Enhanced Novelty (OPEN), which quantitatively prioritizes gene-disease associations based on a diverse group of genomic features. This approach uses only unbiased predictive features and thus is not hampered by a preference towards previously well-characterized genes. We demonstrate success in identifying genetic determinants for CVD-related traits, including cholesterol levels, blood pressure, and conduction system and cardiomyopathy phenotypes. Using OPEN, we prioritize genes, including FLNC, for association with increased left ventricular diameter, which is a defining feature of a prevalent cardiovascular disorder, dilated cardiomyopathy or DCM. Using a zebrafish model, we experimentally validate FLNC and identify a novel FLNC splice-site mutation in a patient with severe DCM. Our approach stands to assist interpretation of large-scale genetic studies without compromising their fundamentally unbiased nature.

ROKU: a novel method for identification of tissue-specific genes.

PubMed

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-06-12

One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes.

ROKU: a novel method for identification of tissue-specific genes

PubMed Central

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-01-01

Background One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. Results We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. Conclusion ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes. PMID:16764735

A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma

PubMed Central

Sharma, Amitabh; Menche, Jörg; Huang, C. Chris; Ort, Tatiana; Zhou, Xiaobo; Kitsak, Maksim; Sahni, Nidhi; Thibault, Derek; Voung, Linh; Guo, Feng; Ghiassian, Susan Dina; Gulbahce, Natali; Baribaud, Frédéric; Tocker, Joel; Dobrin, Radu; Barnathan, Elliot; Liu, Hao; Panettieri, Reynold A.; Tantisira, Kelan G.; Qiu, Weiliang; Raby, Benjamin A.; Silverman, Edwin K.; Vidal, Marc; Weiss, Scott T.; Barabási, Albert-László

2015-01-01

Recent advances in genetics have spurred rapid progress towards the systematic identification of genes involved in complex diseases. Still, the detailed understanding of the molecular and physiological mechanisms through which these genes affect disease phenotypes remains a major challenge. Here, we identify the asthma disease module, i.e. the local neighborhood of the interactome whose perturbation is associated with asthma, and validate it for functional and pathophysiological relevance, using both computational and experimental approaches. We find that the asthma disease module is enriched with modest GWAS P-values against the background of random variation, and with differentially expressed genes from normal and asthmatic fibroblast cells treated with an asthma-specific drug. The asthma module also contains immune response mechanisms that are shared with other immune-related disease modules. Further, using diverse omics (genomics, gene-expression, drug response) data, we identify the GAB1 signaling pathway as an important novel modulator in asthma. The wiring diagram of the uncovered asthma module suggests a relatively close link between GAB1 and glucocorticoids (GCs), which we experimentally validate, observing an increase in the level of GAB1 after GC treatment in BEAS-2B bronchial epithelial cells. The siRNA knockdown of GAB1 in the BEAS-2B cell line resulted in a decrease in the NFkB level, suggesting a novel regulatory path of the pro-inflammatory factor NFkB by GAB1 in asthma. PMID:25586491

[Progress in research on pathogenic genes and gene therapy for inherited retinal diseases].

PubMed

Zhu, Ling; Cao, Cong; Sun, Jiji; Gao, Tao; Liang, Xiaoyang; Nie, Zhipeng; Ji, Yanchun; Jiang, Pingping; Guan, Minxin

2017-02-10

Inherited retinal diseases (IRDs), including retinitis pigmentosa, Usher syndrome, Cone-Rod degenerations, inherited macular dystrophy, Leber's congenital amaurosis, Leber's hereditary optic neuropathy are the most common and severe types of hereditary ocular diseases. So far more than 200 pathogenic genes have been identified. With the growing knowledge of the genetics and mechanisms of IRDs, a number of gene therapeutic strategies have been developed in the laboratory or even entered clinical trials. Here the progress of IRD research on the pathogenic genes and therapeutic strategies, particularly gene therapy, are reviewed.

Gene-Based Sequencing Identifies Lipid-Influencing Variants with Ethnicity-Specific Effects in African Americans

PubMed Central

Bentley, Amy R.; Chen, Guanjie; Shriner, Daniel; Doumatey, Ayo P.; Zhou, Jie; Huang, Hanxia; Mullikin, James C.; Blakesley, Robert W.; Hansen, Nancy F.; Bouffard, Gerard G.; Cherukuri, Praveen F.; Maskeri, Baishali; Young, Alice C.; Adeyemo, Adebowale; Rotimi, Charles N.

2014-01-01

Although a considerable proportion of serum lipids loci identified in European ancestry individuals (EA) replicate in African Americans (AA), interethnic differences in the distribution of serum lipids suggest that some genetic determinants differ by ethnicity. We conducted a comprehensive evaluation of five lipid candidate genes to identify variants with ethnicity-specific effects. We sequenced ABCA1, LCAT, LPL, PON1, and SERPINE1 in 48 AA individuals with extreme serum lipid concentrations (high HDLC/low TG or low HDLC/high TG). Identified variants were genotyped in the full population-based sample of AA (n = 1694) and tested for an association with serum lipids. rs328 (LPL) and correlated variants were associated with higher HDLC and lower TG. Interestingly, a stronger effect was observed on a “European” vs. “African” genetic background at this locus. To investigate this effect, we evaluated the region among West Africans (WA). For TG, the effect size among WA was the same in AA with only African local ancestry (2–3% lower TG), while the larger association among AA with local European ancestry matched previous reports in EA (10%). For HDLC, there was no association with rs328 in AA with only African local ancestry or in WA, while the association among AA with European local ancestry was much greater than what has been observed for EA (15 vs. ∼5 mg/dl), suggesting an interaction with an environmental or genetic factor that differs by ethnicity. Beyond this ancestry effect, the importance of African ancestry-focused, sequence-based work was also highlighted by serum lipid associations of variants that were in higher frequency (or present only) among those of African ancestry. By beginning our study with the sequence variation present in AA individuals, investigating local ancestry effects, and seeking replication in WA, we were able to comprehensively evaluate the role of a set of candidate genes in serum lipids in AA. PMID:24603370

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…

Personalized gene silencing therapeutics for Huntington disease.

PubMed

Kay, C; Skotte, N H; Southwell, A L; Hayden, M R

2014-07-01

Gene silencing offers a novel therapeutic strategy for dominant genetic disorders. In specific diseases, selective silencing of only one copy of a gene may be advantageous over non-selective silencing of both copies. Huntington disease (HD) is an autosomal dominant disorder caused by an expanded CAG trinucleotide repeat in the Huntingtin gene (HTT). Silencing both expanded and normal copies of HTT may be therapeutically beneficial, but preservation of normal HTT expression is preferred. Allele-specific methods can selectively silence the mutant HTT transcript by targeting either the expanded CAG repeat or single nucleotide polymorphisms (SNPs) in linkage disequilibrium with the expansion. Both approaches require personalized treatment strategies based on patient genotypes. We compare the prospect of safe treatment of HD by CAG- and SNP-specific silencing approaches and review HD population genetics used to guide target identification in the patient population. Clinical implementation of allele-specific HTT silencing faces challenges common to personalized genetic medicine, requiring novel solutions from clinical scientists and regulatory authorities. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Gene expression profiling of prostate tissue identifies chromatin regulation as a potential link between obesity and lethal prostate cancer.

PubMed

Ebot, Ericka M; Gerke, Travis; Labbé, David P; Sinnott, Jennifer A; Zadra, Giorgia; Rider, Jennifer R; Tyekucheva, Svitlana; Wilson, Kathryn M; Kelly, Rachel S; Shui, Irene M; Loda, Massimo; Kantoff, Philip W; Finn, Stephen; Vander Heiden, Matthew G; Brown, Myles; Giovannucci, Edward L; Mucci, Lorelei A

2017-11-01

Obese men are at higher risk of advanced prostate cancer and cancer-specific mortality; however, the biology underlying this association remains unclear. This study examined gene expression profiles of prostate tissue to identify biological processes differentially expressed by obesity status and lethal prostate cancer. Gene expression profiling was performed on tumor (n = 402) and adjacent normal (n = 200) prostate tissue from participants in 2 prospective cohorts who had been diagnosed with prostate cancer from 1982 to 2005. Body mass index (BMI) was calculated from the questionnaire immediately preceding cancer diagnosis. Men were followed for metastases or prostate cancer-specific death (lethal disease) through 2011. Gene Ontology biological processes differentially expressed by BMI were identified using gene set enrichment analysis. Pathway scores were computed by averaging the signal intensities of member genes. Odds ratios (ORs) for lethal prostate cancer were estimated with logistic regression. Among 402 men, 48% were healthy weight, 31% were overweight, and 21% were very overweight/obese. Fifteen gene sets were enriched in tumor tissue, but not normal tissue, of very overweight/obese men versus healthy-weight men; 5 of these were related to chromatin modification and remodeling (false-discovery rate < 0.25). Patients with high tumor expression of chromatin-related genes had worse clinical characteristics (Gleason grade > 7, 41% vs 17%; P = 2 × 10 -4 ) and an increased risk of lethal disease that was independent of grade and stage (OR, 5.26; 95% confidence interval, 2.37-12.25). This study improves our understanding of the biology of aggressive prostate cancer and identifies a potential mechanistic link between obesity and prostate cancer death that warrants further study. Cancer 2017;123:4130-4138. © 2017 American Cancer Society. © 2017 American Cancer Society.

Discovering Single Nucleotide Polymorphisms Regulating Human Gene Expression Using Allele Specific Expression from RNA-seq Data

PubMed Central

Kang, Eun Yong; Martin, Lisa J.; Mangul, Serghei; Isvilanonda, Warin; Zou, Jennifer; Ben-David, Eyal; Han, Buhm; Lusis, Aldons J.; Shifman, Sagiv; Eskin, Eleazar

2016-01-01

The study of the genetics of gene expression is of considerable importance to understanding the nature of common, complex diseases. The most widely applied approach to identifying relationships between genetic variation and gene expression is the expression quantitative trait loci (eQTL) approach. Here, we increased the computational power of eQTL with an alternative and complementary approach based on analyzing allele specific expression (ASE). We designed a novel analytical method to identify cis-acting regulatory variants based on genome sequencing and measurements of ASE from RNA-sequencing (RNA-seq) data. We evaluated the power and resolution of our method using simulated data. We then applied the method to map regulatory variants affecting gene expression in lymphoblastoid cell lines (LCLs) from 77 unrelated northern and western European individuals (CEU), which were part of the HapMap project. A total of 2309 SNPs were identified as being associated with ASE patterns. The SNPs associated with ASE were enriched within promoter regions and were significantly more likely to signal strong evidence for a regulatory role. Finally, among the candidate regulatory SNPs, we identified 108 SNPs that were previously associated with human immune diseases. With further improvements in quantifying ASE from RNA-seq, the application of our method to other datasets is expected to accelerate our understanding of the biological basis of common diseases. PMID:27765809

Gene Expression Correlated with Severe Asthma Characteristics Reveals Heterogeneous Mechanisms of Severe Disease

PubMed Central

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

2017-01-01

Rationale: Severe asthma (SA) is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of bronchial epithelial cells in individuals with asthma have provided biological insight and underscored possible mechanistic differences between individuals. Objectives: Identify networks of genes reflective of underlying biological processes that define SA. Methods: Airway epithelial cell gene expression from 155 subjects with asthma and healthy control subjects in the Severe Asthma Research Program was analyzed by weighted gene coexpression network analysis to identify gene networks and profiles associated with SA and its specific characteristics (i.e., pulmonary function tests, quality of life scores, urgent healthcare use, and steroid use), which potentially identified underlying biological processes. A linear model analysis confirmed these findings while adjusting for potential confounders. Measurements and Main Results: Weighted gene coexpression network analysis constructed 64 gene network modules, including modules corresponding to T1 and T2 inflammation, neuronal function, cilia, epithelial growth, and repair mechanisms. Although no network selectively identified SA, genes in modules linked to epithelial growth and repair and neuronal function were markedly decreased in SA. Several hub genes of the epithelial growth and repair module were found located at the 17q12–21 locus, near a well-known asthma susceptibility locus. T2 genes increased with severity in those treated with corticosteroids but were also elevated in untreated, mild-to-moderate disease compared with healthy control subjects. T1 inflammation, especially when associated with increased T2 gene expression, was elevated in a subgroup of younger patients with SA. Conclusions: In this hypothesis-generating analysis, gene expression networks in relation to asthma severity provided potentially new insight into biological mechanisms associated with the development of SA and its

Genetics and molecular mapping of genes for race-specific all-stage resistance and non-race-specific high-temperature adult-plant resistance to stripe rust in spring wheat cultivar Alpowa.

