Science.gov

Sample records for identifying disease genes

  1. Strategies to identify disease genes.

    PubMed

    Ashton, Gabrielle H S; McGrath, John A; South, Andrew P

    2002-04-01

    The correlation between genes and disease began in earnest in the early 1900s with the identification of Mendelian-like inheritance of "inborn errors of metabolism." Since then, the ever-broadening field of genetics has been established as one of the most important and groundbreaking branches of science and medicine to date. With the announcement of a "working draft" sequence of the human genome in 2001, the vast array of both genomic and expressed sequence information available in the public databases alone has meant that the concept of hunting for genes is evolving. Nowadays, researchers can substitute many labor-intensive hours in the lab for less time searching on the World Wide Web. Specialization within genetics has been continuously providing subsets of the genre such as genomics, pharmacogenetics, chemogenomics, gene therapy, proteomics and functional genomics, all of which are based on the fundamental starting block, the gene. This review aims to summarize both traditional and current strategies for identifying susceptibility and monogenetic disease genes and describes how these strategies have evolved in tune with the ever-expanding wealth of information now available at our fingertips.

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

    PubMed Central

    2013-01-01

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

  3. Reconstructability analysis as a tool for identifying gene-gene interactions in studies of human diseases.

    PubMed

    Shervais, Stephen; Kramer, Patricia L; Westaway, Shawn K; Cox, Nancy J; Zwick, Martin

    2010-01-01

    There are a number of common human diseases for which the genetic component may include an epistatic interaction of multiple genes. Detecting these interactions with standard statistical tools is difficult because there may be an interaction effect, but minimal or no main effect. Reconstructability analysis (RA) uses Shannon's information theory to detect relationships between variables in categorical datasets. We applied RA to simulated data for five different models of gene-gene interaction, and find that even with heritability levels as low as 0.008, and with the inclusion of 50 non-associated genes in the dataset, we can identify the interacting gene pairs with an accuracy of > or =80%. We applied RA to a real dataset of type 2 non-insulin-dependent diabetes (NIDDM) cases and controls, and closely approximated the results of more conventional single SNP disease association studies. In addition, we replicated prior evidence for epistatic interactions between SNPs on chromosomes 2 and 15.

  4. Gene-based rare allele analysis identified a risk gene of Alzheimer's disease.

    PubMed

    Kim, Jong Hun; Song, Pamela; Lim, Hyunsun; Lee, Jae-Hyung; Lee, Jun Hong; Park, Sun Ah

    2014-01-01

    Alzheimer's disease (AD) has a strong propensity to run in families. However, the known risk genes excluding APOE are not clinically useful. In various complex diseases, gene studies have targeted rare alleles for unsolved heritability. Our study aims to elucidate previously unknown risk genes for AD by targeting rare alleles. We used data from five publicly available genetic studies from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the database of Genotypes and Phenotypes (dbGaP). A total of 4,171 cases and 9,358 controls were included. The genotype information of rare alleles was imputed using 1,000 genomes. We performed gene-based analysis of rare alleles (minor allele frequency≤3%). The genome-wide significance level was defined as meta P<1.8×10(-6) (0.05/number of genes in human genome = 0.05/28,517). ZNF628, which is located at chromosome 19q13.42, showed a genome-wide significant association with AD. The association of ZNF628 with AD was not dependent on APOE ε4. APOE and TREM2 were also significantly associated with AD, although not at genome-wide significance levels. Other genes identified by targeting common alleles could not be replicated in our gene-based rare allele analysis. We identified that rare variants in ZNF628 are associated with AD. The protein encoded by ZNF628 is known as a transcription factor. Furthermore, the associations of APOE and TREM2 with AD were highly significant, even in gene-based rare allele analysis, which implies that further deep sequencing of these genes is required in AD heritability studies.

  5. LGscore: A method to identify disease-related genes using biological literature and Google data.

    PubMed

    Kim, Jeongwoo; Kim, Hyunjin; Yoon, Youngmi; Park, Sanghyun

    2015-04-01

    Since the genome project in 1990s, a number of studies associated with genes have been conducted and researchers have confirmed that genes are involved in disease. For this reason, the identification of the relationships between diseases and genes is important in biology. We propose a method called LGscore, which identifies disease-related genes using Google data and literature data. To implement this method, first, we construct a disease-related gene network using text-mining results. We then extract gene-gene interactions based on co-occurrences in abstract data obtained from PubMed, and calculate the weights of edges in the gene network by means of Z-scoring. The weights contain two values: the frequency and the Google search results. The frequency value is extracted from literature data, and the Google search result is obtained using Google. We assign a score to each gene through a network analysis. We assume that genes with a large number of links and numerous Google search results and frequency values are more likely to be involved in disease. For validation, we investigated the top 20 inferred genes for five different diseases using answer sets. The answer sets comprised six databases that contain information on disease-gene relationships. We identified a significant number of disease-related genes as well as candidate genes for Alzheimer's disease, diabetes, colon cancer, lung cancer, and prostate cancer. Our method was up to 40% more accurate than existing methods.

  6. Systematic analysis of microarray datasets to identify Parkinson's disease-associated pathways and genes

    PubMed Central

    Feng, Yinling; Wang, Xuefeng

    2017-01-01

    In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co-expression networks and clinical information was adopted, using weighted gene co-expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co-pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution-based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD-associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis. PMID:28098893

  7. Genes that affect brain structure and function identified by rare variant analyses of Mendelian neurologic disease

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

    2015-01-01

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

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

    PubMed

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

    2015-12-10

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

  10. Analysis of gene expression in the nervous system identifies key genes and novel candidates for health and disease.

    PubMed

    Carpanini, Sarah M; Wishart, Thomas M; Gillingwater, Thomas H; Manson, Jean C; Summers, Kim M

    2017-04-01

    The incidence of neurodegenerative diseases in the developed world has risen over the last century, concomitant with an increase in average human lifespan. A major challenge is therefore to identify genes that control neuronal health and viability with a view to enhancing neuronal health during ageing and reducing the burden of neurodegeneration. Analysis of gene expression data has recently been used to infer gene functions for a range of tissues from co-expression networks. We have now applied this approach to transcriptomic datasets from the mammalian nervous system available in the public domain. We have defined the genes critical for influencing neuronal health and disease in different neurological cell types and brain regions. The functional contribution of genes in each co-expression cluster was validated using human disease and knockout mouse phenotypes, pathways and gene ontology term annotation. Additionally a number of poorly annotated genes were implicated by this approach in nervous system function. Exploiting gene expression data available in the public domain allowed us to validate key nervous system genes and, importantly, to identify additional genes with minimal functional annotation but with the same expression pattern. These genes are thus novel candidates for a role in neurological health and disease and could now be further investigated to confirm their function and regulation during ageing and neurodegeneration.

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

    PubMed Central

    Song, Min

    2016-01-01

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

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed

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

    2014-07-04

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

  14. DNA methylation map of mouse and human brain identifies target genes in Alzheimer’s disease

    PubMed Central

    Sanchez-Mut, Jose V.; Aso, Ester; Panayotis, Nicolas; Lott, Ira; Dierssen, Mara; Rabano, Alberto; Urdinguio, Rocio G.; Fernandez, Agustin F.; Astudillo, Aurora; Martin-Subero, Jose I.; Balint, Balazs; Fraga, Mario F.; Gomez, Antonio; Gurnot, Cecile; Roux, Jean-Christophe; Avila, Jesus; Hensch, Takao K.; Ferrer, Isidre

    2013-01-01

    The central nervous system has a pattern of gene expression that is closely regulated with respect to functional and anatomical regions. DNA methylation is a major regulator of transcriptional activity, and aberrations in the distribution of this epigenetic mark may be involved in many neurological disorders, such as Alzheimer’s disease. Herein, we have analysed 12 distinct mouse brain regions according to their CpG 5’-end gene methylation patterns and observed their unique epigenetic landscapes. The DNA methylomes obtained from the cerebral cortex were used to identify aberrant DNA methylation changes that occurred in two mouse models of Alzheimer’s disease. We were able to translate these findings to patients with Alzheimer’s disease, identifying DNA methylation-associated silencing of three targets genes: thromboxane A2 receptor (TBXA2R), sorbin and SH3 domain containing 3 (SORBS3) and spectrin beta 4 (SPTBN4). These hypermethylation targets indicate that the cyclic AMP response element-binding protein (CREB) activation pathway and the axon initial segment could contribute to the disease. PMID:24030951

  15. DNA methylation map of mouse and human brain identifies target genes in Alzheimer's disease.

    PubMed

    Sanchez-Mut, Jose V; Aso, Ester; Panayotis, Nicolas; Lott, Ira; Dierssen, Mara; Rabano, Alberto; Urdinguio, Rocio G; Fernandez, Agustin F; Astudillo, Aurora; Martin-Subero, Jose I; Balint, Balazs; Fraga, Mario F; Gomez, Antonio; Gurnot, Cecile; Roux, Jean-Christophe; Avila, Jesus; Hensch, Takao K; Ferrer, Isidre; Esteller, Manel

    2013-10-01

    The central nervous system has a pattern of gene expression that is closely regulated with respect to functional and anatomical regions. DNA methylation is a major regulator of transcriptional activity, and aberrations in the distribution of this epigenetic mark may be involved in many neurological disorders, such as Alzheimer's disease. Herein, we have analysed 12 distinct mouse brain regions according to their CpG 5'-end gene methylation patterns and observed their unique epigenetic landscapes. The DNA methylomes obtained from the cerebral cortex were used to identify aberrant DNA methylation changes that occurred in two mouse models of Alzheimer's disease. We were able to translate these findings to patients with Alzheimer's disease, identifying DNA methylation-associated silencing of three targets genes: thromboxane A2 receptor (TBXA2R), sorbin and SH3 domain containing 3 (SORBS3) and spectrin beta 4 (SPTBN4). These hypermethylation targets indicate that the cyclic AMP response element-binding protein (CREB) activation pathway and the axon initial segment could contribute to the disease.

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

    PubMed Central

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

    2007-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  19. 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.

  20. 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

  1. Genome Screen to Identify Susceptibility Genes for Parkinson Disease in a Sample without parkin Mutations

    PubMed Central

    Pankratz, Nathan; Nichols, William C.; Uniacke, Sean K.; Halter, Cheryl; Rudolph, Alice; Shults, Cliff; Conneally, P. Michael; Foroud, Tatiana

    2002-01-01

    Parkinson disease (PD) is a common neurodegenerative disorder characterized by bradykinesia, resting tremor, muscular rigidity, and postural instability, as well as by a clinically significant response to treatment with levodopa. Mutations in the α-synuclein gene have been found to result in autosomal dominant PD, and mutations in the parkin gene produce autosomal recessive juvenile-onset PD. We have studied 203 sibling pairs with PD who were evaluated by a rigorous neurological assessment based on (a) inclusion criteria consisting of clinical features highly associated with autopsy-confirmed PD and (b) exclusion criteria highly associated with other, non-PD pathological diagnoses. Families with positive LOD scores for a marker in an intron of the parkin gene were prioritized for parkin-gene testing, and mutations in the parkin gene were identified in 22 families. To reduce genetic heterogeneity, these families were not included in subsequent genome-screen analysis. Thus, a total of 160 multiplex families without evidence of a parkin mutation were used in multipoint nonparametric linkage analysis to identify PD-susceptibility genes. Two models of PD affection status were considered: model I included only those individuals with a more stringent diagnosis of verified PD (96 sibling pairs from 90 families), whereas model II included all examined individuals as affected, regardless of their final diagnostic classification (170 sibling pairs from 160 families). Under model I, the highest LOD scores were observed on chromosome X (LOD score 2.1) and on chromosome 2 (LOD score 1.9). Analyses performed with all available sibling pairs (model II) found even greater evidence of linkage to chromosome X (LOD score 2.7) and to chromosome 2 (LOD score 2.5). Evidence of linkage was also found to chromosomes 4, 5, and 13 (LOD scores >1.5). Our findings are consistent with those of other linkage studies that have reported linkage to chromosomes 5 and X. PMID:12058349

  2. 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

  3. A Genome-wide Association Study Identifies LIPA as a Susceptibility Gene for Coronary Artery Disease

    PubMed Central

    Wild, Philipp S; Zeller, Tanja; Schillert, Arne; Szymczak, Silke; Sinning, Christoph R; Deiseroth, Arne; Schnabel, Renate B; Lubos, Edith; Keller, Till; Eleftheriadis, Medea S; Bickel, Christoph; Rupprecht, Hans J; Wilde, Sandra; Rossmann, Heidi; Diemert, Patrick; Cupples, L Adrienne; Perret, Claire; Erdmann, Jeanette; Stark, Klaus; Kleber, Marcus E; Epstein, Stephen E; Voight, Benjamin F; Kuulasmaa, Kari; Li, Mingyao; Schäfer, Arne S; Klopp, Norman; Braund, Peter S; Sager, Hendrik B; Demissie, Serkalem; Proust, Carole; König, Inke R; Wichmann, Heinz-Erich; Reinhard, Wibke; Hoffmann, Michael M; Virtamo, Jarmo; Burnett, Mary Susan; Siscovick, David; Wiklund, Per Gunnar; Qu, Liming; El Mokthari, Nour Eddine; Thompson, John R; Peters, Annette; Smith, Albert V; Yon, Emmanuelle; Baumert, Jens; Hengstenberg, Christian; März, Winfried; Amouyel, Philippe; Devaney, Joseph; Schwartz, Stephen M; Saarela, Olli; Mehta, Nehal N; Rubin, Diana; Silander, Kaisa; Hall, Alistair S; Ferrieres, Jean; Harris, Tamara B; Melander, Olle; Kee, Frank; Hakonarson, Hakon; Schrezenmeir, Juergen; Gudnason, Vilmundur; Elosua, Roberto; Arveiler, Dominique; Evans, Alun; Rader, Daniel J; Illig, Thomas; Schreiber, Stefan; Bis, Joshua C; Altshuler, David; Kavousi, Maryam; Witteman, Jaqueline CM; Uitterlinden, Andre G; Hofman, Albert; Folsom, Aaron R; Barbalic, Maja; Boerwinkle, Eric; Kathiresan, Sekar; Reilly, Muredach P; O'Donnell, Christopher J; Samani, Nilesh J; Schunkert, Heribert; Cambien, Francois; Lackner, Karl J; Tiret, Laurence; Salomaa, Veikko; Munzel, Thomas; Ziegler, Andreas; Blankenberg, Stefan

    2011-01-01

    Background eQTL analyses are important to improve the understanding of genetic association results. Here, we performed a genome-wide association and global gene expression study to identify functionally relevant variants affecting the risk of coronary artery disease (CAD). Methods and Results In a genome-wide association analysis of 2,078 CAD cases and 2,953 controls, we identified 950 single nucleotide polymorphisms (SNPs) that were associated with CAD at P<10-3. Subsequent in silico and wet-lab replication stages and a final meta-analysis of 21,428 CAD cases and 38,361 controls revealed a novel association signal at chromosome 10q23.31 within the LIPA (Lysosomal Acid Lipase A) gene (P=3.7×10-8; OR 1.1; 95% CI: 1.07-1.14). The association of this locus with global gene expression was assessed by genome-wide expression analyses in the monocyte transcriptome of 1,494 individuals. The results showed a strong association of this locus with expression of the LIPA transcript (P=1.3×10-96). An assessment of LIPA SNPs and transcript with cardiovascular phenotypes revealed an association of LIPA transcript levels with impaired endothelial function (P=4.4×10-3). Conclusions The use of data on genetic variants and the addition of data on global monocytic gene expression led to the identification of the novel functional CAD susceptibility locus LIPA, located on chromosome 10q23.31. The respective eSNPs associated with CAD strongly affect LIPA gene expression level, which itself was related to endothelial dysfunction, a precursor of CAD. PMID:21606135

  4. 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

  5. Can modular analysis identify disease-associated candidate genes for therapeutics?

    PubMed

    Tegnér, Jesper

    2009-01-01

    Complex diseases such as allergy change gene expression in several cell types and tissues. Benson and colleagues have now shown, in a paper in BMC Systems Biology, that this complexity can be studied effectively using an integrated experimental and computational modular analysis. Their strategy revealed a core of allergy-associated genes of potential therapeutic value.

  6. Hypomorphic mutations identified in candidate Leber congenital amaurosis disease gene CLUAP1

    PubMed Central

    Soens, Zachry T.; Li, Yuanyuan; Zhao, Li; Eblimit, Aiden; Dharmat, Rachayata; Li, Yumei; Chen, Yiyun; Naqeeb, Mohammed; Fajardo, Norma; Lopez, Irma; Sun, Zhaoxia; Koenekoop, Robert K.; Chen, Rui

    2015-01-01

    Purpose Leber congenital amaurosis (LCA) is an early-onset form of retinal degeneration and six of the 22 known LCA disease genes encode photoreceptor ciliary proteins. Despite the identification of 22 LCA disease genes, the genetic basis of approximately 30% of LCA patients remains unknown. We sought to investigate the cause of disease in the remaining 30% by examining cilia-associated genes. Methods Whole-exome sequencing was performed on an LCA cohort of 212 unsolved probands previously screened for mutations in known retinal disease genes. Immunohistochemistry using mouse retinas was used to confirm protein localization and zebrafish were used to perform rescue experiments. Results A homozygous nonsynonymous mutation was found in a single proband in CLUAP1, a gene required for ciliogenesis and cilia maintenance. Cluap1 knockout zebrafish exhibit photoreceptor cell death as early as five days post fertilization and rescue experiments revealed that our proband’s mutation is significantly hypomorphic. Conclusion Consistent with the knowledge that CLUAP1 plays an important role in cilia function and that cilia are critical to photoreceptor function, our results indicate that hypomorphic mutations in CLUAP1 can result in dysfunctional photoreceptors without systemic abnormalities. This represents the first report linking mutations in CLUAP1 to human disease and establishes CLUAP1 as a candidate LCA gene. PMID:26820066

  7. ToP: a trend-of-disease-progression procedure works well for identifying cancer genes from multi-state cohort gene expression data for human colorectal cancer.

    PubMed

    Chung, Feng-Hsiang; Lee, Henry Hsin-Chung; Lee, Hoong-Chien

    2013-01-01

    Significantly expressed genes extracted from microarray gene expression data have proved very useful for identifying genetic biomarkers of diseases, including cancer. However, deriving a disease related inference from a list of differentially expressed genes has proven less than straightforward. In a systems disease such as cancer, how genes interact with each other should matter just as much as the level of gene expression. Here, in a novel approach, we used the network and disease progression properties of individual genes in state-specific gene-gene interaction networks (GGINs) to select cancer genes for human colorectal cancer (CRC) and obtain a much higher hit rate of known cancer genes when compared with methods not based on network theory. We constructed GGINs by integrating gene expression microarray data from multiple states--healthy control (Nor), adenoma (Ade), inflammatory bowel disease (IBD) and CRC--with protein-protein interaction database and Gene Ontology. We tracked changes in the network degrees and clustering coefficients of individual genes in the GGINs as the disease state changed from one to another. From these we inferred the state sequences Nor-Ade-CRC and Nor-IBD-CRC both exhibited a trend of (disease) progression (ToP) toward CRC, and devised a ToP procedure for selecting cancer genes for CRC. Of the 141 candidates selected using ToP, ∼50% had literature support as cancer genes, compared to hit rates of 20% to 30% for standard methods using only gene expression data. Among the 16 candidate cancer genes that encoded transcription factors, 13 were known to be tumorigenic and three were novel: CDK1, SNRPF, and ILF2. We identified 13 of the 141 predicted cancer genes as candidate markers for early detection of CRC, 11 and 2 at the Ade and IBD states, respectively.

  8. Disease-targeted sequencing of ion channel genes identifies de novo mutations in patients with non-familial Brugada syndrome.

    PubMed

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

    2014-10-23

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

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  10. HDR: a statistical two-step approach successfully identifies disease genes in autosomal recessive families.

    PubMed

    Imai, Atsuko; Kohda, Masakazu; Nakaya, Akihiro; Sakata, Yasushi; Murayama, Kei; Ohtake, Akira; Lathrop, Mark; Okazaki, Yasushi; Ott, Jurg

    2016-11-01

    In the search for sequence variants underlying disease, commonly applied filtering steps usually result in a number of candidate variants that cannot further be narrowed down. In autosomal recessive families, disease usually occurs only in one generation so that genetic linkage analysis is unlikely to help. Because homozygous recessive mutations tend to be inherited together with flanking homozygous variants, we developed a statistical method to detect pathogenic variants in autosomal recessive families: We look for differences in patterns of homozygosity around candidate variants between patients and control individuals and expect that such differences are greater for pathogenic variants than random candidate variants. In six autosomal recessive mitochondrial disease families, in which pathogenic homozygous variants have already been identified, our approach succeeded in prioritizing pathogenic mutations. Our method is applicable to single patients from recessive families with at least a few dozen control individuals from the same population; it is easy to use and is highly effective for detecting causative mutations in autosomal recessive families.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. Identify potential drugs for cardiovascular diseases caused by stress-induced genes in vascular smooth muscle cells

    PubMed Central

    Ciou, Jin-Shuei; Chen, Shun-Tsung; Chung, Yi; Tsai, Jeffrey J. P.; Kurubanjerdjit, Nilubon

    2016-01-01

    Background Abnormal proliferation of vascular smooth muscle cells (VSMC) is a major cause of cardiovascular diseases (CVDs). Many studies suggest that vascular injury triggers VSMC dedifferentiation, which results in VSMC changes from a contractile to a synthetic phenotype; however, the underlying molecular mechanisms are still unclear. Methods In this study, we examined how VSMC responds under mechanical stress by using time-course microarray data. A three-phase study was proposed to investigate the stress-induced differentially expressed genes (DEGs) in VSMC. First, DEGs were identified by using the moderated t-statistics test. Second, more DEGs were inferred by using the Gaussian Graphical Model (GGM). Finally, the topological parameters-based method and cluster analysis approach were employed to predict the last batch of DEGs. To identify the potential drugs for vascular diseases involve VSMC proliferation, the drug-gene interaction database, Connectivity Map (cMap) was employed. Success of the predictions were determined using in-vitro data, i.e. MTT and clonogenic assay. Results Based on the differential expression calculation, at least 23 DEGs were found, and the findings were qualified by previous studies on VSMC. The results of gene set enrichment analysis indicated that the most often found enriched biological processes are cell-cycle-related processes. Furthermore, more stress-induced genes, well supported by literature, were found by applying graph theory to the gene association network (GAN). Finally, we showed that by processing the cMap input queries with a cluster algorithm, we achieved a substantial increase in the number of potential drugs with experimental IC50 measurements. With this novel approach, we have not only successfully identified the DEGs, but also improved the DEGs prediction by performing the topological and cluster analysis. Moreover, the findings are remarkably validated and in line with the literature. Furthermore, the cMap and

  13. Candidate-gene criteria for clinical reporting: diagnostic exome sequencing identifies altered candidate genes among 8% of patients with undiagnosed diseases

    PubMed Central

    Farwell Hagman, Kelly D.; Shinde, Deepali N.; Mroske, Cameron; Smith, Erica; Radtke, Kelly; Shahmirzadi, Layla; El-Khechen, Dima; Powis, Zöe; Chao, Elizabeth C.; Alcaraz, Wendy A.; Helbig, Katherine L.; Sajan, Samin A.; Rossi, Mari; Lu, Hsiao-Mei; Huether, Robert; Li, Shuwei; Wu, Sitao; Nuñes, Mark E.; Tang, Sha

    2017-01-01

    Purpose: Diagnostic exome sequencing (DES) is now a commonly ordered test for individuals with undiagnosed genetic disorders. In addition to providing a diagnosis for characterized diseases, exome sequencing has the capacity to uncover novel candidate genes for disease. Methods: Family-based DES included analysis of both characterized and novel genetic etiologies. To evaluate candidate genes for disease in the clinical setting, we developed a systematic, rule-based classification schema. Results: Testing identified a candidate gene among 7.7% (72/934) of patients referred for DES; 37 (4.0%) and 35 (3.7%) of the genes received evidence scores of “candidate” and “suspected candidate,” respectively. A total of 71 independent candidate genes were reported among the 72 patients, and 38% (27/71) were subsequently corroborated in the peer-reviewed literature. This rate of corroboration increased to 51.9% (27/52) among patients whose gene was reported at least 12 months previously. Conclusions: Herein, we provide transparent, comprehensive, and standardized scoring criteria for the clinical reporting of candidate genes. These results demonstrate that DES is an integral tool for genetic diagnosis, especially for elucidating the molecular basis for both characterized and novel candidate genetic etiologies. Gene discoveries also advance the understanding of normal human biology and more common diseases. Genet Med 19 2, 224–235. PMID:27513193

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

    PubMed Central

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

    2015-01-01

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

  15. 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.

  16. Genome-wide linkage scan identifies two novel genetic loci for coronary artery disease: in GeneQuest families.

    PubMed

    Gao, Hanxiang; Li, Lin; Rao, Shaoqi; Shen, Gongqing; Xi, Quansheng; Chen, Shenghan; Zhang, Zheng; Wang, Kai; Ellis, Stephen G; Chen, Qiuyun; Topol, Eric J; Wang, Qing K

    2014-01-01

    Coronary artery disease (CAD) is the leading cause of death worldwide. Recent genome-wide association studies (GWAS) identified >50 common variants associated with CAD or its complication myocardial infarction (MI), but collectively they account for <20% of heritability, generating a phenomena of "missing heritability". Rare variants with large effects may account for a large portion of missing heritability. Genome-wide linkage studies of large families and follow-up fine mapping and deep sequencing are particularly effective in identifying rare variants with large effects. Here we show results from a genome-wide linkage scan for CAD in multiplex GeneQuest families with early onset CAD and MI. Whole genome genotyping was carried out with 408 markers that span the human genome by every 10 cM and linkage analyses were performed using the affected relative pair analysis implemented in GENEHUNTER. Affected only nonparametric linkage (NPL) analysis identified two novel CAD loci with highly significant evidence of linkage on chromosome 3p25.1 (peak NPL  = 5.49) and 3q29 (NPL  = 6.84). We also identified four loci with suggestive linkage on 9q22.33, 9q34.11, 17p12, and 21q22.3 (NPL  = 3.18-4.07). These results identify novel loci for CAD and provide a framework for fine mapping and deep sequencing to identify new susceptibility genes and novel variants associated with risk of CAD.

  17. Genetic analysis of fin development in zebrafish identifies furin and hemicentin1 as potential novel fraser syndrome disease genes.

    PubMed

    Carney, Thomas J; Feitosa, Natália Martins; Sonntag, Carmen; Slanchev, Krasimir; Kluger, Johannes; Kiyozumi, Daiji; Gebauer, Jan M; Coffin Talbot, Jared; Kimmel, Charles B; Sekiguchi, Kiyotoshi; Wagener, Raimund; Schwarz, Heinz; Ingham, Phillip W; Hammerschmidt, Matthias

    2010-04-15

    Using forward genetics, we have identified the genes mutated in two classes of zebrafish fin mutants. The mutants of the first class are characterized by defects in embryonic fin morphogenesis, which are due to mutations in a Laminin subunit or an Integrin alpha receptor, respectively. The mutants of the second class display characteristic blistering underneath the basement membrane of the fin epidermis. Three of them are due to mutations in zebrafish orthologues of FRAS1, FREM1, or FREM2, large basement membrane protein encoding genes that are mutated in mouse bleb mutants and in human patients suffering from Fraser Syndrome, a rare congenital condition characterized by syndactyly and cryptophthalmos. Fin blistering in a fourth group of zebrafish mutants is caused by mutations in Hemicentin1 (Hmcn1), another large extracellular matrix protein the function of which in vertebrates was hitherto unknown. Our mutant and dose-dependent interaction data suggest a potential involvement of Hmcn1 in Fraser complex-dependent basement membrane anchorage. Furthermore, we present biochemical and genetic data suggesting a role for the proprotein convertase FurinA in zebrafish fin development and cell surface shedding of Fras1 and Frem2, thereby allowing proper localization of the proteins within the basement membrane of forming fins. Finally, we identify the extracellular matrix protein Fibrillin2 as an indispensable interaction partner of Hmcn1. Thus we have defined a series of zebrafish mutants modelling Fraser Syndrome and have identified several implicated novel genes that might help to further elucidate the mechanisms of basement membrane anchorage and of the disease's aetiology. In addition, the novel genes might prove helpful to unravel the molecular nature of thus far unresolved cases of the human disease.

  18. Identified molecular mechanism of interaction between environmental risk factors and differential expression genes in cartilage of Kashin-Beck disease.

    PubMed

    Yu, Fang-Fang; Zhang, Yan-Xiang; Zhang, Lian-He; Li, Wen-Rong; Guo, Xiong; Lammi, Mikko J

    2016-12-01

    As environmental risk factors (ERFs) play an important role in the pathogenesis of Kashin-Beck disease (KBD), it is important to identify the interaction between ERFs and differentially expression genes (DEGs) in KBD. The environmental response genes (ERGs) were analyzed in cartilage of KBD in comparison to normal controls.We searched 5 English and 3 Chinese databases from inception to September 2015, to identify case-control studies that examined ERFs for KBD using integrative meta-analysis and systematic review. Total RNA was isolated from articular cartilage of KBD patients and healthy controls. Human whole genome microarray chip (Agilent) was used to analyze the amplified, labeled, and hybridized total RNA, and the validated microarray data were partially verified using real-time quantitative polymerase chain reaction (qRT-PCR). The ERGs were derived from the Comparative Toxicogenomics Database. The identified ERGs were subjected to KEGG pathway enrichment, biological process (BP), and interaction network analyses using the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7, and STRING.The trace elements (selenium and iodine), vitamin E, and polluted grains (T-2 toxin/HT-2 toxin, deoxynivalenol, and nivalenol) were identified as the ERFs for KBD using meta-analysis and review. We identified 21 upregulated ERGs and 7 downregulated ERGs in cartilage with KBD compared with healthy controls, which involved in apoptosis, metabolism, and growth and development. KEGG pathway enrichment analysis found that 2 significant pathways were involved with PI3K-Akt signaling pathway and P53 signaling pathway, and gene ontology function analysis found 3 BPs involved with apoptosis, death, and cell death in KBD cartilage.According to previous results and our own research, we suggest that the trace element selenium and vitamin E induce PI3K-Akt signaling pathway and the mycotoxins (T-2 toxin/HT-2 toxin and DON) induce P53 signaling pathway, contributing

  19. Identified molecular mechanism of interaction between environmental risk factors and differential expression genes in cartilage of Kashin–Beck disease

    PubMed Central

    Yu, Fang-Fang; Zhang, Yan-Xiang; Zhang, Lian-He; Li, Wen-Rong; Guo, Xiong; Lammi, Mikko J.

    2016-01-01

    Abstract As environmental risk factors (ERFs) play an important role in the pathogenesis of Kashin–Beck disease (KBD), it is important to identify the interaction between ERFs and differentially expression genes (DEGs) in KBD. The environmental response genes (ERGs) were analyzed in cartilage of KBD in comparison to normal controls. We searched 5 English and 3 Chinese databases from inception to September 2015, to identify case–control studies that examined ERFs for KBD using integrative meta-analysis and systematic review. Total RNA was isolated from articular cartilage of KBD patients and healthy controls. Human whole genome microarray chip (Agilent) was used to analyze the amplified, labeled, and hybridized total RNA, and the validated microarray data were partially verified using real-time quantitative polymerase chain reaction (qRT-PCR). The ERGs were derived from the Comparative Toxicogenomics Database. The identified ERGs were subjected to KEGG pathway enrichment, biological process (BP), and interaction network analyses using the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7, and STRING. The trace elements (selenium and iodine), vitamin E, and polluted grains (T-2 toxin/HT-2 toxin, deoxynivalenol, and nivalenol) were identified as the ERFs for KBD using meta-analysis and review. We identified 21 upregulated ERGs and 7 downregulated ERGs in cartilage with KBD compared with healthy controls, which involved in apoptosis, metabolism, and growth and development. KEGG pathway enrichment analysis found that 2 significant pathways were involved with PI3K-Akt signaling pathway and P53 signaling pathway, and gene ontology function analysis found 3 BPs involved with apoptosis, death, and cell death in KBD cartilage. According to previous results and our own research, we suggest that the trace element selenium and vitamin E induce PI3K-Akt signaling pathway and the mycotoxins (T-2 toxin/HT-2 toxin and DON) induce P53 signaling pathway

  20. Genome-wide association study for acute otitis media in children identifies FNDC1 as disease contributing gene

    PubMed Central

    van Ingen, Gijs; Li, Jin; Goedegebure, André; Pandey, Rahul; Li, Yun Rose; March, Michael E.; Jaddoe, Vincent W. V.; Bakay, Marina; Mentch, Frank D.; Thomas, Kelly; Wei, Zhi; Chang, Xiao; Hain, Heather S.; Uitterlinden, André G.; Moll, Henriette A.; van Duijn, Cornelia M.; Rivadeneira, Fernando; Raat, Hein; Baatenburg de Jong, Robert J.; Sleiman, Patrick M.; van der Schroeff, Marc P.; Hakonarson, Hakon

    2016-01-01

    Acute otitis media (AOM) is among the most common pediatric diseases, and the most frequent reason for antibiotic treatment in children. Risk of AOM is dependent on environmental and host factors, as well as a significant genetic component. We identify genome-wide significance at a locus on 6q25.3 (rs2932989, Pmeta=2.15 × 10−09), and show that the associated variants are correlated with the methylation status of the FNDC1 gene (cg05678571, P=1.43 × 10−06), and further show it is an eQTL for FNDC1 (P=9.3 × 10−05). The mouse homologue, Fndc1, is expressed in middle ear tissue and its expression is upregulated upon lipopolysaccharide treatment. In this first GWAS of AOM and the largest OM genetic study to date, we identify the first genome-wide significant locus associated with AOM. PMID:27677580

  1. Genome-Wide Linkage Scan Identifies Two Novel Genetic Loci for Coronary Artery Disease: In GeneQuest Families

    PubMed Central

    Shen, Gongqing; Xi, Quansheng; Chen, Shenghan; Zhang, Zheng; Wang, Kai; Ellis, Stephen G.; Chen, Qiuyun; Topol, Eric J.; Wang, Qing K.

    2014-01-01

    Coronary artery disease (CAD) is the leading cause of death worldwide. Recent genome-wide association studies (GWAS) identified >50 common variants associated with CAD or its complication myocardial infarction (MI), but collectively they account for <20% of heritability, generating a phenomena of “missing heritability”. Rare variants with large effects may account for a large portion of missing heritability. Genome-wide linkage studies of large families and follow-up fine mapping and deep sequencing are particularly effective in identifying rare variants with large effects. Here we show results from a genome-wide linkage scan for CAD in multiplex GeneQuest families with early onset CAD and MI. Whole genome genotyping was carried out with 408 markers that span the human genome by every 10 cM and linkage analyses were performed using the affected relative pair analysis implemented in GENEHUNTER. Affected only nonparametric linkage (NPL) analysis identified two novel CAD loci with highly significant evidence of linkage on chromosome 3p25.1 (peak NPL  = 5.49) and 3q29 (NPL  = 6.84). We also identified four loci with suggestive linkage on 9q22.33, 9q34.11, 17p12, and 21q22.3 (NPL  = 3.18–4.07). These results identify novel loci for CAD and provide a framework for fine mapping and deep sequencing to identify new susceptibility genes and novel variants associated with risk of CAD. PMID:25485937

  2. Whole blood transcriptional profiling in ankylosing spondylitis identifies novel candidate genes that might contribute to the inflammatory and tissue-destructive disease aspects

    PubMed Central

    2011-01-01

    Introduction A number of genetic-association studies have identified genes contributing to ankylosing spondylitis (AS) susceptibility but such approaches provide little information as to the gene activity changes occurring during the disease process. Transcriptional profiling generates a 'snapshot' of the sampled cells' activity and thus can provide insights into the molecular processes driving the disease process. We undertook a whole-genome microarray approach to identify candidate genes associated with AS and validated these gene-expression changes in a larger sample cohort. Methods A total of 18 active AS patients, classified according to the New York criteria, and 18 gender- and age-matched controls were profiled using Illumina HT-12 whole-genome expression BeadChips which carry cDNAs for 48,000 genes and transcripts. Class comparison analysis identified a number of differentially expressed candidate genes. These candidate genes were then validated in a larger cohort using qPCR-based TaqMan low density arrays (TLDAs). Results A total of 239 probes corresponding to 221 genes were identified as being significantly different between patients and controls with a P-value <0.0005 (80% confidence level of false discovery rate). Forty-seven genes were then selected for validation studies, using the TLDAs. Thirteen of these genes were validated in the second patient cohort with 12 downregulated 1.3- to 2-fold and only 1 upregulated (1.6-fold). Among a number of identified genes with well-documented inflammatory roles we also validated genes that might be of great interest to the understanding of AS progression such as SPOCK2 (osteonectin) and EP300, which modulate cartilage and bone metabolism. Conclusions We have validated a gene expression signature for AS from whole blood and identified strong candidate genes that may play roles in both the inflammatory and joint destruction aspects of the disease. PMID:21470430

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

    PubMed Central

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

    2011-01-01

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

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

    PubMed

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

    2015-05-01

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

  5. A Simple Screening Approach To Prioritize Genes for Functional Analysis Identifies a Role for Interferon Regulatory Factor 7 in the Control of Respiratory Syncytial Virus Disease

    PubMed Central

    McDonald, Jacqueline U.; Kaforou, Myrsini; Clare, Simon; Hale, Christine; Ivanova, Maria; Huntley, Derek; Dorner, Marcus; Wright, Victoria J.; Levin, Michael; Martinon-Torres, Federico; Herberg, Jethro A.

