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Sample records for combined gene analysis

  1. Combined clustering models for the analysis of gene expression

    SciTech Connect

    Angelova, M. Ellman, J.

    2010-02-15

    Clustering has become one of the fundamental tools for analyzing gene expression and producing gene classifications. Clustering models enable finding patterns of similarity in order to understand gene function, gene regulation, cellular processes and sub-types of cells. The clustering results however have to be combined with sequence data or knowledge about gene functionality in order to make biologically meaningful conclusions. In this work, we explore a new model that integrates gene expression with sequence or text information.

  2. Combined analysis of fourteen nuclear genes refines the Ursidae phylogeny.

    PubMed

    Pagès, Marie; Calvignac, Sébastien; Klein, Catherine; Paris, Mathilde; Hughes, Sandrine; Hänni, Catherine

    2008-04-01

    Despite numerous studies, questions remain about the evolutionary history of Ursidae and additional independent genetic markers were needed to elucidate these ambiguities. For this purpose, we sequenced ten nuclear genes for all the eight extant bear species. By combining these new sequences with those of four other recently published nuclear markers, we provide new insights into the phylogenetic relationships of the Ursidae family members. The hypothesis that the giant panda was the first species to diverge among ursids is definitively confirmed and the precise branching order within the Ursus genus is clarified for the first time. Moreover, our analyses indicate that the American and the Asiatic black bears do not cluster as sister taxa, as had been previously hypothesised. Sun and sloth bears clearly appear as the most basal ursine species but uncertainties about their exact relationships remain. Since our larger dataset did not enable us to clarify this last question, identifying rare genomic changes in bear genomes could be a promising solution for further studies.

  3. Combined Analysis of ChIP Sequencing and Gene Expression Dataset in Breast Cancer.

    PubMed

    Liu, Pengfei; Jiang, Wenhua; Zhou, Shiyong; Gao, Jun; Zhang, Huilai

    2017-04-01

    Breast cancer is a common malignancy in women and contribute largely to the cancer related death. The purpose of this study is to confirm the roles of GATA3 and identify potential biomarkers of breast cancer. Chromatin Immunoprecipitation combined with high-throughput sequencing (ChIP-Seq) (GSM1642515) and gene expression profiles (GSE24249) were downloaded from the Gene Expression Omnibus (GEO) database. Bowtie2 and MACS2 were used for the mapping and peak calling of the ChIP-Seq data respectively. ChIPseeker, a R bioconductor package was adopted for the annotation of the enriched peaks. For the gene expression profiles, we used affy and limma package to do normalization and differential expression analysis. The genes with fold change >2 and adjusted P-Value <0.05 were screened out. Besides, BETA (Binding and Expression Target Analysis) was used to do the combined analysis of ChIP-Seq and gene expression profiles. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for the functional enrichment analysis of overlapping genes between the target genes and differential expression genes (DEGs). What's more, the protein-protein interaction (PPI) network of the overlapping genes was obtained through the Human Protein Reference Database (HPRD). A total of 46,487 peaks were identified for GATA3 and out of which, 3256 ones were found to located at -3000 ~ 0 bp from the transcription start sites (TSS) of their nearby gene. A total of 236 down- and 343 up-regulated genes were screened out in GATA3 overexpression breast cancer samples compared with those in control. The combined analysis of ChIP-Seq and gene expression dataset showed GATA3 act as a repressor in breast cancer. Besides, 68 overlaps were obtained between the DEGs and genes included in peaks located at -3000 ~ 0 bp from TSS. Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to cancer progression and gene regulation were found to be

  4. Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis.

    PubMed

    Tejera, Eduardo; Cruz-Monteagudo, Maykel; Burgos, Germán; Sánchez, María-Eugenia; Sánchez-Rodríguez, Aminael; Pérez-Castillo, Yunierkis; Borges, Fernanda; Cordeiro, Maria Natália Dias Soeiro; Paz-Y-Miño, César; Rebelo, Irene

    2017-08-08

    Preeclampsia is a multifactorial disease with unknown pathogenesis. Even when recent studies explored this disease using several bioinformatics tools, the main objective was not directed to pathogenesis. Additionally, consensus prioritization was proved to be highly efficient in the recognition of genes-disease association. However, not information is available about the consensus ability to early recognize genes directly involved in pathogenesis. Therefore our aim in this study is to apply several theoretical approaches to explore preeclampsia; specifically those genes directly involved in the pathogenesis. We firstly evaluated the consensus between 12 prioritization strategies to early recognize pathogenic genes related to preeclampsia. A communality analysis in the protein-protein interaction network of previously selected genes was done including further enrichment analysis. The enrichment analysis includes metabolic pathways as well as gene ontology. Microarray data was also collected and used in order to confirm our results or as a strategy to weight the previously enriched pathways. The consensus prioritized gene list was rationally filtered to 476 genes using several criteria. The communality analysis showed an enrichment of communities connected with VEGF-signaling pathway. This pathway is also enriched considering the microarray data. Our result point to VEGF, FLT1 and KDR as relevant pathogenic genes, as well as those connected with NO metabolism. Our results revealed that consensus strategy improve the detection and initial enrichment of pathogenic genes, at least in preeclampsia condition. Moreover the combination of the first percent of the prioritized genes with protein-protein interaction network followed by communality analysis reduces the gene space. This approach actually identifies well known genes related with pathogenesis. However, genes like HSP90, PAK2, CD247 and others included in the first 1% of the prioritized list need to be further

  5. Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

    PubMed

    Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

    2015-06-01

    To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Gene expression patterns combined with bioinformatics analysis identify genes associated with cholangiocarcinoma.

    PubMed

    Li, Chen; Shen, Weixing; Shen, Sheng; Ai, Zhilong

    2013-12-01

    To explore the molecular mechanisms of cholangiocarcinoma (CC), microarray technology was used to find biomarkers for early detection and diagnosis. The gene expression profiles from 6 patients with CC and 5 normal controls were downloaded from Gene Expression Omnibus and compared. As a result, 204 differentially co-expressed genes (DCGs) in CC patients compared to normal controls were identified using a computational bioinformatics analysis. These genes were mainly involved in coenzyme metabolic process, peptidase activity and oxidation reduction. A regulatory network was constructed by mapping the DCGs to known regulation data. Four transcription factors, FOXC1, ZIC2, NKX2-2 and GCGR, were hub nodes in the network. In conclusion, this study provides a set of targets useful for future investigations into molecular biomarker studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. A combined analysis of microarray gene expression studies of the human prefrontal cortex identifies genes implicated in schizophrenia.

    PubMed

    Pérez-Santiago, Josué; Diez-Alarcia, Rebeca; Callado, Luis F; Zhang, Jin X; Chana, Gursharan; White, Cory H; Glatt, Stephen J; Tsuang, Ming T; Everall, Ian P; Meana, J Javier; Woelk, Christopher H

    2012-11-01

    Small cohort sizes and modest levels of gene expression changes in brain tissue have plagued the statistical approaches employed in microarray studies investigating the mechanism of schizophrenia. To combat these problems a combined analysis of six prior microarray studies was performed to facilitate the robust statistical analysis of gene expression data from the dorsolateral prefrontal cortex of 107 patients with schizophrenia and 118 healthy subjects. Multivariate permutation tests identified 144 genes that were differentially expressed between schizophrenia and control groups. Seventy of these genes were identified as differentially expressed in at least one component microarray study but none of these individual studies had the power to identify the remaining 74 genes, demonstrating the utility of a combined approach. Gene ontology terms and biological pathways that were significantly enriched for differentially expressed genes were related to neuronal cell-cell signaling, mesenchymal induction, and mitogen-activated protein kinase signaling, which have all previously been associated with the etiopathogenesis of schizophrenia. The differential expression of BAG3, C4B, EGR1, MT1X, NEUROD6, SST and S100A8 was confirmed by real-time quantitative PCR in an independent cohort using postmortem human prefrontal cortex samples. Comparison of gene expression between schizophrenic subjects with and without detectable levels of antipsychotics in their blood suggests that the modulation of MT1X and S100A8 may be the result of drug exposure. In conclusion, this combined analysis has resulted in a statistically robust identification of genes whose dysregulation may contribute to the mechanism of schizophrenia.

  8. Identification of Drosophila Mitotic Genes by Combining Co-Expression Analysis and RNA Interference

    PubMed Central

    Somma, Maria Patrizia; Ceprani, Francesca; Bucciarelli, Elisabetta; Naim, Valeria; De Arcangelis, Valeria; Piergentili, Roberto; Palena, Antonella; Ciapponi, Laura; Giansanti, Maria Grazia; Pellacani, Claudia; Petrucci, Romano; Cenci, Giovanni; Vernì, Fiammetta; Fasulo, Barbara; Goldberg, Michael L.; Di Cunto, Ferdinando; Gatti, Maurizio

    2008-01-01

    RNAi screens have, to date, identified many genes required for mitotic divisions of Drosophila tissue culture cells. However, the inventory of such genes remains incomplete. We have combined the powers of bioinformatics and RNAi technology to detect novel mitotic genes. We found that Drosophila genes involved in mitosis tend to be transcriptionally co-expressed. We thus constructed a co-expression–based list of 1,000 genes that are highly enriched in mitotic functions, and we performed RNAi for each of these genes. By limiting the number of genes to be examined, we were able to perform a very detailed phenotypic analysis of RNAi cells. We examined dsRNA-treated cells for possible abnormalities in both chromosome structure and spindle organization. This analysis allowed the identification of 142 mitotic genes, which were subdivided into 18 phenoclusters. Seventy of these genes have not previously been associated with mitotic defects; 30 of them are required for spindle assembly and/or chromosome segregation, and 40 are required to prevent spontaneous chromosome breakage. We note that the latter type of genes has never been detected in previous RNAi screens in any system. Finally, we found that RNAi against genes encoding kinetochore components or highly conserved splicing factors results in identical defects in chromosome segregation, highlighting an unanticipated role of splicing factors in centromere function. These findings indicate that our co-expression–based method for the detection of mitotic functions works remarkably well. We can foresee that elaboration of co-expression lists using genes in the same phenocluster will provide many candidate genes for small-scale RNAi screens aimed at completing the inventory of mitotic proteins. PMID:18797514

  9. Unravelling enzymatic discoloration in potato through a combined approach of candidate genes, QTL, and expression analysis

    PubMed Central

    Kloosterman, Bjorn; Celis-Gamboa, Carolina; de Vos, C. H. Ric; America, Twan; Visser, Richard G. F.; Bachem, Christian W. B.

    2007-01-01

    Enzymatic discoloration (ED) of potato tubers was investigated in an attempt to unravel the underlying genetic factors. Both enzyme and substrate concentration have been reported to influence the degree of discoloration and as such this trait can be regarded as polygenic. The diploid mapping population C × E, consisting of 249 individuals, was assayed for the degree of ED and levels of chlorogenic acid and tyrosine. Using this data, Quantitative Trait Locus (QTL) analysis was performed. Three QTLs for ED have been found on parental chromosomes C3, C8, E1, and E8. For chlorogenic acid a QTL has been identified on C2 and for tyrosine levels, a QTL has been detected on C8. None of the QTLs overlap, indicating the absence of genetic correlations between these components underlying ED, in contrast to earlier reports in literature. An obvious candidate gene for the QTL for ED on Chromosome 8 is polyphenol oxidase (PPO), which was previously mapped on chromosome 8. With gene-specific primers for PPO gene POT32 a CAPS marker was developed. Three different alleles (POT32-1, -2, and -3) could be discriminated. The segregating POT32 alleles were used to map the POT32 CAPS marker and QTL analysis was redone, showing that POT32 coincides with the QTL peak. A clear correlation between allele combinations and degree of discoloration was observed. In addition, analysis of POT32 gene expression in a subset of genotypes indicated a correlation between the level of gene expression and allele composition. On average, genotypes having two copies of allele 1 had both the highest degree of discoloration as well as the highest level of POT32 gene expression. PMID:17492422

  10. Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis.

    PubMed

    Liu, Mingyuan; Hou, Xiaojun; Zhang, Ping; Hao, Yong; Yang, Yiting; Wu, Xiongfeng; Zhu, Desheng; Guan, Yangtai

    2013-05-01

    Multiple sclerosis (MS) is the most prevalent demyelinating disease and the principal cause of neurological disability in young adults. Recent microarray gene expression profiling studies have identified several genetic variants contributing to the complex pathogenesis of MS, however, expressional and functional studies are still required to further understand its molecular mechanism. The present study aimed to analyze the molecular mechanism of MS using microarray analysis combined with bioinformatics techniques. We downloaded the gene expression profile of MS from Gene Expression Omnibus (GEO) and analysed the microarray data using the differentially coexpressed genes (DCGs) and links package in R and Database for Annotation, Visualization and Integrated Discovery. The regulatory impact factor (RIF) algorithm was used to measure the impact factor of transcription factor. A total of 1,297 DCGs between MS patients and healthy controls were identified. Functional annotation indicated that these DCGs were associated with immune and neurological functions. Furthermore, the RIF result suggested that IKZF1, BACH1, CEBPB, EGR1, FOS may play central regulatory roles in controlling gene expression in the pathogenesis of MS. Our findings confirm the presence of multiple molecular alterations in MS and indicate the possibility for identifying prognostic factors associated with MS pathogenesis.

  11. [Mass spectrometry combined with gene analysis for prenatal diagnosis of glutaric acidemia type Ⅰ].

    PubMed

    Han, F; Han, L S; Ji, W J; Chen, T; Xu, F; Wang, Y; Ye, J; Qiu, W J; Zhang, H W; Jiang, Y Z; Hou, C; Gu, X F

    2017-07-02

    Objective: To investigate the value of amniotic fluid metabolite detection by mass spectrometry combined with gene mutation analysis in the prenatal diagnosis of glutaric acidemia type Ⅰ (GA-Ⅰ). Method: From January 2009 to December 2016, Department of Pediatric Endocrinology and Genetic, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine carried out prenatal diagnosis for 24 cases of pregnant women with GA-Ⅰproband. 24 pregnant women without organic acidemia proband for conventional prenatal diagnosis at the same period were used as the control group. The pregnant women of the two groups had the amniocentesis at 16 to 20 weeks of gestation.The levels of glutaryl carnitine (C5DC) and octanoylcarnitine (C8) in amniotic fluid were detected by tandem mass spectrometry, and the levels of glutaric acid was determined by gas chromatography-mass spectrometry. All the amniotic fluid cells underwent GCDH gene testing. Result: A total of 4 cases of fetuses were diagnosed by gene mutation analysis combined with mass spectrometry detection, the levels of C5DC (1.58(0.89-2.85) μmol/L), C5DC/C8 (19.74(12.40-25.93))and glutaric acid (129.96 (90.09-66.02) mmol/mol Cr) were significantly higher than the upper limit of the reference, of which in one case with the proband only on mutation was detected, and in the amniotic fluid cells also only one mutation was detected, the diagnosis was made according to the significantly increased levels of amniotic fluid C5DC, C5DC/C8 and glutaric acid. Twenty cases of fetuses were identified as non-GA-Ⅰchildren, of whom in 2 cases of proband only one mutation was detected, and also in amniotic fluid cells one mutation was detected, in 2 cases the diagnosis was excluded because the normal levels of C5DC, C5DC/C8 and glutaric acid. There were 2 cases whose levels of C5DC or glutaric acid were slightly higher than the upper limit of the reference, but the diagnosis was excluded according to genetic testing

  12. Gene identification for risk of relapse in stage I lung adenocarcinoma patients: a combined methodology of gene expression profiling and computational gene network analysis.

    PubMed

    Ludovini, Vienna; Bianconi, Fortunato; Siggillino, Annamaria; Piobbico, Danilo; Vannucci, Jacopo; Metro, Giulio; Chiari, Rita; Bellezza, Guido; Puma, Francesco; Della Fazia, Maria Agnese; Servillo, Giuseppe; Crinò, Lucio

    2016-05-24

    Risk assessment and treatment choice remains a challenge in early non-small-cell lung cancer (NSCLC). The aim of this study was to identify novel genes involved in the risk of early relapse (ER) compared to no relapse (NR) in resected lung adenocarcinoma (AD) patients using a combination of high throughput technology and computational analysis. We identified 18 patients (n.13 NR and n.5 ER) with stage I AD. Frozen samples of patients in ER, NR and corresponding normal lung (NL) were subjected to Microarray technology and quantitative-PCR (Q-PCR). A gene network computational analysis was performed to select predictive genes. An independent set of 79 ADs stage I samples was used to validate selected genes by Q-PCR.From microarray analysis we selected 50 genes, using the fold change ratio of ER versus NR. They were validated both in pool and individually in patient samples (ER and NR) by Q-PCR. Fourteen increased and 25 decreased genes showed a concordance between two methods. They were used to perform a computational gene network analysis that identified 4 increased (HOXA10, CLCA2, AKR1B10, FABP3) and 6 decreased (SCGB1A1, PGC, TFF1, PSCA, SPRR1B and PRSS1) genes. Moreover, in an independent dataset of ADs samples, we showed that both high FABP3 expression and low SCGB1A1 expression was associated with a worse disease-free survival (DFS).Our results indicate that it is possible to define, through gene expression and computational analysis, a characteristic gene profiling of patients with an increased risk of relapse that may become a tool for patient selection for adjuvant therapy.

  13. Dissection of complex gene expression using the combined analysis of pleiotropy and epistasis.

    PubMed

    Philip, Vivek M; Tyler, Anna L; Carter, Gregory W

    2014-01-01

    Global transcript expression experiments are commonly used to investigate the biological processes that underlie complex traits. These studies can exhibit complex patterns of pleiotropy when trans-acting genetic factors influence overlapping sets of multiple transcripts. Dissecting these patterns into biological modules with distinct genetic etiology can provide models of how genetic variants affect specific processes that contribute to a trait. Here we identify transcript modules associated with pleiotropic genetic factors and apply genetic interaction analysis to disentangle the regulatory architecture in a mouse intercross study of kidney function. The method, called the combined analysis of pleiotropy and epistasis (CAPE), has been previously used to model genetic networks for multiple physiological traits. It simultaneously models multiple phenotypes to identify direct genetic influences as well as influences mediated through genetic interactions. We first identify candidate trans expression quantitative trait loci (eQTL) and the transcripts potentially affected. We then clustered the transcripts into modules of co-expressed genes, from which we compute summary module phenotypes. Finally, we applied CAPE to map the network of interacting module QTL (modQTL) affecting the gene modules. The resulting network mapped how multiple modQTL both directly and indirectly affect modules associated with metabolic functions and biosynthetic processes. This work demonstrates how the integration of pleiotropic signals in gene expression data can be used to infer a complex hypothesis of how multiple loci interact to co-regulate transcription programs, thereby providing additional constraints to prioritize validation experiments.

  14. Regression Analysis of Combined Gene Expression Regulation in Acute Myeloid Leukemia

    PubMed Central

    Li, Yue; Liang, Minggao; Zhang, Zhaolei

    2014-01-01

    Gene expression is a combinatorial function of genetic/epigenetic factors such as copy number variation (CNV), DNA methylation (DM), transcription factors (TF) occupancy, and microRNA (miRNA) post-transcriptional regulation. At the maturity of microarray/sequencing technologies, large amounts of data measuring the genome-wide signals of those factors became available from Encyclopedia of DNA Elements (ENCODE) and The Cancer Genome Atlas (TCGA). However, there is a lack of an integrative model to take full advantage of these rich yet heterogeneous data. To this end, we developed RACER (Regression Analysis of Combined Expression Regulation), which fits the mRNA expression as response using as explanatory variables, the TF data from ENCODE, and CNV, DM, miRNA expression signals from TCGA. Briefly, RACER first infers the sample-specific regulatory activities by TFs and miRNAs, which are then used as inputs to infer specific TF/miRNA-gene interactions. Such a two-stage regression framework circumvents a common difficulty in integrating ENCODE data measured in generic cell-line with the sample-specific TCGA measurements. As a case study, we integrated Acute Myeloid Leukemia (AML) data from TCGA and the related TF binding data measured in K562 from ENCODE. As a proof-of-concept, we first verified our model formalism by 10-fold cross-validation on predicting gene expression. We next evaluated RACER on recovering known regulatory interactions, and demonstrated its superior statistical power over existing methods in detecting known miRNA/TF targets. Additionally, we developed a feature selection procedure, which identified 18 regulators, whose activities clustered consistently with cytogenetic risk groups. One of the selected regulators is miR-548p, whose inferred targets were significantly enriched for leukemia-related pathway, implicating its novel role in AML pathogenesis. Moreover, survival analysis using the inferred activities identified C-Fos as a potential AML

  15. Combining metabolomic analysis and microarray gene expression analysis in the characterization of the medicinal plant Chelidonium majus L.

    PubMed

    Orland, A; Knapp, K; König, G M; Ulrich-Merzenich, G; Knöß, W

    2014-10-15

    Even though herbal medicines have played an important role in disease management and health for many centuries, their present frequent use is challenged by the necessity to determine their complex composition and their multitarget mode of action. In the present study, modern methods were investigated towards their potential in the characterization of herbal substances. As a model the herbal substance Chelidonii herba was used, for which several reports on liver toxicities exist. Extracts of Chelidonii herba with different solvents were characterized phytochemically and functionally by experiments with HepG2 liver cells. Chelidonii herba was extracted with four solvents of different polarity (dichloromethane, water, ethanol, and ethanol 50% (V/V); four replicates each). The different extracts were characterized metabolomically by (1)H-NMR fingerprinting analysis and principal component analysis (PCA). The content of alkaloids was additionally determined by RP-HPLC. Functional characterization was achieved by the determination of cell proliferation and by transcriptomics techniques (Whole Genome Gene Expression Microarrays v2, Agilent Technologies) in HepG2 cells after exposure to the different extracts (four experimental replicates each). Based on data from (1)H-NMR fingerprints and RP-HPLC analyses the different extracts showed a divergent composition of constituents depending on the solvent used. HepG2 liver cells responded differentially to the four extracts. Microarray analysis revealed a significant regulation of genes and signal cascades related to biotransformation. Also liver-toxic signal cascades were activated. Neither the activated genes nor the proliferation response could be clearly related to the differing alkaloid content of the extracts. Different manufacturing processes lead to different herbal preparations. A systems biology approach combining a metabolomic plant analysis with a functional characterization by gene expression profiling in HepG2

  16. The microarray gene profiling analysis of glioblastoma cancer cells reveals genes affected by FAK inhibitor Y15 and combination of Y15 and temozolomide.

    PubMed

    Huang, Grace; Ho, Baotran; Conroy, Jeffrey; Liu, Song; Qiang, Hu; Golubovskaya, Vita

    2014-01-01

    Focal adhesion is known to be highly expressed and activated in glioma cells. Recently, we demonstrated that FAK autophosphorylation inhibitor, Y15 significantly decreased tumor growth of DBTRG and U87 cells, especially in combination with temozolomide. In the present report, we performed gene expression analysis in these cells to reveal genes affected by Y15, temozolomide and combination of Y15 and temozolomide. We tested the effect of Y15 on gene expression by Illumina Human HT12v4 microarray assay and detected 8087 and 6555 genes, which were significantly either up- or down-regulated by Y15-treatment in DBTRG and U87 cells, respectively (p<0.05). Moreover, DBTRG and U87 cells treated with Y15 changed expression of 1332 and 462 genes more than 1.5 fold, p<0.05, respectively and had 237 common genes affected by Y15. The common genes up-regulated by Y15 included GADD45A, HSPA6 (heat-shock 70); DUSP1, DUSP 5 (dual-phosphatase 5); CDKN1A (p21) and common down-regulated genes included kinesins, such as KIF11, 14, 20A, 20B; topoisomerase II, TOP2A; cyclin F; cell cycle protein: BUB1; PARP1, POLA1. In addition, we detected genes affected by temozolomide and by combination of Y15 and temozolomide treatment in U87 cells. Among genes up-regulated by Y15 and temozolomide more significantly than by each agent alone were: COX7B; interferon, gamma-inducible transcript: IFI16; DDIT4; GADD45G and down-regulated: KIF3A, AKT1; ABL; JAK1, GLI3 and ALDH1A3. Thus, microarray gene expression analysis can be effective in establishing genes affected in response to FAK inhibitor alone and in response to combination of Y15 with temozolomide that is important for glioblastoma therapy.

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2012-01-01

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

  19. A combination of gene expression ranking and co-expression network analysis increases discovery rate in large-scale mutant screens for novel Arabidopsis thaliana abiotic stress genes.

    PubMed

    Ransbotyn, Vanessa; Yeger-Lotem, Esti; Basha, Omer; Acuna, Tania; Verduyn, Christoph; Gordon, Michal; Chalifa-Caspi, Vered; Hannah, Matthew A; Barak, Simon

    2015-05-01

    As challenges to food security increase, the demand for lead genes for improving crop production is growing. However, genetic screens of plant mutants typically yield very low frequencies of desired phenotypes. Here, we present a powerful computational approach for selecting candidate genes for screening insertion mutants. We combined ranking of Arabidopsis thaliana regulatory genes according to their expression in response to multiple abiotic stresses (Multiple Stress [MST] score), with stress-responsive RNA co-expression network analysis to select candidate multiple stress regulatory (MSTR) genes. Screening of 62 T-DNA insertion mutants defective in candidate MSTR genes, for abiotic stress germination phenotypes yielded a remarkable hit rate of up to 62%; this gene discovery rate is 48-fold greater than that of other large-scale insertional mutant screens. Moreover, the MST score of these genes could be used to prioritize them for screening. To evaluate the contribution of the co-expression analysis, we screened 64 additional mutant lines of MST-scored genes that did not appear in the RNA co-expression network. The screening of these MST-scored genes yielded a gene discovery rate of 36%, which is much higher than that of classic mutant screens but not as high as when picking candidate genes from the co-expression network. The MSTR co-expression network that we created, AraSTressRegNet is publicly available at http://netbio.bgu.ac.il/arnet. This systems biology-based screening approach combining gene ranking and network analysis could be generally applicable to enhancing identification of genes regulating additional processes in plants and other organisms provided that suitable transcriptome data are available.

  20. Combined analysis of DNA methylome and transcriptome reveal novel candidate genes with susceptibility to bovine Staphylococcus aureus subclinical mastitis

    PubMed Central

    Song, Minyan; He, Yanghua; Zhou, Huangkai; Zhang, Yi; Li, Xizhi; Yu, Ying

    2016-01-01

    Subclinical mastitis is a widely spread disease of lactating cows. Its major pathogen is Staphylococcus aureus (S. aureus). In this study, we performed genome-wide integrative analysis of DNA methylation and transcriptional expression to identify candidate genes and pathways relevant to bovine S. aureus subclinical mastitis. The genome-scale DNA methylation profiles of peripheral blood lymphocytes in cows with S. aureus subclinical mastitis (SA group) and healthy controls (CK) were generated by methylated DNA immunoprecipitation combined with microarrays. We identified 1078 differentially methylated genes in SA cows compared with the controls. By integrating DNA methylation and transcriptome data, 58 differentially methylated genes were shared with differently expressed genes, in which 20.7% distinctly hypermethylated genes showed down-regulated expression in SA versus CK, whereas 14.3% dramatically hypomethylated genes showed up-regulated expression. Integrated pathway analysis suggested that these genes were related to inflammation, ErbB signalling pathway and mismatch repair. Further functional analysis revealed that three genes, NRG1, MST1 and NAT9, were strongly correlated with the progression of S. aureus subclinical mastitis and could be used as powerful biomarkers for the improvement of bovine mastitis resistance. Our studies lay the groundwork for epigenetic modification and mechanistic studies on susceptibility of bovine mastitis. PMID:27411928

  1. Global Transcriptome Analysis of Combined Abiotic Stress Signaling Genes Unravels Key Players in Oryza sativa L.: An In silico Approach

    PubMed Central

    Muthuramalingam, Pandiyan; Krishnan, Subramanian R.; Pothiraj, Ramanujam; Ramesh, Manikandan

    2017-01-01

    Combined abiotic stress (CAbS) affects the field grown plants simultaneously. The multigenic and quantitative nature of uncontrollable abiotic stresses complicates the process of understanding the stress response by plants. Considering this, we analyzed the CAbS response of C3 model plant, Oryza sativa by meta-analysis. The datasets of commonly expressed genes by drought, salinity, submergence, metal, natural expression, biotic, and abiotic stresses were data mined through publically accessible transcriptomic abiotic stress (AbS) responsive datasets. Of which 1,175, 12,821, and 42,877 genes were commonly expressed in meta differential, individual differential, and unchanged expressions respectively. Highly regulated 100 differentially expressed AbS genes were derived through integrative meta-analysis of expression data (INMEX). Of this 30 genes were identified from AbS gene families through expression atlas that were computationally analyzed for their physicochemical properties. All AbS genes were physically mapped against O. sativa genome. Comparative mapping of these genes demonstrated the orthologous relationship with related C4 panicoid genome. In silico expression analysis of these genes showed differential expression patterns in different developmental tissues. Protein–protein interaction of these genes, represented the complexity of AbS. Computational expression profiling of candidate genes in response to multiple stresses suggested the putative involvement of OS05G0350900, OS02G0612700, OS05G0104200, OS03G0596200, OS12G0225900, OS07G0152000, OS08G0119500, OS06G0594700, and Os01g0393100 in CAbS. These potential candidate genes need to be studied further to decipher their functional roles in AbS dynamics. PMID:28555143

  2. A combined strategy of "in silico" transcriptome analysis and web search engine optimization allows an agile identification of reference genes suitable for normalization in gene expression studies.

    PubMed

    Faccioli, Primetta; Ciceri, Gian Paolo; Provero, Paolo; Stanca, Antonio Michele; Morcia, Caterina; Terzi, Valeria

    2007-03-01

    Traditionally housekeeping genes have been employed as endogenous reference (internal control) genes for normalization in gene expression studies. Since the utilization of single housekeepers cannot assure an unbiased result, new normalization methods involving multiple housekeeping genes and normalizing using their mean expression have been recently proposed. Moreover, since a gold standard gene suitable for every experimental condition does not exist, it is also necessary to validate the expression stability of every putative control gene on the specific requirements of the planned experiment. As a consequence, finding a good set of reference genes is for sure a non-trivial problem requiring quite a lot of lab-based experimental testing. In this work we identified novel candidate barley reference genes suitable for normalization in gene expression studies. An advanced web search approach aimed to collect, from publicly available web resources, the most interesting information regarding the expression profiling of candidate housekeepers on a specific experimental basis has been set up and applied, as an example, on stress conditions. A complementary lab-based analysis has been carried out to verify the expression profile of the selected genes in different tissues and during heat shock response. This combined dry/wet approach can be applied to any species and physiological condition of interest and can be considered very helpful to identify putative reference genes to be shortlisted every time a new experimental design has to be set up.

  3. Combined analysis of chromosomal instabilities and gene expression for colon cancer progression inference.

    PubMed

    Cava, Claudia; Zoppis, Italo; Gariboldi, Manuela; Castiglioni, Isabella; Mauri, Giancarlo; Antoniotti, Marco

    2014-01-24

    Copy number alterations (CNAs) represent an important component of genetic variations. Such alterations are related with certain type of cancer including those of the pancreas, colon, and breast, among others. CNAs have been used as biomarkers for cancer prognosis in multiple studies, but few works report on the relation of CNAs with the disease progression. Moreover, most studies do not consider the following two important issues. (I) The identification of CNAs in genes which are responsible for expression regulation is fundamental in order to define genetic events leading to malignant transformation and progression. (II) Most real domains are best described by structured data where instances of multiple types are related to each other in complex ways. Our main interest is to check whether the colorectal cancer (CRC) progression inference benefits when considering both (I) the expression levels of genes with CNAs, and (II) relationships (i.e. dissimilarities) between patients due to expression level differences of the altered genes. We first evaluate the accuracy performance of a state-of-the-art inference method (support vector machine) when subjects are represented only through sets of available attribute values (i.e. gene expression level). Then we check whether the inference accuracy improves, when explicitly exploiting the information mentioned above. Our results suggest that the CRC progression inference improves when the combined data (i.e. CNA and expression level) and the considered dissimilarity measures are applied. Through our approach, classification is intuitively appealing and can be conveniently obtained in the resulting dissimilarity spaces. Different public datasets from Gene Expression Omnibus (GEO) were used to validate the results.

  4. Combined analysis of chromosomal instabilities and gene expression for colon cancer progression inference

    PubMed Central

    2014-01-01

    Background Copy number alterations (CNAs) represent an important component of genetic variations. Such alterations are related with certain type of cancer including those of the pancreas, colon, and breast, among others. CNAs have been used as biomarkers for cancer prognosis in multiple studies, but few works report on the relation of CNAs with the disease progression. Moreover, most studies do not consider the following two important issues. (I) The identification of CNAs in genes which are responsible for expression regulation is fundamental in order to define genetic events leading to malignant transformation and progression. (II) Most real domains are best described by structured data where instances of multiple types are related to each other in complex ways. Results Our main interest is to check whether the colorectal cancer (CRC) progression inference benefits when considering both (I) the expression levels of genes with CNAs, and (II) relationships (i.e. dissimilarities) between patients due to expression level differences of the altered genes. We first evaluate the accuracy performance of a state-of-the-art inference method (support vector machine) when subjects are represented only through sets of available attribute values (i.e. gene expression level). Then we check whether the inference accuracy improves, when explicitly exploiting the information mentioned above. Our results suggest that the CRC progression inference improves when the combined data (i.e. CNA and expression level) and the considered dissimilarity measures are applied. Conclusions Through our approach, classification is intuitively appealing and can be conveniently obtained in the resulting dissimilarity spaces. Different public datasets from Gene Expression Omnibus (GEO) were used to validate the results. PMID:24456927

  5. High-resolution mapping of the gene for cystinosis, using combined biochemical and linkage analysis.

    PubMed

    Jean, G; Fuchshuber, A; Town, M M; Gribouval, O; Schneider, J A; Broyer, M; van't Hoff, W; Niaudet, P; Antignac, C

    1996-03-01

    Infantile nephropathic cystinosis is an autosomal recessive disorder characterized biochemically by an abnormally high intracellular content of free cystine in different organs and tissues due to a transport defect of cystine through the lysosomal membrane. Affected children present with the Fanconi syndrome and usually develop progressive renal failure within the 1st decade of life. Measurement of free cystine in purified polymorphonuclear leukocytes provides an accurate method for diagnosis and detection of heterozygous carriers. In order to localize the gene locus for cystinosis we performed linkage analysis in 18 cystinosis families. However, since 17 of these were simplex families, we decided to include the phenotypes of the heterozygous carriers previously determined by their leukocyte cystine content in the linkage analysis. This approach allowed us to obtain highly significant results, confirming the localization of the cystinosis gene locus recently mapped to the short arm of chromosome 17 by the Cystinosis Collaborative Research Group. Crucial recombination events allowed us to refine the interval of the cystinosis gene to a genetic distance of 1 cM. No evidence of genetic heterogeneity was found. Our results demonstrate that the use of the previously determined phenotypes of heterozygous carriers in linkage analysis provides a reliable method for the investigation of simplex families in autosomal recessive traits.

  6. Combination of microdissection and microarray analysis to identify gene expression changes between differentially located tumour cells in breast cancer.

    PubMed

    Zhu, Gang; Reynolds, Louise; Crnogorac-Jurcevic, Tatjana; Gillett, Cheryl E; Dublin, Edwin A; Marshall, John F; Barnes, Diana; D'Arrigo, Corrado; Van Trappen, Philippe O; Lemoine, Nicholas R; Hart, Ian R

    2003-06-12

    Comparison of gene expression changes between cancer cells at the periphery and in the centre of breast cancers was performed using a combination of microdissection and microarray analysis. Cancer cells from the two areas were pooled separately from five patients with ductal carcinoma in situ and separately from five patients with frankly invasive cancer. Limited total RNA, 100-200 ng, from this microdissected tissue required use of the Atlas SMART trade mark Probe Amplification Kit to synthesize and amplify cDNA and make (33)P-labelled probes. Probes were then hybridized to Atlas Human Cancer 1.2 Arrays containing 1176 known genes. Triplicate analysis revealed that 22 genes changed their expression levels in the periphery relative to the central region: 15 upregulated and seven downregulated (arbitrary threshold of 1.5-fold or greater). Differences in RNA levels were confirmed by quantitative real-time PCR for two of the genes and by changes in protein levels, detected by immunohistochemistry, for a couple of representative gene products. Thus, changes in gene expression associated with variation in microanatomical location of neoplastic cells can be detected within even small developing tumour masses.

  7. High-resolution mapping of the gene for cystinosis, using combined biochemical and linkage analysis

    SciTech Connect

    Jean, G.; Fuchshuber, A.; Gribouval, O.

    1996-03-01

    Infantile nephropathic cystinosis is an autosomal recessive disorder characterized biochemically by an abnormally high intracellular content of free cystine in different organs and tissues due to a transport defect of cystine through the lysosomal membrane. Affected children present with the Fanconi syndrome and usually develop progressive renal failure within the 1st decade of life. Measurement of free cystine in purified polymorphonuclear leukocytes provides an accurate method for diagnosis and detection of heterozygous carriers previously determined by their leukocyte cystine content in the linkage analysis. This approach allowed us to obtain highly significant results, confirming the localization of the cystinosis gene locus recently mapped to the short arm of chromosome 17 by the Cystinosis Collaborative Research Group. Crucial recombination events allowed us to refine the interval of the cystinosis gene to a genetic distance of 1 cM. No evidence of genetic heterogeneity was found. Our results demonstrate that the use of the previously determined phenotypes of heterozygous carriers in linkage analysis provides a reliable method for the investigation of simplex families in autosomal recessive traits. 25 refs., 4 figs., 1 tab.

  8. A fungal phylogeny based on 42 complete genomes derived from supertree and combined gene analysis

    PubMed Central

    Fitzpatrick, David A; Logue, Mary E; Stajich, Jason E; Butler, Geraldine

    2006-01-01

    Background To date, most fungal phylogenies have been derived from single gene comparisons, or from concatenated alignments of a small number of genes. The increase in fungal genome sequencing presents an opportunity to reconstruct evolutionary events using entire genomes. As a tool for future comparative, phylogenomic and phylogenetic studies, we used both supertrees and concatenated alignments to infer relationships between 42 species of fungi for which complete genome sequences are available. Results A dataset of 345,829 genes was extracted from 42 publicly available fungal genomes. Supertree methods were employed to derive phylogenies from 4,805 single gene families. We found that the average consensus supertree method may suffer from long-branch attraction artifacts, while matrix representation with parsimony (MRP) appears to be immune from these. A genome phylogeny was also reconstructed from a concatenated alignment of 153 universally distributed orthologs. Our MRP supertree and concatenated phylogeny are highly congruent. Within the Ascomycota, the sub-phyla Pezizomycotina and Saccharomycotina were resolved. Both phylogenies infer that the Leotiomycetes are the closest sister group to the Sordariomycetes. There is some ambiguity regarding the placement of Stagonospora nodurum, the sole member of the class Dothideomycetes present in the dataset. Within the Saccharomycotina, a monophyletic clade containing organisms that translate CTG as serine instead of leucine is evident. There is also strong support for two groups within the CTG clade, one containing the fully sexual species Candida lusitaniae, Candida guilliermondii and Debaryomyces hansenii, and the second group containing Candida albicans, Candida dubliniensis, Candida tropicalis, Candida parapsilosis and Lodderomyces elongisporus. The second major clade within the Saccharomycotina contains species whose genomes have undergone a whole genome duplication (WGD), and their close relatives. We could not

  9. Phylogenetics of flowering plants based on combined analysis of plastid atpB and rbcL gene sequences.

    PubMed

    Savolainen, V; Chase, M W; Hoot, S B; Morton, C M; Soltis, D E; Bayer, C; Fay, M F; de Bruijn, A Y; Sullivan, S; Qiu, Y L

    2000-06-01

    Following (1) the large-scale molecular phylogeny of seed plants based on plastid rbcL gene sequences (published in 1993 by Chase et al., Ann. Missouri Bot. Gard. 80:528-580) and (2) the 18S nuclear phylogeny of flowering plants (published in 1997 by Soltis et al., Ann. Missouri Bot. Gard. 84:1-49), we present a phylogenetic analysis of flowering plants based on a second plastid gene, atpB, analyzed separately and in combination with rbcL sequences for 357 taxa. Despite some discrepancies, the atpB-based phylogenetic trees were highly congruent with those derived from the analysis of rbcL and 18S rDNA, and the combination of atpB and rbcL DNA sequences (comprising approximately 3000 base pairs) produced increased bootstrap support for many major sets of taxa. The angiosperms are divided into two major groups: noneudicots with inaperturate or uniaperturate pollen (monocots plus Laurales, Magnoliales, Piperales, Ceratophyllales, and Amborellaceae-Nymphaeaceae-Illiciaceae) and the eudicots with triaperturate pollen (particularly asterids and rosids). Based on rbcL alone and atpB/rbcL combined, the noneudicots (excluding Ceratophyllum) are monophyletic, whereas in the atpB trees they form a grade. Ceratophyllum is sister to the rest of angiosperms with rbcL alone and in the combined atpB/rbcL analysis, whereas with atpB alone, Amborellaceae, Nymphaeaceae, and Illiciaceae/Schisandraceae form a grade at the base of the angiosperms. The phylogenetic information at each codon position and the different types of substitutions (observed transitions and transversions in the trees vs. pairwise comparisons) were examined; taking into account their respective consistency and retention indices, we demonstrate that third-codon positions and transitions are the most useful characters in these phylogenetic reconstructions. This study further demonstrates that phylogenetic analysis of large matrices is feasible.

  10. Gene expression profiling of osteoclast differentiation by combined suppression subtractive hybridization (SSH) and cDNA microarray analysis.

    PubMed

    Rho, Jaerang; Altmann, Curtis R; Socci, Nicholas D; Merkov, Lubomir; Kim, Nacksung; So, Hongseob; Lee, Okbok; Takami, Masamichi; Brivanlou, Ali H; Choi, Yongwon

    2002-08-01

    Bone homeostasis is maintained by the balanced action of bone-forming osteoblasts and bone-resorbing osteoclasts. Multinucleated, mature osteoclasts develop from hematopoietic stem cells via the monocyte-macrophage lineage, which also give rise to macrophages and dendritic cells. Despite their distinct physiologic roles in bone and the immune system, these cell types share many molecular and biochemical features. To provide insights into how osteoclasts differentiate and function to control bone metabolism, we employed a systematic approach to profile patterns of osteoclast-specific gene expression by combining suppression subtractive hybridization (SSH) and cDNA microarray analysis. Here we examined how gene expression profiles of mature osteoclast differ from macrophage or dendritic cells, how gene expression profiles change during osteoclast differentiation, and how Mitf, a transcription factor critical for osteoclast maturation, affects the gene expression profile. This approach revealed a set of genes coordinately regulated for osteoclast function, some of which have previously been implicated in several bone diseases in humans.

  11. Gene-based multiple regression association testing for combined examination of common and low frequency variants in quantitative trait analysis.