PubMed

Lin, F; Chen, X M

2007-05-01

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is one of the most widespread and destructive wheat diseases worldwide. Growing resistant cultivars is the preferred control of the disease. The spring wheat cultivar 'Alpowa' has both race-specific, all-stage resistance and non-race-specific, high-temperature adult-plant (HTAP) resistances to stripe rust. To identify genes for the stripe rust resistances, Alpowa was crossed with 'Avocet Susceptible' (AVS). Seedlings of the parents, and F(1), F(2) and F(3) progeny were tested with races PST-1 and PST-21 of P. striiformis f. sp. tritici under controlled greenhouse conditions. Alpowa has a single partially dominant gene, designated as YrAlp, conferring all-stage resistance. Resistance gene analog polymorphism (RGAP) and simple sequence repeat (SSR) techniques were used to identify molecular markers linked to YrAlp. A linkage group of five RGAP markers and two SSR markers was constructed for YrAlp using 136 F(3) lines. Amplification of a set of nulli-tetrasomic Chinese Spring lines with RGAP markers Xwgp47 and Xwgp48 and the two SSR markers indicated that YrAlp is located on the short arm of chromosome 1B. To map quantitative trait loci (QTLs) for the non-race-specific HTAP resistance, the parents and 136 F(3) lines were tested at two sites near Pullman and one site near Mount Vernon, Washington, under naturally infected conditions. A major HTAP QTL was consistently detected across environments and was located on chromosome 7BL. Because of its chromosomal location and the non-race-specific nature of the HTAP resistance, this gene is different from previously described genes for adult-plant resistance, and is therefore designated Yr39. The gene contributed to 64.2% of the total variation of relative area under disease progress curve (AUDPC) data and 59.1% of the total variation of infection type data recorded at the heading-flowering stages. Two RGAP markers, Xwgp36 and Xwgp45 with the highest R (2) values

Mutations in the Norrie disease gene.

PubMed

Schuback, D E; Chen, Z Y; Craig, I W; Breakefield, X O; Sims, K B

1995-01-01

We report our experience to date in mutation identification in the Norrie disease (ND) gene. We carried out mutational analysis in 26 kindreds in an attempt to identify regions presumed critical to protein function and potentially correlated with generation of the disease phenotype. All coding exons, as well as noncoding regions of exons 1 and 2, 636 nucleotides in the noncoding region of exon 3, and 197 nucleotides of 5' flanking sequence, were analyzed for single-strand conformation polymorphisms (SSCP) by polymerase chain reaction (PCR) amplification of genomic DNA. DNA fragments that showed altered SSCP band mobilities were sequenced to locate the specific mutations. In addition to three previously described submicroscopic deletions encompassing the entire ND gene, we have now identified 6 intragenic deletions, 8 missense (seven point mutations, one 9-bp deletion), 6 nonsense (three point mutations, three single bp deletions/frameshift) and one 10-bp insertion, creating an expanded repeat in the 5' noncoding region of exon 1. Thus, mutations have been identified in a total of 24 of 26 (92%) of the kindreds we have studied to date. With the exception of two different mutations, each found in two apparently unrelated kindreds, these mutations are unique and expand the genotype database. Localization of the majority of point mutations at or near cysteine residues, potentially critical in protein tertiary structure, supports a previous protein model for norrin as member of a cystine knot growth factor family (Meitinger et al., 1993). Genotype-phenotype correlations were not evident with the limited clinical data available, except in the cases of larger submicroscopic deletions associated with a more severe neurologic syndrome.(ABSTRACT TRUNCATED AT 250 WORDS)

Meta-Analysis of Genome-Wide Association Studies for Abdominal Aortic Aneurysm Identifies Four New Disease-Specific Risk Loci

PubMed Central

Tromp, Gerard; Kuivaniemi, Helena; Gretarsdottir, Solveig; Baas, Annette F.; Giusti, Betti; Strauss, Ewa; van‘t Hof, Femke N.G.; Webb, Thomas R.; Erdman, Robert; Ritchie, Marylyn D.; Elmore, James R.; Verma, Anurag; Pendergrass, Sarah; Kullo, Iftikhar J.; Ye, Zi; Peissig, Peggy L.; Gottesman, Omri; Verma, Shefali S.; Malinowski, Jennifer; Rasmussen-Torvik, Laura J.; Borthwick, Kenneth M.; Smelser, Diane T.; Crosslin, David R.; de Andrade, Mariza; Ryer, Evan J.; McCarty, Catherine A.; Böttinger, Erwin P.; Pacheco, Jennifer A.; Crawford, Dana C.; Carrell, David S.; Gerhard, Glenn S.; Franklin, David P.; Carey, David J.; Phillips, Victoria L.; Williams, Michael J.A.; Wei, Wenhua; Blair, Ross; Hill, Andrew A.; Vasudevan, Thodor M.; Lewis, David R.; Thomson, Ian A.; Krysa, Jo; Hill, Geraldine B.; Roake, Justin; Merriman, Tony R.; Oszkinis, Grzegorz; Galora, Silvia; Saracini, Claudia; Abbate, Rosanna; Pulli, Raffaele; Pratesi, Carlo; Saratzis, Athanasios; Verissimo, Ana R.; Bumpstead, Suzannah; Badger, Stephen A.; Clough, Rachel E.; Cockerill, Gillian; Hafez, Hany; Scott, D. Julian A.; Futers, T. Simon; Romaine, Simon P.R.; Bridge, Katherine; Griffin, Kathryn J.; Bailey, Marc A.; Smith, Alberto; Thompson, Matthew M.; van Bockxmeer, Frank M.; Matthiasson, Stefan E.; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Blankensteijn, Jan D.; Teijink, Joep A.W.; Wijmenga, Cisca; de Graaf, Jacqueline; Kiemeney, Lambertus A.; Lindholt, Jes S.; Hughes, Anne; Bradley, Declan T.; Stirrups, Kathleen; Golledge, Jonathan; Norman, Paul E.; Powell, Janet T.; Humphries, Steve E.; Hamby, Stephen E.; Goodall, Alison H.; Nelson, Christopher P.; Sakalihasan, Natzi; Courtois, Audrey; Ferrell, Robert E.; Eriksson, Per; Folkersen, Lasse; Franco-Cereceda, Anders; Eicher, John D.; Johnson, Andrew D.; Betsholtz, Christer; Ruusalepp, Arno; Franzén, Oscar; Schadt, Eric E.; Björkegren, Johan L.M.; Lipovich, Leonard; Drolet, Anne M.; Verhoeven, Eric L.; Zeebregts, Clark J.; Geelkerken, Robert H.; van Sambeek, Marc R.; van Sterkenburg, Steven M.; de Vries, Jean-Paul; Stefansson, Kari; Thompson, John R.; de Bakker, Paul I.W.; Deloukas, Panos; Sayers, Robert D.; Harrison, Seamus C.; van Rij, Andre M.; Samani, Nilesh J.

2017-01-01

Rationale: Abdominal aortic aneurysm (AAA) is a complex disease with both genetic and environmental risk factors. Together, 6 previously identified risk loci only explain a small proportion of the heritability of AAA. Objective: To identify additional AAA risk loci using data from all available genome-wide association studies. Methods and Results: Through a meta-analysis of 6 genome-wide association study data sets and a validation study totaling 10 204 cases and 107 766 controls, we identified 4 new AAA risk loci: 1q32.3 (SMYD2), 13q12.11 (LINC00540), 20q13.12 (near PCIF1/MMP9/ZNF335), and 21q22.2 (ERG). In various database searches, we observed no new associations between the lead AAA single nucleotide polymorphisms and coronary artery disease, blood pressure, lipids, or diabetes mellitus. Network analyses identified ERG, IL6R, and LDLR as modifiers of MMP9, with a direct interaction between ERG and MMP9. Conclusions: The 4 new risk loci for AAA seem to be specific for AAA compared with other cardiovascular diseases and related traits suggesting that traditional cardiovascular risk factor management may only have limited value in preventing the progression of aneurysmal disease. PMID:27899403

Use of deep whole-genome sequencing data to identify structure risk variants in breast cancer susceptibility genes.

PubMed

Guo, Xingyi; Shi, Jiajun; Cai, Qiuyin; Shu, Xiao-Ou; He, Jing; Wen, Wanqing; Allen, Jamie; Pharoah, Paul; Dunning, Alison; Hunter, David J; Kraft, Peter; Easton, Douglas F; Zheng, Wei; Long, Jirong

2018-03-01

Functional disruptions of susceptibility genes by large genomic structure variant (SV) deletions in germlines are known to be associated with cancer risk. However, few studies have been conducted to systematically search for SV deletions in breast cancer susceptibility genes. We analysed deep (> 30x) whole-genome sequencing (WGS) data generated in blood samples from 128 breast cancer patients of Asian and European descent with either a strong family history of breast cancer or early cancer onset disease. To identify SV deletions in known or suspected breast cancer susceptibility genes, we used multiple SV calling tools including Genome STRiP, Delly, Manta, BreakDancer and Pindel. SV deletions were detected by at least three of these bioinformatics tools in five genes. Specifically, we identified heterozygous deletions covering a fraction of the coding regions of BRCA1 (with approximately 80kb in two patients), and TP53 genes (with ∼1.6 kb in two patients), and of intronic regions (∼1 kb) of the PALB2 (one patient), PTEN (three patients) and RAD51C genes (one patient). We confirmed the presence of these deletions using real-time quantitative PCR (qPCR). Our study identified novel SV deletions in breast cancer susceptibility genes and the identification of such SV deletions may improve clinical testing.

Epigenetic regulation of depot-specific gene expression in adipose tissue.

PubMed

Gehrke, Sandra; Brueckner, Bodo; Schepky, Andreas; Klein, Johannes; Iwen, Alexander; Bosch, Thomas C G; Wenck, Horst; Winnefeld, Marc; Hagemann, Sabine

2013-01-01

In humans, adipose tissue is distributed in subcutaneous abdominal and subcutaneous gluteal depots that comprise a variety of functional differences. Whereas energy storage in gluteal adipose tissue has been shown to mediate a protective effect, an increase of abdominal adipose tissue is associated with metabolic disorders. However, the molecular basis of depot-specific characteristics is not completely understood yet. Using array-based analyses of transcription profiles, we identified a specific set of genes that was differentially expressed between subcutaneous abdominal and gluteal adipose tissue. To investigate the role of epigenetic regulation in depot-specific gene expression, we additionally analyzed genome-wide DNA methylation patterns in abdominal and gluteal depots. By combining both data sets, we identified a highly significant set of depot-specifically expressed genes that appear to be epigenetically regulated. Interestingly, the majority of these genes form part of the homeobox gene family. Moreover, genes involved in fatty acid metabolism were also differentially expressed. Therefore we suppose that changes in gene expression profiles might account for depot-specific differences in lipid composition. Indeed, triglycerides and fatty acids of abdominal adipose tissue were more saturated compared to triglycerides and fatty acids in gluteal adipose tissue. Taken together, our results uncover clear differences between abdominal and gluteal adipose tissue on the gene expression and DNA methylation level as well as in fatty acid composition. Therefore, a detailed molecular characterization of adipose tissue depots will be essential to develop new treatment strategies for metabolic syndrome associated complications.

Gene Network for Identifying the Entropy Changes of Different Modules in Pediatric Sepsis.

PubMed

Yang, Jing; Zhang, Pingli; Wang, Lumin

2016-01-01

Pediatric sepsis is a disease that threatens life of children. The incidence of pediatric sepsis is higher in developing countries due to various reasons, such as insufficient immunization and nutrition, water and air pollution, etc. Exploring the potential genes via different methods is of significance for the prevention and treatment of pediatric sepsis. This study aimed to identify potential genes associated with pediatric sepsis utilizing analysis of gene network and entropy. The mRNA expression in the blood samples collected from 20 septic children and 30 healthy controls was quantified by using Affymetrix HG-U133A microarray. Two condition-specific protein-protein interaction networks (PINs), one for the healthy control and the other one for the children with sepsis, were deduced by combining the fundamental human PINs with gene expression profiles in the two phenotypes. Subsequently, distinct modules from the two conditional networks were extracted by adopting a maximal clique-merging approach. Delta entropy (ΔS) was calculated between sepsis and control modules. Then, key genes displaying changes in gene composition were identified by matching the control and sepsis modules. Two objective modules were obtained, in which ribosomal protein RPL4 and RPL9 as well as TOP2A were probably considered as the key genes differentiating sepsis from healthy controls. According to previous reports and this work, TOP2A is the potential gene therapy target for pediatric sepsis. The relationship between pediatric sepsis and RPL4 and RPL9 needs further investigation. © 2016 The Author(s) Published by S. Karger AG, Basel.

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

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.