    2016-01-01

    ABSTRACT Greater understanding of the functions of host gene products in response to infection is required. While many of these genes enable pathogen clearance, some enhance pathogen growth or contribute to disease symptoms. Many studies have profiled transcriptomic and proteomic responses to infection, generating large data sets, but selecting targets for further study is challenging. Here we propose a novel data-mining approach combining multiple heterogeneous data sets to prioritize genes for further study by using respiratory syncytial virus (RSV) infection as a model pathogen with a significant health care impact. The assumption was that the more frequently a gene is detected across multiple studies, the more important its role is. A literature search was performed to find data sets of genes and proteins that change after RSV infection. The data sets were standardized, collated into a single database, and then panned to determine which genes occurred in multiple data sets, generating a candidate gene list. This candidate gene list was validated by using both a clinical cohort and in vitro screening. We identified several genes that were frequently expressed following RSV infection with no assigned function in RSV control, including IFI27, IFIT3, IFI44L, GBP1, OAS3, IFI44, and IRF7. Drilling down into the function of these genes, we demonstrate a role in disease for the gene for interferon regulatory factor 7, which was highly ranked on the list, but not for IRF1, which was not. Thus, we have developed and validated an approach for collating published data sets into a manageable list of candidates, identifying novel targets for future analysis. IMPORTANCE Making the most of “big data” is one of the core challenges of current biology. There is a large array of heterogeneous data sets of host gene responses to infection, but these data sets do not inform us about gene function and require specialized skill sets and training for their utilization. Here we

  6. Systems analysis of immune responses in Marek's disease virus-infected chickens identifies a gene involved in susceptibility and highlights a possible novel pathogenicity mechanism.

    PubMed

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

    2011-11-01

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

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

    PubMed

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

    2015-12-15

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

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

    PubMed Central

    Sysol, Justin R.; Abbasi, Taimur; Patel, Amit R.; Lang, Roberto M.; Gupta, Akash; Garcia, Joe G. N.; Gordeuk, Victor R.; Machado, Roberto F.

    2016-01-01

    Background Diastolic dysfunction is common in sickle cell disease (SCD), and is associated with an increased risk of mortality. However, the molecular pathogenesis underlying this development is poorly understood. The aim of this study was to identify a gene expression profile that is associated with diastolic function in SCD, potentially elucidating molecular mechanisms behind diastolic dysfunction development. Methods Diastolic function was measured via echocardiography in 65 patients with SCD from two independent study populations. Gene expression microarray data was compared with diastolic function in both study cohorts. Candidate genes that associated in both analyses were tested for validation in a murine SCD model. Lastly, genotyping array data from the replication cohort was used to derive cis-expression quantitative trait loci (cis-eQTLs) and genetic associations within the candidate gene regions. Results Transcriptome data from both patient cohorts implicated 7 genes associated with diastolic function, and mouse SCD myocardial expression validated 3 of these genes. Genetic associations and eQTLs were detected in 2 of the 3 genes, FUCA2 and IL18. Conclusions FUCA2 and IL18 are associated with diastolic function in SCD patients, and may be involved in the pathogenesis of the disease. Genetic polymorphisms within the FUCA2 and IL18 gene regions are also associated with diastolic function in SCD, likely by affecting expression levels of the genes. PMID:27636371

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-08-22

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

  11. Meta-analysis of gene expression studies in endometrial cancer identifies gene expression profiles associated with aggressive disease and patient outcome

    PubMed Central

    O’Mara, Tracy A.; Zhao, Min; Spurdle, Amanda B.

    2016-01-01

    Although endometrioid endometrial cancer (EEC; comprising ~80% of all endometrial cancers diagnosed) is typically associated with favourable patient outcome, a significant portion (~20%) of women with this subtype will relapse. We hypothesised that gene expression predictors of the more aggressive non-endometrioid endometrial cancers (NEEC) could be used to predict EEC patients with poor prognosis. To explore this hypothesis, we performed meta-analysis of 12 gene expression microarray studies followed by validation using RNA-Seq data from The Cancer Genome Atlas (TCGA) and identified 1,253 genes differentially expressed between EEC and NEEC. Analysis found 121 genes were associated with poor outcome among EEC patients. Forward selection likelihood-based modelling identified a 9-gene signature associated with EEC outcome in our discovery RNA-Seq dataset which remained significant after adjustment for clinical covariates, but was not significant in a smaller RNA-Seq dataset. Our study demonstrates the value of employing meta-analysis to improve the power of gene expression microarray data, and highlight genes and molecular pathways of importance for endometrial cancer therapy. PMID:27830726

  12. Pooled sequencing of 531 genes in inflammatory bowel disease identifies an associated rare variant in BTNL2 and implicates other immune related genes.

    PubMed

    Prescott, Natalie J; Lehne, Benjamin; Stone, Kristina; Lee, James C; Taylor, Kirstin; Knight, Jo; Papouli, Efterpi; Mirza, Muddassar M; Simpson, Michael A; Spain, Sarah L; Lu, Grace; Fraternali, Franca; Bumpstead, Suzannah J; Gray, Emma; Amar, Ariella; Bye, Hannah; Green, Peter; Chung-Faye, Guy; Hayee, Bu'Hussain; Pollok, Richard; Satsangi, Jack; Parkes, Miles; Barrett, Jeffrey C; Mansfield, John C; Sanderson, Jeremy; Lewis, Cathryn M; Weale, Michael E; Schlitt, Thomas; Mathew, Christopher G

    2015-02-01

    The contribution of rare coding sequence variants to genetic susceptibility in complex disorders is an important but unresolved question. Most studies thus far have investigated a limited number of genes from regions which contain common disease associated variants. Here we investigate this in inflammatory bowel disease by sequencing the exons and proximal promoters of 531 genes selected from both genome-wide association studies and pathway analysis in pooled DNA panels from 474 cases of Crohn's disease and 480 controls. 80 variants with evidence of association in the sequencing experiment or with potential functional significance were selected for follow up genotyping in 6,507 IBD cases and 3,064 population controls. The top 5 disease associated variants were genotyped in an extension panel of 3,662 IBD cases and 3,639 controls, and tested for association in a combined analysis of 10,147 IBD cases and 7,008 controls. A rare coding variant p.G454C in the BTNL2 gene within the major histocompatibility complex was significantly associated with increased risk for IBD (p = 9.65x10-10, OR = 2.3[95% CI = 1.75-3.04]), but was independent of the known common associated CD and UC variants at this locus. Rare (<1%) and low frequency (1-5%) variants in 3 additional genes showed suggestive association (p<0.005) with either an increased risk (ARIH2 c.338-6C>T) or decreased risk (IL12B p.V298F, and NICN p.H191R) of IBD. These results provide additional insights into the involvement of the inhibition of T cell activation in the development of both sub-phenotypes of inflammatory bowel disease. We suggest that although rare coding variants may make a modest overall contribution to complex disease susceptibility, they can inform our understanding of the molecular pathways that contribute to pathogenesis.

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

    PubMed Central

    Zhao, M; Chen, L; Qu, H

    2016-01-01

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

  14. Gene Therapy for Autoimmune Disease.

    PubMed

    Shu, Shang-An; Wang, Jinjun; Tao, Mi-Hua; Leung, Patrick S C

    2015-10-01

    Advances in understanding the immunological and molecular basis of autoimmune diseases have made gene therapy a promising approach to treat the affected patients. Gene therapy for autoimmune diseases aims to regulate the levels of proinflammatory cytokines or molecules and the infiltration of lymphocytes to the effected sites through successful delivery and expression of therapeutic genes in appropriate cells. The ultimate goal of gene therapy is to restore and maintain the immune tolerance to the relevant autoantigens and improve clinical outcomes for patients. Here, we summarize the recent progress in identifying genes responsible for autoimmune diseases and present examples where gene therapy has been applied as treatments or prevention in autoimmune diseases both in animal models and the clinical trials. Discussion on the advantages and pitfalls of gene therapy strategies employed is provided. The intent of this review is to inspire further studies toward the development of new strategies for successful treatment of autoimmune diseases.

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

    PubMed Central

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

    2014-01-01

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

  16. Shared gene expression patterns in mesenchymal progenitors derived from lung and epidermis in pulmonary arterial hypertension: identifying key pathways in pulmonary vascular disease

    PubMed Central

    Gaskill, Christa; Marriott, Shennea; Pratap, Sidd; Menon, Swapna; Hedges, Lora K.; Fessel, Joshua P.; Kropski, Jonathan A.; Ames, DeWayne; Wheeler, Lisa; Loyd, James E.; Hemnes, Anna R.; Roop, Dennis R.; Klemm, Dwight J.; Austin, Eric D.

    2016-01-01

    Abstract Rapid access to lung-derived cells from stable subjects is a major challenge in the pulmonary hypertension field, given the relative contraindication of lung biopsy. In these studies, we sought to demonstrate the importance of evaluating a cell type that actively participates in disease processes, as well as the potential to translate these findings to vascular beds in other nonlung tissues, in this instance perivascular skin mesenchymal cells (MCs). We utilized posttransplant or autopsy lung explant–derived cells (ABCG2-expressing mesenchymal progenitor cells [MPCs], fibroblasts) and skin-derived MCs to test the hypothesis that perivascular ABCG2 MPCs derived from pulmonary arterial hypertension (PAH) patient lung and skin would express a gene profile reflective of ongoing vascular dysfunction. By analyzing the genetic signatures and pathways associated with abnormal ABCG2 lung MPC phenotypes during PAH and evaluating them in lung- and skin-derived MCs, we have identified potential predictor genes for detection of PAH as well as a targetable mechanism to restore MPCs and microvascular function. These studies are the first to explore the utility of expanding the study of ABCG2 MPC regulation of the pulmonary microvasculature to the epidermis, in order to identify potential markers for adult lung vascular disease, such as PAH. PMID:28090290

  17. Shared gene expression patterns in mesenchymal progenitors derived from lung and epidermis in pulmonary arterial hypertension: identifying key pathways in pulmonary vascular disease.

    PubMed

    Gaskill, Christa; Marriott, Shennea; Pratap, Sidd; Menon, Swapna; Hedges, Lora K; Fessel, Joshua P; Kropski, Jonathan A; Ames, DeWayne; Wheeler, Lisa; Loyd, James E; Hemnes, Anna R; Roop, Dennis R; Klemm, Dwight J; Austin, Eric D; Majka, Susan M

    2016-12-01

    Rapid access to lung-derived cells from stable subjects is a major challenge in the pulmonary hypertension field, given the relative contraindication of lung biopsy. In these studies, we sought to demonstrate the importance of evaluating a cell type that actively participates in disease processes, as well as the potential to translate these findings to vascular beds in other nonlung tissues, in this instance perivascular skin mesenchymal cells (MCs). We utilized posttransplant or autopsy lung explant-derived cells (ABCG2-expressing mesenchymal progenitor cells [MPCs], fibroblasts) and skin-derived MCs to test the hypothesis that perivascular ABCG2 MPCs derived from pulmonary arterial hypertension (PAH) patient lung and skin would express a gene profile reflective of ongoing vascular dysfunction. By analyzing the genetic signatures and pathways associated with abnormal ABCG2 lung MPC phenotypes during PAH and evaluating them in lung- and skin-derived MCs, we have identified potential predictor genes for detection of PAH as well as a targetable mechanism to restore MPCs and microvascular function. These studies are the first to explore the utility of expanding the study of ABCG2 MPC regulation of the pulmonary microvasculature to the epidermis, in order to identify potential markers for adult lung vascular disease, such as PAH.

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

    PubMed

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

    2014-09-15

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

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

    PubMed Central

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

    2014-01-01

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

  20. Network Analysis Identifies Disease-Specific Pathways for Parkinson's Disease.

    PubMed

    Monti, Chiara; Colugnat, Ilaria; Lopiano, Leonardo; Chiò, Adriano; Alberio, Tiziana

    2016-12-21

    Neurodegenerative diseases are characterized by the progressive loss of specific neurons in selected regions of the central nervous system. The main clinical manifestation (movement disorders, cognitive impairment, and/or psychiatric disturbances) depends on the neuron population being primarily affected. Parkinson's disease is a common movement disorder, whose etiology remains mostly unknown. Progressive loss of dopaminergic neurons in the substantia nigra causes an impairment of the motor control. Some of the pathogenetic mechanisms causing the progressive deterioration of these neurons are not specific for Parkinson's disease but are shared by other neurodegenerative diseases, like Alzheimer's disease and amyotrophic lateral sclerosis. Here, we performed a meta-analysis of the literature of all the quantitative proteomic investigations of neuronal alterations in different models of Parkinson's disease, Alzheimer's disease, and amyotrophic lateral sclerosis to distinguish between general and Parkinson's disease-specific pattern of neurodegeneration. Then, we merged proteomics data with genetics information from the DisGeNET database. The comparison of gene and protein information allowed us to identify 25 proteins involved uniquely in Parkinson's disease and we verified the alteration of one of them, i.e., transaldolase 1 (TALDO1), in the substantia nigra of 5 patients. By using open-source bioinformatics tools, we identified the biological processes specifically affected in Parkinson's disease, i.e., proteolysis, mitochondrion organization, and mitophagy. Eventually, we highlighted four cellular component complexes mostly involved in the pathogenesis: the proteasome complex, the protein phosphatase 2A, the chaperonins CCT complex, and the complex III of the respiratory chain.

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

    PubMed Central

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

    2015-01-01

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

  2. Parkinson's disease: gene therapies.

    PubMed

    Coune, Philippe G; Schneider, Bernard L; Aebischer, Patrick

    2012-04-01

    With the recent development of effective gene delivery systems, gene therapy for the central nervous system is finding novel applications. Here, we review existing viral vectors and discuss gene therapy strategies that have been proposed for Parkinson's disease. To date, most of the clinical trials were based on viral vectors to deliver therapeutic transgenes to neurons within the basal ganglia. Initial trials used genes to relieve the major motor symptoms caused by nigrostriatal degeneration. Although these new genetic approaches still need to prove more effective than existing symptomatic treatments, there is a need for disease-modifying strategies. The investigation of the genetic factors implicated in Parkinson's disease is providing precious insights in disease pathology that, combined with innovative gene delivery systems, will hopefully offer novel opportunities for gene therapy interventions to slow down, or even halt disease progression.

  3. Midbrain Gene Screening Identifies a New Mesoaccumbal Glutamatergic Pathway and a Marker for Dopamine Cells Neuroprotected in Parkinson’s Disease

    PubMed Central

    Viereckel, Thomas; Dumas, Sylvie; Smith-Anttila, Casey J. A.; Vlcek, Bianca; Bimpisidis, Zisis; Lagerström, Malin C.; Konradsson-Geuken, Åsa; Wallén-Mackenzie, Åsa

    2016-01-01

    The ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) of the midbrain are associated with Parkinson’s disease (PD), schizophrenia, mood disorders and addiction. Based on the recently unraveled heterogeneity within the VTA and SNc, where glutamate, GABA and co-releasing neurons have been found to co-exist with the classical dopamine neurons, there is a compelling need for identification of gene expression patterns that represent this heterogeneity and that are of value for development of human therapies. Here, several unique gene expression patterns were identified in the mouse midbrain of which NeuroD6 and Grp were expressed within different dopaminergic subpopulations of the VTA, and TrpV1 within a small heterogeneous population. Optogenetics-coupled in vivo amperometry revealed a previously unknown glutamatergic mesoaccumbal pathway characterized by TrpV1-Cre-expression. Human GRP was strongly detected in non-melanized dopaminergic neurons within the SNc of both control and PD brains, suggesting GRP as a marker for neuroprotected neurons in PD. This study thus unravels markers for distinct subpopulations of neurons within the mouse and human midbrain, defines unique anatomical subregions within the VTA and exposes an entirely new glutamatergic pathway. Finally, both TRPV1 and GRP are implied in midbrain physiology of importance to neurological and neuropsychiatric disorders. PMID:27762319

  4. Identifying potential cancer driver genes by genomic data integration

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  5. Differentially Coexpressed Disease Gene Identification Based on Gene Coexpression Network.

    PubMed

    Jiang, Xue; Zhang, Han; Quan, Xiongwen

    2016-01-01

    Screening disease-related genes by analyzing gene expression data has become a popular theme. Traditional disease-related gene selection methods always focus on identifying differentially expressed gene between case samples and a control group. These traditional methods may not fully consider the changes of interactions between genes at different cell states and the dynamic processes of gene expression levels during the disease progression. However, in order to understand the mechanism of disease, it is important to explore the dynamic changes of interactions between genes in biological networks at different cell states. In this study, we designed a novel framework to identify disease-related genes and developed a differentially coexpressed disease-related gene identification method based on gene coexpression network (DCGN) to screen differentially coexpressed genes. We firstly constructed phase-specific gene coexpression network using time-series gene expression data and defined the conception of differential coexpression of genes in coexpression network. Then, we designed two metrics to measure the value of gene differential coexpression according to the change of local topological structures between different phase-specific networks. Finally, we conducted meta-analysis of gene differential coexpression based on the rank-product method. Experimental results demonstrated the feasibility and effectiveness of DCGN and the superior performance of DCGN over other popular disease-related gene selection methods through real-world gene expression data sets.

  6. Differentially Coexpressed Disease Gene Identification Based on Gene Coexpression Network

    PubMed Central

    Quan, Xiongwen

    2016-01-01

    Screening disease-related genes by analyzing gene expression data has become a popular theme. Traditional disease-related gene selection methods always focus on identifying differentially expressed gene between case samples and a control group. These traditional methods may not fully consider the changes of interactions between genes at different cell states and the dynamic processes of gene expression levels during the disease progression. However, in order to understand the mechanism of disease, it is important to explore the dynamic changes of interactions between genes in biological networks at different cell states. In this study, we designed a novel framework to identify disease-related genes and developed a differentially coexpressed disease-related gene identification method based on gene coexpression network (DCGN) to screen differentially coexpressed genes. We firstly constructed phase-specific gene coexpression network using time-series gene expression data and defined the conception of differential coexpression of genes in coexpression network. Then, we designed two metrics to measure the value of gene differential coexpression according to the change of local topological structures between different phase-specific networks. Finally, we conducted meta-analysis of gene differential coexpression based on the rank-product method. Experimental results demonstrated the feasibility and effectiveness of DCGN and the superior performance of DCGN over other popular disease-related gene selection methods through real-world gene expression data sets. PMID:28042568

  7. Identifying essential genes in Arabidopsis thaliana.

    PubMed

    Meinke, David; Muralla, Rosanna; Sweeney, Colleen; Dickerman, Allan

    2008-09-01

    Eight years after publication of the Arabidopsis genome sequence and two years before completing the first phase of an international effort to characterize the function of every Arabidopsis gene, plant biologists remain unable to provide a definitive answer to the following basic question: what is the minimal gene set required for normal growth and development? The purpose of this review is to summarize different strategies employed to identify essential genes in Arabidopsis, an important component of the minimal gene set in plants, to present an overview of the datasets and specific genes identified to date, and to discuss the prospects for future saturation of this important class of genes. The long-term goal of this collaborative effort is to facilitate basic research in plant biology and complement ongoing research with other model organisms.

  8. Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

    PubMed

    Wolen, Aaron R; Miles, Michael F

    2012-01-01

    For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

  9. Identifying genes related with rheumatoid arthritis via system biology analysis.

    PubMed

    Liu, Tao; Lin, Xinmei; Yu, Hongjian

    2015-10-15

    Rheumatoid arthritis (RA) is a chronic, inflammatory joint disease that mainly attacks synovial joints. However, the underlying systematic relationship among different genes and biological processes involved in the pathogenesis are still unclear. By analyzing and comparing the transcriptional profiles from RA, OA (osteoarthritis) patients as well as ND (normal donors) with bioinformatics methods, we tend to uncover the potential molecular networks and critical genes which play important roles in RA and OA development. Initially, hierarchical clustering was performed to classify the overall transcriptional profiles. Differentially expressed genes (DEGs) between ND and RA and OA patients were identified. Furthermore, PPI networks were constructed, functional modules were extracted, and functional annotation was also applied. Our functional analysis identifies 22 biological processes and 2 KEGG pathways enriched in the commonly-regulated gene set. However, we found that number of set of genes differentially expressed genes only between RA and ND reaches up to 244, indicating this gene set may specifically accounts for processing to disease of RA. Additionally, 142 biological processes and 19 KEGG pathways are over-represented by these 244 genes. Meanwhile, although another 21 genes were differentially expressed only in OA and ND, no biological process nor pathway is over-represented by them.

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

    PubMed Central

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

    2016-01-01

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

  11. Systems biology approaches to identify developmental bases for lung diseases.

    PubMed

    Bhattacharya, Soumyaroop; Mariani, Thomas J

    2013-04-01

    A greater understanding of the regulatory processes contributing to lung development could be helpful to identify strategies to ameliorate morbidity and mortality in premature infants and to identify individuals at risk for congenital and/or chronic lung diseases. Over the past decade, genomics technologies have enabled the production of rich gene expression databases providing information for all genes across developmental time or in diseased tissue. These data sets facilitate systems biology approaches for identifying underlying biological modules and programs contributing to the complex processes of normal development and those that may be associated with disease states. The next decade will undoubtedly see rapid and significant advances in redefining both lung development and disease at the systems level.

  12. 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

  13. Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes

    PubMed Central

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

    2016-01-01

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

  14. Analysis of gene expression profile identifies potential biomarkers for atherosclerosis

    PubMed Central

    Liu, Luran; Liu, Yan; Liu, Chang; Zhang, Zhuobo; Du, Yaojun; Zhao, Hao

    2016-01-01

    The present study aimed to identify potential biomarkers for atherosclerosis via analysis of gene expression profiles. The microarray dataset no. GSE20129 was downloaded from the Gene Expression Omnibus database. A total of 118 samples from the peripheral blood of female patients was used, including 47 atherosclerotic and 71 non-atherosclerotic patients. The differentially expressed genes (DEGs) in the atherosclerosis samples were identified using the Limma package. Gene ontology term and Kyoto Encyclopedia of Genes and Genomes pathway analyses for DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery tool. The recursive feature elimination (RFE) algorithm was applied for feature selection via iterative classification, and support vector machine classifier was used for the validation of prediction accuracy. A total of 430 DEGs in the atherosclerosis samples were identified, including 149 up- and 281 downregulated genes. Subsequently, the RFE algorithm was used to identify 11 biomarkers, whose receiver operating characteristic curves had an area under curve of 0.92, indicating that the identified 11 biomarkers were representative. The present study indicated that APH1B, JAM3, FBLN2, CSAD and PSTPIP2 may have important roles in the progression of atherosclerosis in females and may be potential biomarkers for early diagnosis and prognosis as well as treatment targets for this disease. PMID:27573188

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  17. Genotype analysis identifies the cause of the "royal disease".

    PubMed

    Rogaev, Evgeny I; Grigorenko, Anastasia P; Faskhutdinova, Gulnaz; Kittler, Ellen L W; Moliaka, Yuri K

    2009-11-06

    The "royal disease," a blood disorder transmitted from Queen Victoria to European royal families, is a striking example of X-linked recessive inheritance. Although the disease is widely recognized to be a form of the blood clotting disorder hemophilia, its molecular basis has never been identified, and the royal disease is now likely extinct. We identified the likely disease-causing mutation by applying genomic methodologies (multiplex target amplification and massively parallel sequencing) to historical specimens from the Romanov branch of the royal family. The mutation occurs in F9, a gene on the X chromosome that encodes blood coagulation factor IX, and is predicted to alter RNA splicing and to lead to production of a truncated form of factor IX. Thus, the royal disease is the severe form of hemophilia, also known as hemophilia B or Christmas disease.

  18. Gene mutations in Cushing's disease

    PubMed Central

    Xiong, Qi; Ge, Wei

    2016-01-01

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

  19. Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

    PubMed Central

    Jiang, Bing; Li, Shuwen; Jiang, Zhi

    2017-01-01

    Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding. PMID:28232943

  20. Identifying genes of gene regulatory networks using formal concept analysis.

    PubMed

    Gebert, Jutta; Motameny, Susanne; Faigle, Ulrich; Forst, Christian V; Schrader, Rainer

    2008-03-01

    In order to understand the behavior of a gene regulatory network, it is essential to know the genes that belong to it. Identifying the correct members (e.g., in order to build a model) is a difficult task even for small subnetworks. Usually only few members of a network are known and one needs to guess the missing members based on experience or informed speculation. It is beneficial if one can additionally rely on experimental data to support this guess. In this work we present a new method based on formal concept analysis to detect unknown members of a gene regulatory network from gene expression time series data. We show that formal concept analysis is able to find a list of candidate genes for inclusion into a partially known basic network. This list can then be reduced by a statistical analysis so that the resulting genes interact strongly with the basic network and therefore should be included when modeling the network. The method has been applied to the DNA repair system of Mycobacterium tuberculosis. In this application, our method produces comparable results to an already existing method of component selection while it is applicable to a broader range of problems.

  1. Chapter 15: Disease Gene Prioritization

    PubMed Central

    Bromberg, Yana

    2013-01-01

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

  2. Network Topology Reveals Key Cardiovascular Disease Genes

    PubMed Central

    Stojković, Neda; Radak, Djordje; Pržulj, Nataša

    2013-01-01

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

  3. Advances in identifying beryllium sensitization and disease.

    PubMed

    Middleton, Dan; Kowalski, Peter

    2010-01-01

    Beryllium is a lightweight metal with unique qualities related to stiffness, corrosion resistance, and conductivity. While there are many useful applications, researchers in the 1930s and 1940s linked beryllium exposure to a progressive occupational lung disease. Acute beryllium disease is a pulmonary irritant response to high exposure levels, whereas chronic beryllium disease (CBD) typically results from a hypersensitivity response to lower exposure levels. A blood test, the beryllium lymphocyte proliferation test (BeLPT), was an important advance in identifying individuals who are sensitized to beryllium (BeS) and thus at risk for developing CBD. While there is no true "gold standard" for BeS, basic epidemiologic concepts have been used to advance our understanding of the different screening algorithms.

  4. Disease gene identification strategies for exome sequencing

    PubMed Central

    Gilissen, Christian; Hoischen, Alexander; Brunner, Han G; Veltman, Joris A

    2012-01-01

    Next generation sequencing can be used to search for Mendelian disease genes in an unbiased manner by sequencing the entire protein-coding sequence, known as the exome, or even the entire human genome. Identifying the pathogenic mutation amongst thousands to millions of genomic variants is a major challenge, and novel variant prioritization strategies are required. The choice of these strategies depends on the availability of well-phenotyped patients and family members, the mode of inheritance, the severity of the disease and its population frequency. In this review, we discuss the current strategies for Mendelian disease gene identification by exome resequencing. We conclude that exome strategies are successful and identify new Mendelian disease genes in approximately 60% of the projects. Improvements in bioinformatics as well as in sequencing technology will likely increase the success rate even further. Exome sequencing is likely to become the most commonly used tool for Mendelian disease gene identification for the coming years. PMID:22258526

  5. Pedigree and BRCA gene analysis in breast cancer patients to identify hereditary breast and ovarian cancer syndrome to prevent morbidity and mortality of disease in Indian population.

    PubMed

    Darooei, Mina; Poornima, Subhadra; Salma, Bibi Umae; Iyer, Gayatri R; Pujar, Akhilesh N; Annapurna, Srirambhatla; Shah, Ashwin; Maddali, Srinivas; Hasan, Qurratulain

    2017-02-01

    Global burden of breast cancer is expected to increase to >2 million new cases every year by 2030 and 10% of these are likely to have hereditary breast and ovarian cancer syndrome. Identifying these individuals by pedigree and BRCA1/2 mutation analyses will enable us to offer targeted mutation testing and appropriate counseling. This study from a tertiary care hospital showed that of the 127 breast cancer patients on treatment during 2014-2015, 24 of them fulfilled the criteria of hereditary breast and ovarian cancer syndrome after detailed verbal autopsy and pedigree analysis, and BRCA1 and 2 next-generation sequencing done after pre-test counseling revealed mutations in 13 cases (54%), these included 9 BRCA1 mutations (69%) and 4 BRCA2 mutation (31%). Subsequent post-test counseling recommended targeted mutation analysis for 64 high-risk members in these 13 families with pathogenic mutations, which will help in surveillance for early detection, appropriate management, and prevention of the disease by decreasing the burden to both family and nation. Results from this preliminary study highlight the importance of genetic counseling, pedigree analysis, and genetic testing. It can be recommended that all oncology units should have a genetic counseling service for providing appropriate support to oncologists, patients, and families to prevent unnecessary testing; however, breast cancer screening program is incomplete without evaluating for hereditary breast and ovarian cancer syndrome.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed Central

    Perry, George; Ray, Monika

    2014-01-01

    In late-onset Alzheimer's disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with low topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases. PMID:25147748

  8. Efficient Strategy to Identify Gene-Gene Interactions and Its Application to Type 2 Diabetes

    PubMed Central

    Li, Donghe

    2016-01-01

    Over the past decade, the detection of gene-gene interactions has become more and more popular in the field of genome-wide association studies (GWASs). The goal of the GWAS is to identify genetic susceptibility to complex diseases by assaying and analyzing hundreds of thousands of single-nucleotide polymorphisms. However, such tests are computationally demanding and methodologically challenging. Recently, a simple but powerful method, named “BOolean Operation-based Screening and Testing” (BOOST), was proposed for genome-wide gene-gene interaction analyses. BOOST was designed with a Boolean representation of genotype data and is approximately equivalent to the log-linear model. It is extremely fast, and genome-wide gene-gene interaction analyses can be completed within a few hours. However, BOOST can not adjust for covariate effects, and its type-1 error control is not correct. Thus, we considered two-step approaches for gene-gene interaction analyses. First, we selected gene-gene interactions with BOOST and applied logistic regression with covariate adjustments to select gene-gene interactions. We applied the two-step approach to type 2 diabetes (T2D) in the Korea Association Resource (KARE) cohort and identified some promising pairs of single-nucleotide polymorphisms associated with T2D. PMID:28154506

  9. Gene Therapy for Skin Diseases

    PubMed Central

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

    2014-01-01

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

  10. Gene Therapy for Metabolic Diseases

    PubMed Central

    Chandler, Randy J.; Venditti, Charles P.

    2016-01-01

    SUMMARY Gene therapy has recently shown great promise as an effective treatment for a number of metabolic diseases caused by genetic defects in both animal models and human clinical trials. Most of the current success has been achieved using a viral mediated gene addition approach, but gene-editing technology has progressed rapidly and gene modification is being actively pursued in clinical trials. This review focuses on viral mediated gene addition approaches, because most of the current clinical trials utilize this approach to treat metabolic diseases. PMID:27853673

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

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

    2014-01-01

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

  14. A Metastatic Mouse Model Identifies Genes That Regulate Neuroblastoma Metastasis.

    PubMed

    Seong, Bo Kyung A; Fathers, Kelly E; Hallett, Robin; Yung, Christina K; Stein, Lincoln D; Mouaaz, Samar; Kee, Lynn; Hawkins, Cynthia E; Irwin, Meredith S; Kaplan, David R

    2017-02-01

    Metastatic relapse is the major cause of death in pediatric neuroblastoma, where there remains a lack of therapies to target this stage of disease. To understand the molecular mechanisms mediating neuroblastoma metastasis, we developed a mouse model using intracardiac injection and in vivo selection to isolate malignant cell subpopulations with a higher propensity for metastasis to bone and the central nervous system. Gene expression profiling revealed primary and metastatic cells as two distinct cell populations defined by differential expression of 412 genes and of multiple pathways, including CADM1, SPHK1, and YAP/TAZ, whose expression independently predicted survival. In the metastatic subpopulations, a gene signature was defined (MET-75) that predicted survival of neuroblastoma patients with metastatic disease. Mechanistic investigations demonstrated causal roles for CADM1, SPHK1, and YAP/TAZ in mediating metastatic phenotypes in vitro and in vivo Notably, pharmacologic targeting of SPHK1 or YAP/TAZ was sufficient to inhibit neuroblastoma metastasis in vivo Overall, we identify gene expression signatures and candidate therapeutics that could improve the treatment of metastatic neuroblastoma. Cancer Res; 77(3); 696-706. ©2017 AACR.

  15. NIH Researchers Identify OCD Risk Gene

    MedlinePlus

    ... gene (SERT), site of action for the selective serotonin reuptake inhibitors (SSRIs) that are today's mainstay medications for OCD, other anxiety disorders and depression. "Improved knowledge of SERT's role in OCD raises ...

  16. 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).

  17. Cancer genomics identifies disrupted epigenetic genes.

    PubMed

    Simó-Riudalbas, Laia; Esteller, Manel

    2014-06-01

    Latest advances in genome technologies have greatly advanced the discovery of epigenetic genes altered in cancer. The initial single candidate gene approaches have been coupled with newly developed epigenomic platforms to hasten the convergence of scientific discoveries and translational applications. Here, we present an overview of the evolution of cancer epigenomics and an updated catalog of disruptions in epigenetic pathways, whose misregulation can culminate in cancer. The creation of these basic mutational catalogs in cell lines and primary tumors will provide us with enough knowledge to move diagnostics and therapy from the laboratory bench to the bedside.

  18. GenePANDA—a novel network-based gene prioritizing tool for complex diseases

    PubMed Central

    Yin, Tianshu; Chen, Shu; Wu, Xiaohui; Tian, Weidong

    2017-01-01

    Here we describe GenePANDA, a novel network-based tool for prioritizing candidate disease genes. GenePANDA assesses whether a gene is likely a candidate disease gene based on its relative distance to known disease genes in a functional association network. A unique feature of GenePANDA is the introduction of adjusted network distance derived by normalizing the raw network distance between two genes with their respective mean raw network distance to all other genes in the network. The use of adjusted network distance significantly improves GenePANDA’s performance on prioritizing complex disease genes. GenePANDA achieves superior performance over five previously published algorithms for prioritizing disease genes. Finally, GenePANDA can assist in prioritizing functionally important SNPs identified by GWAS. PMID:28252032

  19. GeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profiles

    PubMed Central

    Antanaviciute, Agne; Daly, Catherine; Crinnion, Laura A.; Markham, Alexander F.; Watson, Christopher M.; Bonthron, David T.; Carr, Ian M.