    PubMed

    Yoo, Yun Joo; Sun, Lei; Bull, Shelley B

    2013-01-01

    Multi-marker methods for genetic association analysis can be performed for common and low frequency SNPs to improve power. Regression models are an intuitive way to formulate multi-marker tests. In previous studies we evaluated regression-based multi-marker tests for common SNPs, and through identification of bins consisting of correlated SNPs, developed a multi-bin linear combination (MLC) test that is a compromise between a 1 df linear combination test and a multi-df global test. Bins of SNPs in high linkage disequilibrium (LD) are identified, and a linear combination of individual SNP statistics is constructed within each bin. Then association with the phenotype is represented by an overall statistic with df as many or few as the number of bins. In this report we evaluate multi-marker tests for SNPs that occur at low frequencies. There are many linear and quadratic multi-marker tests that are suitable for common or low frequency variant analysis. We compared the performance of the MLC tests with various linear and quadratic statistics in joint or marginal regressions. For these comparisons, we performed a simulation study of genotypes and quantitative traits for 85 genes with many low frequency SNPs based on HapMap Phase III. We compared the tests using (1) set of all SNPs in a gene, (2) set of common SNPs in a gene (MAF ≥ 5%), (3) set of low frequency SNPs (1% ≤ MAF < 5%). For different trait models based on low frequency causal SNPs, we found that combined analysis using all SNPs including common and low frequency SNPs is a good and robust choice whereas using common SNPs alone or low frequency SNP alone can lose power. MLC tests performed well in combined analysis except where two low frequency causal SNPs with opposing effects are positively correlated. Overall, across different sets of analysis, the joint regression Wald test showed consistently good performance whereas other statistics including the ones based on marginal regression had lower power for

  12. Combined gene expression and proteomic analysis of EGF induced apoptosis in A431 cells suggests multiple pathways trigger apoptosis.

    PubMed

    Alanazi, Ibrahim; Ebrahimie, Esmaeil; Hoffmann, Peter; Adelson, David L

    2013-11-01

    A431 cells, derived from epidermoid carcinoma, overexpress the epidermal growth factor receptor (EGFR) and when treated with a high dose of EGF will undergo apoptosis. We exploited microarray and proteomics techniques and network prediction to study the regulatory mechanisms of EGF-induced apoptosis in A431 cells. We observed significant changes in gene expression in 162 genes, approximately evenly split between pro-apoptotic and anti-apoptotic genes and identified 30 proteins from the proteomic data that had either pro or anti-apoptotic annotation. Our correlation analysis of gene expression and proteome modeled a number of distinct sub-networks that are associated with the onset of apoptosis, allowing us to identify specific pathways and components. These include components of the interferon signalling pathway, and down stream components, including cytokines and suppressors of cytokine signalling. A central component of almost all gene expression sub-networks identified was TP53, which is mutated in A431 cells, and was down regulated. This down regulation of TP53 appeared to be correlated with proteomic sub-networks of cytoskeletal or cell adhesion components that might induce apoptosis by triggering cytochrome C release. Of the only three genes also differentially expressed as proteins, only serpinb1 had a known association with apoptosis. We confirmed that up regulation and cleavage of serpinb1 into L-DNAaseII was correlated with the induction of apoptosis. It is unlikely that a single pathway, but more likely a combination of pathways is needed to trigger EGF induced apoptosis in A431cells.

  13. Association analysis of bovine Foxa2 gene single sequence variant and haplotype combinations with growth traits in Chinese cattle.

    PubMed

    Liu, Mei; Li, Mijie; Wang, Shaoqiang; Xu, Yao; Lan, Xianyong; Li, Zhuanjian; Lei, Chuzhao; Yang, Dongying; Jia, Yutang; Chen, Hong

    2014-02-25

    Forkhead box A2 (Foxa2) has been recognized as one of the most potent transcriptional activators that is implicated in the control of feeding behavior and energy homeostasis. However, similar researches about the effects of genetic variations of Foxa2 gene on growth traits are lacking. Therefore, this study detected Foxa2 gene polymorphisms by DNA pool sequencing, PCR-RFLP and PCR-ACRS methods in 822 individuals from three Chinese cattle breeds. The results showed that four sequence variants (SVs) were screened, including two mutations (SV1, g. 7005 C>T and SV2, g. 7044 C>G) in intron 4, one mutation (SV3, g. 8449 A>G) in exon 5 and one mutation (SV4, g. 8537 T>C) in the 3'UTR. Notably, association analysis of the single mutations with growth traits in total individuals (at 24months) revealed that significant statistical difference was found in four SVs, and SV4 locus was highly significantly associated with growth traits throughout all three breeds (P<0.05 or P<0.01). Meanwhile, haplotype combination CCCCAGTC also indicated remarkably associated to better chest girth and body weight in Jiaxian Red cattle (P<0.05). We herein described a comprehensive study on the variability of bovine Foxa2 gene that was predictive of molecular markers in cattle breeding for the first time. Copyright © 2013 Elsevier B.V. All rights reserved.

  14. Introducing Transgenes Into Insect Populations Using Combined Gene-drive Strategies: Modeling and Analysis

    PubMed Central

    Magori, Krisztian; Lloyd, Alun L.; Gould, Fred

    2007-01-01

    Engineered underdominance (EU), meiotic drive (MD) and Wolbachia have been proposed as mechanisms for driving anti-pathogen transgenes into natural populations of insect vectors of human diseases. EU can drive transgenes to high and stable frequencies but requires the release of sizeable numbers of engineered insects. MD and Wolbachia either cannot maintain high frequencies of transgenes or lack appropriate expression in critical tissues, but both can drive the transgenes to spread from very low initial frequencies. Here we use mathematical models to assess the utility of combining EU with MD or with Wolbachia. Under some conditions, the combination of EU and MD results in a more efficient transgene-drive strategy than either mechanism alone. This combined strategy could drive the transgenes to stable fixation and would require fewer released insects than EU alone, especially when only males are released. However, a combination of EU and Wolbachia does not work better than EU alone because it requires the release of even more engineered insects. PMID:17785193

  15. Detection of putative functional angiotensinogen (AGT) gene variants controlling plasma AGT levels by combined segregation-linkage analysis.

    PubMed

    Brand, Eva; Chatelain, Nathalie; Paillard, Françoise; Tiret, Laurence; Visvikis, Sophie; Lathrop, Mark; Soubrier, Florent; Demenais, Florence

    2002-11-01

    Previous studies have suggested that angiotensinogen (AGT) gene variants are associated with increased plasma AGT levels, and may also contribute towards the inherited component of predisposition to essential hypertension in humans. To explore the potential functionality of several AGT polymorphisms and estimate their effects, together with other sources of familial correlations, on plasma AGT, we undertook a large study involving 545 healthy French volunteers in 130 nuclear families that include 285 offspring. Plasma AGT levels were measured in all participants, and bi-allelic AGT variants were analysed as candidate functional variants at three sites in the 5'-flanking region (C-532T, A-20C, G-6A), two sites in exon 2 (M235T, T174M) and two newly identified variant sites in the untranslated sequence of exon 5 and the 3'-flanking region (C+2054A, C+2127T) of the gene. Analysis with the class D regressive model showed significant effects influencing plasma AGT levels of all AGT polymorphisms tested, with the exception of T174M. The most significant result was found at C-532T (P=0.000001), which accounts for 4.3% of total plasma AGT variability in parents and 5.5% in offspring, with substantial residual familial correlations. Maximum likelihood estimates of haplotype frequencies and tests of linkage disequilibrium between each AGT polymorphism and a putative QTL are in agreement with a complete confounding of C-532T with the QTL, when taking into account sex and generation specific effects of the QTL. However, further combined segregation-linkage analyses showed significant evidence for additional effects of G-6A, M235T and C+2054A polymorphisms after accounting for C-532T, which supports a complex model with at least two functional variants within the AGT gene controlling AGT levels.

  16. Gene-Category Analysis.

    PubMed

    Bauer, Sebastian

    2017-01-01

    Gene-category analysis is one important knowledge integration approach in biomedical sciences that combines knowledge bases such as Gene Ontology with lists of genes or their products, which are often the result of high-throughput experiments, gained from either wet-lab or synthetic experiments. In this chapter, we will motivate this class of analyses and describe an often used variant that is based on Fisher's exact test. We show that this approach has some problems in the context of Gene Ontology of which users should be aware. We then describe some more recent algorithms that try to address some of the shortcomings of the standard approach.

  17. Molecular phylogeny of monocotyledons inferred from combined analysis of plastid matK and rbcL gene sequences.

    PubMed

    Tamura, Minoru N; Yamashita, Jun; Fuse, Shizuka; Haraguchi, Masatake

    2004-04-01

    Using matK and rbcL sequences (3,269 bp in total) from 113 genera of 45 families, we conducted a combined analysis to contribute to the understanding of major evolutionary relationships in the monocotyledons. Trees resulting from the parsimony analysis are similar to those generated by earlier single or multiple gene analyses, but their strict consensus tree provides much better resolution of relationships among major clades. We find that Acorus (Acorales) is a sister group to the rest of the monocots, which receives 100% bootstrap support. A clade comprising Alismatales is diverged as the next branch, followed successively by Petrosaviaceae, the Dioscoreales-Pandanales clade, Liliales, Asparagales and commelinoids. All of these clades are strongly supported (with more than 90% bootstrap support). The sister-group relationship is also strongly supported between Alismatales and the remaining monocots (except for Acorus) (100%), between Petrosaviaceae and the remaining monocots (except for Acorus and Alismatales) (100%), between the clade comprising Dioscoreales and Pandanales and the clade comprising Liliales, Asparagales and commelinoids (87%), and between Liliales and the Asparagales-commelinoids clade (89%). Only the sister-group relationship between Asparagales and commelinoids is weakly supported (68%). Results also support the inclusion of Petrosaviaceae in its own order Petrosaviales, Nartheciaceae in Dioscoreales and Hanguanaceae in Commelinales.

  18. Combining localized PCR mutagenesis and natural transformation in direct genetic analysis of a transcriptional regulator gene, pobR.

    PubMed Central

    Kok, R G; D'Argenio, D A; Ornston, L N

    1997-01-01

    We present a procedure for efficient random mutagenesis of selected genes in a bacterial chromosome. The method combines PCR replication errors with the uptake of PCR-amplified DNA via natural transformation. Cloning of PCR fragments is not required, since mutations are transferred directly to the chromosome via homologous recombination. Random mutations were introduced into the Acinetobacter chromosomal pobR gene encoding the transcriptional activator of pobA, the structural gene for 4-hydroxybenzoate 3-hydroxylase. Mutant strains with strongly reduced PobR activity were selected by demanding the inability to convert 4-hydroxybenzoate to a toxic metabolite. Of spontaneous pobR mutants, 80% carry the insertion element IS1236, rendering them inappropriate for structure-function studies. Transformation with Taq-amplified pobR DNA increased the mutation frequency 240-fold and reduced the proportion of IS1236 inserts to undetectable levels. The relative fidelity of Pfu polymerase compared with Taq polymerase was illustrated by a reduced effect on the mutation frequency; a procedure for rapid assessment of relative polymerase fidelity in PCR follows from this observation. Over 150 independent mutations were localized by transformation with DNA fragments containing nested deletions of wild-type pobR. Sequence analysis of 89 of the mutant pobR alleles showed that the mutations were predominantly single-nucleotide substitutions broadly distributed within pobR. Promoter mutations were recovered, as were two mutations that are likely to block pobR translation. One-third of the recovered mutations conferred a leaky or temperature-sensitive phenotype, whereas the remaining null mutations completely blocked growth with 4-hydroxybenzoate. Strains containing two different nonsense mutations in pobR were transformed with PCR-amplified DNA to identify permissible codon substitutions. Independently, second-site suppressor mutations were recovered within pcaG, another member of the

  19. Analysis of Polymorphism of Angiotensin System Genes (ACE, AGTR1, and AGT) and Gene ITGB3 in Patients with Arterial Hypertension in Combination with Metabolic Syndrome.

    PubMed

    Zotova, T Yu; Kubanova, A P; Azova, M M; Aissa, A Ait; Gigani, O O; Frolov, V A

    2016-07-01

    Changes in the frequencies of genotypes and mutant alleles of ACE, AGTR1, AGT, and ITGB3 genes were analyzed in patients with arterial hypertension coupled with metabolic syndrome (N=15) and compared with population data and corresponding parameters in patients with isolated hypertension (N=15). Increased frequency of genotype ID of ACE gene (hypertension predictor) was confirmed for both groups. In case of isolated hypertension, M235M genotype (gene AGT) was more frequent, in case of hypertension combined with metabolic syndrome, the frequency of genotypes A1166C and C1166C of the gene AGTR1 was higher in comparison with population data. Comparison of mutant allele frequencies in the two groups showed that at the 90% significance level allele T of the AGT gene was more frequent in hypertension coupled with metabolic syndrome (OR=1.26) and genotype A1166A of the AGTR1 gene was more frequent in the group with isolated hypertension.

  20. Analysis of differentially expressed genes in placental tissues of preeclampsia patients using microarray combined with the Connectivity Map database.

    PubMed

    Song, Y; Liu, J; Huang, S; Zhang, L

    2013-12-01

    Preeclampsia (PE), which affects 2-7% of human pregnancies, causes significant maternal and neonatal morbidity and mortality. To better understand the pathophysiology of PE, the gene expression profiles of placental tissue from 5 controls and 5 PE patients were assessed using microarray. A total of 224 transcripts were significantly differentially expressed (>2-fold change and q value <0.05, SAM software). Gene Ontology (GO) enrichment analysis indicated that genes involved in hypoxia and oxidative and reductive processes were significantly changed. Three differentially expressed genes (DEGs) involved in these biological processes were further verified by quantitative real-time PCR. Finally, the potential therapeutic agents for PE were explored via the Connectivity Map database. In conclusion, the data obtained in this study might provide clues to better understand the pathophysiology of PE and to identify potential therapeutic agents for PE patients.

  1. Weighted-SAMGSR: combining significance analysis of microarray-gene set reduction algorithm with pathway topology-based weights to select relevant genes.

    PubMed

    Tian, Suyan; Chang, Howard H; Wang, Chi

    2016-09-29

    It has been demonstrated that a pathway-based feature selection method that incorporates biological information within pathways during the process of feature selection usually outperforms a gene-based feature selection algorithm in terms of predictive accuracy and stability. Significance analysis of microarray-gene set reduction algorithm (SAMGSR), an extension to a gene set analysis method with further reduction of the selected pathways to their respective core subsets, can be regarded as a pathway-based feature selection method. In SAMGSR, whether a gene is selected is mainly determined by its expression difference between the phenotypes, and partially by the number of pathways to which this gene belongs. It ignores the topology information among pathways. In this study, we propose a weighted version of the SAMGSR algorithm by constructing weights based on the connectivity among genes and then combing these weights with the test statistics. Using both simulated and real-world data, we evaluate the performance of the proposed SAMGSR extension and demonstrate that the weighted version outperforms its original version. CONCLUSIONS: To conclude, the additional gene connectivity information does faciliatate feature selection. This article was reviewed by Drs. Limsoon Wong, Lev Klebanov, and, I. King Jordan.

  2. Combined chromatin and expression analysis reveals specific regulatory mechanisms within cytokine genes in the macrophage early immune response.

    PubMed

    Iglesias, Maria Jesus; Jesus Iglesias, Maria; Reilly, Sarah-Jayne; Emanuelsson, Olof; Sennblad, Bengt; Pirmoradian Najafabadi, Mohammad; Folkersen, Lasse; Mälarstig, Anders; Lagergren, Jens; Eriksson, Per; Hamsten, Anders; Odeberg, Jacob

    2012-01-01

    Macrophages play a critical role in innate immunity, and the expression of early response genes orchestrate much of the initial response of the immune system. Macrophages undergo extensive transcriptional reprogramming in response to inflammatory stimuli such as Lipopolysaccharide (LPS).To identify gene transcription regulation patterns involved in early innate immune responses, we used two genome-wide approaches--gene expression profiling and chromatin immunoprecipitation-sequencing (ChIP-seq) analysis. We examined the effect of 2 hrs LPS stimulation on early gene expression and its relation to chromatin remodeling (H3 acetylation; H3Ac) and promoter binding of Sp1 and RNA polymerase II phosphorylated at serine 5 (S5P RNAPII), which is a marker for transcriptional initiation. Our results indicate novel and alternative gene regulatory mechanisms for certain proinflammatory genes. We identified two groups of up-regulated inflammatory genes with respect to chromatin modification and promoter features. One group, including highly up-regulated genes such as tumor necrosis factor (TNF), was characterized by H3Ac, high CpG content and lack of TATA boxes. The second group, containing inflammatory mediators (interleukins and CCL chemokines), was up-regulated upon LPS stimulation despite lacking H3Ac in their annotated promoters, which were low in CpG content but did contain TATA boxes. Genome-wide analysis showed that few H3Ac peaks were unique to either +/-LPS condition. However, within these, an unpacking/expansion of already existing H3Ac peaks was observed upon LPS stimulation. In contrast, a significant proportion of S5P RNAPII peaks (approx 40%) was unique to either condition. Furthermore, data indicated a large portion of previously unannotated TSSs, particularly in LPS-stimulated macrophages, where only 28% of unique S5P RNAPII peaks overlap annotated promoters. The regulation of the inflammatory response appears to occur in a very specific manner at the chromatin

  3. Combined Chromatin and Expression Analysis Reveals Specific Regulatory Mechanisms within Cytokine Genes in the Macrophage Early Immune Response

    PubMed Central

    Emanuelsson, Olof; Sennblad, Bengt; Pirmoradian Najafabadi, Mohammad; Folkersen, Lasse; Mälarstig, Anders; Lagergren, Jens; Eriksson, Per; Hamsten, Anders; Odeberg, Jacob

    2012-01-01

    Macrophages play a critical role in innate immunity, and the expression of early response genes orchestrate much of the initial response of the immune system. Macrophages undergo extensive transcriptional reprogramming in response to inflammatory stimuli such as Lipopolysaccharide (LPS). To identify gene transcription regulation patterns involved in early innate immune responses, we used two genome-wide approaches - gene expression profiling and chromatin immunoprecipitation-sequencing (ChIP-seq) analysis. We examined the effect of 2 hrs LPS stimulation on early gene expression and its relation to chromatin remodeling (H3 acetylation; H3Ac) and promoter binding of Sp1 and RNA polymerase II phosphorylated at serine 5 (S5P RNAPII), which is a marker for transcriptional initiation. Our results indicate novel and alternative gene regulatory mechanisms for certain proinflammatory genes. We identified two groups of up-regulated inflammatory genes with respect to chromatin modification and promoter features. One group, including highly up-regulated genes such as tumor necrosis factor (TNF), was characterized by H3Ac, high CpG content and lack of TATA boxes. The second group, containing inflammatory mediators (interleukins and CCL chemokines), was up-regulated upon LPS stimulation despite lacking H3Ac in their annotated promoters, which were low in CpG content but did contain TATA boxes. Genome-wide analysis showed that few H3Ac peaks were unique to either +/−LPS condition. However, within these, an unpacking/expansion of already existing H3Ac peaks was observed upon LPS stimulation. In contrast, a significant proportion of S5P RNAPII peaks (approx 40%) was unique to either condition. Furthermore, data indicated a large portion of previously unannotated TSSs, particularly in LPS-stimulated macrophages, where only 28% of unique S5P RNAPII peaks overlap annotated promoters. The regulation of the inflammatory response appears to occur in a very specific manner at the

  4. The combination of a genome-wide association study of lymphocyte count and analysis of gene expression data reveals novel asthma candidate genes.

    PubMed

    Cusanovich, Darren A; Billstrand, Christine; Zhou, Xiang; Chavarria, Claudia; De Leon, Sherryl; Michelini, Katelyn; Pai, Athma A; Ober, Carole; Gilad, Yoav

    2012-05-01

    Recent genome-wide association studies (GWAS) have identified a number of novel genetic associations with complex human diseases. In spite of these successes, results from GWAS generally explain only a small proportion of disease heritability, an observation termed the 'missing heritability problem'. Several sources for the missing heritability have been proposed, including the contribution of many common variants with small individual effect sizes, which cannot be reliably found using the standard GWAS approach. The goal of our study was to explore a complimentary approach, which combines GWAS results with functional data in order to identify novel genetic associations with small effect sizes. To do so, we conducted a GWAS for lymphocyte count, a physiologic quantitative trait associated with asthma, in 462 Hutterites. In parallel, we performed a genome-wide gene expression study in lymphoblastoid cell lines from 96 Hutterites. We found significant support for genetic associations using the GWAS data when we considered variants near the 193 genes whose expression levels across individuals were most correlated with lymphocyte counts. Interestingly, these variants are also enriched with signatures of an association with asthma susceptibility, an observation we were able to replicate. The associated loci include genes previously implicated in asthma susceptibility as well as novel candidate genes enriched for functions related to T cell receptor signaling and adenosine triphosphate synthesis. Our results, therefore, establish a new set of asthma susceptibility candidate genes. More generally, our observations support the notion that many loci of small effects influence variation in lymphocyte count and asthma susceptibility.

  5. Quantifying evidence for candidate gene polymorphisms: Bayesian analysis combining sequence-specific and quantitative trait loci colocation information.

    PubMed

    Ball, Roderick D

    2007-12-01

    We calculate posterior probabilities for candidate genes as a function of genomic location. Posterior probabilities for quantitative trait loci (QTL) presence in a small interval are calculated using a Bayesian model-selection approach based on the Bayesian information criterion (BIC) and used to combine QTL colocation information with sequence-specific evidence, e.g., from differential expression and/or association studies. Our method takes into account uncertainty in estimation of number and locations of QTL and estimated map position. Posterior probabilities for QTL presence were calculated for simulated data with n = 100, 300, and 1200 QTL progeny and compared with interval mapping and composite-interval mapping. Candidate genes that mapped to QTL regions had substantially larger posterior probabilities. Among candidates with a given Bayes factor, those that map near a QTL are more promising for further investigation with association studies and functional testing or for use in marker-aided selection. The BIC is shown to correspond very closely to Bayes factors for linear models with a nearly noninformative Zellner prior for the simulated QTL data with n > or = 100. It is shown how to modify the BIC to use a subjective prior for the QTL effects.

  6. Analysis of Gene Expression Profiles of Soft Tissue Sarcoma Using a Combination of Knowledge-Based Filtering with Integration of Multiple Statistics

    PubMed Central

    Doi, Ayano; Ichinohe, Risa; Ikuyo, Yoriko; Takahashi, Teruyoshi; Marui, Shigetaka; Yasuhara, Koji; Nakamura, Tetsuro; Sugita, Shintaro; Sakamoto, Hiromi; Yoshida, Teruhiko; Hasegawa, Tadashi

    2014-01-01

    The diagnosis and treatment of soft tissue sarcomas (STS) have been difficult. Of the diverse histological subtypes, undifferentiated pleomorphic sarcoma (UPS) is particularly difficult to diagnose accurately, and its classification per se is still controversial. Recent advances in genomic technologies provide an excellent way to address such problems. However, it is often difficult, if not impossible, to identify definitive disease-associated genes using genome-wide analysis alone, primarily because of multiple testing problems. In the present study, we analyzed microarray data from 88 STS patients using a combination method that used knowledge-based filtering and a simulation based on the integration of multiple statistics to reduce multiple testing problems. We identified 25 genes, including hypoxia-related genes (e.g., MIF, SCD1, P4HA1, ENO1, and STAT1) and cell cycle- and DNA repair-related genes (e.g., TACC3, PRDX1, PRKDC, and H2AFY). These genes showed significant differential expression among histological subtypes, including UPS, and showed associations with overall survival. STAT1 showed a strong association with overall survival in UPS patients (logrank p = 1.84×10−6 and adjusted p value 2.99×10−3 after the permutation test). According to the literature, the 25 genes selected are useful not only as markers of differential diagnosis but also as prognostic/predictive markers and/or therapeutic targets for STS. Our combination method can identify genes that are potential prognostic/predictive factors and/or therapeutic targets in STS and possibly in other cancers. These disease-associated genes deserve further preclinical and clinical validation. PMID:25188299

  7. Combined histomorphometric and gene-expression profiling applied to toxicology.

    PubMed

    Kriete, Andres; Anderson, Mary K; Love, Brad; Freund, John; Caffrey, James J; Young, M Brook; Sendera, Timothy J; Magnuson, Scott R; Braughler, J Mark

    2003-01-01

    We have developed a unique methodology for the combined analysis of histomorphometric and gene-expression profiles amenable to intensive data mining and multisample comparison for a comprehensive approach to toxicology. This hybrid technology, termed extensible morphometric relational gene-expression analysis (EMeRGE), is applied in a toxicological study of time-varied vehicle- and carbon-tetrachloride (CCl4)-treated rats, and demonstrates correlations between specific genes and tissue structures that can augment interpretation of biological observations and diagnosis.

  8. Evidence, from combined segregation and linkage analysis, that a variant of the angiotensin I-converting enzyme (ACE) gene controls plasma ACE levels.

    PubMed Central

    Tiret, L; Rigat, B; Visvikis, S; Breda, C; Corvol, P; Cambien, F; Soubrier, F

    1992-01-01

    The hypothesis of a genetic control of plasma angiotensin I-converting enzyme (ACE) level has been suggested both by segregation analysis and by the identification of an insertion/deletion (I/D) polymorphism of the ACE gene, a polymorphism contributing much to the variability of ACE level. To elucidate whether the I/D polymorphism was directly involved in the genetic regulation, plasma ACE activity and genotype for the I/D polymorphism were both measured in a sample of 98 healthy nuclear families. The pattern of familial correlations of ACE level was compatible with a zero correlation between spouses and equal parent-offspring and sib-sib correlations (.24 +/- .04). A segregation analysis indicated that this familial resemblance could be entirely explained by the transmission of a codominant major gene. The I/D polymorphism was associated with marked differences of ACE levels, although these differences were less pronounced than those observed in the segregation analysis. After adjustment for the polymorphism effects, the residual heritability (.280 +/- .096) was significant. Finally, a combined segregation and linkage analysis provided evidence that the major-gene effect was due to a variant of the ACE gene, in strong linkage disequilibrium with the I/D polymorphism. The marker allele I appeared always associated with the major-gene allele s characterized by lower ACE levels. The frequency of allele I was .431 +/- .025, and that of major allele s was .557 +/- .041. The major gene had codominant effects equal to 1.3 residual SDs and accounted for 44% of the total variability of ACE level, as compared with 28% for the I/D polymorphism.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:1319114

  9. Combined neuroimaging and gene expression analysis of the genetic basis of brain plasticity indicates across species homology.

    PubMed

    Dinai, Yonatan; Wolf, Lior; Assaf, Yaniv

    2014-12-01

    Brain plasticity and memory formation depend on the expression of a large number of genes. This relationship had been studied using several experimental approaches and researchers have identified genes regulating plasticity through a variety of mechanisms. Despite this effort, a great deal remains unknown regarding the role of different genes in brain plasticity. Previous studies usually focused on specific brain structures and many of the genes influencing plasticity have yet to be identified. In this work, we integrate results of in vivo neuroimaging studies of plasticity with whole-brain gene expression data for the study of neuroplasticity. Brain regions, found in the imaging study to be involved in plasticity, are first spatially mapped to the anatomical framework of the genetic database. Feature ranking methods are then applied to identify genes that are differentially expressed in these regions. We find that many of our highly ranked genes are involved in synaptic transmission and that some of these genes have been previously associated with learning and memory. We show these results to be consistent when applying our method to gene expression data from four human subjects. Finally, by performing similar experiments in mice, we reveal significant cross species correlation in the ranking of genes. In addition to the identification of plasticity related candidate genes, our results also demonstrate the potential of data integration approaches as a tool to link high level phenomena such as learning and memory to underlying molecular mechanisms. © 2014 Wiley Periodicals, Inc.

  10. Toward Identification of Black Lemma and Pericarp Gene Blp1 in Barley Combining Bulked Segregant Analysis and Specific-Locus Amplified Fragment Sequencing

    PubMed Central

    Jia, Qiaojun; Wang, Junmei; Zhu, Jinghuan; Hua, Wei; Shang, Yi; Yang, Jianming; Liang, Zongsuo

    2017-01-01

    Black barley is caused by phytomelanin synthesized in lemma and/or pericarp and the trait is controlled by one dominant gene Blp1. The gene is mapped on chromosome 1H by molecular markers, but it is yet to be isolated. Specific-locus amplified fragment sequencing (SLAF-seq) is an effective method for large-scale de novo single nucleotide polymorphism (SNP) discovery and genotyping. In the present study, SLAF-seq with bulked segregant analysis (BSA) was employed to obtain sufficient markers to fine mapping Blp1 gene in an F2 population derived from Hatiexi No.1 × Zhe5819. Based on SNP screening criteria, a total of 77,542 polymorphic SNPs met the requirements for association analysis. Combining two association analysis methods, the overlapped region with a size of 32.41 Mb on chromosome 1H was obtained as the candidate region of Blp1 gene. According to SLAF-seq data, markers were developed in the target region and were used for mapping the Blp1 gene. Linkage analysis showed that Blp1 co-segregated with HZSNP34 and HZSNP36, and was delimited by two markers (HZSNP35 and HZSNP39) spanning 8.1 cM in 172 homozygous yellow grain F2 plants of Hatiexi No.1 × Zhe5819. More polymorphic markers were screened in the reduced target region and were used to genotype the population. As a result, Blp1 was delimited within a 1.66 Mb on chromosome 1H by the upstream marker HZSNP63 and the downstream marker HZSNP59. Our results demonstrated the utility of SLAF-seq-BSA approach to identify the candidate region and discover polymorphic markers at the specific targeted genomic region. PMID:28855914

  11. Combinations of Histone Modifications for Pattern Genes.

    PubMed

    Cui, Xiang-Jun; Shi, Chen-Xia

    2016-06-01

    Histone post-translational modifications play important roles in transcriptional regulation. It is known that multiple histone modifications can act in a combinatorial manner. In this study, we investigated the effects of multiple histone modifications on expression levels of five gene categories (four kinds of pattern genes and non-pattern genes) in coding regions. The combinatorial patterns of modifications for the five gene categories were also studied in the regions. Our results indicated that the differences in the expression levels between any two gene categories were significant. There were some corresponding differences in multiple histone modification levels among the five gene categories. Multiple histone modifications jointly impacted expression levels of every gene category. Four mutual combinations of histone modifications were found and analyzed.

  12. Gene × Physical Activity Interactions in Obesity: Combined Analysis of 111,421 Individuals of European Ancestry

    PubMed Central

    Ahmad, Shafqat; Rukh, Gull; Varga, Tibor V.; Ali, Ashfaq; Kurbasic, Azra; Shungin, Dmitry; Ericson, Ulrika; Koivula, Robert W.; Chu, Audrey Y.; Rose, Lynda M.; Ganna, Andrea; Qi, Qibin; Stančáková, Alena; Sandholt, Camilla H.; Elks, Cathy E.; Curhan, Gary; Jensen, Majken K.; Tamimi, Rulla M.; Allin, Kristine H.; Jørgensen, Torben; Brage, Soren; Langenberg, Claudia; Aadahl, Mette; Grarup, Niels; Linneberg, Allan; Paré, Guillaume; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Boehnke, Michael; Hamsten, Anders; Mohlke, Karen L.; Pasquale, Louis T.; Pedersen, Oluf; Scott, Robert A.; Ridker, Paul M.; Ingelsson, Erik; Laakso, Markku; Hansen, Torben; Qi, Lu; Wareham, Nicholas J.; Chasman, Daniel I.; Hallmans, Göran; Hu, Frank B.; Renström, Frida; Orho-Melander, Marju; Franks, Paul W.

    2013-01-01

    Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age2, sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction = 0.014 vs. n = 71,611, Pinteraction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction = 0.003) and the SEC16B rs10913469 (Pinteraction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal. PMID:23935507

  13. Gene × physical activity interactions in obesity: combined analysis of 111,421 individuals of European ancestry.

    PubMed

    Ahmad, Shafqat; Rukh, Gull; Varga, Tibor V; Ali, Ashfaq; Kurbasic, Azra; Shungin, Dmitry; Ericson, Ulrika; Koivula, Robert W; Chu, Audrey Y; Rose, Lynda M; Ganna, Andrea; Qi, Qibin; Stančáková, Alena; Sandholt, Camilla H; Elks, Cathy E; Curhan, Gary; Jensen, Majken K; Tamimi, Rulla M; Allin, Kristine H; Jørgensen, Torben; Brage, Soren; Langenberg, Claudia; Aadahl, Mette; Grarup, Niels; Linneberg, Allan; Paré, Guillaume; Magnusson, Patrik K E; Pedersen, Nancy L; Boehnke, Michael; Hamsten, Anders; Mohlke, Karen L; Pasquale, Louis T; Pedersen, Oluf; Scott, Robert A; Ridker, Paul M; Ingelsson, Erik; Laakso, Markku; Hansen, Torben; Qi, Lu; Wareham, Nicholas J; Chasman, Daniel I; Hallmans, Göran; Hu, Frank B; Renström, Frida; Orho-Melander, Marju; Franks, Paul W

    2013-01-01

    Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age(2), sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction  = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction  = 0.014 vs. n = 71,611, Pinteraction  = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction  = 0.003) and the SEC16B rs10913469 (Pinteraction  = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.

  14. Which breast carcinomas need HER-2/neu gene study after immunohistochemical analysis? Results of combined use of antibodies against different c-erbB2 protein domains.

    PubMed

    Sapino, A; Coccorullo, Z; Cassoni, P; Ghisolfi, G; Gugliotta, P; Bongiovanni, M; Arisio, R; Crafa, P; Bussolati, G

    2003-10-01

    Evaluation of HER2 gene amplification in breast cancers is a compelling, routine procedure. The aim of this work was to evaluate which breast carcinomas would really benefit from HER-2/neu gene analysis. We studied 130 invasive breast carcinomas by immunohistochemistry (IHC) using CB11 and TAB250 MAbs directed against different domains of the c-erbB2 molecule. From this series, we selected 106 cases (32 G1, 36 G2, and 38 G3) in which HER-2/neu gene analysis, using chromogenic in-situ hybridization (CISH), was successful. IHC results were scored using the FDA approved system with three score values: 0/1+ (negative), 2+, 3+ (positive). In addition, we developed a double scoring system with six score values (0/1+ 2+ negative, 3+, 4+, 5+, 6+ positive) obtained by summating the individual scoring values obtained with each MAb. All double scoring negative cases were non-amplified (100% sensitivity), whereas all cases scored 6+ were amplified. Double scoring values and CISH results were then correlated with grade and histological type. G1 ductal carcinomas and carcinomas of lobular and of special histological type did not show HER-2/neu amplification even in the presence of protein over-expression. The combined results of IHC analysis (double scoring values) obtained using MAbs directed against different c-erbB2 domains correctly indicates the HER-2/neu gene status in 57.5% of cases. In addition, simple morphological features such as low grade and special histological type are good predictors of the non-amplification of the HER-2/neu gene in breast carcinoma.

  15. PRISMA-combined Myeloperoxidase -463G/A gene polymorphism and coronary artery disease: A meta-analysis of 4744 subjects.

    PubMed

    Li, Yan-Yan; Wang, Hui; Qian, Jin; Kim, Hyun Jun; Wu, Jing-Jing; Wang, Lian-Sheng; Zhou, Chuan-Wei; Yang, Zhi-Jian; Lu, Xin-Zheng

    2017-03-01

    Myeloperoxidase (MPO) -463G/A gene polymorphism may be associated with an increased risk of developing coronary artery disease (CAD). Studies on the subject, however, do not provide a clear consensus. This meta-analysis was performed to explore the relationship between MPO gene -463G/A polymorphism and CAD risk. This meta-analysis combines data from 4744 subjects from 9 independent studies. By using fixed or random effect models, the pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were assessed. Our analysis found a significant association between MPO gene -463G/A polymorphism and CAD in the whole population under all genetic models: allelic (OR: 0.68, 95% CI: 0.54-0.85, P = 0.0009), recessive (OR: 0.41, 95% CI: 0.22-0.76, P = 0.005), dominant (OR: 0.682, 95% CI: 0.534-0.871, P = 0.002), homozygous (OR: 0.36, 95% CI: 0.16-0.79, P = 0.01), heterozygous genetic model (OR: 0.832, 95% CI: 0.733-0.945, P = 0.004), and additive (OR: 0.64, 95% CI: 0.46-0.90, P = 0.01), especially in the Chinese subgroup (P < 0.05). On the contrary, we found no such relationship in the non-Chinese subgroup (P > 0.05). The MPO gene -463G/A polymorphism is associated with CAD risk, especially within the Chinese population. The A allele of MPO gene -463G/A polymorphism might protect the people from suffering the CAD risk.

  16. Candidate Gene Analysis of Tooth Agenesis Identifies Novel Mutations in Six Genes and Suggests Significant Role for WNT and EDA Signaling and Allele Combinations

    PubMed Central

    Arte, Sirpa; Parmanen, Satu; Pirinen, Sinikka; Alaluusua, Satu; Nieminen, Pekka

    2013-01-01

    Failure to develop complete dentition, tooth agenesis, is a common developmental anomaly manifested most often as isolated but also as associated with many developmental syndromes. It typically affects third molars or one or few other permanent teeth but severe agenesis is also relatively prevalent. Here we report mutational analyses of seven candidate genes in a cohort of 127 probands with non-syndromic tooth agenesis. 82 lacked more than five permanent teeth excluding third molars, called as oligodontia. We identified 28 mutations, 17 of which were novel. Together with our previous reports, we have identified two mutations in MSX1, AXIN2 and EDARADD, five in PAX9, four in EDA and EDAR, and nine in WNT10A. They were observed in 58 probands (44%), with a mean number of missing teeth of 11.7 (range 4 to 34). Almost all of these probands had severe agenesis. Only few of the probands but several relatives with heterozygous genotypes of WNT10A or EDAR conformed to the common type of non-syndromic tooth agenesis, incisor-premolar hypodontia. Mutations in MSX1 and PAX9 affected predominantly posterior teeth, whereas both deciduous and permanent incisors were especially sensitive to mutations in EDA and EDAR. Many mutations in EDAR, EDARADD and WNT10A were present in several families. Biallelic or heterozygous genotypes of WNT10A were observed in 32 and hemizygous or heterozygous genotypes of EDA, EDAR or EDARADD in 22 probands. An EDARADD variant were in seven probands present together with variants in EDAR or WNT10A, suggesting combined phenotypic effects of alleles in distinct genes. PMID:23991204

  17. Candidate gene analysis of tooth agenesis identifies novel mutations in six genes and suggests significant role for WNT and EDA signaling and allele combinations.

    PubMed

    Arte, Sirpa; Parmanen, Satu; Pirinen, Sinikka; Alaluusua, Satu; Nieminen, Pekka

    2013-01-01

    Failure to develop complete dentition, tooth agenesis, is a common developmental anomaly manifested most often as isolated but also as associated with many developmental syndromes. It typically affects third molars or one or few other permanent teeth but severe agenesis is also relatively prevalent. Here we report mutational analyses of seven candidate genes in a cohort of 127 probands with non-syndromic tooth agenesis. 82 lacked more than five permanent teeth excluding third molars, called as oligodontia. We identified 28 mutations, 17 of which were novel. Together with our previous reports, we have identified two mutations in MSX1, AXIN2 and EDARADD, five in PAX9, four in EDA and EDAR, and nine in WNT10A. They were observed in 58 probands (44%), with a mean number of missing teeth of 11.7 (range 4 to 34). Almost all of these probands had severe agenesis. Only few of the probands but several relatives with heterozygous genotypes of WNT10A or EDAR conformed to the common type of non-syndromic tooth agenesis, incisor-premolar hypodontia. Mutations in MSX1 and PAX9 affected predominantly posterior teeth, whereas both deciduous and permanent incisors were especially sensitive to mutations in EDA and EDAR. Many mutations in EDAR, EDARADD and WNT10A were present in several families. Biallelic or heterozygous genotypes of WNT10A were observed in 32 and hemizygous or heterozygous genotypes of EDA, EDAR or EDARADD in 22 probands. An EDARADD variant were in seven probands present together with variants in EDAR or WNT10A, suggesting combined phenotypic effects of alleles in distinct genes.

  18. A Streamlined Protocol for Molecular Testing of the DMD Gene within a Diagnostic Laboratory: A Combination of Array Comparative Genomic Hybridization and Bidirectional Sequence Analysis

    PubMed Central

    Marquis-Nicholson, Renate; Lai, Daniel; Love, Jennifer M.; Love, Donald R.

    2013-01-01

    Purpose. The aim of this study was to develop a streamlined mutation screening protocol for the DMD gene in order to confirm a clinical diagnosis of Duchenne or Becker muscular dystrophy in affected males and to clarify the carrier status of female family members. Methods. Sequence analysis and array comparative genomic hybridization (aCGH) were used to identify mutations in the dystrophin DMD gene. We analysed genomic DNA from six individuals with a range of previously characterised mutations and from eight individuals who had not previously undergone any form of molecular analysis. Results. We successfully identified the known mutations in all six patients. A molecular diagnosis was also made in three of the four patients with a clinical diagnosis who had not undergone prior genetic screening, and testing for familial mutations was successfully completed for the remaining four patients. Conclusion. The mutation screening protocol described here meets best practice guidelines for molecular testing of the DMD gene in a diagnostic laboratory. The aCGH method is a superior alternative to more conventional assays such as multiplex ligation-dependent probe amplification (MLPA). The combination of aCGH and sequence analysis will detect mutations in 98% of patients with the Duchenne or Becker muscular dystrophy. PMID:23476807

  19. Rounding up active cis-elements in the triple C corral: combining conservation, cleavage and conformation capture for the analysis of regulatory gene domains.

    PubMed

    McBride, David J; Kleinjan, Dirk A

    2004-11-01

    Identification and functional analysis of potential cis-regulatory elements is a laborious process that often depends on removing putative elements from their natural context to study their activity. While such methods provide valuable information about the isolated element, they disregard the potential role of an element's interaction(s) with other regulatory sequences and the three-dimensional structure of an active gene locus. Here, two novel methods are discussed--chromosome conformation capture (3C) and RNA-TRAP--that can be used to detect interactions between distal regulatory sites and which thus indicate the chromosomal conformation that is adopted by a gene locus in various states of transcriptional activity. Combined with comparative genomics and traditional DNase I hypersensitive site mapping, these methods form a powerful approach for the study of the mechanisms of long-range transcriptional regulation.

  20. Expression, SNV identification, linkage disequilibrium, and combined genotype association analysis of the muscle-specific gene CSRP3 in Chinese cattle.

    PubMed

    He, Hua; Zhang, Hui-Lin; Li, Zhi-Xiong; Liu, Yu; Liu, Xiao-Lin

    2014-02-01

    The cysteine and glycine-rich protein 3 (CSRP3) plays an important role in the myofiber differentiation. Here, we identified five SNVs in all exon and intron regions of the CSRP3 gene using DNA sequencing, PCR-RFLP and forced-PCR-RFLP methods in 554 cattle. Four of the five SNVs were significantly associated with growth performance and carcass traits of the cattle. In addition, we evaluated haplotype frequency and linkage disequilibrium coefficient of five sequence variants. The result of haplotype analysis demonstrated 28 haplotypes present in Qinchuan and two haplotypes in Chinese Holstein. Only haplotypes 1 and 8 were being shared by two populations, haplotype 14 had the highest haplotype frequency in Qinchuan (17.4%) and haplotype 8 had the highest haplotype frequency in Chinese Holstein (94.4%). Statistical analyses of combined genotypes indicated that some combined genotypes were significantly or highly significantly associated with growth and carcass traits in the Qinchuan cattle population. qPCR analyses also showed that bovine CSRP3 gene was exclusively expressed in longissimus dorsi muscle and heart tissues. The data support the high potential of the CSRP3 as a marker gene for the improvement of growth performance and carcass traits in selection programs. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Gene Expression Changes Triggered by Exposure of Haemophilus influenzae to Novobiocin or Ciprofloxacin: Combined Transcription and Translation Analysis

    PubMed Central

    Gmuender, Hans; Kuratli, Karin; Di Padova, Karin; Gray, Christopher P.; Keck, Wolfgang; Evers, Stefan

    2001-01-01

    The responses of Haemophilus influenzae to DNA gyrase inhibitors were analyzed at the transcriptional and the translational level. High-density microarrays based on the genomic sequence were used to monitor the expression levels of >80% of the genes in this bacterium. In parallel the proteins were analyzed by two-dimensional electrophoresis. DNA gyrase inhibitors of two different functional classes were used. Novobiocin, as a representative of one class, inhibits the ATPase activity of the enzyme, thereby indirectly changing the degree of DNA supercoiling. Ciprofloxacin, a representative of the second class, obstructs supercoiling by inhibiting the DNA cleavage-resealing reaction. Our results clearly show that different responses can be observed. Treatment with the ATPase inhibitor Novobiocin changed the expression rates of many genes, reflecting the fact that the initiation of transcription for many genes is sensitive to DNA supercoiling. Ciprofloxacin mainly stimulated the expression of DNA repair systems as a response to the DNA damage caused by the stable ternary complexes. In addition, changed expression levels were also observed for some genes coding for proteins either annotated as “unknown function” or “hypothetical” or for proteins not directly involved in DNA topology or repair. [The sequence data described in this paper have been submitted to the EMBL data library under accession nos. AJ297131 and AL135960.] PMID:11156613

  2. Establishment of Functional Genomics Pipeline in Epiblast-Like Tissue by Combining Transcriptomic Analysis and Gene Knockdown/Knockin/Knockout, Using RNA Interference and CRISPR/Cas9.