SpeCond: a method to detect condition-specific gene expression

PubMed Central

2011-01-01

Transcriptomic studies routinely measure expression levels across numerous conditions. These datasets allow identification of genes that are specifically expressed in a small number of conditions. However, there are currently no statistically robust methods for identifying such genes. Here we present SpeCond, a method to detect condition-specific genes that outperforms alternative approaches. We apply the method to a dataset of 32 human tissues to determine 2,673 specifically expressed genes. An implementation of SpeCond is freely available as a Bioconductor package at http://www.bioconductor.org/packages/release/bioc/html/SpeCond.html. PMID:22008066

The Prediction of Drug-Disease Correlation Based on Gene Expression Data.

PubMed

Cui, Hui; Zhang, Menghuan; Yang, Qingmin; Li, Xiangyi; Liebman, Michael; Yu, Ying; Xie, Lu

2018-01-01

The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for

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

Common disease signatures from gene expression analysis in Huntington's disease human blood and brain.

PubMed

Mina, Eleni; van Roon-Mom, Willeke; Hettne, Kristina; van Zwet, Erik; Goeman, Jelle; Neri, Christian; A C 't Hoen, Peter; Mons, Barend; Roos, Marco

2016-08-01

Huntington's disease (HD) is a devastating brain disorder with no effective treatment or cure available. The scarcity of brain tissue makes it hard to study changes in the brain and impossible to perform longitudinal studies. However, peripheral pathology in HD suggests that it is possible to study the disease using peripheral tissue as a monitoring tool for disease progression and/or efficacy of novel therapies. In this study, we investigated if blood can be used to monitor disease severity and progression in brain. Since previous attempts using only gene expression proved unsuccessful, we compared blood and brain Huntington's disease signatures in a functional context. Microarray HD gene expression profiles from three brain regions were compared to the transcriptome of HD blood generated by next generation sequencing. The comparison was performed with a combination of weighted gene co-expression network analysis and literature based functional analysis (Concept Profile Analysis). Uniquely, our comparison of blood and brain datasets was not based on (the very limited) gene overlap but on the similarity between the gene annotations in four different semantic categories: "biological process", "cellular component", "molecular function" and "disease or syndrome". We identified signatures in HD blood reflecting a broad pathophysiological spectrum, including alterations in the immune response, sphingolipid biosynthetic processes, lipid transport, cell signaling, protein modification, spliceosome, RNA splicing, vesicle transport, cell signaling and synaptic transmission. Part of this spectrum was reminiscent of the brain pathology. The HD signatures in caudate nucleus and BA4 exhibited the highest similarity with blood, irrespective of the category of semantic annotations used. BA9 exhibited an intermediate similarity, while cerebellum had the least similarity. We present two signatures that were shared between blood and brain: immune response and spinocerebellar ataxias

Clustering gene expression regulators: new approach to disease subtyping.

PubMed

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

Clustering Gene Expression Regulators: New Approach to Disease Subtyping

PubMed Central

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient. PMID:24416320

Distinct gene-specific mechanisms of arrhythmia revealed by cardiac gene transfer of two long QT disease genes, HERG and KCNE1.

PubMed

Hoppe, U C; Marbán, E; Johns, D C

2001-04-24

The long QT syndrome (LQTS) is a heritable disorder that predisposes to sudden cardiac death. LQTS is caused by mutations in ion channel genes including HERG and KCNE1, but the precise mechanisms remain unclear. To clarify this situation we injected adenoviral vectors expressing wild-type or LQT mutants of HERG and KCNE1 into guinea pig myocardium. End points at 48-72 h included electrophysiology in isolated myocytes and electrocardiography in vivo. HERG increased the rapid component, I(Kr), of the delayed rectifier current, thereby accelerating repolarization, increasing refractoriness, and diminishing beat-to-beat action potential variability. Conversely, HERG-G628S suppressed I(Kr) without significantly delaying repolarization. Nevertheless, HERG-G628S abbreviated refractoriness and increased beat-to-beat variability, leading to early afterdepolarizations (EADs). KCNE1 increased the slow component of the delayed rectifier, I(Ks), without clear phenotypic sequelae. In contrast, KCNE1-D76N suppressed I(Ks) and markedly slowed repolarization, leading to frequent EADs and electrocardiographic QT prolongation. Thus, the two genes predispose to sudden death by distinct mechanisms: the KCNE1 mutant flagrantly undermines cardiac repolarization, and HERG-G628S subtly facilitates the genesis and propagation of premature beats. Our ability to produce electrocardiographic long QT in vivo with a clinical KCNE1 mutation demonstrates the utility of somatic gene transfer in creating genotype-specific disease models.

Identifying Stress Transcription Factors Using Gene Expression and TF-Gene Association Data

PubMed Central

Wu, Wei-Sheng; Chen, Bor-Sen

2007-01-01

Unicellular organisms such as yeasts have evolved to survive environmental stresses by rapidly reorganizing the genomic expression program to meet the challenges of harsh environments. The complex adaptation mechanisms to stress remain to be elucidated. In this study, we developed Stress Transcription Factor Identification Algorithm (STFIA), which integrates gene expression and TF-gene association data to identify the stress transcription factors (TFs) of six kinds of stresses. We identified some general stress TFs that are in response to various stresses, and some specific stress TFs that are in response to one specific stress. The biological significance of our findings is validated by the literature. We found that a small number of TFs may be sufficient to control a wide variety of expression patterns in yeast under different stresses. Two implications can be inferred from this observation. First, the adaptation mechanisms to different stresses may have a bow-tie structure. Second, there may exist extensive regulatory cross-talk among different stress responses. In conclusion, this study proposes a network of the regulators of stress responses and their mechanism of action. PMID:20066130

A Different Microbiome Gene Repertoire in the Airways of Cystic Fibrosis Patients with Severe Lung Disease

PubMed Central

Bacci, Giovanni; Fiscarelli, Ersilia; Taccetti, Giovanni; Dolce, Daniela; Paganin, Patrizia; Morelli, Patrizia; Tuccio, Vanessa; De Alessandri, Alessandra; Lucidi, Vincenzina

2017-01-01

In recent years, next-generation sequencing (NGS) was employed to decipher the structure and composition of the microbiota of the airways in cystic fibrosis (CF) patients. However, little is still known about the overall gene functions harbored by the resident microbial populations and which specific genes are associated with various stages of CF lung disease. In the present study, we aimed to identify the microbial gene repertoire of CF microbiota in twelve patients with severe and normal/mild lung disease by performing sputum shotgun metagenome sequencing. The abundance of metabolic pathways encoded by microbes inhabiting CF airways was reconstructed from the metagenome. We identified a set of metabolic pathways differently distributed in patients with different pulmonary function; namely, pathways related to bacterial chemotaxis and flagellar assembly, as well as genes encoding efflux-mediated antibiotic resistance mechanisms and virulence-related genes. The results indicated that the microbiome of CF patients with low pulmonary function is enriched in virulence-related genes and in genes encoding efflux-mediated antibiotic resistance mechanisms. Overall, the microbiome of severely affected adults with CF seems to encode different mechanisms for the facilitation of microbial colonization and persistence in the lung, consistent with the characteristics of multidrug-resistant microbial communities that are commonly observed in patients with severe lung disease. PMID:28758937

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

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

Unbiased screen identifies aripiprazole as a modulator of abundance of the polyglutamine disease protein, ataxin-3

PubMed Central

Costa, Maria do Carmo; Ashraf, Naila S.; Fischer, Svetlana; Yang, Yemen; Schapka, Emily; Joshi, Gnanada; McQuade, Thomas J.; Dharia, Rahil M.; Dulchavsky, Mark; Ouyang, Michelle; Cook, David; Sun, Duxin; Larsen, Martha J.; Gestwicki, Jason E.; Todi, Sokol V.; Ivanova, Magdalena I.; Paulson, Henry L.

2016-01-01

No disease-modifying treatment exists for the fatal neurodegenerative polyglutamine disease known both as Machado-Joseph disease and spinocerebellar ataxia type 3. As a potential route to therapy, we identified small molecules that reduce levels of the mutant disease protein, ATXN3. Screens of a small molecule collection, including 1250 Food and Drug Administration-approved drugs, in a novel cell-based assay, followed by secondary screens in brain slice cultures from transgenic mice expressing the human disease gene, identified the atypical antipsychotic aripiprazole as one of the hits. Aripiprazole increased longevity in a Drosophila model of Machado-Joseph disease and effectively reduced aggregated ATXN3 species in flies and in brains of transgenic mice treated for 10 days. The aripiprazole-mediated decrease in ATXN3 abundance may reflect a complex response culminating in the modulation of specific components of cellular protein homeostasis. Aripiprazole represents a potentially promising therapeutic drug for Machado-Joseph disease and possibly other neurological proteinopathies. PMID:27645800

A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.

PubMed

Chang, Tzu-Hao; Wu, Shih-Lin; Wang, Wei-Jen; Horng, Jorng-Tzong; Chang, Cheng-Wei

2014-01-01

Microarrays are widely used to assess gene expressions. Most microarray studies focus primarily on identifying differential gene expressions between conditions (e.g., cancer versus normal cells), for discovering the major factors that cause diseases. Because previous studies have not identified the correlations of differential gene expression between conditions, crucial but abnormal regulations that cause diseases might have been disregarded. This paper proposes an approach for discovering the condition-specific correlations of gene expressions within biological pathways. Because analyzing gene expression correlations is time consuming, an Apache Hadoop cloud computing platform was implemented. Three microarray data sets of breast cancer were collected from the Gene Expression Omnibus, and pathway information from the Kyoto Encyclopedia of Genes and Genomes was applied for discovering meaningful biological correlations. The results showed that adopting the Hadoop platform considerably decreased the computation time. Several correlations of differential gene expressions were discovered between the relapse and nonrelapse breast cancer samples, and most of them were involved in cancer regulation and cancer-related pathways. The results showed that breast cancer recurrence might be highly associated with the abnormal regulations of these gene pairs, rather than with their individual expression levels. The proposed method was computationally efficient and reliable, and stable results were obtained when different data sets were used. The proposed method is effective in identifying meaningful biological regulation patterns between conditions.

DGEM--a microarray gene expression database for primary human disease tissues.

PubMed

Xia, Yuni; Campen, Andrew; Rigsby, Dan; Guo, Ying; Feng, Xingdong; Su, Eric W; Palakal, Mathew; Li, Shuyu

2007-01-01

Gene expression patterns can reflect gene regulations in human tissues under normal or pathologic conditions. Gene expression profiling data from studies of primary human disease samples are particularly valuable since these studies often span many years in order to collect patient clinical information and achieve a large sample size. Disease-to-Gene Expression Mapper (DGEM) provides a beneficial community resource to access and analyze these data; it currently includes Affymetrix oligonucleotide array datasets for more than 40 human diseases and 1400 samples. The data are normalized to the same scale and stored in a relational database. A statistical-analysis pipeline was implemented to identify genes abnormally expressed in disease tissues or genes whose expressions are associated with clinical parameters such as cancer patient survival. Data-mining results can be queried through a web-based interface at http://dgem.dhcp.iupui.edu/. The query tool enables dynamic generation of graphs and tables that are further linked to major gene and pathway resources that connect the data to relevant biology, including Entrez Gene and Kyoto Encyclopedia of Genes and Genomes (KEGG). In summary, DGEM provides scientists and physicians a valuable tool to study disease mechanisms, to discover potential disease biomarkers for diagnosis and prognosis, and to identify novel gene targets for drug discovery. The source code is freely available for non-profit use, on request to the authors.

Systems biology approach to late-onset Alzheimer's disease genome-wide association study identifies novel candidate genes validated using brain expression data and Caenorhabditis elegans experiments.

PubMed

Mukherjee, Shubhabrata; Russell, Joshua C; Carr, Daniel T; Burgess, Jeremy D; Allen, Mariet; Serie, Daniel J; Boehme, Kevin L; Kauwe, John S K; Naj, Adam C; Fardo, David W; Dickson, Dennis W; Montine, Thomas J; Ertekin-Taner, Nilufer; Kaeberlein, Matt R; Crane, Paul K

2017-10-01

We sought to determine whether a systems biology approach may identify novel late-onset Alzheimer's disease (LOAD) loci. We performed gene-wide association analyses and integrated results with human protein-protein interaction data using network analyses. We performed functional validation on novel genes using a transgenic Caenorhabditis elegans Aβ proteotoxicity model and evaluated novel genes using brain expression data from people with LOAD and other neurodegenerative conditions. We identified 13 novel candidate LOAD genes outside chromosome 19. Of those, RNA interference knockdowns of the C. elegans orthologs of UBC, NDUFS3, EGR1, and ATP5H were associated with Aβ toxicity, and NDUFS3, SLC25A11, ATP5H, and APP were differentially expressed in the temporal cortex. Network analyses identified novel LOAD candidate genes. We demonstrated a functional role for four of these in a C. elegans model and found enrichment of differentially expressed genes in the temporal cortex. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

PubMed

Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

2011-10-01

Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Systematic Investigation into Aging Related Genes in Brain and Their Relationship with Alzheimer's Disease.