    2015-01-01

    Motivation: In attempts to determine the genetic causes of human disease, researchers are often faced with a large number of candidate genes. Linkage studies can point to a genomic region containing hundreds of genes, while the high-throughput sequencing approach will often identify a great number of non-synonymous genetic variants. Since systematic experimental verification of each such candidate gene is not feasible, a method is needed to decide which genes are worth investigating further. Computational gene prioritization presents itself as a solution to this problem, systematically analyzing and sorting each gene from the most to least likely to be the disease-causing gene, in a fraction of the time it would take a researcher to perform such queries manually. Results: Here, we present Gene TIssue Expression Ranker (GeneTIER), a new web-based application for candidate gene prioritization. GeneTIER replaces knowledge-based inference traditionally used in candidate disease gene prioritization applications with experimental data from tissue-specific gene expression datasets and thus largely overcomes the bias toward the better characterized genes/diseases that commonly afflict other methods. We show that our approach is capable of accurate candidate gene prioritization and illustrate its strengths and weaknesses using case study examples. Availability and Implementation: Freely available on the web at http://dna.leeds.ac.uk/GeneTIER/. Contact: umaan@leeds.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25861967

  20. Identifying driver genes in cancer by triangulating gene expression, gene location, and survival data.

    PubMed

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

    2014-01-01

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

  1. BCIP: a gene-centered platform for identifying potential regulatory genes in breast cancer

    PubMed Central

    Wu, Jiaqi; Hu, Shuofeng; Chen, Yaowen; Li, Zongcheng; Zhang, Jian; Yuan, Hanyu; Shi, Qiang; Shao, Ningsheng; Ying, Xiaomin

    2017-01-01

    Breast cancer is a disease with high heterogeneity. Many issues on tumorigenesis and progression are still elusive. It is critical to identify genes that play important roles in the progression of tumors, especially for tumors with poor prognosis such as basal-like breast cancer and tumors in very young women. To facilitate the identification of potential regulatory or driver genes, we present the Breast Cancer Integrative Platform (BCIP, http://omics.bmi.ac.cn/bcancer/). BCIP maintains multi-omics data selected with strict quality control and processed with uniform normalization methods, including gene expression profiles from 9,005 tumor and 376 normal tissue samples, copy number variation information from 3,035 tumor samples, microRNA-target interactions, co-expressed genes, KEGG pathways, and mammary tissue-specific gene functional networks. This platform provides a user-friendly interface integrating comprehensive and flexible analysis tools on differential gene expression, copy number variation, and survival analysis. The prominent characteristic of BCIP is that users can perform analysis by customizing subgroups with single or combined clinical features, including subtypes, histological grades, pathologic stages, metastasis status, lymph node status, ER/PR/HER2 status, TP53 mutation status, menopause status, age, tumor size, therapy responses, and prognosis. BCIP will help to identify regulatory or driver genes and candidate biomarkers for further research in breast cancer. PMID:28327601

  2. Renal diseases as targets of gene therapy.

    PubMed

    Phillips, Brett; Giannoukakis, Nick; Trucco, Massimo

    2008-01-01

    A number of renal pathologies exist that have seen little or no improvement in treatment methods over the past 20 years. These pathologies include acute and chronic kidney diseases as well as posttransplant kidney survival and host rejection. A novel approach to treatment methodology may provide new insight to further progress our understanding of the disease and overall patient outcome. Recent advances in human genomics and gene delivery systems have opened the door to possible cures through the direct modulation of cellular genes. These techniques of gene therapy have not been extensively applied to renal pathologies, but clinical trials on other organ systems and kidney research in animal models hold promise. Techniques have employed viral and nonviral vectors to deliver gene modulating compounds directly into the cell. These vectors have the capability to replace defective alleles, express novel genes, or suppress the expression of pathogenic genes in a wide variety of kidney cell types. Focus has also been placed on ex vivo modification of kidney tissue to promote allograft survival and limit the resulting immune response to the transplanted organ. This could prove a valuable alternative to current immunosuppressive drugs and their deleterious effects on patients. While continued research and clinical trials are needed to identify a robust system of gene delivery, gene therapy techniques have great potential to treat kidney disease at the cellular level and improve patient quality of life.

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

    PubMed

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

    2012-08-01

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

  4. Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors.

    PubMed

    Bii, Victor M; Trobridge, Grant D

    2016-10-25

    Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types.

  5. Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

    PubMed Central

    Bii, Victor M.; Trobridge, Grant D.

    2016-01-01

    Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types. PMID:27792127

  6. Identifying and Analyzing Novel Epilepsy-Related Genes Using Random Walk with Restart Algorithm

    PubMed Central

    Guo, Wei; Shang, Dong-Mei; Cao, Jing-Hui; Feng, Kaiyan; Wang, ShaoPeng

    2017-01-01

    As a pathological condition, epilepsy is caused by abnormal neuronal discharge in brain which will temporarily disrupt the cerebral functions. Epilepsy is a chronic disease which occurs in all ages and would seriously affect patients' personal lives. Thus, it is highly required to develop effective medicines or instruments to treat the disease. Identifying epilepsy-related genes is essential in order to understand and treat the disease because the corresponding proteins encoded by the epilepsy-related genes are candidates of the potential drug targets. In this study, a pioneering computational workflow was proposed to predict novel epilepsy-related genes using the random walk with restart (RWR) algorithm. As reported in the literature RWR algorithm often produces a number of false positive genes, and in this study a permutation test and functional association tests were implemented to filter the genes identified by RWR algorithm, which greatly reduce the number of suspected genes and result in only thirty-three novel epilepsy genes. Finally, these novel genes were analyzed based upon some recently published literatures. Our findings implicate that all novel genes were closely related to epilepsy. It is believed that the proposed workflow can also be applied to identify genes related to other diseases and deepen our understanding of the mechanisms of these diseases. PMID:28255556

  7. Disease Resistance Gene Analogs (RGAs) in Plants

    PubMed Central

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

    2015-01-01

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

  8. A predictive approach to identify genes differentially expressed

    NASA Astrophysics Data System (ADS)

    Saraiva, Erlandson F.; Louzada, Francisco; Milan, Luís A.; Meira, Silvana; Cobre, Juliana

    2012-10-01

    The main objective of gene expression data analysis is to identify genes that present significant changes in expression levels between a treatment and a control biological condition. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating credibility intervals from predictive densities which are constructed using sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained indicate that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a publicly available data set on Escherichia coli bacteria.

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

    PubMed

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

    2011-12-09

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

  10. Identifying gene-environment and gene-gene interactions using a progressive penalization approach.

    PubMed

    Zhu, Ruoqing; Zhao, Hongyu; Ma, Shuangge

    2014-05-01

    In genomic studies, identifying important gene-environment and gene-gene interactions is a challenging problem. In this study, we adopt the statistical modeling approach, where interactions are represented by product terms in regression models. For the identification of important interactions, we adopt penalization, which has been used in many genomic studies. Straightforward application of penalization does not respect the "main effect, interaction" hierarchical structure. A few recently proposed methods respect this structure by applying constrained penalization. However, they demand very complicated computational algorithms and can only accommodate a small number of genomic measurements. We propose a computationally fast penalization method that can identify important gene-environment and gene-gene interactions and respect a strong hierarchical structure. The method takes a stagewise approach and progressively expands its optimization domain to account for possible hierarchical interactions. It is applicable to multiple data types and models. A coordinate descent method is utilized to produce the entire regularized solution path. Simulation study demonstrates the superior performance of the proposed method. We analyze a lung cancer prognosis study with gene expression measurements and identify important gene-environment interactions.

  11. Patching genes to fight disease

    SciTech Connect

    Holzman, D.

    1990-09-03

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

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

    PubMed Central

    Cheng, Liang; Zhang, Shuo; Hu, Yang

    2016-01-01

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

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

    PubMed

    Li, Jian; Li, Wenwen; Zhou, Jun

    2015-04-01

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

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

    PubMed Central

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

    2015-01-01

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

  15. GENE EXPRESSION PROFILING TO IDENTIFY BIOMARKERS OF REPRODUCTIVE TOXICITY

    EPA Science Inventory

    SOT 2005 SESSION ABSTRACT

    GENE EXPRESSION PROFILING TO IDENTIFY BIOMARKERS OF REPRODUCTIVE TOXICITY

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

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

    PubMed

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

    2015-10-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. A Gene Recommender Algorithm to Identify Coexpressed Genes in C. elegans

    PubMed Central

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

    2003-01-01

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

  20. ENU mutagenesis in mice identifies candidate genes for hypogonadism.

    PubMed

    Weiss, Jeffrey; Hurley, Lisa A; Harris, Rebecca M; Finlayson, Courtney; Tong, Minghan; Fisher, Lisa A; Moran, Jennifer L; Beier, David R; Mason, Christopher; Jameson, J Larry

    2012-06-01

    Genome-wide mutagenesis was performed in mice to identify candidate genes for male infertility, for which the predominant causes remain idiopathic. Mice were mutagenized using N-ethyl-N-nitrosourea (ENU), bred, and screened for phenotypes associated with the male urogenital system. Fifteen heritable lines were isolated and chromosomal loci were assigned using low-density genome-wide SNP arrays. Ten of the 15 lines were pursued further using higher-resolution SNP analysis to narrow the candidate gene regions. Exon sequencing of candidate genes identified mutations in mice with cystic kidneys (Bicc1), cryptorchidism (Rxfp2), restricted germ cell deficiency (Plk4), and severe germ cell deficiency (Prdm9). In two other lines with severe hypogonadism, candidate sequencing failed to identify mutations, suggesting defects in genes with previously undocumented roles in gonadal function. These genomic intervals were sequenced in their entirety and a candidate mutation was identified in SnrpE in one of the two lines. The line harboring the SnrpE variant retains substantial spermatogenesis despite small testis size, an unusual phenotype. In addition to the reproductive defects, heritable phenotypes were observed in mice with ataxia (Myo5a), tremors (Pmp22), growth retardation (unknown gene), and hydrocephalus (unknown gene). These results demonstrate that the ENU screen is an effective tool for identifying potential causes of male infertility.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2013-11-01

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

  3. Genes and Disease: Prader-Willi Syndrome

    MedlinePlus

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

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

    PubMed Central

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

    2015-01-01

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

  5. 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.

  6. Network analysis reveals crosstalk between autophagy genes and disease genes

    PubMed Central

    Wang, Ji-Ye; Yao, Wei-Xuan; Wang, Yun; Fan, Yi-lei; Wu, Jian-Bing

    2017-01-01

    Autophagy is a protective and life-sustaining process in which cytoplasmic components are packaged into double-membrane vesicles and targeted to lysosomes for degradation. Accumulating evidence supports that autophagy is associated with several pathological conditions. However, research on the functional cross-links between autophagy and disease genes remains in its early stages. In this study, we constructed a disease-autophagy network (DAN) by integrating known disease genes, known autophagy genes and protein-protein interactions (PPI). Dissecting the topological properties of the DAN suggested that nodes that both autophagy and disease genes (inter-genes), are topologically important in the DAN structure. Next, a core network from the DAN was extracted to analyze the functional links between disease and autophagy genes. The genes in the core network were significantly enriched in multiple disease-related pathways, suggesting that autophagy genes may function in various disease processes. Of 17 disease classes, 11 significantly overlapped with autophagy genes, including cancer diseases, metabolic diseases and hematological diseases, a finding that is supported by the literatures. We also found that autophagy genes have a bridging role in the connections between pairs of disease classes. Altogether, our study provides a better understanding of the molecular mechanisms underlying human diseases and the autophagy process. PMID:28295050

  7. 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

  8. A novel approach for identifying causal models of complex diseases from family data.

    PubMed

    Park, Leeyoung; Kim, Ju H

    2015-04-01

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

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

    PubMed Central

    Lin, Peng-Lin; Yu, Ya-Wen

    2016-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  11. Identifying gene regulatory network rewiring using latent differential graphical models

    PubMed Central

    Tian, Dechao; Gu, Quanquan; Ma, Jian

    2016-01-01

    Gene regulatory networks (GRNs) are highly dynamic among different tissue types. Identifying tissue-specific gene regulation is critically important to understand gene function in a particular cellular context. Graphical models have been used to estimate GRN from gene expression data to distinguish direct interactions from indirect associations. However, most existing methods estimate GRN for a specific cell/tissue type or in a tissue-naive way, or do not specifically focus on network rewiring between different tissues. Here, we describe a new method called Latent Differential Graphical Model (LDGM). The motivation of our method is to estimate the differential network between two tissue types directly without inferring the network for individual tissues, which has the advantage of utilizing much smaller sample size to achieve reliable differential network estimation. Our simulation results demonstrated that LDGM consistently outperforms other Gaussian graphical model based methods. We further evaluated LDGM by applying to the brain and blood gene expression data from the GTEx consortium. We also applied LDGM to identify network rewiring between cancer subtypes using the TCGA breast cancer samples. Our results suggest that LDGM is an effective method to infer differential network using high-throughput gene expression data to identify GRN dynamics among different cellular conditions. PMID:27378774

  12. 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.

  13. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

    PubMed

    Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

    2015-01-01

    The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  14. Using RNA interference to identify genes required for RNA interference

    PubMed Central

    Dudley, Nathaniel R.; Labbé, Jean-Claude; Goldstein, Bob

    2002-01-01

    RNA interference (RNAi) is a phenomenon in which double-stranded RNA (dsRNA) silences endogenous gene expression. By injecting pools of dsRNAs into Caenorhabditis elegans, we identified a dsRNA that acts as a potent suppressor of the RNAi mechanism. We have used coinjection of dsRNAs to identify four additional candidates for genes involved in the RNAi mechanism in C. elegans. Three of the genes are C. elegans mes genes, some of which encode homologs of the Drosophila chromatin-binding Polycomb-group proteins. We have used loss-of-function mutants to confirm a role for mes-3, -4, and -6 in RNAi. Interestingly, introducing very low levels of dsRNA can bypass a requirement for these genes in RNAi. The finding that genes predicted to encode proteins that associate with chromatin are involved in RNAi in C. elegans raises the possibility that chromatin may play a role in RNAi in animals, as it does in plants. PMID:11904378

  15. 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.

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

    EPA Science Inventory

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

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

    PubMed

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

    2012-01-01

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

  18. A genomics approach identifies senescence-specific gene expression regulation

    PubMed Central

    Lackner, Daniel H; Hayashi, Makoto T; Cesare, Anthony J; Karlseder, Jan

    2014-01-01

    Replicative senescence is a fundamental tumor-suppressive mechanism triggered by telomere erosion that results in a permanent cell cycle arrest. To understand the impact of telomere shortening on gene expression, we analyzed the transcriptome of diploid human fibroblasts as they progressed toward and entered into senescence. We distinguished novel transcription regulation due to replicative senescence by comparing senescence-specific expression profiles to profiles from cells arrested by DNA damage or serum starvation. Only a small specific subset of genes was identified that was truly senescence-regulated and changes in gene expression were exacerbated from presenescent to senescent cells. The majority of gene expression regulation in replicative senescence was shown to occur due to telomere shortening, as exogenous telomerase activity reverted most of these changes. PMID:24863242

  19. A genomics approach identifies senescence-specific gene expression regulation.

    PubMed

    Lackner, Daniel H; Hayashi, Makoto T; Cesare, Anthony J; Karlseder, Jan

    2014-10-01

    Replicative senescence is a fundamental tumor-suppressive mechanism triggered by telomere erosion that results in a permanent cell cycle arrest. To understand the impact of telomere shortening on gene expression, we analyzed the transcriptome of diploid human fibroblasts as they progressed toward and entered into senescence. We distinguished novel transcription regulation due to replicative senescence by comparing senescence-specific expression profiles to profiles from cells arrested by DNA damage or serum starvation. Only a small specific subset of genes was identified that was truly senescence-regulated and changes in gene expression were exacerbated from presenescent to senescent cells. The majority of gene expression regulation in replicative senescence was shown to occur due to telomere shortening, as exogenous telomerase activity reverted most of these changes.

  20. Variation in Arabidopsis flooding responses identifies numerous putative "tolerance genes".

    PubMed

    Vashisht, Divya; van Veen, Hans; Akman, Melis; Sasidharan, Rashmi

    2016-11-01

    Plant survival in flooded environments requires a combinatory response to multiple stress conditions such as limited light availability, reduced gas exchange and nutrient uptake. The ability to fine-tune the molecular response at the transcriptional and/or post-transcriptional level that can eventually lead to metabolic and anatomical adjustments are the underlying requirements to confer tolerance. Previously, we compared the transcriptomic adjustment of submergence tolerant, intolerant accessions and identified a core conserved and genotype-specific response to flooding stress, identifying numerous 'putative' tolerance genes. Here, we performed genome wide association analyses on 81 natural Arabidopsis accessions that identified 30 additional SNP markers associated with flooding tolerance. We argue that, given the many genes associated with flooding tolerance in Arabidopsis, improving resistance to submergence requires numerous genetic changes.

  1. A candidate gene study of canine joint diseases.

    PubMed

    Clements, Dylan N; Short, Andrea D; Barnes, Annette; Kennedy, Lorna J; Ferguson, John F; Butterworth, Steven J; Fitzpatrick, Noel; Pead, Matthew; Bennett, David; Innes, John F; Carter, Stuart D; Ollier, William E R

    2010-01-01

    Canine osteoarthritis (OA) commonly occurs in association with articular diseases, such as hip dysplasia (HD), elbow dysplasia (ED), or cranial cruciate ligament rupture (CCLR). We hypothesized that a common genomic risk for the development of canine joint disease and canine OA would be identified by evaluating the allele frequencies of candidate gene single nucleotide polymorphisms (SNPs) in dogs with OA associated with different articular diseases when compared with a general population of breed-matched dogs. DNA was extracted from blood samples obtained from Labrador Retrievers and Golden Retrievers surgically treated for ED, HD, and CCLR and confirmed to have radiographic evidence of OA. One hundred and thirteen SNPs in 20 candidate genes were genotyped. No significant associations were identified for SNPs or haplotypes in the candidate genes for the diseases evaluated. The candidate gene approach for the study of genetic association is unlikely to be successful for complex canine diseases such as OA without prior trait mapping evaluation.

  2. Gene expression profiling in bladder cancer identifies potential therapeutic targets

    PubMed Central

    Hussain, Syed A.; Palmer, Daniel H.; Syn, Wing-Kin; Sacco, Joseph J.; Greensmith, Richard M.D.; Elmetwali, Taha; Aachi, Vijay; Lloyd, Bryony H.; Jithesh, Puthen V.; Arrand, John; Barton, Darren; Ansari, Jawaher; Sibson, D. Ross; James, Nicholas D.

    2017-01-01

    Despite advances in management, bladder cancer remains a major cause of cancer related complications. Characterisation of gene expression patterns in bladder cancer allows the identification of pathways involved in its pathogenesis, and may stimulate the development of novel therapies targeting these pathways. Between 2004 and 2005, cystoscopic bladder biopsies were obtained from 19 patients and 11 controls. These were subjected to whole transcript-based microarray analysis. Unsupervised hierarchical clustering was used to identify samples with similar expression profiles. Hypergeometric analysis was used to identify canonical pathways and curated networks having statistically significant enrichment of differentially expressed genes. Osteopontin (OPN) expression was validated by immunohistochemistry. Hierarchical clustering defined signatures, which differentiated between cancer and healthy tissue, muscle-invasive or non-muscle invasive cancer and healthy tissue, grade 1 and grade 3. Pathways associated with cell cycle and proliferation were markedly upregulated in muscle-invasive and grade 3 cancers. Genes associated with the classical complement pathway were downregulated in non-muscle invasive cancer. Osteopontin was markedly overexpressed in invasive cancer compared to healthy tissue. The present study contributes to a growing body of work on gene expression signatures in bladder cancer. The data support an important role for osteopontin in bladder cancer, and identify several pathways worthy of further investigation. PMID:28259975

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

    PubMed Central

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

    2015-01-01

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

  4. The FUN of identifying gene function in bacterial pathogens; insights from Salmonella functional genomics.

    PubMed

    Hammarlöf, Disa L; Canals, Rocío; Hinton, Jay C D

    2013-10-01

    The availability of thousands of genome sequences of bacterial pathogens poses a particular challenge because each genome contains hundreds of genes of unknown function (FUN). How can we easily discover which FUN genes encode important virulence factors? One solution is to combine two different functional genomic approaches. First, transcriptomics identifies bacterial FUN genes that show differential expression during the process of mammalian infection. Second, global mutagenesis identifies individual FUN genes that the pathogen requires to cause disease. The intersection of these datasets can reveal a small set of candidate genes most likely to encode novel virulence attributes. We demonstrate this approach with the Salmonella infection model, and propose that a similar strategy could be used for other bacterial pathogens.

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

    PubMed

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

    2013-09-01

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

  6. 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.

  7. Phage cluster relationships identified through single gene analysis

    PubMed Central

    2013-01-01

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

  8. Two-stage designs to identify the effects of SNP combinations on complex diseases.

    PubMed

    Kang, Guolian; Yue, Weihua; Zhang, Jifeng; Huebner, Marianne; Zhang, Handi; Ruan, Yan; Lu, Tianlan; Ling, Yansu; Zuo, Yijun; Zhang, Dai

    2008-01-01

    The genetic basis of complex diseases is expected to be highly heterogeneous, with many disease genes, where each gene by itself has only a small effect. Based on the nonlinear contributions of disease genes across the genome to complex diseases, we introduce the concept of single nucleotide polymorphism (SNP) synergistic blocks. A two-stage approach is applied to detect the genetic association of synergistic blocks with a disease. In the first stage, synergistic blocks associated with a complex disease are identified by clustering SNP patterns and choosing blocks within a cluster that minimize a diversity criterion. In the second stage, a logistic regression model is given for a synergistic block. Using simulated case-control data, we demonstrate that our method has reasonable power to identify gene-gene interactions. To further evaluate the performance of our method, we apply our method to 17 loci of four candidate genes for paranoid schizophrenia in a Chinese population. Five synergistic blocks are found to be associated with schizophrenia, three of which are negatively associated (odds ratio, OR < 0.3, P < 0.05), while the others are positively associated (OR > 2.0, P < 0.05). The mathematical models of these five synergistic blocks are presented. The results suggest that there may be interactive effects for schizophrenia among variants of the genes neuregulin 1 (NRG1, 8p22-p11), G72 (13q34), the regulator of G-protein signaling-4 (RGS4, 1q21-q22) and frizzled 3 (FZD3, 8p21). Using synergistic blocks, we can reduce the dimensionality in a multi-locus association analysis, and evaluate the sizes of interactive effects among multiple disease genes on complex phenotypes.

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

    PubMed Central

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

    Magnetic bacteria synthesize nanoscale crystals of magnetite in intracellular, membrane-bounded organelles (magnetosomes). These crystals are preserved in the fossil record at least as far back as the late Neoproterozoic and have been tentatively identified in much older rocks (1). This fossil record may provide deep time calibration points for molecular evolution studies once the genes involved in biologically controlled magnetic mineralization (BCMM) are known. Further, a genetic and biochemical understanding of BCMM will give insight into the depositional environment and biogeochemical cycles in which magnetic bacteria play a role. The BCMM process is not well understood, though proteins have been identified from the magnetosome membrane and genetic manipulation and biochemical characterization of these proteins are underway. Most of the proteins currently thought to be involved are encoded within the mam cluster, a large cluster of genes whose products localize to the magnetosome membrane and are conserved among magnetic bacteria (2). In an effort to identify all of the genes necessary for bacterial BCMM, we undertook a transposon mutagenesis of Magnetospirillum magneticum AMB-1. Non-magnetic mutants (MNMs) were identified by growth in liquid culture followed by a magnetic assay. The insertion site of the transposon was identified two ways. First MNMs were screened with a PCR assay to determine if the transposon had inserted into the mam cluster. Second, the transposon was rescued from the mutant DNA and cloned for sequencing. The majority insertion sites are located within the mam cluster. Insertion sites also occur in operons which have not previously been suspected to be involved in magnetite biomineralization. None of the insertion sites have occurred within genes reported from previous transposon mutagenesis studies of AMB-1 (3, 4). Two of the non-mam cluster insertion sites occur in operons containing genes conserved particularly between MS-1 and MC-1. We

  11. Identifying genes required for respiratory growth of fission yeast

    PubMed Central

    2016-01-01

    We have used both auxotroph and prototroph versions of the latest deletion-mutant library to identify genes required for respiratory growth on solid glycerol medium in fission yeast. This data set complements and enhances our recent study on functional and regulatory aspects of energy metabolism by providing additional proteins that are involved in respiration. Most proteins identified in this mutant screen have not been implicated in respiration in budding yeast. We also provide a protocol to generate a prototrophic mutant library, and data on technical and biological reproducibility of colony-based high-throughput screens. PMID:27918601

  12. Axon Regeneration Genes Identified by RNAi Screening in C. elegans

    PubMed Central

    Nix, Paola; Hammarlund, Marc; Hauth, Linda; Lachnit, Martina; Jorgensen, Erik M.

    2014-01-01

    Axons of the mammalian CNS lose the ability to regenerate soon after development due to both an inhibitory CNS environment and the loss of cell-intrinsic factors necessary for regeneration. The complex molecular events required for robust regeneration of mature neurons are not fully understood, particularly in vivo. To identify genes affecting axon regeneration in Caenorhabditis elegans, we performed both an RNAi-based screen for defective motor axon regeneration in unc-70/β-spectrin mutants and a candidate gene screen. From these screens, we identified at least 50 conserved genes with growth-promoting or growth-inhibiting functions. Through our analysis of mutants, we shed new light on certain aspects of regeneration, including the role of β-spectrin and membrane dynamics, the antagonistic activity of MAP kinase signaling pathways, and the role of stress in promoting axon regeneration. Many gene candidates had not previously been associated with axon regeneration and implicate new pathways of interest for therapeutic intervention. PMID:24403161

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

    PubMed Central

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

    2014-01-01

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

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

    DOEpatents

    Shizuya, Hiroaki

    2006-01-31

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

  15. OrthoDisease: tracking disease gene orthologs across 100 species.

    PubMed

    Forslund, Kristoffer; Schreiber, Fabian; Thanintorn, Nattaphon; Sonnhammer, Erik L L

    2011-09-01

    Orthology is one of the most important tools available to modern biology, as it allows making inferences from easily studied model systems to much less tractable systems of interest, such as ourselves. This becomes important not least in the study of genetic diseases. We here review work on the orthology of disease-associated genes and also present an updated version of the InParanoid-based disease orthology database and web site OrthoDisease, with 14-fold increased species coverage since the previous version. Using this resource, we survey the taxonomic distribution of orthologs of human genes involved in different disease categories. The hypothesis that paralogs can mask the effect of deleterious mutations predicts that known heritable disease genes should have fewer close paralogs. We found large-scale support for this hypothesis as significantly fewer duplications were observed for disease genes in the OrthoDisease ortholog groups.

  16. [Gene therapy of neurological diseases].

    PubMed

    Kahn, A; Haase, G; Akli, S; Guidotti, J E

    1996-01-01

    In hereditary neurological diseases, gene transfer into neurons is made difficult by: the nature of the cells (postmitotic cells, that cannot be cultured, genetically modified ex vivo, then retransplanted), sometimes, their widespread localization, the blood-brain barrier. However, three viral vectors derived from adenovirus, Herpes simplex virus and adeno-associated virus have been shown to be very efficient in transferring DNA into brain cells. All of these vectors can infect resting cells, especially neurons, and are efficient in vivo. Retroviral vectors which can infect dividing cells only are mainly used for ex vivo genetic modification of cells (neural progenitor cells, myoblasts, fibroblasts) followed by intracerebral transplantation. Alternatively, genetically modified cells can be transplanted in a peripheral site if the transgene product is able to cross the blood-brain barrier or to be transported retrogradely from the nerve terminals. We have especially investigated the potential interest of adenoviral vectors to transfer foreign genes into brain cells and to treat animal models of neurological diseases. These vectors allowed us to transfer the lacZ gene into any neural cell type, including neurons, glia, photoreceptors and olfactory receptors, ex vivo, in cell culture, and in vivo, by stereotactic administration. In addition, axonal transport of adenoviral vectors has been demonstrated, e.g. in the substantia nigra after injection into the striatum, in the olfactory bulb after intranasal instillation and in spinal motor neurons after intramuscular injection. After intracerebroventricular injection, ependymal cells are massively infected and express the transgene for several months, as this is also observed in neurons. Through the spinal canal and cerebrospinal fluid, the vector can diffuse to a considerable distance from the injection point, e.g. to the lumbar spinal cord after injection in the suboccipital region. To test the biological function of

  17. Analysis of gene order conservation in eukaryotes identifies transcriptionally and functionally linked genes.

    PubMed

    Dávila López, Marcela; Martínez Guerra, Juan José; Samuelsson, Tore

    2010-05-14

    The order of genes in eukaryotes is not entirely random. Studies of gene order conservation are important to understand genome evolution and to reveal mechanisms why certain neighboring genes are more difficult to separate during evolution. Here, genome-wide gene order information was compiled for 64 species, representing a wide variety of eukaryotic phyla. This information is presented in a browser where gene order may be displayed and compared between species. Factors related to non-random gene order in eukaryotes were examined by considering pairs of neighboring genes. The evolutionary conservation of gene pairs was studied with respect to relative transcriptional direction, intergenic distance and functional relationship as inferred by gene ontology. The results show that among gene pairs that are conserved the divergently and co-directionally transcribed genes are much more common than those that are convergently transcribed. Furthermore, highly conserved pairs, in particular those of fungi, are characterized by a short intergenic distance. Finally, gene pairs of metazoa and fungi that are evolutionary conserved and that are divergently transcribed are much more likely to be related by function as compared to poorly conserved gene pairs. One example is the ribosomal protein gene pair L13/S16, which is unusual as it occurs both in fungi and alveolates. A specific functional relationship between these two proteins is also suggested by the fact that they are part of the same operon in both eubacteria and archaea. In conclusion, factors associated with non-random gene order in eukaryotes include relative gene orientation, intergenic distance and functional relationships. It seems likely that certain pairs of genes are conserved because the genes involved have a transcriptional and/or functional relationship. The results also indicate that studies of gene order conservation aid in identifying genes that are related in terms of transcriptional control.

  18. Analysis of Gene Order Conservation in Eukaryotes Identifies Transcriptionally and Functionally Linked Genes

    PubMed Central

    Dávila López, Marcela; Martínez Guerra, Juan José; Samuelsson, Tore

    2010-01-01

    The order of genes in eukaryotes is not entirely random. Studies of gene order conservation are important to understand genome evolution and to reveal mechanisms why certain neighboring genes are more difficult to separate during evolution. Here, genome-wide gene order information was compiled for 64 species, representing a wide variety of eukaryotic phyla. This information is presented in a browser where gene order may be displayed and compared between species. Factors related to non-random gene order in eukaryotes were examined by considering pairs of neighboring genes. The evolutionary conservation of gene pairs was studied with respect to relative transcriptional direction, intergenic distance and functional relationship as inferred by gene ontology. The results show that among gene pairs that are conserved the divergently and co-directionally transcribed genes are much more common than those that are convergently transcribed. Furthermore, highly conserved pairs, in particular those of fungi, are characterized by a short intergenic distance. Finally, gene pairs of metazoa and fungi that are evolutionary conserved and that are divergently transcribed are much more likely to be related by function as compared to poorly conserved gene pairs. One example is the ribosomal protein gene pair L13/S16, which is unusual as it occurs both in fungi and alveolates. A specific functional relationship between these two proteins is also suggested by the fact that they are part of the same operon in both eubacteria and archaea. In conclusion, factors associated with non-random gene order in eukaryotes include relative gene orientation, intergenic distance and functional relationships. It seems likely that certain pairs of genes are conserved because the genes involved have a transcriptional and/or functional relationship. The results also indicate that studies of gene order conservation aid in identifying genes that are related in terms of transcriptional control. PMID:20498846

  19. Using Drosophila melanogaster to identify chemotherapy toxicity genes.

    PubMed

    King, Elizabeth G; Kislukhin, Galina; Walters, Kelli N; Long, Anthony D

    2014-09-01

    The severity of the toxic side effects of chemotherapy shows a great deal of interindividual variability, and much of this variation is likely genetically based. Simple DNA tests predictive of toxic side effects could revolutionize the way chemotherapy is carried out. Due to the challenges in identifying polymorphisms that affect toxicity in humans, we use Drosophila fecundity following oral exposure to carboplatin, gemcitabine and mitomycin C as a model system to identify naturally occurring DNA variants predictive of toxicity. We use the Drosophila Synthetic Population Resource (DSPR), a panel of recombinant inbred lines derived from a multiparent advanced intercross, to map quantitative trait loci affecting chemotoxicity. We identify two QTL each for carboplatin and gemcitabine toxicity and none for mitomycin. One QTL is associated with fly orthologs of a priori human carboplatin candidate genes ABCC2 and MSH2, and a second QTL is associated with fly orthologs of human gemcitabine candidate genes RRM2 and RRM2B. The third, a carboplatin QTL, is associated with a posteriori human orthologs from solute carrier family 7A, INPP4A&B, and NALCN. The fourth, a gemcitabine QTL that also affects methotrexate toxicity, is associated with human ortholog GPx4. Mapped QTL each explain a significant fraction of variation in toxicity, yet individual SNPs and transposable elements in the candidate gene regions fail to singly explain QTL peaks. Furthermore, estimates of founder haplotype effects are consistent with genes harboring several segregating functional alleles. We find little evidence for nonsynonymous SNPs explaining mapped QTL; thus it seems likely that standing variation in toxicity is due to regulatory alleles.

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

    PubMed Central

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

    2016-01-01

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

  1. 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

  2. Meta-analysis of gene expression data identifies causal genes for prostate cancer.

    PubMed

    Wang, Xiang-Yang; Hao, Jian-Wei; Zhou, Rui-Jin; Zhang, Xiang-Sheng; Yan, Tian-Zhong; Ding, De-Gang; Shan, Lei

    2013-01-01

    Prostate cancer is a leading cause of death in male populations across the globe. With the advent of gene expression arrays, many microarray studies have been conducted in prostate cancer, but the results have varied across different studies. To better understand the genetic and biologic mechanisms of prostate cancer, we conducted a meta-analysis of two studies on prostate cancer. Eight key genes were identified to be differentially expressed with progression. After gene co-expression analysis based on data from the GEO database, we obtained a co- expressed gene list which included 725 genes. Gene Ontology analysis revealed that these genes are involved in actin filament-based processes, locomotion and cell morphogenesis. Further analysis of the gene list should provide important clues for developing new prognostic markers and therapeutic targets.

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

    PubMed

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

    2015-08-01

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

  4. A recellularized human colon model identifies cancer driver genes

    PubMed Central

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

    2016-01-01

    Refined cancer models are needed to bridge the gap between cell-line, animal and clinical research. Here we describe the engineering of an organotypic colon cancer model by recellularization of a native human matrix that contains cell-populated mucosa and an intact muscularis mucosa layer. This ex vivo system recapitulates the pathophysiological progression from APC-mutant neoplasia to submucosal invasive tumor. We used it to perform a Sleeping Beauty transposon mutagenesis screen to identify genes that cooperate with mutant APC in driving invasive neoplasia. 38 candidate invasion driver genes were identified, 17 of which have been previously implicated in colorectal cancer progression, including TCF7L2, TWIST2, MSH2, DCC and EPHB1/2. Six invasion driver genes that to our knowledge have not been previously described were validated in vitro using cell proliferation, migration and invasion assays, and ex vivo using recellularized human colon. These results demonstrate the utility of our organoid model for studying cancer biology. PMID:27398792

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

    PubMed Central

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

    2015-01-01

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

  6. 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

  7. Anaerobically expressed Escherichia coli genes identified by operon fusion techniques.

    PubMed Central

    Choe, M; Reznikoff, W S

    1991-01-01

    Genes that are expressed under anaerobic conditions were identified by operon fusion techniques with a hybrid bacteriophage of lambda and Mu, lambda placMu53, which creates transcriptional fusions to lacZY. Cells were screened for anaerobic expression on XG medium. Nine strains were selected, and the insertion point of the hybrid phage in each strain was mapped on the Escherichia coli chromosome linkage map. The anaerobic and aerobic expression levels of these genes were measured by beta-galactosidase assays in different medium conditions and in the presence of three regulatory mutations (fnr, narL, and rpoN). The anaerobically expressed genes (aeg) located at minute 99 (aeg-99) and 75 (aeg-75) appeared to be partially regulated by fnr, and aeg-93 is tightly regulated by fnr. aeg-60 requires a functional rpoN gene for its anaerobic expression. aeg-46.5 is repressed by narL. aeg-65A and aeg-65C are partially controlled by fnr but only in media containing nitrate or fumarate. aeg-47.5 and aeg-48.5 were found to be anaerobically induced only in rich media. The effects of a narL mutation on aeg-46.5 expression were observed in all medium conditions regardless of the presence or absence of nitrate. This suggests that narL has a regulatory function in the absence of exogenously added nitrate. PMID:1917846

  8. Immunoglobulin A coating identifies colitogenic bacteria in inflammatory bowel disease.

    PubMed

    Palm, Noah W; de Zoete, Marcel R; Cullen, Thomas W; Barry, Natasha A; Stefanowski, Jonathan; Hao, Liming; Degnan, Patrick H; Hu, Jianzhong; Peter, Inga; Zhang, Wei; Ruggiero, Elizabeth; Cho, Judy H; Goodman, Andrew L; Flavell, Richard A

    2014-08-28

    Specific members of the intestinal microbiota dramatically affect inflammatory bowel disease (IBD) in mice. In humans, however, identifying bacteria that preferentially affect disease susceptibility and severity remains a major challenge. Here, we used flow-cytometry-based bacterial cell sorting and 16S sequencing to characterize taxa-specific coating of the intestinal microbiota with immunoglobulin A (IgA-SEQ) and show that high IgA coating uniquely identifies colitogenic intestinal bacteria in a mouse model of microbiota-driven colitis. We then used IgA-SEQ and extensive anaerobic culturing of fecal bacteria from IBD patients to create personalized disease-associated gut microbiota culture collections with predefined levels of IgA coating. Using these collections, we found that intestinal bacteria selected on the basis of high coating with IgA conferred dramatic susceptibility to colitis in germ-free mice. Thus, our studies suggest that IgA coating identifies inflammatory commensals that preferentially drive intestinal disease. Targeted elimination of such bacteria may reduce, reverse, or even prevent disease development.