    PubMed

    Takata, Nozomu; Sakakura, Eriko; Kasukawa, Takeya; Sakuma, Tetsushi; Yamamoto, Takashi; Sasai, Yoshiki

    2016-06-01

    The epiblast (foremost embryonic ectoderm) generates all three germ layers and therefore has crucial roles in the formation of all mammalian body cells. However, regulation of epiblast gene expression is poorly understood because of the difficulty of manipulating epiblast tissues in vivo. In the present study, using the self-organizing properties of embryonic stem cell (ESC), we generated and characterized epiblast-like tissue in three-dimensional culture. We identified significant genome-wide gene expression changes in this epiblast-like tissue by transcriptomic analysis. In addition, we identified the particular significance of the Erk/Mapk and integrin-linked kinase pathways, and genes related to ectoderm/epithelial formation, using the bioinformatics resources IPA and DAVID. Here, we focused on Fgf5, which ranked in the top 10 among the discovered genes. To develop a functional analysis of Fgf5, we created an efficient method combining CRISPR/Cas9-mediated genome engineering and RNA interference (RNAi). Notably, we show one-step generation of various Fgf5 reporter lines including heterozygous and homozygous knockins (the GET method). For time- and dose-dependent depletion of fgf5 over the course of development, we generated an ESC line harboring Tol2 transposon-mediated integration of an inducible short hairpin RNA interference system (pdiRNAi). Our findings raised the possibility that Fgf/Erk signaling and apicobasal epithelial integrity are important factors in epiblast development. In addition, our methods provide a framework for a broad array of applications in the areas of mammalian genetics and molecular biology to understand development and to improve future therapeutics.

  3. Combining Genotype, Phenotype, and Environment to Infer Potential Candidate Genes.

    PubMed

    Talbot, Benoit; Chen, Ting-Wen; Zimmerman, Shawna; Joost, Stéphane; Eckert, Andrew J; Crow, Taylor M; Semizer-Cuming, Devrim; Seshadri, Chitra; Manel, Stéphanie

    2017-03-01

    Population genomic analysis can be an important tool in understanding local adaptation. Identification of potential adaptive loci in such analyses is usually based on the survey of a large genomic dataset in combination with environmental variables. Phenotypic data are less commonly incorporated into such studies, although combining a genome scan analysis with a phenotypic trait analysis can greatly improve the insights obtained from each analysis individually. Here, we aimed to identify loci potentially involved in adaptation to climate in 283 Loblolly pine (Pinus taeda) samples from throughout the species' range in the southeastern United States. We analyzed associations between phenotypic, molecular, and environmental variables from datasets of 3082 single nucleotide polymorphism (SNP) loci and 3 categories of phenotypic traits (gene expression, metabolites, and whole-plant traits). We found only 6 SNP loci that displayed potential signals of local adaptation. Five of the 6 identified SNPs are linked to gene expression traits for lignin development, and 1 is linked with whole-plant traits. We subsequently compared the 6 candidate genes with environmental variables and found a high correlation in only 3 of them (R2 > 0.2). Our study highlights the need for a combination of genotypes, phenotypes, and environmental variables, and for an appropriate sampling scheme and study design, to improve confidence in the identification of potential candidate genes. © The American Genetic Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  4. Microarray gene expression analysis of chemosensitivity for docetaxel, cisplatin and 5-fluorouracil (TPF) combined chemotherapeutic regimen in hypopharyngeal squamous cell carcinoma.

    PubMed

    Lian, Meng; Wang, Haizhou; Fang, Jugao; Zhai, Jie; Wang, Ru; Shen, Xixi; Yang, Yifan; Ma, Zhihong; Liu, Honggang

    2017-06-01

    To screen out a set of candidate genes which could help to determine whether patients with hypopharyngeal squamous cell carcinoma (HSCC) could benefit from docetaxel, cisplatin and 5-fluorouracil (TPF) induction chemotherapy. Gene-expression profiles in 12 TPF-sensitive patients were compared to 9 resistant controls by microarray analysis. Subsequently, expression levels of potential biomarkers in chemosensitive cell line FaDu after TPF treatment were observed by quantitative real-time polymerase chain reaction (qRT-PCR). Through microarray analysis, 1,579 differentially expressed genes were identified, of which 815 were up-regulated in TPF chemotherapy-responsive tissues whereas 764 were down-regulated. Gene ontology (GO) analysis suggested these genes participating in physiological processes including transcription and its regulation, cellular signal transduction and metabolic process. Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) database revealed that MAPK and Jat/STAT signaling pathways occupied important roles in TPF chemotherapeutic sensitivity. Moreover, in vitro cell culture experiments revealed the expression alternations of IL-6, MAPK14, JUN, CDK5 and CAMK2A exposed to TPF treatment by qRT-PCR, whilst providing an insight into the mechanism underlying TPF chemotherapeutic response in HSCC. These results provided a battery of genes related to TPF chemotherapeutic sensitivity and might act as molecular targets in HSCC treatment. Moreover, these candidate biomarkers could contribute to HSCC individualized treatment.

  5. Gene expression analysis in the roots of salt-stressed wheat and the cytogenetic derivatives of wheat combined with the salt-tolerant wheatgrass, Lophopyrum elongatum.

    PubMed

    Hussein, Zina; Dryanova, Ani; Maret, Deborah; Gulick, Patrick J

    2014-01-01

    Using microarray analysis, we identified regulatory and signaling-related genes with differential expression in three genotypes with varying degrees of salt tolerance, Triticum aestivum , the amphiploid, and the wheat substitution line DS3E(3A). Lophopyrum elongatum is among one of the most salt-tolerant members of the Triticeae; important genetic stocks developed from crosses between wheat and L. elongatum provide a unique opportunity to compare gene expression in response to salt stress between these highly related species. The octaploid amphiploid contains the entire genome of T. aestivum and L. elongatum, and the disomic substitution line DS3E(3A) has chromosome 3A of wheat replaced by chromosome 3E of L. elongatum. In this study, microarray analysis was used to characterize gene expression profiles in the roots of three genotypes, Triticum aestivum, the octaploid amphiploid, and the wheat DS3E(3A) substitution line, in response to salt stress. We first examined changes in gene expression in wheat over a time course of 3 days of salt stress, and then compared changes in gene expression in wheat, the T. aestivum × L. elongatum amphiploid, and in the DS3E(3A) substitution line after 3 days of salt stress. In the time course experiment, 237 genes had 1.5 fold or greater change at least one out of three time points assayed in the experiment. The comparison between the three genotypes revealed 304 genes with significant differences in changes of expression between the genotypes. Forty-two of these genes had at least a twofold change in expression in response to salt treatment; 18 of these genes have signaling or regulatory function. Genes with significant differences in induction or repression between genotypes included transcription factors, protein kinases, ubiquitin ligases and genes related to phospholipid signaling.

  6. Gene expression analysis of bovine oocytes at optimal coasting time combined with GnRH antagonist during the no-FSH period.

    PubMed

    Labrecque, Rémi; Vigneault, Christian; Blondin, Patrick; Sirard, Marc-André

    2014-05-01

    Ovarian stimulation with FSH combined with an appropriate period of FSH withdrawal (coasting) before ovum pick-up now appears to be a successful way to obtain oocytes with high developmental competence in bovine. Recent results showed that extending follicular growth by only 24 hours has a detrimental effect on oocyte quality as shown by the reduced blastocyst formation rate. Although these treatments are initiated during the luteal phase with low LH level, the small LH pulsatility present at that time could potentially impact follicular development as well as oocyte quality. In this study, a GnRH antagonist (Cetrotide) was used to suppress LH secretion during follicular differentiation to get a better insight into the physiological importance of the LH support during that period. Oocytes were collected by ovum pick-up, and quality was assessed by measuring the blastocyst formation rate obtained after IVM-IVF. The oocyte transcriptome from GnRH antagonist-treated animals was also compared with that from a control group (coasting duration of 68 hours) to detect possible alterations at the messenger RNA (mRNA) level. The oocyte quality was not statistically affected by the treatment as shown by the blastocyst formation rate obtained. However, microarray analysis showed that a total of 226 genes had a significant difference (fold change > 2; P < 0.05) at the mRNA level, with the majority being in overabundance in the treated group. Many genes related to RNA posttranscriptional modifications presented different abundance at the mRNA level significant differences in the control group (68 hours), whereas translation function appeared to be affected, with many genes related to structural constituents of the ribosome presenting a overabundance in the GnRH antagonist-treated group. Specific mRNAs with crucial roles in chromosome segregation control also showed significant difference at the mRNA level after Cetrotide treatment. The results presented here indicated that the

  7. Combined magnetic and gravity analysis

    NASA Technical Reports Server (NTRS)

    Hinze, W. J.; Braile, L. W.; Chandler, V. W.; Mazella, F. E.

    1975-01-01

    Efforts are made to identify methods of decreasing magnetic interpretation ambiguity by combined gravity and magnetic analysis, to evaluate these techniques in a preliminary manner, to consider the geologic and geophysical implications of correlation, and to recommend a course of action to evaluate methods of correlating gravity and magnetic anomalies. The major thrust of the study was a search and review of the literature. The literature of geophysics, geology, geography, and statistics was searched for articles dealing with spatial correlation of independent variables. An annotated bibliography referencing the Germane articles and books is presented. The methods of combined gravity and magnetic analysis techniques are identified and reviewed. A more comprehensive evaluation of two types of techniques is presented. Internal correspondence of anomaly amplitudes is examined and a combined analysis is done utilizing Poisson's theorem. The geologic and geophysical implications of gravity and magnetic correlation based on both theoretical and empirical relationships are discussed.

  8. Suppression subtractive hybridization (SSH) combined with bioinformatics method: an integrated functional annotation approach for analysis of differentially expressed immune-genes in insects.

    PubMed

    Badapanda, Chandan

    2013-01-01

    The suppression subtractive hybridization (SSH) approach, a PCR based approach which amplifies differentially expressed cDNAs (complementary DNAs), while simultaneously suppressing amplification of common cDNAs, was employed to identify immuneinducible genes in insects. This technique has been used as a suitable tool for experimental identification of novel genes in eukaryotes as well as prokaryotes; whose genomes have been sequenced, or the species whose genomes have yet to be sequenced. In this article, I have proposed a method for in silico functional characterization of immune-inducible genes from insects. Apart from immune-inducible genes from insects, this method can be applied for the analysis of genes from other species, starting from bacteria to plants and animals. This article is provided with a background of SSH-based method taking specific examples from innate immune-inducible genes in insects, and subsequently a bioinformatics pipeline is proposed for functional characterization of newly sequenced genes. The proposed workflow presented here, can also be applied for any newly sequenced species generated from Next Generation Sequencing (NGS) platforms.

  9. [Differential gene expression in incompatible interaction between Lilium regale Wilson and Fusarium oxysporum f. sp. lilii revealed by combined SSH and microarray analysis].

    PubMed

    Rao, J; Liu, D; Zhang, N; He, H; Ge, F; Chen, C

    2014-01-01

    Fusarium wilt, caused by a soilborne pathogen Fusarium oxysporum f. sp. lilii, is the major disease of lily (Lilium L.). In order to isolate the genes differentially expressed in a resistant reaction to F. oxysporum in L. regale Wilson, a cDNA library was constructed with L. regale root during F. oxysporum infection using the suppression subtractive hybridization (SSH), and a total of 585 unique expressed sequence tags (ESTs) were obtained. Furthermore, the gene expression profiles in the incompatible interaction between L. regale and F. oxysporum were revealed by oligonucleotide microarray analysis of 585 unique ESTs comparison to the compatible interaction between a susceptible Lilium Oriental Hybrid 'Siberia' and F. oxysporum. The result of expression profile analysis indicated that the genes encoding pathogenesis-related proteins (PRs), antioxidative stress enzymes, secondary metabolism enzymes, transcription factors, signal transduction proteins as well as a large number of unknown genes were involved in early defense response of L. regale to F. oxysporum infection. Moreover, the following quantitative reverse transcription PCR (QRT-PCR) analysis confirmed reliability of the oligonucleotide microarray data. In the present study, isolation of differentially expressed genes in L. regale during response to F. oxysporum helped to uncover the molecular mechanism associated with the resistance of L. regale against F. oxysporum.

  10. Use of meta-analysis to combine candidate gene association studies: application to study the relationship between the ESR PvuII polymorphism and sow litter size

    PubMed Central

    Alfonso, Leopoldo

    2005-01-01

    This article investigates the application of meta-analysis on livestock candidate gene effects. The PvuII polymorphism of the ESR gene is used as an example. The association among ESR PvuII alleles with the number of piglets born alive and total born in the first (NBA1, TNB1) and later parities (NBA, TNB) is reviewed by conducting a meta-analysis of 15 published studies including 9329 sows. Under a fixed effects model, litter size values were significantly lower in the "AA" genotype groups when compared with "AB" and "BB" homozygotes. Under the random effects model, the results were similar although differences between "AA" and "AB" genotype groups were not clearly significant for NBA and TNB. Nevertheless, the most noticeable result was the high and significant heterogeneity estimated among studies. This heterogeneity could be assigned to error sampling, genotype by environment interaction, linkage or epistasis, as referred to in the literature, but also to the hypothesis of population admixture/stratification. It is concluded that meta-analysis can be considered as a helpful analytical tool to synthesise and discuss livestock candidate gene effects. The main difficulty found was the insufficient information on the standard errors of the estimated genotype effects in several publications. Consequently, the convenience of publishing the standard errors or the concrete P-values instead of the test significance level should be recommended to guarantee the quality of candidate gene effect meta-analyses. PMID:15943920

  11. Citrate Accumulation-Related Gene Expression and/or Enzyme Activity Analysis Combined With Metabolomics Provide a Novel Insight for an Orange Mutant

    PubMed Central

    Guo, Ling-Xia; Shi, Cai-Yun; Liu, Xiao; Ning, Dong-Yuan; Jing, Long-Fei; Yang, Huan; Liu, Yong-Zhong

    2016-01-01

    ‘Hong Anliu’ (HAL, Citrus sinensis cv. Hong Anliu) is a bud mutant of ‘Anliu’ (AL), characterized by a comprehensive metabolite alteration, such as lower accumulation of citrate, high accumulation of lycopene and soluble sugars in fruit juice sacs. Due to carboxylic acid metabolism connects other metabolite biosynthesis and/or catabolism networks, we therefore focused analyzing citrate accumulation-related gene expression profiles and/or enzyme activities, along with metabolic fingerprinting between ‘HAL’ and ‘AL’. Compared with ‘AL’, the transcript levels of citrate biosynthesis- and utilization-related genes and/or the activities of their respective enzymes such as citrate synthase, cytosol aconitase and ATP-citrate lyase were significantly higher in ‘HAL’. Nevertheless, the mitochondrial aconitase activity, the gene transcript levels of proton pumps, including vacuolar H+-ATPase, vacuolar H+-PPase, and the juice sac-predominant p-type proton pump gene (CsPH8) were significantly lower in ‘HAL’. These results implied that ‘HAL’ has higher abilities for citrate biosynthesis and utilization, but lower ability for the citrate uptake into vacuole compared with ‘AL’. Combined with the metabolites-analyzing results, a model was then established and suggested that the reduction in proton pump activity is the key factor for the low citrate accumulation and the comprehensive metabolite alterations as well in ‘HAL’. PMID:27385485

  12. A combination of genome-wide association and transcriptome analysis reveals candidate genes controlling harvest index-related traits in Brassica napus

    PubMed Central

    Lu, Kun; Xiao, Zhongchun; Jian, Hongju; Peng, Liu; Qu, Cunmin; Fu, Minglian; He, Bin; Tie, Linmei; Liang, Ying; Xu, Xingfu; Li, Jiana

    2016-01-01

    Harvest index (HI), the ratio of seed mass to total biomass of the aboveground plant parts, is an important trait for harvestable yield of crops. Unfortunately, HI of Brassica napus is lower than that of other economically important crops. To identify candidate genes associated with high HI, a genome-wide association study of HI and four HI-related traits was conducted with 520 B. napus accessions cultivated in both Yunnan and Chongqing. We detected 294 single nucleotide polymorphisms significantly associated with the abovementioned traits, including 79 SNPs that affected two or more traits. Differentially expressed genes between extremely high- and low-HI accessions were identified in 8 tissues at two cultivated regions. Combination of linkage disequilibrium and transcriptome analyses revealed 33 functional candidate genes located within the confidence intervals of significant SNPs associated with more than one trait, such as SHOOT GRAVITROPISM 5 (Bna.SGR5), ATP-CITRATE LYASE A-3 (Bna.ACLA-3) and CAROTENOID CLEAVAGE DIOXYGENASE 1 (Bna.CCD1), their orthologs in the Arabidopsis thaliana have been shown to play key roles in photosynthesis, inflorescence, and silique development. Our results provide insight into the molecular mechanisms underlying establishment of high-HI B. napus and lay a foundation for characterization of candidate genes aimed at developing high-HI B. napus varieties. PMID:27811979

  13. Combining Gene Signatures Improves Prediction of Breast Cancer Survival

    PubMed Central

    Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

    2011-01-01

    Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast

  14. COMBAT: A Combined Association Test for Genes Using Summary Statistics.

    PubMed

    Wang, Minghui; Huang, Jianfei; Liu, Yiyuan; Ma, Li; Potash, James B; Han, Shizhong

    2017-09-06

    Genome-wide association studies (GWAS) have been widely used for identifying common variants associated with complex diseases. Traditional analysis of GWAS typically examines one marker at a time, usually single nucleotide polymorphisms (SNPs), to identify individual variants associated with a disease. However, due to the small effect sizes of common variants, the power to detect individual risk variants is generally low. As a complementary approach to SNP-level analysis, a variety of gene-based association tests have been proposed. However, the power of existing gene-based tests is often dependent on the underlying genetic models, and it is not known a priori which test is optimal. Here we propose a combined association test (COMBAT) for genes, which incorporates strengths from existing gene-based tests and shows higher overall performance than any individual test. Our method does not require raw genotype or phenotype data, but needs only SNP-level p-values and correlations between SNPs from ancestry-matched samples. Extensive simulations showed that COMBAT has an appropriate type I error rate, maintains higher power across a wide range of genetic models, and is more robust than any individual gene-based test. We further demonstrated the superior performance of COMBAT over several other gene-based tests through reanalysis of the meta-analytic results of GWAS for bipolar disorder. Our method allows for the more powerful application of gene-based analysis to complex diseases, which will have broad use given that GWAS summary results are increasingly publicly available. Copyright © 2017, Genetics.

  15. Phylogenetic analysis of the nuclear alcohol dehydrogenase (Adh) gene family in Carex section Acrocystis (Cyperaceae) and combined analyses of Adh and nuclear ribosomal ITS and ETS sequences for inferring species relationships.

    PubMed

    Roalson, Eric H; Friar, Elizabeth A

    2004-12-01

    We analyzed sequence variation for the alcohol dehydrogenase (Adh) gene family in Carex section Acrocystis (Cyperaceae) to reconstruct Adh gene trees for Acrocystis species and to characterize the structure of the Adh gene family in Carex. Two Adh loci were included with ITS and ETS sequences in a combined Bayesian inference analysis of Carex section Acrocystis to gain a better understanding of species relationships in the section. In addition, we comment on how the results presented here contribute to our knowledge of the birth-death process of the Adh gene family in angiosperms. It appears that the structure of the Adh gene family in Carex is complex with possibly six loci present in the gene family. Additionally, variation among Acrocystis species within loci is quite low, and there is little phylogenetic resolution in the individual datasets. Bayesian inference analysis of the combined ITS, ETS, Adh1, and Adh2 datasets resulted in a moderately well-supported phylogenetic hypothesis of relationships in the section which is discussed in relation to previous hypotheses of relationships.

  16. A combination of PhP typing and β-d-glucuronidase gene sequence variation analysis for differentiation of Escherichia coli from humans and animals.

    PubMed

    Masters, N; Christie, M; Katouli, M; Stratton, H

    2015-06-01

    We investigated the usefulness of the β-d-glucuronidase gene variance in Escherichia coli as a microbial source tracking tool using a novel algorithm for comparison of sequences from a prescreened set of host-specific isolates using a high-resolution PhP typing method. A total of 65 common biochemical phenotypes belonging to 318 E. coli strains isolated from humans and domestic and wild animals were analysed for nucleotide variations at 10 loci along a 518 bp fragment of the 1812 bp β-d-glucuronidase gene. Neighbour-joining analysis of loci variations revealed 86 (76.8%) human isolates and 91.2% of animal isolates were correctly identified. Pairwise hierarchical clustering improved assignment; where 92 (82.1%) human and 204 (99%) animal strains were assigned to their respective cluster. Our data show that initial typing of isolates and selection of common types from different hosts prior to analysis of the β-d-glucuronidase gene sequence improves source identification. We also concluded that numerical profiling of the nucleotide variations can be used as a valuable approach to differentiate human from animal E. coli. This study signifies the usefulness of the β-d-glucuronidase gene as a marker for differentiating human faecal pollution from animal sources.

  17. Mapping of a Novel Race Specific Resistance Gene to Phytophthora Root Rot of Pepper (Capsicum annuum) Using Bulked Segregant Analysis Combined with Specific Length Amplified Fragment Sequencing Strategy

    PubMed Central

    Xu, Xiaomei; Chao, Juan; Cheng, Xueli; Wang, Rui; Sun, Baojuan; Wang, Hengming; Luo, Shaobo; Xu, Xiaowan; Wu, Tingquan; Li, Ying

    2016-01-01

    Phytophthora root rot caused by Phytophthora capsici (P. capsici) is a serious limitation to pepper production in Southern China, with high temperature and humidity. Mapping PRR resistance genes can provide linked DNA markers for breeding PRR resistant varieties by molecular marker-assisted selection (MAS). Two BC1 populations and an F2 population derived from a cross between P. capsici-resistant accession, Criollo de Morelos 334 (CM334) and P. capsici-susceptible accession, New Mexico Capsicum Accession 10399 (NMCA10399) were used to investigate the genetic characteristics of PRR resistance. PRR resistance to isolate Byl4 (race 3) was controlled by a single dominant gene, PhR10, that was mapped to an interval of 16.39Mb at the end of the long arm of chromosome 10. Integration of bulked segregant analysis (BSA) and Specific Length Amplified Fragment sequencing (SLAF-seq) provided an efficient genetic mapping strategy. Ten polymorphic Simple Sequence Repeat (SSR) markers were found within this region and used to screen the genotypes of 636 BC1 plants, delimiting PhR10 to a 2.57 Mb interval between markers P52-11-21 (1.5 cM away) and P52-11-41 (1.1 cM). A total of 163 genes were annotated within this region and 31 were predicted to be associated with disease resistance. PhR10 is a novel race specific gene for PRR, and this paper describes linked SSR markers suitable for marker-assisted selection of PRR resistant varieties, also laying a foundation for cloning the resistance gene. PMID:26992080

  18. Mapping of a Novel Race Specific Resistance Gene to Phytophthora Root Rot of Pepper (Capsicum annuum) Using Bulked Segregant Analysis Combined with Specific Length Amplified Fragment Sequencing Strategy.

    PubMed

    Xu, Xiaomei; Chao, Juan; Cheng, Xueli; Wang, Rui; Sun, Baojuan; Wang, Hengming; Luo, Shaobo; Xu, Xiaowan; Wu, Tingquan; Li, Ying

    2016-01-01

    Phytophthora root rot caused by Phytophthora capsici (P. capsici) is a serious limitation to pepper production in Southern China, with high temperature and humidity. Mapping PRR resistance genes can provide linked DNA markers for breeding PRR resistant varieties by molecular marker-assisted selection (MAS). Two BC1 populations and an F2 population derived from a cross between P. capsici-resistant accession, Criollo de Morelos 334 (CM334) and P. capsici-susceptible accession, New Mexico Capsicum Accession 10399 (NMCA10399) were used to investigate the genetic characteristics of PRR resistance. PRR resistance to isolate Byl4 (race 3) was controlled by a single dominant gene, PhR10, that was mapped to an interval of 16.39Mb at the end of the long arm of chromosome 10. Integration of bulked segregant analysis (BSA) and Specific Length Amplified Fragment sequencing (SLAF-seq) provided an efficient genetic mapping strategy. Ten polymorphic Simple Sequence Repeat (SSR) markers were found within this region and used to screen the genotypes of 636 BC1 plants, delimiting PhR10 to a 2.57 Mb interval between markers P52-11-21 (1.5 cM away) and P52-11-41 (1.1 cM). A total of 163 genes were annotated within this region and 31 were predicted to be associated with disease resistance. PhR10 is a novel race specific gene for PRR, and this paper describes linked SSR markers suitable for marker-assisted selection of PRR resistant varieties, also laying a foundation for cloning the resistance gene.

  19. Combining metabolomics and gene expression analysis reveals that propionyl- and butyryl-carnitines are involved in late stages of arbuscular mycorrhizal symbiosis.

    PubMed

    Laparre, Jérôme; Malbreil, Mathilde; Letisse, Fabien; Portais, Jean Charles; Roux, Christophe; Bécard, Guillaume; Puech-Pagès, Virginie

    2014-03-01

    The arbuscular mycorrhizal (AM) symbiosis is a widespread mutualistic association between soil fungi (Glomeromycota) and the roots of most plant species. AM fungi are obligate biotrophs whose development is partially under the control of their plant host. We explored the possibility to combine metabolomic and transcriptomic approaches to find putative mycorrhiza-associated metabolites regulating AM fungal development. Methanol extracts of Medicago truncatula roots colonized or not with the AM fungus Rhizophagus irregularis were analyzed and compared by ultra-high-performance liquid chromatography (UHPLC), high-resolution mass spectrometry (Q-TOF), and multivariate statistical discrimination. We detected 71 mycorrhiza-associated analytes exclusively present or at least 10-fold more abundant in mycorrhizal roots. To identify among these analytes those that could regulate AM fungal development, we fractionated by preparative and semi-preparative HPLC the mycorrhizal and non-mycorrhizal root extracts and established how the 71 analytes were distributed among the fractions. Then we tested the activity of the fractions on germinating spores of R. irregularis by quantifying the expression of 96 genes known for their diverse in planta expression patterns. These investigations reveal that propionyl- and butyryl-carnitines accumulated in mycorrhizal roots. The results suggest that these two molecules regulate fungal gene expression in planta and represent interesting candidates for further biological characterization.

  20. Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks

    PubMed Central

    2011-01-01

    Background Gene co-expression, in the form of a correlation coefficient, has been valuable in the analysis, classification and prediction of protein-protein interactions. However, it is susceptible to bias from a few samples having a large effect on the correlation coefficient. Gene co-expression stability is a means of quantifying this bias, with high stability indicating robust, unbiased co-expression correlation coefficients. We assess the utility of gene co-expression stability as an additional measure to support the co-expression correlation in the analysis of protein-protein interaction networks. Results We studied the patterns of co-expression correlation and stability in interacting proteins with respect to their interaction promiscuity, levels of intrinsic disorder, and essentiality or disease-relatedness. Co-expression stability, along with co-expression correlation, acts as a better classifier of hub proteins in interaction networks, than co-expression correlation alone, enabling the identification of a class of hubs that are functionally distinct from the widely accepted transient (date) and obligate (party) hubs. Proteins with high levels of intrinsic disorder have low co-expression correlation and high stability with their interaction partners suggesting their involvement in transient interactions, except for a small group that have high co-expression correlation and are typically subunits of stable complexes. Similar behavior was seen for disease-related and essential genes. Interacting proteins that are both disordered have higher co-expression stability than ordered protein pairs. Using co-expression correlation and stability, we found that transient interactions are more likely to occur between an ordered and a disordered protein while obligate interactions primarily occur between proteins that are either both ordered, or disordered. Conclusions We observe that co-expression stability shows distinct patterns in structurally and functionally

  1. Combining SNP discovery from next-generation sequencing data with bulked segregant analysis (BSA) to fine-map genes in polyploid wheat

    PubMed Central

    2012-01-01

    Background Next generation sequencing (NGS) technologies are providing new ways to accelerate fine-mapping and gene isolation in many species. To date, the majority of these efforts have focused on diploid organisms with readily available whole genome sequence information. In this study, as a proof of concept, we tested the use of NGS for SNP discovery in tetraploid wheat lines differing for the previously cloned grain protein content (GPC) gene GPC-B1. Bulked segregant analysis (BSA) was used to define a subset of putative SNPs within the candidate gene region, which were then used to fine-map GPC-B1. Results We used Illumina paired end technology to sequence mRNA (RNAseq) from near isogenic lines differing across a ~30-cM interval including the GPC-B1 locus. After discriminating for SNPs between the two homoeologous wheat genomes and additional quality filtering, we identified inter-varietal SNPs in wheat unigenes between the parental lines. The relative frequency of these SNPs was examined by RNAseq in two bulked samples made up of homozygous recombinant lines differing for their GPC phenotype. SNPs that were enriched at least 3-fold in the corresponding pool (6.5% of all SNPs) were further evaluated. Marker assays were designed for a subset of the enriched SNPs and mapped using DNA from individuals of each bulk. Thirty nine new SNP markers, corresponding to 67% of the validated SNPs, mapped across a 12.2-cM interval including GPC-B1. This translated to 1 SNP marker per 0.31 cM defining the GPC-B1 gene to within 13-18 genes in syntenic cereal genomes and to a 0.4 cM interval in wheat. Conclusions This study exemplifies the use of RNAseq for SNP discovery in polyploid species and supports the use of BSA as an effective way to target SNPs to specific genetic intervals to fine-map genes in unsequenced genomes. PMID:22280551

  2. Analysis of immune system gene expression in small rheumatoid arthritis biopsies using a combination of subtractive hybridization and high-density cDNA arrays.

    PubMed

    Zanders, E D; Goulden, M G; Kennedy, T C; Kempsell, K E

    2000-01-13

    Subtractive hybridization of cDNAs generated from synovial RNA which had been isolated from patients with rheumatoid arthritis (RA) or normal controls was used in conjunction with high-density array hybridization to identify genes of immunological interest. The method was designed to detect gene expression in small needle biopsy specimens by means of a prior amplification of nanogram amounts of total RNA to full-length cDNA using PCR. The latter was cut with Rsa I, ligated with adapters, hybridized with unmodified driver cDNA, and subjected to suppression subtraction PCR. Differentially expressed products were cloned into E. coli and picked into 384 well plates. Inserts were obtained by PCR across the multiple cloning site, and the products arrayed at high density on nylon filters. The subtracted cDNAs were also labelled by random priming for use as probes for library screening. The libraries chosen were the subtracted one described above and a set of 45,000 ESTs from the I.M. A.G.E consortium. Clones showing positive hybridization were identified by sequence analysis and homology searching. The results showed that the subtracted hybridization approach could identify many gene fragments expressed at different levels, the most abundant being immunoglobulins and HLA-DR. The expression profile was characteristic of macrophage, B cell and plasma cell infiltration with evidence of interferon induction. In addition, a significant number of sequences without matches in the nucleotide databases were obtained, this demonstrates the utility of the method in finding novel gene fragments for further characterisation as potential members of the immune system. Although RA was studied here, the technology is applicable to any disease process even in cases where amounts of tissue may be limited.

  3. A Combination of Culture Conditions and Gene Expression Analysis Can Be Used to Investigate and Predict hES Cell Differentiation Potential towards Male Gonadal Cells

    PubMed Central

    Kjartansdóttir, Kristín Rós; Reda, Ahmed; Panula, Sarita; Day, Kelly; Hultenby, Kjell; Söder, Olle; Hovatta, Outi; Stukenborg, Jan-Bernd

    2015-01-01

    Human embryonic stem cell differentiation towards various cell types belonging to ecto-, endo- and mesodermal cell lineages has been demonstrated, with high efficiency rates using standardized differentiation protocols. However, germ cell differentiation from human embryonic stem cells has been very inefficient so far. Even though the influence of various growth factors has been evaluated, the gene expression of different cell lines in relation to their differentiation potential has not yet been extensively examined. In this study, the potential of three male human embryonic stem cell lines to differentiate towards male gonadal cells was explored by analysing their gene expression profiles. The human embryonic stem cell lines were cultured for 14 days as monolayers on supporting human foreskin fibroblasts or as spheres in suspension, and were differentiated using BMP7, or spontaneous differentiation by omitting exogenous FGF2. TLDA analysis revealed that in the undifferentiated state, these cell lines have diverse mRNA profiles and exhibit significantly different potentials for differentiation towards the cell types present in the male gonads. This potential was associated with important factors directing the fate of the male primordial germ cells in vivo to form gonocytes, such as SOX17 or genes involved in the NODAL/ACTIVIN pathway, for example. Stimulation with BMP7 in suspension culture resulted in up-regulation of cytoplasmic SOX9 protein expression in all three lines. The observation that human embryonic stem cells differentiate towards germ and somatic cells after spontaneous and BMP7-induced stimulation in suspension emphasizes the important role of somatic cells in germ cell differentiation in vitro. PMID:26630562

  4. A Combination of Culture Conditions and Gene Expression Analysis Can Be Used to Investigate and Predict hES Cell Differentiation Potential towards Male Gonadal Cells.

    PubMed

    Kjartansdóttir, Kristín Rós; Reda, Ahmed; Panula, Sarita; Day, Kelly; Hultenby, Kjell; Söder, Olle; Hovatta, Outi; Stukenborg, Jan-Bernd

    2015-01-01

    Human embryonic stem cell differentiation towards various cell types belonging to ecto-, endo- and mesodermal cell lineages has been demonstrated, with high efficiency rates using standardized differentiation protocols. However, germ cell differentiation from human embryonic stem cells has been very inefficient so far. Even though the influence of various growth factors has been evaluated, the gene expression of different cell lines in relation to their differentiation potential has not yet been extensively examined. In this study, the potential of three male human embryonic stem cell lines to differentiate towards male gonadal cells was explored by analysing their gene expression profiles. The human embryonic stem cell lines were cultured for 14 days as monolayers on supporting human foreskin fibroblasts or as spheres in suspension, and were differentiated using BMP7, or spontaneous differentiation by omitting exogenous FGF2. TLDA analysis revealed that in the undifferentiated state, these cell lines have diverse mRNA profiles and exhibit significantly different potentials for differentiation towards the cell types present in the male gonads. This potential was associated with important factors directing the fate of the male primordial germ cells in vivo to form gonocytes, such as SOX17 or genes involved in the NODAL/ACTIVIN pathway, for example. Stimulation with BMP7 in suspension culture resulted in up-regulation of cytoplasmic SOX9 protein expression in all three lines. The observation that human embryonic stem cells differentiate towards germ and somatic cells after spontaneous and BMP7-induced stimulation in suspension emphasizes the important role of somatic cells in germ cell differentiation in vitro.

  5. Application of multidisciplinary analysis to gene expression.

    SciTech Connect

    Wang, Xuefel; Kang, Huining; Fields, Chris; Cowie, Jim R.; Davidson, George S.; Haaland, David Michael; Sibirtsev, Valeriy; Mosquera-Caro, Monica P.; Xu, Yuexian; Martin, Shawn Bryan; Helman, Paul; Andries, Erik; Ar, Kerem; Potter, Jeffrey; Willman, Cheryl L.; Murphy, Maurice H.

    2004-01-01

    Molecular analysis of cancer, at the genomic level, could lead to individualized patient diagnostics and treatments. The developments to follow will signal a significant paradigm shift in the clinical management of human cancer. Despite our initial hopes, however, it seems that simple analysis of microarray data cannot elucidate clinically significant gene functions and mechanisms. Extracting biological information from microarray data requires a complicated path involving multidisciplinary teams of biomedical researchers, computer scientists, mathematicians, statisticians, and computational linguists. The integration of the diverse outputs of each team is the limiting factor in the progress to discover candidate genes and pathways associated with the molecular biology of cancer. Specifically, one must deal with sets of significant genes identified by each method and extract whatever useful information may be found by comparing these different gene lists. Here we present our experience with such comparisons, and share methods developed in the analysis of an infant leukemia cohort studied on Affymetrix HG-U95A arrays. In particular, spatial gene clustering, hyper-dimensional projections, and computational linguistics were used to compare different gene lists. In spatial gene clustering, different gene lists are grouped together and visualized on a three-dimensional expression map, where genes with similar expressions are co-located. In another approach, projections from gene expression space onto a sphere clarify how groups of genes can jointly have more predictive power than groups of individually selected genes. Finally, online literature is automatically rearranged to present information about genes common to multiple groups, or to contrast the differences between the lists. The combination of these methods has improved our understanding of infant leukemia. While the complicated reality of the biology dashed our initial, optimistic hopes for simple answers from

  6. Gene Circuit Analysis of the Terminal Gap Gene huckebein

    PubMed Central

    Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

    2009-01-01

    The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network. PMID:19876378

  7. Synergistic nanomedicine by combined gene and photothermal therapy.

    PubMed

    Kim, Jinhwan; Kim, Jihoon; Jeong, Cherlhyun; Kim, Won Jong

    2016-03-01

    To date, various nanomaterials with the ability for gene delivery or photothermal effect have been developed in the field of biomedicine. The therapeutic potential of these nanomaterials has raised considerable interests in their use in potential next-generation strategies for effective anticancer therapy. In particular, the advancement of novel nanomedicines utilizing both therapeutic strategies of gene delivery and photothermal effect has generated much optimism regarding the imminent development of effective and successful cancer treatments. In this review, we discuss current research progress with regard to combined gene and photothermal therapy. This review focuses on synergistic therapeutic systems combining gene regulation and photothermal ablation as well as logically designed nano-carriers aimed at enhancing the delivery efficiency of therapeutic genes using the photothermal effect. The examples detailed in this review provide insight to further our understanding of combinatorial gene and photothermal therapy, thus paving the way for the design of promising nanomedicines.

  8. Identification and Functional Analysis of Light-Responsive Unique Genes and Gene Family Members in Rice

    PubMed Central

    Jung, Ki-Hong; Lee, Jinwon; Dardick, Chris; Seo, Young-Su; Cao, Peijian; Canlas, Patrick; Phetsom, Jirapa; Xu, Xia; Ouyang, Shu; An, Kyungsook; Cho, Yun-Ja; Lee, Geun-Cheol; Lee, Yoosook; An, Gynheung; Ronald, Pamela C.

    2008-01-01

    Functional redundancy limits detailed analysis of genes in many organisms. Here, we report a method to efficiently overcome this obstacle by combining gene expression data with analysis of gene-indexed mutants. Using a rice NSF45K oligo-microarray to compare 2-week-old light- and dark-grown rice leaf tissue, we identified 365 genes that showed significant 8-fold or greater induction in the light relative to dark conditions. We then screened collections of rice T-DNA insertional mutants to identify rice lines with mutations in the strongly light-induced genes. From this analysis, we identified 74 different lines comprising two independent mutant lines for each of 37 light-induced genes. This list was further refined by mining gene expression data to exclude genes that had potential functional redundancy due to co-expressed family members (12 genes) and genes that had inconsistent light responses across other publicly available microarray datasets (five genes). We next characterized the phenotypes of rice lines carrying mutations in ten of the remaining candidate genes and then carried out co-expression analysis associated with these genes. This analysis effectively provided candidate functions for two genes of previously unknown function and for one gene not directly linked to the tested biochemical pathways. These data demonstrate the efficiency of combining gene family-based expression profiles with analyses of insertional mutants to identify novel genes and their functions, even among members of multi-gene families. PMID:18725934

  9. The etiology of otosclerosis: a combination of genes and environment.

    PubMed

    Schrauwen, Isabelle; Van Camp, Guy

    2010-06-01

    Otosclerosis is a common form of hearing loss characterized by abnormal bone remodeling in the otic capsule. It is a complex genetic disease, caused by a combination of genetic and environmental factors. During the past decade, several attempts have been made to identify factors for otosclerosis. This review provides an overview of the current understanding of the etiology of otosclerosis and describes the genetic and environmental factors that have been implicated in the disease. Environmental factors include fluoride and viral factors, particularly measles. Genetic association studies for otosclerosis have reported several associations of genetic variants that influence the risk of disease, mainly involving bone remodeling pathways, although their individual risk contributions are small. Rare monogenic forms of otosclerosis also exist, which are caused by a mutation in a single gene leading to a clear familial segregation of the disease. Linkage analysis of large otosclerosis families has led to the identification of seven loci, and recently evidence was found that T cell receptor beta is a gene responsible for familial otosclerosis, suggesting an underlying immunological pathway. However, this might also represent an autoimmune process, a hypothesis that is supported by other data as well. In conclusion, a variety of pathways have been identified to be involved in the development of otosclerosis, showing that distinct mechanisms involving both genetic and environmental risk factors can influence and contribute to a similar disease outcome.

  10. Gene expression analysis of rheumatoid arthritis synovial lining regions by cDNA microarray combined with laser microdissection: up-regulation of inflammation-associated STAT1, IRF1, CXCL9, CXCL10, and CCL5

    PubMed Central

    Yoshida, S; Arakawa, F; Higuchi, F; Ishibashi, Y; Goto, M; Sugita, Y; Nomura, Y; Niino, D; Shimizu, K; Aoki, R; Hashikawa, K; Kimura, Y; Yasuda, K; Tashiro, K; Kuhara, S; Nagata, K; Ohshima, K

    2012-01-01

    Objectives The main histological change in rheumatoid arthritis (RA) is the villous proliferation of synovial lining cells, an important source of cytokines and chemokines, which are associated with inflammation. The aim of this study was to evaluate gene expression in the microdissected synovial lining cells of RA patients, using those of osteoarthritis (OA) patients as the control. Methods Samples were obtained during total joint replacement from 11 RA and five OA patients. Total RNA from the synovial lining cells was derived from selected specimens by laser microdissection (LMD) for subsequent cDNA microarray analysis. In addition, the expression of significant genes was confirmed immunohistochemically. Results The 14 519 genes detected by cDNA microarray were used to compare gene expression levels in synovial lining cells from RA with those from OA patients. Cluster analysis indicated that RA cells, including low- and high-expression subgroups, and OA cells were stored in two main clusters. The molecular activity of RA was statistically consistent with its clinical and histological activity. Expression levels of signal transducer and activator of transcription 1 (STAT1), interferon regulatory factor 1 (IRF1), and the chemokines CXCL9, CXCL10, and CCL5 were statistically significantly higher in the synovium of RA than in that of OA. Immunohistochemically, the lining synovium of RA, but not that of OA, clearly expressed STAT1, IRF1, and chemokines, as was seen in microarray analysis combined with LMD. Conclusions Our findings indicate an important role for lining synovial cells in the inflammatory and proliferative processes of RA. Further understanding of the local signalling in structural components is important in rheumatology. PMID:22401175

  11. The relationship between gene transcription and combinations of histone modifications

    NASA Astrophysics Data System (ADS)

    Cui, Xiangjun; Li, Hong; Luo, Liaofu

    2012-09-01

    Histone modification is an important subject of epigenetics which plays an intrinsic role in transcriptional regulation. It is known that multiple histone modifications act in a combinatorial fashion. In this study, we demonstrated that the pathways within constructed Bayesian networks can give an indication for the combinations among 12 histone modifications which have been studied in the TSS+1kb region in S. cerevisiae. After Bayesian networks for the genes with high transcript levels (H-network) and low transcript levels (L-network) were constructed, the combinations of modifications within the two networks were analyzed from the view of transcript level. The results showed that different combinations played dissimilar roles in the regulation of gene transcription when there exist differences for gene expression at transcription level.