PubMed

Meng, Guofeng; Zhong, Xiaoyan; Mei, Hongkang

2016-01-01

Aging, as a complex biological process, is accompanied by the accumulation of functional loses at different levels, which makes age to be the biggest risk factor to many neurological diseases. Even following decades of investigation, the process of aging is still far from being fully understood, especially at a systematic level. In this study, we identified aging related genes in brain by collecting the ones with sustained and consistent gene expression or DNA methylation changes in the aging process. Functional analysis with Gene Ontology to these genes suggested transcriptional regulators to be the most affected genes in the aging process. Transcription regulation analysis found some transcription factors, especially Specificity Protein 1 (SP1), to play important roles in regulating aging related gene expression. Module-based functional analysis indicated these genes to be associated with many well-known aging related pathways, supporting the validity of our approach to select aging related genes. Finally, we investigated the roles of aging related genes on Alzheimer's Disease (AD). We found that aging and AD related genes both involved some common pathways, which provided a possible explanation why aging made the brain more vulnerable to Alzheimer's Disease.

Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids

PubMed Central

2014-01-01

Background Computational methods for mining of biomedical literature can be useful in augmenting manual searches of the literature using keywords for disease-specific biomarker discovery from biofluids. In this work, we develop and apply a semi-automated literature mining method to mine abstracts obtained from PubMed to discover putative biomarkers of breast and lung cancers in specific biofluids. Methodology A positive set of abstracts was defined by the terms ‘breast cancer’ and ‘lung cancer’ in conjunction with 14 separate ‘biofluids’ (bile, blood, breastmilk, cerebrospinal fluid, mucus, plasma, saliva, semen, serum, synovial fluid, stool, sweat, tears, and urine), while a negative set of abstracts was defined by the terms ‘(biofluid) NOT breast cancer’ or ‘(biofluid) NOT lung cancer.’ More than 5.3 million total abstracts were obtained from PubMed and examined for biomarker-disease-biofluid associations (34,296 positive and 2,653,396 negative for breast cancer; 28,355 positive and 2,595,034 negative for lung cancer). Biological entities such as genes and proteins were tagged using ABNER, and processed using Python scripts to produce a list of putative biomarkers. Z-scores were calculated, ranked, and used to determine significance of putative biomarkers found. Manual verification of relevant abstracts was performed to assess our method’s performance. Results Biofluid-specific markers were identified from the literature, assigned relevance scores based on frequency of occurrence, and validated using known biomarker lists and/or databases for lung and breast cancer [NCBI’s On-line Mendelian Inheritance in Man (OMIM), Cancer Gene annotation server for cancer genomics (CAGE), NCBI’s Genes & Disease, NCI’s Early Detection Research Network (EDRN), and others]. The specificity of each marker for a given biofluid was calculated, and the performance of our semi-automated literature mining method assessed for breast and lung cancer

Systematic Analysis and Comparison of Nucleotide-Binding Site Disease Resistance Genes in a Diploid Cotton Gossypium raimondii

PubMed Central

Wei, Hengling; Li, Wei; Sun, Xiwei; Zhu, Shuijin; Zhu, Jun

2013-01-01

Plant disease resistance genes are a key component of defending plants from a range of pathogens. The majority of these resistance genes belong to the super-family that harbors a Nucleotide-binding site (NBS). A number of studies have focused on NBS-encoding genes in disease resistant breeding programs for diverse plants. However, little information has been reported with an emphasis on systematic analysis and comparison of NBS-encoding genes in cotton. To fill this gap of knowledge, in this study, we identified and investigated the NBS-encoding resistance genes in cotton using the whole genome sequence information of Gossypium raimondii. Totally, 355 NBS-encoding resistance genes were identified. Analyses of the conserved motifs and structural diversity showed that the most two distinct features for these genes are the high proportion of non-regular NBS genes and the high diversity of N-termini domains. Analyses of the physical locations and duplications of NBS-encoding genes showed that gene duplication of disease resistance genes could play an important role in cotton by leading to an increase in the functional diversity of the cotton NBS-encoding genes. Analyses of phylogenetic comparisons indicated that, in cotton, the NBS-encoding genes with TIR domain not only have their own evolution pattern different from those of genes without TIR domain, but also have their own species-specific pattern that differs from those of TIR genes in other plants. Analyses of the correlation between disease resistance QTL and NBS-encoding resistance genes showed that there could be more than half of the disease resistance QTL associated to the NBS-encoding genes in cotton, which agrees with previous studies establishing that more than half of plant resistance genes are NBS-encoding genes. PMID:23936305

Suppression subtractive hybridization identifies an autotransporter adhesin gene of E. coli IMT5155 specifically associated with avian pathogenic Escherichia coli (APEC).

PubMed

Dai, Jianjun; Wang, Shaohui; Guerlebeck, Doreen; Laturnus, Claudia; Guenther, Sebastian; Shi, Zhenyu; Lu, Chengping; Ewers, Christa

2010-09-09

Extraintestinal pathogenic E. coli (ExPEC) represent a phylogenetically diverse group of bacteria which are implicated in a large range of infections in humans and animals. Although subgroups of different ExPEC pathotypes, including uropathogenic, newborn meningitis causing, and avian pathogenic E. coli (APEC) share a number of virulence features, there still might be factors specifically contributing to the pathogenesis of a certain subset of strains or a distinct pathotype. Thus, we made use of suppression subtractive hybridization and compared APEC strain IMT5155 (O2:K1:H5; sequence type complex 95) with human uropathogenic E. coli strain CFT073 (O6:K2:H5; sequence type complex 73) to identify factors which may complete the currently existing model of APEC pathogenicity and further elucidate the position of this avian pathotype within the whole ExPEC group. Twenty-eight different genomic loci were identified, which are present in IMT5155 but not in CFT073. One of these loci contained a gene encoding a putative autotransporter adhesin. The open reading frame of the gene spans a 3,498 bp region leading to a putative 124-kDa adhesive protein. A specific antibody was raised against this protein and expression of the adhesin was shown under laboratory conditions. Adherence and adherence inhibition assays demonstrated a role for the corresponding protein in adhesion to DF-1 chicken fibroblasts. Sequence analyses revealed that the flanking regions of the chromosomally located gene contained sequences of mobile genetic elements, indicating a probable spread among different strains by horizontal gene transfer. In accordance with this hypothesis, the adhesin was found to be present not only in different phylogenetic groups of extraintestinal pathogenic but also of commensal E. coli strains, yielding a significant association with strains of avian origin. We identified a chromosomally located autotransporter gene in a highly virulent APEC strain which confers increased

Mice, humans and haplotypes--the hunt for disease genes in SLE.

PubMed

Rigby, R J; Fernando, M M A; Vyse, T J

2006-09-01

Defining the polymorphisms that contribute to the development of complex genetic disease traits is a challenging, although increasingly tractable problem. Historically, the technical difficulties in conducting association studies across the entire human genome are such that murine models have been used to generate candidate genes for analysis in human complex diseases, such as SLE. In this article we discuss the advantages and disadvantages of this approach and specifically address some assumptions made in the transition from studying one species to another, using lupus as an example. These issues include differences in genetic structure and genetic organisation which are a reflection on the population history. Clearly there are major differences in the histories of the human population and inbred laboratory strains of mice. Both human and murine genomes do exhibit structure at the genetic level. That is to say, they comprise haplotypes which are genomic regions that carry runs of polymorphisms that are not independently inherited. Haplotypes therefore reduce the number of combinations of the polymorphisms in the DNA in that region and facilitate the identification of disease susceptibility genes in both mice and humans. There are now novel means of generating candidate genes in SLE using mutagenesis (with ENU) in mice and identifying mice that generate antinuclear autoimmunity. In addition, murine models still provide a valuable means of exploring the functional consequences of genetic variation. However, advances in technology are such that human geneticists can now screen large fractions of the human genome for disease associations using microchip technologies that provide information on upwards of 100,000 different polymorphisms. These approaches are aimed at identifying haplotypes that carry disease susceptibility mutations and rely less on the generation of candidate genes.

Secretome Characterization and Correlation Analysis Reveal Putative Pathogenicity Mechanisms and Identify Candidate Avirulence Genes in the Wheat Stripe Rust Fungus Puccinia striiformis f. sp. tritici.

PubMed

Xia, Chongjing; Wang, Meinan; Cornejo, Omar E; Jiwan, Derick A; See, Deven R; Chen, Xianming

2017-01-01

Stripe (yellow) rust, caused by Puccinia striiformis f. sp. tritici ( Pst ), is one of the most destructive diseases of wheat worldwide. Planting resistant cultivars is an effective way to control this disease, but race-specific resistance can be overcome quickly due to the rapid evolving Pst population. Studying the pathogenicity mechanisms is critical for understanding how Pst virulence changes and how to develop wheat cultivars with durable resistance to stripe rust. We re-sequenced 7 Pst isolates and included additional 7 previously sequenced isolates to represent balanced virulence/avirulence profiles for several avirulence loci in seretome analyses. We observed an uneven distribution of heterozygosity among the isolates. Secretome comparison of Pst with other rust fungi identified a large portion of species-specific secreted proteins, suggesting that they may have specific roles when interacting with the wheat host. Thirty-two effectors of Pst were identified from its secretome. We identified candidates for Avr genes corresponding to six Yr genes by correlating polymorphisms for effector genes to the virulence/avirulence profiles of the 14 Pst isolates. The putative AvYr76 was present in the avirulent isolates, but absent in the virulent isolates, suggesting that deleting the coding region of the candidate avirulence gene has produced races virulent to resistance gene Yr76 . We conclude that incorporating avirulence/virulence phenotypes into correlation analysis with variations in genomic structure and secretome, particularly presence/absence polymorphisms of effectors, is an efficient way to identify candidate Avr genes in Pst . The candidate effector genes provide a rich resource for further studies to determine the evolutionary history of Pst populations and the co-evolutionary arms race between Pst and wheat. The Avr candidates identified in this study will lead to cloning avirulence genes in Pst , which will enable us to understand molecular mechanisms

Genome-wide identification of lineage-specific genes in Arabidopsis, Oryza and Populus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaohan; Jawdy, Sara; Tschaplinski, Timothy J

2009-01-01

Protein sequences were compared among Arabidopsis, Oryza and Populus to identify differential gene (DG) sets that are in one but not the other two genomes. The DG sets were screened against a plant transcript database, the NR protein database and six newly-sequenced genomes (Carica, Glycine, Medicago, Sorghum, Vitis and Zea) to identify a set of species-specific genes (SS). Gene expression, protein motif and intron number were examined. 192, 641 and 109 SS genes were identified in Arabidopsis, Oryza and Populus, respectively. Some SS genes were preferentially expressed in flowers, roots, xylem and cambium or up-regulated by stress. Six conserved motifsmore » in Arabidopsis and Oryza SS proteins were found in other distant lineages. The SS gene sets were enriched with intronless genes. The results reflect functional and/or anatomical differences between monocots and eudicots or between herbaceous and woody plants. The Populus-specific genes are candidates for carbon sequestration and biofuel research.« less

Predicting hepatocellular carcinoma through cross-talk genes identified by risk pathways

PubMed Central

Shao, Zhuo; Huo, Diwei; Zhang, Denan; Xie, Hongbo; Yang, Jingbo; Liu, Qiuqi; Chen, Xiujie

2018-01-01

Hepatocellular carcinoma (HCC) is the most frequent type of liver cancer with poor survival rate and high mortality. Despite efforts on the mechanism of HCC, new molecular markers are needed for exact diagnosis, evaluation and treatment. Here, we combined transcriptome of HCC with networks and pathways to identify reliable molecular markers. Through integrating 249 differentially expressed genes with syncretic protein interaction networks, we constructed a HCC-specific network, from which we further extracted 480 pivotal genes. Based on the cross-talk between the enriched pathways of the pivotal genes, we finally identified a HCC signature of 45 genes, which could accurately distinguish HCC patients with normal individuals and reveal the prognosis of HCC patients. Among these 45 genes, 15 showed dysregulated expression patterns and a part have been reported to be associated with HCC and/or other cancers. These findings suggested that our identified 45 gene signature could be potential and valuable molecular markers for diagnosis and evaluation of HCC. PMID:29765536

Gene expression profiling following NRF2 and KEAP1 siRNA knockdown in human lung fibroblasts identifies CCL11/Eotaxin-1 as a novel NRF2 regulated gene