  9. Identifying Neighborhoods of Coordinated Gene Expression and Metabolite Profiles

    PubMed Central

    Hancock, Timothy; Wicker, Nicolas; Takigawa, Ichigaku; Mamitsuka, Hiroshi

    2012-01-01

    In this paper we investigate how metabolic network structure affects any coordination between transcript and metabolite profiles. To achieve this goal we conduct two complementary analyses focused on the metabolic response to stress. First, we investigate the general size of any relationship between metabolic network gene expression and metabolite profiles. We find that strongly correlated transcript-metabolite profiles are sustained over surprisingly long network distances away from any target metabolite. Secondly, we employ a novel pathway mining method to investigate the structure of this transcript-metabolite relationship. The objective of this method is to identify a minimum set of metabolites which are the target of significantly correlated gene expression pathways. The results reveal that in general, a global regulation signature targeting a small number of metabolites is responsible for a large scale metabolic response. However, our method also reveals pathway specific effects that can degrade this global regulation signature and complicates the observed coordination between transcript-metabolite profiles. PMID:22355360

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

    PubMed Central

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

    2015-01-01

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

  11. Novel radiation response genes identified in gene-trapped MCF10A mammary epithelial cells.

    PubMed

    Malone, Jennifer; Ullrich, Robert

    2007-02-01

    We have used a gene-trapping strategy to screen human mammary epithelial cells for radiation response genes. Relative mRNA expression levels of five candidate genes in MCF10A cells were analyzed, both with and without exposure to radiation. In all five cases, the trapped genes were significantly down-regulated after radiation treatment. Sequence analysis of the fusion transcripts identified the trapped genes: (1) the human androgen receptor, (2) the uncharacterized DREV1 gene, which has known homology to DNA methyltransferases, (3) the human creatine kinase gene, (4) the human eukaryotic translation elongation factor 1 beta 2, and (5) the human ribosomal protein L27. All five genes were down-regulated significantly after treatment with varying doses of ionizing radiation (0.10 to 4.0 Gy) and at varying times (2-30 h after treatment). The genes were also analyzed in human fibroblast and lymphoblastoid cell lines to determine whether the radiation response being observed was cell-type specific. The results verified that the observed radiation response was not a cell-type-specific phenomenon, suggesting that the genes play essential roles in the radiation damage control pathways. This study demonstrates the potential of the gene-trap approach for the identification and functional analysis of novel radiation response genes.

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

    PubMed Central

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

    2015-01-01

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

  13. Using hyperspectral imaging technology to identify diseased tomato leaves

    NASA Astrophysics Data System (ADS)

    Li, Cuiling; Wang, Xiu; Zhao, Xueguan; Meng, Zhijun; Zou, Wei

    2016-11-01

    In the process of tomato plants growth, due to the effect of plants genetic factors, poor environment factors, or disoperation of parasites, there will generate a series of unusual symptoms on tomato plants from physiology, organization structure and external form, as a result, they cannot grow normally, and further to influence the tomato yield and economic benefits. Hyperspectral image usually has high spectral resolution, not only contains spectral information, but also contains the image information, so this study adopted hyperspectral imaging technology to identify diseased tomato leaves, and developed a simple hyperspectral imaging system, including a halogen lamp light source unit, a hyperspectral image acquisition unit and a data processing unit. Spectrometer detection wavelength ranged from 400nm to 1000nm. After hyperspectral images of tomato leaves being captured, it was needed to calibrate hyperspectral images. This research used spectrum angle matching method and spectral red edge parameters discriminant method respectively to identify diseased tomato leaves. Using spectral red edge parameters discriminant method produced higher recognition accuracy, the accuracy was higher than 90%. Research results have shown that using hyperspectral imaging technology to identify diseased tomato leaves is feasible, and provides the discriminant basis for subsequent disease control of tomato plants.

  14. Transposon tagging of disease resistance genes

    SciTech Connect

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

    1989-01-01

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

  15. Identifying the genes of unconventional high temperature superconductors.

    PubMed

    Hu, Jiangping

    We elucidate a recently emergent framework in unifying the two families of high temperature (high [Formula: see text]) superconductors, cuprates and iron-based superconductors. The unification suggests that the latter is simply the counterpart of the former to realize robust extended s-wave pairing symmetries in a square lattice. The unification identifies that the key ingredients (gene) of high [Formula: see text] superconductors is a quasi two dimensional electronic environment in which the d-orbitals of cations that participate in strong in-plane couplings to the p-orbitals of anions are isolated near Fermi energy. With this gene, the superexchange magnetic interactions mediated by anions could maximize their contributions to superconductivity. Creating the gene requires special arrangements between local electronic structures and crystal lattice structures. The speciality explains why high [Formula: see text] superconductors are so rare. An explicit prediction is made to realize high [Formula: see text] superconductivity in Co/Ni-based materials with a quasi two dimensional hexagonal lattice structure formed by trigonal bipyramidal complexes.

  16. New mutations identified in the ocular albinism type 1 gene.

    PubMed

    Roma, Cristin; Ferrante, Paola; Guardiola, Ombretta; Ballabio, Andrea; Zollo, Massimo

    2007-11-01

    As the most common form of ocular albinism, ocular albinism type I (OA1) is an X-linked disorder that has an estimated prevalence of about 1:50,000. We searched for mutations through the human genome sequence draft by direct sequencing on eighteen patients with OA1, both within the coding region and in a thousand base pairs upstream of its start site. Here, we have identified eight new mutations located in the coding region of the gene. Two independent mutations, both located in the most carboxyterminal protein regions, were further characterized by immunofluorescence confocal microscopy, thus showing an impairment in their subcellular distribution into the lysosomal compartment of Cos-7A cells. The mutations found can result in protein misfolding, thus underlining the importance of the structure-function relationships of the protein as a major pathogenic mechanism in ocular albinism. Seven individuals out of eighteen (38.9%) with a clinical diagnosis of ocular albinism showed mutations, thus underlining the discrepancies between the clinical phenotype features and their genotype correlations. We postulate that mutations that have not yet been identified are potentially located in non-coding conserved regions or regulatory sequences of the OA1 gene.

  17. [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.

  18. Identifying photoreceptors in blind eyes caused by RPE65 mutations: Prerequisite for human gene therapy success.

    PubMed

    Jacobson, Samuel G; Aleman, Tomas S; Cideciyan, Artur V; Sumaroka, Alexander; Schwartz, Sharon B; Windsor, Elizabeth A M; Traboulsi, Elias I; Heon, Elise; Pittler, Steven J; Milam, Ann H; Maguire, Albert M; Palczewski, Krzysztof; Stone, Edwin M; Bennett, Jean

    2005-04-26

    Mutations in RPE65, a gene essential to normal operation of the visual (retinoid) cycle, cause the childhood blindness known as Leber congenital amaurosis (LCA). Retinal gene therapy restores vision to blind canine and murine models of LCA. Gene therapy in blind humans with LCA from RPE65 mutations may also have potential for success but only if the retinal photoreceptor layer is intact, as in the early-disease stage-treated animals. Here, we use high-resolution in vivo microscopy to quantify photoreceptor layer thickness in the human disease to define the relationship of retinal structure to vision and determine the potential for gene therapy success. The normally cone photoreceptor-rich central retina and rod-rich regions were studied. Despite severely reduced cone vision, many RPE65-mutant retinas had near-normal central microstructure. Absent rod vision was associated with a detectable but thinned photoreceptor layer. We asked whether abnormally thinned RPE65-mutant retina with photoreceptor loss would respond to treatment. Gene therapy in Rpe65(-/-) mice at advanced-disease stages, a more faithful mimic of the humans we studied, showed success but only in animals with better-preserved photoreceptor structure. The results indicate that identifying and then targeting retinal locations with retained photoreceptors will be a prerequisite for successful gene therapy in humans with RPE65 mutations and in other retinal degenerative disorders now moving from proof-of-concept studies toward clinical trials.

  19. Improved integrative framework combining association data with gene expression features to prioritize Crohn's disease genes.

    PubMed

    Ning, Kaida; Gettler, Kyle; Zhang, Wei; Ng, Sok Meng; Bowen, B Monica; Hyams, Jeffrey; Stephens, Michael C; Kugathasan, Subra; Denson, Lee A; Schadt, Eric E; Hoffman, Gabriel E; Cho, Judy H

    2015-07-15

    Genome-wide association studies in Crohn's disease (CD) have identified 140 genome-wide significant loci. However, identification of genes driving association signals remains challenging. Furthermore, genome-wide significant thresholds limit false positives at the expense of decreased sensitivity. In this study, we explored gene features contributing to CD pathogenicity, including gene-based association data from CD and autoimmune (AI) diseases, as well as gene expression features (eQTLs, epigenetic markers of expression and intestinal gene expression data). We developed an integrative model based on a CD reference gene set. This integrative approach outperformed gene-based association signals alone in identifying CD-related genes based on statistical validation, gene ontology enrichment, differential expression between M1 and M2 macrophages and a validation using genes causing monogenic forms of inflammatory bowel disease as a reference. Besides gene-level CD association P-values, association with AI diseases was the strongest predictor, highlighting generalized mechanisms of inflammation, and the interferon-γ pathway particularly. Within the 140 high-confidence CD regions, 598 of 1328 genes had low prioritization scores, highlighting genes unlikely to contribute to CD pathogenesis. For select regions, comparably high integrative model scores were observed for multiple genes. This is particularly evident for regions having extensive linkage disequilibrium such as the IBD5 locus. Our analyses provide a standardized reference for prioritizing potential CD-related genes, in regions with both highly significant and nominally significant gene-level association P-values. Our integrative model may be particularly valuable in prioritizing rare, potentially private, missense variants for which genome-wide evidence for association may be unattainable.

  20. Improved integrative framework combining association data with gene expression features to prioritize Crohn's disease genes

    PubMed Central

    Ning, Kaida; Gettler, Kyle; Zhang, Wei; Ng, Sok Meng; Bowen, B. Monica; Hyams, Jeffrey; Stephens, Michael C.; Kugathasan, Subra; Denson, Lee A.; Schadt, Eric E.; Hoffman, Gabriel E.; Cho, Judy H.

    2015-01-01

    Genome-wide association studies in Crohn's disease (CD) have identified 140 genome-wide significant loci. However, identification of genes driving association signals remains challenging. Furthermore, genome-wide significant thresholds limit false positives at the expense of decreased sensitivity. In this study, we explored gene features contributing to CD pathogenicity, including gene-based association data from CD and autoimmune (AI) diseases, as well as gene expression features (eQTLs, epigenetic markers of expression and intestinal gene expression data). We developed an integrative model based on a CD reference gene set. This integrative approach outperformed gene-based association signals alone in identifying CD-related genes based on statistical validation, gene ontology enrichment, differential expression between M1 and M2 macrophages and a validation using genes causing monogenic forms of inflammatory bowel disease as a reference. Besides gene-level CD association P-values, association with AI diseases was the strongest predictor, highlighting generalized mechanisms of inflammation, and the interferon-γ pathway particularly. Within the 140 high-confidence CD regions, 598 of 1328 genes had low prioritization scores, highlighting genes unlikely to contribute to CD pathogenesis. For select regions, comparably high integrative model scores were observed for multiple genes. This is particularly evident for regions having extensive linkage disequilibrium such as the IBD5 locus. Our analyses provide a standardized reference for prioritizing potential CD-related genes, in regions with both highly significant and nominally significant gene-level association P-values. Our integrative model may be particularly valuable in prioritizing rare, potentially private, missense variants for which genome-wide evidence for association may be unattainable. PMID:25935003

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

    PubMed

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

    2016-04-07

    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.

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

    PubMed Central

    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

    Objective 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. Methods 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. Results 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. Conclusion 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

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

    PubMed

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

    2016-05-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  6. Assessment of gene order computing methods for Alzheimer's disease

    PubMed Central

    2013-01-01

    Background Computational genomics of Alzheimer disease (AD), the most common form of senile dementia, is a nascent field in AD research. The field includes AD gene clustering by computing gene order which generates higher quality gene clustering patterns than most other clustering methods. However, there are few available gene order computing methods such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Further, their performance in gene order computation using AD microarray data is not known. We thus set forth to evaluate the performances of current gene order computing methods with different distance formulas, and to identify additional features associated with gene order computation. Methods Using different distance formulas- Pearson distance and Euclidean distance, the squared Euclidean distance, and other conditions, gene orders were calculated by ACO and GA (including standard GA and improved GA) methods, respectively. The qualities of the gene orders were compared, and new features from the calculated gene orders were identified. Results Compared to the GA methods tested in this study, ACO fits the AD microarray data the best when calculating gene order. In addition, the following features were revealed: different distance formulas generated a different quality of gene order, and the commonly used Pearson distance was not the best distance formula when used with both GA and ACO methods for AD microarray data. Conclusion Compared with Pearson distance and Euclidean distance, the squared Euclidean distance generated the best quality gene order computed by GA and ACO methods. PMID:23369541

  7. 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.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  11. A gain-of-function screen to identify genes that reduce lifespan in the adult of Drosophila melanogaster

    PubMed Central

    2014-01-01

    Background Several lines of evidence associate misregulated genetic expression with risk factors for diabetes, Alzheimer’s, and other diseases that sporadically develop in healthy adults with no background of hereditary disorders. Thus, we are interested in genes that may be expressed normally through parts of an individual’s life, but can cause physiological defects and disease when misexpressed in adulthood. Results We attempted to identify these genes in a model organism by arbitrarily misexpressing specific genes in adult Drosophila melanogaster, using 14,133 Gene Search lines. We identified 39 “reduced-lifespan genes” that, when misexpressed in adulthood, shortened the flies’ lifespan to less than 30% of that of control flies. About half of these genes have human orthologs that are known to be involved in human diseases. For about one-fourth of the reduced-lifespan genes, suppressing apoptosis restored the lifespan shortened by their misexpression. We determined the organs responsible for reduced lifespan when these genes were misexpressed specifically in adulthood, and found that while some genes induced reduced lifespan only when misexpressed in specific adult organs, others could induce reduced lifespan when misexpressed in various organs. This finding suggests that tissue-specific dysfunction may be involved in reduced lifespan related to gene misexpression. Gene ontology analysis showed that reduced-lifespan genes are biased toward genes related to development. Conclusions We identified 39 genes that, when misexpressed in adulthood, shortened the lifespan of adult flies. Suppressing apoptosis rescued this shortened lifespan for only a subset of the reduced-lifespan genes. The adult tissues in which gene misexpression caused early death differed among the reduced-lifespan genes. These results suggest that the cause of reduced lifespan upon misexpression differed among the genes. PMID:24739137

  12. 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.

  13. A Comprehensive Gene Expression Meta-analysis Identifies Novel Immune Signatures in Rheumatoid Arthritis Patients

    PubMed Central

    Afroz, Sumbul; Giddaluru, Jeevan; Vishwakarma, Sandeep; Naz, Saima; Khan, Aleem Ahmed; Khan, Nooruddin

    2017-01-01

    Rheumatoid arthritis (RA), a symmetric polyarticular arthritis, has long been feared as one of the most disabling forms of arthritis. Identification of gene signatures associated with RA onset and progression would lead toward development of novel diagnostics and therapeutic interventions. This study was undertaken to identify unique gene signatures of RA patients through large-scale meta-profiling of a diverse collection of gene expression data sets. We carried out a meta-analysis of 8 publicly available RA patients’ (107 RA patients and 76 healthy controls) gene expression data sets and further validated a few meta-signatures in RA patients through quantitative real-time PCR (RT-qPCR). We identified a robust meta-profile comprising 33 differentially expressed genes, which were consistently and significantly expressed across all the data sets. Our meta-analysis unearthed upregulation of a few novel gene signatures including PLCG2, HLA-DOB, HLA-F, EIF4E2, and CYFIP2, which were validated in peripheral blood mononuclear cell samples of RA patients. Further, functional and pathway enrichment analysis reveals perturbation of several meta-genes involved in signaling pathways pertaining to inflammation, antigen presentation, hypoxia, and apoptosis during RA. Additionally, PLCG2 (phospholipase Cγ2) popped out as a novel meta-gene involved in most of the pathways relevant to RA including inflammasome activation, platelet aggregation, and activation, thereby suggesting PLCG2 as a potential therapeutic target for controlling excessive inflammation during RA. In conclusion, these findings highlight the utility of meta-analysis approach in identifying novel gene signatures that might provide mechanistic insights into disease onset, progression and possibly lead toward the development of better diagnostic and therapeutic interventions against RA. PMID:28210261

  14. A Comprehensive Gene Expression Meta-analysis Identifies Novel Immune Signatures in Rheumatoid Arthritis Patients.

    PubMed

    Afroz, Sumbul; Giddaluru, Jeevan; Vishwakarma, Sandeep; Naz, Saima; Khan, Aleem Ahmed; Khan, Nooruddin

    2017-01-01

    Rheumatoid arthritis (RA), a symmetric polyarticular arthritis, has long been feared as one of the most disabling forms of arthritis. Identification of gene signatures associated with RA onset and progression would lead toward development of novel diagnostics and therapeutic interventions. This study was undertaken to identify unique gene signatures of RA patients through large-scale meta-profiling of a diverse collection of gene expression data sets. We carried out a meta-analysis of 8 publicly available RA patients' (107 RA patients and 76 healthy controls) gene expression data sets and further validated a few meta-signatures in RA patients through quantitative real-time PCR (RT-qPCR). We identified a robust meta-profile comprising 33 differentially expressed genes, which were consistently and significantly expressed across all the data sets. Our meta-analysis unearthed upregulation of a few novel gene signatures including PLCG2, HLA-DOB, HLA-F, EIF4E2, and CYFIP2, which were validated in peripheral blood mononuclear cell samples of RA patients. Further, functional and pathway enrichment analysis reveals perturbation of several meta-genes involved in signaling pathways pertaining to inflammation, antigen presentation, hypoxia, and apoptosis during RA. Additionally, PLCG2 (phospholipase Cγ2) popped out as a novel meta-gene involved in most of the pathways relevant to RA including inflammasome activation, platelet aggregation, and activation, thereby suggesting PLCG2 as a potential therapeutic target for controlling excessive inflammation during RA. In conclusion, these findings highlight the utility of meta-analysis approach in identifying novel gene signatures that might provide mechanistic insights into disease onset, progression and possibly lead toward the development of better diagnostic and therapeutic interventions against RA.

  15. Gene therapy for CNS diseases – Krabbe disease

    PubMed Central

    Rafi, Mohammad A.

    2016-01-01

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

  16. Gene therapy for childhood immunological diseases.

    PubMed

    Kohn, D B

    2008-01-01

    Gene therapy using autologous hematopoietic stem cells (HSC) that are corrected with the normal gene may have a beneficial effect on blood cell production or function, without the immunologic complications of allogeneic HSC transplantation. Childhood immunological diseases are highly favorable candidates for responses to gene therapy using HSC. Hemoglobinopathies, lysosomal and metabolic disorders and defects of hematopoietic stem and progenitor cells should also be ameliorated by gene therapy using autologous HSC. At present, gene therapy has been beneficial for patients with XSCID, ADA-deficient SCID and chronic granulomatous disease. The principle that partial marrow conditioning increases engraftment of gene-corrected HSC has been demonstrated. Clinical trials are being developed in Europe and the United States to treat several other genetic blood cell disorders. This progress is tempered by the serious complication observed in XSCID patients developing T lymphoproliferative disease. New methods for gene transfer (lentiviral and foamy viral vectors, semi-viral systems and gene correction) may retain or further increase the efficacy and decrease the risks from gene therapy using HSC. Ultimately, the relative benefits and risks of autologous gene therapy will be weighed against other available options (for example, allogeneic HSCT) to determine the treatment of choice.

  17. Gene Therapy for Diseases and Genetic Disorders

    MedlinePlus

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

  18. Gene Expression Profile of High IFN-γ Producers Stimulated with Leishmania braziliensis Identifies Genes Associated with Cutaneous Leishmaniasis

    PubMed Central

    Carneiro, Marcia W.; Fukutani, Kiyoshi F.; Andrade, Bruno B.; Curvelo, Rebecca P.; Cristal, Juqueline R.; Carvalho, Augusto M.; Barral, Aldina

    2016-01-01

    Background The initial response to Leishmania parasites is essential in determining disease development or resistance. In vitro, a divergent response to Leishmania, characterized by high or low IFN-γ production has been described as a potential tool to predict both vaccine response and disease susceptibility in vivo. Methods and findings We identified uninfected and healthy individuals that were shown to be either high- or low IFN-γ producers (HPs and LPs, respectively) following stimulation of peripheral blood cells with Leishmania braziliensis. Following stimulation, RNA was processed for gene expression analysis using immune gene arrays. Both HPs and LPs were shown to upregulate the expression of CXCL10, IFI27, IL6 and LTA. Genes expressed in HPs only (CCL7, IL8, IFI44L and IL1B) were associated with pathways related to IL17 and TREM 1 signaling. In LPs, uniquely expressed genes (for example IL9, IFI44, IFIT1 and IL2RA) were associated with pathways related to pattern recognition receptors and interferon signaling. We then investigated whether the unique gene expression profiles described here could be recapitulated in vivo, in individuals with active Cutaneous Leishmaniasis or with subclinical infection. Indeed, using a set of six genes (TLR2, JAK2, IFI27, IFIT1, IRF1 and IL6) modulated in HPs and LPs, we could successfully discriminate these two clinical groups. Finally, we demonstrate that these six genes are significantly overexpressed in CL lesions. Conclusion Upon interrogation of the peripheral response of naive individuals with diverging IFN-γ production to L. braziliensis, we identified differences in the innate response to the parasite that are recapitulated in vivo and that discriminate CL patients from individuals presenting a subclinical infection. PMID:27870860

  19. Gene Conversion in Human Genetic Disease

    PubMed Central

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

    2010-01-01

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

  20. Diseases originate and terminate by genes: unraveling nonviral gene delivery.

    PubMed

    Swami, Rajan; Singh, Indu; Khan, Wahid; Ramakrishna, Sistla

    2013-12-01

    The world is driving in to the era of transformation of chemical therapeutic molecules to biological genetic material therapeutics, and that is where the biological drugs especially "genes" come into existence. These genes worked as "magical bullets" to specifically silence faulty genes responsible for progression of diseases. Viral gene delivery research is far ahead of nonviral gene delivery technique. However, with more advancement in polymer science, new ways are opening for better and efficient nonviral gene delivery. But efficient delivery method is always considered as a bottleneck for gene delivery as success of which will decide the fate of gene in cells. During the past decade, it became evident that extracellular as well as intracellular barriers compromise the transfection efficiency of nonviral vectors. The challenge for gene therapy research is to pinpoint the rate-limiting steps in this complex process and implement strategies to overcome the biological physiochemical and metabolic barriers encountered during targeting. The synergy between studies that investigate the mechanism of breaking in and breaking out of nonviral gene delivery carrier through various extracellular and intracellular barriers with desired characteristics will enable the rational design of vehicles and revolutionize the treatment of various diseases.

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

    PubMed

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

    2015-07-01

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

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

    PubMed

    Pasipoularides, Ares

    2015-12-01

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

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

    PubMed

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

    2016-04-01

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

  4. Candidate diseases for prenatal gene therapy.

    PubMed

    David, Anna L; Waddington, Simon N

    2012-01-01

    Prenatal gene therapy aims to deliver genes to cells and tissues early in prenatal life, allowing correction of a genetic defect, before irreparable tissue damage has occurred. In contrast to postnatal gene therapy, prenatal application may target genes to a large population of stem cells, and the smaller fetal size allows a higher vector to target cell ratio to be achieved. Early gestation delivery may allow the development of immune tolerance to the transgenic protein, which would facilitate postnatal repeat vector administration if needed. Moreover, early delivery would avoid anti-vector immune responses which are often acquired in postnatal life. The NIH Recombinant DNA Advisory Committee considered that a candidate disease for prenatal gene therapy should pose serious morbidity and mortality risks to the fetus or neonate, and not have any effective postnatal treatment. Prenatal gene therapy would therefore be appropriate for life-threatening disorders, in which prenatal gene delivery maintains a clear advantage over cell transplantation or postnatal gene therapy. If deemed safer and more efficacious, prenatal gene therapy may be applicable for nonlethal conditions if adult gene transfer is unlikely to be of benefit. Many candidate diseases will be inherited congenital disorders such as thalassaemia or lysosomal storage disorders. However, obstetric conditions such as fetal growth restriction may also be treated using a targeted gene therapy approach. In each disease, the condition must be diagnosed prenatally, either via antenatal screening and prenatal diagnosis, for example, in the case of hemophilias, or by ultrasound assessment of the fetus, for example, congenital diaphragmatic hernia. In this chapter, we describe some examples of the candidate diseases and discuss how a prenatal gene therapy approach might work.

  5. Identifying suitable reference genes for gene expression analysis in developing skeletal muscle in pigs

    PubMed Central

    Zhang, YuanYuan; Hua, Chaoju; Wang, Zishuai; Li, Kui

    2016-01-01

    The selection of suitable reference genes is crucial to accurately evaluate and normalize the relative expression level of target genes for gene function analysis. However, commonly used reference genes have variable expression levels in developing skeletal muscle. There are few reports that systematically evaluate the expression stability of reference genes across prenatal and postnatal developing skeletal muscle in mammals. Here, we used quantitative PCR to examine the expression levels of 15 candidate reference genes (ACTB, GAPDH, RNF7, RHOA, RPS18, RPL32, PPIA, H3F3, API5, B2M, AP1S1, DRAP1, TBP, WSB, and VAPB) in porcine skeletal muscle at 26 different developmental stages (15 prenatal and 11 postnatal periods). We evaluated gene expression stability using the computer algorithms geNorm, NormFinder, and BestKeeper. Our results indicated that GAPDH and ACTB had the greatest variability among the candidate genes across prenatal and postnatal stages of skeletal muscle development. RPS18, API5, and VAPB had stable expression levels in prenatal stages, whereas API5, RPS18, RPL32, and H3F3 had stable expression levels in postnatal stages. API5 and H3F3 expression levels had the greatest stability in all tested prenatal and postnatal stages, and were the most appropriate reference genes for gene expression normalization in developing skeletal muscle. Our data provide valuable information for gene expression analysis during different stages of skeletal muscle development in mammals. This information can provide a valuable guide for the analysis of human diseases. PMID:27994956

  6. Identifying suitable reference genes for gene expression analysis in developing skeletal muscle in pigs.

    PubMed

    Niu, Guanglin; Yang, Yalan; Zhang, YuanYuan; Hua, Chaoju; Wang, Zishuai; Tang, Zhonglin; Li, Kui

    2016-01-01

    The selection of suitable reference genes is crucial to accurately evaluate and normalize the relative expression level of target genes for gene function analysis. However, commonly used reference genes have variable expression levels in developing skeletal muscle. There are few reports that systematically evaluate the expression stability of reference genes across prenatal and postnatal developing skeletal muscle in mammals. Here, we used quantitative PCR to examine the expression levels of 15 candidate reference genes (ACTB, GAPDH, RNF7, RHOA, RPS18, RPL32, PPIA, H3F3, API5, B2M, AP1S1, DRAP1, TBP, WSB, and VAPB) in porcine skeletal muscle at 26 different developmental stages (15 prenatal and 11 postnatal periods). We evaluated gene expression stability using the computer algorithms geNorm, NormFinder, and BestKeeper. Our results indicated that GAPDH and ACTB had the greatest variability among the candidate genes across prenatal and postnatal stages of skeletal muscle development. RPS18, API5, and VAPB had stable expression levels in prenatal stages, whereas API5, RPS18, RPL32, and H3F3 had stable expression levels in postnatal stages. API5 and H3F3 expression levels had the greatest stability in all tested prenatal and postnatal stages, and were the most appropriate reference genes for gene expression normalization in developing skeletal muscle. Our data provide valuable information for gene expression analysis during different stages of skeletal muscle development in mammals. This information can provide a valuable guide for the analysis of human diseases.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-12-21

    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.

  9. Integration of text- and data-mining using ontologies successfully selects disease gene candidates.

    PubMed

    Tiffin, Nicki; Kelso, Janet F; Powell, Alan R; Pan, Hong; Bajic, Vladimir B; Hide, Winston A

    2005-01-01

    Genome-wide techniques such as microarray analysis, Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS), linkage analysis and association studies are used extensively in the search for genes that cause diseases, and often identify many hundreds of candidate disease genes. Selection of the most probable of these candidate disease genes for further empirical analysis is a significant challenge. Additionally, identifying the genes that cause complex diseases is problematic due to low penetrance of multiple contributing genes. Here, we describe a novel bioinformatic approach that selects candidate disease genes according to their expression profiles. We use the eVOC anatomical ontology to integrate text-mining of biomedical literature and data-mining of available human gene expression data. To demonstrate that our method is successful and widely applicable, we apply it to a database of 417 candidate genes containing 17 known disease genes. We successfully select the known disease gene for 15 out of 17 diseases and reduce the candidate gene set to 63.3% (+/-18.8%) of its original size. This approach facilitates direct association between genomic data describing gene expression and information from biomedical texts describing disease phenotype, and successfully prioritizes candidate genes according to their expression in disease-affected tissues.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-25

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

  13. High throughput in vivo functional validation of candidate congenital heart disease genes in Drosophila.

    PubMed

    Zhu, Jun-Yi; Fu, Yulong; Nettleton, Margaret; Richman, Adam; Han, Zhe

    2017-01-20

    Genomic sequencing has implicated large numbers of genes and de novo mutations as potential disease risk factors. A high throughput in vivo model system is needed to validate gene associations with pathology. We developed a Drosophila-based functional system to screen candidate disease genes identified from Congenital Heart Disease (CHD) patients. 134 genes were tested in the Drosophila heart using RNAi-based gene silencing. Quantitative analyses of multiple cardiac phenotypes demonstrated essential structural, functional, and developmental roles for more than 70 genes, including a subgroup encoding histone H3K4 modifying proteins. We also demonstrated the use of Drosophila to evaluate cardiac phenotypes resulting from specific, patient-derived alleles of candidate disease genes. We describe the first high throughput in vivo validation system to screen candidate disease genes identified from patients. This approach has the potential to facilitate development of precision medicine approaches for CHD and other diseases associated with genetic factors.

  14. MHC Genes Linked to Autoimmune Disease.

    PubMed

    Deitiker, Philip; Atassi, M Zouhair

    2015-01-01

    Autoimmune diseases (ADs), or autoinflammatoiy diseases, are growing in complexity as diagnoses improve and many factors escalate disease risk. Considerable genetic similarity is found among ADs, and they are frequently associated with major histocompatibility complex (MHC) genes. However, a given disease may be associated with more than one human leukocyte antigen (HLA) allotype, and a given HLA may be associated with more than one AD. The associations of non-MHC genes with AD present an additional problem, and the situation is further complicated by the role that other factors, such as age, diet, therapeutic drugs, and regional influences, play in disease. This review discusses some of the genetics and biochemistry of HLA-linked AD and inflammation, covering some of the best-studied examples and summarizing indicators for class I- and II-mediated disease. However, the scope of this review limits a detailed discussion of all known ADs.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-03-01

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

  17. Identifying Unstable Regions of Proteins Involved in Misfolding Diseases

    NASA Astrophysics Data System (ADS)

    Guest, Will; Cashman, Neil; Plotkin, Steven

    2009-05-01

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

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

    PubMed

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

    2011-10-01

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

  19. 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.

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

    PubMed Central

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

    2014-01-01

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

  1. A New Strategy to Identify and Annotate Human RPE-Specific Gene Expression

    PubMed Central

    Booij, Judith C.; ten Brink, Jacoline B.; Swagemakers, Sigrid M. A.; Verkerk, Annemieke J. M. H.; Essing, Anke H. W.; van der Spek, Peter J.; Bergen, Arthur A. B.

    2010-01-01

    Background To identify and functionally annotate cell type-specific gene expression in the human retinal pigment epithelium (RPE), a key tissue involved in age-related macular degeneration and retinitis pigmentosa. Methodology RPE, photoreceptor and choroidal cells were isolated from selected freshly frozen healthy human donor eyes using laser microdissection. RNA isolation, amplification and hybridization to 44 k microarrays was carried out according to Agilent specifications. Bioinformatics was carried out using Rosetta Resolver, David and Ingenuity software. Principal Findings Our previous 22 k analysis of the RPE transcriptome showed that the RPE has high levels of protein synthesis, strong energy demands, is exposed to high levels of oxidative stress and a variable degree of inflammation. We currently use a complementary new strategy aimed at the identification and functional annotation of RPE-specific expressed transcripts. This strategy takes advantage of the multilayered cellular structure of the retina and overcomes a number of limitations of previous studies. In triplicate, we compared the transcriptomes of RPE, photoreceptor and choroidal cells and we deduced RPE specific expression. We identified at least 114 entries with RPE-specific gene expression. Thirty-nine of these 114 genes also show high expression in the RPE, comparison with the literature showed that 85% of these 39 were previously identified to be expressed in the RPE. In the group of 114 RPE specific genes there was an overrepresentation of genes involved in (membrane) transport, vision and ophthalmic disease. More fundamentally, we found RPE-specific involvement in the RAR-activation, retinol metabolism and GABA receptor signaling pathways. Conclusions In this study we provide a further specification and understanding of the RPE transcriptome by identifying and analyzing genes that are specifically expressed in the RPE. PMID:20479888

  2. Identifying Aβ-specific pathogenic mechanisms using a nematode model of Alzheimer’s disease

    PubMed Central

    Dostal, Vishantie; Huemann, Brady N.; Yerg, John E.; Link, Christopher D.

    2014-01-01

    Multiple gene expression alterations have been linked to Alzheimer’s disease (AD), implicating multiple metabolic pathways in its pathogenesis. However, a clear distinction between AD-specific gene expression changes and those resulting from non-specific responses to toxic aggregating proteins has not been made. We investigated alterations in gene expression induced by human β-amyloid peptide (Aβ) in a Caenorhabditis elegans Alzheimer’s disease model. Aβ-induced gene expression alterations were compared to those caused by a synthetic aggregating protein to identify Aβ-specific effects. Both Aβ-specific and non-specific alterations were observed. Among Aβ-specific genes were those involved in aging, proteasome function, and mitochondrial function. An intriguing observation was the significant overlap between gene expression changes induced by Aβ and those induced by Cry5B, a bacterial pore-forming toxin. This led us to hypothesize that Aβ exerts its toxic effect, at least in part, by causing damage to biological membranes. We provide in vivo evidence consistent with this hypothesis. This study distinguishes between Aβ-specific and non-specific mechanisms and provides potential targets for therapeutics discovery. PMID:25457027

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-12-01

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

  5. Interference, heterogeneity and disease gene mapping

    SciTech Connect

    Keats, B.

    1996-12-31

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

  6. Expressed sequences tags of the anther smut fungus, Microbotryum violaceum, identify mating and pathogenicity genes

    PubMed Central

    Yockteng, Roxana; Marthey, Sylvain; Chiapello, Hélène; Gendrault, Annie; Hood, Michael E; Rodolphe, François; Devier, Benjamin; Wincker, Patrick; Dossat, Carole; Giraud, Tatiana

    2007-01-01

    Background The basidiomycete fungus Microbotryum violaceum is responsible for the anther-smut disease in many plants of the Caryophyllaceae family and is a model in genetics and evolutionary biology. Infection is initiated by dikaryotic hyphae produced after the conjugation of two haploid sporidia of opposite mating type. This study describes M. violaceum ESTs corresponding to nuclear genes expressed during conjugation and early hyphal production. Results A normalized cDNA library generated 24,128 sequences, which were assembled into 7,765 unique genes; 25.2% of them displayed significant similarity to annotated proteins from other organisms, 74.3% a weak similarity to the same set of known proteins, and 0.5% were orphans. We identified putative pheromone receptors and genes that in other fungi are involved in the mating process. We also identified many sequences similar to genes known to be involved in pathogenicity in other fungi. The M. violaceum EST database, MICROBASE, is available on the Web and provides access to the sequences, assembled contigs, annotations and programs to compare similarities against MICROBASE. Conclusion This study provides a basis for cloning the mating type locus, for further investigation of pathogenicity genes in the anther smut fungi, and for comparative genomics. PMID:17692127

  7. 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

  8. Progressive retinal atrophy in Schapendoes dogs: mutation of the newly identified CCDC66 gene.

    PubMed

    Dekomien, Gabriele; Vollrath, Conni; Petrasch-Parwez, Elisabeth; Boevé, Michael H; Akkad, Denis A; Gerding, Wanda M; Epplen, Jörg T

    2010-05-01

    Canine generalized progressive retinal atrophy (gPRA) is characterized by continuous degeneration of photoreceptor cells leading to night blindness and progressive vision loss. Until now, mutations in 11 genes have been described that account for gPRA in dogs, mostly following an autosomal recessive inheritance mode. Here, we describe a gPRA locus comprising the newly identified gene coiled-coil domain containing 66 (CCDC66) on canine chromosome 20, as identified via linkage analysis in the Schapendoes breed. Mutation screening of the CCDC66 gene revealed a 1-bp insertion in exon 6 leading to a stop codon as the underlying cause of disease. The insertion is present in all affected dogs in the homozygous state as well as in all obligatory mutation carriers in the heterozygous state. The CCDC66 gene is evolutionarily conserved in different vertebrate species and exhibits a complex pattern of differential RNA splicing resulting in various isoforms in the retina. Immunohistochemically, CCDC66 protein is detected mainly in the inner segments of photoreceptors in mouse, dog, and man. The affected Schapendoes retina lacks CCDC66 protein. Thus this natural canine model for gPRA yields superior potential to understand functional implications of this newly identified protein including its physiology, and it opens new perspectives for analyzing different aspects of the general pathophysiology of gPRA.