  12. Risk analysis of colorectal cancer incidence by gene expression analysis

    PubMed Central

    Shangkuan, Wei-Chuan; Lin, Hung-Che; Chang, Yu-Tien; Jian, Chen-En; Fan, Hueng-Chuen; Chen, Kang-Hua; Liu, Ya-Fang; Hsu, Huan-Ming; Chou, Hsiu-Ling; Yao, Chung-Tay

    2017-01-01

    Background Colorectal cancer (CRC) is one of the leading cancers worldwide. Several studies have performed microarray data analyses for cancer classification and prognostic analyses. Microarray assays also enable the identification of gene signatures for molecular characterization and treatment prediction. Objective Microarray gene expression data from the online Gene Expression Omnibus (GEO) database were used to to distinguish colorectal cancer from normal colon tissue samples. Methods We collected microarray data from the GEO database to establish colorectal cancer microarray gene expression datasets for a combined analysis. Using the Prediction Analysis for Microarrays (PAM) method and the GSEA MSigDB resource, we analyzed the 14,698 genes that were identified through an examination of their expression values between normal and tumor tissues. Results Ten genes (ABCG2, AQP8, SPIB, CA7, CLDN8, SCNN1B, SLC30A10, CD177, PADI2, and TGFBI) were found to be good indicators of the candidate genes that correlate with CRC. From these selected genes, an average of six significant genes were obtained using the PAM method, with an accuracy rate of 95%. The results demonstrate the potential of utilizing a model with the PAM method for data mining. After a detailed review of the published reports, the results confirmed that the screened candidate genes are good indicators for cancer risk analysis using the PAM method. Conclusions Six genes were selected with 95% accuracy to effectively classify normal and colorectal cancer tissues. We hope that these results will provide the basis for new research projects in clinical practice that aim to rapidly assess colorectal cancer risk using microarray gene expression analysis. PMID:28229027

  13. Subtyping of Gliomaby Combining Gene Expression and CNVs Data Based on a Compressive Sensing Approach

    PubMed Central

    Tang, Wenlong; Cao, Hongbao; Zhang, Ji-Gang; Duan, Junbo; Lin, Dongdong; Wang, Yu-Ping

    2013-01-01

    It is realized that a combined analysis of different types of genomic measurements tends to give more reliable classification results. However, how to efficiently combine data with different resolutions is challenging. We propose a novel compressed sensing based approach for the combined analysis of gene expression and copy number variants data for the purpose of subtyping six types of Gliomas. Experimental results show that the proposed combined approach can substantially improve the classification accuracy compared to that of using either of individual data type. The proposed approach can be applicable to many other types of genomic data. PMID:25267935

  14. Combining SNP genotyping array with bulked segregant analysis to map a gene controlling adult-plant resistance to stripe rust in wheat line 03031-1-5 H62.

    PubMed

    Wu, Jianhui; Wang, Qilin; Xu, Liangsheng; Chen, Xianming; Li, Bei; Mu, Jingmei; Zeng, Qingdong; Huang, Lili; Han, Dejun; Kang, Zhensheng

    2017-08-23

    Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most devastating diseases of wheat worldwide. Growing resistant cultivars is considered the best approach to manage this disease. In order to identify the resistance gene(s) in wheat line 03031-1-5 H62, which displayed high resistance to stripe rust at adult plant stage, a cross was made between 03031-1-5 H62 and susceptible cultivar Avocet S. The mapping population was tested with Chinese Pst race CYR32 through artificial inoculation in a field in Yangling, Shaanxi Province and in Tianshui, Gansu Province under natural infection. The segregation ratios indicated that the resistance was conferred by a single dominant gene, temporarily designated as YrH62. A combination of bulked segregant analysis (BSA) with wheat 90K SNP array was used to identify molecular markers linked to YrH62. A total of 376 polymorphic SNP loci identified from the BSA analysis were located on chromosome 1B, from which 35 KASP markers selected together with 84 SSR markers on 1B were used to screen polymorphism and a chromosome region associated with rust resistance was identified. To saturate the chromosomal region covering the YrH62 locus, a 660K SNP array was used to identify more SNP markers. To develop tightly linked markers for marker-assisted selection of YrH62 in wheat breeding, 18 SNPs were converted into KASP markers. A final linkage map consisting of 15 KASP and 3 SSR markers was constructed with KASP markers AX-109352427 and AX-109862469 flanking the YrH62 locus in a 1.0 cM interval. YrH62 explained 63.8% and 69.3 % of the phenotypic variation for disease severity and infection type, respectively. YrH62 was located near the centromeric region of chromosome 1BS based on the positions of the SSR markers in 1B deletion bins. Based on the origin, responses to Pst races, and marker distances, YrH62 is likely different from the other reported stripe rust resistance genes/QTL on 1B. The gene and tightly linked

  15. Convergence analysis of combinations of different methods

    SciTech Connect

    Kang, Y.

    1994-12-31

    This paper provides a convergence analysis for combinations of different numerical methods for solving systems of differential equations. The author proves that combinations of two convergent linear multistep methods or Runge-Kutta methods produce a new convergent method of which the order is equal to the smaller order of the two original methods.

  16. Combining multiple tools outperforms individual methods in gene set enrichment analyses

    PubMed Central

    Ng, Milica; Wilson, Nicholas J.; Sheridan, Julie M.; Huynh, Huy; Wilson, Michael J.

    2017-01-01

    Abstract Motivation: Gene set enrichment (GSE) analysis allows researchers to efficiently extract biological insight from long lists of differentially expressed genes by interrogating them at a systems level. In recent years, there has been a proliferation of GSE analysis methods and hence it has become increasingly difficult for researchers to select an optimal GSE tool based on their particular dataset. Moreover, the majority of GSE analysis methods do not allow researchers to simultaneously compare gene set level results between multiple experimental conditions. Results: The ensemble of genes set enrichment analyses (EGSEA) is a method developed for RNA-sequencing data that combines results from twelve algorithms and calculates collective gene set scores to improve the biological relevance of the highest ranked gene sets. EGSEA’s gene set database contains around 25 000 gene sets from sixteen collections. It has multiple visualization capabilities that allow researchers to view gene sets at various levels of granularity. EGSEA has been tested on simulated data and on a number of human and mouse datasets and, based on biologists’ feedback, consistently outperforms the individual tools that have been combined. Our evaluation demonstrates the superiority of the ensemble approach for GSE analysis, and its utility to effectively and efficiently extrapolate biological functions and potential involvement in disease processes from lists of differentially regulated genes. Availability and Implementation: EGSEA is available as an R package at http://www.bioconductor.org/packages/EGSEA/. The gene sets collections are available in the R package EGSEAdata from http://www.bioconductor.org/packages/EGSEAdata/. Contacts:monther.alhamdoosh@csl.com.au ormritchie@wehi.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27694195

  17. Combining multiple tools outperforms individual methods in gene set enrichment analyses.

    PubMed

    Alhamdoosh, Monther; Ng, Milica; Wilson, Nicholas J; Sheridan, Julie M; Huynh, Huy; Wilson, Michael J; Ritchie, Matthew E

    2017-02-01

    Gene set enrichment (GSE) analysis allows researchers to efficiently extract biological insight from long lists of differentially expressed genes by interrogating them at a systems level. In recent years, there has been a proliferation of GSE analysis methods and hence it has become increasingly difficult for researchers to select an optimal GSE tool based on their particular dataset. Moreover, the majority of GSE analysis methods do not allow researchers to simultaneously compare gene set level results between multiple experimental conditions. The ensemble of genes set enrichment analyses (EGSEA) is a method developed for RNA-sequencing data that combines results from twelve algorithms and calculates collective gene set scores to improve the biological relevance of the highest ranked gene sets. EGSEA's gene set database contains around 25 000 gene sets from sixteen collections. It has multiple visualization capabilities that allow researchers to view gene sets at various levels of granularity. EGSEA has been tested on simulated data and on a number of human and mouse datasets and, based on biologists' feedback, consistently outperforms the individual tools that have been combined. Our evaluation demonstrates the superiority of the ensemble approach for GSE analysis, and its utility to effectively and efficiently extrapolate biological functions and potential involvement in disease processes from lists of differentially regulated genes. EGSEA is available as an R package at http://www.bioconductor.org/packages/EGSEA/ . The gene sets collections are available in the R package EGSEAdata from http://www.bioconductor.org/packages/EGSEAdata/ . monther.alhamdoosh@csl.com.au mritchie@wehi.edu.au. Supplementary data are available at Bioinformatics online.

  18. Down-weighting overlapping genes improves gene set analysis.

    PubMed

    Tarca, Adi Laurentiu; Draghici, Sorin; Bhatti, Gaurav; Romero, Roberto

    2012-06-19

    The identification of gene sets that are significantly impacted in a given condition based on microarray data is a crucial step in current life science research. Most gene set analysis methods treat genes equally, regardless how specific they are to a given gene set. In this work we propose a new gene set analysis method that computes a gene set score as the mean of absolute values of weighted moderated gene t-scores. The gene weights are designed to emphasize the genes appearing in few gene sets, versus genes that appear in many gene sets. We demonstrate the usefulness of the method when analyzing gene sets that correspond to the KEGG pathways, and hence we called our method Pathway Analysis with Down-weighting of Overlapping Genes (PADOG). Unlike most gene set analysis methods which are validated through the analysis of 2-3 data sets followed by a human interpretation of the results, the validation employed here uses 24 different data sets and a completely objective assessment scheme that makes minimal assumptions and eliminates the need for possibly biased human assessments of the analysis results. PADOG significantly improves gene set ranking and boosts sensitivity of analysis using information already available in the gene expression profiles and the collection of gene sets to be analyzed. The advantages of PADOG over other existing approaches are shown to be stable to changes in the database of gene sets to be analyzed. PADOG was implemented as an R package available at: http://bioinformaticsprb.med.wayne.edu/PADOG/or http://www.bioconductor.org.

  19. Down-weighting overlapping genes improves gene set analysis

    PubMed Central

    2012-01-01

    Background The identification of gene sets that are significantly impacted in a given condition based on microarray data is a crucial step in current life science research. Most gene set analysis methods treat genes equally, regardless how specific they are to a given gene set. Results In this work we propose a new gene set analysis method that computes a gene set score as the mean of absolute values of weighted moderated gene t-scores. The gene weights are designed to emphasize the genes appearing in few gene sets, versus genes that appear in many gene sets. We demonstrate the usefulness of the method when analyzing gene sets that correspond to the KEGG pathways, and hence we called our method Pathway Analysis with Down-weighting of Overlapping Genes (PADOG). Unlike most gene set analysis methods which are validated through the analysis of 2-3 data sets followed by a human interpretation of the results, the validation employed here uses 24 different data sets and a completely objective assessment scheme that makes minimal assumptions and eliminates the need for possibly biased human assessments of the analysis results. Conclusions PADOG significantly improves gene set ranking and boosts sensitivity of analysis using information already available in the gene expression profiles and the collection of gene sets to be analyzed. The advantages of PADOG over other existing approaches are shown to be stable to changes in the database of gene sets to be analyzed. PADOG was implemented as an R package available at: http://bioinformaticsprb.med.wayne.edu/PADOG/or http://www.bioconductor.org. PMID:22713124

  20. Clinical presentation, gene analysis and outcomes in young patients with early-treated combined methylmalonic acidemia and homocysteinemia (cblC type) in Shandong province, China.

    PubMed

    Han, Bingjuan; Cao, Zhiyang; Tian, Liping; Zou, Hui; Yang, Lian; Zhu, Weiwei; Liu, Yingxia

    2016-05-01

    To estimate the incidence of MMA on newborn screening in Shandong province from May 2011 to May 2014 and summarize the clinical presentation, biochemical features, mutation analysis, and treatment regime of early-treated patients with cblC disease. Between May 2011 and May 2014, 35,291 newborns were screened for MMA in Jinan maternal and Child Care Hospital, Shandong province. The levels of C3, C3/C2, methionine and tHcy were measured. Most patients received treatment with intramuscular hydroxocobalamin after diagnosis. Metabolic parameters, clinical presentation and mental development were followed up. Nine patients were identified among 35,291 by newborn screening, giving an estimated incidence of 1:3920 live births for MMA, and all were classified as cblC disease. Among them, five patients received treatment with intramuscular hydroxocobalamin and two patients did not receive any treatment. One patient died of metabolic crises triggered by infection at the age of 38 days. Seven different mutations (c.609G>A, c.455_457delCCC, c.394C>T, c.445_446insA, c.658_660delAAG, c.452A>G and IVS1+1G>A) were detected. The mutations (c.455_457delCCC and IVS1+1G>A) are novel. Five patients who received treatment had favorable metabolic response, with both reduction of urine MMA and tHcy and increase of methionine. We obtained 7 records of DQ assessment. The five patients who received treatment presented with developmental delay and obvious neurological manifestations. In two patients who did not receive any treatment, case 8 presented with severe mental retardation and developmental delay, while case 9 had nearly normal DQ values at the age of 1(1/12)years. Our study characterized variable phenotypes of neurodevelopment in early-treated cblC patients diagnosed on newborn screening. The long-term outcomes of cblC disease are unsatisfactory in spite of conventional treatment and improvement of biochemical abnormalities. Although the number of patients is too small, the

  1. Combined protein construct and synthetic gene engineering for heterologous protein expression and crystallization using Gene Composer

    SciTech Connect

    Raymond, Amy; Lovell, Scott; Lorimer, Don; Walchli, John; Mixon, Mark; Wallace, Ellen; Thompkins, Kaitlin; Archer, Kimberly; Burgin, Alex; Stewart, Lance

    2009-12-01

    With the goal of improving yield and success rates of heterologous protein production for structural studies we have developed the database and algorithm software package Gene Composer. This freely available electronic tool facilitates the information-rich design of protein constructs and their engineered synthetic gene sequences, as detailed in the accompanying manuscript. In this report, we compare heterologous protein expression levels from native sequences to that of codon engineered synthetic gene constructs designed by Gene Composer. A test set of proteins including a human kinase (P38{alpha}), viral polymerase (HCV NS5B), and bacterial structural protein (FtsZ) were expressed in both E. coli and a cell-free wheat germ translation system. We also compare the protein expression levels in E. coli for a set of 11 different proteins with greatly varied G:C content and codon bias. The results consistently demonstrate that protein yields from codon engineered Gene Composer designs are as good as or better than those achieved from the synonymous native genes. Moreover, structure guided N- and C-terminal deletion constructs designed with the aid of Gene Composer can lead to greater success in gene to structure work as exemplified by the X-ray crystallographic structure determination of FtsZ from Bacillus subtilis. These results validate the Gene Composer algorithms, and suggest that using a combination of synthetic gene and protein construct engineering tools can improve the economics of gene to structure research.

  2. In silico identification of breast cancer genes by combined multiple high throughput analyses.

    PubMed

    Shen, Dejun; He, Jianbo; Chang, Helena R

    2005-02-01

    that the combined multiple high throughput analyses is an effective data mining strategy in cancer gene identification. This approach may improve the usage of public available genomic data through strategic data mining of high throughput analysis.

  3. Changes in winter depression phenotype correlate with white blood cell gene expression profiles: a combined metagene and gene ontology approach.

    PubMed

    Bosker, Fokko J; Terpstra, Peter; Gladkevich, Anatoliy V; Janneke Dijck-Brouwer, D A; te Meerman, Gerard; Nolen, Willem A; Schoevers, Robert A; Meesters, Ybe

    2015-04-03

    In the present study we evaluate the feasibility of gene expression in white blood cells as a peripheral marker for winter depression. Sixteen patients with winter type seasonal affective disorder were included in the study. Blood was taken by venous puncture at three time points; in winter prior and following bright light therapy and in summer. RNA was isolated, converted into cRNA, amplified and hybridized on Illumina® gene expression arrays. The raw optical array data were quantile normalized and thereafter analyzed using a metagene approach, based on previously published Affymetrix gene array data. The raw data were also subjected to a secondary analysis focusing on circadian genes and genes involved in serotonergic neurotransmission. Differences between the conditions were analyzed, using analysis of variance on the principal components of the metagene score matrix. After correction for multiple testing no statistically significant differences were found. Another approach uses the correlation between metagene factor weights and the actual expression values, averaged over conditions. When comparing the correlations of winter vs. summer and bright light therapy vs. summer significant changes for several metagenes were found. Subsequent gene ontology analyses (DAVID and GeneTrail) of 5 major metagenes suggest an interaction between brain and white blood cells. The hypothesis driven analysis with a smaller group of genes failed to demonstrate any significant effects. The results from the combined metagene and gene ontology analyses support the idea of communication between brain and white blood cells. Future studies will need a much larger sample size to obtain information at the level of single genes. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. [An experimental research on the combination treatment of sFLK-1 gene therapy combined with gamma knife].

    PubMed

    Chen, Jing; Wang, Zheng-rong; Li, Hao; Wei, Yu-quan; Wang, Wei; Zhu, Bin

    2006-09-01

    To evaluate whether the sustained expression by adenovirus-mediated gene (sFLK-1) transfer can enhance the treatment efficacy of gamma knife radiosurgery. The mouse sFLK-1 gene was cloned to construct the recombinant adenovirus. The gliomata growing in BALB/c female nude mice with an initial mean volume of (109.3 +/- 20.5) mm3 were treated with gamma knife alone (13 Gy on day 12), sFLK-1 adenovirus alone (1 x 10(9) plaque-forming units, PFU was given to two mouse tail vein by injections, 7 and 14 days), gamma knife associated with sFLK-1 adenovirus or control adenovirus (1 x 10(9) PFU was given to two mouse tail vein by injections, 13 and 17 days). After the completion of therapy, the tumor size was recorded. The microvessel density (MVD) and tumor apoptosis were evaluated by immunohistochemical means. As comparing with three other control groups, the combination treatment group with sFLK-1 gene therapy and gamma knife not only significantly reduced tumor volume and prolonged the life span of tumor burden mice as well. In addition, the average tumor weights were lower in sFLK-1 combined with gamma knife group than in any other control group. Immunohistochemical analysis of glioma demonstrated a decreased MVD and a high apoptosis cell rate in sFLK-1 combined with gamma knif group. The antitumor effect of gamma knife can be potentiated by sFLK-1 gene therapy. Thus the combination of sFLK-1 gene therapy and gamma knife results an additive effect of antitumor. The observation may provide an important strategy for treatment cancer metastasis.

  5. The human RHOX gene cluster: target genes and functional analysis of gene variants in infertile men.

    PubMed

    Borgmann, Jennifer; Tüttelmann, Frank; Dworniczak, Bernd; Röpke, Albrecht; Song, Hye-Won; Kliesch, Sabine; Wilkinson, Miles F; Laurentino, Sandra; Gromoll, Jörg

    2016-09-15

    The X-linked reproductive homeobox (RHOX) gene cluster encodes transcription factors preferentially expressed in reproductive tissues. This gene cluster has important roles in male fertility based on phenotypic defects of Rhox-mutant mice and the finding that aberrant RHOX promoter methylation is strongly associated with abnormal human sperm parameters. However, little is known about the molecular mechanism of RHOX function in humans. Using gene expression profiling, we identified genes regulated by members of the human RHOX gene cluster. Some genes were uniquely regulated by RHOXF1 or RHOXF2/2B, while others were regulated by both of these transcription factors. Several of these regulated genes encode proteins involved in processes relevant to spermatogenesis; e.g. stress protection and cell survival. One of the target genes of RHOXF2/2B is RHOXF1, suggesting cross-regulation to enhance transcriptional responses. The potential role of RHOX in human infertility was addressed by sequencing all RHOX exons in a group of 250 patients with severe oligozoospermia. This revealed two mutations in RHOXF1 (c.515G > A and c.522C > T) and four in RHOXF2/2B (-73C > G, c.202G > A, c.411C > T and c.679G > A), of which only one (c.202G > A) was found in a control group of men with normal sperm concentration. Functional analysis demonstrated that c.202G > A and c.679G > A significantly impaired the ability of RHOXF2/2B to regulate downstream genes. Molecular modelling suggested that these mutations alter RHOXF2/F2B protein conformation. By combining clinical data with in vitro functional analysis, we demonstrate how the X-linked RHOX gene cluster may function in normal human spermatogenesis and we provide evidence that it is impaired in human male fertility.

  6. Efficient production of multi-modified pigs for xenotransplantation by 'combineering', gene stacking and gene editing.

    PubMed

    Fischer, Konrad; Kraner-Scheiber, Simone; Petersen, Björn; Rieblinger, Beate; Buermann, Anna; Flisikowska, Tatiana; Flisikowski, Krzysztof; Christan, Susanne; Edlinger, Marlene; Baars, Wiebke; Kurome, Mayuko; Zakhartchenko, Valeri; Kessler, Barbara; Plotzki, Elena; Szczerbal, Izabela; Switonski, Marek; Denner, Joachim; Wolf, Eckhard; Schwinzer, Reinhard; Niemann, Heiner; Kind, Alexander; Schnieke, Angelika

    2016-06-29

    Xenotransplantation from pigs could alleviate the shortage of human tissues and organs for transplantation. Means have been identified to overcome hyperacute rejection and acute vascular rejection mechanisms mounted by the recipient. The challenge is to combine multiple genetic modifications to enable normal animal breeding and meet the demand for transplants. We used two methods to colocate xenoprotective transgenes at one locus, sequential targeted transgene placement - 'gene stacking', and cointegration of multiple engineered large vectors - 'combineering', to generate pigs carrying modifications considered necessary to inhibit short to mid-term xenograft rejection. Pigs were generated by serial nuclear transfer and analysed at intermediate stages. Human complement inhibitors CD46, CD55 and CD59 were abundantly expressed in all tissues examined, human HO1 and human A20 were widely expressed. ZFN or CRISPR/Cas9 mediated homozygous GGTA1 and CMAH knockout abolished α-Gal and Neu5Gc epitopes. Cells from multi-transgenic piglets showed complete protection against human complement-mediated lysis, even before GGTA1 knockout. Blockade of endothelial activation reduced TNFα-induced E-selectin expression, IFNγ-induced MHC class-II upregulation and TNFα/cycloheximide caspase induction. Microbial analysis found no PERV-C, PCMV or 13 other infectious agents. These animals are a major advance towards clinical porcine xenotransplantation and demonstrate that livestock engineering has come of age.

  7. Metabolic profiling of ob/ob mouse fatty liver using HR-MAS (1)H-NMR combined with gene expression analysis reveals alterations in betaine metabolism and the transsulfuration pathway.

    PubMed

    Gogiashvili, Mikheil; Edlund, Karolina; Gianmoena, Kathrin; Marchan, Rosemarie; Brik, Alexander; Andersson, Jan T; Lambert, Jörg; Madjar, Katrin; Hellwig, Birte; Rahnenführer, Jörg; Hengstler, Jan G; Hergenröder, Roland; Cadenas, Cristina

    2017-02-01

    Metabolic perturbations resulting from excessive hepatic fat accumulation are poorly understood. Thus, in this study, leptin-deficient ob/ob mice, a mouse model of fatty liver disease, were used to investigate metabolic alterations in more detail. Metabolites were quantified in intact liver tissues of ob/ob (n = 8) and control (n = 8) mice using high-resolution magic angle spinning (HR-MAS) (1)H-NMR. In addition, after demonstrating that HR-MAS (1)H-NMR does not affect RNA integrity, transcriptional changes were measured by quantitative real-time PCR on RNA extracted from the same specimens after HR-MAS (1)H-NMR measurements. Importantly, the gene expression changes obtained agreed with those observed by Affymetrix microarray analysis performed on RNA isolated directly from fresh-frozen tissue. In total, 40 metabolites could be assigned in the spectra and subsequently quantified. Quantification of lactate was also possible after applying a lactate-editing pulse sequence that suppresses the lipid signal, which superimposes the lactate methyl resonance at 1.3 ppm. Significant differences were detected for creatinine, glutamate, glycine, glycolate, trimethylamine-N-oxide, dimethylglycine, ADP, AMP, betaine, phenylalanine, and uridine. Furthermore, alterations in one-carbon metabolism, supported by both metabolic and transcriptional changes, were observed. These included reduced demethylation of betaine to dimethylglycine and the reduced expression of genes coding for transsulfuration pathway enzymes, which appears to preserve methionine levels, but may limit glutathione synthesis. Overall, the combined approach is advantageous as it identifies changes not only at the single gene or metabolite level but also deregulated pathways, thus providing critical insight into changes accompanying fatty liver disease. Graphical abstract A Evaluation of RNA integrity before and after HR-MAS (1)H-NMR of intact mouse liver tissue. B Metabolite concentrations and gene

  8. Opportunities and challenges in combination gene cancer therapy.

    PubMed

    Nastiuk, Kent L; Krolewski, John J

    2016-03-01

    Treatment for solid tumor malignancies, which constitute the majority of human cancers, is still dominated by surgery and radiotherapies. This is especially true for many localized solid tumors, which are often curable with these treatments. However, metastatic cancers are beyond the reach of these therapies, and many localized cancers that are initially treated with surgery and radiation will recur and metastasize. Thus, for over 60years there has been a concerted effort to develop effective drug treatments for metastatic cancers. Combination therapies are an increasingly important part of the anti-cancer drug armamentarium. In the case of cytotoxic chemotherapy, multi-drug regimens rapidly became the norm, as the earliest single agents were relatively ineffective. In contrast to chemotherapy, where combination therapies were required in order to achieve treatment efficacy, for both hormonal and targeted therapies the impetus to move toward the use of combination therapies is to prevent or reverse the development of treatment resistance. In addition, emerging evidence suggests that combination therapy may also improve cancer treatment by neutralizing an emerging treatment side effect termed therapy-induced metastasis, which accompanies some effective single agent therapies. Finally, although gene therapy is still far from use in the clinic, we propose that combination therapies may enhance its effectiveness. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Gene conversion yields novel gene combinations in paralogs of GOT1 in the copepod Tigriopus californicus.

    PubMed

    Willett, Christopher S

    2013-07-12

    Gene conversion of duplicated genes can slow the divergence of paralogous copies over time but can also result in other interesting evolutionary patterns. Islands of genetic divergence that persist in the face of gene conversion can point to gene regions undergoing selection for new functions. Novel combinations of genetic variation that differ greatly from the original sequence can result from the transfer of genetic variation between paralogous genes by rare gene conversion events. Genetically divergent populations of the copepod Tigriopus californicus provide an excellent model to look at the patterns of divergence among paralogs across multiple independent evolutionary lineages. In this study the evolution of a set of paralogous genes encoding putative aspartate transaminase proteins (called GOT1 here) are examined in populations of the copepod T. californicus. One pair of duplicated genes, GOT1p1 and GOT1p2, has regions of high divergence between the copies in the face of apparent on-going gene conversion. The GOT1p2 gene also has unique haplotypes in two populations that appear to have resulted from a transfer of genetic variation via inter-paralog gene conversion. A second pair of duplicated genes GOT1Sr and GOT1Sd also shows evidence of gene conversion, but this gene conversion does not appear to have maintained each as a functional copy in all populations. The patterns of conservation and sequence divergence across this set of paralogous genes among populations of T. californicus suggest that some interesting evolutionary patterns are occurring at these loci. The results for the GOT1p1/GOT1p2 paralogs illustrate how gene conversion can factor in the creation of a mosaic pattern of regions of high divergence and low divergence. When coupled with rare gene conversion events of divergent regions, this pattern can result in the formation of novel proteins differing substantially from either original protein. The evolutionary patterns across these paralogs show

  10. Gene conversion yields novel gene combinations in paralogs of GOT1 in the copepod Tigriopus californicus

    PubMed Central

    2013-01-01

    Background Gene conversion of duplicated genes can slow the divergence of paralogous copies over time but can also result in other interesting evolutionary patterns. Islands of genetic divergence that persist in the face of gene conversion can point to gene regions undergoing selection for new functions. Novel combinations of genetic variation that differ greatly from the original sequence can result from the transfer of genetic variation between paralogous genes by rare gene conversion events. Genetically divergent populations of the copepod Tigriopus californicus provide an excellent model to look at the patterns of divergence among paralogs across multiple independent evolutionary lineages. Results In this study the evolution of a set of paralogous genes encoding putative aspartate transaminase proteins (called GOT1 here) are examined in populations of the copepod T. californicus. One pair of duplicated genes, GOT1p1 and GOT1p2, has regions of high divergence between the copies in the face of apparent on-going gene conversion. The GOT1p2 gene also has unique haplotypes in two populations that appear to have resulted from a transfer of genetic variation via inter-paralog gene conversion. A second pair of duplicated genes GOT1Sr and GOT1Sd also shows evidence of gene conversion, but this gene conversion does not appear to have maintained each as a functional copy in all populations. Conclusions The patterns of conservation and sequence divergence across this set of paralogous genes among populations of T. californicus suggest that some interesting evolutionary patterns are occurring at these loci. The results for the GOT1p1/GOT1p2 paralogs illustrate how gene conversion can factor in the creation of a mosaic pattern of regions of high divergence and low divergence. When coupled with rare gene conversion events of divergent regions, this pattern can result in the formation of novel proteins differing substantially from either original protein. The evolutionary

  11. Classification of genes based on gene expression analysis

    SciTech Connect

    Angelova, M. Myers, C. Faith, J.

    2008-05-15

    Systems biology and bioinformatics are now major fields for productive research. DNA microarrays and other array technologies and genome sequencing have advanced to the point that it is now possible to monitor gene expression on a genomic scale. Gene expression analysis is discussed and some important clustering techniques are considered. The patterns identified in the data suggest similarities in the gene behavior, which provides useful information for the gene functionalities. We discuss measures for investigating the homogeneity of gene expression data in order to optimize the clustering process. We contribute to the knowledge of functional roles and regulation of E. coli genes by proposing a classification of these genes based on consistently correlated genes in expression data and similarities of gene expression patterns. A new visualization tool for targeted projection pursuit and dimensionality reduction of gene expression data is demonstrated.

  12. Combining gene annotations and gene expression data in model-based clustering: weighted method.

    PubMed

    Huang, Desheng; Wei, Peng; Pan, Wei

    2006-01-01

    It has been increasingly recognized that incorporating prior knowledge into cluster analysis can result in more reliable and meaningful clusters. In contrast to the standard modelbased clustering with a global mixture model, which does not use any prior information, a stratified mixture model was recently proposed to incorporate gene functions or biological pathways as priors in model-based clustering of gene expression profiles: various gene functional groups form the strata in a stratified mixture model. Albeit useful, the stratified method may be less efficient than the global analysis if the strata are non-informative to clustering. We propose a weighted method that aims to strike a balance between a stratified analysis and a global analysis: it weights between the clustering results of the stratified analysis and that of the global analysis; the weight is determined by data. More generally, the weighted method can take advantage of the hierarchical structure of most existing gene functional annotation systems, such as MIPS and Gene Ontology (GO), and facilitate choosing appropriate gene functional groups as priors. We use simulated data and real data to demonstrate the feasibility and advantages of the proposed method.

  13. Rapid Introgression of the Fusarium Wilt Resistance Gene into an Elite Cabbage Line through the Combined Application of a Microspore Culture, Genome Background Analysis, and Disease Resistance-Specific Marker Assisted Foreground Selection

    PubMed Central

    Liu, Xing; Han, Fengqing; Kong, Congcong; Fang, Zhiyuan; Yang, Limei; Zhang, Yangyong; Zhuang, Mu; Liu, Yumei; Li, Zhansheng; Lv, Honghao

    2017-01-01

    Cabbage is an economically important vegetable worldwide. Cabbage Fusarium Wilt (CFW) is a destructive disease that results in considerable yield and quality losses in cole crops. The use of CFW-resistant varieties is the most effective strategy to mitigate the effects of CFW. 01-20 is an elite cabbage line with desirable traits and a high combining ability, but it is highly susceptible to CFW. To rapidly transfer a CFW resistance gene into 01-20 plants, we used microspore cultures to develop 230 doubled haploid (DH) lines from a cross between 01-20 (highly susceptible) and 96-100 (highly resistant). One of the generated DH lines (i.e., D134) was highly resistant to CFW and exhibited a phenotypic performance that was similar to that of line 01-20. Therefore, D134 was applied as the resistance donor parent. We generated 24 insertion–deletion markers using whole genome resequencing data for lines 01-20 and 96-100 to analyze the genomic backgrounds of backcross (BC) progenies. Based on the CFW resistance gene FOC1, a simple sequence repeat (SSR) marker (i.e., Frg13) was developed for foreground selections. We screened 240 BC1 individuals and 280 BC2 individuals with these markers and assessed their phenotypic performance. The proportion of recurrent parent genome (PRPG) of the best individuals in BC1 and BC2 were 95.8 and 99.1%. Finally, a best individual designated as YR01-20 was identified from 80 BC2F1 individuals, with homozygous FOC1 allele and genomic background and phenotype almost the same as those of 01-20. Our results may provide a rapid and efficient way of improving elite lines through the combined application of microspore culture, whole-genome background analysis, and disease resistance-specific marker selection. Additionally, the cabbage lines developed in this study represent elite materials useful for the breeding of new CFW-resistant cabbage varieties. PMID:28392793

  14. Gene indexing: characterization and analysis of NLM's GeneRIFs.

    PubMed

    Mitchell, Joyce A; Aronson, Alan R; Mork, James G; Folk, Lillian C; Humphrey, Susanne M; Ward, Janice M

    2003-01-01

    We present an initial analysis of the National Library of Medicine's (NLM) Gene Indexing initiative. Gene Indexing occurs at the time of indexing for all 4600 journals and over 500,000 articles added to PubMed/MEDLINE each year. Gene Indexing links articles about the basic biology of a gene or protein within eight model organisms to a specific record in the NLM's LocusLink database of gene products. The result is an entry called a Gene Reference Into Function (GeneRIF) within the LocusLink database. We analyzed the numbers of GeneRIFs produced in the first year of GeneRIF production. 27,645 GeneRIFs were produced, pertaining to 9126 loci over eight model organisms. 60% of these were associated with human genes and 27% with mouse genes. About 80% discuss genes with an established MeSH Heading or other MeSH term. We developed a prototype functional alerting system for researchers based on the GeneRIFs, and a strategy to find all of the literature related to genes. We conclude that the Gene Indexing initiative adds considerable value to the life sciences research community.

  15. Combining Click Chemistry-Based Proteomics With Dox-Inducible Gene Expression.

    PubMed

    Gebert, J; Schnölzer, M; Warnken, U; Kopitz, J

    2017-01-01

    Inactivating mutations in single genes can trigger, prevent, promote, or alleviate diseases. Identifying such disease-related genes is a main pillar of medical research. Since proteins play a crucial role in mediating these effects, their impact on the diseased cells' proteome including posttranslational modifications has to be elucidated for a detailed understanding of the role of these genes in the disease process. In complex disorders, like cancer, several genes contribute to the disease process, thereby hampering the assignment of a proteomic change to the corresponding causative gene. To enable comprehensive screening for the impact of inactivation of a gene, e.g., loss of a tumor suppressor in cancer, on the cellular proteome, we present a strategy based on combination of three technologies that is recombinase-mediated cassette exchange, click chemistry, and mass spectrometry. The methodology is exemplified by the analysis of the proteomic changes induced by the loss of a tumor suppressor gene in colorectal cancer cells. To demonstrate the applicability to screen for posttranslational modification changes, we also describe the analysis of protein glycosylation changes caused by the tumor suppressor inactivation. In principle, this strategy can be applied to analyze the effects of any gene of interest on protein expression as well as posttranslational modification by glycosylation. Moreover adaptation of the strategy to an appropriate cell culture model has the potential for application on a broad range of diseases where the disease-promoting mutations have been identified. © 2017 Elsevier Inc. All rights reserved.

  16. Novel strategies to mine alcoholism-related haplotypes and genes by combining existing knowledge framework.

    PubMed

    Zhang, RuiJie; Li, Xia; Jiang, YongShuai; Liu, GuiYou; Li, ChuanXing; Zhang, Fan; Xiao, Yun; Gong, BinSheng

    2009-02-01

    High-throughout single nucleotide polymorphism detection technology and the existing knowledge provide strong support for mining the disease-related haplotypes and genes. In this study, first, we apply four kinds of haplotype identification methods (Confidence Intervals, Four Gamete Tests, Solid Spine of LD and fusing method of haplotype block) into high-throughout SNP genotype data to identify blocks, then use cluster analysis to verify the effectiveness of the four methods, and select the alcoholism-related SNP haplotypes through risk analysis. Second, we establish a mapping from haplotypes to alcoholism-related genes. Third, we inquire NCBI SNP and gene databases to locate the blocks and identify the candidate genes. In the end, we make gene function annotation by KEGG, Biocarta, and GO database. We find 159 haplotype blocks, which relate to the alcoholism most possibly on chromosome 1 approximately 22, including 227 haplotypes, of which 102 SNP haplotypes may increase the risk of alcoholism. We get 121 alcoholism-related genes and verify their reliability by the functional annotation of biology. In a word, we not only can handle the SNP data easily, but also can locate the disease-related genes precisely by combining our novel strategies of mining alcoholism-related haplotypes and genes with existing knowledge framework.

  17. Resolution of gene regulatory conflicts caused by combinations of antibiotics

    PubMed Central

    Bollenbach, Tobias; Kishony, Roy

    2011-01-01

    SUMMARY Regulatory conflicts occur when two signals which individually trigger opposite cellular responses are present simultaneously. Here, we investigate regulatory conflicts in the bacterial response to antibiotic combinations. We use an Escherichia coli promoter-GFP library to study the transcriptional response of many promoters to either additive or antagonistic drug pairs at fine two-dimensional resolution of drug concentration. Surprisingly, we find that this dataset can be characterized as a linear sum of only two principal components. Component one, accounting for over 70% of the response, represents the response to growth inhibition by the drugs. Component two describes how regulatory conflicts are resolved. For the additive drug pair, conflicts are resolved by linearly interpolating the single drug responses, while for the antagonistic drug pair, the growth-limiting drug dominates the response. Importantly, for a given drug pair, the same conflict resolution strategy applies to almost all genes. These results provide a recipe for predicting gene expression responses to antibiotic combinations. PMID:21596308

  18. Combining Genome-Scale Experimental and Computational Methods To Identify Essential Genes in Rhodobacter sphaeroides

    PubMed Central

    Burger, Brian T.; Imam, Saheed; Scarborough, Matthew J.; Noguera, Daniel R.

    2017-01-01

    ABSTRACT Rhodobacter sphaeroides is one of the best-studied alphaproteobacteria from biochemical, genetic, and genomic perspectives. To gain a better systems-level understanding of this organism, we generated a large transposon mutant library and used transposon sequencing (Tn-seq) to identify genes that are essential under several growth conditions. Using newly developed Tn-seq analysis software (TSAS), we identified 493 genes as essential for aerobic growth on a rich medium. We then used the mutant library to identify conditionally essential genes under two laboratory growth conditions, identifying 85 additional genes required for aerobic growth in a minimal medium and 31 additional genes required for photosynthetic growth. In all instances, our analyses confirmed essentiality for many known genes and identified genes not previously considered to be essential. We used the resulting Tn-seq data to refine and improve a genome-scale metabolic network model (GEM) for R. sphaeroides. Together, we demonstrate how genetic, genomic, and computational approaches can be combined to obtain a systems-level understanding of the genetic framework underlying metabolic diversity in bacterial species. IMPORTANCE Knowledge about the role of genes under a particular growth condition is required for a holistic understanding of a bacterial cell and has implications for health, agriculture, and biotechnology. We developed the Tn-seq analysis software (TSAS) package to provide a flexible and statistically rigorous workflow for the high-throughput analysis of insertion mutant libraries, advanced the knowledge of gene essentiality in R. sphaeroides, and illustrated how Tn-seq data can be used to more accurately identify genes that play important roles in metabolism and other processes that are essential for cellular survival. Author Video: An author video summary of this article is available. PMID:28744485

  19. Suicide gene and cytokines combined nonviral gene therapy for spontaneous canine melanoma.

    PubMed

    Finocchiaro, L M E; Fiszman, G L; Karara, A L; Glikin, G C

    2008-03-01

    Canine spontaneous melanoma is a highly aggressive tumor resistant to current therapies. We evaluated the safety, efficacy and antitumor effects of direct intratumor injections of lipoplexes encoding herpes simplex thymidine kinase coadministrated with ganciclovir, and irradiated transgenic xenogeneic cells secreting 20-30 mug day(-1) of human granulocyte-macrophage colony-stimulating factor and interleukin-2. Toxicity was minimal or absent in all patients. This combined treatment (CT) induced tumor regression and a pronounced immune cell infiltration. The objective responses (47%: 21/45) averaged 80% of tumor mass loss. Local CT also induced systemic antitumor response evidenced by complete remission of one pulmonary metastasis and by the significantly higher percentage of metastasis-free patients (76: 34/45)) until the study ending compared to untreated (UC: 29%, 5/17), surgery-treated (CX: 48%, 11/23) or suicide gene-treated controls (SG: 56%, 9/16) (Fisher's exact test). CT significantly improved median survival time: 160 (57-509) days compared to UC (69 (10-169)), CX (82 (43-216)) or SG (94 (46-159)). CT also increased (P<0.00001, Kaplan-Meier analysis) metastasis-free survival: >509 (57-509) days with respect to UC: 41 (10-169), CX: 133 (43-216) and SG: >159 (41-159). Therefore, CT controlled tumor growth by delaying or preventing distant metastasis, thereby significantly extending survival and recovering the quality of life.

  20. HIV-1 CCR5 gene therapy will fail unless it is combined with a suicide gene

    PubMed Central

    Pandit, Aridaman; de Boer, Rob J.

    2015-01-01

    Highly active antiretroviral therapy (ART) has successfully turned Human immunodeficiency virus type 1 (HIV-1) from a deadly pathogen into a manageable chronic infection. ART is a lifelong therapy which is both expensive and toxic, and HIV can become resistant to it. An alternative to lifelong ART is gene therapy that targets the CCR5 co-receptor and creates a population of genetically modified host cells that are less susceptible to viral infection. With generic mathematical models we show that gene therapy that only targets the CCR5 co-receptor fails to suppress HIV-1 (which is in agreement with current data). We predict that the same gene therapy can be markedly improved if it is combined with a suicide gene that is only expressed upon HIV-1 infection. PMID:26674113

  1. HIV-1 CCR5 gene therapy will fail unless it is combined with a suicide gene.

    PubMed

    Pandit, Aridaman; de Boer, Rob J

    2015-12-17

    Highly active antiretroviral therapy (ART) has successfully turned Human immunodeficiency virus type 1 (HIV-1) from a deadly pathogen into a manageable chronic infection. ART is a lifelong therapy which is both expensive and toxic, and HIV can become resistant to it. An alternative to lifelong ART is gene therapy that targets the CCR5 co-receptor and creates a population of genetically modified host cells that are less susceptible to viral infection. With generic mathematical models we show that gene therapy that only targets the CCR5 co-receptor fails to suppress HIV-1 (which is in agreement with current data). We predict that the same gene therapy can be markedly improved if it is combined with a suicide gene that is only expressed upon HIV-1 infection.