PubMed Central

2012-01-01

Background Oxidative Stress contributes to the pathogenesis of many diseases. The NRF2/KEAP1 axis is a key transcriptional regulator of the anti-oxidant response in cells. Nrf2 knockout mice have implicated this pathway in regulating inflammatory airway diseases such as asthma and COPD. To better understand the role the NRF2 pathway has on respiratory disease we have taken a novel approach to define NRF2 dependent gene expression in a relevant lung system. Methods Normal human lung fibroblasts were transfected with siRNA specific for NRF2 or KEAP1. Gene expression changes were measured at 30 and 48 hours using a custom Affymetrix Gene array. Changes in Eotaxin-1 gene expression and protein secretion were further measured under various inflammatory conditions with siRNAs and pharmacological tools. Results An anti-correlated gene set (inversely regulated by NRF2 and KEAP1 RNAi) that reflects specific NRF2 regulated genes was identified. Gene annotations show that NRF2-mediated oxidative stress response is the most significantly regulated pathway, followed by heme metabolism, metabolism of xenobiotics by Cytochrome P450 and O-glycan biosynthesis. Unexpectedly the key eosinophil chemokine Eotaxin-1/CCL11 was found to be up-regulated when NRF2 was inhibited and down-regulated when KEAP1 was inhibited. This transcriptional regulation leads to modulation of Eotaxin-1 secretion from human lung fibroblasts under basal and inflammatory conditions, and is specific to Eotaxin-1 as NRF2 or KEAP1 knockdown had no effect on the secretion of a set of other chemokines and cytokines. Furthermore, the known NRF2 small molecule activators CDDO and Sulphoraphane can also dose dependently inhibit Eotaxin-1 release from human lung fibroblasts. Conclusions These data uncover a previously unknown role for NRF2 in regulating Eotaxin-1 expression and further the mechanistic understanding of this pathway in modulating inflammatory lung disease. PMID:23061798

Early and long-standing rheumatoid arthritis: distinct molecular signatures identified by gene-expression profiling in synovia

PubMed Central

Lequerré, Thierry; Bansard, Carine; Vittecoq, Olivier; Derambure, Céline; Hiron, Martine; Daveau, Maryvonne; Tron, François; Ayral, Xavier; Biga, Norman; Auquit-Auckbur, Isabelle; Chiocchia, Gilles; Le Loët, Xavier; Salier, Jean-Philippe

2009-01-01

Introduction Rheumatoid arthritis (RA) is a heterogeneous disease and its underlying molecular mechanisms are still poorly understood. Because previous microarray studies have only focused on long-standing (LS) RA compared to osteoarthritis, we aimed to compare the molecular profiles of early and LS RA versus control synovia. Methods Synovial biopsies were obtained by arthroscopy from 15 patients (4 early untreated RA, 4 treated LS RA and 7 controls, who had traumatic or mechanical lesions). Extracted mRNAs were used for large-scale gene-expression profiling. The different gene-expression combinations identified by comparison of profiles of early, LS RA and healthy synovia were linked to the biological processes involved in each situation. Results Three combinations of 719, 116 and 52 transcripts discriminated, respectively, early from LS RA, and early or LS RA from healthy synovia. We identified several gene clusters and distinct molecular signatures specifically expressed during early or LS RA, thereby suggesting the involvement of different pathophysiological mechanisms during the course of RA. Conclusions Early and LS RA have distinct molecular signatures with different biological processes participating at different times during the course of the disease. These results suggest that better knowledge of the main biological processes involved at a given RA stage might help to choose the most appropriate treatment. PMID:19563633

Integration of targeted metabolomics and transcriptomics identifies deregulation of phosphatidylcholine metabolism in Huntington's disease peripheral blood samples.

PubMed

Mastrokolias, Anastasios; Pool, Rene; Mina, Eleni; Hettne, Kristina M; van Duijn, Erik; van der Mast, Roos C; van Ommen, GertJan; 't Hoen, Peter A C; Prehn, Cornelia; Adamski, Jerzy; van Roon-Mom, Willeke

Metabolic changes have been frequently associated with Huntington's disease (HD). At the same time peripheral blood represents a minimally invasive sampling avenue with little distress to Huntington's disease patients especially when brain or other tissue samples are difficult to collect. We investigated the levels of 163 metabolites in HD patient and control serum samples in order to identify disease related changes. Additionally, we integrated the metabolomics data with our previously published next generation sequencing-based gene expression data from the same patients in order to interconnect the metabolomics changes with transcriptional alterations. This analysis was performed using targeted metabolomics and flow injection electrospray ionization tandem mass spectrometry in 133 serum samples from 97 Huntington's disease patients (29 pre-symptomatic and 68 symptomatic) and 36 controls. By comparing HD mutation carriers with controls we identified 3 metabolites significantly changed in HD (serine and threonine and one phosphatidylcholine-PC ae C36:0) and an additional 8 phosphatidylcholines (PC aa C38:6, PC aa C36:0, PC ae C38:0, PC aa C38:0, PC ae C38:6, PC ae C42:0, PC aa C36:5 and PC ae C36:0) that exhibited a significant association with disease severity. Using workflow based exploitation of pathway databases and by integrating our metabolomics data with our gene expression data from the same patients we identified 4 deregulated phosphatidylcholine metabolism related genes ( ALDH1B1 , MBOAT1 , MTRR and PLB1 ) that showed significant association with the changes in metabolite concentrations. Our results support the notion that phosphatidylcholine metabolism is deregulated in HD blood and that these metabolite alterations are associated with specific gene expression changes.

The Gene of the Ubiquitin-Specific Protease 8 Is Frequently Mutated in Adenomas Causing Cushing's Disease.

PubMed

Perez-Rivas, Luis G; Theodoropoulou, Marily; Ferraù, Francesco; Nusser, Clara; Kawaguchi, Kohei; Stratakis, Constantine A; Faucz, Fabio Rueda; Wildemberg, Luiz E; Assié, Guillaume; Beschorner, Rudi; Dimopoulou, Christina; Buchfelder, Michael; Popovic, Vera; Berr, Christina M; Tóth, Miklós; Ardisasmita, Arif Ibrahim; Honegger, Jürgen; Bertherat, Jerôme; Gadelha, Monica R; Beuschlein, Felix; Stalla, Günter; Komada, Masayuki; Korbonits, Márta; Reincke, Martin

2015-07-01

We have recently reported somatic mutations in the ubiquitin-specific protease USP8 gene in a small series of adenomas of patients with Cushing's disease. To determine the prevalence of USP8 mutations and the genotype-phenotype correlation in a large series of patients diagnosed with Cushing's disease. We performed a retrospective, multicentric, genetic analysis of 134 functioning and 11 silent corticotroph adenomas using Sanger sequencing. Biochemical and clinical features were collected and examined within the context of the mutational status of USP8, and new mutations were characterized by functional studies. A total of 145 patients who underwent surgery for an ACTH-producing pituitary adenoma. Mutational status of USP8. Biochemical and clinical features included sex, age at diagnosis, tumor size, preoperative and postoperative hormonal levels, and comorbidities. We found somatic mutations in USP8 in 48 (36%) pituitary adenomas from patients with Cushing's disease but in none of 11 silent corticotropinomas. The prevalence was higher in adults than in pediatric cases (41 vs 17%) and in females than in males (43 vs 17%). Adults having USP8-mutated adenomas were diagnosed at an earlier age than those with wild-type lesions (36 vs 44 y). Mutations were primarily found in adenomas of 10 ± 7 mm and were inversely associated with the development of postoperative adrenal insufficiency. All the mutations affected the residues Ser718 or Pro720, including five new identified alterations. Mutations reduced the interaction between USP8 and 14-3-3 and enhanced USP8 activity. USP8 mutants diminished epidermal growth factor receptor ubiquitination and induced Pomc promoter activity in immortalized AtT-20 corticotropinoma cells. USP8 is frequently mutated in adenomas causing Cushing's disease, especially in those from female adult patients diagnosed at a younger age.

The Gene of the Ubiquitin-Specific Protease 8 Is Frequently Mutated in Adenomas Causing Cushing's Disease

PubMed Central

Perez-Rivas, Luis G.; Theodoropoulou, Marily; Ferraù, Francesco; Nusser, Clara; Kawaguchi, Kohei; Stratakis, Constantine A.; Faucz, Fabio Rueda; Wildemberg, Luiz E.; Assié, Guillaume; Beschorner, Rudi; Dimopoulou, Christina; Buchfelder, Michael; Popovic, Vera; Berr, Christina M.; Tóth, Miklós; Ardisasmita, Arif Ibrahim; Honegger, Jürgen; Bertherat, Jerôme; Gadelha, Monica R.; Beuschlein, Felix; Stalla, Günter; Komada, Masayuki; Korbonits, Márta

2015-01-01

Context: We have recently reported somatic mutations in the ubiquitin-specific protease USP8 gene in a small series of adenomas of patients with Cushing's disease. Objective: To determine the prevalence of USP8 mutations and the genotype-phenotype correlation in a large series of patients diagnosed with Cushing's disease. Design: We performed a retrospective, multicentric, genetic analysis of 134 functioning and 11 silent corticotroph adenomas using Sanger sequencing. Biochemical and clinical features were collected and examined within the context of the mutational status of USP8, and new mutations were characterized by functional studies. Patients: A total of 145 patients who underwent surgery for an ACTH-producing pituitary adenoma. Main Outcomes Measures: Mutational status of USP8. Biochemical and clinical features included sex, age at diagnosis, tumor size, preoperative and postoperative hormonal levels, and comorbidities. Results: We found somatic mutations in USP8 in 48 (36%) pituitary adenomas from patients with Cushing's disease but in none of 11 silent corticotropinomas. The prevalence was higher in adults than in pediatric cases (41 vs 17%) and in females than in males (43 vs 17%). Adults having USP8-mutated adenomas were diagnosed at an earlier age than those with wild-type lesions (36 vs 44 y). Mutations were primarily found in adenomas of 10 ± 7 mm and were inversely associated with the development of postoperative adrenal insufficiency. All the mutations affected the residues Ser718 or Pro720, including five new identified alterations. Mutations reduced the interaction between USP8 and 14-3-3 and enhanced USP8 activity. USP8 mutants diminished epidermal growth factor receptor ubiquitination and induced Pomc promoter activity in immortalized AtT-20 corticotropinoma cells. Conclusions: USP8 is frequently mutated in adenomas causing Cushing's disease, especially in those from female adult patients diagnosed at a younger age. PMID:25942478

Universal and specific quantitative detection of botulinum neurotoxin genes

PubMed Central

2010-01-01

Background Clostridium botulinum, an obligate anaerobic spore-forming bacterium, produces seven antigenic variants of botulinum toxin that are distinguished serologically and termed "serotypes". Botulinum toxin blocks the release of acetylcholine at neuromuscular junctions resulting in flaccid paralysis. The potential lethality of the disease warrants a fast and accurate means of diagnosing suspected instances of food contamination or human intoxication. Currently, the Food and Drug Administration (FDA)-accepted assay to detect and type botulinum neurotoxins (BoNTs) is the mouse protection bioassay. While specific and sensitive, this assay requires the use of laboratory animals, may take up to four days to achieve a diagnosis, and is unsuitable for high-throughput analysis. We report here a two-step PCR assay that identifies all toxin types, that achieves the specificity of the mouse bioassay while surpassing it in equivalent sensitivity, that has capability for high-throughput analysis, and that provides quantitative results within hours. The first step of our assay consists of a conventional PCR that detects the presence of C. botulinum regardless of the neurotoxin type. The second step uses quantitative PCR (qPCR) technology to determine the specific serotype of the neurotoxin. Results We assayed purified C. botulinum DNA and crude toxin preparations, as well as food and stool from healthy individuals spiked with purified BoNT DNA, and one stool sample from a case of infant botulism for the presence of the NTNH gene, which is part of the BoNT gene cluster, and for the presence of serotype-specific BoNT genes. The PCR surpassed the mouse bioassay both in specificity and sensitivity, detecting positive signals in BoNT preparations containing well below the 1 LD50 required for detection via the mouse bioassay. These results were type-specific and we were reliably able to quantify as few as 10 genomic copies. Conclusions While other studies have reported

Drosophila CLOCK target gene characterization: implications for circadian tissue-specific gene expression

PubMed Central

Abruzzi, Katharine Compton; Rodriguez, Joseph; Menet, Jerome S.; Desrochers, Jennifer; Zadina, Abigail; Luo, Weifei; Tkachev, Sasha; Rosbash, Michael

2011-01-01

CLOCK (CLK) is a master transcriptional regulator of the circadian clock in Drosophila. To identify CLK direct target genes and address circadian transcriptional regulation in Drosophila, we performed chromatin immunoprecipitation (ChIP) tiling array assays (ChIP–chip) with a number of circadian proteins. CLK binding cycles on at least 800 sites with maximal binding in the early night. The CLK partner protein CYCLE (CYC) is on most of these sites. The CLK/CYC heterodimer is joined 4–6 h later by the transcriptional repressor PERIOD (PER), indicating that the majority of CLK targets are regulated similarly to core circadian genes. About 30% of target genes also show cycling RNA polymerase II (Pol II) binding. Many of these generate cycling RNAs despite not being documented in prior RNA cycling studies. This is due in part to different RNA isoforms and to fly head tissue heterogeneity. CLK has specific targets in different tissues, implying that important CLK partner proteins and/or mechanisms contribute to gene-specific and tissue-specific regulation. PMID:22085964

Recombinational DSBs-intersected genes converge on specific disease- and adaptability-related pathways.