  9. Gene Therapy Techniques for Peripheral Arterial Disease

    SciTech Connect

    Manninen, Hannu I.; Maekinen, Kimmo

    2002-03-15

    Somatic gene therapy is the introduction of new genetic material into selective somatic cells with resulting therapeutic benefits. Vascular wall and, subsequently, cardiovascular diseases have become an interesting target for gene therapy studies.Arteries are an attractive target for gene therapy since vascular interventions, both open surgical and endovascular, are well suited for minimally invasive, easily monitored gene delivery. Promising therapeutic effects have been obtained in animal models in preventing post-angioplasty restenosis and vein graft thickening, as well as increasing blood flow and collateral development in ischemic limbs.First clinical trials suggest a beneficial effect of vascular endothelial growth factor in achieving therapeutic angiogenesis in chronic limb ischemia and the efficacy of decoy oligonucleotides to prevent infrainguinal vein graft stenosis. However, further studies are mandatory to clarify the safety issues, to develop better gene delivery vectors and delivery catheters, to improve transgene expression, as well as to find the most effective and safe treatment genes.

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

    PubMed Central

    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.

    2014-01-01

    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 (FFPE) 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 (BCR). 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. PMID:24713434

  11. 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

  12. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications

    PubMed Central

    Iddamalgoda, Lahiru; Das, Partha S.; Aponso, Achala; Sundararajan, Vijayaraghava S.; Suravajhala, Prashanth; Valadi, Jayaraman K.

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation. PMID:27559342

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

    PubMed

    Zaina, S; Lund, G

    2012-04-01

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

  14. Functional gene group analysis identifies synaptic gene groups as risk factor for schizophrenia

    PubMed Central

    Lips, E S; Cornelisse, L N; Toonen, R F; Min, J L; Hultman, C M; Holmans, P A; O'Donovan, M C; Purcell, S M; Smit, A B; Verhage, M; Sullivan, P F; Visscher, P M; Posthuma, D

    2012-01-01

    Schizophrenia is a highly heritable disorder with a polygenic pattern of inheritance and a population prevalence of ∼1%. Previous studies have implicated synaptic dysfunction in schizophrenia. We tested the accumulated association of genetic variants in expert-curated synaptic gene groups with schizophrenia in 4673 cases and 4965 healthy controls, using functional gene group analysis. Identifying groups of genes with similar cellular function rather than genes in isolation may have clinical implications for finding additional drug targets. We found that a group of 1026 synaptic genes was significantly associated with the risk of schizophrenia (P=7.6 × 10−11) and more strongly associated than 100 randomly drawn, matched control groups of genetic variants (P<0.01). Subsequent analysis of synaptic subgroups suggested that the strongest association signals are derived from three synaptic gene groups: intracellular signal transduction (P=2.0 × 10−4), excitability (P=9.0 × 10−4) and cell adhesion and trans-synaptic signaling (P=2.4 × 10−3). These results are consistent with a role of synaptic dysfunction in schizophrenia and imply that impaired intracellular signal transduction in synapses, synaptic excitability and cell adhesion and trans-synaptic signaling play a role in the pathology of schizophrenia. PMID:21931320

  15. Functional gene group analysis identifies synaptic gene groups as risk factor for schizophrenia.

    PubMed

    Lips, E S; Cornelisse, L N; Toonen, R F; Min, J L; Hultman, C M; Holmans, P A; O'Donovan, M C; Purcell, S M; Smit, A B; Verhage, M; Sullivan, P F; Visscher, P M; Posthuma, D

    2012-10-01

    Schizophrenia is a highly heritable disorder with a polygenic pattern of inheritance and a population prevalence of ~1%. Previous studies have implicated synaptic dysfunction in schizophrenia. We tested the accumulated association of genetic variants in expert-curated synaptic gene groups with schizophrenia in 4673 cases and 4965 healthy controls, using functional gene group analysis. Identifying groups of genes with similar cellular function rather than genes in isolation may have clinical implications for finding additional drug targets. We found that a group of 1026 synaptic genes was significantly associated with the risk of schizophrenia (P=7.6 × 10(-11)) and more strongly associated than 100 randomly drawn, matched control groups of genetic variants (P<0.01). Subsequent analysis of synaptic subgroups suggested that the strongest association signals are derived from three synaptic gene groups: intracellular signal transduction (P=2.0 × 10(-4)), excitability (P=9.0 × 10(-4)) and cell adhesion and trans-synaptic signaling (P=2.4 × 10(-3)). These results are consistent with a role of synaptic dysfunction in schizophrenia and imply that impaired intracellular signal transduction in synapses, synaptic excitability and cell adhesion and trans-synaptic signaling play a role in the pathology of schizophrenia.

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

    PubMed

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

    2012-01-01

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

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

    PubMed Central

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

    2012-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Curing genetic disease with gene therapy.

    PubMed

    Williams, David A

    2014-01-01

    Development of viral vectors that allow high efficiency gene transfer into mammalian cells in the early 1980s foresaw the treatment of severe monogenic diseases in humans. The application of gene transfer using viral vectors has been successful in diseases of the blood and immune systems, albeit with several curative studies also showing serious adverse events (SAEs). In children with X-linked severe combined immunodeficiency (SCID-X1), chronic granulomatous disease, and Wiskott-Aldrich syndrome, these SAEs were caused by inappropriate activation of oncogenes. Subsequent studies have defined the vector sequences responsible for these transforming events. Members of the Transatlantic Gene Therapy Consortium [TAGTC] have collaboratively developed new vectors that have proven safer in preclinical studies and used these vectors in new clinical trials in SCID-X1. These trials have shown evidence of early efficacy and preliminary integration analysis data from the SCID-X1 trial suggest an improved safety profile.

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

    PubMed Central

    2015-01-01

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

  1. An introduction to genes, genomes and disease.

    PubMed

    Hall, Peter A; Reis-Filho, Jorge S; Tomlinson, Ian Pm; Poulsom, Richard

    2010-01-01

    The human and other genome projects and subsequent resequencing programmes have provided new perspectives on the nature of the gene and how genes function. Understanding the complexity of the eukaryotic nucleus and the diversity of genetic regulatory mechanisms, including the role of non-coding RNAs, translational control mechanisms and the extraordinary prevalence of splicing, will be central to understanding how genes function, as will the recognition of gene dosage issues. This introduction to the 2010 Annual Review Issue, Genes, Genomes and Disease, provides overviews of these areas and then considers their relevance to a range of human diseases, including cardiovascular and renal disease, neural tube defects and cancer. The p53 gene is considered as an example of a massively regulated gene and the genetic perturbations in cancer are considered in a historical perspective. High-throughput genomic and transcriptomic methods have led to a paradigm shift in the way cancers are perceived and have changed the way translational research is performed. The progress in our understanding of chromosomal rearrangements in cancer, once believed to be incredibly rare events in epithelial malignancies, is discussed. The identification of low-penetrance cancer susceptibility genes through genome-wide association studies and their implications are reviewed. The contribution and limitations of expression profiling are discussed. In the last series of reviews, future challenges are addressed: the promise of synthetic lethality strategies in cancer therapy, a case for 'systems' approaches to genetic networks and the potential of single molecule genetic technologies. Finally, the question 'Does massively parallel DNA resequencing signify the end of histopathology as we know it?' is posed. Readers should find that the 2010 Annual Review Issue is an invaluable resource on contemporary genetics and its applications to understanding disease.

  2. Gene therapy in Alzheimer's disease - potential for disease modification.

    PubMed

    Nilsson, Per; Iwata, Nobuhisa; Muramatsu, Shin-ichi; Tjernberg, Lars O; Winblad, Bengt; Saido, Takaomi C

    2010-04-01

    Alzheimer's disease (AD) is the major cause of dementia in the elderly, leading to memory loss and cognitive decline. The mechanism underlying onset of the disease has not been fully elucidated. However, characteristic pathological manifestations include extracellular accumulation and aggregation of the amyloid beta-peptide (Abeta) into plaques and intracellular accumulation and aggregation of hyperphosphorylated tau, forming neurofibrillary tangles. Despite extensive research worldwide, no disease modifying treatment is yet available. In this review, we focus on gene therapy as a potential treatment for AD, and summarize recent work in the field, ranging from proof-of-concept studies in animal models to clinical trials. The multifactorial causes of AD offer a variety of possible targets for gene therapy, including two neurotrophic growth factors, nerve growth factor and brain-derived neurotrophic factor, Abeta-degrading enzymes, such as neprilysin, endothelin-converting enzyme and cathepsin B, and AD associated apolipoprotein E. This review also discusses advantages and drawbacks of various rapidly developing virus-mediated gene delivery techniques for gene therapy. Finally, approaches aiming at down-regulating amyloid precursor protein (APP) and beta-site APP cleaving enzyme 1 levels by means of siRNA-mediated knockdown are briefly summarized. Overall, the prospects appear hopeful that gene therapy has the potential to be a disease modifying treatment for AD.

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

    PubMed

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

    2015-10-08

    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.

  4. Genetic mapping and exome sequencing identify variants associated with five novel diseases.

    PubMed

    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.

  5. 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

  6. Identifying nonspecific SAGE tags by context of gene expression.

    PubMed

    Ge, Xijin; Wang, San Ming

    2008-01-01

    Many serial analysis of gene expression (SAGE) tags can be matched to multiple genes, leading to difficulty in SAGE data interpretation and analysis. As only a subset of genes in the human genome are transcribed in a certain type of tissue/cell, we used microarray expression data from different tissue types to define contexts of gene expression and to annotate SAGE tags collected from the same or similar tissue sources. To predict the original transcript contributing a nonspecific SAGE tag collected from a particular tissue, we ranked the corresponding genes by their expression levels determined by microarray. We developed a tissue-specific SAGE tag annotation database based on microarray data collected from 73 normal human tissues and 18 cancer tissues and cell lines. The database can be queried online at: http://www.basic.northwestern.edu/SAGE/. The accuracy of this database was confirmed by experimental data.

  7. An in vivo screening system to identify tumorigenic genes.

    PubMed

    Ihara, T; Hosokawa, Y; Kumazawa, K; Ishikawa, K; Fujimoto, J; Yamamoto, M; Muramkami, T; Goshima, N; Ito, E; Watanabe, S; Semba, K

    2017-04-06

    Screening for oncogenes has mostly been performed by in vitro transformation assays. However, some oncogenes might not exhibit their transforming activities in vitro unless putative essential factors from in vivo microenvironments are adequately supplied. Here, we have developed an in vivo screening system that evaluates the tumorigenicity of target genes. This system uses a retroviral high-efficiency gene transfer technique, a large collection of human cDNA clones corresponding to ~70% of human genes and a luciferase-expressing immortalized mouse mammary epithelial cell line (NMuMG-luc). From 845 genes that were highly expressed in human breast cancer cell lines, we focused on 205 genes encoding membrane proteins and/or kinases as that had the greater possibility of being oncogenes or drug targets. The 205 genes were divided into five subgroups, each containing 34-43 genes, and then introduced them into NMuMG-luc cells. These cells were subcutaneously injected into nude mice and monitored for tumor development by in vivo imaging. Tumors were observed in three subgroups. Using DNA microarray analyses and individual tumorigenic assays, we found that three genes, ADORA2B, PRKACB and LPAR3, were tumorigenic. ADORA2B and LPAR3 encode G-protein-coupled receptors and PRKACB encodes a protein kinase A catalytic subunit. Cells overexpressing ADORA2B, LPAR3 or PRKACB did not show transforming phenotypes in vitro, suggesting that transformation by these genes requires in vivo microenvironments. In addition, several clinical data sets, including one for breast cancer, showed that the expression of these genes correlated with lower overall survival rate.

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

    PubMed

    Sazonova, Olga; Zhao, Yuqi; Nürnberg, Sylvia; Miller, Clint; Pjanic, Milos; Castano, Victor G; Kim, Juyong B; Salfati, Elias L; Kundaje, Anshul B; Bejerano, Gill; Assimes, Themistocles; Yang, Xia; Quertermous, Thomas

    2015-05-01

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

  9. Microarray analysis of hepatic gene expression identifies new genes involved in steatotic liver

    PubMed Central

    Guillén, Natalia; Navarro, María A.; Arnal, Carmen; Noone, Enda; Arbonés-Mainar, José M.; Acín, Sergio; Surra, Joaquín C.; Muniesa, Pedro; Roche, Helen M.; Osada, Jesús

    2009-01-01

    Trans-10, cis-12-conjugated linoleic acid (CLA)-enriched diets promote fatty liver in mice, while cis-9, trans-11-CLA ameliorates this effect, suggesting regulation of multiple genes. To test this hypothesis, apoE-deficient mice were fed a Western-type diet enriched with linoleic acid isomers, and their hepatic gene expression was analyzed with DNA microarrays. To provide an initial screening of candidate genes, only 12 with remarkably modified expression between both CLA isomers were considered and confirmed by quantitative RT-PCR. Additionally mRNA expression of 15 genes involved in lipid metabolism was also studied. Ten genes (Fsp27, Aqp4, Cd36, Ly6d, Scd1, Hsd3b5, Syt1, Cyp7b1, and Tff3) showed significant associations among their expressions and the degree of hepatic steatosis. Their involvement was also analyzed in other models of steatosis. In hyperhomocysteinemic mice lacking Cbs gene, only Fsp27, Cd36, Scd1, Syt1, and Hsd3b5 hepatic expressions were associated with steatosis. In apoE-deficient mice consuming olive-enriched diet displaying reduction of the fatty liver, only Fsp27 and Syt1 expressions were found associated. Using this strategy, we have shown that expression of these genes is highly associated with hepatic steatosis in a genetic disease such as Cbs deficiency and in two common situations such as Western diets containing CLA isomers or a Mediterranean-type diet. Conclusion: The results highlight new processes involved in lipid handling in liver and will help to understand the complex human pathology providing new proteins and new strategies to cope with hepatic steatosis. PMID:19258494

  10. Gene therapy for human genetic disease?

    PubMed

    Friedmann, T; Roblin, R

    1972-03-03

    In our view, gene therapy may ameliorate some human genetic diseases in the future. For this reason, we believe that research directed at the development of techniques for gene therapy should continue. For the foreseeable future, however, we oppose any further attempts at gene therapy in human patients because (i) our understanding of such basic processes as gene regulation and genetic recombination in human cells is inadequate; (ii) our understanding of the details of the relation between the molecular defect and the disease state is rudimentary for essentially all genetic diseases; and (iii) we have no information on the short-range and long-term side effects of gene therapy. We therefore propose that a sustained effort be made to formulate a complete set of ethicoscientific criteria to guide the development and clinical application of gene therapy techniques. Such an endeavor could go a long way toward ensuring that gene therapy is used in humans only in those instances where it will prove beneficial, and toward preventing its misuse through premature application. Two recent papers have provided new demonstrations of directed genetic modification of mammalian cells. Munyon et al. (44) restored the ability to synthesize the enzyme thymidine kinase to thymidine kinase-deficient mouse cells by infection with ultraviolet-irradiated herpes simplex virus. In their experiments the DNA from herpes simplex virus, which contains a gene coding for thymidine kinase, may have formed a hereditable association with the mouse cells. Merril et al. (45) reported that treatment of fibroblasts from patients with galactosemia with exogenous DNA caused increased activity of a missing enzyme, alpha-D-galactose-l-phosphate uridyltransferase. They also provided some evidence that the change persisted after subculturing the treated cells. If this latter report can be confirmed, the feasibility of directed genetic modification of human cells would be clearly demonstrated, considerably

  11. Gene expression profiling identifies distinct molecular subgroups of leiomyosarcoma with clinical relevance

    PubMed Central

    Lee, Yin-Fai; Roe, Toby; Mangham, D Chas; Fisher, Cyril; Grimer, Robert J; Judson, Ian

    2016-01-01

    Background: Soft tissue sarcomas are heterogeneous and a major complication in their management is that the existing classification scheme is not definitive and is still evolving. Leiomyosarcomas, a major histologic category of soft tissue sarcomas, are malignant tumours displaying smooth muscle differentiation. Although defined as a single group, they exhibit a wide range of clinical behaviour. We aimed to carry out molecular classification to identify new molecular subgroups with clinical relevance. Methods: We used gene expression profiling on 20 extra-uterine leiomyosarcomas and cross-study analyses for molecular classification of leiomyosarcomas. Clinical significance of the subgroupings was investigated. Results: We have identified two distinct molecular subgroups of leiomyosarcomas. One group was characterised by high expression of 26 genes that included many genes from the sub-classification gene cluster proposed by Nielsen et al. These sub-classification genes include genes that have importance structurally, as well as in cell signalling. Notably, we found a statistically significant association of the subgroupings with tumour grade. Further refinement led to a group of 15 genes that could recapitulate the tumour subgroupings in our data set and in a second independent sarcoma set. Remarkably, cross-study analyses suggested that these molecular subgroups could be found in four independent data sets, providing strong support for their existence. Conclusions: Our study strongly supported the existence of distinct leiomyosarcoma molecular subgroups, which have clinical association with tumour grade. Our findings will aid in advancing the classification of leiomyosarcomas and lead to more individualised and better management of the disease. PMID:27607470

  12. Progress in gene therapy of dystrophic heart disease.

    PubMed

    Lai, Y; Duan, D

    2012-06-01

    The heart is frequently afflicted in muscular dystrophy. In severe cases, cardiac lesion may directly result in death. Over the years, pharmacological and/or surgical interventions have been the mainstay to alleviate cardiac symptoms in muscular dystrophy patients. Although these traditional modalities remain useful, the emerging field of gene therapy has now provided an unprecedented opportunity to transform our thinking/approach in the treatment of dystrophic heart disease. In fact, the premise is already in place for genetic correction. Gene mutations have been identified and animal models are available for several types of muscular dystrophy. Most importantly, innovative strategies have been developed to effectively deliver therapeutic genes to the heart. Dystrophin-deficient Duchenne cardiomyopathy is associated with Duchenne muscular dystrophy (DMD), the most common lethal muscular dystrophy. Considering its high incidence, there has been a considerable interest and significant input in the development of Duchenne cardiomyopathy gene therapy. Using Duchenne cardiomyopathy as an example, here we illustrate the struggles and successes experienced in the burgeoning field of dystrophic heart disease gene therapy. In light of abundant and highly promising data with the adeno-associated virus (AAV) vector, we have specially emphasized on AAV-mediated gene therapy. Besides DMD, we have also discussed gene therapy for treating cardiac diseases in other muscular dystrophies such as limb-girdle muscular dystrophy.

  13. Gene expression in human hippocampus from cocaine abusers identifies genes which regulate extracellular matrix remodeling.

    PubMed

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

    2007-11-14

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

  14. Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.

    PubMed

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

    2012-01-01

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

  15. An analysis of disease-gene relationship from Medline abstracts by DigSee

    PubMed Central

    Kim, Jeongkyun; Kim, Jung-jae; Lee, Hyunju

    2017-01-01

    Diseases are developed by abnormal behavior of genes in biological events such as gene regulation, mutation, phosphorylation, and epigenetics and post-translational modification. Many studies of text mining attempted to identify the relationship between gene and disease by mining the literature, but they did not consider the biological events in which genes show abnormal behaviour in response to diseases. In this study, we propose to identify disease-related genes that are involved in the development of disease through biological events from Medline abstracts. We identified associations between 13,054 genes and 4,494 disease types, which cover more disease-related genes than manually curated databases for all disease types (e.g., Online Mendelian Inheritance in Man) and also than those for specific diseases (e.g., Alzheimer’s disease and hypertension). We show that the text mining findings are reliable, as per the PubMed scale, in that the disease-disease relationships inferred from the literature-wide findings are similar to those inferred from manually curated databases in a well-known study. In addition, literature-wide distribution of biological events across disease types reveals different characteristics of disease types. PMID:28054646

  16. Genome-wide Linkage Screen in Familial Parkinson Disease Identifies Loci on Chromosomes 3 and 18

    PubMed Central

    Gao, Xiaoyi; Martin, Eden R.; Liu, Yutao; Mayhew, Gregory; Vance, Jeffery M.; Scott, William K.

    2009-01-01

    Parkinson disease (PD) is a complex, multifactorial neurodegenerative disease with substantial evidence for genetic risk factors. We conducted a genome-wide linkage screen of 5824 single-nucleotide polymorphisms in 278 families of European, non-Hispanic descent to localize regions that harbor susceptibility loci for PD. By using parametric and nonparametric linkage analyses and allowing for genetic heterogeneity among families, we found two loci for PD. Significant evidence for linkage was detected on chromosome 18q11 (maximum lod score [MLOD] = 4.1) and suggestive evidence for linkage was obtained on chromosome 3q25 (MLOD = 2.5). These results were strongest in families not previously screened for linkage, and simulation studies suggest that these findings are likely due to locus heterogeneity rather than random statistical error. The finding of two loci (one highly statistically significant) suggests that additional PD susceptibility genes might be identified through targeted candidate gene studies in these regions. PMID:19327735

  17. A molecular signature in blood identifies early Parkinson’s disease

    PubMed Central

    2012-01-01

    Background The search for biomarkers in Parkinson’s disease (PD) is crucial to identify the disease early and monitor the effectiveness of neuroprotective therapies. We aim to assess whether a gene signature could be detected in blood from early/mild PD patients that could support the diagnosis of early PD, focusing on genes found particularly altered in the substantia nigra of sporadic PD. Results The transcriptional expression of seven selected genes was examined in blood samples from 62 early stage PD patients and 64 healthy age-matched controls. Stepwise multivariate logistic regression analysis identified five genes as optimal predictors of PD: p19 S-phase kinase-associated protein 1A (odds ratio [OR] 0.73; 95% confidence interval [CI] 0.60–0.90), huntingtin interacting protein-2 (OR 1.32; CI 1.08–1.61), aldehyde dehydrogenase family 1 subfamily A1 (OR 0.86; 95% CI 0.75–0.99), 19 S proteasomal protein PSMC4 (OR 0.73; 95% CI 0.60–0.89) and heat shock 70-kDa protein 8 (OR 1.39; 95% CI 1.14–1.70). At a 0.5 cut-off the gene panel yielded a sensitivity and specificity in detecting PD of 90.3 and 89.1 respectively and the area under the receiving operating curve (ROC AUC) was 0.96. The performance of the five-gene classifier on the de novo PD individuals alone composing the early PD cohort (n = 38), resulted in a similar ROC with an AUC of 0.95, indicating the stability of the model and also, that patient medication had no significant effect on the predictive probability (PP) of the classifier for PD risk. The predictive ability of the model was validated in an independent cohort of 30 patients at advanced stage of PD, classifying correctly all cases as PD (100% sensitivity). Notably, the nominal average value of the PP for PD (0.95 (SD = 0.09)) in this cohort was higher than that of the early PD group (0.83 (SD = 0.22)), suggesting a potential for the model to assess disease severity. Lastly, the gene panel fully discriminated between PD

  18. Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression.

    PubMed

    Zhang, Shao-Wu; Shao, Dong-Dong; Zhang, Song-Yao; Wang, Yi-Bin

    2014-06-01

    The identification of disease genes is very important not only to provide greater understanding of gene function and cellular mechanisms which drive human disease, but also to enhance human disease diagnosis and treatment. Recently, high-throughput techniques have been applied to detect dozens or even hundreds of candidate genes. However, experimental approaches to validate the many candidates are usually time-consuming, tedious and expensive, and sometimes lack reproducibility. Therefore, numerous theoretical and computational methods (e.g. network-based approaches) have been developed to prioritize candidate disease genes. Many network-based approaches implicitly utilize the observation that genes causing the same or similar diseases tend to correlate with each other in gene-protein relationship networks. Of these network approaches, the random walk with restart algorithm (RWR) is considered to be a state-of-the-art approach. To further improve the performance of RWR, we propose a novel method named ESFSC to identify disease-related genes, by enlarging the seed set according to the centrality of disease genes in a network and fusing information of the protein-protein interaction (PPI) network topological similarity and the gene expression correlation. The ESFSC algorithm restarts at all of the nodes in the seed set consisting of the known disease genes and their k-nearest neighbor nodes, then walks in the global network separately guided by the similarity transition matrix constructed with PPI network topological similarity properties and the correlational transition matrix constructed with the gene expression profiles. As a result, all the genes in the network are ranked by weighted fusing the above results of the RWR guided by two types of transition matrices. Comprehensive simulation results of the 10 diseases with 97 known disease genes collected from the Online Mendelian Inheritance in Man (OMIM) database show that ESFSC outperforms existing methods for

  19. Epidermal growth factor gene is a newly identified candidate gene for gout

    PubMed Central

    Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

    2016-01-01

    Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67–0.88, Padjusted = 6.42 × 10−3). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations. PMID:27506295

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

    PubMed Central

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

    2016-01-01

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

  1. Systems Approaches to Identifying Gene Regulatory Networks in Plants

    PubMed Central

    Long, Terri A.; Brady, Siobhan M.; Benfey, Philip N.

    2009-01-01

    Complex gene regulatory networks are composed of genes, noncoding RNAs, proteins, metabolites, and signaling components. The availability of genome-wide mutagenesis libraries; large-scale transcriptome, proteome, and metabalome data sets; and new high-throughput methods that uncover protein interactions underscores the need for mathematical modeling techniques that better enable scientists to synthesize these large amounts of information and to understand the properties of these biological systems. Systems biology approaches can allow researchers to move beyond a reductionist approach and to both integrate and comprehend the interactions of multiple components within these systems. Descriptive and mathematical models for gene regulatory networks can reveal emergent properties of these plant systems. This review highlights methods that researchers are using to obtain large-scale data sets, and examples of gene regulatory networks modeled with these data. Emergent properties revealed by the use of these network models and perspectives on the future of systems biology are discussed. PMID:18616425

  2. A modifier screen identifies DNAJB6 as a cardiomyopathy susceptibility gene

    PubMed Central

    Ding, Yonghe; Long, Pamela A.; Bos, J. Martijn; Shih, Yu-Huan; Ma, Xiao; Sundsbak, Rhianna S.; Chen, Jianhua; Zhao, Liqun; Hu, Xinyang; Wang, Jianan; Shi, Yongyong; Ackerman, Michael J.; Lin, Xueying; Ekker, Stephen C.; Redfield, Margaret M.; Olson, Timothy M.

    2016-01-01

    Mutagenesis screening is a powerful forward genetic approach that has been successfully applied in lower-model organisms to discover genetic factors for biological processes. This phenotype-based approach has yet to be established in vertebrates for probing major human diseases, largely because of the complexity of colony management. Herein, we report a rapid strategy for identifying genetic modifiers of cardiomyopathy (CM). Based on the application of doxorubicin stress to zebrafish insertional cardiac (ZIC) mutants, we identified 4 candidate CM-modifying genes, of which 3 have been linked previously to CM. The long isoform of DnaJ (Hsp40) homolog, subfamily B, member 6b (dnajb6b(L)) was identified as a CM susceptibility gene, supported by identification of rare variants in its human ortholog DNAJB6 from CM patients. Mechanistic studies indicated that the deleterious, loss-of-function modifying effects of dnajb6b(L) can be ameliorated by inhibition of ER stress. In contrast, overexpression of dnajb6(L) exerts cardioprotective effects on both fish and mouse CM models. Together, our findings establish a mutagenesis screening strategy that is scalable for systematic identification of genetic modifiers of CM, feasible to suggest therapeutic targets, and expandable to other major human diseases. PMID:27642634

  3. Identification of therapeutic targets for Alzheimer's disease via differentially expressed gene and weighted gene co-expression network analyses.

    PubMed

    Jia, Yujie; Nie, Kun; Li, Jing; Liang, Xinyue; Zhang, Xuezhu

    2016-11-01

    In order to investigate the pathogenic targets and associated biological process of Alzheimer's disease in the present study, mRNA expression profiles (GSE28146) and microRNA (miRNA) expression profiles (GSE16759) were downloaded from the Gene Expression Omnibus database. In GSE28146, eight control samples, and Alzheimer's disease samples comprising seven incipient, eight moderate, seven severe Alzheimer's disease samples, were included. The Affy package in R was used for background correction and normalization of the raw microarray data. The differentially expressed genes (DEGs) and differentially expressed miRNAs were identified using the Limma package. In addition, mRNAs were clustered using weighted gene correlation network analysis, and modules found to be significantly associated with the stages of Alzheimer's disease were screened out. The Database for Annotation, Visualization, and Integrated Discovery was used to perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. The target genes of the differentially expressed miRNAs were identified using the miRWalk database. Compared with the control samples, 175,59 genes and 90 DEGs were identified in the incipient, moderate and severe Alzheimer's disease samples, respectively. A module, which contained 1,592 genes was found to be closely associated with the stage of Alzheimer's disease and biological processes. In addition, pathways associated with Alzheimer's disease and other neurological diseases were found to be enriched in those genes. A total of 139 overlapped genes were identified between those genes and the DEGs in the three groups. From the miRNA expression profiles, 189 miRNAs were found differentially expressed in the samples from patients with Alzheimer's disease and 1,647 target genes were obtained. In addition, five overlapped genes were identified between those 1,647 target genes and the 139 genes, and these genes may be important pathogenic targets for Alzheimer

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2014-02-01

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

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

    PubMed Central

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

    2015-01-01

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

  8. Gene Therapy for "Bubble Boy" Disease.

    PubMed

    Hoggatt, Jonathan

    2016-07-14

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

  9. A novel homozygous mutation in SUCLA2 gene identified by exome sequencing

    PubMed Central

    Lamperti, Costanza; Fang, Mingyan; Invernizzi, Federica; Liu, Xuanzhu; Wang, Hairong; Zhang, Qing; Carrara, Franco; Moroni, Isabella; Zeviani, Massimo; Zhang, Jianguo; Ghezzi, Daniele

    2012-01-01

    Mitochondrial disorders with multiple mitochondrial respiratory chain (MRC) enzyme deficiency and depletion of mitochondrial DNA (mtDNA) are autosomal recessive conditions due to mutations in several nuclear genes necessary for proper mtDNA maintenance. In this report, we describe two Italian siblings presenting with encephalomyopathy and mtDNA depletion in muscle. By whole exome-sequencing and prioritization of candidate genes, we identified a novel homozygous missense mutation in the SUCLA2 gene in a highly conserved aminoacid residue. Although a recurrent mutation in the SUCLA2 gene is relatively frequent in the Faroe Islands, mutations in other populations are extremely rare. In contrast with what has been reported in other patients, methyl-malonic aciduria, a biomarker for this genetic defect, was absent in our proband and very mildly elevated in her affected sister. This report demonstrates that next-generation technologies, particularly exome-sequencing, are user friendly, powerful means for the identification of disease genes in genetically and clinically heterogeneous inherited conditions, such as mitochondrial disorders. PMID:23010432

  10. A network-based phenotype mapping approach to identify genes that modulate drug response phenotypes

    PubMed Central

    Cairns, Junmei; Ung, Choong Yong; da Rocha, Edroaldo Lummertz; Zhang, Cheng; Correia, Cristina; Weinshilboum, Richard; Wang, Liewei; Li, Hu

    2016-01-01

    To better address the problem of drug resistance during cancer chemotherapy and explore the possibility of manipulating drug response phenotypes, we developed a network-based phenotype mapping approach (P-Map) to identify gene candidates that upon perturbed can alter sensitivity to drugs. We used basal transcriptomics data from a panel of human lymphoblastoid cell lines (LCL) to infer drug response networks (DRNs) that are responsible for conferring response phenotypes for anthracycline and taxane, two common anticancer agents use in clinics. We further tested selected gene candidates that interact with phenotypic differentially expressed genes (PDEGs), which are up-regulated genes in LCL for a given class of drug response phenotype in triple-negative breast cancer (TNBC) cells. Our results indicate that it is possible to manipulate a drug response phenotype, from resistant to sensitive or vice versa, by perturbing gene candidates in DRNs and suggest plausible mechanisms regulating directionality of drug response sensitivity. More important, the current work highlights a new way to formulate systems-based therapeutic design: supplementing therapeutics that aim to target disease culprits with phenotypic modulators capable of altering DRN properties with the goal to re-sensitize resistant phenotypes. PMID:27841317

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

    PubMed

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

    2016-06-02

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

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

    PubMed Central

    2015-01-01

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

  13. Virus-induced gene silencing of Arabidopsis thaliana gene homologues in wheat identifies genes conferring improved drought tolerance

    PubMed Central

    Lapitan, Nora

    2013-01-01

    In a non-model staple crop like wheat (Triticum aestivumI L.), functional validation of potential drought stress responsive genes identified in Arabidopsis could provide gene targets for breeding. Virus-induced gene silencing (VIGS) of genes of interest can overcome the inherent problems of polyploidy and limited transformation potential that hamper functional validation studies in wheat. In this study, three potential candidate genes shown to be involved in abiotic stress response pathways in Arabidopsis thaliana were selected for VIGS experiments in wheat. These include Era1 (enhanced response to abscisic acid), Cyp707a (ABA 8’-hydroxylase), and Sal1 (inositol polyphosphate 1-phosphatase). Gene homologues for these three genes were identified in wheat and cloned in the viral vector barley stripe mosaic virus (BSMV) in the antisense direction, followed by rub inoculation of BSMV viral RNA transcripts onto wheat plants. Quantitative real-time PCR showed that VIGS-treated wheat plants had significant reductions in target gene transcripts. When VIGS-treated plants generated for Era1 and Sal1 were subjected to limiting water conditions, they showed increased relative water content, improved water use efficiency, reduced gas exchange, and better vigour compared to water-stressed control plants inoculated with RNA from the empty viral vector (BSMV0). In comparison, the Cyp707a-silenced plants showed no improvement over BSMV0-inoculated plants under limited water condition. These results indicate that Era1 and Sal1 play important roles in conferring drought tolerance in wheat. Other traits affected by Era1 silencing were also studied. Delayed seed germination in Era1-silenced plants suggests this gene may be a useful target for developing resistance to pre-harvest sprouting. PMID:23364940

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-03-29

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

  16. NDP gene mutations in 14 French families with Norrie disease.

    PubMed

    Royer, Ghislaine; Hanein, Sylvain; Raclin, Valérie; Gigarel, Nadine; Rozet, Jean-Michel; Munnich, Arnold; Steffann, Julie; Dufier, Jean-Louis; Kaplan, Josseline; Bonnefont, Jean-Paul

    2003-12-01

    Norrie disease is a rare X-inked recessive condition characterized by congenital blindness and occasionally deafness and mental retardation in males. This disease has been ascribed to mutations in the NDP gene on chromosome Xp11.1. Previous investigations of the NDP gene have identified largely sixty disease-causing sequence variants. Here, we report on ten different NDP gene allelic variants in fourteen of a series of 21 families fulfilling inclusion criteria. Two alterations were intragenic deletions and eight were nucleotide substitutions or splicing variants, six of them being hitherto unreported, namely c.112C>T (p.Arg38Cys), c.129C>G (p.His43Gln), c.133G>A (p.Val45Met), c.268C>T (p.Arg90Cys), c.382T>C (p.Cys128Arg), c.23479-1G>C (unknown). No NDP gene sequence variant was found in seven of the 21 families. This observation raises the issue of misdiagnosis, phenocopies, or existence of other X-linked or autosomal genes, the mutations of which would mimic the Norrie disease phenotype.

  17. Genome-wide association study identifies new susceptibility loci for Crohn disease and implicates autophagy in disease pathogenesis.

    PubMed

    Rioux, John D; Xavier, Ramnik J; Taylor, Kent D; Silverberg, Mark S; Goyette, Philippe; Huett, Alan; Green, Todd; Kuballa, Petric; Barmada, M Michael; Datta, Lisa Wu; Shugart, Yin Yao; Griffiths, Anne M; Targan, Stephan R; Ippoliti, Andrew F; Bernard, Edmond-Jean; Mei, Ling; Nicolae, Dan L; Regueiro, Miguel; Schumm, L Philip; Steinhart, A Hillary; Rotter, Jerome I; Duerr, Richard H; Cho, Judy H; Daly, Mark J; Brant, Steven R

    2007-05-01

    We present a genome-wide association study of ileal Crohn disease and two independent replication studies that identify several new regions of association to Crohn disease. Specifically, in addition to the previously established CARD15 and IL23R associations, we identified strong and significantly replicated associations (combined P < 10(-10)) with an intergenic region on 10q21.1 and a coding variant in ATG16L1, the latter of which was also recently reported by another group. We also report strong associations with independent replication to variation in the genomic regions encoding PHOX2B, NCF4 and a predicted gene on 16q24.1 (FAM92B). Finally, we demonstrate that ATG16L1 is expressed in intestinal epithelial cell lines and that functional knockdown of this gene abrogates autophagy of Salmonella typhimurium. Together, these findings suggest that autophagy and host cell responses to intracellular microbes are involved in the pathogenesis of Crohn disease.