  2. Gene set analysis for longitudinal gene expression data

    PubMed Central

    2011-01-01

    Background Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. GSA performs statistical tests for independent microarray samples at the level of gene sets rather than individual genes. Nowadays, an increasing number of microarray studies are conducted to explore the dynamic changes of gene expression in a variety of species and biological scenarios. In these longitudinal studies, gene expression is repeatedly measured over time such that a GSA needs to take into account the within-gene correlations in addition to possible between-gene correlations. Results We provide a robust nonparametric approach to compare the expressions of longitudinally measured sets of genes under multiple treatments or experimental conditions. The limiting distributions of our statistics are derived when the number of genes goes to infinity while the number of replications can be small. When the number of genes in a gene set is small, we recommend permutation tests based on our nonparametric test statistics to achieve reliable type I error and better power while incorporating unknown correlations between and within-genes. Simulation results demonstrate that the proposed method has a greater power than other methods for various data distributions and heteroscedastic correlation structures. This method was used for an IL-2 stimulation study and significantly altered gene sets were identified. Conclusions The simulation study and the real data application showed that the proposed gene set analysis provides a promising tool for longitudinal microarray analysis. R scripts for simulating longitudinal data and calculating the nonparametric statistics are posted on the North Dakota INBRE website http://ndinbre.org/programs/bioinformatics.php. Raw microarray data is available in Gene Expression Omnibus (National Center for Biotechnology Information) with accession number GSE6085. PMID

  3. Screening key genes and pathways in glioma based on gene set enrichment analysis and meta-analysis.

    PubMed

    Tang, Yanyan; He, Wenwu; Wei, Yunfei; Qu, Zhanli; Zeng, Jinming; Qin, Chao

    2013-06-01

    Glioma is a highly invasive, rapidly spreading form of brain cancer, while its etiology is largely unknown. A few recently reported studies have been developed using gene expression microarrays of glioma to identify differentially expressed genes from several to hundreds. This study was designed to analyze vast amounts of glioma-related microarray data and screen the key genes and pathways related to the development and progression of glioma. We used gene set enrichment analysis (GSEA) and meta-analysis of seven included studies after standardized microarray preprocessing, which increased concordance between these gene datasets. After GSEA, there were 14 mixing pathways including 13 up- and 1 down-regulated pathways. Based on the meta-analysis, 268 significant genes were screened out (P < 0.05); there were 249 genes identified by Kyoto Encyclopedia of Genes and Genomes (KEGG), and 27 KEGG pathways closely related to the set of the imported genes were identified. At last, six consistent pathways and key genes in these pathways related to glioma were obtained with combined GSEA and meta-analysis. The gene pathways that we identified could provide insight concerning the development of glioma. Further studies are needed to determine the biological function for the positive genes.

  4. A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae).

    PubMed

    Troyanskaya, Olga G; Dolinski, Kara; Owen, Art B; Altman, Russ B; Botstein, David

    2003-07-08

    Genomic sequencing is no longer a novelty, but gene function annotation remains a key challenge in modern biology. A variety of functional genomics experimental techniques are available, from classic methods such as affinity precipitation to advanced high-throughput techniques such as gene expression microarrays. In the future, more disparate methods will be developed, further increasing the need for integrated computational analysis of data generated by these studies. We address this problem with MAGIC (Multisource Association of Genes by Integration of Clusters), a general framework that uses formal Bayesian reasoning to integrate heterogeneous types of high-throughput biological data (such as large-scale two-hybrid screens and multiple microarray analyses) for accurate gene function prediction. The system formally incorporates expert knowledge about relative accuracies of data sources to combine them within a normative framework. MAGIC provides a belief level with its output that allows the user to vary the stringency of predictions. We applied MAGIC to Saccharomyces cerevisiae genetic and physical interactions, microarray, and transcription factor binding sites data and assessed the biological relevance of gene groupings using Gene Ontology annotations produced by the Saccharomyces Genome Database. We found that by creating functional groupings based on heterogeneous data types, MAGIC improved accuracy of the groupings compared with microarray analysis alone. We describe several of the biological gene groupings identified.

  5. Analysis of fractals with combined partition

    NASA Astrophysics Data System (ADS)

    Dedovich, T. G.; Tokarev, M. V.

    2016-03-01

    The space—time properties in the general theory of relativity, as well as the discreteness and non-Archimedean property of space in the quantum theory of gravitation, are discussed. It is emphasized that the properties of bodies in non-Archimedean spaces coincide with the properties of the field of P-adic numbers and fractals. It is suggested that parton showers, used for describing interactions between particles and nuclei at high energies, have a fractal structure. A mechanism of fractal formation with combined partition is considered. The modified SePaC method is offered for the analysis of such fractals. The BC, PaC, and SePaC methods for determining a fractal dimension and other fractal characteristics (numbers of levels and values of a base of forming a fractal) are considered. It is found that the SePaC method has advantages for the analysis of fractals with combined partition.

  6. An attempt for combining microarray data sets by adjusting gene expressions.

    PubMed

    Kim, Ki-Yeol; Kim, Se Hyun; Ki, Dong Hyuk; Jeong, Jaeheon; Jeong, Ha Jin; Jeung, Hei-Cheul; Chung, Hyun Cheol; Rha, Sun Young

    2007-06-01

    The diverse experimental environments in microarray technology, such as the different platforms or different RNA sources, can cause biases in the analysis of multiple microarrays. These systematic effects present a substantial obstacle for the analysis of microarray data, and the resulting information may be inconsistent and unreliable. Therefore, we introduced a simple integration method for combining microarray data sets that are derived from different experimental conditions, and we expected that more reliable information can be detected from the combined data set rather than from the separated data sets. This method is based on the distributions of the gene expression ratios among the different microarray data sets and it transforms, gene by gene, the gene expression ratios into the form of the reference data set. The efficiency of the proposed integration method was evaluated using two microarray data sets, which were derived from different RNA sources, and a newly defined measure, the mixture score. The proposed integration method intermixed the two data sets that were obtained from different RNA sources, which in turn reduced the experimental bias between the two data sets, and the mixture score increased by 24.2%. A data set combined by the proposed method preserved the inter-group relationship of the separated data sets. The proposed method worked well in adjusting systematic biases, including the source effect. The ability to use an effectively integrated microarray data set yields more reliable results due to the larger sample size and this also decreases the chance of false negatives.

  7. Il2rg gene-targeted severe combined immunodeficiency pigs.

    PubMed

    Suzuki, Shunichi; Iwamoto, Masaki; Saito, Yoriko; Fuchimoto, Daiichiro; Sembon, Shoichiro; Suzuki, Misae; Mikawa, Satoshi; Hashimoto, Michiko; Aoki, Yuki; Najima, Yuho; Takagi, Shinsuke; Suzuki, Nahoko; Suzuki, Emi; Kubo, Masanori; Mimuro, Jun; Kashiwakura, Yuji; Madoiwa, Seiji; Sakata, Yoichi; Perry, Anthony C F; Ishikawa, Fumihiko; Onishi, Akira

    2012-06-14

    A porcine model of severe combined immunodeficiency (SCID) promises to facilitate human cancer studies, the humanization of tissue for xenotransplantation, and the evaluation of stem cells for clinical therapy, but SCID pigs have not been described. We report here the generation and preliminary evaluation of a porcine SCID model. Fibroblasts containing a targeted disruption of the X-linked interleukin-2 receptor gamma chain gene, Il2rg, were used as donors to generate cloned pigs by serial nuclear transfer. Germline transmission of the Il2rg deletion produced healthy Il2rg(+/-) females, while Il2rg(-/Y) males were athymic and exhibited markedly impaired immunoglobulin and T and NK cell production, robustly recapitulating human SCID. Following allogeneic bone marrow transplantation, donor cells stably integrated in Il2rg(-/Y) heterozygotes and reconstituted the Il2rg(-/Y) lymphoid lineage. The SCID pigs described here represent a step toward the comprehensive evaluation of preclinical cellular regenerative strategies.

  8. Familial aggregation analysis of gene expressions

    PubMed Central

    Rao, Shao-Qi; Xu, Liang-De; Zhang, Guang-Mei; Li, Xia; Li, Lin; Shen, Gong-Qing; Jiang, Yang; Yang, Yue-Ying; Gong, Bin-Sheng; Jiang, Wei; Zhang, Fan; Xiao, Yun; Wang, Qing K

    2007-01-01

    Traditional studies of familial aggregation are aimed at defining the genetic (and non-genetic) causes of a disease from physiological or clinical traits. However, there has been little attempt to use genome-wide gene expressions, the direct phenotypic measures of genes, as the traits to investigate several extended issues regarding the distributions of familially aggregated genes on chromosomes or in functions. In this study we conducted a genome-wide familial aggregation analysis by using the in vitro cell gene expressions of 3300 human autosome genes (Problem 1 data provided to Genetic Analysis Workshop 15) in order to answer three basic genetics questions. First, we investigated how gene expressions aggregate among different types (degrees) of relative pairs. Second, we conducted a bioinformatics analysis of highly familially aggregated genes to see how they are distributed on chromosomes. Third, we performed a gene ontology enrichment test of familially aggregated genes to find evidence to support their functional consensus. The results indicated that 1) gene expressions did aggregate in families, especially between sibs. Of 3300 human genes analyzed, there were a total of 1105 genes with one or more significant (empirical p < 0.05) familial correlation; 2) there were several genomic hot spots where highly familially aggregated genes (e.g., the chromosome 6 HLA genes cluster) were clustered; 3) as we expected, gene ontology enrichment tests revealed that the 1105 genes were aggregating not only in families but also in functional categories. PMID:18466548

  9. Combined genetic and splicing analysis of BRCA1 c.[594-2A>C; 641A>G] highlights the relevance of naturally occurring in-frame transcripts for developing disease gene variant classification algorithms.

    PubMed

    de la Hoya, Miguel; Soukarieh, Omar; López-Perolio, Irene; Vega, Ana; Walker, Logan C; van Ierland, Yvette; Baralle, Diana; Santamariña, Marta; Lattimore, Vanessa; Wijnen, Juul; Whiley, Philip; Blanco, Ana; Raponi, Michela; Hauke, Jan; Wappenschmidt, Barbara; Becker, Alexandra; Hansen, Thomas V O; Behar, Raquel; Investigators, KConFaB; Niederacher, Diether; Arnold, Norbert; Dworniczak, Bernd; Steinemann, Doris; Faust, Ulrike; Rubinstein, Wendy; Hulick, Peter J; Houdayer, Claude; Caputo, Sandrine M; Castera, Laurent; Pesaran, Tina; Chao, Elizabeth; Brewer, Carole; Southey, Melissa C; van Asperen, Christi J; Singer, Christian F; Sullivan, Jan; Poplawski, Nicola; Mai, Phuong; Peto, Julian; Johnson, Nichola; Burwinkel, Barbara; Surowy, Harald; Bojesen, Stig E; Flyger, Henrik; Lindblom, Annika; Margolin, Sara; Chang-Claude, Jenny; Rudolph, Anja; Radice, Paolo; Galastri, Laura; Olson, Janet E; Hallberg, Emily; Giles, Graham G; Milne, Roger L; Andrulis, Irene L; Glendon, Gord; Hall, Per; Czene, Kamila; Blows, Fiona; Shah, Mitul; Wang, Qin; Dennis, Joe; Michailidou, Kyriaki; McGuffog, Lesley; Bolla, Manjeet K; Antoniou, Antonis C; Easton, Douglas F; Couch, Fergus J; Tavtigian, Sean; Vreeswijk, Maaike P; Parsons, Michael; Meeks, Huong D; Martins, Alexandra; Goldgar, David E; Spurdle, Amanda B

    2016-06-01

    A recent analysis using family history weighting and co-observation classification modeling indicated that BRCA1 c.594-2A > C (IVS9-2A > C), previously described to cause exon 10 skipping (a truncating alteration), displays characteristics inconsistent with those of a high risk pathogenic BRCA1 variant. We used large-scale genetic and clinical resources from the ENIGMA, CIMBA and BCAC consortia to assess pathogenicity of c.594-2A > C. The combined odds for causality considering case-control, segregation and breast tumor pathology information was 3.23 × 10(-8) Our data indicate that c.594-2A > C is always in cis with c.641A > G. The spliceogenic effect of c.[594-2A > C;641A > G] was characterized using RNA analysis of human samples and splicing minigenes. As expected, c.[594-2A > C; 641A > G] caused exon 10 skipping, albeit not due to c.594-2A > C impairing the acceptor site but rather by c.641A > G modifying exon 10 splicing regulatory element(s). Multiple blood-based RNA assays indicated that the variant allele did not produce detectable levels of full-length transcripts, with a per allele BRCA1 expression profile composed of ≈70-80% truncating transcripts, and ≈20-30% of in-frame Δ9,10 transcripts predicted to encode a BRCA1 protein with tumor suppression function.We confirm that BRCA1c.[594-2A > C;641A > G] should not be considered a high-risk pathogenic variant. Importantly, results from our detailed mRNA analysis suggest that BRCA-associated cancer risk is likely not markedly increased for individuals who carry a truncating variant in BRCA1 exons 9 or 10, or any other BRCA1 allele that permits 20-30% of tumor suppressor function. More generally, our findings highlight the importance of assessing naturally occurring alternative splicing for clinical evaluation of variants in disease-causing genes. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  10. Combined genetic and splicing analysis of BRCA1 c.[594-2A>C; 641A>G] highlights the relevance of naturally occurring in-frame transcripts for developing disease gene variant classification algorithms

    PubMed Central

    de la Hoya, Miguel; Soukarieh, Omar; López-Perolio, Irene; Vega, Ana; Walker, Logan C.; van Ierland, Yvette; Baralle, Diana; Santamariña, Marta; Lattimore, Vanessa; Wijnen, Juul; Whiley, Philip; Blanco, Ana; Raponi, Michela; Hauke, Jan; Wappenschmidt, Barbara; Becker, Alexandra; Hansen, Thomas V. O.; Behar, Raquel; Investigators, KConFaB; Niederacher, Diether; Arnold, Norbert; Dworniczak, Bernd; Steinemann, Doris; Faust, Ulrike; Rubinstein, Wendy; Hulick, Peter J.; Houdayer, Claude; Caputo, Sandrine M.; Castera, Laurent; Pesaran, Tina; Chao, Elizabeth; Brewer, Carole; Southey, Melissa C.; van Asperen, Christi J.; Singer, Christian F.; Sullivan, Jan; Poplawski, Nicola; Mai, Phuong; Peto, Julian; Johnson, Nichola; Burwinkel, Barbara; Surowy, Harald; Bojesen, Stig E.; Flyger, Henrik; Lindblom, Annika; Margolin, Sara; Chang-Claude, Jenny; Rudolph, Anja; Radice, Paolo; Galastri, Laura; Olson, Janet E.; Hallberg, Emily; Giles, Graham G.; Milne, Roger L.; Andrulis, Irene L.; Glendon, Gord; Hall, Per; Czene, Kamila; Blows, Fiona; Shah, Mitul; Wang, Qin; Dennis, Joe; Michailidou, Kyriaki; McGuffog, Lesley; Bolla, Manjeet K.; Antoniou, Antonis C.; Easton, Douglas F.; Couch, Fergus J.; Tavtigian, Sean; Vreeswijk, Maaike P.; Parsons, Michael; Meeks, Huong D.; Martins, Alexandra; Goldgar, David E.; Spurdle, Amanda B.

    2016-01-01

    A recent analysis using family history weighting and co-observation classification modeling indicated that BRCA1 c.594-2A > C (IVS9-2A > C), previously described to cause exon 10 skipping (a truncating alteration), displays characteristics inconsistent with those of a high risk pathogenic BRCA1 variant. We used large-scale genetic and clinical resources from the ENIGMA, CIMBA and BCAC consortia to assess pathogenicity of c.594-2A > C. The combined odds for causality considering case-control, segregation and breast tumor pathology information was 3.23 × 10−8. Our data indicate that c.594-2A > C is always in cis with c.641A > G. The spliceogenic effect of c.[594-2A > C;641A > G] was characterized using RNA analysis of human samples and splicing minigenes. As expected, c.[594-2A > C; 641A > G] caused exon 10 skipping, albeit not due to c.594-2A > C impairing the acceptor site but rather by c.641A > G modifying exon 10 splicing regulatory element(s). Multiple blood-based RNA assays indicated that the variant allele did not produce detectable levels of full-length transcripts, with a per allele BRCA1 expression profile composed of ≈70–80% truncating transcripts, and ≈20–30% of in-frame Δ9,10 transcripts predicted to encode a BRCA1 protein with tumor suppression function. We confirm that BRCA1c.[594-2A > C;641A > G] should not be considered a high-risk pathogenic variant. Importantly, results from our detailed mRNA analysis suggest that BRCA-associated cancer risk is likely not markedly increased for individuals who carry a truncating variant in BRCA1 exons 9 or 10, or any other BRCA1 allele that permits 20–30% of tumor suppressor function. More generally, our findings highlight the importance of assessing naturally occurring alternative splicing for clinical evaluation of variants in disease-causing genes. PMID:27008870

  11. Proposals for revival of Streptomyces setonii and reclassification of S. fimicarius as a later synonym of S. setonii and S. albovinaceus as a later synonym of S. globisporus based on combined 16S rRNA-gyrB gene analysis

    USDA-ARS?s Scientific Manuscript database

    The 16S rRNA and gyrB genes of 22 Streptomyces species belonging to the Streptomyces griseus cluster were sequenced, and their taxonomic positions were re-evaluated. For correct analysis, all of the publicly available sequences of the species were collected and compared with those obtained in this s...

  12. Drug Combinations: Tests and Analysis with Isoboles

    PubMed Central

    Tallarida, Ronald J.

    2016-01-01

    Described in this unit are experimental and computational methods to detect and classify drug interactions. In most cases this relates to two drugs or compounds with overtly similar effects, e.g., two analgesics or two anti-hypertensives. From the dose-response data of the individual drugs it is possible to generate a curve, the isobole, that defines all dose combinations that are expected to yield a specified effect. The theory underlying the isobole involves the calculation of doses of drug A that are effectively equivalent to doses of drug B with that equivalence determining whether the isobole is linear or nonlinear. In either case the isobole allows for a comparison with actual combination effects making it possible to determine whether the interaction is synergistic, additive or sub-additive. Actual as well as illustrative data are employed to illustrate experimental design and data analysis. PMID:26995550

  13. Bacterial reference genes for gene expression studies by RT-qPCR: survey and analysis.

    PubMed

    Rocha, Danilo J P; Santos, Carolina S; Pacheco, Luis G C

    2015-09-01

    The appropriate choice of reference genes is essential for accurate normalization of gene expression data obtained by the method of reverse transcription quantitative real-time PCR (RT-qPCR). In 2009, a guideline called the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) highlighted the importance of the selection and validation of more than one suitable reference gene for obtaining reliable RT-qPCR results. Herein, we searched the recent literature in order to identify the bacterial reference genes that have been most commonly validated in gene expression studies by RT-qPCR (in the first 5 years following publication of the MIQE guidelines). Through a combination of different search parameters with the text mining tool MedlineRanker, we identified 145 unique bacterial genes that were recently tested as candidate reference genes. Of these, 45 genes were experimentally validated and, in most of the cases, their expression stabilities were verified using the software tools geNorm and NormFinder. It is noteworthy that only 10 of these reference genes had been validated in two or more of the studies evaluated. An enrichment analysis using Gene Ontology classifications demonstrated that genes belonging to the functional categories of DNA Replication (GO: 0006260) and Transcription (GO: 0006351) rendered a proportionally higher number of validated reference genes. Three genes in the former functional class were also among the top five most stable genes identified through an analysis of gene expression data obtained from the Pathosystems Resource Integration Center. These results may provide a guideline for the initial selection of candidate reference genes for RT-qPCR studies in several different bacterial species.

  14. Integrated analysis of gene expression and methylation profiles of 48 candidate genes in breast cancer patients.

    PubMed

    Li, Zibo; Heng, Jianfu; Yan, Jinhua; Guo, Xinwu; Tang, Lili; Chen, Ming; Peng, Limin; Wu, Yepeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Wang, Jun

    2016-11-01

    Gene-specific methylation and expression have shown biological and clinical importance for breast cancer diagnosis and prognosis. Integrated analysis of gene methylation and gene expression may identify genes associated with biology mechanism and clinical outcome of breast cancer and aid in clinical management. Using high-throughput microfluidic quantitative PCR, we analyzed the expression profiles of 48 candidate genes in 96 Chinese breast cancer patients and investigated their correlation with gene methylation and associations with breast cancer clinical parameters. Breast cancer-specific gene expression alternation was found in 25 genes with significant expression difference between paired tumor and normal tissues. A total of 9 genes (CCND2, EGFR, GSTP1, PGR, PTGS2, RECK, SOX17, TNFRSF10D, and WIF1) showed significant negative correlation between methylation and gene expression, which were validated in the TCGA database. Total 23 genes (ACADL, APC, BRCA2, CADM1, CAV1, CCND2, CST6, EGFR, ESR2, GSTP1, ICAM5, NPY, PGR, PTGS2, RECK, RUNX3, SFRP1, SOX17, SYK, TGFBR2, TNFRSF10D, WIF1, and WRN) annotated with potential TFBSs in the promoter regions showed negative correlation between methylation and expression. In logistics regression analysis, 31 of the 48 genes showed improved performance in disease prediction with combination of methylation and expression coefficient. Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

  15. A combined approach exploring gene function based on Worm-Human Orthology

    PubMed Central

    Tamas, Ivica; Hodges, Emily; Dessi, Patrick; Johnsen, Robert; Vaz Gomes, Ana

    2005-01-01

    Background Many aspects of the nematode Caenorhabditis elegans biology are conserved between invertebrates and vertebrates establishing this particular organism as an excellent genetic model. Because of its small size, large populations and self-fertilization of the hermaphrodite, functional predictions carried out by genetic modifications as well as RNAi screens, can be rapidly tested. Results In order to explore the function of a set of C. elegans genes of unknown function, as well as their potential functional roles in the human genome, we performed a phylogenetic analysis to select the most probable worm orthologs. A total of 13 C. elegans genes were subjected to down- regulation via RNAi and characterization of expression profiles using GFP strains. Previously unknown distinct expression patterns were observed for four of the analyzed genes, as well as four visible RNAi phenotypes. In addition, subcellular protein over-expression profiles of the human orthologs for seven out of the thirteen genes using human cells were also analyzed. Conclusion By combining a whole-organism approach using C. elegans with complementary experimental work done on human cell lines, this analysis extends currently available information on the selected set of genes. PMID:15877817

  16. Gene therapy model of X-linked severe combined immunodeficiency using a modified foamy virus vector.

    PubMed

    Horino, Satoshi; Uchiyama, Toru; So, Takanori; Nagashima, Hiroyuki; Sun, Shu-Lan; Sato, Miki; Asao, Atsuko; Haji, Yoichi; Sasahara, Yoji; Candotti, Fabio; Tsuchiya, Shigeru; Kure, Shigeo; Sugamura, Kazuo; Ishii, Naoto

    2013-01-01

    X-linked severe combined immunodeficiency (SCID-X1) is an inherited genetic immunodeficiency associated with mutations in the common cytokine receptor γ chain (γc) gene, and characterized by a complete defect of T and natural killer (NK) cells. Gene therapy for SCID-X1 using conventional retroviral (RV) vectors carrying the γc gene results in the successful reconstitution of T cell immunity. However, the high incidence of vector-mediated T cell leukemia, caused by vector insertion near or within cancer-related genes has been a serious problem. In this study, we established a gene therapy model of mouse SCID-X1 using a modified foamy virus (FV) vector expressing human γc. Analysis of vector integration in a human T cell line demonstrated that the FV vector integration sites were significantly less likely to be located within or near transcriptional start sites than RV vector integration sites. To evaluate the therapeutic efficacy, bone marrow cells from γc-knockout (γc-KO) mice were infected with the FV vector and transplanted into γc-KO mice. Transplantation of the FV-treated cells resulted in the successful reconstitution of functionally active T and B cells. These data suggest that FV vectors can be effective and may be safer than conventional RV vectors for gene therapy for SCID-X1.

  17. Gene Therapy Model of X-linked Severe Combined Immunodeficiency Using a Modified Foamy Virus Vector

    PubMed Central

    Horino, Satoshi; Uchiyama, Toru; So, Takanori; Nagashima, Hiroyuki; Sun, Shu-lan; Sato, Miki; Asao, Atsuko; Haji, Yoichi; Sasahara, Yoji; Candotti, Fabio; Tsuchiya, Shigeru; Kure, Shigeo; Sugamura, Kazuo; Ishii, Naoto

    2013-01-01

    X-linked severe combined immunodeficiency (SCID-X1) is an inherited genetic immunodeficiency associated with mutations in the common cytokine receptor γ chain (γc) gene, and characterized by a complete defect of T and natural killer (NK) cells. Gene therapy for SCID-X1 using conventional retroviral (RV) vectors carrying the γc gene results in the successful reconstitution of T cell immunity. However, the high incidence of vector-mediated T cell leukemia, caused by vector insertion near or within cancer-related genes has been a serious problem. In this study, we established a gene therapy model of mouse SCID-X1 using a modified foamy virus (FV) vector expressing human γc. Analysis of vector integration in a human T cell line demonstrated that the FV vector integration sites were significantly less likely to be located within or near transcriptional start sites than RV vector integration sites. To evaluate the therapeutic efficacy, bone marrow cells from γc-knockout (γc-KO) mice were infected with the FV vector and transplanted into γc-KO mice. Transplantation of the FV-treated cells resulted in the successful reconstitution of functionally active T and B cells. These data suggest that FV vectors can be effective and may be safer than conventional RV vectors for gene therapy for SCID-X1. PMID:23990961

  18. 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

  19. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Gene set analysis using variance component tests.

    PubMed

    Huang, Yen-Tsung; Lin, Xihong

    2013-06-28

    Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data.

  1. Gene set analysis using variance component tests

    PubMed Central

    2013-01-01

    Background Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. Results We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). Conclusion We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data. PMID:23806107

  2. Iterative carotenogenic screens identify combinations of yeast gene deletions that enhance sclareol production.

    PubMed

    Trikka, Fotini A; Nikolaidis, Alexandros; Athanasakoglou, Anastasia; Andreadelli, Aggeliki; Ignea, Codruta; Kotta, Konstantia; Argiriou, Anagnostis; Kampranis, Sotirios C; Makris, Antonios M

    2015-04-24

    Terpenoids (isoprenoids) have numerous applications in flavors, fragrances, drugs and biofuels. The number of microbially produced terpenoids is increasing as new biosynthetic pathways are being elucidated. However, efforts to improve terpenoid production in yeast have mostly taken advantage of existing knowledge of the sterol biosynthetic pathway, while many additional factors may affect the output of the engineered system. Aiming to develop a yeast strain that can support high titers of sclareol, a diterpene of great importance for the perfume industry, we sought to identify gene deletions that improved carotenoid, and thus potentially sclareol, production. Using a carotenogenic screen, the best 100 deletion mutants, out of 4,700 mutant strains, were selected to create a subset for further analysis. To identify combinations of deletions that cooperate to further boost production, iterative carotenogenic screens were applied, and each time the top performing gene deletions were further ranked according to the number of genetic and physical interactions known for each specific gene. The gene selected in each round was deleted and the resulting strain was employed in a new round of selection. This approach led to the development of an EG60 derived haploid strain combining six deletions (rox1, dos2, yer134c, vba5, ynr063w and ygr259c) and exhibiting a 40-fold increase in carotenoid and 12-fold increase in sclareol titers, reaching 750 mg/L sclareol in shake flask cultivation. Using an iterative approach, we identified novel combinations of yeast gene deletions that improve carotenoid and sclareol production titers without compromising strain growth and viability. Most of the identified deletions have not previously been implicated in sterol pathway control. Applying the same approach using a different starting point could yield alternative sets of deletions with similar or improved outcome.

  3. FDR-FET: an optimizing gene set enrichment analysis method

    PubMed Central

    Ji, Rui-Ru; Ott, Karl-Heinz; Yordanova, Roumyana; Bruccoleri, Robert E

    2011-01-01

    Gene set enrichment analysis for analyzing large profiling and screening experiments can reveal unifying biological schemes based on previously accumulated knowledge represented as “gene sets”. Most of the existing implementations use a fixed fold-change or P value cutoff to generate regulated gene lists. However, the threshold selection in most cases is arbitrary, and has a significant effect on the test outcome and interpretation of the experiment. We developed a new gene set enrichment analysis method, ie, FDR-FET, which dynamically optimizes the threshold choice and improves the sensitivity and selectivity of gene set enrichment analysis. The procedure translates experimental results into a series of regulated gene lists at multiple false discovery rate (FDR) cutoffs, and computes the P value of the overrepresentation of a gene set using a Fisher’s exact test (FET) in each of these gene lists. The lowest P value is retained to represent the significance of the gene set. We also implemented improved methods to define a more relevant global reference set for the FET. We demonstrate the validity of the method using a published microarray study of three protease inhibitors of the human immunodeficiency virus and compare the results with those from other popular gene set enrichment analysis algorithms. Our results show that combining FDR with multiple cutoffs allows us to control the error while retaining genes that increase information content. We conclude that FDR-FET can selectively identify significant affected biological processes. Our method can be used for any user-generated gene list in the area of transcriptome, proteome, and other biological and scientific applications. PMID:21918636

  4. FDR-FET: an optimizing gene set enrichment analysis method.

    PubMed

    Ji, Rui-Ru; Ott, Karl-Heinz; Yordanova, Roumyana; Bruccoleri, Robert E

    2011-01-01

    Gene set enrichment analysis for analyzing large profiling and screening experiments can reveal unifying biological schemes based on previously accumulated knowledge represented as "gene sets". Most of the existing implementations use a fixed fold-change or P value cutoff to generate regulated gene lists. However, the threshold selection in most cases is arbitrary, and has a significant effect on the test outcome and interpretation of the experiment. We developed a new gene set enrichment analysis method, ie, FDR-FET, which dynamically optimizes the threshold choice and improves the sensitivity and selectivity of gene set enrichment analysis. The procedure translates experimental results into a series of regulated gene lists at multiple false discovery rate (FDR) cutoffs, and computes the P value of the overrepresentation of a gene set using a Fisher's exact test (FET) in each of these gene lists. The lowest P value is retained to represent the significance of the gene set. We also implemented improved methods to define a more relevant global reference set for the FET. We demonstrate the validity of the method using a published microarray study of three protease inhibitors of the human immunodeficiency virus and compare the results with those from other popular gene set enrichment analysis algorithms. Our results show that combining FDR with multiple cutoffs allows us to control the error while retaining genes that increase information content. We conclude that FDR-FET can selectively identify significant affected biological processes. Our method can be used for any user-generated gene list in the area of transcriptome, proteome, and other biological and scientific applications.

  5. 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.

  6. Combining Static Analysis and Model Checking for Software Analysis

    NASA Technical Reports Server (NTRS)

    Brat, Guillaume; Visser, Willem; Clancy, Daniel (Technical Monitor)

    2003-01-01

    We present an iterative technique in which model checking and static analysis are combined to verify large software systems. The role of the static analysis is to compute partial order information which the model checker uses to reduce the state space. During exploration, the model checker also computes aliasing information that it gives to the static analyzer which can then refine its analysis. The result of this refined analysis is then fed back to the model checker which updates its partial order reduction. At each step of this iterative process, the static analysis computes optimistic information which results in an unsafe reduction of the state space. However we show that the process converges to a fired point at which time the partial order information is safe and the whole state space is explored.

  7. Annotation of plant gene function via combined genomics, metabolomics and informatics.

    PubMed

    Tohge, Takayuki; Fernie, Alisdair R

    2012-06-17

    Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as knockout mutants, wild accessions and advanced breeding populations, there is a rising burden for gene functional annotation. In this protocol, annotation of plant gene function using combined co-expression gene analysis, metabolomics and informatics is provided (Figure 1). This approach is based on the theory of using target genes of known function to allow the identification of non-annotated genes likely to be involved in a certain metabolic process, with the identification of target compounds via metabolomics. Strategies are put forward for applying this information on populations generated by both forward and reverse genetics approaches in spite of none of these are effortless. By corollary this approach can also be used as an approach to characterise unknown peaks representing new or specific secondary metabolites in the limited tissues, plant species or stress treatment, which is currently the important trial to understanding plant metabolism.

  8. Combined Arms Training Program Cost Analysis.

    DTIC Science & Technology

    1980-12-01

    Air Ground Combat Center is tasked with the mission of developing , administering, and evaluating the Marine Corps Combined Arms Training Program. The...Marine Corps Air Ground Combat Center is tasked with the mission of developing , administering, and evaluating the Marine Corps Combined Arms Training...Combined Arms Exercises (CAX). It has the mission of developing , administering, and evaluating the Combined Arms Training Program (CATP) [13:1]. A CAX is

  9. Knowledge-guided gene ranking by coordinative component analysis.

    PubMed

    Wang, Chen; Xuan, Jianhua; Li, Huai; Wang, Yue; Zhan, Ming; Hoffman, Eric P; Clarke, Robert

    2010-03-30

    In cancer, gene networks and pathways often exhibit dynamic behavior, particularly during the process of carcinogenesis. Thus, it is important to prioritize those genes that are strongly associated with the functionality of a network. Traditional statistical methods are often inept to identify biologically relevant member genes, motivating researchers to incorporate biological knowledge into gene ranking methods. However, current integration strategies are often heuristic and fail to incorporate fully the true interplay between biological knowledge and gene expression data. To improve knowledge-guided gene ranking, we propose a novel method called coordinative component analysis (COCA) in this paper. COCA explicitly captures those genes within a specific biological context that are likely to be expressed in a coordinative manner. Formulated as an optimization problem to maximize the coordinative effort, COCA is designed to first extract the coordinative components based on a partial guidance from knowledge genes and then rank the genes according to their participation strengths. An embedded bootstrapping procedure is implemented to improve statistical robustness of the solutions. COCA was initially tested on simulation data and then on published gene expression microarray data to demonstrate its improved performance as compared to traditional statistical methods. Finally, the COCA approach has been applied to stem cell data to identify biologically relevant genes in signaling pathways. As a result, the COCA approach uncovers novel pathway members that may shed light into the pathway deregulation in cancers. We have developed a new integrative strategy to combine biological knowledge and microarray data for gene ranking. The method utilizes knowledge genes for a guidance to first extract coordinative components, and then rank the genes according to their contribution related to a network or pathway. The experimental results show that such a knowledge-guided strategy

  10. Screening of susceptibility genes and multi-gene risk analysis in gastric cancer.

    PubMed

    Shen, Xiao-bing; Wang, Jia; Li, Peng-fei; Ren, Xiao-feng; Yan, Xiao-luan; Wang, Fan

    2014-10-01

    The aim of the study was to explore the relations between the genetic polymorphism and the susceptibility to the gastric cancer in Chinese Han population, and to analyze the multi-genes risk in the development of gastric carcinoma. A case-control study of 1:1 matching was performed on 564 individuals with primary gastric carcinoma in Nanjing, China. The genotypes of CYP2E1, GSTMl, GSTTl, NAT2, ALDH2, MTHFR, XRCCl, IL-1β, VDR, and TNF were detected by molecular biological techniques (PCR-RFLP and AS-PCR). Sole gene and gene-gene interactions were analyzed using Logistic regression model. The effect of multi-genes on gastric carcinoma was analyzed using multi-gene risk analysis model, which focused on the effect of multi-gene interaction on the development of gastric carcinoma. The genotypes involved in the susceptibility of gastric carcinoma were CYP2E1(c1/c1), NAT2M1(T/T), NAT2M2(A/A), XRCC1194(T/T), NAT2 phenotype (slow acetylator), MTHFR1298(A/C), and VDR TaqI(T/T), respectively. Multi-gene risk analysis model was introduced to analyze the effect of these genes on the gastric carcinoma. The results showed that there was a strong relation between odds ratio (OR) value of polygene combination and the gene frequency. With the increase of susceptibility gene frequency, the risk distribution curve of gastric carcinoma would shift to a more dangerous phase and exhibit a quantitative relation. Our results demonstrated that the OR of each gene can be utilized as an index to assess the effect of multiple susceptible genes on the occurrence of gastric carcinoma.

  11. Gene Ontology density estimation and discourse analysis for automatic GeneRiF extraction.

    PubMed

    Gobeill, Julien; Tbahriti, Imad; Ehrler, Frédéric; Mottaz, Anaïs; Veuthey, Anne-Lise; Ruch, Patrick

    2008-04-11

    This paper describes and evaluates a sentence selection engine that extracts a GeneRiF (Gene Reference into Functions) as defined in ENTREZ-Gene based on a MEDLINE record. Inputs for this task include both a gene and a pointer to a MEDLINE reference. In the suggested approach we merge two independent sentence extraction strategies. The first proposed strategy (LASt) uses argumentative features, inspired by discourse-analysis models. The second extraction scheme (GOEx) uses an automatic text categorizer to estimate the density of Gene Ontology categories in every sentence; thus providing a full ranking of all possible candidate GeneRiFs. A combination of the two approaches is proposed, which also aims at reducing the size of the selected segment by filtering out non-content bearing rhetorical phrases. Based on the TREC-2003 Genomics collection for GeneRiF identification, the LASt extraction strategy is already competitive (52.78%). When used in a combined approach, the extraction task clearly shows improvement, achieving a Dice score of over 57% (+10%). Argumentative representation levels and conceptual density estimation using Gene Ontology contents appear complementary for functional annotation in proteomics.

  12. Gene Ontology density estimation and discourse analysis for automatic GeneRiF extraction

    PubMed Central

    Gobeill, Julien; Tbahriti, Imad; Ehrler, Frédéric; Mottaz, Anaïs; Veuthey, Anne-Lise; Ruch, Patrick

    2008-01-01

    Background This paper describes and evaluates a sentence selection engine that extracts a GeneRiF (Gene Reference into Functions) as defined in ENTREZ-Gene based on a MEDLINE record. Inputs for this task include both a gene and a pointer to a MEDLINE reference. In the suggested approach we merge two independent sentence extraction strategies. The first proposed strategy (LASt) uses argumentative features, inspired by discourse-analysis models. The second extraction scheme (GOEx) uses an automatic text categorizer to estimate the density of Gene Ontology categories in every sentence; thus providing a full ranking of all possible candidate GeneRiFs. A combination of the two approaches is proposed, which also aims at reducing the size of the selected segment by filtering out non-content bearing rhetorical phrases. Results Based on the TREC-2003 Genomics collection for GeneRiF identification, the LASt extraction strategy is already competitive (52.78%). When used in a combined approach, the extraction task clearly shows improvement, achieving a Dice score of over 57% (+10%). Conclusions Argumentative representation levels and conceptual density estimation using Gene Ontology contents appear complementary for functional annotation in proteomics. PMID:18426554

  13. Analysis of multiwavelength coherent beam combining effect.

    PubMed

    Kai, Han; Xiaojun, Xu; Zejin, Liu

    2012-12-01

    The combination effect of multiwavelength active coherent beam combination (CBC) is investigated theoretically. The dependence of the combination effect on the optical path control precision, spectral width, wavelength number, and channel number is revealed. In the case of small optical path variance, the combination effect approximately decreases in quadratic form with wavelength number N, spectral width Δν, and optical path variance σ increasing. In the case of large optical path variance, the combination effect is independent of the optical path variance and the spectral width. The larger the wavelength number is, the smaller the Strehl ratio expectation is, and it finally degenerates to the incoherent combination. The necessity of optical path control is discussed. This study is helpful for multiwavelength CBC system design and the combination effect estimation.

  14. PRGdb: a bioinformatics platform for plant resistance gene analysis

    PubMed Central

    Sanseverino, Walter; Roma, Guglielmo; De Simone, Marco; Faino, Luigi; Melito, Sara; Stupka, Elia; Frusciante, Luigi; Ercolano, Maria Raffaella

    2010-01-01

    PRGdb is a web accessible open-source (http://www.prgdb.org) database that represents the first bioinformatic resource providing a comprehensive overview of resistance genes (R-genes) in plants. PRGdb holds more than 16 000 known and putative R-genes belonging to 192 plant species challenged by 115 different pathogens and linked with useful biological information. The complete database includes a set of 73 manually curated reference R-genes, 6308 putative R-genes collected from NCBI and 10463 computationally predicted putative R-genes. Thanks to a user-friendly interface, data can be examined using different query tools. A home-made prediction pipeline called Disease Resistance Analysis and Gene Orthology (DRAGO), based on reference R-gene sequence data, was developed to search for plant resistance genes in public datasets such as Unigene and Genbank. New putative R-gene classes containing unknown domain combinations were discovered and characterized. The development of the PRG platform represents an important starting point to conduct various experimental tasks. The inferred cross-link between genomic and phenotypic information allows access to a large body of information to find answers to several biological questions. The database structure also permits easy integration with other data types and opens up prospects for future implementations. PMID:19906694

  15. PRISMA-combined Myeloperoxidase -463G/A gene polymorphism and coronary artery disease

    PubMed Central

    Li, Yan-Yan; Wang, Hui; Qian, Jin; Kim, Hyun Jun; Wu, Jing-jing; Wang, Lian-sheng; Zhou, Chuan-wei; Yang, Zhi-Jian; Lu, Xin-Zheng

    2017-01-01

    Abstract Background: Myeloperoxidase (MPO) -463G/A gene polymorphism may be associated with an increased risk of developing coronary artery disease (CAD). Studies on the subject, however, do not provide a clear consensus. This meta-analysis was performed to explore the relationship between MPO gene -463G/A polymorphism and CAD risk. Methods: This meta-analysis combines data from 4744 subjects from 9 independent studies. By using fixed or random effect models, the pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were assessed. Results: Our analysis found a significant association between MPO gene -463G/A polymorphism and CAD in the whole population under all genetic models: allelic (OR: 0.68, 95% CI: 0.54–0.85, P = 0.0009), recessive (OR: 0.41, 95% CI: 0.22–0.76, P = 0.005), dominant (OR: 0.682, 95% CI: 0.534–0.871, P = 0.002), homozygous (OR: 0.36, 95% CI: 0.16–0.79, P = 0.01), heterozygous genetic model (OR: 0.832, 95% CI: 0.733–0.945, P = 0.004), and additive (OR: 0.64, 95% CI: 0.46–0.90, P = 0.01), especially in the Chinese subgroup (P < 0.05). On the contrary, we found no such relationship in the non-Chinese subgroup (P > 0.05). Conclusion: The MPO gene -463G/A polymorphism is associated with CAD risk, especially within the Chinese population. The A allele of MPO gene -463G/A polymorphism might protect the people from suffering the CAD risk. PMID:28328864

  16. Sequence analysis of porothramycin biosynthetic gene cluster.

    PubMed

    Najmanova, Lucie; Ulanova, Dana; Jelinkova, Marketa; Kamenik, Zdenek; Kettnerova, Eliska; Koberska, Marketa; Gazak, Radek; Radojevic, Bojana; Janata, Jiri

    2014-11-01

    The biosynthetic gene cluster of porothramycin, a sequence-selective DNA alkylating compound, was identified in the genome of producing strain Streptomyces albus subsp. albus (ATCC 39897) and sequentially characterized. A 39.7 kb long DNA region contains 27 putative genes, 18 of them revealing high similarity with homologous genes from biosynthetic gene cluster of closely related pyrrolobenzodiazepine (PBD) compound anthramycin. However, considering the structures of both compounds, the number of differences in the gene composition of compared biosynthetic gene clusters was unexpectedly high, indicating participation of alternative enzymes in biosynthesis of both porothramycin precursors, anthranilate, and branched L-proline derivative. Based on the sequence analysis of putative NRPS modules Por20 and Por21, we suppose that in porothramycin biosynthesis, the methylation of anthranilate unit occurs prior to the condensation reaction, while modifications of branched proline derivative, oxidation, and dimethylation of the side chain occur on already condensed PBD core. Corresponding two specific methyltransferase encoding genes por26 and por25 were identified in the porothramycin gene cluster. Surprisingly, also methyltransferase gene por18 homologous to orf19 from anthramycin biosynthesis was detected in porothramycin gene cluster even though the appropriate biosynthetic step is missing, as suggested by ultra high-performance liquid chromatography-diode array detection-mass spectrometry (UHPLC-DAD-MS) analysis of the product in the S. albus culture broth.