PubMed

Yang, Zhi-Kai; Luo, Hao; Zhang, Yanming; Wang, Baijing; Gao, Feng

2018-05-03

The budding yeast Saccharomyces cerevisiae is a model species powerful for studying the recombination of eukaryotes. Although many recombination studies have been performed for this species by experimental methods, the population genomic study based on bioinformatics analyses is urgently needed to greatly increase the range and accuracy of recombination detection. Here, we carry out the population genomic analysis of recombination in S. cerevisiae to reveal the potential rules between recombination and evolution in eukaryotes. By population genomic analysis, we discover significantly more and longer recombination events in clinical strains, which indicates that adverse environmental conditions create an obviously wider range of genetic combination in response to the selective pressure. Based on the analysis of recombinational DSBs-intersected genes (RDIGs), we find that RDIGs significantly converge on specific disease- and adaptability-related pathways, indicating that recombination plays a biologically key role in the repair of DSBs related to diseases and environmental adaptability, especially the human neurological disorders (NDs). By evolutionary analysis of RDIGs, we find that the RDIGs highly prevailing in populations of yeast tend to be more evolutionarily conserved, indicating the accurate repair of DSBs in these RDIGs is critical to ensure the eukaryotic survival or fitness. fgao@tju.edu.cn. Supplementary data are available at Bioinformatics online.

A whole-blood transcriptome meta-analysis identifies gene expression signatures of cigarette smoking

PubMed Central

Huan, Tianxiao; Joehanes, Roby; Schurmann, Claudia; Schramm, Katharina; Pilling, Luke C.; Peters, Marjolein J.; Mägi, Reedik; DeMeo, Dawn; O'Connor, George T.; Ferrucci, Luigi; Teumer, Alexander; Homuth, Georg; Biffar, Reiner; Völker, Uwe; Herder, Christian; Waldenberger, Melanie; Peters, Annette; Zeilinger, Sonja; Metspalu, Andres; Hofman, Albert; Uitterlinden, André G.; Hernandez, Dena G.; Singleton, Andrew B.; Bandinelli, Stefania; Munson, Peter J.; Lin, Honghuang; Benjamin, Emelia J.; Esko, Tõnu; Grabe, Hans J.; Prokisch, Holger; van Meurs, Joyce B.J.; Melzer, David; Levy, Daniel

2016-01-01

Abstract Cigarette smoking is a leading modifiable cause of death worldwide. We hypothesized that cigarette smoking induces extensive transcriptomic changes that lead to target-organ damage and smoking-related diseases. We performed a meta-analysis of transcriptome-wide gene expression using whole blood-derived RNA from 10,233 participants of European ancestry in six cohorts (including 1421 current and 3955 former smokers) to identify associations between smoking and altered gene expression levels. At a false discovery rate (FDR) <0.1, we identified 1270 differentially expressed genes in current vs. never smokers, and 39 genes in former vs. never smokers. Expression levels of 12 genes remained elevated up to 30 years after smoking cessation, suggesting that the molecular consequence of smoking may persist for decades. Gene ontology analysis revealed enrichment of smoking-related genes for activation of platelets and lymphocytes, immune response, and apoptosis. Many of the top smoking-related differentially expressed genes, including LRRN3 and GPR15, have DNA methylation loci in promoter regions that were recently reported to be hypomethylated among smokers. By linking differential gene expression with smoking-related disease phenotypes, we demonstrated that stroke and pulmonary function show enrichment for smoking-related gene expression signatures. Mediation analysis revealed the expression of several genes (e.g. ALAS2) to be putative mediators of the associations between smoking and inflammatory biomarkers (IL6 and C-reactive protein levels). Our transcriptomic study provides potential insights into the effects of cigarette smoking on gene expression in whole blood and their relations to smoking-related diseases. The results of such analyses may highlight attractive targets for treating or preventing smoking-related health effects. PMID:28158590

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

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

Next-generation DNA sequencing identifies novel gene variants and pathways involved in specific language impairment.

PubMed

Chen, Xiaowei Sylvia; Reader, Rose H; Hoischen, Alexander; Veltman, Joris A; Simpson, Nuala H; Francks, Clyde; Newbury, Dianne F; Fisher, Simon E

2017-04-25

A significant proportion of children have unexplained problems acquiring proficient linguistic skills despite adequate intelligence and opportunity. Developmental language disorders are highly heritable with substantial societal impact. Molecular studies have begun to identify candidate loci, but much of the underlying genetic architecture remains undetermined. We performed whole-exome sequencing of 43 unrelated probands affected by severe specific language impairment, followed by independent validations with Sanger sequencing, and analyses of segregation patterns in parents and siblings, to shed new light on aetiology. By first focusing on a pre-defined set of known candidates from the literature, we identified potentially pathogenic variants in genes already implicated in diverse language-related syndromes, including ERC1, GRIN2A, and SRPX2. Complementary analyses suggested novel putative candidates carrying validated variants which were predicted to have functional effects, such as OXR1, SCN9A and KMT2D. We also searched for potential "multiple-hit" cases; one proband carried a rare AUTS2 variant in combination with a rare inherited haplotype affecting STARD9, while another carried a novel nonsynonymous variant in SEMA6D together with a rare stop-gain in SYNPR. On broadening scope to all rare and novel variants throughout the exomes, we identified biological themes that were enriched for such variants, including microtubule transport and cytoskeletal regulation.

Next-generation DNA sequencing identifies novel gene variants and pathways involved in specific language impairment

PubMed Central

Chen, Xiaowei Sylvia; Reader, Rose H.; Hoischen, Alexander; Veltman, Joris A.; Simpson, Nuala H.; Francks, Clyde; Newbury, Dianne F.; Fisher, Simon E.

2017-01-01

A significant proportion of children have unexplained problems acquiring proficient linguistic skills despite adequate intelligence and opportunity. Developmental language disorders are highly heritable with substantial societal impact. Molecular studies have begun to identify candidate loci, but much of the underlying genetic architecture remains undetermined. We performed whole-exome sequencing of 43 unrelated probands affected by severe specific language impairment, followed by independent validations with Sanger sequencing, and analyses of segregation patterns in parents and siblings, to shed new light on aetiology. By first focusing on a pre-defined set of known candidates from the literature, we identified potentially pathogenic variants in genes already implicated in diverse language-related syndromes, including ERC1, GRIN2A, and SRPX2. Complementary analyses suggested novel putative candidates carrying validated variants which were predicted to have functional effects, such as OXR1, SCN9A and KMT2D. We also searched for potential “multiple-hit” cases; one proband carried a rare AUTS2 variant in combination with a rare inherited haplotype affecting STARD9, while another carried a novel nonsynonymous variant in SEMA6D together with a rare stop-gain in SYNPR. On broadening scope to all rare and novel variants throughout the exomes, we identified biological themes that were enriched for such variants, including microtubule transport and cytoskeletal regulation. PMID:28440294

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

A survey of disease connections for CD4+ T cell master genes and their directly linked genes.

PubMed

Li, Wentian; Espinal-Enríquez, Jesús; Simpfendorfer, Kim R; Hernández-Lemus, Enrique

2015-12-01

Genome-wide association studies and other genetic analyses have identified a large number of genes and variants implicating a variety of disease etiological mechanisms. It is imperative for the study of human diseases to put these genetic findings into a coherent functional context. Here we use system biology tools to examine disease connections of five master genes for CD4+ T cell subtypes (TBX21, GATA3, RORC, BCL6, and FOXP3). We compiled a list of genes functionally interacting (protein-protein interaction, or by acting in the same pathway) with the master genes, then we surveyed the disease connections, either by experimental evidence or by genetic association. Embryonic lethal genes (also known as essential genes) are over-represented in master genes and their interacting genes (55% versus 40% in other genes). Transcription factors are significantly enriched among genes interacting with the master genes (63% versus 10% in other genes). Predicted haploinsufficiency is a feature of most these genes. Disease-connected genes are enriched in this list of genes: 42% of these genes have a disease connection according to Online Mendelian Inheritance in Man (OMIM) (versus 23% in other genes), and 74% are associated with some diseases or phenotype in a Genome Wide Association Study (GWAS) (versus 43% in other genes). Seemingly, not all of the diseases connected to genes surveyed were immune related, which may indicate pleiotropic functions of the master regulator genes and associated genes. Copyright © 2015 Elsevier Ltd. All rights reserved.

A hybrid network-based method for the detection of disease-related genes

NASA Astrophysics Data System (ADS)

Cui, Ying; Cai, Meng; Dai, Yang; Stanley, H. Eugene

2018-02-01

Detecting disease-related genes is crucial in disease diagnosis and drug design. The accepted view is that neighbors of a disease-causing gene in a molecular network tend to cause the same or similar diseases, and network-based methods have been recently developed to identify novel hereditary disease-genes in available biomedical networks. Despite the steady increase in the discovery of disease-associated genes, there is still a large fraction of disease genes that remains under the tip of the iceberg. In this paper we exploit the topological properties of the protein-protein interaction (PPI) network to detect disease-related genes. We compute, analyze, and compare the topological properties of disease genes with non-disease genes in PPI networks. We also design an improved random forest classifier based on these network topological features, and a cross-validation test confirms that our method performs better than previous similar studies.

Gene therapy for Stargardt disease associated with ABCA4 gene.

PubMed

Han, Zongchao; Conley, Shannon M; Naash, Muna I

2014-01-01

Mutations in the photoreceptor-specific flippase ABCA4 lead to accumulation of the toxic bisretinoid A2E, resulting in atrophy of the retinal pigment epithelium (RPE) and death of the photoreceptor cells. Many blinding diseases are associated with these mutations including Stargardt's disease (STGD1), cone-rod dystrophy, retinitis pigmentosa (RP), and increased susceptibility to age-related macular degeneration. There are no curative treatments for any of these dsystrophies. While the monogenic nature of many of these conditions makes them amenable to treatment with gene therapy, the ABCA4 cDNA is 6.8 kb and is thus too large for the AAV vectors which have been most successful for other ocular genes. Here we review approaches to ABCA4 gene therapy including treatment with novel AAV vectors, lentiviral vectors, and non-viral compacted DNA nanoparticles. Lentiviral and compacted DNA nanoparticles in particular have a large capacity and have been successful in improving disease phenotypes in the Abca4 (-/-) murine model. Excitingly, two Phase I/IIa clinical trials are underway to treat patients with ABCA4-associated Startgardt's disease (STGD1). As a result of the development of these novel technologies, effective therapies for ABCA4-associated diseases may finally be within reach.

Whole Exome Sequencing in Dominant Cataract Identifies a New Causative Factor, CRYBA2, and a Variety of Novel Alleles in Known Genes

PubMed Central

Reis, Linda M.; Tyler, Rebecca C.; Muheisen, Sanaa; Raggio, Victor; Salviati, Leonardo; Han, Dennis P.; Costakos, Deborah; Yonath, Hagith; Hall, Sarah; Power, Patricia; Semina, Elena V.

2013-01-01

Pediatric cataracts are observed in 1–15 per 10,000 births with 10–25% of cases attributed to genetic causes; autosomal dominant inheritance is the most commonly observed pattern. Since the specific cataract phenotype is not sufficient to predict which gene is mutated, whole exome sequencing (WES) was utilized to concurrently screen all known cataract genes and to examine novel candidate factors for a disease-causing mutation in probands from 23 pedigrees affected with familial dominant cataract. Review of WES data for 36 known cataract genes identified causative mutations in nine pedigrees (39%) in CRYAA, CRYBB1, CRYBB3, CRYGC (2), CRYGD, GJA8 (2), and MIP and an additional likely causative mutation in EYA1; the CRYBB3 mutation represents the first dominant allele in this gene and demonstrates incomplete penetrance. Examination of crystallin genes not yet linked to human disease identified a novel cataract gene, CRYBA2, a member of the βγ-crystallin superfamily. The p.(Val50Met) mutation in CRYBA2 cosegregated with disease phenotype in a four-generation pedigree with autosomal dominant congenital cataracts with incomplete penetrance. Expression studies detected cryba2 transcripts during early lens development in zebrafish, supporting its role in congenital disease. Our data highlight the extreme genetic heterogeneity of dominant cataract as the eleven causative/likely causative mutations affected nine different genes and the majority of mutant alleles were novel. Furthermore, these data suggest that less than half of dominant cataract can be explained by mutations in currently known genes. PMID:23508780

The mitochondrial import gene tomm22 is specifically required for hepatocyte survival and provides a liver regeneration model

PubMed Central

Curado, Silvia; Ober, Elke A.; Walsh, Susan; Cortes-Hernandez, Paulina; Verkade, Heather; Koehler, Carla M.; Stainier, Didier Y. R.