  18. Approaches for recognizing disease genes based on network.

    PubMed

    Zou, Quan; Li, Jinjin; Wang, Chunyu; Zeng, Xiangxiang

    2014-01-01

    Diseases are closely related to genes, thus indicating that genetic abnormalities may lead to certain diseases. The recognition of disease genes has long been a goal in biology, which may contribute to the improvement of health care and understanding gene functions, pathways, and interactions. However, few large-scale gene-gene association datasets, disease-disease association datasets, and gene-disease association datasets are available. A number of machine learning methods have been used to recognize disease genes based on networks. This paper states the relationship between disease and gene, summarizes the approaches used to recognize disease genes based on network, analyzes the core problems and challenges of the methods, and outlooks future research direction.

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

    PubMed Central

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

    2014-01-01

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

  20. Gene polymorphisms and chronic obstructive pulmonary disease.

    PubMed

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

    2014-01-01

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

  1. Yeast Augmented Network Analysis (YANA): a new systems approach to identify therapeutic targets for human genetic diseases

    PubMed Central

    Wiley, David J.; Juan, Ilona; Le, Hao; Cai, Xiaodong; Baumbach, Lisa; Beattie, Christine; D'Urso, Gennaro

    2014-01-01

    Genetic interaction networks that underlie most human diseases are highly complex and poorly defined. Better-defined networks will allow identification of a greater number of therapeutic targets. Here we introduce our Yeast Augmented Network Analysis (YANA) approach and test it with the X-linked spinal muscular atrophy (SMA) disease gene UBA1. First, we express UBA1 and a mutant variant in fission yeast and use high-throughput methods to identify fission yeast genetic modifiers of UBA1. Second, we analyze available protein-protein interaction network databases in both fission yeast and human to construct UBA1 genetic networks. Third, from these networks we identified potential therapeutic targets for SMA. Finally, we validate one of these targets in a vertebrate (zebrafish) SMA model. This study demonstrates the power of combining synthetic and chemical genetics with a simple model system to identify human disease gene networks that can be exploited for treating human diseases. PMID:25075304

  2. Expression Quantitative Trait Loci Analysis Identifies Associations Between Genotype and Gene Expression in Human Intestine

    PubMed Central

    KABAKCHIEV, BOYKO; SILVERBERG, MARK S.

    2013-01-01

    BACKGROUND & AIMS Genome-wide association studies have greatly increased our understanding of intestinal disease. However, little is known about how genetic variations result in phenotypic changes. Some polymorphisms have been shown to modulate quantifiable phenotypic traits; these are called quantitative trait loci. Quantitative trait loci that affect levels of gene expression are called expression quantitative trait loci (eQTL), which can provide insight into the biological relevance of data from genome-wide association studies. We performed a comprehensive eQTL scan of intestinal tissue. METHODS Total RNA was extracted from ileal biopsy specimens and genomic DNA was obtained from whole-blood samples from the same cohort of individuals. Cis- and trans-eQTL analyses were performed using a custom software pipeline for samples from 173 subjects. The analyses determined the expression levels of 19,047 unique autosomal genes listed in the US National Center for Biotechnology Information database and more than 580,000 variants from the Single Nucleotide Polymorphism database. RESULTS The presence of more than 15,000 cis- and trans-eQTL was detected with statistical significance. eQTL associated with the same expression trait were in high linkage disequilibrium. Comparative analysis with previous eQTL studies showed that 30% to 40% of genes identified as eQTL in monocytes, liver tissue, lymphoblastoid cell lines, T cells, and fibroblasts are also eQTL in ileal tissue. Conversely, most of the significant eQTL have not been previously identified and could be tissue specific. These are involved in many cell functions, including division and antigen processing and presentation. Our analysis confirmed that previously published cis-eQTL are single nucleotide polymorphisms associated with inflammatory bowel disease: rs2298428/UBE2L3, rs1050152/SLC22A4, and SLC22A5. We identified many new associations between inflammatory bowel disease susceptibility loci and gene expression

  3. Exploiting natural variation to identify insect-resistance genes.

    PubMed

    Broekgaarden, Colette; Snoeren, Tjeerd A L; Dicke, Marcel; Vosman, Ben

    2011-10-01

    Herbivorous insects are widespread and often serious constraints to crop production. The use of insect-resistant crops is a very effective way to control insect pests in agriculture, and the development of such crops can be greatly enhanced by knowledge on plant resistance mechanisms and the genes involved. Plants have evolved diverse ways to cope with insect attack that has resulted in natural variation for resistance towards herbivorous insects. Studying the molecular genetics and transcriptional background of this variation has facilitated the identification of resistance genes and processes that lead to resistance against insects. With the development of new technologies, molecular studies are not restricted to model plants anymore. This review addresses the need to exploit natural variation in resistance towards insects to increase our knowledge on resistance mechanisms and the genes involved. We will discuss how this knowledge can be exploited in breeding programmes to provide sustainable crop protection against insect pests. Additionally, we discuss the current status of genetic research on insect-resistance genes. We conclude that insect-resistance mechanisms are still unclear at the molecular level and that exploiting natural variation with novel technologies will contribute greatly to the development of insect-resistant crop varieties.

  4. Transcriptome meta-analysis reveals common differential and global gene expression profiles in cystic fibrosis and other respiratory disorders and identifies CFTR regulators.

    PubMed

    Clarke, Luka A; Botelho, Hugo M; Sousa, Lisete; Falcao, Andre O; Amaral, Margarida D

    2015-11-01

    A meta-analysis of 13 independent microarray data sets was performed and gene expression profiles from cystic fibrosis (CF), similar disorders (COPD: chronic obstructive pulmonary disease, IPF: idiopathic pulmonary fibrosis, asthma), environmental conditions (smoking, epithelial injury), related cellular processes (epithelial differentiation/regeneration), and non-respiratory "control" conditions (schizophrenia, dieting), were compared. Similarity among differentially expressed (DE) gene lists was assessed using a permutation test, and a clustergram was constructed, identifying common gene markers. Global gene expression values were standardized using a novel approach, revealing that similarities between independent data sets run deeper than shared DE genes. Correlation of gene expression values identified putative gene regulators of the CF transmembrane conductance regulator (CFTR) gene, of potential therapeutic significance. Our study provides a novel perspective on CF epithelial gene expression in the context of other lung disorders and conditions, and highlights the contribution of differentiation/EMT and injury to gene signatures of respiratory disease.

  5. An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways

    PubMed Central

    Ander, Bradley P.; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R.; Yang, Xiaowei

    2013-01-01

    The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with ‘large p, small n’ problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed. PMID:23844055

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

    PubMed Central

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

    2013-01-01

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

  7. Genome-wide RNAi screening identifies protein damage as a regulator of osmoprotective gene expression

    PubMed Central

    Lamitina, Todd; Huang, Chunyi George; Strange, Kevin

    2006-01-01

    The detection, stabilization, and repair of stress-induced damage are essential requirements for cellular life. All cells respond to osmotic stress-induced water loss with increased expression of genes that mediate accumulation of organic osmolytes, solutes that function as chemical chaperones and restore osmotic homeostasis. The signals and signaling mechanisms that regulate osmoprotective gene expression in animal cells are poorly understood. Here, we show that gpdh-1 and gpdh-2, genes that mediate the accumulation of the organic osmolyte glycerol, are essential for survival of the nematode Caenorhabditis elegans during osmotic stress. Expression of GFP driven by the gpdh-1 promoter (Pgpdh-1::GFP) is detected only during hypertonic stress but is not induced by other stressors. Using Pgpdh-1::GFP expression as a phenotype, we screened ≈16,000 genes by RNAi feeding and identified 122 that cause constitutive activation of gpdh-1 expression and glycerol accumulation. Many of these genes function to regulate protein translation and cotranslational protein folding and to target and degrade denatured proteins, suggesting that the accumulation of misfolded proteins functions as a signal to activate osmoprotective gene expression and organic osmolyte accumulation in animal cells. Consistent with this hypothesis, 73% of these protein-homeostasis genes have been shown to slow age-dependent protein aggregation in C. elegans. Because diverse environmental stressors and numerous disease states result in protein misfolding, mechanisms must exist that discriminate between osmotically induced and other forms of stress-induced protein damage. Our findings provide a foundation for understanding how these damage-selectivity mechanisms function. PMID:16880390

  8. Gene expression profiling identifies genes predictive of oral squamous cell carcinoma.

    PubMed

    Chen, Chu; Méndez, Eduardo; Houck, John; Fan, Wenhong; Lohavanichbutr, Pawadee; Doody, Dave; Yueh, Bevan; Futran, Neal D; Upton, Melissa; Farwell, D Gregory; Schwartz, Stephen M; Zhao, Lue Ping

    2008-08-01

    Oral squamous cell carcinoma (OSCC) is associated with substantial mortality and morbidity. To identify potential biomarkers for the early detection of invasive OSCC, we compared the gene expressions of incident primary OSCC, oral dysplasia, and clinically normal oral tissue from surgical patients without head and neck cancer or preneoplastic oral lesions (controls), using Affymetrix U133 2.0 Plus arrays. We identified 131 differentially expressed probe sets using a training set of 119 OSCC patients and 35 controls. Forward and stepwise logistic regression analyses identified 10 successive combinations of genes which expression differentiated OSCC from controls. The best model included LAMC2, encoding laminin-gamma2 chain, and COL4A1, encoding collagen, type IV alpha1 chain. Subsequent modeling without these two markers showed that COL1A1, encoding collagen, type I alpha1 chain, and PADI1, encoding peptidyl arginine deiminase, type 1, could also distinguish OSCC from controls. We validated these two models using an internal independent testing set of 48 invasive OSCC and 10 controls and an external testing set of 42 head and neck squamous cell carcinoma cases and 14 controls (GEO GSE6791), with sensitivity and specificity above 95%. These two models were also able to distinguish dysplasia (n = 17) from control (n = 35) tissue. Differential expression of these four genes was confirmed by quantitative reverse transcription-PCR. If confirmed in larger studies, the proposed models may hold promise for monitoring local recurrence at surgical margins and the development of second primary oral cancer in patients with OSCC.

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

    PubMed Central

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

    2015-01-01

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

  10. Transcriptome Sequencing Identified Genes and Gene Ontologies Associated with Early Freezing Tolerance in Maize

    PubMed Central

    Li, Zhao; Hu, Guanghui; Liu, Xiangfeng; Zhou, Yao; Li, Yu; Zhang, Xu; Yuan, Xiaohui; Zhang, Qian; Yang, Deguang; Wang, Tianyu; Zhang, Zhiwu

    2016-01-01

    Originating in a tropical climate, maize has faced great challenges as cultivation has expanded to the majority of the world's temperate zones. In these zones, frost and cold temperatures are major factors that prevent maize from reaching its full yield potential. Among 30 elite maize inbred lines adapted to northern China, we identified two lines of extreme, but opposite, freezing tolerance levels—highly tolerant and highly sensitive. During the seedling stage of these two lines, we used RNA-seq to measure changes in maize whole genome transcriptome before and after freezing treatment. In total, 19,794 genes were expressed, of which 4550 exhibited differential expression due to either treatment (before or after freezing) or line type (tolerant or sensitive). Of the 4550 differently expressed genes, 948 exhibited differential expression due to treatment within line or lines under freezing condition. Analysis of gene ontology found that these 948 genes were significantly enriched for binding functions (DNA binding, ATP binding, and metal ion binding), protein kinase activity, and peptidase activity. Based on their enrichment, literature support, and significant levels of differential expression, 30 of these 948 genes were selected for quantitative real-time PCR (qRT-PCR) validation. The validation confirmed our RNA-Seq-based findings, with squared correlation coefficients of 80% and 50% in the tolerance and sensitive lines, respectively. This study provided valuable resources for further studies to enhance understanding of the molecular mechanisms underlying maize early freezing response and enable targeted breeding strategies for developing varieties with superior frost resistance to achieve yield potential. PMID:27774095

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

    EPA Science Inventory

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

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

    PubMed

    Guney, Emre; Oliva, Baldo

    2014-01-01

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

  13. 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

  14. Computational identifying and characterizing circular RNAs and their associated genes in hepatocellular carcinoma

    PubMed Central

    Li, Yan; Dong, Yongcheng; Huang, Ziyan; Kuang, Qifan; Wu, Yiming; Li, Yizhou; Li, Menglong

    2017-01-01

    Hepatocellular carcinoma (HCC) is currently still a major factor leading to death, lacking of reliable biomarkers. Therefore, deep understanding the pathogenesis for HCC is of great importance. The emergence of circular RNA (circRNA) provides a new way to study the pathogenesis of human disease. Here, we employed the prediction tool to identify circRNAs based on RNA-seq data. Then, to investigate the biological function of the circRNA, the candidate circRNAs were associated with the protein-coding genes (PCGs) by GREAT. We found significant candidate circRNAs expression alterations between normal and tumor samples. Additionally, the PCGs associated with these candidate circRNAs were also found have discriminative expression patterns between normal and tumor samples. The enrichment analysis illustrated that these PCGs were predominantly enriched for liver/cardiovascular-related diseases such as atherosclerosis, myocardial ischemia and coronary heart disease, and participated in various metabolic processes. Together, a further network analysis indicated that these PCGs play important roles in the regulatory and the PPI network. Finally, we built a classification model to distinguish normal and tumor samples by using candidate circRNAs and their associated genes, respectively. Both of them obtained satisfactory results (~ 0.99 of AUC for circRNA and PCG). Our findings suggested that the circRNA could be a critical factor in HCC, providing a useful resource to explore the pathogenesis of HCC. PMID:28346469

  15. A framework to identify gene expression profiles in a model of inflammation induced by lipopolysaccharide after treatment with thalidomide

    PubMed Central

    2012-01-01

    Background Thalidomide is an anti-inflammatory and anti-angiogenic drug currently used for the treatment of several diseases, including erythema nodosum leprosum, which occurs in patients with lepromatous leprosy. In this research, we use DNA microarray analysis to identify the impact of thalidomide on gene expression responses in human cells after lipopolysaccharide (LPS) stimulation. We employed a two-stage framework. Initially, we identified 1584 altered genes in response to LPS. Modulation of this set of genes was then analyzed in the LPS stimulated cells treated with thalidomide. Results We identified 64 genes with altered expression induced by thalidomide using the rank product method. In addition, the lists of up-regulated and down-regulated genes were investigated by means of bioinformatics functional analysis, which allowed for the identification of biological processes affected by thalidomide. Confirmatory analysis was done in five of the identified genes using real time PCR. Conclusions The results showed some genes that can further our understanding of the biological mechanisms in the action of thalidomide. Of the five genes evaluated with real time PCR, three were down regulated and two were up regulated confirming the initial results of the microarray analysis. PMID:22695124

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

    PubMed Central

    2014-01-01

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

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

    PubMed Central

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

    2011-01-01

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

  18. A Genome-wide CRISPR Screen in Toxoplasma Identifies Essential Apicomplexan Genes.

    PubMed

    Sidik, Saima M; Huet, Diego; Ganesan, Suresh M; Huynh, My-Hang; Wang, Tim; Nasamu, Armiyaw S; Thiru, Prathapan; Saeij, Jeroen P J; Carruthers, Vern B; Niles, Jacquin C; Lourido, Sebastian

    2016-09-08

    Apicomplexan parasites are leading causes of human and livestock diseases such as malaria and toxoplasmosis, yet most of their genes remain uncharacterized. Here, we present the first genome-wide genetic screen of an apicomplexan. We adapted CRISPR/Cas9 to assess the contribution of each gene from the parasite Toxoplasma gondii during infection of human fibroblasts. Our analysis defines ∼200 previously uncharacterized, fitness-conferring genes unique to the phylum, from which 16 were investigated, revealing essential functions during infection of human cells. Secondary screens identify as an invasion factor the claudin-like apicomplexan microneme protein (CLAMP), which resembles mammalian tight-junction proteins and localizes to secretory organelles, making it critical to the initiation of infection. CLAMP is present throughout sequenced apicomplexan genomes and is essential during the asexual stages of the malaria parasite Plasmodium falciparum. These results provide broad-based functional information on T. gondii genes and will facilitate future approaches to expand the horizon of antiparasitic interventions.

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

    PubMed Central

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

    2014-01-01

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

  20. Identification of dysfunctional modules and disease genes in congenital heart disease by a network-based approach

    PubMed Central

    2011-01-01

    Background The incidence of congenital heart disease (CHD) is continuously increasing among infants born alive nowadays, making it one of the leading causes of infant morbidity worldwide. Various studies suggest that both genetic and environmental factors lead to CHD, and therefore identifying its candidate genes and disease-markers has been one of the central topics in CHD research. By using the high-throughput genomic data of CHD which are available recently, network-based methods provide powerful alternatives of systematic analysis of complex diseases and identification of dysfunctional modules and candidate disease genes. Results In this paper, by modeling the information flow from source disease genes to targets of differentially expressed genes via a context-specific protein-protein interaction network, we extracted dysfunctional modules which were then validated by various types of measurements and independent datasets. Network topology analysis of these modules revealed major and auxiliary pathways and cellular processes in CHD, demonstrating the biological usefulness of the identified modules. We also prioritized a list of candidate CHD genes from these modules using a guilt-by-association approach, which are well supported by various kinds of literature and experimental evidence. Conclusions We provided a network-based analysis to detect dysfunctional modules and disease genes of CHD by modeling the information transmission from source disease genes to targets of differentially expressed genes. Our method resulted in 12 modules from the constructed CHD subnetwork. We further identified and prioritized candidate disease genes of CHD from these dysfunctional modules. In conclusion, module analysis not only revealed several important findings with regard to the underlying molecular mechanisms of CHD, but also suggested the distinct network properties of causal disease genes which lead to identification of candidate CHD genes. PMID:22136190

  1. 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.

  2. Integrative literature and data mining to rank disease candidate genes.

    PubMed

    Wu, Chao; Zhu, Cheng; Jegga, Anil G

    2014-01-01

    While the genomics-derived discoveries promise benefits to basic research and health care, the speed and affordability of sequencing following recent technological advances has further aggravated the data deluge. Seamless integration of the ever-increasing clinical, genomic, and experimental data and efficient mining for knowledge extraction, delivering actionable insight and generating testable hypotheses are therefore critical for the needs of biomedical research. For instance, high-throughput techniques are frequently applied to detect disease candidate genes. Experimental validation of these candidates however is both time-consuming and expensive. Hence, several computational approaches based on literature and data mining have been developed to identify the most promising candidates for follow-up studies. Based on "guilt by association" principle, most of these methods use prior knowledge about a disease of interest to discover and rank novel candidate genes. In this chapter, we provide a brief overview of recent advances made in literature- and data-mining-based approaches for candidate gene prioritization. As a case study, we focus on a Web-based computational approach that uses integrated heterogeneous data sources including gene-literature associations for ranking disease candidate genes and explain how to run typical queries using this system.

  3. Gene therapy: progress in childhood disease.

    PubMed

    Ginn, Samantha L; Alexander, Ian E

    2012-06-01

    The recent sequencing of the human genome combined with the development of massively high throughput genetic analysis technologies is driving unprecedented growth in our knowledge of the molecular basis of disease. While this has already had a major impact on our diagnostic power, the therapeutic benefits remain largely unrealised. This review examines progress in the exciting and challenging field of gene therapy. In particular we focus on the treatment of genetic disease in infants and children where the most significant successes have been observed to date, despite the majority of trial participants being adults. Notably, gene transfer to the haematopoietic compartment has provided the clearest examples of therapeutic benefit, particularly in the context of primary immunodeficiencies. The triumphs and tribulations of these successes are explored, and the key challenges confronting researchers as they seek to further advance the field are defined and discussed.

  4. Identifying Foodborne Disease Hazards in Food Service Establishments

    ERIC Educational Resources Information Center

    Bryan, Frank L.

    1974-01-01

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

  5. 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.

  6. Seven newly identified loci for autoimmune thyroid disease.

    PubMed

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

    2012-12-01

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

  7. Gene expression profiling of CD34+ cells identifies a molecular signature of chronic myeloid leukemia blast crisis.

    PubMed

    Zheng, C; Li, L; Haak, M; Brors, B; Frank, O; Giehl, M; Fabarius, A; Schatz, M; Weisser, A; Lorentz, C; Gretz, N; Hehlmann, R; Hochhaus, A; Seifarth, W

    2006-06-01

    Despite recent success in the treatment of early-stage disease, blastic phase (BP) of chronic myeloid leukemia (CML) that is characterized by rapid expansion of therapy-refractory and differentiation-arrested blasts, remains a therapeutic challenge. The development of resistance upon continuous administration of imatinib mesylate is associated with poor prognosis pointing to the need for alternative therapeutic strategies and a better understanding of the molecular mechanisms underlying disease progression. To identify transcriptional signatures that may explain pathological characteristics and aggressive behavior of BP blasts, we performed comparative gene expression profiling on CD34+ Ph+ cells purified from patients with untreated newly diagnosed chronic phase CML (CP, n=11) and from patients in BP (n=9) using Affymetrix oligonucleotide arrays. Supervised microarray data analysis revealed 114 differentially expressed genes (P<10(-4)), 34 genes displaying more than two-fold transcriptional changes when comparing CP and BP groups. While 24 of these genes were downregulated, 10 genes, especially suppressor of cytokine signalling 2 (SOCS2), CAMPATH-1 antigen (CD52), and four human leukocyte antigen-related genes were strongly overexpressed in BP. Expression of selected genes was validated by real-time-polymerase chain reaction and flow cytometry. Our data suggest the existence of a common gene expression profile of CML-BP and provide new insight into the molecular phenotype of blasts associated with disease progression and high malignancy.

  8. DNA methylation profiling identifies CG methylation clusters in Arabidopsis genes.

    PubMed

    Tran, Robert K; Henikoff, Jorja G; Zilberman, Daniel; Ditt, Renata F; Jacobsen, Steven E; Henikoff, Steven

    2005-01-26

    Cytosine DNA methylation in vertebrates is widespread, but methylation in plants is found almost exclusively at transposable elements and repetitive DNA. Within regions of methylation, methylcytosines are typically found in CG, CNG, and asymmetric contexts. CG sites are maintained by a plant homolog of mammalian Dnmt1 acting on hemi-methylated DNA after replication. Methylation of CNG and asymmetric sites appears to be maintained at each cell cycle by other mechanisms. We report a new type of DNA methylation in Arabidopsis, dense CG methylation clusters found at scattered sites throughout the genome. These clusters lack non-CG methylation and are preferentially found in genes, although they are relatively deficient toward the 5' end. CG methylation clusters are present in lines derived from different accessions and in mutants that eliminate de novo methylation, indicating that CG methylation clusters are stably maintained at specific sites. Because 5-methylcytosine is mutagenic, the appearance of CG methylation clusters over evolutionary time predicts a genome-wide deficiency of CG dinucleotides and an excess of C(A/T)G trinucleotides within transcribed regions. This is exactly what we find, implying that CG methylation clusters have contributed profoundly to plant gene evolution. We suggest that CG methylation clusters silence cryptic promoters that arise sporadically within transcription units.

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

    PubMed Central

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

    2013-01-01

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

  10. Fluid Mechanics, Arterial Disease, and Gene Expression

    PubMed Central

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

    2014-01-01

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

  11. Fluid Mechanics, Arterial Disease, and Gene Expression.

    PubMed

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

    2014-01-01

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

  12. Gene Network Analysis of Small Molecules with Autoimmune Disease Associated Genes Predicts a Novel Strategy for Drug Efficacy

    PubMed Central

    Maiti, Amit K.; Nath, Swapan K.

    2012-01-01

    Numerous genes/SNPs in autoimmune diseases (ADs) are identified through genome-wide association studies (GWAS) and likely to contribute in developing autoimmune phenotypes. Constructions of biologically meaningful pathways are necessary to determine how these genes interact each other and with other small molecules to develop various complex ADs phenotypes prior to beginning time-consuming rigorous experimentation. We have constructed biological pathways with genetically identified genes leading to shared ADs phenotypes. Various environmental and endogenous factors interact with these ADs associated genes suggesting their critical role in developing diseases and further association studies could be designed for assessing the role of these factors with risk allele in a specific gene. Additionally, existing drugs that have been used long before the identification of these genetically associated genes also interact with these newly associated genes. Thus advanced therapeutic strategies could be designed by grouping patients with risk allele(s) in particular genes that directly or closely interact with the specified drugs. This drug-susceptible gene network will not only increase our understanding about the additional molecular basis for effectiveness against these diseases but also which drug could be more effective for those patients carrying risk allele(s) in that gene. Additionally, we have also identified several interlinking genes in the pathways that could be used for designing future association studies. PMID:23000205

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

    PubMed

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

    2005-01-01

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

  14. Synthetic lethal screening in the mammalian central nervous system identifies Gpx6 as a modulator of Huntington's disease.

    PubMed

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

    2015-01-06

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

  15. Linkage, Association, and Gene-Expression Analyses Identify CNTNAP2 as an Autism-Susceptibility Gene

    PubMed Central

    Alarcón, Maricela; Abrahams, Brett S.; Stone, Jennifer L.; Duvall, Jacqueline A.; Perederiy, Julia V.; Bomar, Jamee M.; Sebat, Jonathan; Wigler, Michael; Martin, Christa L.; Ledbetter, David H.; Nelson, Stanley F.; Cantor, Rita M.; Geschwind, Daniel H.

    2008-01-01

    Autism is a genetically complex neurodevelopmental syndrome in which language deficits are a core feature. We describe results from two complimentary approaches used to identify risk variants on chromosome 7 that likely contribute to the etiology of autism. A two-stage association study tested 2758 SNPs across a 10 Mb 7q35 language-related autism QTL in AGRE (Autism Genetic Resource Exchange) trios1,2 and found significant association with Contactin Associated Protein-Like 2 (CNTNAP2), a strong a priori candidate. Male-only containing families were identified as primarily responsible for this association signal, consistent with the strong male affection bias in ASD and other language-based disorders. Gene-expression analyses in developing human brain further identified CNTNAP2 as enriched in circuits important for language development. Together, these results provide convergent evidence for involvement of CNTNAP2, a Neurexin family member, in autism, and demonstrate a connection between genetic risk for autism and specific brain structures. PMID:18179893

  16. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development.

    PubMed

    Takeda, Haruna; Rust, Alistair G; Ward, Jerrold M; Yew, Christopher Chin Kuan; Jenkins, Nancy A; Copeland, Neal G

    2016-04-05

    Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4(+/-) mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC.

  17. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development

    PubMed Central

    Takeda, Haruna; Rust, Alistair G.; Ward, Jerrold M.; Yew, Christopher Chin Kuan; Jenkins, Nancy A.; Copeland, Neal G.

    2016-01-01

    Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4+/− mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC. PMID:27006499

  18. Elevating crop disease resistance with cloned genes

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  20. Interlocus gene conversion events introduce deleterious mutations into at least 1% of human genes associated with inherited disease.

    PubMed

    Casola, Claudio; Zekonyte, Ugne; Phillips, Andrew D; Cooper, David N; Hahn, Matthew W

    2012-03-01

    Establishing the molecular basis of DNA mutations that cause inherited disease is of fundamental importance to understanding the origin, nature, and clinical sequelae of genetic disorders in humans. The majority of disease-associated mutations constitute single-base substitutions and short deletions and/or insertions resulting from DNA replication errors and the repair of damaged bases. However, pathological mutations can also be introduced by nonreciprocal recombination events between paralogous sequences, a phenomenon known as interlocus gene conversion (IGC). IGC events have thus far been linked to pathology in more than 20 human genes. However, the large number of duplicated gene sequences in the human genome implies that many more disease-associated mutations could originate via IGC. Here, we have used a genome-wide computational approach to identify disease-associated mutations derived from IGC events. Our approach revealed hundreds of known pathological mutations that could have been caused by IGC. Further, we identified several dozen high-confidence cases of inherited disease mutations resulting from IGC in ∼1% of all genes analyzed. About half of the donor sequences associated with such mutations are functional paralogous genes, suggesting that epistatic interactions or differential expression patterns will determine the impact upon fitness of specific substitutions between duplicated genes. In addition, we identified thousands of hitherto undescribed and potentially deleterious mutations that could arise via IGC. Our findings reveal the extent of the impact of interlocus gene conversion upon the spectrum of human inherited disease.

  1. Biomedical Information Extraction: Mining Disease Associated Genes from Literature

    ERIC Educational Resources Information Center

    Huang, Zhong

    2014-01-01

    Disease associated gene discovery is a critical step to realize the future of personalized medicine. However empirical and clinical validation of disease associated genes are time consuming and expensive. In silico discovery of disease associated genes from literature is therefore becoming the first essential step for biomarker discovery to…

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

    PubMed Central

    Liu, Jingyan; Li, Lanrong; Liu, Qingmin

    2015-01-01

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

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

    PubMed

    Liu, Jingyan; Li, Lanrong; Liu, Qingmin

    2015-01-01

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

  4. Identifying the rooted species tree from the distribution of unrooted gene trees under the coalescent.

    PubMed

    Allman, Elizabeth S; Degnan, James H; Rhodes, John A

    2011-06-01

    Gene trees are evolutionary trees representing the ancestry of genes sampled from multiple populations. Species trees represent populations of individuals-each with many genes-splitting into new populations or species. The coalescent process, which models ancestry of gene copies within populations, is often used to model the probability distribution of gene trees given a fixed species tree. This multispecies coalescent model provides a framework for phylogeneticists to infer species trees from gene trees using maximum likelihood or Bayesian approaches. Because the coalescent models a branching process over time, all trees are typically assumed to be rooted in this setting. Often, however, gene trees inferred by traditional phylogenetic methods are unrooted. We investigate probabilities of unrooted gene trees under the multispecies coalescent model. We show that when there are four species with one gene sampled per species, the distribution of unrooted gene tree topologies identifies the unrooted species tree topology and some, but not all, information in the species tree edges (branch lengths). The location of the root on the species tree is not identifiable in this situation. However, for 5 or more species with one gene sampled per species, we show that the distribution of unrooted gene tree topologies identifies the rooted species tree topology and all its internal branch lengths. The length of any pendant branch leading to a leaf of the species tree is also identifiable for any species from which more than one gene is sampled.

  5. Genomic variants, genes, and pathways of Alzheimer's disease: An overview.

    PubMed

    Naj, Adam C; Schellenberg, Gerard D

    2017-01-01

    Alzheimer's disease (AD) (MIM: 104300) is a highly heritable disease with great complexity in its genetic contributors, and represents the most common form of dementia. With the gradual aging of the world's population, leading to increased prevalence of AD, and the substantial cost of care for those afflicted, identifying the genetic causes of disease represents a critical effort in identifying therapeutic targets. Here we provide a comprehensive review of genomic studies of AD, from the earliest linkage studies identifying monogenic contributors to early-onset forms of AD to the genome-wide and rare variant association studies of recent years that are being used to characterize the mosaic of genetic contributors to late-onset AD (LOAD), and which have identified approximately ∼20 genes with common variants contributing to LOAD risk. In addition, we explore studies employing alternative approaches to identify genetic contributors to AD, including studies of AD-related phenotypes and multi-variant association studies such as pathway analyses. Finally, we introduce studies of next-generation sequencing, which have recently helped identify multiple low-frequency and rare variant contributors to AD, and discuss on-going efforts with next-generation sequencing studies to develop statistically well- powered and comprehensive genomic studies of AD. Through this review, we help uncover the many insights the genetics of AD have provided into the pathways and pathophysiology of AD. © 2016 Wiley Periodicals, Inc.

  6. A yeast functional screen predicts new candidate ALS disease genes

    PubMed Central

    Couthouis, Julien; Hart, Michael P.; Shorter, James; DeJesus-Hernandez, Mariely; Erion, Renske; Oristano, Rachel; Liu, Annie X.; Ramos, Daniel; Jethava, Niti; Hosangadi, Divya; Epstein, James; Chiang, Ashley; Diaz, Zamia; Nakaya, Tadashi; Ibrahim, Fadia; Kim, Hyung-Jun; Solski, Jennifer A.; Williams, Kelly L.; Mojsilovic-Petrovic, Jelena; Ingre, Caroline; Boylan, Kevin; Graff-Radford, Neill R.; Dickson, Dennis W.; Clay-Falcone, Dana; Elman, Lauren; McCluskey, Leo; Greene, Robert; Kalb, Robert G.; Lee, Virginia M.-Y.; Trojanowski, John Q.; Ludolph, Albert; Robberecht, Wim; Andersen, Peter M.; Nicholson, Garth A.; Blair, Ian P.; King, Oliver D.; Bonini, Nancy M.; Van Deerlin, Vivianna; Rademakers, Rosa; Mourelatos, Zissimos; Gitler, Aaron D.

    2011-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating and universally fatal neurodegenerative disease. Mutations in two related RNA-binding proteins, TDP-43 and FUS, that harbor prion-like domains, cause some forms of ALS. There are at least 213 human proteins harboring RNA recognition motifs, including FUS and TDP-43, raising the possibility that additional RNA-binding proteins might contribute to ALS pathogenesis. We performed a systematic survey of these proteins to find additional candidates similar to TDP-43 and FUS, followed by bioinformatics to predict prion-like domains in a subset of them. We sequenced one of these genes, TAF15, in patients with ALS and identified missense variants, which were absent in a large number of healthy controls. These disease-associated variants of TAF15 caused formation of cytoplasmic foci when expressed in primary cultures of spinal cord neurons. Very similar to TDP-43 and FUS, TAF15 aggregated in vitro and conferred neurodegeneration in Drosophila, with the ALS-linked variants having a more severe effect than wild type. Immunohistochemistry of postmortem spinal cord tissue revealed mislocalization of TAF15 in motor neurons of patients with ALS. We propose that aggregation-prone RNA-binding proteins might contribute very broadly to ALS pathogenesis and the genes identified in our yeast functional screen, coupled with prion-like domain prediction analysis, now provide a powerful resource to facilitate ALS disease gene discovery. PMID:22065782

  7. 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.

  8. CFTR gene mutations in isolated chronic obstructive pulmonary disease

    SciTech Connect

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

    1994-09-01

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

  9. Prioritization of Disease Susceptibility Genes Using LSM/SVD.

    PubMed

    Gong, Lejun; Yang, Ronggen; Yan, Qin; Sun, Xiao

    2013-12-01

    Understanding the role of genetics in diseases is one of the most important tasks in the postgenome era. It is generally too expensive and time consuming to perform experimental validation for all candidate genes related to disease. Computational methods play important roles for prioritizing these candidates. Herein, we propose an approach to prioritize disease genes using latent semantic mapping based on singular value decomposition. Our hypothesis is that similar functional genes are likely to cause similar diseases. Measuring the functional similarity between known disease susceptibility genes and unknown genes is to predict new disease susceptibility genes. Taking autism as an instance, the analysis results of the top ten genes prioritized demonstrate they might be autism susceptibility genes, which also indicates our approach could discover new disease susceptibility genes. The novel approach of disease gene prioritization could discover new disease susceptibility genes, and latent disease-gene relations. The prioritized results could also support the interpretive diversity and experimental views as computational evidence for disease researchers.

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

    PubMed

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

    2016-02-11

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

  11. Harnessing genomics to identify environmental determinants of heritable disease

    EPA Science Inventory

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

  12. Effective Boolean dynamics analysis to identify functionally important genes in large-scale signaling networks.

    PubMed

    Trinh, Hung-Cuong; Kwon, Yung-Keun

    2015-11-01

    Efficiently identifying functionally important genes in order to understand the minimal requirements of normal cellular development is challenging. To this end, a variety of structural measures have been proposed and their effectiveness has been investigated in recent literature; however, few studies have shown the effectiveness of dynamics-based measures. This led us to investigate a dynamic measure to identify functionally important genes, and the effectiveness of which was verified through application on two large-scale human signaling networks. We specifically consider Boolean sensitivity-based dynamics against an update-rule perturbation (BSU) as a dynamic measure. Through investigations on two large-scale human signaling networks, we found that genes with relatively high BSU values show slower evolutionary rate and higher proportions of essential genes and drug targets than other genes. Gene-ontology analysis showed clear differences between the former and latter groups of genes. Furthermore, we compare the identification accuracies of essential genes and drug targets via BSU and five well-known structural measures. Although BSU did not always show the best performance, it effectively identified the putative set of genes, which is significantly different from the results obtained via the structural measures. Most interestingly, BSU showed the highest synergy effect in identifying the functionally important genes in conjunction with other measures. Our results imply that Boolean-sensitive dynamics can be used as a measure to effectively identify functionally important genes in signaling networks.