  17. Functional analysis of the human neurofilament light chain gene promoter.

    PubMed Central

    Yazdanbakhsh, K; Fraser, P; Kioussis, D; Vidal, M; Grosveld, F; Lindenbaum, M

    1993-01-01

    We have carried out a structural and functional analysis on the human NF-L (H-NF-L) gene. It contains a methylation-free island, spanning the 5' flanking sequences and the first exon and a number of neuronal-specific DNase I hypersensitive sites have been identified in the upstream region as well as within the body of the gene. Analysis in cell lines and transgenic mice using a combination of these sites has revealed the presence of a conserved element(s) between -300bp and -190bp which is required for neuronal-specific expression. Images PMID:8441658

  18. Analysis of soybean flowering-time genes

    USDA-ARS?s Scientific Manuscript database

    Control of soybean flowering time is important for geographic adaptation, and maximizing yield. RT-PCR analysis was performed using primers synthesized for a number of putative flowering-time genes based on homology of soybean EST and genomic sequences to Arabidopsis genes. RNA for cDNA synthesis ...

  19. Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis.

    PubMed

    Lee, Won Jun; Kim, Sang Cheol; Yoon, Jung-Ho; Yoon, Sang Jun; Lim, Johan; Kim, You-Sun; Kwon, Sung Won; Park, Jeong Hill

    2016-01-01

    Generally, cancer stem cells have epithelial-to-mesenchymal-transition characteristics and other aggressive properties that cause metastasis. However, there have been no confident markers for the identification of cancer stem cells and comparative methods examining adherent and sphere cells are widely used to investigate mechanism underlying cancer stem cells, because sphere cells have been known to maintain cancer stem cell characteristics. In this study, we conducted a meta-analysis that combined gene expression profiles from several studies that utilized tumorsphere technology to investigate tumor stem-like breast cancer cells. We used our own gene expression profiles along with the three different gene expression profiles from the Gene Expression Omnibus, which we combined using the ComBat method, and obtained significant gene sets using the gene set analysis of our datasets and the combined dataset. This experiment focused on four gene sets such as cytokine-cytokine receptor interaction that demonstrated significance in both datasets. Our observations demonstrated that among the genes of four significant gene sets, six genes were consistently up-regulated and satisfied the p-value of < 0.05, and our network analysis showed high connectivity in five genes. From these results, we established CXCR4, CXCL1 and HMGCS1, the intersecting genes of the datasets with high connectivity and p-value of < 0.05, as significant genes in the identification of cancer stem cells. Additional experiment using quantitative reverse transcription-polymerase chain reaction showed significant up-regulation in MCF-7 derived sphere cells and confirmed the importance of these three genes. Taken together, using meta-analysis that combines gene set and network analysis, we suggested CXCR4, CXCL1 and HMGCS1 as candidates involved in tumor stem-like breast cancer cells. Distinct from other meta-analysis, by using gene set analysis, we selected possible markers which can explain the biological

  20. Autistic behavior, behavior analysis, and the gene

    PubMed Central

    Malott, Richard W.

    2004-01-01

    This article addresses the meaning of autism, the etiology of autistic behavior and values, the nature-nurture debate, contingencies vs. genes, and resistance to a behavioral analysis of autism. PMID:22477285

  1. Analysis of PTCH/SMO/SHH pathway genes in medulloblastoma.

    PubMed

    Zurawel, R H; Allen, C; Chiappa, S; Cato, W; Biegel, J; Cogen, P; de Sauvage, F; Raffel, C

    2000-01-01

    Inactivation of the PTCH tumor suppressor gene occurs in a subset of sporadic medulloblastomas, suggesting that alterations in the PTCH pathway may be important in the development of this tumor. In order to address the frequency of genetic alterations affecting genes in this pathway, we used a combination of loss of heterozygosity (LOH) analysis, single-stranded conformational polymorphism (SSCP) analysis, and direct sequencing of DNA samples from sporadic primitive neuroectodermal tumors (PNETs). To identify alterations in the PTCH gene, we performed LOH analysis on 37 tumor DNA samples. Of those with matched constitutional DNA samples, one demonstrated LOH. Of those without matched constitutional DNA, six were homozygous with all markers. All exons of the PTCH gene were sequenced in these seven tumors, and three mutations were found. To identify alterations in the SHH and SMO genes, we analyzed all exons of both genes in 24 tumors with SSCP and sequenced any exons that showed aberrant band patterns. No mutations were found in either SHH or SMO in any tumor. We also identified the following genes as candidate tumor suppressors based on their roles in controlling hh/ptc signaling in Drosophila: EN-1 and EN-2, deletion of which results in a lack of cerebellar development in mice; SMAD family members 1-7, and protein kinase A subunits RIalpha, RIbeta, RIIbeta, Calpha, and Cbeta. Each of these genes was investigated in a panel of 24 matched constitutional and tumor DNA samples. Our search revealed no mutations in any of these genes. Thus, PTCH is the only gene in this complex pathway that is mutated with notable frequency in PNET. Genes Chromosomes Cancer 27:44-51, 2000.

  2. Comparative analysis of hepatocellular carcinoma and cirrhosis gene expression profiles

    PubMed Central

    Jiang, Mingming; Zeng, Qingfang; Dai, Suiping; Liang, Huixia; Dai, Fengying; Xie, Xueling; Lu, Kunlin; Gao, Chunfang

    2017-01-01

    Gene expression data of hepatocellular carcinoma (HCC) was compared with that of cirrhosis (C) to identify critical genes in HCC. A total of five gene expression data sets were downloaded from Gene Expression Omnibus. HCC and healthy samples were combined as dataset HCC, whereas cirrhosis samples were included in dataset C. A network was constructed for dataset HCC with the package R for performing Weighted Gene Co-expression Network Analysis. Modules were identified by cluster analysis with the packages flashClust and dynamicTreeCut. Hub genes were screened out by calculating connectivity. Functional annotations were assigned to the hub genes using the Database for Annotation, Visualization and Integration Discovery, and functional annotation networks were visualized with Cytoscape. Following the exclusion of outlier samples, 394 HCC samples and 47 healthy samples were included in dataset HCC and 233 cirrhosis samples were included in dataset C. A total of 6 modules were identified in the weighted gene co-expression network of dataset HCC (blue, brown, turquoise, green, red and yellow). Modules blue, brown and turquoise had high preservation whereas module yellow exhibited the lowest preservation. These modules were associated with transcription, mitosis, cation transportation, cation homeostasis, secretion and regulation of cyclase activity. Various hub genes of module yellow were cytokines, including chemokine (C-C motif) ligand 22 and interleukin-19, which may be important in the development of HCC. Gene expression profiles of HCC were compared with those of cirrhosis and numerous critical genes were identified, which may contribute to the progression of HCC. Further studies on these genes may improve the understanding of HCC pathogenesis. PMID:27959423

  3. Comparative analysis of hepatocellular carcinoma and cirrhosis gene expression profiles.

    PubMed

    Jiang, Mingming; Zeng, Qingfang; Dai, Suiping; Liang, Huixia; Dai, Fengying; Xie, Xueling; Lu, Kunlin; Gao, Chunfang

    2017-01-01

    Gene expression data of hepatocellular carcinoma (HCC) was compared with that of cirrhosis (C) to identify critical genes in HCC. A total of five gene expression data sets were downloaded from Gene Expression Omnibus. HCC and healthy samples were combined as dataset HCC, whereas cirrhosis samples were included in dataset C. A network was constructed for dataset HCC with the package R for performing Weighted Gene Co‑expression Network Analysis. Modules were identified by cluster analysis with the packages flashClust and dynamicTreeCut. Hub genes were screened out by calculating connectivity. Functional annotations were assigned to the hub genes using the Database for Annotation, Visualization and Integration Discovery, and functional annotation networks were visualized with Cytoscape. Following the exclusion of outlier samples, 394 HCC samples and 47 healthy samples were included in dataset HCC and 233 cirrhosis samples were included in dataset C. A total of 6 modules were identified in the weighted gene co‑expression network of dataset HCC (blue, brown, turquoise, green, red and yellow). Modules blue, brown and turquoise had high preservation whereas module yellow exhibited the lowest preservation. These modules were associated with transcription, mitosis, cation transportation, cation homeostasis, secretion and regulation of cyclase activity. Various hub genes of module yellow were cytokines, including chemokine (C‑C motif) ligand 22 and interleukin‑19, which may be important in the development of HCC. Gene expression profiles of HCC were compared with those of cirrhosis and numerous critical genes were identified, which may contribute to the progression of HCC. Further studies on these genes may improve the understanding of HCC pathogenesis.

  4. Combined gene and stem cell therapy for cutaneous wound healing.

    PubMed

    Gauglitz, Gerd G; Jeschke, Marc G

    2011-10-03

    In current medical practice, wound therapy remains a clinical challenge and much effort has been focused on the development of novel therapeutic approaches for wound treatment. Gene therapy, initially developed for treatment of congenital defects, represents a promising option for enhancing wound repair. In order to accelerate wound closure, genes encoding for growth factors or cytokines have shown the most potential. The majority of gene delivery systems are based on viral transfection, naked DNA application, high pressure injection, and liposomal vectors. Besides advances stemming from breakthroughs in recombinant growth factors and bioengineered skin, there has been a significant increase in the understanding of stem cell biology in the field of cutaneous wound healing. A variety of sources, such as bone marrow, umbilical cord blood, adipose tissue and skin/hair follicles, have been utilized to isolate stem cells and to modulate the healing response of acute and chronic wounds. Recent data have demonstrated the feasibility of autologous adult stem cell therapy in cutaneous repair and regeneration. Very recently, stem cell based skin engineering in conjunction with gene recombination, in which the stem cells act as both the seed cells and the vehicle for gene delivery to the wound site, represents the most attractive field for generating a regenerative strategy for wound therapy. The aim of this article is to discuss the use and the potential of these novel technologies in order to improve wound healing capacities.

  5. Reliability analysis of RC containment structures under combined loads

    SciTech Connect

    Hwang, H.; Reich, M.; Kagami, S.

    1984-01-01

    This paper discusses a reliability analysis method and load combination design criteria for reinforced concrete containment structures under combined loads. The probability based reliability analysis method is briefly described. For load combination design criteria, derivations of the load factors for accidental pressure due to a design basis accident and safe shutdown earthquake (SSE) for three target limit state probabilities are presented.

  6. Gene expression changes in peripheral mononuclear cells from schizophrenic patients treated with a combination of antipsychotic with fluvoxamine.

    PubMed

    Chertkow, Yael; Weinreb, Orly; Youdim, Moussa B H; Silver, Henry

    2007-10-01

    Antipsychotic treatment combined with Selective Serotonin Reuptake Inhibitor (SSRI) antidepressant can improve negative symptoms in schizophrenic patients that are unresponsive to antipsychotic drugs alone. The mechanism of this therapeutic effect is not clear. The current study examined molecular changes induced by the combined treatment in human peripheral mononuclear cells (PMC) in order to get insight into its mechanism of action. Gene expression profile of PMC from antipsychotic-treated patients was examined before addition of the SSRI fluvoxamine, and 3 and 6 weeks after. Gene expression patterns screened with a cDNA array, comprising 1176 genes, revealed homologous changes in a range of transcripts related to G-protein coupled receptors (GPCR). Genes related to GPCR-family were assayed using customized cDNA array and the results verified by real-time RT-PCR. The mRNA expression of chemokine receptors, IL8RA and CCR1, and of RGS7 was significantly down-regulated following fluvoxamine augmentation. The clinical assessments showed improvement in negative symptoms following the combined treatment. The transcriptional analysis suggests that the therapeutic mechanism of the combined antipsychotic-fluvoxamine treatment may involve genes associated with G-protein coupled receptors (GPCR). Our findings suggest that gene expression changes in PMC may be useful in investigating the mechanism of drug action in schizophrenia.

  7. Combined effects of ionizing radiation and cycloheximide on gene expression

    SciTech Connect

    Woloschak, G.E.; Felcher, P.; Chang-Liu, Chin-Mei

    1993-11-01

    Experiments were done to determine the effects of ionizing radiation exposure on expression of genes following exposure of Syrian hamster embryo (SHE) cells to the protein synthesis inhibitor cycloheximide (including such genes as {beta}-actin, c-fos, H4-histone, c-myc, c-jun, Rb, and p53). Results revealed that when ionizing radiations (either fission-spectrum neutrons or {gamma}-rays) were administered 15 min following the cycloheximide treatment of SHE cells, the radiation exposure reduced cycloheximide-mediated gene induction for most of the induced genes studied (c-fos, H4-histone, c-jun) In addition, dose-rate differences were found when radiation exposure most significantly inhibited the cycloheximide response. Our results suggest (1) that ionizing radiation does not act as a general protein synthesis inhibitor and (2) that the presence of a labile (metastable) protein is required for the maintenance of transcription and mRNA accumulation following radiation exposure, especially for radiation administered at high dose-rates.

  8. Structural changes and differentially expressed genes in Pseudomonas aeruginosa exposed to meropenem-ciprofloxacin combination.

    PubMed

    Siqueira, Vera Lúcia Dias; Cardoso, Rosilene Fressatti; Caleffi-Ferracioli, Katiany Rizzieri; Scodro, Regiane Bertin de Lima; Fernandez, Maria Aparecida; Fiorini, Adriana; Ueda-Nakamura, Tania; Dias-Filho, Benedito Prado; Nakamura, Celso Vataru

    2014-07-01

    The effect of a meropenem-ciprofloxacin combination (MCC) on the susceptibility of multidrug-resistant (MDR) Pseudomonas aeruginosa (MRPA) clinical isolates was determined using checkerboard and time-kill curve techniques. Structural changes and differential gene expression that resulted from the synergistic action of the MCC against one of the P. aeruginosa isolates (1071-MRPA]) were evaluated using electron microscopy and representational difference analysis (RDA), respectively. The differentially expressed, SOS response-associated, and resistance-associated genes in 1071-MRPA exposed to meropenem, ciprofloxacin, and the MCC were monitored by quantitative PCR. The MCC was synergistic against 25% and 40.6% of MDR P. aeruginosa isolates as shown by the checkerboard and time-kill curves, respectively. The morphological and structural changes that resulted from the synergistic action of the MCC against 1071-MRPA were a summation of the effects observed with each antimicrobial alone. One exception included outer membrane vesicles, which were seen in a greater amount upon ciprofloxacin exposure but were significantly inhibited upon MCC exposure. Cell wall- and DNA repair-associated genes were differentially expressed in 1071-MRPA exposed to meropenem, ciprofloxacin, and the MCC. However, some of the RDA-detected, resistance-associated, and SOS response-associated genes were expressed at significantly lower levels in 1071-MRPA exposed to the MCC. The MCC may be an alternative for the treatment of MDR P. aeruginosa. The effect of this antimicrobial combination may be not only the result of a summation of the effects of meropenem and ciprofloxacin but also a result of differential action that likely inhibits protective mechanisms in the bacteria. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

  9. Structural Changes and Differentially Expressed Genes in Pseudomonas aeruginosa Exposed to Meropenem-Ciprofloxacin Combination

    PubMed Central

    Siqueira, Vera Lúcia Dias; Cardoso, Rosilene Fressatti; Caleffi-Ferracioli, Katiany Rizzieri; de Lima Scodro, Regiane Bertin; Fernandez, Maria Aparecida; Fiorini, Adriana; Ueda-Nakamura, Tania; Dias-Filho, Benedito Prado

    2014-01-01

    The effect of a meropenem-ciprofloxacin combination (MCC) on the susceptibility of multidrug-resistant (MDR) Pseudomonas aeruginosa (MRPA) clinical isolates was determined using checkerboard and time-kill curve techniques. Structural changes and differential gene expression that resulted from the synergistic action of the MCC against one of the P. aeruginosa isolates (1071-MRPA]) were evaluated using electron microscopy and representational difference analysis (RDA), respectively. The differentially expressed, SOS response-associated, and resistance-associated genes in 1071-MRPA exposed to meropenem, ciprofloxacin, and the MCC were monitored by quantitative PCR. The MCC was synergistic against 25% and 40.6% of MDR P. aeruginosa isolates as shown by the checkerboard and time-kill curves, respectively. The morphological and structural changes that resulted from the synergistic action of the MCC against 1071-MRPA were a summation of the effects observed with each antimicrobial alone. One exception included outer membrane vesicles, which were seen in a greater amount upon ciprofloxacin exposure but were significantly inhibited upon MCC exposure. Cell wall- and DNA repair-associated genes were differentially expressed in 1071-MRPA exposed to meropenem, ciprofloxacin, and the MCC. However, some of the RDA-detected, resistance-associated, and SOS response-associated genes were expressed at significantly lower levels in 1071-MRPA exposed to the MCC. The MCC may be an alternative for the treatment of MDR P. aeruginosa. The effect of this antimicrobial combination may be not only the result of a summation of the effects of meropenem and ciprofloxacin but also a result of differential action that likely inhibits protective mechanisms in the bacteria. PMID:24798291

  10. Analysis of cascading failure in gene networks.

    PubMed

    Sun, Longxiao; Wang, Shudong; Li, Kaikai; Meng, Dazhi

    2012-01-01

    It is an important subject to research the functional mechanism of cancer-related genes make in formation and development of cancers. The modern methodology of data analysis plays a very important role for deducing the relationship between cancers and cancer-related genes and analyzing functional mechanism of genome. In this research, we construct mutual information networks using gene expression profiles of glioblast and renal in normal condition and cancer conditions. We investigate the relationship between structure and robustness in gene networks of the two tissues using a cascading failure model based on betweenness centrality. Define some important parameters such as the percentage of failure nodes of the network, the average size-ratio of cascading failure, and the cumulative probability of size-ratio of cascading failure to measure the robustness of the networks. By comparing control group and experiment groups, we find that the networks of experiment groups are more robust than that of control group. The gene that can cause large scale failure is called structural key gene. Some of them have been confirmed to be closely related to the formation and development of glioma and renal cancer respectively. Most of them are predicted to play important roles during the formation of glioma and renal cancer, maybe the oncogenes, suppressor genes, and other cancer candidate genes in the glioma and renal cancer cells. However, these studies provide little information about the detailed roles of identified cancer genes.

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

    PubMed

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

    2017-01-21

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

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

    PubMed Central

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

    2017-01-01

    We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues. PMID:28117714

  13. Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets

    PubMed Central

    Xiong, Qing; Ancona, Nicola; Hauser, Elizabeth R.; Mukherjee, Sayan; Furey, Terrence S.

    2012-01-01

    Single variant or single gene analyses generally account for only a small proportion of the phenotypic variation in complex traits. Alternatively, gene set or pathway association analyses are playing an increasingly important role in uncovering genetic architectures of complex traits through the identification of systematic genetic interactions. Two dominant paradigms for gene set analyses are association analyses based on SNP genotypes and those based on gene expression profiles. However, gene–disease association can manifest in many ways, such as alterations of gene expression, genotype, and copy number; thus, an integrative approach combining multiple forms of evidence can more accurately and comprehensively capture pathway associations. We have developed a single statistical framework, Gene Set Association Analysis (GSAA), that simultaneously measures genome-wide patterns of genetic variation and gene expression variation to identify sets of genes enriched for differential expression and/or trait-associated genetic markers. Simulation studies illustrate that joint analyses of genomic data increase the power to detect real associations when compared with gene set methods that use only one genomic data type. The analysis of two human diseases, glioblastoma and Crohn's disease, detected abnormalities in previously identified disease-associated pathways, such as pathways related to PI3K signaling, DNA damage response, and the activation of NFKB. In addition, GSAA predicted novel pathway associations, for example, differential genetic and expression characteristics in genes from the ABC transporter family in glioblastoma and from the HLA system in Crohn's disease. These demonstrate that GSAA can help uncover biological pathways underlying human diseases and complex traits. PMID:21940837

  14. Identification of oral cancer related candidate genes by integrating protein-protein interactions, gene ontology, pathway analysis and immunohistochemistry.

    PubMed

    Kumar, Ravindra; Samal, Sabindra K; Routray, Samapika; Dash, Rupesh; Dixit, Anshuman

    2017-05-30

    In the recent years, bioinformatics methods have been reported with a high degree of success for candidate gene identification. In this milieu, we have used an integrated bioinformatics approach assimilating information from gene ontologies (GO), protein-protein interaction (PPI) and network analysis to predict candidate genes related to oral squamous cell carcinoma (OSCC). A total of 40973 PPIs were considered for 4704 cancer-related genes to construct human cancer gene network (HCGN). The importance of each node was measured in HCGN by ten different centrality measures. We have shown that the top ranking genes are related to a significantly higher number of diseases as compared to other genes in HCGN. A total of 39 candidate oral cancer target genes were predicted by combining top ranked genes and the genes corresponding to significantly enriched oral cancer related GO terms. Initial verification using literature and available experimental data indicated that 29 genes were related with OSCC. A detailed pathway analysis led us to propose a role for the selected candidate genes in the invasion and metastasis in OSCC. We further validated our predictions using immunohistochemistry (IHC) and found that the gene FLNA was upregulated while the genes ARRB1 and HTT were downregulated in the OSCC tissue samples.

  15. EST analysis reveals putative genes involved in glycyrrhizin biosynthesis

    PubMed Central

    2010-01-01

    Background Glycyrrhiza uralensis is one of the most popular medicinal plants in the world and is also widely used in the flavoring of food and tobacco. Due to limited genomic and transcriptomic data, the biosynthetic pathway of glycyrrhizin, the major bioactive compound in G. uralensis, is currently unclear. Identification of candidate genes involved in the glycyrrhizin biosynthetic pathway will significantly contribute to the understanding of the biosynthetic and medicinal chemistry of this compound. Results We used the 454 GS FLX platform and Titanium regents to produce a substantial expressed sequence tag (EST) dataset from the vegetative organs of G. uralensis. A total of 59,219 ESTs with an average read length of 409 bp were generated. 454 ESTs were combined with the 50,666 G. uralensis ESTs in GenBank. The combined ESTs were assembled into 27,229 unique sequences (11,694 contigs and 15,535 singletons). A total of 20,437 unique gene elements representing approximately 10,000 independent transcripts were annotated using BLAST searches (e-value ≤ 1e-5) against the SwissProt, KEGG, TAIR, Nr and Nt databases. The assembled sequences were annotated with gene names and Gene Ontology (GO) terms. With respect to the genes related to glycyrrhizin metabolism, genes encoding 16 enzymes of the 18 total steps of the glycyrrhizin skeleton synthesis pathway were found. To identify novel genes that encode cytochrome P450 enzymes and glycosyltransferases, which are related to glycyrrhizin metabolism, a total of 125 and 172 unigenes were found to be homologous to cytochrome P450s and glycosyltransferases, respectively. The cytochrome P450 candidate genes were classified into 32 CYP families, while the glycosyltransferase candidate genes were classified into 45 categories by GO analysis. Finally, 3 cytochrome P450 enzymes and 6 glycosyltransferases were selected as the candidates most likely to be involved in glycyrrhizin biosynthesis through an organ-specific expression

  16. Combined Gene Expression and RNAi Screening to Identify Alkylation Damage Survival Pathways from Fly to Human.

    PubMed

    Zanotto-Filho, Alfeu; Dashnamoorthy, Ravi; Loranc, Eva; de Souza, Luis H T; Moreira, José C F; Suresh, Uthra; Chen, Yidong; Bishop, Alexander J R

    2016-01-01

    Alkylating agents are a key component of cancer chemotherapy. Several cellular mechanisms are known to be important for its survival, particularly DNA repair and xenobiotic detoxification, yet genomic screens indicate that additional cellular components may be involved. Elucidating these components has value in either identifying key processes that can be modulated to improve chemotherapeutic efficacy or may be altered in some cancers to confer chemoresistance. We therefore set out to reevaluate our prior Drosophila RNAi screening data by comparison to gene expression arrays in order to determine if we could identify any novel processes in alkylation damage survival. We noted a consistent conservation of alkylation survival pathways across platforms and species when the analysis was conducted on a pathway/process level rather than at an individual gene level. Better results were obtained when combining gene lists from two datasets (RNAi screen plus microarray) prior to analysis. In addition to previously identified DNA damage responses (p53 signaling and Nucleotide Excision Repair), DNA-mRNA-protein metabolism (transcription/translation) and proteasome machinery, we also noted a highly conserved cross-species requirement for NRF2, glutathione (GSH)-mediated drug detoxification and Endoplasmic Reticulum stress (ER stress)/Unfolded Protein Responses (UPR) in cells exposed to alkylation. The requirement for GSH, NRF2 and UPR in alkylation survival was validated by metabolomics, protein studies and functional cell assays. From this we conclude that RNAi/gene expression fusion is a valid strategy to rapidly identify key processes that may be extendable to other contexts beyond damage survival.

  17. Combined expression patterns of QTL-linked candidate genes best predict thermotolerance in Drosophila melanogaster.

    PubMed

    Norry, Fabian M; Larsen, Peter F; Liu, Yongjie; Loeschcke, Volker

    2009-11-01

    Knockdown resistance to high temperature (KRHT) is a thermal adaptation trait in Drosophila melanogaster. Here we used quantitative real-time PCR (qRT-PCR) to test for possible associations between KRHT and the expression of candidate genes within quantitative trait loci (QTL) in eight recombinant inbred lines (RIL). hsp60 and hsc70-3 map within an X-linked QTL, while CG10383, catsup, ddc, trap1, and cyp6a13 are linked in a KRHT-QTL on chromosome 2. hsc70-3 expression increased by heat-hardening. Principal Components analysis revealed that catsup, ddc and trap1 were either co-expressed or combined in their expression levels. This composite expression variable (e-PC1) was positively associated to KRHT in non-hardened RIL. In heat-hardened flies, hsp60 was negatively related to hsc70-3 on e-PC2, with effects on KRHT. These results are consistent with the notion that QTL can be shaped by expression variation in combined candidate loci. We found composite variables of gene expression (e-PCs) that best correlated to KRHT. Network effects with other untested linked loci are apparent because, in spite of their associations with KRHT phenotypes, e-PCs were sometimes uncorrelated with their QTL genotype.

  18. In vitro therapeutic effect of PDT combined with VEGF-A gene therapy

    NASA Astrophysics Data System (ADS)

    Lecaros, Rumwald Leo G.; Huang, Leaf; Hsu, Yih-Chih

    2014-02-01

    Vascular endothelial growth factor A (VEGF-A), commonly known as VEGF, is one of the primary factors that affect tumor angiogenesis. It was found to be expressed in cancer cell lines including oral squamous cell carcinoma. Photodynamic therapy (PDT) is a novel therapeutic modality to treat cancer by using a photosensitizer which is activated by a light source to produce reactive oxygen species and mediates oxygen-independent hypoxic conditions to tumor. Another emerging treatment to cure cancer is the use of interference RNA (e.g. siRNA) to silence a specific mRNA sequence. VEGF-A was found to be expressed in oral squamous cell carcinoma and overexpressed after 24 hour post-PDT by Western blot analysis. Cell viability was found to decrease at 25 nM of transfected VEGF-A siRNA. In vitro combined therapy of PDT and VEGF-A siRNA showed better response as compared with PDT and gene therapy alone. The results suggest that PDT combined with targeted gene therapy has a potential mean to achieve better therapeutic outcome.

  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. Identification and Evaluation of Reference Genes for Quantitative Analysis of Brazilian Pine (Araucaria angustifolia Bertol. Kuntze) Gene Expression.

    PubMed

    Elbl, Paula; Navarro, Bruno V; de Oliveira, Leandro F; Almeida, Juliana; Mosini, Amanda C; Dos Santos, André L W; Rossi, Magdalena; Floh, Eny I S

    2015-01-01

    Quantitative analysis of gene expression is a fundamental experimental approach in many fields of plant biology, but it requires the use of internal controls representing constitutively expressed genes for reliable transcript quantification. In this study, we identified fifteen putative reference genes from an A. angustifolia transcriptome database. Variation in transcript levels was first evaluated in silico by comparing read counts and then by quantitative real-time PCR (qRT-PCR), resulting in the identification of six candidate genes. The consistency of transcript abundance was also calculated applying geNorm and NormFinder software packages followed by a validation approach using four target genes. The results presented here indicate that a diverse set of samples should ideally be used in order to identify constitutively expressed genes, and that the use of any two reference genes in combination, of the six tested genes, is sufficient for effective expression normalization. Finally, in agreement with the in silico prediction, a comprehensive analysis of the qRT-PCR data combined with validation analysis revealed that AaEIF4B-L and AaPP2A are the most suitable reference genes for comparative studies of A. angustifolia gene expression.

  2. Independent component analysis of Alzheimer's DNA microarray gene expression data

    PubMed Central

    Kong, Wei; Mou, Xiaoyang; Liu, Qingzhong; Chen, Zhongxue; Vanderburg, Charles R; Rogers, Jack T; Huang, Xudong

    2009-01-01

    vector machine recursive feature elimination (SVM-RFE) methods, which are widely used in microarray data analysis, ICA can identify more AD-related genes. Furthermore, we have validated and identified many genes that are associated with AD pathogenesis. Conclusion We demonstrated that ICA exploits higher-order statistics to identify gene expression profiles as linear combinations of elementary expression patterns that lead to the construction of potential AD-related pathogenic pathways. Our computing results also validated that the ICA model outperformed PCA and the SVM-RFE method. This report shows that ICA as a microarray data analysis tool can help us to elucidate the molecular taxonomy of AD and other multifactorial and polygenic complex diseases. PMID:19173745

  3. Combining Hi-C data with phylogenetic correlation to predict the target genes of distal regulatory elements in human genome.

    PubMed

    Lu, Yulan; Zhou, Yuanpeng; Tian, Weidong

    2013-12-01

    Defining the target genes of distal regulatory elements (DREs), such as enhancer, repressors and insulators, is a challenging task. The recently developed Hi-C technology is designed to capture chromosome conformation structure by high-throughput sequencing, and can be potentially used to determine the target genes of DREs. However, Hi-C data are noisy, making it difficult to directly use Hi-C data to identify DRE-target gene relationships. In this study, we show that DREs-gene pairs that are confirmed by Hi-C data are strongly phylogenetic correlated, and have thus developed a method that combines Hi-C read counts with phylogenetic correlation to predict long-range DRE-target gene relationships. Analysis of predicted DRE-target gene pairs shows that genes regulated by large number of DREs tend to have essential functions, and genes regulated by the same DREs tend to be functionally related and co-expressed. In addition, we show with a couple of examples that the predicted target genes of DREs can help explain the causal roles of disease-associated single-nucleotide polymorphisms located in the DREs. As such, these predictions will be of importance not only for our understanding of the function of DREs but also for elucidating the causal roles of disease-associated noncoding single-nucleotide polymorphisms.

  4. Combined effect of common gene variants on response to drug withdrawal therapy in medication overuse headache.

    PubMed

    Cargnin, Sarah; Viana, Michele; Sances, Grazia; Bianchi, Marika; Ghiotto, Natascia; Tassorelli, Cristina; Nappi, Giuseppe; Canonico, Pier Luigi; Genazzani, Armando A; Terrazzino, Salvatore

    2014-10-01

    No information is currently available on genetic determinants of short-term response to drug withdrawal in medication overuse headache (MOH). In the present study, we aimed to evaluate the role of 14 polymorphisms in 8 candidate genes potentially relevant for drug addiction (OPRM1, DRD2, DBH, COMT, BDNF, SLC6A4, 5HT2A, and SLC1A2) as predictors for detoxification outcome of MOH patients at 2 months of follow-up. Genotyping was conducted by PCR, PCR-RFLP analysis, or real-time PCR allelic discrimination assay on genomic DNA extracted from peripheral blood. The association between gene variants and risk of unsuccessful detoxification was evaluated by univariate and multivariate logistic regression analyses. One hundred and eight MOH patients with effective drug withdrawal therapy and 65 MOH patients with unsuccessful detoxification were available for the analysis. In the multivariable logistic regression analysis, triptan overuse (odds ratio (OR) 0.271, 95% confidence interval (CI) 0.083-0.890, P = 0.031) and TT genotype carriage of DRD2 NcoI (OR 0.115, 95% CI 0.014-0.982, P = 0.048) emerged as independent predictors for unsuccessful detoxification. In addition, carriers of at least four of the six top-ranked gene variants (P < 0.10) were found at higher odds for unsuccessful detoxification than patients with ≤3 high-risk genotypes (OR 3.40, 95% CI 1.65-7.01, P = 0.001). This exploratory study suggests that DRD2 NcoI may be a genetic determinant of detoxification outcome in MOH patients. Our findings also show that an approach based on the combination of multiple genetic markers could be clinically useful for identification of MOH patients at higher risk for unsuccessful detoxification.

  5. Gene Expression Analysis of Breast Cancer Progression

    DTIC Science & Technology

    2005-07-01

    representation of the retroviral vectors SFG-tdRFP-cmvFLuc, constitutively expressing tdRFP and firefly luciferase; and Cis-TGFD1-Smads- HSV1 - tk/GFP...AD Award Number: DAMD 17-02-1-0484 TITLE: Gene Expression Analysis of Breast Cancer Progression PRINCIPAL INVESTIGATOR: William L. Gerald, M.D., Ph.D...CONTRACT NUMBER Gene Expression Analysis of Breast Cancer Progression 5b. GRANT NUMBER DAMD17-02-1-0484 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 6d

  6. Combinations of gene ontology and pathway characterize and predict prognosis genes for recurrence of gastric cancer after surgery.

    PubMed

    Fan, Haiyan; Guo, Zhanjun; Wang, Cuijv

    2015-09-01

    Gastric cancer (GC) is the second leading cause of death from cancer globally. The most common cause of GC is the infection of Helicobacter pylori, but ∼11% of cases are caused by genetic factors. However, recurrences occur in approximately one-third of stage II GC patients, even if they are treated with adjuvant chemotherapy or chemoradiotherapy. This is potentially due to expression variation of genes; some candidate prognostic genes were identified in patients with high-risk recurrences. The objective of this study was to develop an effective computational method for meaningfully interpreting these GC-related genes and accurately predicting novel prognostic genes for high-risk recurrence patients. We employed properties of genes (gene ontology [GO] and KEGG pathway information) as features to characterize GC-related genes. We obtained an optimal set of features for interpreting these genes. By applying the minimum redundancy maximum relevance algorithm, we predicted the GC-related genes. With the same approach, we further predicted the genes for the prognostic of high-risk recurrence. We obtained 1104 GO terms and KEGG pathways and 530 GO terms and KEGG pathways, respectively, that characterized GC-related genes and recurrence-related genes well. Finally, three novel prognostic genes were predicted to help supplement genetic markers of high-risk GC patients for recurrence after surgery. An in-depth text mining indicated that the results are quite consistent with previous knowledge. Survival analysis of patients confirmed the novel prognostic genes as markers. By analyzing the related genes, we developed a systematic method to interpret the possible underlying mechanism of GC. The novel prognostic genes facilitate the understanding and therapy of GC recurrences after surgery.

  7. Internal ribosome entry site-based vectors for combined gene therapy.

    PubMed

    Renaud-Gabardos, Edith; Hantelys, Fransky; Morfoisse, Florent; Chaufour, Xavier; Garmy-Susini, Barbara; Prats, Anne-Catherine

    2015-02-20

    Gene therapy appears as a promising strategy to treat incurable diseases. In particular, combined gene therapy has shown improved therapeutic efficiency. Internal ribosome entry sites (IRESs), RNA elements naturally present in the 5' untranslated regions of a few mRNAs, constitute a powerful tool to co-express several genes of interest. IRESs are translational enhancers allowing the translational machinery to start protein synthesis by internal initiation. This feature allowed the design of multi-cistronic vectors expressing several genes from a single mRNA. IRESs exhibit tissue specificity, and drive translation in stress conditions when the global cell translation is blocked, which renders them useful for gene transfer in hypoxic conditions occurring in ischemic diseases and cancer. IRES-based viral and non viral vectors have been used successfully in preclinical and clinical assays of combined gene therapy and resulted in therapeutic benefits for various pathologies including cancers, cardiovascular diseases and degenerative diseases.

  8. Combining gene therapy and fetal hemoglobin induction for treatment of β-thalassemia.

    PubMed

    Breda, Laura; Rivella, Stefano; Zuccato, Cristina; Gambari, Roberto

    2013-06-01

    β-thalassemias are caused by nearly 300 mutations of the β-globin gene, leading to a low or absent production of adult hemoglobin (HbA). Two major therapeutic approaches have recently been proposed: gene therapy and induction of fetal hemoglobin (HbF) with the objective of achieving clinically relevant levels of Hbs. The objective of this article is to describe the development of therapeutic strategies based on a combination of gene therapy and induction of HbFs. An increase of β-globin gene expression in β-thalassemia cells can be achieved by gene therapy, although de novo production of clinically relevant levels of adult Hb may be difficult to obtain. On the other hand, an increased production of HbF is beneficial in β-thalassemia. The combination of gene therapy and HbF induction appears to be a pertinent strategy to achieve clinically relevant results.

  9. Clique-Based Clustering of Correlated SNPs in a Gene Can Improve Performance of Gene-Based Multi-Bin Linear Combination Test.

    PubMed

    Yoo, Yun Joo; Kim, Sun Ah; Bull, Shelley B

    2015-01-01

    Gene-based analysis of multiple single nucleotide polymorphisms (SNPs) in a gene region is an alternative to single SNP analysis. The multi-bin linear combination test (MLC) proposed in previous studies utilizes the correlation among SNPs within a gene to construct a gene-based global test. SNPs are partitioned into clusters of highly correlated SNPs, and the MLC test statistic quadratically combines linear combination statistics constructed for each cluster. The test has degrees of freedom equal to the number of clusters and can be more powerful than a fully quadratic or fully linear test statistic. In this study, we develop a new SNP clustering algorithm designed to find cliques, which are complete subnetworks of SNPs with all pairwise correlations above a threshold. We evaluate the performance of the MLC test using the clique-based CLQ algorithm versus using the tag-SNP-based LDSelect algorithm. In our numerical power calculations we observed that the two clustering algorithms produce identical clusters about 40~60% of the time, yielding similar power on average. However, because the CLQ algorithm tends to produce smaller clusters with stronger positive correlation, the MLC test is less likely to be affected by the occurrence of opposing signs in the individual SNP effect coefficients.

  10. Combined 3D and hypoxic culture improves cartilage-specific gene expression in human chondrocytes.

    PubMed

    Foldager, Casper B; Nielsen, Anna B; Munir, Samir; Ulrich-Vinther, Michael; Søballe, Kjeld; Bünger, Cody; Lind, Martin

    2011-04-01

    In vitro expansion of autologous chondrocytes is an essential part of many clinically used cartilage repair treatments. Native chondrocytes reside in a 3-dimensional (3D) network and are exposed to low levels of oxygen. We compared monolayer culture to combined 3D and hypoxic culture using quantitative gene expression analysis. Cartilage biopsies were collected from the intercondylar groove in the distal femur from 12 patients with healthy cartilage. Cells were used for either monolayer or scaffold culture. The scaffolds were clinically available MPEG-PLGA scaffolds (ASEED). After harvesting of cells for baseline investigation, the remainder was divided into 3 groups for incubation in conditions of normoxia (21% oxygen), hypoxia (5% oxygen), or severe hypoxia (1% oxygen). RNA extractions were performed 1, 2, and 6 days after the baseline time point, respectively. Quantitative RT-PCR was performed using assays for RNA encoding collagen types 1 and 2, aggrecan, sox9, ankyrin repeat domain-37, and glyceraldehyde-3-phosphate dehydrogenase relative to 2 hypoxia-stable housekeeping genes. Sox9, aggrecan, and collagen type 2 RNA expression increased with reduced oxygen. On day 6, the expression of collagen type 2 and aggrecan RNA was higher in 3D culture than in monolayer culture. Our findings suggest that there was a combined positive effect of 3D culture and hypoxia on cartilage-specific gene expression. The positive effects of 3D culture alone were not detected until day 6, suggesting that seeding of chondrocytes onto a scaffold for matrix-assisted chondrocyte implantation should be performed earlier than 2 days before implantation.

  11. SHIELDING ANALYSIS FOR PORTABLE GAUGING COMBINATION SOURCES

    SciTech Connect

    J. TOMPKINS; L. LEONARD; ET AL

    2000-08-01

    Radioisotopic decay has been used as a source of photons and neutrons for industrial gauging operations since the late 1950s. Early portable moisture/density gauging equipment used Americium (Am)-241/Beryllium (Be)/Cesium (Cs)-137 combination sources to supply the required nuclear energy for gauging. Combination sources typically contained 0.040 Ci of Am-241 and 0.010 Ci of CS-137 in the same source capsule. Most of these sources were manufactured approximately 30 years ago. Collection, transportation, and storage of these sources once removed from their original device represent a shielding problem with distinct gamma and neutron components. The Off-Site Source Recovery (OSR) Project is planning to use a multi-function drum (MFD) for the collection, shipping, and storage of AmBe sources, as well as the eventual waste package for disposal. The MFD is an approved TRU waste container design for DOE TRU waste known as the 12 inch Pipe Component Overpack. As the name indicates, this drum is based on a 12 inch ID stainless steel weldment approximately 25 inch in internal length. The existing drum design allows for addition of shielding within the pipe component up to the 110 kg maximum pay load weight. The 12 inch pipe component is packaged inside a 55-gallon drum, with the balance of the interior space filled with fiberboard dunnage. This packaging geometry is similar to the design of a DOT 6M, Type B shipping container.

  12. Association of haplotype combination of serotonin transporter gene polymorphisms with monthly headache days in MOH patients.

    PubMed

    Terrazzino, S; Tassorelli, C; Sances, G; Allena, M; Viana, M; Monaco, F; Bellomo, G; Nappi, G; Canonico, P L; Genazzani, A A

    2012-01-01

    To evaluate the role of 5-HTTLPR, STin2 VNTR, and rs1042173T>G polymorphisms of the serotonin transporter gene (SLC6A4) as susceptibility factors for medication overuse headache (MOH) and to assess their value as predictors of the number of headache days per month, a potential marker of disease severity. Genotyping was performed by PCR and PCR-RFLP on genomic DNA extracted from peripheral blood of 227 MOH patients and 312 control subjects. Logistic regression analysis was used to evaluate the association between the SL6A4 gene polymorphisms and MOH risk. The association between polymorphic variants and monthly headache days was evaluated by linear regression analysis. Logistic regression analysis, adjusted for age and gender, revealed a nominal association between rs1042173T>G and MOH risk (TT vs. TG + GG, OR: 1.58 95% CI: 1.05-2.37, P = 0.028). In the linear regression analysis adjusted for age, gender, primary headache diagnosis, acute drug overused and monthly drug number, STin2 VNTR was found nominally associated with monthly headache days (12/12 vs. others, difference: 1.55 days, 95% CI: 0.01-3.08, P = 0.050). When STin2 VNTR and rs1042173T>G were analyzed in haplotypic combination, a global haplotype association emerged with monthly headache days which remained significant after Bonferroni correction for multiple comparisons (global haplotype association P = 0.0056). Although a minor contribution of SLC6A4 variants in the genetic liability of MOH cannot be excluded, haplotype-based analysis of STin2 VNTR and rs1042173T>G polymorphisms allowed to identify a subgroup of MOH patients with a higher number of monthly headache and, possibly, with a more severe disease. © 2011 The Author(s). European Journal of Neurology © 2011 EFNS.