2010-01-01

SUMMARY Understanding liver development should lead to greater insights into liver diseases and improve therapeutic strategies. In a forward genetic screen for genes regulating liver development in zebrafish, we identified a mutant – oliver – that exhibits liver-specific defects. In oliver mutants, the liver is specified, bile ducts form and hepatocytes differentiate. However, the hepatocytes die shortly after their differentiation, and thus the resulting mutant liver consists mainly of biliary tissue. We identified a mutation in the gene encoding translocase of the outer mitochondrial membrane 22 (Tomm22) as responsible for this phenotype. Mutations in tomm genes have been associated with mitochondrial dysfunction, but most studies on the effect of defective mitochondrial protein translocation have been carried out in cultured cells or unicellular organisms. Therefore, the tomm22 mutant represents an important vertebrate genetic model to study mitochondrial biology and hepatic mitochondrial diseases. We further found that the temporary knockdown of Tomm22 levels by morpholino antisense oligonucleotides causes a specific hepatocyte degeneration phenotype that is reversible: new hepatocytes repopulate the liver as Tomm22 recovers to wild-type levels. The specificity and reversibility of hepatocyte ablation after temporary knockdown of Tomm22 provides an additional model to study liver regeneration, under conditions where most hepatocytes have died. We used this regeneration model to analyze the signaling commonalities between hepatocyte development and regeneration. PMID:20483998

Genes, epigenetic regulation and environmental factors: which is the most relevant in developing autoimmune diseases?

PubMed

Costenbader, Karen H; Gay, Steffen; Alarcón-Riquelme, Marta E; Iaccarino, Luca; Doria, Andrea

2012-06-01

Autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis and inflammatory bowel disease, have complex pathogeneses and likely multifactorial etiologies. The current paradigm for understanding their development is that the disease is triggered in genetically-susceptible individuals by exposure to environmental factors. Some of these environmental factors have been specifically identified, while others are hypothesized and not yet proven, and it is likely that most have yet to be identified. One interesting hypothesis is that environmental effects on immune responses could be mediated by changes in epigenetic regulation. Major mechanisms of epigenetic gene regulation include DNA methylation and histone modification. In these cases, gene expression is modified without involving changes in DNA sequence. Epigenetics is a new and interesting research field in autoimmune diseases. We review the roles of genetic factors, epigenetic regulation and the most studied environmental risk factors such as cigarette smoke, crystalline silica, Epstein-Barr virus, and reproductive hormones in the pathogenesis of autoimmune disease. Copyright © 2011 Elsevier B.V. All rights reserved.

Functional Profiling Identifies Genes Involved in Organ-Specific Branches of the PIF3 Regulatory Network in Arabidopsis[C][W

PubMed Central

Sentandreu, Maria; Martín, Guiomar; González-Schain, Nahuel; Leivar, Pablo; Soy, Judit; Tepperman, James M.; Quail, Peter H.; Monte, Elena

2011-01-01

The phytochrome (phy)-interacting basic helix-loop-helix transcription factors (PIFs) constitutively sustain the etiolated state of dark-germinated seedlings by actively repressing deetiolation in darkness. This action is rapidly reversed upon light exposure by phy-induced proteolytic degradation of the PIFs. Here, we combined a microarray-based approach with a functional profiling strategy and identified four PIF3-regulated genes misexpressed in the dark (MIDAs) that are novel regulators of seedling deetiolation. We provide evidence that each one of these four MIDA genes regulates a specific facet of etiolation (hook maintenance, cotyledon appression, or hypocotyl elongation), indicating that there is branching in the signaling that PIF3 relays. Furthermore, combining inferred MIDA gene function from mutant analyses with their expression profiles in response to light-induced degradation of PIF3 provides evidence consistent with a model where the action of the PIF3/MIDA regulatory network enables an initial fast response to the light and subsequently prevents an overresponse to the initial light trigger, thus optimizing the seedling deetiolation process. Collectively, the data suggest that at least part of the phy/PIF system acts through these four MIDAs to initiate and optimize seedling deetiolation, and that this mechanism might allow the implementation of spatial (i.e., organ-specific) and temporal responses during the photomorphogenic program. PMID:22108407

Systematic identification of latent disease-gene associations from PubMed articles

PubMed Central

Mojarad, Majid Rastegar; Li, Dingcheng; Liu, Sijia; Tao, Cui; Yu, Yue; Liu, Hongfang

2018-01-01

Recent scientific advances have accumulated a tremendous amount of biomedical knowledge providing novel insights into the relationship between molecular and cellular processes and diseases. Literature mining is one of the commonly used methods to retrieve and extract information from scientific publications for understanding these associations. However, due to large data volume and complicated associations with noises, the interpretability of such association data for semantic knowledge discovery is challenging. In this study, we describe an integrative computational framework aiming to expedite the discovery of latent disease mechanisms by dissecting 146,245 disease-gene associations from over 25 million of PubMed indexed articles. We take advantage of both Latent Dirichlet Allocation (LDA) modeling and network-based analysis for their capabilities of detecting latent associations and reducing noises for large volume data respectively. Our results demonstrate that (1) the LDA-based modeling is able to group similar diseases into disease topics; (2) the disease-specific association networks follow the scale-free network property; (3) certain subnetwork patterns were enriched in the disease-specific association networks; and (4) genes were enriched in topic-specific biological processes. Our approach offers promising opportunities for latent disease-gene knowledge discovery in biomedical research. PMID:29373609

Systematic identification of latent disease-gene associations from PubMed articles.

PubMed

Zhang, Yuji; Shen, Feichen; Mojarad, Majid Rastegar; Li, Dingcheng; Liu, Sijia; Tao, Cui; Yu, Yue; Liu, Hongfang

2018-01-01

Recent scientific advances have accumulated a tremendous amount of biomedical knowledge providing novel insights into the relationship between molecular and cellular processes and diseases. Literature mining is one of the commonly used methods to retrieve and extract information from scientific publications for understanding these associations. However, due to large data volume and complicated associations with noises, the interpretability of such association data for semantic knowledge discovery is challenging. In this study, we describe an integrative computational framework aiming to expedite the discovery of latent disease mechanisms by dissecting 146,245 disease-gene associations from over 25 million of PubMed indexed articles. We take advantage of both Latent Dirichlet Allocation (LDA) modeling and network-based analysis for their capabilities of detecting latent associations and reducing noises for large volume data respectively. Our results demonstrate that (1) the LDA-based modeling is able to group similar diseases into disease topics; (2) the disease-specific association networks follow the scale-free network property; (3) certain subnetwork patterns were enriched in the disease-specific association networks; and (4) genes were enriched in topic-specific biological processes. Our approach offers promising opportunities for latent disease-gene knowledge discovery in biomedical research.

Disease Specific Productivity of American Cancer Hospitals

PubMed Central

Goldstein, Jeffery A.; Prasad, Vinay

2015-01-01

Context Research-oriented cancer hospitals in the United States treat and study patients with a range of diseases. Measures of disease specific research productivity, and comparison to overall productivity, are currently lacking. Hypothesis Different institutions are specialized in research of particular diseases. Objective To report disease specific productivity of American cancer hospitals, and propose a summary measure. Method We conducted a retrospective observational survey of the 50 highest ranked cancer hospitals in the 2013 US News and World Report rankings. We performed an automated search of PubMed and Clinicaltrials.gov for published reports and registrations of clinical trials (respectively) addressing specific cancers between 2008 and 2013. We calculated the summed impact factor for the publications. We generated a summary measure of productivity based on the number of Phase II clinical trials registered and the impact factor of Phase II clinical trials published for each institution and disease pair. We generated rankings based on this summary measure. Results We identified 6076 registered trials and 6516 published trials with a combined impact factor of 44280.4, involving 32 different diseases over the 50 institutions. Using a summary measure based on registered and published clinical trails, we ranked institutions in specific diseases. As expected, different institutions were highly ranked in disease-specific productivity for different diseases. 43 institutions appeared in the top 10 ranks for at least 1 disease (vs 10 in the overall list), while 6 different institutions were ranked number 1 in at least 1 disease (vs 1 in the overall list). Conclusion Research productivity varies considerably among the sample. Overall cancer productivity conceals great variation between diseases. Disease specific rankings identify sites of high academic productivity, which may be of interest to physicians, patients and researchers. PMID:25781329

Disease specific productivity of american cancer hospitals.

PubMed

Goldstein, Jeffery A; Prasad, Vinay

2015-01-01

Research-oriented cancer hospitals in the United States treat and study patients with a range of diseases. Measures of disease specific research productivity, and comparison to overall productivity, are currently lacking. Different institutions are specialized in research of particular diseases. To report disease specific productivity of American cancer hospitals, and propose a summary measure. We conducted a retrospective observational survey of the 50 highest ranked cancer hospitals in the 2013 US News and World Report rankings. We performed an automated search of PubMed and Clinicaltrials.gov for published reports and registrations of clinical trials (respectively) addressing specific cancers between 2008 and 2013. We calculated the summed impact factor for the publications. We generated a summary measure of productivity based on the number of Phase II clinical trials registered and the impact factor of Phase II clinical trials published for each institution and disease pair. We generated rankings based on this summary measure. We identified 6076 registered trials and 6516 published trials with a combined impact factor of 44280.4, involving 32 different diseases over the 50 institutions. Using a summary measure based on registered and published clinical trails, we ranked institutions in specific diseases. As expected, different institutions were highly ranked in disease-specific productivity for different diseases. 43 institutions appeared in the top 10 ranks for at least 1 disease (vs 10 in the overall list), while 6 different institutions were ranked number 1 in at least 1 disease (vs 1 in the overall list). Research productivity varies considerably among the sample. Overall cancer productivity conceals great variation between diseases. Disease specific rankings identify sites of high academic productivity, which may be of interest to physicians, patients and researchers.

Global and disease-associated genetic variation in the human Fanconi anemia gene family

PubMed Central

Rogers, Kai J.; Fu, Wenqing; Akey, Joshua M.; Monnat, Raymond J.

2014-01-01

Fanconi anemia (FA) is a human recessive genetic disease resulting from inactivating mutations in any of 16 FANC (Fanconi) genes. Individuals with FA are at high risk of developmental abnormalities, early bone marrow failure and leukemia. These are followed in the second and subsequent decades by a very high risk of carcinomas of the head and neck and anogenital region, and a small continuing risk of leukemia. In order to characterize base pair-level disease-associated (DA) and population genetic variation in FANC genes and the segregation of this variation in the human population, we identified 2948 unique FANC gene variants including 493 FA DA variants across 57 240 potential base pair variation sites in the 16 FANC genes. We then analyzed the segregation of this variation in the 7578 subjects included in the Exome Sequencing Project (ESP) and the 1000 Genomes Project (1KGP). There was a remarkably high frequency of FA DA variants in ESP/1KGP subjects: at least 1 FA DA variant was identified in 78.5% (5950 of 7578) individuals included in these two studies. Six widely used functional prediction algorithms correctly identified only a third of the known, DA FANC missense variants. We also identified FA DA variants that may be good candidates for different types of mutation-specific therapies. Our results demonstrate the power of direct DNA sequencing to detect, estimate the frequency of and follow the segregation of deleterious genetic variation in human populations. PMID:25104853

Discovery of cancer common and specific driver gene sets

PubMed Central

2017-01-01

Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295

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

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

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

PubMed Central

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

PubMed

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

Gene Expression Differences in Peripheral Blood of Parkinson’s Disease Patients with Distinct Progression Profiles

PubMed Central

Soreq, Lilach; Lobo, Patrícia P.; Mestre, Tiago; Coelho, Miguel; Rosa, Mário M.; Gonçalves, Nilza; Wales, Pauline; Mendes, Tiago; Gerhardt, Ellen; Fahlbusch, Christiane; Bonifati, Vincenzo; Bonin, Michael; Miltenberger-Miltényi, Gabriel; Borovecki, Fran; Soreq, Hermona; Ferreira, Joaquim J.; F. Outeiro, Tiago

2016-01-01

The prognosis of neurodegenerative disorders is clinically challenging due to the inexistence of established biomarkers for predicting disease progression. Here, we performed an exploratory cross-sectional, case-control study aimed at determining whether gene expression differences in peripheral blood may be used as a signature of Parkinson’s disease (PD) progression, thereby shedding light into potential molecular mechanisms underlying disease development. We compared transcriptional profiles in the blood from 34 PD patients who developed postural instability within ten years with those of 33 patients who did not develop postural instability within this time frame. Our study identified >200 differentially expressed genes between the two groups. The expression of several of the genes identified was previously found deregulated in animal models of PD and in PD patients. Relevant genes were selected for validation by real-time PCR in a subset of patients. The genes validated were linked to nucleic acid metabolism, mitochondria, immune response and intracellular-transport. Interestingly, we also found deregulation of these genes in a dopaminergic cell model of PD, a simple paradigm that can now be used to further dissect the role of these molecular players on dopaminergic cell loss. Altogether, our study provides preliminary evidence that expression changes in specific groups of genes and pathways, detected in peripheral blood samples, may be correlated with differential PD progression. Our exploratory study suggests that peripheral gene expression profiling may prove valuable for assisting in prediction of PD prognosis, and identifies novel culprits possibly involved in dopaminergic cell death. Given the exploratory nature of our study, further investigations using independent, well-characterized cohorts will be essential in order to validate our candidates as predictors of PD prognosis and to definitively confirm the value of gene expression analysis in aiding

A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer.