  13. A Systems Genetics Approach Identifies CXCL14, ITGAX, and LPCAT2 as Novel Aggressive Prostate Cancer Susceptibility Genes

    PubMed Central

    Andreas, Jonathan; Patel, Shashank J.; Zhang, Suiyuan; Chines, Peter; Elkahloun, Abdel; Chandrasekharappa, Settara; Gutkind, J. Silvio; Molinolo, Alfredo A.; Crawford, Nigel P. S.

    2014-01-01

    Although prostate cancer typically runs an indolent course, a subset of men develop aggressive, fatal forms of this disease. We hypothesize that germline variation modulates susceptibility to aggressive prostate cancer. The goal of this work is to identify susceptibility genes using the C57BL/6-Tg(TRAMP)8247Ng/J (TRAMP) mouse model of neuroendocrine prostate cancer. Quantitative trait locus (QTL) mapping was performed in transgene-positive (TRAMPxNOD/ShiLtJ) F2 intercross males (n = 228), which facilitated identification of 11 loci associated with aggressive disease development. Microarray data derived from 126 (TRAMPxNOD/ShiLtJ) F2 primary tumors were used to prioritize candidate genes within QTLs, with candidate genes deemed as being high priority when possessing both high levels of expression-trait correlation and a proximal expression QTL. This process enabled the identification of 35 aggressive prostate tumorigenesis candidate genes. The role of these genes in aggressive forms of human prostate cancer was investigated using two concurrent approaches. First, logistic regression analysis in two human prostate gene expression datasets revealed that expression levels of five genes (CXCL14, ITGAX, LPCAT2, RNASEH2A, and ZNF322) were positively correlated with aggressive prostate cancer and two genes (CCL19 and HIST1H1A) were protective for aggressive prostate cancer. Higher than average levels of expression of the five genes that were positively correlated with aggressive disease were consistently associated with patient outcome in both human prostate cancer tumor gene expression datasets. Second, three of these five genes (CXCL14, ITGAX, and LPCAT2) harbored polymorphisms associated with aggressive disease development in a human GWAS cohort consisting of 1,172 prostate cancer patients. This study is the first example of using a systems genetics approach to successfully identify novel susceptibility genes for aggressive prostate cancer. Such approaches will

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

    PubMed

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

    2016-01-01

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

  15. Growth factor gene therapy for Alzheimer disease.

    PubMed

    Tuszynski, Mark H; U, Hoi Sang; Alksne, John; Bakay, Roy A; Pay, Mary Margaret; Merrill, David; Thal, Leon J

    2002-11-15

    The capacity to prevent neuronal degeneration and death during the course of progressive neurological disorders such as Alzheimer disease (AD) would represent a significant advance in therapy. Nervous system growth factors are families of naturally produced proteins that, in animal models, exhibit extensive potency in preventing neuronal death due to a variety of causes, reversing age-related atrophy of neurons, and ameliorating functional deficits. The main challenge in translating growth factor therapy to the clinic has been delivery of growth factors to the brain in sufficient concentrations to influence neuronal function. One means of achieving growth factor delivery to the central nervous system in a highly targeted, effective manner may be gene therapy. In this article the authors summarize the development and implementation of nerve growth factor gene delivery as a potential means of reducing cell loss in AD.

  16. Using Registries to Identify Adverse Events in Rheumatic Diseases

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-11-01

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

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

    PubMed

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

    2015-12-01

    Alzheimer's disease (AD) and Parkinson's disease (PD) are the first and second most common neurodegenerative diseases in the elderly. Shared clinical and pathological features have been reported. Recent large-scale genome-wide association studies (GWAS) have been conducted and reported a number of AD and PD variants. Until now, the underlying genetic mechanisms for all these newly identified PD variants as well as the association between AD and PD are still unclear exactly. We think that PD variants may contribute to AD and PD by influence on brain gene expression. Here, we conducted a systems analysis using (1) AD and PD variants (P < 5.00E-08) identified by the published GWAS; (2) four brain expression GWAS datasets using expression quantitative trait loci from the cerebellum and temporal cortex; (3) large-scale AD GWAS from the Alzheimer Disease Genetics Consortium (ADGC); (4) a protein-protein interaction network. Our results indicated that PD variants around the 17q21 were associated with gene expression and suggestive AD risk. We also identified significant interaction among AD and PD susceptibility genes. We believe that our findings may explain the underlying genetic mechanisms for newly identified PD variants in PD and AD, as well as the association between AD and PD, which may be very useful for future genetic studies for both diseases.

  19. Exome Array Analysis Identifies a Common Variant in IL27 Associated with Chronic Obstructive Pulmonary Disease

    PubMed Central

    Parker, Margaret M.; Chen, Han; Lao, Taotao; Hardin, Megan; Qiao, Dandi; Hawrylkiewicz, Iwona; Sliwinski, Pawel; Yim, Jae-Joon; Kim, Woo Jin; Kim, Deog Kyeom; Castaldi, Peter J.; Hersh, Craig P.; Morrow, Jarrett; Celli, Bartolome R.; Pinto-Plata, Victor M.; Criner, Gerald J.; Marchetti, Nathaniel; Bueno, Raphael; Agustí, Alvar; Make, Barry J.; Crapo, James D.; Calverley, Peter M.; Donner, Claudio F.; Lomas, David A.; Wouters, Emiel F. M.; Vestbo, Jorgen; Paré, Peter D.; Levy, Robert D.; Rennard, Stephen I.; Zhou, Xiaobo; Laird, Nan M.; Lin, Xihong; Beaty, Terri H.; Silverman, Edwin K.

    2016-01-01

    Rationale: Chronic obstructive pulmonary disease (COPD) susceptibility is in part related to genetic variants. Most genetic studies have been focused on genome-wide common variants without a specific focus on coding variants, but common and rare coding variants may also affect COPD susceptibility. Objectives: To identify coding variants associated with COPD. Methods: We tested nonsynonymous, splice, and stop variants derived from the Illumina HumanExome array for association with COPD in five study populations enriched for COPD. We evaluated single variants with a minor allele frequency greater than 0.5% using logistic regression. Results were combined using a fixed effects meta-analysis. We replicated novel single-variant associations in three additional COPD cohorts. Measurements and Main Results: We included 6,004 control subjects and 6,161 COPD cases across five cohorts for analysis. Our top result was rs16969968 (P = 1.7 × 10−14) in CHRNA5, a locus previously associated with COPD susceptibility and nicotine dependence. Additional top results were found in AGER, MMP3, and SERPINA1. A nonsynonymous variant, rs181206, in IL27 (P = 4.7 × 10−6) was just below the level of exome-wide significance but attained exome-wide significance (P = 5.7 × 10−8) when combined with results from other cohorts. Gene expression datasets revealed an association of rs181206 and the surrounding locus with expression of multiple genes; several were differentially expressed in COPD lung tissue, including TUFM. Conclusions: In an exome array analysis of COPD, we identified nonsynonymous variants at previously described loci and a novel exome-wide significant variant in IL27. This variant is at a locus previously described in genome-wide associations with diabetes, inflammatory bowel disease, and obesity and appears to affect genes potentially related to COPD pathogenesis. PMID:26771213

  20. Rapid-throughput skeletal phenotyping of 100 knockout mice identifies 9 new genes that determine bone strength.

    PubMed

    Bassett, J H Duncan; Gogakos, Apostolos; White, Jacqueline K; Evans, Holly; Jacques, Richard M; van der Spek, Anne H; Ramirez-Solis, Ramiro; Ryder, Edward; Sunter, David; Boyde, Alan; Campbell, Michael J; Croucher, Peter I; Williams, Graham R

    2012-01-01

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

  1. Human monogenic disease genes have frequently functionally redundant paralogs.

    PubMed

    Chen, Wei-Hua; Zhao, Xing-Ming; van Noort, Vera; Bork, Peer

    2013-01-01

    Mendelian disorders are often caused by mutations in genes that are not lethal but induce functional distortions leading to diseases. Here we study the extent of gene duplicates that might compensate genes causing monogenic diseases. We provide evidence for pervasive functional redundancy of human monogenic disease genes (MDs) by duplicates by manifesting 1) genes involved in human genetic disorders are enriched in duplicates and 2) duplicated disease genes tend to have higher functional similarities with their closest paralogs in contrast to duplicated non-disease genes of similar age. We propose that functional compensation by duplication of genes masks the phenotypic effects of deleterious mutations and reduces the probability of purging the defective genes from the human population; this functional compensation could be further enhanced by higher purification selection between disease genes and their duplicates as well as their orthologous counterpart compared to non-disease genes. However, due to the intrinsic expression stochasticity among individuals, the deleterious mutations could still be present as genetic diseases in some subpopulations where the duplicate copies are expressed at low abundances. Consequently the defective genes are linked to genetic disorders while they continue propagating within the population. Our results provide insight into the molecular basis underlying the spreading of duplicated disease genes.

  2. [Development of gene therapy in major brain diseases].

    PubMed

    Fan, Li; Jiang, Xin-guo

    2010-09-01

    In recent years, the development of molecular biology and medicine has prompted the research of gene therapy for brain diseases. In this review, we summarized the current gene therapy approaches of major brain diseases. Against the pathogenesis of major brain diseases, including brain tumors, Parkinson's disease, Alzheimer's disease and cerebrovascular disorders, there are several effective gene therapy strategies. It is no doubt that, gene therapy, as a novel treatment, is of great significance for understanding the causes, as well as comprehensive treatment for brain diseases.

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

    PubMed Central

    Greene, Daniel; Richardson, Sylvia; Turro, Ernest

    2016-01-01

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

  4. PhenomeScape: a cytoscape app to identify differentially regulated sub-networks using known disease associations

    PubMed Central

    Soul, Jamie; Dunn, Sara L.; Hardingham, Tim E.; Boot-Handford, Ray P.; Schwartz, Jean-Marc

    2016-01-01

    Summary: PhenomeScape is a Cytoscape app which provides easy access to the PhenomeExpress algorithm to interpret gene expression data. PhenomeExpress integrates protein interaction networks with known phenotype to gene associations to find active sub-networks enriched in differentially expressed genes. It also incorporates cross-species phenotypes and associations to include results from animal models of disease. With expression data imported into PhenomeScape, the user can quickly generate and visualise interactive sub-networks. PhenomeScape thus enables researchers to use prior knowledge of a disease to identify differentially regulated sub-networks and to generate an overview of altered biologically processes specific to that disease. Availability and Implementation: Freely available for download at https://github.com/soulj/PhenomeScape Contact: jamie.soul@postgrad.manchester.ac.uk or jean-marc.schwartz@manchester.ac.uk PMID:27559157

  5. PhenomeScape: a cytoscape app to identify differentially regulated sub-networks using known disease associations.

    PubMed

    Soul, Jamie; Dunn, Sara L; Hardingham, Tim E; Boot-Handford, Ray P; Schwartz, Jean-Marc

    2016-12-15

    PhenomeScape is a Cytoscape app which provides easy access to the PhenomeExpress algorithm to interpret gene expression data. PhenomeExpress integrates protein interaction networks with known phenotype to gene associations to find active sub-networks enriched in differentially expressed genes. It also incorporates cross-species phenotypes and associations to include results from animal models of disease. With expression data imported into PhenomeScape, the user can quickly generate and visualise interactive sub-networks. PhenomeScape thus enables researchers to use prior knowledge of a disease to identify differentially regulated sub-networks and to generate an overview of altered biologically processes specific to that disease.

  6. Using Network Extracted Ontologies to Identify Novel Genes with Roles in Appressorium Development in the Rice Blast Fungus Magnaporthe oryzae

    PubMed Central

    Ames, Ryan M.

    2017-01-01

    Magnaporthe oryzae is the causal agent of rice blast disease, the most important infection of rice worldwide. Half the world’s population depends on rice for its primary caloric intake and, as such, rice blast poses a serious threat to food security. The stages of M. oryzae infection are well defined, with the formation of an appressorium, a cell type that allows penetration of the plant cuticle, particularly well studied. However, many of the key pathways and genes involved in this disease stage are yet to be identified. In this study, I have used network-extracted ontologies (NeXOs), hierarchical structures inferred from RNA-Seq data, to identify pathways involved in appressorium development, which in turn highlights novel genes with potential roles in this process. This study illustrates the use of NeXOs for pathway identification from large-scale genomics data and also identifies novel genes with potential roles in disease. The methods presented here will be useful to study disease processes in other pathogenic species and these data represent predictions of novel targets for intervention in M. oryzae. PMID:28106722

  7. Genotype-based association models of complex diseases to detect gene-gene and gene-environment interactions.

    PubMed

    Lobach, Iryna; Fan, Ruzong; Manga, Prashiela

    A central problem in genetic epidemiology is to identify and rank genetic markers involved in a disease. Complex diseases, such as cancer, hypertension, diabetes, are thought to be caused by an interaction of a panel of genetic factors, that can be identified by markers, which modulate environmental factors. Moreover, the effect of each genetic marker may be small. Hence, the association signal may be missed unless a large sample is considered, or a priori biomedical data are used. Recent advances generated a vast variety of a priori information, including linkage maps and information about gene regulatory dependence assembled into curated pathway databases. We propose a genotype-based approach that takes into account linkage disequilibrium (LD) information between genetic markers that are in moderate LD while modeling gene-gene and gene-environment interactions. A major advantage of our method is that the observed genetic information enters a model directly thus eliminating the need to estimate haplotype-phase. Our approach results in an algorithm that is inexpensive computationally and does not suffer from bias induced by haplotype-phase ambiguity. We investigated our model in a series of simulation experiments and demonstrated that the proposed approach results in estimates that are nearly unbiased and have small variability. We applied our method to the analysis of data from a melanoma case-control study and investigated interaction between a set of pigmentation genes and environmental factors defined by age and gender. Furthermore, an application of our method is demonstrated using a study of Alcohol Dependence.

  8. Leber congenital amaurosis: genes, proteins and disease mechanisms.

    PubMed

    den Hollander, Anneke I; Roepman, Ronald; Koenekoop, Robert K; Cremers, Frans P M

    2008-07-01

    Leber congenital amaurosis (LCA) is the most severe retinal dystrophy causing blindness or severe visual impairment before the age of 1 year. Linkage analysis, homozygosity mapping and candidate gene analysis facilitated the identification of 14 genes mutated in patients with LCA and juvenile retinal degeneration, which together explain approximately 70% of the cases. Several of these genes have also been implicated in other non-syndromic or syndromic retinal diseases, such as retinitis pigmentosa and Joubert syndrome, respectively. CEP290 (15%), GUCY2D (12%), and CRB1 (10%) are the most frequently mutated LCA genes; one intronic CEP290 mutation (p.Cys998X) is found in approximately 20% of all LCA patients from north-western Europe, although this frequency is lower in other populations. Despite the large degree of genetic and allelic heterogeneity, it is possible to identify the causative mutations in approximately 55% of LCA patients by employing a microarray-based, allele-specific primer extension analysis of all known DNA variants. The LCA genes encode proteins with a wide variety of retinal functions, such as photoreceptor morphogenesis (CRB1, CRX), phototransduction (AIPL1, GUCY2D), vitamin A cycling (LRAT, RDH12, RPE65), guanine synthesis (IMPDH1), and outer segment phagocytosis (MERTK). Recently, several defects were identified that are likely to affect intra-photoreceptor ciliary transport processes (CEP290, LCA5, RPGRIP1, TULP1). As the eye represents an accessible and immune-privileged organ, it appears to be uniquely suitable for human gene replacement therapy. Rodent (Crb1, Lrat, Mertk, Rpe65, Rpgrip1), avian (Gucy2D) and canine (Rpe65) models for LCA and profound visual impairment have been successfully corrected employing adeno-associated virus or lentivirus-based gene therapy. Moreover, phase 1 clinical trials have been carried out in humans with RPE65 deficiencies. Apart from ethical considerations inherently linked to treating children, major

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

    PubMed Central

    Zhao, Junfei; Sheng, Jinsong; Rubin, Donald H.

    2016-01-01

    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. PMID:27632082

  10. Aging syndrome genes and premature coronary artery disease

    PubMed Central

    Low, Adrian F; O'Donnell, Christopher J; Kathiresan, Sekar; Everett, Brendan; Chae, Claudia U; Shaw, Stanley Y; Ellinor, Patrick T; MacRae, Calum A

    2005-01-01

    Background Vascular disease is a feature of aging, and coronary vascular events are a major source of morbidity and mortality in rare premature aging syndromes. One such syndrome is caused by mutations in the lamin A/C (LMNA) gene, which also has been implicated in familial insulin resistance. A second gene related to premature aging in man and in murine models is the KLOTHO gene, a hypomorphic variant of which (KL-VS) is significantly more common in the first-degree relatives of patients with premature coronary artery disease (CAD). We evaluated whether common variants at the LMNA or KLOTHO genes are associated with rigorously defined premature CAD. Methods We identified 295 patients presenting with premature acute coronary syndromes confirmed by angiography. A control group of 145 patients with no evidence of CAD was recruited from outpatient referral clinics. Comprehensive haplotyping of the entire LMNA gene, including the promoter and untranslated regions, was performed using a combination of TaqMan® probes and direct sequencing of 14 haplotype-tagging single nucleotide polymorphisms (SNPs). The KL-VS variant of the KLOTHO gene was typed using restriction digest of a PCR amplicon. Results Two SNPs that were not in Hardy Weinberg equilibrium were excluded from analysis. We observed no significant differences in allele, genotype or haplotype frequencies at the LMNA or KLOTHO loci between the two groups. In addition, there was no evidence of excess homozygosity at the LMNA locus. Conclusion Our data do not support the hypothesis that premature CAD is associated with common variants in the progeroid syndrome genes LMNA and KLOTHO. PMID:16262891

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

    PubMed Central

    Chen, Yong; Jiang, Tao; Jiang, Rui

    2011-01-01

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

  12. Identifying Neisseria Species by Use of the 50S Ribosomal Protein L6 (rplF) Gene

    PubMed Central

    Bennett, Julia S.; Watkins, Eleanor R.; Jolley, Keith A.; Harrison, Odile B.

    2014-01-01

    The comparison of 16S rRNA gene sequences is widely used to differentiate bacteria; however, this gene can lack resolution among closely related but distinct members of the same genus. This is a problem in clinical situations in those genera, such as Neisseria, where some species are associated with disease while others are not. Here, we identified and validated an alternative genetic target common to all Neisseria species which can be readily sequenced to provide an assay that rapidly and accurately discriminates among members of the genus. Ribosomal multilocus sequence typing (rMLST) using ribosomal protein genes has been shown to unambiguously identify these bacteria. The PubMLST Neisseria database (http://pubmlst.org/neisseria/) was queried to extract the 53 ribosomal protein gene sequences from 44 genomes from diverse species. Phylogenies reconstructed from these genes were examined, and a single 413-bp fragment of the 50S ribosomal protein L6 (rplF) gene was identified which produced a phylogeny that was congruent with the phylogeny reconstructed from concatenated ribosomal protein genes. Primers that enabled the amplification and direct sequencing of the rplF gene fragment were designed to validate the assay in vitro and in silico. Allele sequences were defined for the gene fragment, associated with particular species names, and stored on the PubMLST Neisseria database, providing a curated electronic resource. This approach provides an alternative to 16S rRNA gene sequencing, which can be readily replicated for other organisms for which more resolution is required, and it has potential applications in high-resolution metagenomic studies. PMID:24523465

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

    PubMed

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

    2016-01-01

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

  14. Identifying predictors of hospice eligibility in patients with Parkinson disease.

    PubMed

    Goy, Elizabeth R; Bohlig, Amanda; Carter, Julie; Ganzini, Linda

    2015-02-01

    This study aims to improve recognition of hospice eligibility for patients with Parkinson disease (PD) by ascertaining which variables have a higher probability of occurring uniquely in 6 to 12 months before death when compared to 18 to 24 months before death. Participants were 339 patients who died who were diagnosed with PD or Parkinsonism and treated with dopaminergic prescriptions for at least 3 years in northwestern US Veterans Affairs medical centers. A range of indicators were compared across 3 time periods (30-36 months, 24-18 months, and 12-6 months before death) using within-subjects repeated measures design. Results indicate that body mass index less than 18, alone or combined with a shift in prescribing (when benefits of dopaminergic medications no longer outweigh their risk of side effects), may signal appropriate timing for hospice referral.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2015-01-01

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

  18. Identifying the optimal gene and gene set in hepatocellular carcinoma based on differential expression and differential co-expression algorithm.

    PubMed

    Dong, Li-Yang; Zhou, Wei-Zhong; Ni, Jun-Wei; Xiang, Wei; Hu, Wen-Hao; Yu, Chang; Li, Hai-Yan

    2017-02-01

    The objective of this study was to identify the optimal gene and gene set for hepatocellular carcinoma (HCC) utilizing differential expression and differential co-expression (DEDC) algorithm. The DEDC algorithm consisted of four parts: calculating differential expression (DE) by absolute t-value in t-statistics; computing differential co-expression (DC) based on Z-test; determining optimal thresholds on the basis of Chi-squared (χ2) maximization and the corresponding gene was the optimal gene; and evaluating functional relevance of genes categorized into different partitions to determine the optimal gene set with highest mean minimum functional information (FI) gain (Δ*G). The optimal thresholds divided genes into four partitions, high DE and high DC (HDE-HDC), high DE and low DC (HDE-LDC), low DE and high DC (LDE‑HDC), and low DE and low DC (LDE-LDC). In addition, the optimal gene was validated by conducting reverse transcription-polymerase chain reaction (RT-PCR) assay. The optimal threshold for DC and DE were 1.032 and 1.911, respectively. Using the optimal gene, the genes were divided into four partitions including: HDE-HDC (2,053 genes), HED-LDC (2,822 genes), LDE-HDC (2,622 genes), and LDE-LDC (6,169 genes). The optimal gene was microtubule‑associated protein RP/EB family member 1 (MAPRE1), and RT-PCR assay validated the significant difference between the HCC and normal state. The optimal gene set was nucleoside metabolic process (GO\\GO:0009116) with Δ*G = 18.681 and 24 HDE-HDC partitions in total. In conclusion, we successfully investigated the optimal gene, MAPRE1, and gene set, nucleoside metabolic process, which may be potential biomarkers for targeted therapy and provide significant insight for revealing the pathological mechanism underlying HCC.

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

    PubMed Central

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

    1993-01-01

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

  20. An Integrative Transcriptomic Analysis for Identifying Novel Target Genes Corresponding to Severity Spectrum in Spinal Muscular Atrophy

    PubMed Central

    Yang, Chung-Wei; Chen, Chien-Lin; Chou, Wei-Chun; Lin, Ho-Chen; Jong, Yuh-Jyh; Tsai, Li-Kai; Chuang, Chun-Yu

    2016-01-01

    Spinal muscular atrophy (SMA) is an inherited neuromuscular disease resulting from a recessive mutation in the SMN1 gene. This disease affects multiple organ systems with varying degrees of severity. Exploration of the molecular pathological changes occurring in different cell types in SMA is crucial for developing new therapies. This study collected 39 human microarray datasets from ArrayExpress and GEO databases to build an integrative transcriptomic analysis for recognizing novel SMA targets. The transcriptomic analysis was conducted through combining weighted correlation network analysis (WGCNA) for gene module detection, gene set enrichment analysis (GSEA) for functional categorization and filtration, and Cytoscape (visual interaction gene network analysis) for target gene identification. Seven novel target genes (Bmp4, Serpine1, Gata6, Ptgs2, Bcl2, IL6 and Cntn1) of SMA were revealed, and are all known in the regulation of TNFα for controlling neural, cardiac and bone development. Sequentially, the differentially expressed patterns of these 7 target genes in mouse tissues (e.g., spinal cord, heart, muscles and bone) were validated in SMA mice of different severities (pre-symptomatic, mildly symptomatic, and severely symptomatic). In severely symptomatic SMA mice, TNFα was up-regulated with attenuation of Bmp4 and increase of Serpine1 and Gata6 (a pathway in neural and cardiac development), but not in pre-symptomatic and mildly symptomatic SMA mice. The severely symptomatic SMA mice also had the elevated levels of Ptgs2 and Bcl2 (a pathway in skeletal development) as well as IL6 and Cntn1 (a pathway in nervous system development). Thus, the 7 genes identified in this study might serve as potential target genes for future investigations of disease pathogenesis and SMA therapy. PMID:27331400

  1. Mapping autosomal recessive intellectual disability: combined microarray and exome sequencing identifies 26 novel candidate genes in 192 consanguineous families.

    PubMed

    Harripaul, R; Vasli, N; Mikhailov, A; Rafiq, M A; Mittal, K; Windpassinger, C; Sheikh, T I; Noor, A; Mahmood, H; Downey, S; Johnson, M; Vleuten, K; Bell, L; Ilyas, M; Khan, F S; Khan, V; Moradi, M; Ayaz, M; Naeem, F; Heidari, A; Ahmed, I; Ghadami, S; Agha, Z; Zeinali, S; Qamar, R; Mozhdehipanah, H; John, P; Mir, A; Ansar, M; French, L; Ayub, M; Vincent, J B

    2017-04-11

    Approximately 1% of the global population is affected by intellectual disability (ID), and the majority receive no molecular diagnosis. Previous studies have indicated high levels of genetic heterogeneity, with estimates of more than 2500 autosomal ID genes, the majority of which are autosomal recessive (AR). Here, we combined microarray genotyping, homozygosity-by-descent (HBD) mapping, copy number variation (CNV) analysis, and whole exome sequencing (WES) to identify disease genes/mutations in 192 multiplex Pakistani and Iranian consanguineous families with non-syndromic ID. We identified definite or candidate mutations (or CNVs) in 51% of families in 72 different genes, including 26 not previously reported for ARID. The new ARID genes include nine with loss-of-function mutations (ABI2, MAPK8, MPDZ, PIDD1, SLAIN1, TBC1D23, TRAPPC6B, UBA7 and USP44), and missense mutations include the first reports of variants in BDNF or TET1 associated with ID. The genes identified also showed overlap with de novo gene sets for other neuropsychiatric disorders. Transcriptional studies showed prominent expression in the prenatal brain. The high yield of AR mutations for ID indicated that this approach has excellent clinical potential and should inform clinical diagnostics, including clinical whole exome and genome sequencing, for populations in which consanguinity is common. As with other AR disorders, the relevance will also apply to outbred populations.Molecular Psychiatry advance online publication, 11 April 2017; doi:10.1038/mp.2017.60.

  2. The ANKH gene and familial calcium pyrophosphate dihydrate deposition disease.

    PubMed

    Netter, Patrick; Bardin, Thomas; Bianchi, Arnaud; Richette, Pascal; Loeuille, Damien

    2004-09-01

    Familial calcium pyrophosphate dihydrate deposition (CPPD) disease is a chronic condition in which CPPD microcrystals deposit in the joint fluid, cartilage, and periarticular tissues. Two forms of familial CPPD disease have been identified: CCAL1 and CCAL2. The CCAL1 locus is located on the long arm of chromosome 8 and is associated with CPPD and severe osteoarthritis. The CCAL2 locus has been mapped to the short arm of chromosome 5 and identified in families from the Alsace region of France and the United Kingdom. The ANKH protein is involved in pyrophosphate metabolism and, more specifically, in pyrophosphate transport from the intracellular to the extracellular compartment. Numerous ANKH gene mutations cause familial CCAL2; they enhance ANKH protein activity, thereby elevating extracellular pyrophosphate levels and promoting the formation of pyrophosphate crystals, which produce the manifestations of the disease. Recent studies show that growth factors and cytokines can modify the expression of the normal ANKH protein. These results suggest a role for ANKH in sporadic CPPD disease and in CPPD associated with degenerative disease.

  3. Gene Expression Signature-Based Screening Identifies New Broadly Effective Influenza A Antivirals

    PubMed Central

    Josset, Laurence; Textoris, Julien; Loriod, Béatrice; Ferraris, Olivier; Moules, Vincent; Lina, Bruno; N'Guyen, Catherine; Diaz, Jean-Jacques; Rosa-Calatrava, Manuel

    2010-01-01

    Classical antiviral therapies target viral proteins and are consequently subject to resistance. To counteract this limitation, alternative strategies have been developed that target cellular factors. We hypothesized that such an approach could also be useful to identify broad-spectrum antivirals. The influenza A virus was used as a model for its viral diversity and because of the need to develop therapies against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection by different influenza A virus subtypes which would allow the identification of potential antiviral drugs with a broad anti-influenza spectrum of activity. We analyzed the cellular gene expression response to infection with five different human and avian influenza A virus strains and identified 300 genes as differentially expressed between infected and non-infected samples. The most 20 dysregulated genes were used to screen the connectivity map, a database of drug-associated gene expression profiles. Candidate antivirals were then identified by their inverse correlation to the query signature. We hypothesized that such molecules would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified and their effects were tested in vitro on five influenza A strains. Six of the molecules inhibited influenza viral growth. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five out of the eight identified molecules, demonstrating that this strategy could contribute to identifying new broad anti-influenza agents acting on cellular gene expression. The identified infection signature genes, the expression of which are modified upon infection, could encode cellular proteins involved in the viral life cycle. This is the first study showing that gene expression-based screening can be

  4. Transcriptome sequencing of neurologic diseases associated genes in HHV-6A infected human astrocyte

    PubMed Central

    Tang, Junwei; Lu, Shuai; Feng, Dongju; Cheng, Ci; Qing, Lanqun; Yao, Kun; Chen, Yun

    2016-01-01

    Human Herpesvirus 6 (HHV-6) has been involved in the development of several central nervous system (CNS) diseases, such as Alzheimer's disease, multiple sclerosis and glioma. In order to identify the pathogenic mechanism of HHV-6A infection, we carried out mRNA-seq study of human astrocyte HA1800 cell with HHV-6A GS infection. Using mRNA-seq analysis of HA1800-control cells with HA1800-HHV-6A GS cells, we identified 249 differentially expressed genes. After investigating these candidate genes, we found seven genes associated with two or more CNS diseases: CTSS, PTX3, CHI3L1, Mx1, CXCL16, BIRC3, and BST2. This is the first transcriptome sequencing study which showed the significant association of these genes between HHV-6A infection and neurologic diseases. We believe that our findings can provide a new perspective to understand the pathogenic mechanism of HHV-6A infection and neurologic diseases. PMID:27344170

  5. Whole exome sequencing identifies three recessive FIG4 mutations in an apparently dominant pedigree with Charcot-Marie-Tooth disease.

    PubMed

    Menezes, Manoj P; Waddell, Leigh; Lenk, Guy M; Kaur, Simranpreet; MacArthur, Daniel G; Meisler, Miriam H; Clarke, Nigel F

    2014-08-01

    Charcot-Marie-Tooth disease (CMT) is genetically heterogeneous and classification based on motor nerve conduction velocity and inheritance is used to direct genetic testing. With the less common genetic forms of CMT, identifying the causative genetic mutation by Sanger sequencing of individual genes can be time-consuming and costly. Next-generation sequencing technologies show promise for clinical testing in diseases where a similar phenotype is caused by different genes. We report the unusual occurrence of CMT4J, caused by mutations in FIG4, in a apparently dominant pedigree. The affected proband and her mother exhibit different disease severities associated with different combinations of compound heterozygous FIG4 mutations, identified by whole exome sequencing. The proband was also shown to carry a de novo nonsense mutation in the dystrophin gene, which may contribute to her more severe phenotype. This study is a cautionary reminder that in families with two generations affected, explanations other than dominant inheritance are possible, such as recessive inheritance due to three mutations segregating in the family. It also emphasises the advantages of next-generation sequencing approaches that screen multiple CMT genes at once for patients in whom the common genes have been excluded.

  6. 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

  7. Newborn Screening Quality Assurance Program for CFTR Mutation Detection and Gene Sequencing to Identify Cystic Fibrosis

    PubMed Central

    Hendrix, Miyono M.; Foster, Stephanie L.; Cordovado, Suzanne K.

    2016-01-01

    All newborn screening laboratories in the United States and many worldwide screen for cystic fibrosis. Most laboratories use a second-tier genotyping assay to identify a panel of mutations in the CF transmembrane regulator (CFTR) gene. Centers for Disease Control and Prevention’s Newborn Screening Quality Assurance Program houses a dried blood spot repository of samples containing CFTR mutations to assist newborn screening laboratories and ensure high-quality mutation detection in a high-throughput environment. Recently, CFTR mutation detection has increased in complexity with expanded genotyping panels and gene sequencing. To accommodate the growing quality assurance needs, the repository samples were characterized with several multiplex genotyping methods, Sanger sequencing, and 3 next-generation sequencing assays using a high-throughput, low-concentration DNA extraction method. The samples performed well in all of the assays, providing newborn screening laboratories with a resource for complex CFTR mutation detection and next-generation sequencing as they transition to new methods. PMID:28261631

  8. 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

  9. Utility and Limitations of Using Gene Expression Data to Identify Functional Associations

    PubMed Central

    Peng, Cheng; Shiu, Shin-Han

    2016-01-01

    Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets. PMID:27935950

  10. Systems Biology Approach to Identify Gene Network Signatures for Colorectal Cancer

    PubMed Central

    Sonachalam, Madhankumar; Shen, Jeffrey; Huang, Hui; Wu, Xiaogang

    2012-01-01

    In this work, we integrated prior knowledge from gene signatures and protein interactions with gene set enrichment analysis (GSEA), and gene/protein network modeling together to identify gene network signatures from gene expression microarray data. We demonstrated how to apply this approach into discovering gene network signatures for colorectal cancer (CRC) from microarray datasets. First, we used GSEA to analyze the microarray data through enriching differential genes in different CRC-related gene sets from two publicly available up-to-date gene set databases – Molecular Signatures Database (MSigDB) and Gene Signatures Database (GeneSigDB). Second, we compared the enriched gene sets through enrichment score, false-discovery rate, and nominal p-value. Third, we constructed an integrated protein–protein interaction (PPI) network through connecting these enriched genes by high-quality interactions from a human annotated and predicted protein interaction database, with a confidence score labeled for each interaction. Finally, we mapped differential gene expressions onto the constructed network to build a comprehensive network model containing visualized transcriptome and proteome data. The results show that although MSigDB has more CRC-relevant gene sets than GeneSigDB, the integrated PPI network connecting the enriched genes from both MSigDB and GeneSigDB can provide a more complete view for discovering gene network signatures. We also found several important sub-network signatures for CRC, such as TP53 sub-network, PCNA sub-network, and IL8 sub-network, corresponding to apoptosis, DNA repair, and immune response, respectively. PMID:22629282

  11. Update of the G2D tool for prioritization of gene candidates to inherited diseases

    PubMed Central

    Perez-Iratxeta, Carolina; Bork, Peer; Andrade-Navarro, Miguel A.

    2007-01-01

    G2D (genes to diseases) is a web resource for prioritizing genes as candidates for inherited diseases. It uses three algorithms based on different prioritization strategies. The input to the server is the genomic region where the user is looking for the disease-causing mutation, plus an additional piece of information depending on the algorithm used. This information can either be the disease phenotype (described as an online Mendelian inheritance in man (OMIM) identifier), one or several genes known or suspected to be associated with the disease (defined by their Entrez Gene identifiers), or a second genomic region that has been linked as well to the disease. In the latter case, the tool uses known or predicted interactions between genes in the two regions extracted from the STRING database. The output in every case is an ordered list of candidate genes in the region of interest. For the first two of the three methods, the candidate genes are first retrieved through sequence homology search, then scored accordingly to the corresponding method. This means that some of them will correspond to well-known characterized genes, and others will overlap with predicted genes, thus providing a wider analysis. G2D is publicly available at http://www.ogic.ca/projects/g2d_2/ PMID:17478516

  12. Discovery of gene-gene interactions across multiple independent datasets of Late Onset Alzheimer Disease from the Alzheimer Disease Genetics Consortium

    PubMed Central

    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.

    2015-01-01

    Late-onset Alzheimer disease (LOAD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance and gene-gene interactions; however, the investigation of interactions in recent GWAS has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across thirteen datasets from the Alzheimer Disease Genetics Consortium. Fifteen SNP-SNP pairs within three gene-gene combinations were identified: SIRT1 x ABCB1, PSAP x PEBP4, and GRIN2B x ADRA1A. Additionally, we extend a previously identified interaction from an endophenotype analysis between RYR3 x 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 manuscript highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis. PMID:26827652

  13. 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.