  13. Photothermal combined gene therapy achieved by polyethyleneimine-grafted oxidized mesoporous carbon nanospheres.

    PubMed

    Meng, Ying; Wang, Shanshan; Li, Chengyi; Qian, Min; Yan, Xueying; Yao, Shuangchao; Peng, Xiyue; Wang, Yi; Huang, Rongqin

    2016-09-01

    Combining controllable photothermal therapy and efficacious gene therapy in a single platform holds great promise in cancer therapy due to the enhanced combined therapeutic effects. Herein, polyethyleneimine-grafted oxidized mesoporous carbon nanospheres (OP) were developed for combined photothermal combined gene therapy in vitro and in vivo. The synthesized OP was characterized to have three dimensional spherical structure with uniformed diameter, ordered mesopores with graphitic domains, high water dispersion with zeta potential of +22 mV, and good biocompatibility. Consequently, OP was exploited as the photothermal convertor with strong NIR absorption and the gene vector via electrostatic interaction, which therefore cannot only deliver the therapeutic gene (pING4) to tumors for gene therapy, but also can eliminate the tumors by photothermal ablation. Moreover, the improved gene therapy accompanied by the NIR photothermally enhanced gene release was also well achieved based on OP. The excellent combined therapeutic effects demonstrated in vitro and in vivo suggested the OP's potential for cancer therapy.

  14. Combining Hierarchical and Associative Gene Ontology Relations with Textual Evidence in Estimating Gene and Gene Product Similarity

    SciTech Connect

    Sanfilippo, Antonio P.; Posse, Christian; Gopalan, Banu; Riensche, Roderick M.; Beagley, Nathaniel; Baddeley, Bob L.; Tratz, Stephen C.; Gregory, Michelle L.

    2007-03-01

    Gene and gene product similarity is a fundamental diagnostic measure in analyzing biological data and constructing predictive models for functional genomics. With the rising influence of the Gene Ontology, two complementary approaches have emerged where the similarity between two genes or gene products is obtained by comparing Gene Ontology (GO) annotations associated with the genes or gene products. One approach captures GO-based similarity in terms of hierarchical relations within each gene subontology. The other approach identifies GO-based similarity in terms of associative relations across the three gene subontologies. We propose a novel methodology where the two approaches can be merged with ensuing benefits in coverage and accuracy, and demonstrate that further improvements can be obtained by integrating textual evidence extracted from relevant biomedical literature.

  15. A two-locus model of selection in autotetraploids: Chromosomal gametic disequilibrium and selection for an adaptive epistatic gene combination.

    PubMed

    Griswold, C K; Williamson, M W

    2017-08-23

    In this paper, we present a two-locus model of selection for an autotetraploid population. We also investigate a measure of disequilibrium that occurs between homologous chromosomes in the diploid gametes of autotetraploids, namely chromosomal gametic disequilibrium. We apply the model and measure of disequilibrium to compare how an adaptive epistatic gene combination is inherited and selected for in an autotetraploid versus diploid population. Autotetraploids are expected to have higher genomic mutation and recombination rates relative to diploids, due to a greater ploidy level. These two processes can work in opposition in terms of selection for adaptive epistatic gene combinations. While a higher genomic mutation rate can generate the alleles that confer an epistatic combination more quickly, a higher recombination rate is expected to break the combination down more quickly. We show that chromosomal gametic disequilibrium in autotetraploids can potentially compensate for less linkage disequilibrium in autotetraploids. We also explore how double reduction affects the inheritance of and selection for an epistatic gene combination. Over all, our analysis provides theoretical evidence that adaptive epistatic combinations can be selected for more efficiently in autotetraploids versus diploids. This may provide insight into empirical work that finds epistasis has a role in causing population differentiation between autotetraploid plant populations.Heredity advance online publication, 23 August 2017; doi:10.1038/hdy.2017.44.

  16. PCAN: phenotype consensus analysis to support disease-gene association.

    PubMed

    Godard, Patrice; Page, Matthew

    2016-12-07

    Bridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest. We describe Phenotype Consensus Analysis (PCAN); a method to assess the consensus semantic similarity of phenotypes in a candidate gene's signaling neighborhood. We demonstrate that significant phenotype consensus (p < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high quality String interactions + Metabase pathways and use Joubert Syndrome to demonstrate the ease with which a significant result can be interrogated to highlight discriminatory traits linked to mechanistically related genes. We advocate phenotype consensus as an intuitive and versatile method to aid disease-gene association, which naturally lends itself to the mechanistic deconvolution of diverse phenotypes. We provide PCAN to the community as an R package ( http://bioconductor.org/packages/PCAN/ ) to allow flexible configuration, extension and standalone use or integration to supplement existing gene prioritization workflows.

  17. [Polymorphism of POU1F1 gene and PRL gene and their combined effects on milk performance traits in Chinese Holstein cattle].

    PubMed

    Jia, Xiang-Jie; Wang, Chang-Fa; Yang, Gui-Wen; Huang, Jin-Ming; Li, Qiu-Ling; Zhong, Ji-Feng

    2011-12-01

    Three novel SNPs were found by DNA sequencing, PCR-RFLP and CRS-PCR methods were used for genotyping in 979 Chinese Holstein cattle. One SNP, G1178C, was identified in exon 2 of POU1F1 gene. Two novel SNPs, A906G and A1134G, were identified in 5'-flanking regulatory region (5'-UTR) of PRL gene. The association between polymorphisms of the two genes and milk performance traits were analyzed with PROC GLM of SAS. The results showed that GC genotype at 1178 locus of POU1F1 gene was advantageous for milk yield, milk protein yield, and milk fat yield. AG genotype at 906 locus was advantageous for milk yield. There was no significant difference between 1134 locus and milk performance traits of 5'-UTR of PRL gene. Analysis of genotype combination effect on milk production traits showed that the effect of combined genotype was not simple sum of single genotypes and the effects of gene pyramiding seemed to be more important in molecular breeding.

  18. Atomic-Based-Combined-Cycle Analysis

    NASA Technical Reports Server (NTRS)

    Han, Samuel S.

    1999-01-01

    Atomic-based-combined-cycle (ABCC) engine combines an air-breathing ramjet engine with an atomic reactor to increase the mission-averaged specific impulse and thereby increasing the dry-mass ratio. ABCC engine is similar to RBCC engine except that energy needed for the propulsive power is derived from nuclear reaction rather than chemical combustion used in the RBCC engine. The potential performance improvement of an ABCC engine over a RBCC engine comes from two factors. Firstly, the energy density of nuclear reaction is several order of magnitudes higher than the chemical combustion. Secondly, hydrogen can produce much higher nozzle exit velocity because of its small molecular weight. A one-dimensional, transient numerical model was used to analyze a generic RBCC engine and it is used as a baseline to evaluate an imaginary ABCC engine performance. A nuclear reactor is treated as a black box energy source that replaces the role of the primary rocket and the chemical combustion chamber in a RBCC engine. The performance of a generic ABCC engine along a flight path (q0 =10 (exp 3) lbf per square ft) shows that the mission averaged-specific impulse is about twice larger than RBCC engine and the dry mass-ratio is about 50% larger. Results of the present ABCC engine performance are based on the assumptions that the flow passage of working fluids is identical to that of RBCC engine and that a nuclear reactor is treated as an energy black box. Preliminary heat transfer calculation shows that the rate of heat transfer to the working fluids is within the limit of turbulent convective heat transfer regimes. The flow passage of realistic ABCC engine must be known for a better prediction of ABCC engine performance. Also, critical heat transfer calculations must be performed for the ejector mode and ramjet mode operations. This is possible only when the details of a reactor configuration are available.

  19. Atomic-Based-Combined-Cycle Analysis

    NASA Technical Reports Server (NTRS)

    Han, Sam; Bai, Don; Schmidt, George

    2000-01-01

    Atomic-based-combined-cycle (ABCC) engine combines an air-breathing ramjet engine with an atomic reactor to increase the mission-averaged specific impulse and thereby increasing the dry-mass ratio. ABCC engine is similar to RBCC engine except that energy needed for the propulsive power is derived from nuclear reaction rather than chemical combustion used in the RBCC engine. The potential performance improvement of an ABCC engine over a RBCC engine comes from two factors. Firstly, the energy density of nuclear reaction is several order of magnitudes higher than the chemical combustion. Secondly, hydrogen can produce much higher nozzle exit velocity because of its small molecular weight. A one-dimensional, transient numerical model was used to analyze a generic scramjet engine and it is used as a baseline to evaluate an imaginary ABCC engine performance. A nuclear reactor is treated as a black box energy source that replaces the role of the primary rocket and the chemical combustion chamber in a RBCC engine. Hydrogen is heated by the reactor and accelerated to produce high-speed ejection velocity. The ejection velocity up 10,000 m/sec is theoretically possible because of high energy density from the reactor and large gas constant of the hydrogen. Oxygen contained in the entrained air reacts with hydrogen and produces propulsive power for ejector mode operation. To provide enough thrust for initial acceleration, relatively large amount of hydrogen must be pumped through the reactor. Amount of oxygen contained in the entrained air may not be sufficient to burn all hydrogen and consequently combustion could occur at the end of exit nozzle. It is assumed that this combustion process is constant-pressure combustion at 1.0 atmospheric pressure and thus not affects the nozzle exit condition.

  20. Combining Selective Pressures to Enhance the Durability of Disease Resistance Genes

    PubMed Central

    Bourguet, Denis

    2016-01-01

    The efficacy of disease resistance genes in plants decreases over time because of the selection of virulent pathogen genotypes. A key goal of crop protection programs is to increase the durability of the resistance conferred by these genes. The spatial and temporal deployment of plant disease resistance genes is considered to be a major factor determining their durability. In the literature, four principal strategies combining resistance genes over time and space have been considered to delay the evolution of virulent pathogen genotypes. We reviewed this literature with the aim of determining which deployment strategy results in the greatest durability of resistance genes. Although theoretical and empirical studies comparing deployment strategies of more than one resistance gene are very scarce, they suggest that the overall durability of disease resistance genes can be increased by combining their presence in the same plant (pyramiding). Retrospective analyses of field monitoring data also suggest that the pyramiding of disease resistance genes within a plant is the most durable strategy. By extension, we suggest that the combination of disease resistance genes with other practices for pathogen control (pesticides, farming practices) may be a relevant management strategy to slow down the evolution of virulent pathogen genotypes. PMID:28066472

  1. Combining Selective Pressures to Enhance the Durability of Disease Resistance Genes.

    PubMed

    2016-01-01

    The efficacy of disease resistance genes in plants decreases over time because of the selection of virulent pathogen genotypes. A key goal of crop protection programs is to increase the durability of the resistance conferred by these genes. The spatial and temporal deployment of plant disease resistance genes is considered to be a major factor determining their durability. In the literature, four principal strategies combining resistance genes over time and space have been considered to delay the evolution of virulent pathogen genotypes. We reviewed this literature with the aim of determining which deployment strategy results in the greatest durability of resistance genes. Although theoretical and empirical studies comparing deployment strategies of more than one resistance gene are very scarce, they suggest that the overall durability of disease resistance genes can be increased by combining their presence in the same plant (pyramiding). Retrospective analyses of field monitoring data also suggest that the pyramiding of disease resistance genes within a plant is the most durable strategy. By extension, we suggest that the combination of disease resistance genes with other practices for pathogen control (pesticides, farming practices) may be a relevant management strategy to slow down the evolution of virulent pathogen genotypes.

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

    PubMed Central

    2015-01-01

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

  3. Selection of suitable reference genes for assessing gene expression in pearl millet under different abiotic stresses and their combinations

    PubMed Central

    Shivhare, Radha; Lata, Charu

    2016-01-01

    Pearl millet [Pennisetum glaucum (L.) R. Br.] a widely used grain and forage crop, is grown in areas frequented with one or more abiotic stresses, has superior drought and heat tolerance and considered a model crop for stress tolerance studies. Selection of suitable reference genes for quantification of target stress-responsive gene expression through quantitative real-time (qRT)-PCR is important for elucidating the molecular mechanisms of improved stress tolerance. For precise normalization of gene expression data in pearl millet, ten candidate reference genes were examined in various developmental tissues as well as under different individual abiotic stresses and their combinations at 1 h (early) and 24 h (late) of stress using geNorm, NormFinder and RefFinder algorithms. Our results revealed EF-1α and UBC-E2 as the best reference genes across all samples, the specificity of which was confirmed by assessing the relative expression of a PgAP2 like-ERF gene that suggested use of these two reference genes is sufficient for accurate transcript normalization under different stress conditions. To our knowledge this is the first report on validation of reference genes under different individual and multiple abiotic stresses in pearl millet. The study can further facilitate fastidious discovery of stress-tolerance genes in this important stress-tolerant crop. PMID:26972345

  4. Selection of suitable reference genes for assessing gene expression in pearl millet under different abiotic stresses and their combinations.

    PubMed

    Shivhare, Radha; Lata, Charu

    2016-03-14

    Pearl millet [Pennisetum glaucum (L.) R. Br.] a widely used grain and forage crop, is grown in areas frequented with one or more abiotic stresses, has superior drought and heat tolerance and considered a model crop for stress tolerance studies. Selection of suitable reference genes for quantification of target stress-responsive gene expression through quantitative real-time (qRT)-PCR is important for elucidating the molecular mechanisms of improved stress tolerance. For precise normalization of gene expression data in pearl millet, ten candidate reference genes were examined in various developmental tissues as well as under different individual abiotic stresses and their combinations at 1 h (early) and 24 h (late) of stress using geNorm, NormFinder and RefFinder algorithms. Our results revealed EF-1α and UBC-E2 as the best reference genes across all samples, the specificity of which was confirmed by assessing the relative expression of a PgAP2 like-ERF gene that suggested use of these two reference genes is sufficient for accurate transcript normalization under different stress conditions. To our knowledge this is the first report on validation of reference genes under different individual and multiple abiotic stresses in pearl millet. The study can further facilitate fastidious discovery of stress-tolerance genes in this important stress-tolerant crop.

  5. Quantitative DNA Methylation Analysis of Candidate Genes in Cervical Cancer

    PubMed Central

    Siegel, Erin M.; Riggs, Bridget M.; Delmas, Amber L.; Koch, Abby; Hakam, Ardeshir; Brown, Kevin D.

    2015-01-01

    Aberrant DNA methylation has been observed in cervical cancer; however, most studies have used non-quantitative approaches to measure DNA methylation. The objective of this study was to quantify methylation within a select panel of genes previously identified as targets for epigenetic silencing in cervical cancer and to identify genes with elevated methylation that can distinguish cancer from normal cervical tissues. We identified 49 women with invasive squamous cell cancer of the cervix and 22 women with normal cytology specimens. Bisulfite-modified genomic DNA was amplified and quantitative pyrosequencing completed for 10 genes (APC, CCNA, CDH1, CDH13, WIF1, TIMP3, DAPK1, RARB, FHIT, and SLIT2). A Methylation Index was calculated as the mean percent methylation across all CpG sites analyzed per gene (~4-9 CpG site) per sequence. A binary cut-point was defined at >15% methylation. Sensitivity, specificity and area under ROC curve (AUC) of methylation in individual genes or a panel was examined. The median methylation index was significantly higher in cases compared to controls in 8 genes, whereas there was no difference in median methylation for 2 genes. Compared to HPV and age, the combination of DNA methylation level of DAPK1, SLIT2, WIF1 and RARB with HPV and age significantly improved the AUC from 0.79 to 0.99 (95% CI: 0.97–1.00, p-value = 0.003). Pyrosequencing analysis confirmed that several genes are common targets for aberrant methylation in cervical cancer and DNA methylation level of four genes appears to increase specificity to identify cancer compared to HPV detection alone. Alterations in DNA methylation of specific genes in cervical cancers, such as DAPK1, RARB, WIF1, and SLIT2, may also occur early in cervical carcinogenesis and should be evaluated. PMID:25826459

  6. Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms.

    PubMed

    Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

    2017-06-28

    Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric phenotypes and reduces the risk of false-positive findings. We apply this method focusing on the role of perceived parental support, psychological control, and harsh punishment in depressive symptoms in adolescence. Analyses were conducted on 982 adolescents of Caucasian origin (Mage (SD) = 13.78 (.94) years) genotyped for 4,947 SNPs in 263 genes, selected based on a literature survey. The Leuven Adolescent Perceived Parenting Scale (LAPPS) and the Parental Behavior Scale (PBS) were used to assess perceived parental psychological control, harsh punishment, and support. The Center for Epidemiologic Studies Depression Scale (CES-D) was the outcome. We used gene-based testing taking into account linkage disequilibrium to identify genes containing SNPs exhibiting an interaction with environmental factors yielding a p-value per single gene. Significant results at the corrected p-value of p < 1.90 × 10(-4) were examined in an independent replication sample of Dutch adolescents (N = 1354). Two genes showed evidence for interaction with perceived support: GABRR1 (p = 4.62 × 10(-5) ) and GABRR2 (p = 9.05 × 10(-6) ). No genes interacted significantly with psychological control or harsh punishment. Gene-based analysis was unable to confirm the interaction of GABRR1 or GABRR2 with support in the replication sample. However, for GABRR2, but not GABRR1, the correlation of the estimates between the two datasets was significant (r (46) = .32; p = .027) and a gene-based analysis of the combined datasets supported GABRR2 × support interaction (p = 1.63 × 10(-4) ). We present a gene-based method for gene-environment interactions in a polygenic context and show that genes

  7. Measuring semantic similarities by combining gene ontology annotations and gene co-function networks

    SciTech Connect

    Peng, Jiajie; Uygun, Sahra; Kim, Taehyong; Wang, Yadong; Rhee, Seung Y.; Chen, Jin

    2015-02-14

    Background: Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms. Results: We introduce a novel approach called NETSIM (network-based similarity measure) that incorporates information from gene co-function networks in addition to using the GO structure and annotations. Using metabolic reaction maps of yeast, Arabidopsis, and human, we demonstrate that NETSIM can improve the accuracy of GO term similarities. We also demonstrate that NETSIM works well even for genomes with sparser gene annotation data. We applied NETSIM on large Arabidopsis gene families such as cytochrome P450 monooxygenases to group the members functionally and show that this grouping could facilitate functional characterization of genes in these families. Conclusions: Using NETSIM as an example, we demonstrated that the performance of a semantic similarity measure could be significantly improved after incorporating genome-specific information. NETSIM incorporates both GO annotations and gene co-function network data as a priori knowledge in the model. Therefore, functional similarities of GO terms that are not explicitly encoded in GO but are relevant in a taxon-specific manner become measurable when GO annotations are limited.

  8. Measuring semantic similarities by combining gene ontology annotations and gene co-function networks

    DOE PAGES

    Peng, Jiajie; Uygun, Sahra; Kim, Taehyong; ...

    2015-02-14

    Background: Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms. Results: We introduce a novel approach called NETSIM (network-based similarity measure) that incorporates information from gene co-function networks in addition to using the GO structure and annotations. Using metabolic reaction maps of yeast, Arabidopsis, and human, we demonstrate that NETSIM can improve the accuracy of GO term similarities. We also demonstratemore » that NETSIM works well even for genomes with sparser gene annotation data. We applied NETSIM on large Arabidopsis gene families such as cytochrome P450 monooxygenases to group the members functionally and show that this grouping could facilitate functional characterization of genes in these families. Conclusions: Using NETSIM as an example, we demonstrated that the performance of a semantic similarity measure could be significantly improved after incorporating genome-specific information. NETSIM incorporates both GO annotations and gene co-function network data as a priori knowledge in the model. Therefore, functional similarities of GO terms that are not explicitly encoded in GO but are relevant in a taxon-specific manner become measurable when GO annotations are limited.« less

  9. Measuring semantic similarities by combining gene ontology annotations and gene co-function networks.

    PubMed

    Peng, Jiajie; Uygun, Sahra; Kim, Taehyong; Wang, Yadong; Rhee, Seung Y; Chen, Jin

    2015-02-14

    Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms. We introduce a novel approach called NETSIM (network-based similarity measure) that incorporates information from gene co-function networks in addition to using the GO structure and annotations. Using metabolic reaction maps of yeast, Arabidopsis, and human, we demonstrate that NETSIM can improve the accuracy of GO term similarities. We also demonstrate that NETSIM works well even for genomes with sparser gene annotation data. We applied NETSIM on large Arabidopsis gene families such as cytochrome P450 monooxygenases to group the members functionally and show that this grouping could facilitate functional characterization of genes in these families. Using NETSIM as an example, we demonstrated that the performance of a semantic similarity measure could be significantly improved after incorporating genome-specific information. NETSIM incorporates both GO annotations and gene co-function network data as a priori knowledge in the model. Therefore, functional similarities of GO terms that are not explicitly encoded in GO but are relevant in a taxon-specific manner become measurable when GO annotations are limited. Supplementary information and software are available at http://www.msu.edu/~jinchen/NETSIM .

  10. Analyses of differentially expressed genes after exposure to acute stress, acute ethanol, or a combination of both in mice.

    PubMed

    Baker, Jessica A; Li, Jingxin; Zhou, Diana; Yang, Ming; Cook, Melloni N; Jones, Byron C; Mulligan, Megan K; Hamre, Kristin M; Lu, Lu

    2017-02-01

    Alcohol abuse is a complex disorder, which is confounded by other factors, including stress. In the present study, we examined gene expression in the hippocampus of BXD recombinant inbred mice after exposure to ethanol (NOE), stress (RSS), and the combination of both (RSE). Mice were given an intraperitoneal (i.p.) injection of 1.8 g/kg ethanol or saline, and subsets of both groups were exposed to acute restraint stress for 15 min or controls. Gene expression in the hippocampus was examined using microarray analysis. Genes that were significantly (p < 0.05, q < 0.1) differentially expressed were further evaluated. Bioinformatic analyses were predominantly performed using tools available at GeneNetwork.org, and included gene ontology, presence of cis-regulation or polymorphisms, phenotype correlations, and principal component analyses. Comparisons of differential gene expression between groups showed little overlap. Gene Ontology demonstrated distinct biological processes in each group with the combined exposure (RSE) being unique from either the ethanol (NOE) or stress (RSS) group, suggesting that the interaction between these variables is mediated through diverse molecular pathways. This supports the hypothesis that exposure to stress alters ethanol-induced gene expression changes and that exposure to alcohol alters stress-induced gene expression changes. Behavior was profiled in all groups following treatment, and many of the differentially expressed genes are correlated with behavioral variation within experimental groups. Interestingly, in each group several genes were correlated with the same phenotype, suggesting that these genes are the potential origins of significant genetic networks. The distinct sets of differentially expressed genes within each group provide the basis for identifying molecular networks that may aid in understanding the complex interactions between stress and ethanol, and potentially provide relevant therapeutic targets. Using Ptp4

  11. Combination Patterns of Major R Genes Determine the Level of Resistance to the M. oryzae in Rice (Oryza sativa L.).

    PubMed

    Wu, Yunyu; Xiao, Ning; Yu, Ling; Pan, Cunhong; Li, Yuhong; Zhang, Xiaoxiang; Liu, Guangqing; Dai, Zhengyuan; Pan, Xuebiao; Li, Aihong

    2015-01-01

    Rice blast caused by Magnaporthe oryzae is the most devastating disease of rice and poses a serious threat to world food security. In this study, the distribution and effectiveness of 18 R genes in 277 accessions were investigated based on pathogenicity assays and molecular markers. The results showed that most of the accessions exhibited some degree of resistance (resistance frequency, RF >50%). Accordingly, most of the accessions were observed to harbor two or more R genes, and the number of R genes harbored in accessions was significantly positively correlated with RF. Some R genes were demonstrated to be specifically distributed in the genomes of rice sub-species, such as Pigm, Pi9, Pi5 and Pi1, which were only detected in indica-type accessions, and Pik and Piz, which were just harbored in japonica-type accessions. By analyzing the relationship between R genes and RF using a multiple stepwise regression model, the R genes Pid3, Pi5, Pi9, Pi54, Pigm and Pit were found to show the main effects against M. oryzae in indica-type accessions, while Pita, Pb1, Pik, Pizt and Pia were indicated to exhibit the main effects against M. oryzae in japonica-type accessions. Principal component analysis (PCA) and cluster analysis revealed that combination patterns of major R genes were the main factors determining the resistance of rice varieties to M. oryzae, such as 'Pi9+Pi54', 'Pid3+Pigm', 'Pi5+Pid3+Pigm', 'Pi5+Pi54+Pid3+Pigm', 'Pi5+Pid3' and 'Pi5+Pit+Pid3' in indica-type accessions and 'Pik+Pib', 'Pik+Pita', 'Pik+Pb1', 'Pizt+Pia' and 'Pizt+Pita' in japonica-type accessions, which were able to confer effective resistance against M. oryzae. The above results provide good theoretical support for the rational utilization of combinations of major R genes in developing rice cultivars with broad-spectrum resistance.

  12. Genetic Analysis of δheld and δuvrd Mutations in Combination with Other Genes in the Recf Recombination Pathway in Escherichia Coli: Suppression of a Ruvb Mutation by a Uvrd Deletion

    PubMed Central

    Mendonca, V. M.; Matson, S. W.

    1995-01-01

    Helicase II (uvrD gene product) and helicase IV (helD gene product) have been shown previously to be involved in the RecF pathway of recombination. To better understand the role of these two proteins in homologous recombination in the RecF pathway [recBCsbcB(C) background], we investigated the interactions between helD, uvrD and the following RecF pathway genes: recF, recO, recN and ruvAB. We observed synergistic interactions between uvrD and the recF, recN, recO and recG genes in both conjugational recombination and the repair of methylmethane sulfonate (MMS)-induced DNA damage. No synergistic interactions were detected between helD and the recF, recO and recN genes when conjugational recombination was analyzed. We did, however, detect synergistic interactions between helD and recF/recO in recombinational repair. Suprisingly, the uvrD deletion completely suppressed the phenotype of a ruvB mutation in a recBCsbcB(C) background. Both conjugational recombination efficiency and MMS-damaged DNA repair proficiency returned to wild-type levels in the δuvrDruvB9 double mutant. Suppression of the effects of the ruvB mutation by a uvrD deletion was dependent on the recG and recN genes and not dependent on the recF/O/R genes. These data are discussed in the context of two ``RecF'' homologous recombination pathways operating in a recBCsbcB(C) strain background. PMID:8647383

  13. 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

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

    PubMed

    Feng, Yinling; Wang, Xuefeng

    2017-03-01

    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.

  15. Combining a regeneration-promoting ipt gene and site-specific recombination allows a more efficient apricot transformation and the elimination of marker genes.

    PubMed

    López-Noguera, Sonia; Petri, César; Burgos, Lorenzo

    2009-12-01

    The presence of marker genes conferring antibiotic resistance in transgenic plants represents a serious obstacle for their public acceptance and future commercialization. In addition, their elimination may allow gene stacking by the same selection strategy. In apricot, selection using the selectable marker gene nptII, that confers resistance to aminoglycoside antibiotics, is relatively effective. An attractive alternative is offered by the MAT system (multi-auto-transformation), which combines the ipt gene for positive selection with the recombinase system R/RS for removal of marker genes from transgenic cells after transformation. Transformation with an MAT vector has been attempted in the apricot cultivar 'Helena'. Regeneration from infected leaves with Agrobacterium harboring a plasmid containing the ipt gene was significantly higher than that from non-transformed controls in a non-selective medium. In addition, transformation efficiencies were much higher than those previously reported using antibiotic selection, probably due to the integration of the regeneration-promoting ipt gene. However, the lack of an ipt expression-induced differential phenotype in apricot made difficult in detecting the marker genes excision and plants had to be evaluated at different times. PCR analysis showed that cassette excision start occurring after 6 months approximately and 1 year in culture was necessary for complete elimination of the cassette in all the transgenic lines. Excision was confirmed by Southern blot analysis. We report here for the first time in a temperate fruit tree that the MAT vector system improves regeneration and transformation efficiency and would allow complete elimination of marker genes from transgenic apricot plants by site-specific recombination.

  16. Combined sense-antisense Alu elements activate the EGFP reporter gene when stable transfection.

    PubMed

    Ma, Zhihong; Kong, Xianglong; Liu, Shufeng; Yin, Shuxian; Zhao, Yuehua; Liu, Chao; Lv, Zhanjun; Wang, Xiufang

    2017-08-01

    Alu elements in the human genome are present in more than one million copies, accounting for 10% of the genome. However, the biological functions of most Alu repeats are unknown. In this present study, we detected the effects of Alu elements on EGFP gene expression using a plasmid system to find the roles of Alu elements in human genome. We inserted 5'-4TMI-Alus-CMV promoter-4TMI-Alus (or antisense Alus)-3' sequences into the pEGFP-C1 vector to construct expression vectors. We altered the copy number of Alus, the orientation of the Alus, and the presence of an enhancer (4TMI) in the inserted 5'-4TMI-Alus-CMV promoter-4TMI-Alus (or antisense Alus)-3' sequences. These expression vectors were stably transfected into HeLa cells, and EGFP reporter gene expression was determined. Our results showed that combined sense-antisense Alu elements activated the EGFP reporter gene in the presence of enhancers and stable transfection. The combined sense-antisense Alu vectors carrying four copies of Alus downstream of inserted CMV induced much stronger EGFP gene expression than two copies. Alus downstream of inserted CMV were replaced to AluJBs (having 76% homology with Alu) to construct expression vectors. We found that combined sense-antisense Alu (or antisense AluJB) vectors induced strong EGFP gene expression after stable transfection and heat shock. To further explore combined sense-antisense Alus activating EGFP gene expression, we constructed Tet-on system vectors, mini-C1-Alu-sense-sense and mini-C1-Alu-sense-antisense (EGFP gene was driven by mini-CMV). We found that combined sense-antisense Alus activated EGFP gene in the presence of reverse tetracycline repressor (rTetR) and doxycycline (Dox). Clone experiments showed that Mini-C1-Alu-sense-antisense vector had more positive cells than that of Mini-C1-Alu-sense-sense vector. The results in this paper proved that Alu repetitive sequences inhibited gene expression and combined sense-antisense Alus activated EGFP reporter

  17. Network Analysis of Human Genes Influencing Susceptibility to Mycobacterial Infections

    PubMed Central

    Lipner, Ettie M.; Garcia, Benjamin J.; Strong, Michael

    2016-01-01

    Tuberculosis and nontuberculous mycobacterial infections constitute a high burden of pulmonary disease in humans, resulting in over 1.5 million deaths per year. Building on the premise that genetic factors influence the instance, progression, and defense of infectious disease, we undertook a systems biology approach to investigate relationships among genetic factors that may play a role in increased susceptibility or control of mycobacterial infections. We combined literature and database mining with network analysis and pathway enrichment analysis to examine genes, pathways, and networks, involved in the human response to Mycobacterium tuberculosis and nontuberculous mycobacterial infections. This approach allowed us to examine functional relationships among reported genes, and to identify novel genes and enriched pathways that may play a role in mycobacterial susceptibility or control. Our findings suggest that the primary pathways and genes influencing mycobacterial infection control involve an interplay between innate and adaptive immune proteins and pathways. Signaling pathways involved in autoimmune disease were significantly enriched as revealed in our networks. Mycobacterial disease susceptibility networks were also examined within the context of gene-chemical relationships, in order to identify putative drugs and nutrients with potential beneficial immunomodulatory or anti-mycobacterial effects. PMID:26751573

  18. Combining gene mutation with gene expression data improves outcome prediction in myelodysplastic syndromes

    PubMed Central

    Gerstung, Moritz; Pellagatti, Andrea; Malcovati, Luca; Giagounidis, Aristoteles; Porta, Matteo G Della; Jädersten, Martin; Dolatshad, Hamid; Verma, Amit; Cross, Nicholas C. P.; Vyas, Paresh; Killick, Sally; Hellström-Lindberg, Eva; Cazzola, Mario; Papaemmanuil, Elli; Campbell, Peter J.; Boultwood, Jacqueline

    2015-01-01

    Cancer is a genetic disease, but two patients rarely have identical genotypes. Similarly, patients differ in their clinicopathological parameters, but how genotypic and phenotypic heterogeneity are interconnected is not well understood. Here we build statistical models to disentangle the effect of 12 recurrently mutated genes and 4 cytogenetic alterations on gene expression, diagnostic clinical variables and outcome in 124 patients with myelodysplastic syndromes. Overall, one or more genetic lesions correlate with expression levels of ~20% of all genes, explaining 20–65% of observed expression variability. Differential expression patterns vary between mutations and reflect the underlying biology, such as aberrant polycomb repression for ASXL1 and EZH2 mutations or perturbed gene dosage for copy-number changes. In predicting survival, genomic, transcriptomic and diagnostic clinical variables all have utility, with the largest contribution from the transcriptome. Similar observations are made on the TCGA acute myeloid leukaemia cohort, confirming the general trends reported here. PMID:25574665

  19. Phylomemetics—Evolutionary Analysis beyond the Gene

    PubMed Central

    Howe, Christopher J.; Windram, Heather F.

    2011-01-01

    Genes are propagated by error-prone copying, and the resulting variation provides the basis for phylogenetic reconstruction of evolutionary relationships. Horizontal gene transfer may be superimposed on a tree-like evolutionary pattern, with some relationships better depicted as networks. The copying of manuscripts by scribes is very similar to the replication of genes, and phylogenetic inference programs can be used directly for reconstructing the copying history of different versions of a manuscript text. Phylogenetic methods have also been used for some time to analyse the evolution of languages and the development of physical cultural artefacts. These studies can help to answer a range of anthropological questions. We propose the adoption of the term “phylomemetics” for phylogenetic analysis of reproducing non-genetic elements. PMID:21655311

  20. Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations.

    PubMed

    Yaari, Gur; Bolen, Christopher R; Thakar, Juilee; Kleinstein, Steven H

    2013-10-01

    Enrichment analysis of gene sets is a popular approach that provides a functional interpretation of genome-wide expression data. Existing tests are affected by inter-gene correlations, resulting in a high Type I error. The most widely used test, Gene Set Enrichment Analysis, relies on computationally intensive permutations of sample labels to generate a null distribution that preserves gene-gene correlations. A more recent approach, CAMERA, attempts to correct for these correlations by estimating a variance inflation factor directly from the data. Although these methods generate P-values for detecting gene set activity, they are unable to produce confidence intervals or allow for post hoc comparisons. We have developed a new computational framework for Quantitative Set Analysis of Gene Expression (QuSAGE). QuSAGE accounts for inter-gene correlations, improves the estimation of the variance inflation factor and, rather than evaluating the deviation from a null hypothesis with a P-value, it quantifies gene-set activity with a complete probability density function. From this probability density function, P-values and confidence intervals can be extracted and post hoc analysis can be carried out while maintaining statistical traceability. Compared with Gene Set Enrichment Analysis and CAMERA, QuSAGE exhibits better sensitivity and specificity on real data profiling the response to interferon therapy (in chronic Hepatitis C virus patients) and Influenza A virus infection. QuSAGE is available as an R package, which includes the core functions for the method as well as functions to plot and visualize the results.

  1. MAGMA: Generalized Gene-Set Analysis of GWAS Data

    PubMed Central

    de Leeuw, Christiaan A.; Mooij, Joris M.; Heskes, Tom; Posthuma, Danielle

    2015-01-01

    By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohn’s Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn’s Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohn’s Disease data was found to be considerably faster as well. PMID:25885710

  2. MAGMA: generalized gene-set analysis of GWAS data.

    PubMed

    de Leeuw, Christiaan A; Mooij, Joris M; Heskes, Tom; Posthuma, Danielle

    2015-04-01

    By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohn's Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn's Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohn's Disease data was found to be considerably faster as well.

  3. Combination of cold atmospheric plasma and iron nanoparticles in breast cancer: gene expression and apoptosis study

    PubMed Central

    Jalili, Azam; Irani, Shiva; Mirfakhraie, Reza

    2016-01-01

    Background Current cancer treatments have unexpected side effects of which the death of normal cells is one. In some cancers, iron nanoparticles (NPs) can be subjected to diagnosis and passive targeting treatment. Cold atmospheric plasma (CAP) has a proven induction of selective cell death ability. In this study, we have attempted to analyze the synergy between CAP and iron NPs in human breast adenocarcinoma cells (MCF-7). Materials and methods In vitro cytotoxicity of CAP treatment and NPs in cells measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and cell death was shown by 4′,6-diamidino-2-phenylindole and annexin V staining. Fluctuations in BAX and BCL-2 gene expression were investigated by means of real-time polymerase chain reaction. Results MTT assay results showed that combination of plasma and iron NPs decreased the viability of cancer cells significantly (P<0.05). Real-time analysis showed that the combination therapy induced shifting the BAX/BCL-2 ratio in favor of apoptosis. Conclusion Our data indicate that synergy between CAP and iron NPs can be applied in breast cancer treatment selectively. PMID:27729800

  4. Identification of Potential Transcriptomic Markers in Developing Ankylosing Spondylitis: A Meta-Analysis of Gene Expression Profiles

    PubMed Central

    Fang, Fang; Pan, Jian; Xu, Lixiao; Li, Gang; Wang, Jian

    2015-01-01

    The goal of this study was to identify potential transcriptomic markers in developing ankylosing spondylitis by a meta-analysis of multiple public microarray datasets. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed (DE) genes in ankylosing spondylitis and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DE genes identified in the meta-analysis. Three microarray datasets (26 cases and 29 controls in total) were collected for meta-analysis. 905 consistently DE genes were identified in ankylosing spondylitis, among which 482 genes were upregulated and 423 genes were downregulated. The upregulated gene with the smallest combined rank product (RP) was GNG11 (combined RP = 299.64). The downregulated gene with the smallest combined RP was S100P (combined RP = 335.94). In the gene ontology (GO) analysis, the most significantly enriched GO term was “immune system process” (P = 3.46 × 10−26). The most significant pathway identified in the pathway analysis was antigen processing and presentation (P = 8.40 × 10−5). The consistently DE genes in ankylosing spondylitis and biological pathways associated with those DE genes identified provide valuable information for studying the pathophysiology of ankylosing spondylitis. PMID:25688367

  5. Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes.

    PubMed

    Arvind, Prathima; Jayashree, Shanker; Jambunathan, Srikarthika; Nair, Jiny; Kakkar, Vijay V

    2015-12-01

    Molecular mechanism underlying the patho-physiology of coronary artery disease (CAD) is complex. We used global expression profiling combined with analysis of biological network to dissect out potential genes and pathways associated with CAD in a representative case-control Asian Indian cohort. We initially performed blood transcriptomics profiling in 20 subjects, including 10 CAD patients and 10 healthy controls on the Agilent microarray platform. Data was analysed with Gene Spring Gx12.5, followed by network analysis using David v 6.7 and Reactome databases. The most significant differentially expressed genes from microarray were independently validated by real time PCR in 97 cases and 97 controls. A total of 190 gene transcripts showed significant differential expression (fold change>2,P<0.05) between the cases and the controls of which 142 genes were upregulated and 48 genes were downregulated. Genes associated with inflammation, immune response, cell regulation, proliferation and apoptotic pathways were enriched, while inflammatory and immune response genes were displayed as hubs in the network, having greater number of interactions with the neighbouring genes. Expression of EGR1/2/3, IL8, CXCL1, PTGS2, CD69, IFNG, FASLG, CCL4, CDC42, DDX58, NFKBID and NR4A2 genes were independently validated; EGR1/2/3 and IL8 showed >8-fold higher expression in cases relative to the controls implying their important role in CAD. In conclusion, global gene expression profiling combined with network analysis can help in identifying key genes and pathways for CAD.

  6. Classification of breast cancer subtypes by combining gene expression and DNA methylation data.

    PubMed

    List, Markus; Hauschild, Anne-Christin; Tan, Qihua; Kruse, Torben A; Mollenhauer, Jan; Baumbach, Jan; Batra, Richa

    2014-06-13

    Selecting the most promising treatment strategy for breast cancer crucially depends on determining the correct subtype. In recent years, gene expression profiling has been investigated as an alternative to histochemical methods. Since databases like TCGA provide easy and unrestricted access to gene expression data for hundreds of patients, the challenge is to extract a minimal optimal set of genes with good prognostic properties from a large bulk of genes making a moderate contribution to classification. Several studies have successfully applied machine learning algorithms to solve this so-called gene selection problem. However, more diverse data from other OMICS technologies are available, including methylation. We hypothesize that combining methylation and gene expression data could already lead to a largely improved classification model, since the resulting model will reflect differences not only on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10-20% and classification error of 1-50%, depending on breast cancer subtype and model. The gene expression model was clearly superior to the methylation model, which was also reflected in the combined model, which mainly selected features from gene expression data. However, the methylation model was able to identify unique features not considered as relevant by the gene expression model, which might provide deeper insights into breast cancer subtype differentiation on an epigenetic level.

  7. Gene expression analysis of flax seed development.

    PubMed

    Venglat, Prakash; Xiang, Daoquan; Qiu, Shuqing; Stone, Sandra L; Tibiche, Chabane; Cram, Dustin; Alting-Mees, Michelle; Nowak, Jacek; Cloutier, Sylvie; Deyholos, Michael; Bekkaoui, Faouzi; Sharpe, Andrew; Wang, Edwin; Rowland, Gordon; Selvaraj, Gopalan; Datla, Raju

    2011-04-29

    Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages) seed coats (globular and torpedo stages) and endosperm (pooled globular to torpedo stages) and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST) (GenBank accessions LIBEST_026995 to LIBEST_027011) were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152) had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. We have developed a foundational database of expressed sequences and collection of plasmid clones that comprise even low-expressed genes such as

  8. Gene expression analysis of flax seed development

    PubMed Central

    2011-01-01

    Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages) seed coats (globular and torpedo stages) and endosperm (pooled globular to torpedo stages) and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST) (GenBank accessions LIBEST_026995 to LIBEST_027011) were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152) had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid clones that comprise

  9. Bullous impetigo in children infected with methicillin-resistant Staphylococcus aureus alone or in combination with methicillin-susceptible S. aureus: analysis of genetic characteristics, including assessment of exfoliative toxin gene carriage.

    PubMed

    Shi, Da; Higuchi, Wataru; Takano, Tomomi; Saito, Kohei; Ozaki, Kyoko; Takano, Misao; Nitahara, Yoshiyuki; Yamamoto, Tatsuo

    2011-05-01

    Among bullous impetigo isolates, exfoliative toxin (ET) gene carriage was found in 61.5% of methicillin-resistant Staphylococcus aureus (MRSA) isolates versus 90.6% of methicillin-susceptible S. aureus (MSSA) isolates. MRSA-only cases were ETB or ETA positive, while MRSA/MSSA coinfection cases were ET negative for MRSA but ETA positive for MSSA. Collagen adhesin may facilitate some MRSA infections.