PubMed

Yang, Mary Qu; Li, Dan; Yang, William; Zhang, Yifan; Liu, Jun; Tong, Weida

2017-01-01

Clear cell renal cell carcinoma (ccRCC) is the most common and most aggressive form of renal cell cancer (RCC). The incidence of RCC has increased steadily in recent years. The pathogenesis of renal cell cancer remains poorly understood. Many of the tumor suppressor genes, oncogenes, and dysregulated pathways in ccRCC need to be revealed for improvement of the overall clinical outlook of the disease. Here, we developed a systems biology approach to prioritize the somatic mutated genes that lead to dysregulation of pathways in ccRCC. The method integrated multi-layer information to infer causative mutations and disease genes. First, we identified differential gene modules in ccRCC by coupling transcriptome and protein-protein interactions. Each of these modules consisted of interacting genes that were involved in similar biological processes and their combined expression alterations were significantly associated with disease type. Then, subsequent gene module-based eQTL analysis revealed somatic mutated genes that had driven the expression alterations of differential gene modules. Our study yielded a list of candidate disease genes, including several known ccRCC causative genes such as BAP1 and PBRM1 , as well as novel genes such as NOD2, RRM1, CSRNP1, SLC4A2, TTLL1 and CNTN1. The differential gene modules and their driver genes revealed by our study provided a new perspective for understanding the molecular mechanisms underlying the disease. Moreover, we validated the results in independent ccRCC patient datasets. Our study provided a new method for prioritizing disease genes and pathways.

Identification of a novel Gig2 gene family specific to non-amniote vertebrates.

PubMed

Zhang, Yi-Bing; Liu, Ting-Kai; Jiang, Jun; Shi, Jun; Liu, Ying; Li, Shun; Gui, Jian-Fang

2013-01-01

Gig2 (grass carp reovirus (GCRV)-induced gene 2) is first identified as a novel fish interferon (IFN)-stimulated gene (ISG). Overexpression of a zebrafish Gig2 gene can protect cultured fish cells from virus infection. In the present study, we identify a novel gene family that is comprised of genes homologous to the previously characterized Gig2. EST/GSS search and in silico cloning identify 190 Gig2 homologous genes in 51 vertebrate species ranged from lampreys to amphibians. Further large-scale search of vertebrate and invertebrate genome databases indicate that Gig2 gene family is specific to non-amniotes including lampreys, sharks/rays, ray-finned fishes and amphibians. Phylogenetic analysis and synteny analysis reveal lineage-specific expansion of Gig2 gene family and also provide valuable evidence for the fish-specific genome duplication (FSGD) hypothesis. Although Gig2 family proteins exhibit no significant sequence similarity to any known proteins, a typical Gig2 protein appears to consist of two conserved parts: an N-terminus that bears very low homology to the catalytic domains of poly(ADP-ribose) polymerases (PARPs), and a novel C-terminal domain that is unique to this gene family. Expression profiling of zebrafish Gig2 family genes shows that some duplicate pairs have diverged in function via acquisition of novel spatial and/or temporal expression under stresses. The specificity of this gene family to non-amniotes might contribute to a large extent to distinct physiology in non-amniote vertebrates.

The V471A Polymorphism in Autophagy-Related Gene ATG7 Modifies Age at Onset Specifically in Italian Huntington Disease Patients

PubMed Central

Metzger, Silke; Walter, Carolin; Riess, Olaf; Roos, Raymund A. C.; Nielsen, Jørgen E.; Craufurd, David; Nguyen, Huu Phuc

2013-01-01

The cause of Huntington disease (HD) is a polyglutamine repeat expansion of more than 36 units in the huntingtin protein, which is inversely correlated with the age at onset of the disease. However, additional genetic factors are believed to modify the course and the age at onset of HD. Recently, we identified the V471A polymorphism in the autophagy-related gene ATG7, a key component of the autophagy pathway that plays an important role in HD pathogenesis, to be associated with the age at onset in a large group of European Huntington disease patients. To confirm this association in a second independent patient cohort, we analysed the ATG7 V471A polymorphism in additional 1,464 European HD patients of the “REGISTRY” cohort from the European Huntington Disease Network (EHDN). In the entire REGISTRY cohort we could not confirm a modifying effect of the ATG7 V471A polymorphism. However, analysing a modifying effect of ATG7 in these REGISTRY patients and in patients of our previous HD cohort according to their ethnic origin, we identified a significant effect of the ATG7 V471A polymorphism on the HD age at onset only in the Italian population (327 patients). In these Italian patients, the polymorphism is associated with a 6-years earlier disease onset and thus seems to have an aggravating effect. We could specify the role of ATG7 as a genetic modifier for HD particularly in the Italian population. This result affirms the modifying influence of the autophagic pathway on the course of HD, but also suggests population-specific modifying mechanisms in HD pathogenesis. PMID:23894380

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- ...

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes.

PubMed

Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-10-03

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes

PubMed Central

Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-01-01

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes. PMID:29108274

Schistosoma mansoni: resistant specific infection-induced gene expression in Biomphalaria glabrata identified by fluorescent-based differential display.

PubMed

Lockyer, Anne E; Noble, Leslie R; Rollinson, David; Jones, Catherine S

2004-01-01

The freshwater tropical snail Biomphalaria glabrata is an intermediate host for Schistosoma mansoni, the causative agent of human intestinal schistosomiasis, and strains differ in their susceptibility to parasite infection. Changes in gene expression in response to parasite infection have been simultaneously examined in a susceptible strain (NHM1742) and a resistant strain (NHM1981) using a newly developed fluorescent-based differential display method. Such RNA profiling techniques allow the examination of changes in gene expression in response to parasite infection, without requiring previous sequence knowledge, or selecting candidate genes that may be involved in the complex neuroendocrine or defence systems of the snail. Thus, novel genes may be identified. Ten transcripts were initially identified, present only in the profiles derived from snails of the resistant strain when exposed to infection. The differential expression of five of these genes, including HSP70 and several novel transcripts with one containing at least two globin-like domains, has been confirmed by semi-quantitative RT-PCR.

Rational confederation of genes and diseases: NGS interpretation via GeneCards, MalaCards and VarElect.

PubMed

Rappaport, Noa; Fishilevich, Simon; Nudel, Ron; Twik, Michal; Belinky, Frida; Plaschkes, Inbar; Stein, Tsippi Iny; Cohen, Dana; Oz-Levi, Danit; Safran, Marilyn; Lancet, Doron

2017-08-18

A key challenge in the realm of human disease research is next generation sequencing (NGS) interpretation, whereby identified filtered variant-harboring genes are associated with a patient's disease phenotypes. This necessitates bioinformatics tools linked to comprehensive knowledgebases. The GeneCards suite databases, which include GeneCards (human genes), MalaCards (human diseases) and PathCards (human pathways) together with additional tools, are presented with the focus on MalaCards utility for NGS interpretation as well as for large scale bioinformatic analyses. VarElect, our NGS interpretation tool, leverages the broad information in the GeneCards suite databases. MalaCards algorithms unify disease-related terms and annotations from 69 sources. Further, MalaCards defines hierarchical relatedness-aliases, disease families, a related diseases network, categories and ontological classifications. GeneCards and MalaCards delineate and share a multi-tiered, scored gene-disease network, with stringency levels, including the definition of elite status-high quality gene-disease pairs, coming from manually curated trustworthy sources, that includes 4500 genes for 8000 diseases. This unique resource is key to NGS interpretation by VarElect. VarElect, a comprehensive search tool that helps infer both direct and indirect links between genes and user-supplied disease/phenotype terms, is robustly strengthened by the information found in MalaCards. The indirect mode benefits from GeneCards' diverse gene-to-gene relationships, including SuperPaths-integrated biological pathways from 12 information sources. We are currently adding an important information layer in the form of "disease SuperPaths", generated from the gene-disease matrix by an algorithm similar to that previously employed for biological pathway unification. This allows the discovery of novel gene-disease and disease-disease relationships. The advent of whole genome sequencing necessitates capacities to go beyond

Inference of cancer-specific gene regulatory networks using soft computing rules.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations

PubMed Central

2010-01-01

Background In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pathways. Here we describe an attempt to extend our understanding of these complex relationships by reanalyzing the data using three-dimensional (3D) network layouts, displayed through 2D and 3D viewing methods. Findings The 3D network layout (displayed through the 3D viewing method) revealed that genes implicated in many diseases (non-specific genes) tended to be predominantly down-regulated, whereas genes regulated in a few diseases (disease-specific genes) tended to be up-regulated. This new global relationship was quantitatively validated through comparison to 1000 random permutations of networks of the same size and distribution. Our new finding appeared to be the result of using specific features of the 3D viewing method to analyze the 3D renal network. Conclusions The global relationship between gene regulation and gene specificity is the first clue from human studies that there exist common mechanisms across several renal diseases, which suggest hypotheses for the underlying mechanisms. Furthermore, the study suggests hypotheses for why the 3D visualization helped to make salient a new regularity that was difficult to detect in 2D. Future research that tests these hypotheses should enable a more systematic understanding of when and how to use 3D network visualizations to reveal complex regularities in biological networks. PMID:21070623

Fourteen-Genome Comparison Identifies DNA Markers for Severe-Disease-Associated Strains of Clostridium difficile▿†

PubMed Central

Forgetta, Vincenzo; Oughton, Matthew T.; Marquis, Pascale; Brukner, Ivan; Blanchette, Ruth; Haub, Kevin; Magrini, Vince; Mardis, Elaine R.; Gerding, Dale N.; Loo, Vivian G.; Miller, Mark A.; Mulvey, Michael R.; Rupnik, Maja; Dascal, Andre; Dewar, Ken

2011-01-01

Clostridium difficile is a common cause of infectious diarrhea in hospitalized patients. A severe and increased incidence of C. difficile infection (CDI) is associated predominantly with the NAP1 strain; however, the existence of other severe-disease-associated (SDA) strains and the extensive genetic diversity across C. difficile complicate reliable detection and diagnosis. Comparative genome analysis of 14 sequenced genomes, including those of a subset of NAP1 isolates, allowed the assessment of genetic diversity within and between strain types to identify DNA markers that are associated with severe disease. Comparative genome analysis of 14 isolates, including five publicly available strains, revealed that C. difficile has a core genome of 3.4 Mb, comprising ∼3,000 genes. Analysis of the core genome identified candidate DNA markers that were subsequently evaluated using a multistrain panel of 177 isolates, representing more than 50 pulsovars and 8 toxinotypes. A subset of 117 isolates from the panel had associated patient data that allowed assessment of an association between the DNA markers and severe CDI. We identified 20 candidate DNA markers for species-wide detection and 10,683 single nucleotide polymorphisms (SNPs) associated with the predominant SDA strain (NAP1). A species-wide detection candidate marker, the sspA gene, was found to be the same across 177 sequenced isolates and lacked significant similarity to those of other species. Candidate SNPs in genes CD1269 and CD1265 were found to associate more closely with disease severity than currently used diagnostic markers, as they were also present in the toxin A-negative and B-positive (A-B+) strain types. The genetic markers identified illustrate the potential of comparative genomics for the discovery of diagnostic DNA-based targets that are species specific or associated with multiple SDA strains. PMID:21508155

Genome-Wide Analysis Identifies IL-18 and FUCA2 as Novel Genes Associated with Diastolic Function in African Americans with Sickle Cell Disease

PubMed Central