  14. On the origins of Mendelian disease genes in man: the impact of gene duplication.

    PubMed

    Dickerson, Jonathan E; Robertson, David L

    2012-01-01

    Over 3,000 human diseases are known to be linked to heritable genetic variation, mapping to over 1,700 unique genes. Dating of the evolutionary age of these disease-associated genes has suggested that they have a tendency to be ancient, specifically coming into existence with early metazoa. The approach taken by past studies, however, assumes that the age of a disease is the same as the age of its common ancestor, ignoring the fundamental contribution of duplication events in the evolution of new genes and function. Here, we date both the common ancestor and the duplication history of known human disease-associated genes. We find that the majority of disease genes (80%) are genes that have been duplicated in their evolutionary history. Periods for which there are more disease-associated genes, for example, at the origins of bony vertebrates, are explained by the emergence of more genes at that time, and the majority of these are duplicates inferred to have arisen by whole-genome duplication. These relationships are similar for different disease types and the disease-associated gene's cellular function. This indicates that the emergence of duplication-associated diseases has been ongoing and approximately constant (relative to the retention of duplicate genes) throughout the evolution of life. This continued until approximately 390 Ma from which time relatively fewer novel genes came into existence on the human lineage, let alone disease genes. For single-copy genes associated with disease, we find that the numbers of disease genes decreases with recency. For the majority of duplicates, the disease-associated mutation is associated with just one of the duplicate copies. A universal explanation for heritable disease is, thus, that it is merely a by-product of the evolutionary process; the evolution of new genes (de novo or by duplication) results in the potential for new diseases to emerge.

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

    PubMed

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

    2015-01-01

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

  16. Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification

    PubMed Central

    Chen, Liming; Jenjaroenpun, Piroon; Pillai, Andrea Mun Ching; Ivshina, Anna V.; Ow, Ghim Siong; Efthimios, Motakis; Zhiqun, Tang; Lee, Song-Choon; Rogers, Keith; Ward, Jerrold M.; Mori, Seiichi; Adams, David J.; Jenkins, Nancy A.; Copeland, Neal G.; Ban, Kenneth Hon-Kim; Kuznetsov, Vladimir A.; Thiery, Jean Paul

    2017-01-01

    Robust prognostic gene signatures and therapeutic targets are difficult to derive from expression profiling because of the significant heterogeneity within breast cancer (BC) subtypes. Here, we performed forward genetic screening in mice using Sleeping Beauty transposon mutagenesis to identify candidate BC driver genes in an unbiased manner, using a stabilized N-terminal truncated β-catenin gene as a sensitizer. We identified 134 mouse susceptibility genes from 129 common insertion sites within 34 mammary tumors. Of these, 126 genes were orthologous to protein-coding genes in the human genome (hereafter, human BC susceptibility genes, hBCSGs), 70% of which are previously reported cancer-associated genes, and ∼16% are known BC suppressor genes. Network analysis revealed a gene hub consisting of E1A binding protein P300 (EP300), CD44 molecule (CD44), neurofibromin (NF1) and phosphatase and tensin homolog (PTEN), which are linked to a significant number of mutated hBCSGs. From our survival prediction analysis of the expression of human BC genes in 2,333 BC cases, we isolated a six-gene-pair classifier that stratifies BC patients with high confidence into prognostically distinct low-, moderate-, and high-risk subgroups. Furthermore, we proposed prognostic classifiers identifying three basal and three claudin-low tumor subgroups. Intriguingly, our hBCSGs are mostly unrelated to cell cycle/mitosis genes and are distinct from the prognostic signatures currently used for stratifying BC patients. Our findings illustrate the strength and validity of integrating functional mutagenesis screens in mice with human cancer transcriptomic data to identify highly prognostic BC subtyping biomarkers. PMID:28251929

  17. Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification.

    PubMed

    Chen, Liming; Jenjaroenpun, Piroon; Pillai, Andrea Mun Ching; Ivshina, Anna V; Ow, Ghim Siong; Efthimios, Motakis; Zhiqun, Tang; Tan, Tuan Zea; Lee, Song-Choon; Rogers, Keith; Ward, Jerrold M; Mori, Seiichi; Adams, David J; Jenkins, Nancy A; Copeland, Neal G; Ban, Kenneth Hon-Kim; Kuznetsov, Vladimir A; Thiery, Jean Paul

    2017-03-14

    Robust prognostic gene signatures and therapeutic targets are difficult to derive from expression profiling because of the significant heterogeneity within breast cancer (BC) subtypes. Here, we performed forward genetic screening in mice using Sleeping Beauty transposon mutagenesis to identify candidate BC driver genes in an unbiased manner, using a stabilized N-terminal truncated β-catenin gene as a sensitizer. We identified 134 mouse susceptibility genes from 129 common insertion sites within 34 mammary tumors. Of these, 126 genes were orthologous to protein-coding genes in the human genome (hereafter, human BC susceptibility genes, hBCSGs), 70% of which are previously reported cancer-associated genes, and ∼16% are known BC suppressor genes. Network analysis revealed a gene hub consisting of E1A binding protein P300 (EP300), CD44 molecule (CD44), neurofibromin (NF1) and phosphatase and tensin homolog (PTEN), which are linked to a significant number of mutated hBCSGs. From our survival prediction analysis of the expression of human BC genes in 2,333 BC cases, we isolated a six-gene-pair classifier that stratifies BC patients with high confidence into prognostically distinct low-, moderate-, and high-risk subgroups. Furthermore, we proposed prognostic classifiers identifying three basal and three claudin-low tumor subgroups. Intriguingly, our hBCSGs are mostly unrelated to cell cycle/mitosis genes and are distinct from the prognostic signatures currently used for stratifying BC patients. Our findings illustrate the strength and validity of integrating functional mutagenesis screens in mice with human cancer transcriptomic data to identify highly prognostic BC subtyping biomarkers.

  18. Using phylogenomic patterns and gene ontology to identify proteins of importance in plant evolution.

    PubMed

    Cibrián-Jaramillo, Angélica; De la Torre-Bárcena, Jose E; Lee, Ernest K; Katari, Manpreet S; Little, Damon P; Stevenson, Dennis W; Martienssen, Rob; Coruzzi, Gloria M; DeSalle, Rob

    2010-07-12

    We use measures of congruence on a combined expressed sequenced tag genome phylogeny to identify proteins that have potential significance in the evolution of seed plants. Relevant proteins are identified based on the direction of partitioned branch and hidden support on the hypothesis obtained on a 16-species tree, constructed from 2,557 concatenated orthologous genes. We provide a general method for detecting genes or groups of genes that may be under selection in directions that are in agreement with the phylogenetic pattern. Gene partitioning methods and estimates of the degree and direction of support of individual gene partitions to the overall data set are used. Using this approach, we correlate positive branch support of specific genes for key branches in the seed plant phylogeny. In addition to basic metabolic functions, such as photosynthesis or hormones, genes involved in posttranscriptional regulation by small RNAs were significantly overrepresented in key nodes of the phylogeny of seed plants. Two genes in our matrix are of critical importance as they are involved in RNA-dependent regulation, essential during embryo and leaf development. These are Argonaute and the RNA-dependent RNA polymerase 6 found to be overrepresented in the angiosperm clade. We use these genes as examples of our phylogenomics approach and show that identifying partitions or genes in this way provides a platform to explain some of the more interesting organismal differences among species, and in particular, in the evolution of plants.

  19. Genes identified by visible mutant phenotypes show increased bias toward one of two subgenomes of maize.

    PubMed

    Schnable, James C; Freeling, Michael

    2011-03-10

    Not all genes are created equal. Despite being supported by sequence conservation and expression data, knockout homozygotes of many genes show no visible effects, at least under laboratory conditions. We have identified a set of maize (Zea mays L.) genes which have been the subject of a disproportionate share of publications recorded at MaizeGDB. We manually anchored these "classical" maize genes to gene models in the B73 reference genome, and identified syntenic orthologs in other grass genomes. In addition to proofing the most recent version 2 maize gene models, we show that a subset of these genes, those that were identified by morphological phenotype prior to cloning, are retained at syntenic locations throughout the grasses at much higher levels than the average expressed maize gene, and are preferentially found on the maize1 subgenome even with a duplicate copy is still retained on the opposite subgenome. Maize1 is the subgenome that experienced less gene loss following the whole genome duplication in maize lineage 5-12 million years ago and genes located on this subgenome tend to be expressed at higher levels in modern maize. Links to the web based software that supported our syntenic analyses in the grasses should empower further research and support teaching involving the history of maize genetic research. Our findings exemplify the concept of "grasses as a single genetic system," where what is learned in one grass may be applied to another.

  20. Large-scale functional RNAi screen in C. elegans identifies genes that regulate the dysfunction of mutant polyglutamine neurons

    PubMed Central

    2012-01-01

    Background A central goal in Huntington's disease (HD) research is to identify and prioritize candidate targets for neuroprotective intervention, which requires genome-scale information on the modifiers of early-stage neuron injury in HD. Results Here, we performed a large-scale RNA interference screen in C. elegans strains that express N-terminal huntingtin (htt) in touch receptor neurons. These neurons control the response to light touch. Their function is strongly impaired by expanded polyglutamines (128Q) as shown by the nearly complete loss of touch response in adult animals, providing an in vivo model in which to manipulate the early phases of expanded-polyQ neurotoxicity. In total, 6034 genes were examined, revealing 662 gene inactivations that either reduce or aggravate defective touch response in 128Q animals. Several genes were previously implicated in HD or neurodegenerative disease, suggesting that this screen has effectively identified candidate targets for HD. Network-based analysis emphasized a subset of high-confidence modifier genes in pathways of interest in HD including metabolic, neurodevelopmental and pro-survival pathways. Finally, 49 modifiers of 128Q-neuron dysfunction that are dysregulated in the striatum of either R/2 or CHL2 HD mice, or both, were identified. Conclusions Collectively, these results highlight the relevance to HD pathogenesis, providing novel information on the potential therapeutic targets for neuroprotection in HD. PMID:22413862

  1. Integrated, multicohort analysis of systemic sclerosis identifies robust transcriptional signature of disease severity

    PubMed Central

    Lofgren, Shane; Aren, Kathleen; Arroyo, Esperanza; Cheung, Peggie; Kuo, Alex; Valenzuela, Antonia; Haemel, Anna; Wolters, Paul J.; Gordon, Jessica; Spiera, Robert; Assassi, Shervin; Boin, Francesco; Chung, Lorinda; Fiorentino, David; Utz, Paul J.; Whitfield, Michael L.

    2016-01-01

    Systemic sclerosis (SSc) is a rare autoimmune disease with the highest case-fatality rate of all connective tissue diseases. Current efforts to determine patient response to a given treatment using the modified Rodnan skin score (mRSS) are complicated by interclinician variability, confounding, and the time required between sequential mRSS measurements to observe meaningful change. There is an unmet critical need for an objective metric of SSc disease severity. Here, we performed an integrated, multicohort analysis of SSc transcriptome data across 7 datasets from 6 centers composed of 515 samples. Using 158 skin samples from SSc patients and healthy controls recruited at 2 centers as a discovery cohort, we identified a 415-gene expression signature specific for SSc, and validated its ability to distinguish SSc patients from healthy controls in an additional 357 skin samples from 5 independent cohorts. Next, we defined the SSc skin severity score (4S). In every SSc cohort of skin biopsy samples analyzed in our study, 4S correlated significantly with mRSS, allowing objective quantification of SSc disease severity. Using transcriptome data from the largest longitudinal trial of SSc patients to date, we showed that 4S allowed us to objectively monitor individual SSc patients over time, as (a) the change in 4S of a patient is significantly correlated with change in the mRSS, and (b) the change in 4S at 12 months of treatment could predict the change in mRSS at 24 months. Our results suggest that 4S could be used to distinguish treatment responders from nonresponders prior to mRSS change. Our results demonstrate the potential clinical utility of a novel robust molecular signature and a computational approach to SSc disease severity quantification. PMID:28018971

  2. Affected Kindred Analysis of Human X Chromosome Exomes to Identify Novel X-Linked Intellectual Disability Genes

    PubMed Central

    Niranjan, Tejasvi S.; Skinner, Cindy; May, Melanie; Turner, Tychele; Rose, Rebecca; Stevenson, Roger; Schwartz, Charles E.; Wang, Tao

    2015-01-01

    X-linked Intellectual Disability (XLID) is a group of genetically heterogeneous disorders caused by mutations in genes on the X chromosome. Deleterious mutations in ~10% of X chromosome genes are implicated in causing XLID disorders in ~50% of known and suspected XLID families. The remaining XLID genes are expected to be rare and even private to individual families. To systematically identify these XLID genes, we sequenced the X chromosome exome (X-exome) in 56 well-established XLID families (a single affected male from 30 families and two affected males from 26 families) using an Agilent SureSelect X-exome kit and the Illumina HiSeq 2000 platform. To enrich for disease-causing mutations, we first utilized variant filters based on dbSNP, the male-restricted portions of the 1000 Genomes Project, or the Exome Variant Server datasets. However, these databases present limitations as automatic filters for enrichment of XLID genes. We therefore developed and optimized a strategy that uses a cohort of affected male kindred pairs and an additional small cohort of affected unrelated males to enrich for potentially pathological variants and to remove neutral variants. This strategy, which we refer to as Affected Kindred/Cross-Cohort Analysis, achieves a substantial enrichment for potentially pathological variants in known XLID genes compared to variant filters from public reference databases, and it has identified novel XLID candidate genes. We conclude that Affected Kindred/Cross-Cohort Analysis can effectively enrich for disease-causing genes in rare, Mendelian disorders, and that public reference databases can be used effectively, but cautiously, as automatic filters for X-linked disorders. PMID:25679214

  3. Affected kindred analysis of human X chromosome exomes to identify novel X-linked intellectual disability genes.

    PubMed

    Niranjan, Tejasvi S; Skinner, Cindy; May, Melanie; Turner, Tychele; Rose, Rebecca; Stevenson, Roger; Schwartz, Charles E; Wang, Tao

    2015-01-01

    X-linked Intellectual Disability (XLID) is a group of genetically heterogeneous disorders caused by mutations in genes on the X chromosome. Deleterious mutations in ~10% of X chromosome genes are implicated in causing XLID disorders in ~50% of known and suspected XLID families. The remaining XLID genes are expected to be rare and even private to individual families. To systematically identify these XLID genes, we sequenced the X chromosome exome (X-exome) in 56 well-established XLID families (a single affected male from 30 families and two affected males from 26 families) using an Agilent SureSelect X-exome kit and the Illumina HiSeq 2000 platform. To enrich for disease-causing mutations, we first utilized variant filters based on dbSNP, the male-restricted portions of the 1000 Genomes Project, or the Exome Variant Server datasets. However, these databases present limitations as automatic filters for enrichment of XLID genes. We therefore developed and optimized a strategy that uses a cohort of affected male kindred pairs and an additional small cohort of affected unrelated males to enrich for potentially pathological variants and to remove neutral variants. This strategy, which we refer to as Affected Kindred/Cross-Cohort Analysis, achieves a substantial enrichment for potentially pathological variants in known XLID genes compared to variant filters from public reference databases, and it has identified novel XLID candidate genes. We conclude that Affected Kindred/Cross-Cohort Analysis can effectively enrich for disease-causing genes in rare, Mendelian disorders, and that public reference databases can be used effectively, but cautiously, as automatic filters for X-linked disorders.

  4. Gene Transcript Abundance Profiles Distinguish Kawasaki Disease from Adenovirus Infection

    PubMed Central

    Popper, Stephen J.; Watson, Virginia E.; Shimizu, Chisato; Kanegaye, John T.; Burns, Jane C.; Relman, David A.

    2010-01-01

    Background Acute Kawasaki disease (KD) is difficult to distinguish from other illnesses that involve acute rash or fever, in part because the etiologic agent(s) and pathophysiology remain poorly characterized. As a result, diagnosis and critical therapies may be delayed. Methods We used DNA microarrays to identify possible diagnostic features of KD. We compared gene expression patterns in the blood of 23 children with acute KD and 18 age-matched febrile children with 3 illnesses that resemble KD. Results Genes associated with platelet and neutrophil activation were expressed at higher levels in patients with KD than in patients with acute adenovirus infections or systemic adverse drug reactions, but levels in patients with KD were not higher than those in patients with scarlet fever. Genes associated with B cell activation were also expressed at higher levels in patients with KD than in control subjects. A striking absence of interferon-stimulated gene expression in patients with KD was confirmed in an independent cohort of patients with KD. Using a set of 38 gene transcripts, we successfully predicted the diagnosis for 21 of 23 patients with KD and 7 of 8 patients with adenovirus infection. Conclusions These findings provide insight into the molecular features that distinguish KD from other febrile illnesses and support the feasibility of developing novel diagnostic reagents for KD based on the host response. PMID:19583510

  5. A novel reverse-genetic approach (SIMF) identifies Mutator insertions in new Myb genes.

    PubMed

    Rabinowicz, P D; Grotewold, E

    2000-11-01

    We have developed a new strategy designated SIMF (Systematic Insertional Mutagenesis of Families), to identify DNA insertions in many members of a gene family simultaneously. This method requires only a short amino acid sequence conserved in all members of the family to make a degenerate oligonucleotide, and a sequence from the end of the DNA insertion. The SIMF strategy was successfully applied to the large maize R2R3 Myb family of regulatory genes, and Mutator insertions in several novel Myb genes were identified. Application of this technique to identify insertions in other large gene families could significantly decrease the effort involved in screening at the same time for insertions in all members of groups of genes that share a limited sequence identity.

  6. [Exome sequencing: an efficient strategy for identifying the causative genes of monogenic disorders].

    PubMed

    Rebiya, Nuli; Patamu, Mohemaiti

    2011-10-01

    The development of new generation sequencing technologies has brought new opportunities for the study of diseases. Exome sequencing has shown to be an effective, rapid, high performance technique that has already been used in research of inherited diseases such as monogenic disorders. It has already been approved by scientists in the field of monogenic disorder study, and will become widely used. This approach will accelerate discovery of the causative genes of Mendelian disorders. This article reviews some recent applications of exome sequencing in the study of gene-related diseases.

  7. A functional siRNA screen identifies genes modulating angiotensin II-mediated EGFR transactivation

    PubMed Central

    George, Amee J.; Purdue, Brooke W.; Gould, Cathryn M.; Thomas, Daniel W.; Handoko, Yanny; Qian, Hongwei; Quaife-Ryan, Gregory A.; Morgan, Kylie A.; Simpson, Kaylene J.; Thomas, Walter G.; Hannan, Ross D.

    2013-01-01

    Summary The angiotensin type 1 receptor (AT1R) transactivates the epidermal growth factor receptor (EGFR) to mediate cellular growth, however, the molecular mechanisms involved have not yet been resolved. To address this, we performed a functional siRNA screen of the human kinome in human mammary epithelial cells that demonstrate a robust AT1R–EGFR transactivation. We identified a suite of genes encoding proteins that both positively and negatively regulate AT1R–EGFR transactivation. Many candidates are components of EGFR signalling networks, whereas others, including TRIO, BMX and CHKA, have not been previously linked to EGFR transactivation. Individual knockdown of TRIO, BMX or CHKA attenuated tyrosine phosphorylation of the EGFR by angiotensin II stimulation, but this did not occur following direct stimulation of the EGFR with EGF, indicating that these proteins function between the activated AT1R and the EGFR. Further investigation of TRIO and CHKA revealed that their activity is likely to be required for AT1R–EGFR transactivation. CHKA also mediated EGFR transactivation in response to another G protein-coupled receptor (GPCR) ligand, thrombin, indicating a pervasive role for CHKA in GPCR–EGFR crosstalk. Our study reveals the power of unbiased, functional genomic screens to identify new signalling mediators important for tissue remodelling in cardiovascular disease and cancer. PMID:24046455

  8. 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

  9. The compact Selaginella genome identifies changes in gene content associated with the evolution of vascular plants

    SciTech Connect

    Grigoriev, Igor V.; Banks, Jo Ann; Nishiyama, Tomoaki; Hasebe, Mitsuyasu; Bowman, John L.; Gribskov, Michael; dePamphilis, Claude; Albert, Victor A.; Aono, Naoki; Aoyama, Tsuyoshi; Ambrose, Barbara A.; Ashton, Neil W.; Axtell, Michael J.; Barker, Elizabeth; Barker, Michael S.; Bennetzen, Jeffrey L.; Bonawitz, Nicholas D.; Chapple, Clint; Cheng, Chaoyang; Correa, Luiz Gustavo Guedes; Dacre, Michael; DeBarry, Jeremy; Dreyer, Ingo; Elias, Marek; Engstrom, Eric M.; Estelle, Mark; Feng, Liang; Finet, Cedric; Floyd, Sandra K.; Frommer, Wolf B.; Fujita, Tomomichi; Gramzow, Lydia; Gutensohn, Michael; Harholt, Jesper; Hattori, Mitsuru; Heyl, Alexander; Hirai, Tadayoshi; Hiwatashi, Yuji; Ishikawa, Masaki; Iwata, Mineko; Karol, Kenneth G.; Koehler, Barbara; Kolukisaoglu, Uener; Kubo, Minoru; Kurata, Tetsuya; Lalonde, Sylvie; Li, Kejie; Li, Ying; Litt, Amy; Lyons, Eric; Manning, Gerard; Maruyama, Takeshi; Michael, Todd P.; Mikami, Koji; Miyazaki, Saori; Morinaga, Shin-ichi; Murata, Takashi; Mueller-Roeber, Bernd; Nelson, David R.; Obara, Mari; Oguri, Yasuko; Olmstead, Richard G.; Onodera, Naoko; Petersen, Bent Larsen; Pils, Birgit; Prigge, Michael; Rensing, Stefan A.; Riano-Pachon, Diego Mauricio; Roberts, Alison W.; Sato, Yoshikatsu; Scheller, Henrik Vibe; Schulz, Burkhard; Schulz, Christian; Shakirov, Eugene V.; Shibagaki, Nakako; Shinohara, Naoki; Shippen, Dorothy E.; Sorensen, Iben; Sotooka, Ryo; Sugimoto, Nagisa; Sugita, Mamoru; Sumikawa, Naomi; Tanurdzic, Milos; Theilsen, Gunter; Ulvskov, Peter; Wakazuki, Sachiko; Weng, Jing-Ke; Willats, William W.G.T.; Wipf, Daniel; Wolf, Paul G.; Yang, Lixing; Zimmer, Andreas D.; Zhu, Qihui; Mitros, Therese; Hellsten, Uffe; Loque, Dominique; Otillar, Robert; Salamov, Asaf; Schmutz, Jeremy; Shapiro, Harris; Lindquist, Erika; Lucas, Susan; Rokhsar, Daniel

    2011-04-28

    We report the genome sequence of the nonseed vascular plant, Selaginella moellendorffii, and by comparative genomics identify genes that likely played important roles in the early evolution of vascular plants and their subsequent evolution

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

    SciTech Connect

    Not Available

    1987-09-04

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

  11. Genome-Wide RNAi Screens in C. elegans to Identify Genes Influencing Lifespan and Innate Immunity.

    PubMed

    Sinha, Amit; Rae, Robbie

    2016-01-01

    RNA interference is a rapid, inexpensive, and highly effective tool used to inhibit gene function. In C. elegans, whole genome screens have been used to identify genes involved with numerous traits including aging and innate immunity. RNAi in C. elegans can be carried out via feeding, soaking, or injection. Here we outline protocols used to maintain, grow, and carry out RNAi via feeding in C. elegans and determine whether the inhibited genes are essential for lifespan or innate immunity.

  12. Protein functional links in Trypanosoma brucei, identified by gene fusion analysis

    PubMed Central

    2011-01-01

    Background Domain or gene fusion analysis is a bioinformatics method for detecting gene fusions in one organism by comparing its genome to that of other organisms. The occurrence of gene fusions suggests that the two original genes that participated in the fusion are functionally linked, i.e. their gene products interact either as part of a multi-subunit protein complex, or in a metabolic pathway. Gene fusion analysis has been used to identify protein functional links in prokaryotes as well as in eukaryotic model organisms, such as yeast and Drosophila. Results In this study we have extended this approach to include a number of recently sequenced protists, four of which are pathogenic, to identify fusion linked proteins in Trypanosoma brucei, the causative agent of African sleeping sickness. We have also examined the evolution of the gene fusion events identified, to determine whether they can be attributed to fusion or fission, by looking at the conservation of the fused genes and of the individual component genes across the major eukaryotic and prokaryotic lineages. We find relatively limited occurrence of gene fusions/fissions within the protist lineages examined. Our results point to two trypanosome-specific gene fissions, which have recently been experimentally confirmed, one fusion involving proteins involved in the same metabolic pathway, as well as two novel putative functional links between fusion-linked protein pairs. Conclusions This is the first study of protein functional links in T. brucei identified by gene fusion analysis. We have used strict thresholds and only discuss results which are highly likely to be genuine and which either have already been or can be experimentally verified. We discuss the possible impact of the identification of these novel putative protein-protein interactions, to the development of new trypanosome therapeutic drugs. PMID:21729286

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

    PubMed Central

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

    2016-01-01

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

  14. Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments.

    PubMed

    Leng, Ning; Chu, Li-Fang; Barry, Chris; Li, Yuan; Choi, Jeea; Li, Xiaomao; Jiang, Peng; Stewart, Ron M; Thomson, James A; Kendziorski, Christina

    2015-10-01

    Oscillatory gene expression is fundamental to development, but technologies for monitoring expression oscillations are limited. We have developed a statistical approach called Oscope to identify and characterize the transcriptional dynamics of oscillating genes in single-cell RNA-seq data from an unsynchronized cell population. Applying Oscope to a number of data sets, we demonstrated its utility and also identified a potential artifact in the Fluidigm C1 platform.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. Epigenetic Characterization of the Growth Hormone Gene Identifies SmcHD1 as a Regulator of Autosomal Gene Clusters

    PubMed Central

    Massah, Shabnam; Hollebakken, Robert; Labrecque, Mark P.; Kolybaba, Addie M.; Beischlag, Timothy V.; Prefontaine, Gratien G.

    2014-01-01

    Regulatory elements for the mouse growth hormone (GH) gene are located distally in a putative locus control region (LCR) in addition to key elements in the promoter proximal region. The role of promoter DNA methylation for GH gene regulation is not well understood. Pit-1 is a POU transcription factor required for normal pituitary development and obligatory for GH gene expression. In mammals, Pit-1 mutations eliminate GH production resulting in a dwarf phenotype. In this study, dwarf mice illustrated that Pit-1 function was obligatory for GH promoter hypomethylation. By monitoring promoter methylation levels during developmental GH expression we found that the GH promoter became hypomethylated coincident with gene expression. We identified a promoter differentially methylated region (DMR) that was used to characterize a methylation-dependent DNA binding activity. Upon DNA affinity purification using the DMR and nuclear extracts, we identified structural maintenance of chromosomes hinge domain containing -1 (SmcHD1). To better understand the role of SmcHD1 in genome-wide gene expression, we performed microarray analysis and compared changes in gene expression upon reduced levels of SmcHD1 in human cells. Knock-down of SmcHD1 in human embryonic kidney (HEK293) cells revealed a disproportionate number of up-regulated genes were located on the X-chromosome, but also suggested regulation of genes on non-sex chromosomes. Among those, we identified several genes located in the protocadherin β cluster. In addition, we found that imprinted genes in the H19/Igf2 cluster associated with Beckwith-Wiedemann and Silver-Russell syndromes (BWS & SRS) were dysregulated. For the first time using human cells, we showed that SmcHD1 is an important regulator of imprinted and clustered genes. PMID:24818964

  17. Identifying Novel Transcriptional and Epigenetic Features of Nuclear Lamina-associated Genes.

    PubMed

    Wu, Feinan; Yao, Jie

    2017-12-01

    Because a large portion of the mammalian genome is associated with the nuclear lamina (NL), it is interesting to study how native genes resided there are transcribed and regulated. In this study, we report unique transcriptional and epigenetic features of nearly 3,500 NL-associated genes (NL genes). Promoter regions of active NL genes are often excluded from NL-association, suggesting that NL-promoter interactions may repress transcription. Active NL genes with higher RNA polymerase II (Pol II) recruitment levels tend to display Pol II promoter-proximal pausing, while Pol II recruitment and Pol II pausing are not correlated among non-NL genes. At the genome-wide scale, NL-association and H3K27me3 distinguishes two large gene classes with low transcriptional activities. Notably, NL-association is anti-correlated with both transcription and active histone mark levels among genes not significantly enriched with H3K9me3 or H3K27me3, suggesting that NL-association may represent a novel gene repression pathway. Interestingly, an NL gene subgroup is not significantly enriched with H3K9me3 or H3K27me3 and is transcribed at higher levels than the rest of NL genes. Furthermore, we identified distal enhancers associated with active NL genes and reported their epigenetic features.

  18. A genetic screen in zebrafish identifies the mutants vps18, nf2 and foie gras as models of liver disease.

    PubMed

    Sadler, Kirsten C; Amsterdam, Adam; Soroka, Carol; Boyer, James; Hopkins, Nancy

    2005-08-01

    Hepatomegaly is a sign of many liver disorders. To identify zebrafish mutants to serve as models for hepatic pathologies, we screened for hepatomegaly at day 5 of embryogenesis in 297 zebrafish lines bearing mutations in genes that are essential for embryonic development. Seven mutants were identified, and three have phenotypes resembling different liver diseases. Mutation of the class C vacuolar protein sorting gene vps18 results in hepatomegaly associated with large, vesicle-filled hepatocytes, which we attribute to the failure of endosomal-lysosomal trafficking. Additionally, these mutants develop defects in the bile canaliculi and have marked biliary paucity, suggesting that vps18 also functions to traffic vesicles to the hepatocyte apical membrane and may play a role in the development of the intrahepatic biliary tree. Similar findings have been reported for individuals with arthrogryposis-renal dysfunction-cholestasis (ARC) syndrome, which is due to mutation of another class C vps gene. A second mutant, resulting from disruption of the tumor suppressor gene nf2, develops extrahepatic choledochal cysts in the common bile duct, suggesting that this gene regulates division of biliary cells during development and that nf2 may play a role in the hyperplastic tendencies observed in biliary cells in individuals with choledochal cysts. The third mutant is in the novel gene foie gras, which develops large, lipid-filled hepatocytes, resembling those in individuals with fatty liver disease. These mutants illustrate the utility of zebrafish as a model for studying liver development and disease, and provide valuable tools for investigating the molecular pathogenesis of congenital biliary disorders and fatty liver disease.

  19. High throughput in vivo functional validation of candidate congenital heart disease genes in Drosophila

    PubMed Central

    Zhu, Jun-yi; Fu, Yulong; Nettleton, Margaret; Richman, Adam; Han, Zhe

    2017-01-01

    Genomic sequencing has implicated large numbers of genes and de novo mutations as potential disease risk factors. A high throughput in vivo model system is needed to validate gene associations with pathology. We developed a Drosophila-based functional system to screen candidate disease genes identified from Congenital Heart Disease (CHD) patients. 134 genes were tested in the Drosophila heart using RNAi-based gene silencing. Quantitative analyses of multiple cardiac phenotypes demonstrated essential structural, functional, and developmental roles for more than 70 genes, including a subgroup encoding histone H3K4 modifying proteins. We also demonstrated the use of Drosophila to evaluate cardiac phenotypes resulting from specific, patient-derived alleles of candidate disease genes. We describe the first high throughput in vivo validation system to screen candidate disease genes identified from patients. This approach has the potential to facilitate development of precision medicine approaches for CHD and other diseases associated with genetic factors. DOI: http://dx.doi.org/10.7554/eLife.22617.001 PMID:28084990

  20. A genomic strategy for the functional validation of colorectal cancer genes identifies potential therapeutic targets.

    PubMed

    Grade, Marian; Hummon, Amanda B; Camps, Jordi; Emons, Georg; Spitzner, Melanie; Gaedcke, Jochen; Hoermann, Patrick; Ebner, Reinhard; Becker, Heinz; Difilippantonio, Michael J; Ghadimi, B Michael; Beissbarth, Tim; Caplen, Natasha J; Ried, Thomas

    2011-03-01

    Genes that are highly overexpressed in tumor cells can be required for tumor cell survival and have the potential to be selective therapeutic targets. In an attempt to identify such targets, we combined a functional genomics and a systems biology approach to assess the consequences of RNAi-mediated silencing of overexpressed genes that were selected from 140 gene expression profiles from colorectal cancers (CRCs) and matched normal mucosa. In order to identify credible models for in-depth functional analysis, we first confirmed the overexpression of these genes in 25 different CRC cell lines. We then identified five candidate genes that profoundly reduced the viability of CRC cell lines when silenced with either siRNAs or short-hairpin RNAs (shRNAs), i.e., HMGA1, TACSTD2, RRM2, RPS2 and NOL5A. These genes were further studied by systematic analysis of comprehensive gene expression profiles generated following siRNA-mediated silencing. Exploration of these RNAi-specific gene expression signatures allowed the identification of the functional space in which the five genes operate and showed enrichment for cancer-specific signaling pathways, some known to be involved in CRC. By comparing the expression of the RNAi signature genes with their respective expression levels in an independent set of primary rectal carcinomas, we could recapitulate these defined RNAi signatures, therefore, establishing the biological relevance of our observations. This strategy identified the signaling pathways that are affected by the prominent oncogenes HMGA1 and TACSTD2, established a yet unknown link between RRM2 and PLK1 and identified RPS2 and NOL5A as promising potential therapeutic targets in CRC.

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

    PubMed

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

    1994-05-27

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

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

    SciTech Connect

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

    1994-05-27

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

  3. Differentiating disease subtypes by using pathway patterns constructed from gene expressions and protein networks.

    PubMed

    Hung, Fei-Hung; Chiu, Hung-Wen

    2015-01-01

    Gene expression profiles differ in different diseases. Even if diseases are at the same stage, such diseases exhibit different gene expressions, not to mention the different subtypes at a single lesion site. Distinguishing different disease subtypes at a single lesion site is difficult. In early cases, subtypes were initially distinguished by doctors. Subsequently, further differences were found through pathological experiments. For example, a brain tumor can be classified according to its origin, its cell-type origin, or the tumor site. Because of the advancements in bioinformatics and the techniques for accumulating gene expressions, researchers can use gene expression data to classify disease subtypes. Because the operation of a biopathway is closely related to the disease mechanism, the application of gene expression profiles for clustering disease subtypes is insufficient. In this study, we collected gene expression data of healthy and four myelodysplastic syndrome subtypes and applied a method that integrated protein-protein interaction and gene expression data to identify different patterns of disease subtypes. We hope it is efficient for the classification of disease subtypes in adventure.

  4. Successes and challenges of using whole exome sequencing to identify novel genes underlying an inherited predisposition for thoracic aortic aneurysms and acute aortic dissections.

    PubMed

    Milewicz, Dianna M; Regalado, Ellen S; Shendure, Jay; Nickerson, Deborah A; Guo, Dong-chuan

    2014-02-01

    Thoracic aortic aneurysms involving the aortic root and/or ascending aorta can lead to acute aortic dissections. Approximately 20% of patients with thoracic aortic aneurysms and dissections (TAAD) have a family history of the disease, referred to as familial TAAD (FTAAD) that can be inherited in an autosomal dominant manner with variable expression with respect to disease presentation, age of onset and associated features. Whole exome sequencing (WES) has been used to identify causative mutations in novel genes for TAAD. The strategy used to reduce the large number of rare variants identified using WES is to sequence distant relatives with TAAD and filter for heterozygous rare variants that are shared between the relatives, predicted to disrupt protein function and segregate with the TAAD phenotype in other family members. Putative genes are validated by identifying additional families with a causative mutation in the genes. This approach has successfully identified novel genes for FTAAD.

  5. Targeted sequencing approach to identify genetic mutations in Nasu-Hakola disease

    PubMed Central

    Satoh, Jun-ichi; Yanaizu, Motoaki; Tosaki, Youhei; Sakai, Kenji; Kino, Yoshihiro

    2016-01-01

    Summary Nasu-Hakola disease (NHD) is a rare autosomal recessive disorder characterized by sclerosing leukoencephalopathy and multifocal bone cysts, caused by a loss-of-function mutation of either TYROBP (DAP12) or TREM2. TREM2 and DAP12 constitute a receptor/adaptor signaling complex expressed exclusively on osteoclasts, dendritic cells, macrophages, and microglia. Premortem molecular diagnosis of NHD requires genetic analysis of both TYROBP and TREM2, in which 20 distinct NHD-causing mutations have been reported. Due to genetic heterogeneity, it is often difficult to identify the exact mutation responsible for NHD. Recently, the revolution of the next-generation sequencing (NGS) technology has greatly advanced the field of genome research. A targeted sequencing approach allows us to investigate a selected set of disease-causing genes and mutations in a number of samples within several days. By targeted sequencing using the TruSight One Sequencing Panel, we resequenced genetic mutations of seven NHD cases with known molecular diagnosis and two control subjects. We identified homozygous variants of TYROBP or TREM2 in all NHD cases, composed of a frameshift mutation of c.141delG in exon 3 of TYROBP in four cases, a missense mutation of c.2T>C in exon 1