  10. Bullous Impetigo in Children Infected with Methicillin-Resistant Staphylococcus aureus Alone or in Combination with Methicillin-Susceptible S. aureus: Analysis of Genetic Characteristics, Including Assessment of Exfoliative Toxin Gene Carriage▿

    PubMed Central

    Shi, Da; Higuchi, Wataru; Takano, Tomomi; Saito, Kohei; Ozaki, Kyoko; Takano, Misao; Nitahara, Yoshiyuki; Yamamoto, Tatsuo

    2011-01-01

    Among bullous impetigo isolates, exfoliative toxin (ET) gene carriage was found in 61.5% of methicillin-resistant Staphylococcus aureus (MRSA) isolates versus 90.6% of methicillin-susceptible S. aureus (MSSA) isolates. MRSA-only cases were ETB or ETA positive, while MRSA/MSSA coinfection cases were ET negative for MRSA but ETA positive for MSSA. Collagen adhesin may facilitate some MRSA infections. PMID:21430094

  11. Comparative genomic analysis of prion genes

    PubMed Central

    Premzl, Marko; Gamulin, Vera

    2007-01-01

    Background The homologues of human disease genes are expected to contribute to better understanding of physiological and pathogenic processes. We made use of the present availability of vertebrate genomic sequences, and we have conducted the most comprehensive comparative genomic analysis of the prion protein gene PRNP and its homologues, shadow of prion protein gene SPRN and doppel gene PRND, and prion testis-specific gene PRNT so far. Results While the SPRN and PRNP homologues are present in all vertebrates, PRND is known in tetrapods, and PRNT is present in primates. PRNT could be viewed as a TE-associated gene. Using human as the base sequence for genomic sequence comparisons (VISTA), we annotated numerous potential cis-elements. The conserved regions in SPRNs harbour the potential Sp1 sites in promoters (mammals, birds), C-rich intron splicing enhancers and PTB intron splicing silencers in introns (mammals, birds), and hsa-miR-34a sites in 3'-UTRs (eutherians). We showed the conserved PRNP upstream regions, which may be potential enhancers or silencers (primates, dog). In the PRNP 3'-UTRs, there are conserved cytoplasmic polyadenylation element sites (mammals, birds). The PRND core promoters include highly conserved CCAAT, CArG and TATA boxes (mammals). We deduced 42 new protein primary structures, and performed the first phylogenetic analysis of all vertebrate prion genes. Using the protein alignment which included 122 sequences, we constructed the neighbour-joining tree which showed four major clusters, including shadoos, shadoo2s and prion protein-likes (cluster 1), fish prion proteins (cluster 2), tetrapode prion proteins (cluster 3) and doppels (cluster 4). We showed that the entire prion protein conformationally plastic region is well conserved between eutherian prion proteins and shadoos (18–25% identity and 28–34% similarity), and there could be a potential structural compatibility between shadoos and the left-handed parallel beta-helical fold

  12. Correction of ADA-SCID by stem cell gene therapy combined with nonmyeloablative conditioning.

    PubMed

    Aiuti, Alessandro; Slavin, Shimon; Aker, Memet; Ficara, Francesca; Deola, Sara; Mortellaro, Alessandra; Morecki, Shoshana; Andolfi, Grazia; Tabucchi, Antonella; Carlucci, Filippo; Marinello, Enrico; Cattaneo, Federica; Vai, Sergio; Servida, Paolo; Miniero, Roberto; Roncarolo, Maria Grazia; Bordignon, Claudio

    2002-06-28

    Hematopoietic stem cell (HSC) gene therapy for adenosine deaminase (ADA)-deficient severe combined immunodeficiency (SCID) has shown limited clinical efficacy because of the small proportion of engrafted genetically corrected HSCs. We describe an improved protocol for gene transfer into HSCs associated with nonmyeloablative conditioning. This protocol was used in two patients for whom enzyme replacement therapy was not available, which allowed the effect of gene therapy alone to be evaluated. Sustained engraftment of engineered HSCs with differentiation into multiple lineages resulted in increased lymphocyte counts, improved immune functions (including antigen-specific responses), and lower toxic metabolites. Both patients are currently at home and clinically well, with normal growth and development. These results indicate the safety and efficacy of HSC gene therapy combined with nonmyeloablative conditioning for the treatment of SCID.

  13. [Antitumor research on mouse melanoma with combined application of Newcastle disease virus and its HN gene].

    PubMed

    Mi, Zhi-Qiang; Jin, Ning-Yi; Sun, Ying-Chun; Li, Xiao; Lian, Hai; Li, Jie; Guan, Guo-Fang

    2004-08-01

    Although Newcastle disease virus (NDV) shows antitumor effect on many tumors, its mechanism is unclear. Hemagglutinin-neuraminidase (HN) gene was found to play an important role in NDV antitumor effect and HN protein located on tumor cell surface. This research was to evaluate the possibility of HN protein as a foreign antigen of tumor cell and the antitumor effect of the combined application of HN gene and NDV. C57BL/6 mice were subcutaneously inoculated with 2 x 10(5) B16 tumor cells in the right hindlimb. Combination group: on 2nd day post-inoculation, the recombinant plasmid containing HN gene was injected intramuscularly in the left hindlimb; on 7th day post-inoculation, 2 x 10(9) pfu NDV was administrated intratumorally. The alone HN gene group, NDV group, and PBS control group were treated as above. The antitumor effect was observed through tumor suppression rate, the antitumor mechanisms were researched with specific cytotoxic T lymphocyte (CTL) assay, and the expression determination of HN protein, ICAM-I, and CD48 on the B16 tumor cells. The antitumor efficacy of the combined application of NDV and its HN gene increased compared with NDV,and its HN gene alone, the tumor suppression rates were 82.8%, 41.0%, and 56.6%; the specific CTL activity were 18.4%, 10.1%, and 4.4%, respectively. Furthermore, the expression of HN gene had been detected, and the expression of ICAM-I and CD48 were up-regulated on the tumor cells after NDV injection. HN protein located on the surface of tumor cells and mediated the specific repulsion to tumor cells; the antitumor efficacy increased after the combined application of NDV and its HN gene.

  14. Gene therapy for severe combined immunodeficiency due to adenosine deaminase deficiency.

    PubMed

    Montiel-Equihua, Claudia A; Thrasher, Adrian J; Gaspar, H Bobby

    2012-02-01

    The severe combined immunodeficiency caused by the absence of adenosine deaminase (SCID-ADA) was the first monogenic disorder for which gene therapy was developed. Over 30 patients have been treated worldwide using the current protocols, and most of them have experienced clinical benefit; importantly, in the absence of any vector-related complications. In this document, we review the progress made so far in the development and establishment of gene therapy as an alternative form of treatment for ADA-SCID patients.

  15. Bioinformatic analysis of nematode migration-associated genes identifies novel vertebrate neural crest markers.

    PubMed

    Kwon, Seung-Hae; Park, Ok Kyu; Nie, Shuyi; Kwak, Jina; Hwang, Byung Joon; Bronner, Marianne E; Kee, Yun

    2014-01-01

    Neural crest cells are highly motile, yet a limited number of genes governing neural crest migration have been identified by conventional studies. To test the hypothesis that cell migration genes are likely to be conserved over large evolutionary distances and from diverse tissues, we searched for vertebrate homologs of genes important for migration of various cell types in the invertebrate nematode and examined their expression during vertebrate neural crest cell migration. Our systematic analysis utilized a combination of comparative genomic scanning, functional pathway analysis and gene expression profiling to uncover previously unidentified genes expressed by premigratory, emigrating and/or migrating neural crest cells. The results demonstrate that similar gene sets are expressed in migratory cell types across distant animals and different germ layers. Bioinformatics analysis of these factors revealed relationships between these genes within signaling pathways that may be important during neural crest cell migration.

  16. Analysis of MHC class I genes across horse MHC haplotypes

    PubMed Central

    Tallmadge, Rebecca L.; Campbell, Julie A.; Miller, Donald C.; Antczak, Douglas F.

    2010-01-01

    The genomic sequences of 15 horse Major Histocompatibility Complex (MHC) class I genes and a collection of MHC class I homozygous horses of five different haplotypes were used to investigate the genomic structure and polymorphism of the equine MHC. A combination of conserved and locus-specific primers was used to amplify horse MHC class I genes with classical and non-classical characteristics. Multiple clones from each haplotype identified three to five classical sequences per homozygous animal, and two to three non-classical sequences. Phylogenetic analysis was applied to these sequences and groups were identified which appear to be allelic series, but some sequences were left ungrouped. Sequences determined from MHC class I heterozygous horses and previously described MHC class I sequences were then added, representing a total of ten horse MHC haplotypes. These results were consistent with those obtained from the MHC homozygous horses alone, and 30 classical sequences were assigned to four previously confirmed loci and three new provisional loci. The non-classical genes had few alleles and the classical genes had higher levels of allelic polymorphism. Alleles for two classical loci with the expected pattern of polymorphism were found in the majority of haplotypes tested, but alleles at two other commonly detected loci had more variation outside of the hypervariable region than within. Our data indicate that the equine Major Histocompatibility Complex is characterized by variation in the complement of class I genes expressed in different haplotypes in addition to the expected allelic polymorphism within loci. PMID:20099063

  17. Separate enrichment analysis of pathways for up- and downregulated genes.

    PubMed

    Hong, Guini; Zhang, Wenjing; Li, Hongdong; Shen, Xiaopei; Guo, Zheng

    2014-03-06

    Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

  18. Analysis of baseline gene expression levels from ...

    EPA Pesticide Factsheets

    The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

  19. Network analysis of genes and their association with diseases.

    PubMed

    Kontou, Panagiota I; Pavlopoulou, Athanasia; Dimou, Niki L; Pavlopoulos, Georgios A; Bagos, Pantelis G

    2016-09-15

    A plethora of network-based approaches within the Systems Biology universe have been applied, to date, to investigate the underlying molecular mechanisms of various human diseases. In the present study, we perform a bipartite, topological and clustering graph analysis in order to gain a better understanding of the relationships between human genetic diseases and the relationships between the genes that are implicated in them. For this purpose, disease-disease and gene-gene networks were constructed from combined gene-disease association networks. The latter, were created by collecting and integrating data from three diverse resources, each one with different content covering from rare monogenic disorders to common complex diseases. This data pluralism enabled us to uncover important associations between diseases with unrelated phenotypic manifestations but with common genetic origin. For our analysis, the topological attributes and the functional implications of the individual networks were taken into account and are shortly discussed. We believe that some observations of this study could advance our understanding regarding the etiology of a disease with distinct pathological manifestations, and simultaneously provide the springboard for the development of preventive and therapeutic strategies and its underlying genetic mechanisms.

  20. Gene delivery systems by the combination of lipid bubbles and ultrasound.

    PubMed

    Negishi, Yoichi; Endo-Takahashi, Yoko; Maruyama, Kazuo

    2016-11-28

    Gene therapy is promising for the treatment of many diseases including cancers and genetic diseases. From the viewpoint of safety, ultrasound (US)-mediated gene delivery with nano/ microbubbles was recently developed as a novel non-viral vector system. US-mediated gene delivery using nano/microbubbles are able to produce transient changes in the permeability of the cell membrane after US-induced cavitation while reducing cellular damage and enables the tissue-specific or the site-specific intracellular delivery of gene both in vitro and in vivo. We have recently developed novel lipid nanobubbles (Lipid Bubbles). These nanobubbles can also be used to enhance the efficacy of the US-mediated genes (plasmid DNA, siRNA, and miRNA etc.) delivery. In this review, we describe US-mediated delivery systems combined with nano/microbubbles and discuss their feasibility as non-viral vector systems.

  1. The evolution of gene therapy in X-linked severe combined immunodeficiency.

    PubMed

    Rans, Tonya S; England, Ronald

    2009-05-01

    To review the evolution of gene therapy in infants with X-linked severe combined immunodeficiency (XL-SCID) and to evaluate the current challenges facing this evolving field. The MEDLINE, OVID, CINAHL, and HealthSTAR databases were searched to identify pertinent articles using the following keywords: gene therapy, XL-SCID, bone marrow transplant, and viral vectors. Journal articles were selected for their relevance to human gene therapy in patients with XL-SCID. Gene therapy with a retrovirus-derived vector has been used to treat 20 patients with XL-SCID internationally. Although most patients derived improvements in T- and B-cell immune numbers and function, severe adverse effects have occurred. After gene therapy, 5 of the 20 patients developed leukemia. This outcome has been associated with insertion of the corrected gene near the T-cell proto-oncogene LMO2. One of the 5 patients subsequently died. Within the past decade, effective improvements in vectorology and cell culture conditions have resulted in clinical success in some infants with SCID and have revived interest after many years of setbacks. However, clinical success and significant adverse events have been reported in patients with XL-SCID who have undergone gene therapy using a retroviral vector. As extensive research into improving safety through vector development and monitoring of gene therapy continues, further progress in gene therapy development can be anticipated.

  2. CEDER: Accurate detection of differentially expressed genes by combining significance of exons using RNA-Seq

    PubMed Central

    Wan, Lin; Sun, Fengzhu

    2012-01-01

    RNA-Seq is widely used in transcriptome studies, and the detection of differentially expressed genes (DEGs) between two classes of individuals, e.g. cases vs controls, using RNA-Seq is of fundamental importance. Many statistical methods for DEG detection based on RNA-Seq data have been developed and most of them are based on the read counts mapped to individual genes. On the other hand, genes are composed of exons and the distribution of reads for the different exons can be heterogeneous. We hypothesize that the detection accuracy of differentially expressed genes can be increased by analyzing individual exons within a gene and then combining the results of the exons. We therefore developed a novel program, termed CEDER, to accurately detect DGEs by combining the significance of the exons. CEDER first tests for differentially expressed exons yielding a p-value for each, and then gives a score indicating the potential for a gene to be differentially expressed by integrating the p-values of the exons in the gene. We showed that CEDER can significantly increase the accuracy of existing methods for detecting DEGs on two benchmark RNA-Seq datasets and simulated datasets. PMID:22641709

  3. Selection of reference genes for qRT-PCR analysis of gene expression in sea cucumber Apostichopus japonicus during aestivation

    NASA Astrophysics Data System (ADS)

    Zhao, Ye; Chen, Muyan; Wang, Tianming; Sun, Lina; Xu, Dongxue; Yang, Hongsheng

    2014-11-01

    Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a technique that is widely used for gene expression analysis, and its accuracy depends on the expression stability of the internal reference genes used as normalization factors. However, many applications of qRT-PCR used housekeeping genes as internal controls without validation. In this study, the expression stability of eight candidate reference genes in three tissues (intestine, respiratory tree, and muscle) of the sea cucumber Apostichopus japonicus was assessed during normal growth and aestivation using the geNorm, NormFinder, delta CT, and RefFinder algorithms. The results indicate that the reference genes exhibited significantly different expression patterns among the three tissues during aestivation. In general, the β-tubulin (TUBB) gene was relatively stable in the intestine and respiratory tree tissues. The optimal reference gene combination for intestine was 40S ribosomal protein S18 (RPS18), TUBB, and NADH dehydrogenase (NADH); for respiratory tree, it was β-actin (ACTB), TUBB, and succinate dehydrogenase cytochrome B small subunit (SDHC); and for muscle it was α-tubulin (TUBA) and NADH dehydrogenase [ubiquinone] 1 α subcomplex subunit 13 (NDUFA13). These combinations of internal control genes should be considered for use in further studies of gene expression in A. japonicus during aestivation.

  4. Growth inhibition of human pancreatic cancer cells by human interferon-beta gene combined with gemcitabine.

    PubMed

    Endou, Masato; Mizuno, Masaaki; Nagata, Takuya; Tsukada, Kazuhiro; Nakahara, Norimoto; Tsuno, Takaya; Osawa, Hirokatsu; Kuno, Tomohiko; Fujita, Mitsugu; Hatano, Manabu; Yoshida, Jun

    2005-02-01

    We examined the anti-tumor effect of cationic multilamellar liposome containing human IFN-beta (huIFN-beta) gene against cultured human pancreatic cancer cells. We also evaluated the combined effect of huIFN-beta gene entrapped in liposomes and gemcitabine. Furthermore, we examined the anti-tumor mechanisms of the therapy, with emphasis on the Ras-related signal pathway. Three human pancreatic cancer cell lines (AsPc-1, MIAPaCa-2, and PANC-1) were used in this study. The growth inhibition together with the therapy were evaluated by WST-1 assay; the production of huIFN-beta protein was measured by ELISA; the cell cycle and apoptosis were analyzed using a FACScan flow cytometer; the protein levels of Son of sevenless (SOS-1) and Ras-GAP were measured by Western blotting; and the activation of Ras-GTP was evaluated by the immunoprecipitation method. As a result, we found that huIFN-beta gene entrapped in liposomes demonstrated a strong anti-tumor effect against human pancreatic cancer cells. The treatment that combined huIFN-beta gene entrapped in liposomes and gemcitabine was more effective than each treatment alone. Although gemcitabine remarkably reduced the level of SOS-1, the above combined therapy reduced the level of SOS-1 even more significantly. Both huIFN-beta gene entrapped in liposomes and the com-bination of huIFN-beta gene entrapped in liposomes and gemcitabine increased the level of Ras-GAP, and decreased the activity of Ras-GTP. These results suggest that this combination therapy can induce strong anti-tumor activity against human pancreatic cancer cells through the regulation of the Ras-related signal pathway.

  5. 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.

  6. Human gene copy number spectra analysis in congenital heart malformations

    PubMed Central

    Mahnke, Donna K.; Struble, Craig A.; Tuffnell, Maureen E.; Stamm, Karl D.; Hidestrand, Mats; Harris, Susan E.; Goetsch, Mary A.; Simpson, Pippa M.; Bick, David P.; Broeckel, Ulrich; Pelech, Andrew N.; Tweddell, James S.; Mitchell, Michael E.

    2012-01-01

    The clinical significance of copy number variants (CNVs) in congenital heart disease (CHD) continues to be a challenge. Although CNVs including genes can confer disease risk, relationships between gene dosage and phenotype are still being defined. Our goal was to perform a quantitative analysis of CNVs involving 100 well-defined CHD risk genes identified through previously published human association studies in subjects with anatomically defined cardiac malformations. A novel analytical approach permitting CNV gene frequency “spectra” to be computed over prespecified regions to determine phenotype-gene dosage relationships was employed. CNVs in subjects with CHD (n = 945), subphenotyped into 40 groups and verified in accordance with the European Paediatric Cardiac Code, were compared with two control groups, a disease-free cohort (n = 2,026) and a population with coronary artery disease (n = 880). Gains (≥200 kb) and losses (≥100 kb) were determined over 100 CHD risk genes and compared using a Barnard exact test. Six subphenotypes showed significant enrichment (P ≤ 0.05), including aortic stenosis (valvar), atrioventricular canal (partial), atrioventricular septal defect with tetralogy of Fallot, subaortic stenosis, tetralogy of Fallot, and truncus arteriosus. Furthermore, CNV gene frequency spectra were enriched (P ≤ 0.05) for losses at: FKBP6, ELN, GTF2IRD1, GATA4, CRKL, TBX1, ATRX, GPC3, BCOR, ZIC3, FLNA and MID1; and gains at: PRKAB2, FMO5, CHD1L, BCL9, ACP6, GJA5, HRAS, GATA6 and RUNX1. Of CHD subjects, 14% had causal chromosomal abnormalities, and 4.3% had likely causal (significantly enriched), large, rare CNVs. CNV frequency spectra combined with precision phenotyping may lead to increased molecular understanding of etiologic pathways. PMID:22318994

  7. 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

  8. Rabbit MSTN gene polymorphisms and genetic effect analysis.

    PubMed

    Qiao, X B; Xu, K Y; Li, B; Luan, X; Xia, T; Fan, X Z

    2014-04-08

    We analyzed meat samples of nine pure lines of rabbit and its 37 hybrid combinations by sequencing and single-strand conformation polymorphism techniques to explore genetic polymorphisms of all the three exon regions and part of the 5'-regulatory region of the myostatin (MSTN) gene. Thus, we detected a single nucleotide mutation (T→C) on the 476 locus of the 5'-regulatory region, but no mutation sites were detected in the exon areas. The correlation analysis showed that the mutation had some favorable genetic effects, and it resulted in increased liver weight, carcass weight, forelegs weight, back and waist weight, ham weight, and tare weight, whereas it decreased muscle drip loss and cooking loss (P < 0.05). These results suggest that the mutations in the upstream regulatory region of the MSTN gene are beneficial to the rabbit soma development, and the mutations can be used as molecular markers for the selection of the meat quality of rabbits.

  9. Combining growth-promoting genes leads to positive epistasis in Arabidopsis thaliana

    PubMed Central

    Vanhaeren, Hannes; Gonzalez, Nathalie; Coppens, Frederik; De Milde, Liesbeth; Van Daele, Twiggy; Vermeersch, Mattias; Eloy, Nubia B; Storme, Veronique; Inzé, Dirk

    2014-01-01

    Several genes positively influence final leaf size in Arabidopsis when mutated or overexpressed. The connections between these growth regulators are still poorly understood although such knowledge would further contribute to understand the processes driving leaf growth. In this study, we performed a combinatorial screen with 13 transgenic Arabidopsis lines with an increased leaf size. We found that from 61 analyzed combinations, 39% showed an additional increase in leaf size and most resulted from a positive epistasis on growth. Similar to what is found in other organisms in which such an epistasis assay was performed, only few genes were highly connected in synergistic combinations as we observed a positive epistasis in the majority of the combinations with samba, BRI1OE or SAUR19OE. Furthermore, positive epistasis was found with combinations of genes with a similar mode of action, but also with genes which affect distinct processes, such as cell proliferation and cell expansion. DOI: http://dx.doi.org/10.7554/eLife.02252.001 PMID:24843021

  10. Identification of metastasis-associated genes in colorectal cancer through an integrated genomic and transcriptomic analysis

    PubMed Central

    Peng, Sihua

    2013-01-01

    Objective Identification of colorectal cancer (CRC) metastasis genes is one of the most important issues in CRC research. For the purpose of mining CRC metastasis-associated genes, an integrated analysis of microarray data was presented, by combined with evidence acquired from comparative genomic hybridization (CGH) data. Methods Gene expression profile data of CRC samples were obtained at Gene Expression Omnibus (GEO) website. The 15 important chromosomal aberration sites detected by using CGH technology were used for integrated genomic and transcriptomic analysis. Significant Analysis of Microarray (SAM) was used to detect significantly differentially expressed genes across the whole genome. The overlapping genes were selected in their corresponding chromosomal aberration regions, and analyzed by using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Finally, SVM-T-RFE gene selection algorithm was applied to identify metastasis-associated genes in CRC. Results A minimum gene set was obtained with the minimum number [14] of genes, and the highest classification accuracy (100%) in both PRI and META datasets. A fraction of selected genes are associated with CRC or its metastasis. Conclusions Our results demonstrated that integration analysis is an effective strategy for mining cancer-associated genes. PMID:24385689

  11. Analysis of human disease genes in the context of gene essentiality.

    PubMed

    Park, Donghyun; Park, Jungsun; Park, Seung Gu; Park, Taesung; Choi, Sun Shim

    2008-12-01

    The characteristics of human disease genes were investigated through a comparative analysis with mouse mutant phenotype data. Mouse orthologs with mutations that resulted in discernible phenotypes were separated from mutations with no phenotypic defect, listing 'phenotype' and 'no phenotype' genes. First, we showed that phenotype genes are more likely to be disease genes compared to no phenotype genes. Phenotype genes were further divided into 'embryonic lethal', 'postnatal lethal', and 'non-lethal phenotype' groups. Interestingly, embryonic lethal genes, the most essential genes in mouse, were less likely to be disease genes than postnatal lethal genes. These findings indicate that some extremely essential genes are less likely to be disease genes, although human disease genes tend to display characteristics of essential genes. We also showed that, in lethal groups, non-disease genes tend to evolve slower than disease genes indicating a strong purifying selection on non-disease genes in this group. In addition, phenotype and no phenotype groups showed differing types of disease mutations. Disease genes in the no phenotype group displayed a higher frequency of regulatory mutations while those in the phenotype group had more frequent coding mutations, indicating that the types of disease mutations vary depending on gene essentiality. Furthermore, missense disease mutations in no phenotype genes were found to be more radical amino acid substitutions than those in phenotype genes.

  12. GeneSigDB: a manually curated database and resource for analysis of gene expression signatures

    PubMed Central

    Culhane, Aedín C.; Schröder, Markus S.; Sultana, Razvan; Picard, Shaita C.; Martinelli, Enzo N.; Kelly, Caroline; Haibe-Kains, Benjamin; Kapushesky, Misha; St Pierre, Anne-Alyssa; Flahive, William; Picard, Kermshlise C.; Gusenleitner, Daniel; Papenhausen, Gerald; O'Connor, Niall; Correll, Mick; Quackenbush, John

    2012-01-01

    GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a ‘basket’ feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org. PMID:22110038

  13. Identification of suitable reference genes for quantitative gene expression analysis in rat adipose stromal cells induced to trilineage differentiation.

    PubMed

    Santos, Bruno Paiva Dos; da Costa Diesel, Luciana Fraga; da Silva Meirelles, Lindolfo; Nardi, Nance Beyer; Camassola, Melissa

    2016-12-15

    This study was designed to (i) identify stable reference genes for the analysis of gene expression during in vitro differentiation of rat adipose stromal cells (rASCs), (ii) recommend stable genes for individual treatment conditions, and (iii) validate these genes by comparison with normalization results from stable and unstable reference genes. On the basis of a literature review, eight genes were selected: Actb, B2m, Hprt1, Ppia, Rplp0, Rpl13a, Rpl5, and Ywhaz. Genes were ranked according to their stability under different culture conditions as assessed using GenNorm, NormFinder, and RefFinder algorithms. Although the employed algorithms returned different rankings, the most frequently top-ranked genes were: B2m and/or Ppia for all 28day treatments (ALL28); Ppia and Hprt1 (adipogenic differentiation; A28), B2m (chondrogenic differentiation; C28), Rpl5 (controls maintained in complete culture medium; CCM), Rplp0 (osteogenic differentiation for 3days; O3), Rpl13a and Actb (osteogenic differentiation for 7days; O7), Rplp0 and Ppia (osteogenic differentiation for 14days; O14), Hprt1 and Ppia (osteogenic differentiation for 28days; O28), as well as Actb (all osteogenesis time points combined; ALLOSTEO). The obtained results indicate that the performance of reference genes depends on the differentiation protocol and on the analysis time, thus providing valuable information for the design of RT-PCR experiments.

  14. Gene expression profiling of acute type A aortic dissection combined with in vitroassessment†.

    PubMed

    Kimura, Naoyuki; Futamura, Kyoko; Arakawa, Mamoru; Okada, Naoko; Emrich, Fabian; Okamura, Homare; Sato, Tetsuya; Shudo, Yasuhiro; Koyano, Tiffany K; Yamaguchi, Atsushi; Adachi, Hideo; Matsuda, Akio; Kawahito, Koji; Matsumoto, Kenji; Fischbein, Michael P

    2017-04-11

    The mechanisms underlying aortic dissection remain to be fully elucidated. We aimed to identify key molecules driving dissection through gene expression profiling achieved by microarray analysis and subsequent in vitro experiments using human aortic endothelial cells (HAECs) and aortic vascular smooth muscle cells (AoSMCs). Total RNA, including microRNA (miRNA), was isolated from the intima-media layer of dissected ascending aorta obtained intraoperatively from acute type A aortic dissection (ATAAD) patients without familial thoracic aortic disease ( n  = 8) and that of non-dissected ascending aorta obtained from transplant donors ( n  = 9). Gene expression profiling was performed with mRNA and miRNA microarrays, and results were confirmed by quantitative polymerase chain reaction (qPCR). Target genes and miRNA were identified by gene ontology analysis and a literature search. To reproduce the in silico results, HAECs and AoSMCs were stimulated in vitro by upstream cytokines, and expression of target genes was assessed by qPCR. Microarray analysis revealed 1536 genes (3.6%, 1536/42 545 probes) and 41 miRNAs (3.0%, 41/1368 probes) that were differentially expressed in the ATAAD group (versus donor group). The top 15 related pathways included regulation of inflammatory response, growth factor activity and extracellular matrix. Gene ontology analysis identified JAK2 (regulation of inflammatory response), PDGFA, TGFB1, VEGFA (growth factor activity) and TIMP3 , TIMP4, SERPINE1 (extracellular matrix) as the target genes and miR-21-5p, a TIMP3 repressor, as target miRNA that interacts with the target genes. Validation qPCR confirmed the altered expression of all 7 target genes and miR-21-5p in dissected aorta specimens (all genes, P  < 0.05). Ingenuity pathway analysis showed TNF-α and TGF-β to be upstream cytokines for the target genes. In vitro experiments showed these cytokines inhibit TIMP3 expression ( P  < 0.05) and enhance VEGFA expression ( P

  15. Combination effect of cytochrome P450 1A1 gene polymorphisms on uterine leiomyoma: A case-control study

    PubMed Central

    Salimi, Saeedeh; Sajadian, Mojtaba; Khodamian, Maryam; Yazdi, Atefeh; Rezaee, Soodabeh; Mohammadpour-Gharehbagh, Abbas; Mokhtari, Mojgan; Yaghmaie, Minoo

    2016-01-01

    Uterine leiomyoma (UL) is an estrogen-dependent neoplasm of the uterus, and estrogen metabolizing enzymes affect its progression. This study aimed to evaluate the association between two single-nucleotide polymorphisms of cytochrome P450 1A1 (CYP1A1) gene and UL risk. The study consisted of 105 patients with UL and 112 healthy women as controls. Ile462Val (A/G) and Asp449Asp (T/C) polymorphisms of CYP1A1 gene were analyzed by DNA sequencing and polymerase chain reaction-restriction fragment length polymorphism methods, respectively. The findings indicated no association between Ile462Val (A/G) and Asp449Asp (T/C) polymorphisms of CYP1A1 gene and UL (p < 0.05). However, the combination effect of TT/AG genotypes of the Asp449Asp (T/C) and Ile462Val (A/G) polymorphisms was associated with 4.3-fold higher risk of UL. In addition, haplotype analysis revealed that TG haplotype of the Asp449Asp (T/C) and Ile462Val (A/G) polymorphisms could increase the UL risk nearly 4.9-fold. Asp449Asp (T/C) and Ile462Val (A/G) polymorphisms of CYP1A1 gene were not associated with UL susceptibility; however, the combination of the TT/AG genotypes and TG haplotype could increase the UL risk. PMID:27333216

  16. Phylogeny Inference of Closely Related Bacterial Genomes: Combining the Features of Both Overlapping Genes and Collinear Genomic Regions

    PubMed Central

    Zhang, Yan-Cong; Lin, Kui

    2015-01-01

    Overlapping genes (OGs) represent one type of widespread genomic feature in bacterial genomes and have been used as rare genomic markers in phylogeny inference of closely related bacterial species. However, the inference may experience a decrease in performance for phylogenomic analysis of too closely or too distantly related genomes. Another drawback of OGs as phylogenetic markers is that they usually take little account of the effects of genomic rearrangement on the similarity estimation, such as intra-chromosome/genome translocations, horizontal gene transfer, and gene losses. To explore such effects on the accuracy of phylogeny reconstruction, we combine phylogenetic signals of OGs with collinear genomic regions, here called locally collinear blocks (LCBs). By putting these together, we refine our previous metric of pairwise similarity between two closely related bacterial genomes. As a case study, we used this new method to reconstruct the phylogenies of 88 Enterobacteriale genomes of the class Gammaproteobacteria. Our results demonstrated that the topological accuracy of the inferred phylogeny was improved when both OGs and LCBs were simultaneously considered, suggesting that combining these two phylogenetic markers may reduce, to some extent, the influence of gene loss on phylogeny inference. Such phylogenomic studies, we believe, will help us to explore a more effective approach to increasing the robustness of phylogeny reconstruction of closely related bacterial organisms. PMID:26715828

  17. Meta Analysis of Gene Expression Data within and Across Species

    PubMed Central

    Fierro, Ana C; Vandenbussche, Filip; Engelen, Kristof; Van de Peer, Yves; Marchal, Kathleen

    2008-01-01

    Since the second half of the 1990s, a large number of genome-wide analyses have been described that study gene expression at the transcript level. To this end, two major strategies have been adopted, a first one relying on hybridization techniques such as microarrays, and a second one based on sequencing techniques such as serial analysis of gene expression (SAGE), cDNA-AFLP, and analysis based on expressed sequence tags (ESTs). Despite both types of profiling experiments becoming routine techniques in many research groups, their application remains costly and laborious. As a result, the number of conditions profiled in individual studies is still relatively small and usually varies from only two to few hundreds of samples for the largest experiments. More and more, scientific journals require the deposit of these high throughput experiments in public databases upon publication. Mining the information present in these databases offers molecular biologists the possibility to view their own small-scale analysis in the light of what is already available. However, so far, the richness of the public information remains largely unexploited. Several obstacles such as the correct association between ESTs and microarray probes with the corresponding gene transcript, the incompleteness and inconsistency in the annotation of experimental conditions, and the lack of standardized experimental protocols to generate gene expression data, all impede the successful mining of these data. Here, we review the potential and difficulties of combining publicly available expression data from respectively EST analyses and microarray experiments. With examples from literature, we show how meta-analysis of expression profiling experiments can be used to study expression behavior in a single organism or between organisms, across a wide range of experimental conditions. We also provide an overview of the methods and tools that can aid molecular biologists in exploiting these public data. PMID

  18. Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in TNF Responders

    PubMed Central

    Oswald, Michaela; Curran, Mark; Lamberth, Sarah; Townsend, Robert; Hamilton, Jennifer D.; Chernoff, David N.; Carulli, John; Townsend, Michael; Weinblatt, Michael; Kern, Marlena; Pond, Cassandra; Lee, Annette; Gregersen, Peter K.

    2015-01-01

    Objective To establish whether the analysis of whole blood gene expression can be useful in predicting or monitoring response to anti-TNF therapy in RA. Methods Whole blood RNA (PAXgene) was obtained at baseline and 14 weeks on three independent cohorts with a combined total of 250 patients with rheumatoid arthritis beginning anti-TNF therapy. We employed an approach to gene expression analysis that is based on gene expression “modules”. Results Good and Moderate Responders by EULAR criteria exhibited highly significant and consistent changes in multiple gene expression modules using a hyper geometric analysis after 14 weeks of therapy. Strikingly, non responders exhibited very little change in any modules, despite exposure to TNF blockade. These patterns of change were highly consistent across all three cohorts, indicating that immunological changes after TNF treatment are specific to the combination of both drug exposure and responder status. In contrast, modular patterns of gene expression did not exhibit consistent differences between responders and non-responders at baseline in the three cohorts. Conclusions These data provide evidence that using gene expression modules related to inflammatory disease may provide a valuable method for objective monitoring of the response of RA patients who are treated with TNF inhibitors. PMID:25371395

  19. Combining CRISPR/Cas9 and rAAV Templates for Efficient Gene Editing.

    PubMed

    Kaulich, Manuel; Dowdy, Steven F

    2015-12-01

    Altering endogenous genes in cells is an integral tool of modern cell biology. The ease-of-use of the CRISPR/Cas9 system to introduce genomic DNA breaks at specific sites in vivo has led to its rapid and wide adoption. In the absence of a DNA template, the lesion is repaired by nonhomologous end joining resolving as internal deletions. However, in the presence of a homologous DNA template, homology-directed repair occurs with variable efficiencies. Recent work has demonstrated that highly efficient gene targeting can be induced by combining CRISPR/Cas9 targeting of genomic loci with recombinant adeno-associated virus (rAAV) to provide a single-stranded homologous DNA template. Here we review the current state of CRISPR/Cas-based gene editing and provide a practical guide to applying the CRISPR/Cas and rAAV system for highly efficient, time- and cost-effective gene targeting.

  20. Combining CRISPR/Cas9 and rAAV Templates for Efficient Gene Editing

    PubMed Central

    Kaulich, Manuel

    2015-01-01

    Altering endogenous genes in cells is an integral tool of modern cell biology. The ease-of-use of the CRISPR/Cas9 system to introduce genomic DNA breaks at specific sites in vivo has led to its rapid and wide adoption. In the absence of a DNA template, the lesion is repaired by nonhomologous end joining resolving as internal deletions. However, in the presence of a homologous DNA template, homology-directed repair occurs with variable efficiencies. Recent work has demonstrated that highly efficient gene targeting can be induced by combining CRISPR/Cas9 targeting of genomic loci with recombinant adeno-associated virus (rAAV) to provide a single-stranded homologous DNA template. Here we review the current state of CRISPR/Cas-based gene editing and provide a practical guide to applying the CRISPR/Cas and rAAV system for highly efficient, time- and cost-effective gene targeting. PMID:26540648

  1. Photochemically induced gene silencing using small interfering RNA molecules in combination with lipid carriers.

    PubMed

    Bøe, S; Longva, A S; Hovig, E

    2007-01-01

    Novel strategies for efficient delivery of small interfering RNA (siRNA) molecules with a potential for targeting are required for development of RNA interference (RNAi) therapeutics. Here, we present a strategy that is based on delivery of siRNA molecules through the endocytic pathway, in order to develop a method for site-specific gene silencing. To achieve this, we combined the use of cationic lipids and photochemical internalization (PCI). Using the human S100A4 gene as a model system, we obtained potent gene silencing in four tested human cancer cell lines following PCI induction when using the cationic lipid jetSI-ENDO. Gene silencing was shown at both the RNA and protein levels, with no observed PCI toxicity when using the jetSI reagent and an optimized PCI protocol. This novel induction method opens for in vivo site-specific delivery of siRNA molecules toward a sequence of interest.

  2. Development of gene therapy: potential in severe combined immunodeficiency due to adenosine deaminase deficiency.

    PubMed

    Montiel-Equihua, Claudia A; Thrasher, Adrian J; Gaspar, H Bobby

    2009-12-22

    The history of stem cell gene therapy is strongly linked to the development of gene therapy for severe combined immunodeficiencies (SCID) and especially adenosine deaminase (ADA)-deficient SCID. Here we discuss the developments achieved in over two decades of clinical and laboratory research that led to the establishment of a protocol for the autologous transplant of retroviral vector-mediated gene-modified hematopoietic stem cells, which has proved to be both successful and, to date, safe. Patients in trials in three different countries have shown long-term immunological and metabolic correction. Nevertheless, improvements to the safety profile of viral vectors are underway and will undoubtedly reinforce the position of stem cell gene therapy as a treatment option for ADA-SCID.

  3. Development of gene therapy: potential in severe combined immunodeficiency due to adenosine deaminase deficiency

    PubMed Central

    Montiel-Equihua, Claudia A; Thrasher, Adrian J; Gaspar, H Bobby

    2010-01-01

    The history of stem cell gene therapy is strongly linked to the development of gene therapy for severe combined immunodeficiencies (SCID) and especially adenosine deaminase (ADA)-deficient SCID. Here we discuss the developments achieved in over two decades of clinical and laboratory research that led to the establishment of a protocol for the autologous transplant of retroviral vector-mediated gene-modified hematopoietic stem cells, which has proved to be both successful and, to date, safe. Patients in trials in three different countries have shown long-term immunological and metabolic correction. Nevertheless, improvements to the safety profile of viral vectors are underway and will undoubtedly reinforce the position of stem cell gene therapy as a treatment option for ADA-SCID. PMID:24198507

  4. A Systems Genetics Approach Implicates USF1, FADS3, and Other Causal Candidate Genes for Familial Combined Hyperlipidemia

    PubMed Central

    Plaisier, Christopher L.; Horvath, Steve; Huertas-Vazquez, Adriana; Cruz-Bautista, Ivette; Herrera, Miguel F.; Tusie-Luna, Teresa; Aguilar-Salinas, Carlos; Pajukanta, Päivi

    2009-01-01

    We hypothesized that a common SNP in the 3' untranslated region of the upstream transcription factor 1 (USF1), rs3737787, may affect lipid traits by influencing gene expression levels, and we investigated this possibility utilizing the Mexican population, which has a high predisposition to dyslipidemia. We first associated rs3737787 genotypes in Mexican Familial Combined Hyperlipidemia (FCHL) case/control fat biopsies, with global expression patterns. To identify sets of co-expressed genes co-regulated by similar factors such as transcription factors, genetic variants, or environmental effects, we utilized weighted gene co-expression network analysis (WGCNA). Through WGCNA in the Mexican FCHL fat biopsies we identified two significant Triglyceride (TG)-associated co-expression modules. One of these modules was also associated with FCHL, the other FCHL component traits, and rs3737787 genotypes. This USF1-regulated FCHL-associated (URFA) module was enriched for genes involved in lipid metabolic processes. Using systems genetics procedures we identified 18 causal candidate genes in the URFA module. The FCHL causal candidate gene fatty acid desaturase 3 (FADS3) was associated with TGs in a recent Caucasian genome-wide significant association study and we replicated this association in Mexican FCHL families. Based on a USF1-regulated FCHL-associated co-expression module and SNP rs3737787, we identify a set of causal candidate genes for FCHL-related traits. We then provide evidence from two independent datasets supporting FADS3 as a causal gene for FCHL and elevated TGs in Mexicans. PMID:19750004

  5. Identification of the minimal combination of clinical features in probands for efficient mutation detection in the FBN1 gene

    PubMed Central

    Stheneur, Chantal; Collod-Béroud, Gwenaëlle; Faivre, Laurence; Buyck, Jean François; Gouya, Laurent; Le Parc, Jean-Marie; Moura, Bertrand; Muti, Christine; Grandchamp, Bernard; Sultan, Gilles; Claustres, Mireille; Aegerter, Philippe; Chevallier, Bertrand; Jondeau, Guillaume; Boileau, Catherine

    2009-01-01

    Mutations identified in the fibrillin-1 (FBN1) gene have been associated with Marfan syndrome (MFS). Molecular analysis of the gene is classically performed in probands with MFS to offer diagnosis for at-risk relatives and in children highly suspected of MFS. However, FBN1 gene mutations are found in an ill-defined group of diseases termed ‘type I fibrillinopathies', which are associated with an increased risk of aortic dilatation and dissection. Thus, there is growing awareness of the need to identify these non-MFS probands, for which FBN1 gene screening should be performed. To answer this need we compiled the molecular data obtained from the screening of the FBN1 gene in 586 probands, which had been addressed to our laboratory for molecular diagnosis. In this group, the efficacy of FBN1 gene screening was high in classical MFS probands (72.5%,), low (58%) in those referred for incomplete MFS and only slight (14.3%) for patients referred as possible MFS. Using recursive partitioning, we found that the best predictor of the identification of a mutation in the FBN1 gene was the presence of features in at least three organ systems, combining one major, and various minor criteria. We also show that our original recommendation of two systems involved with at least one with major criterion represents the minimal criteria because in probands not meeting these criteria, the yield of mutation identification drastically falls. This recommendation should help clinicians and biologists in identifying probands with a high probability of carrying a FBN1 gene mutation, and thus optimize biological resources. PMID:19293843

  6. Mosquito larvicidal activity of Escherichia coli with combinations of genes from Bacillus thuringiensis subsp. israelensis.

    PubMed Central

    Ben-Dov, E; Boussiba, S; Zaritsky, A

    1995-01-01

    The genes cryIVA and cryIVD, encoding 134- and 72-kDa proteins, respectively, and the gene for a regulatory 20-kDa polypeptide of Bacillus thuringiensis subsp. israelensis (serovar H14) were cloned in all seven possible combinations by the Escherichia coli expression vectors pT7 and pUHE. The four combinations containing cryIVA (cryIVA alone, with cryIVD, with the 20-kDa-protein gene, and with both) displayed high levels of mosquito larvicidal activity in pUHE. The toxicity of the combination of cryIVA and cryIVD, with or without the 20-kDa-protein gene, was higher than has ever been achieved with delta-endotoxin genes in recombinant E. coli. Fifty percent lethal concentrations against third-instar Aedes aegypti larvae for these clones decreased (i.e., toxicity increased) continuously to about 3 x 10(5) cells ml-1 after 4 h of induction. Larvicidal activities, obtained after 30 min of induction, were lower for clones in pT7 and decreased for an additional 3.5 h. Induction of either cryIVD or the 20-kDa-protein gene alone resulted in no larvicidal activity in either pT7 or pUHE20. Cloned together, these genes were slightly toxic in pT7 but not in pUHE20. Five minutes of induction of this combination (cryIVD with the 20-kDa-protein gene) in pT7 yielded a maximal mortality of about 40%, which decreased rapidly and disappeared completely after 50 min. CryIVD is thus apparently degraded in E. coli and partially stabilized by the 20-kDa regulatory protein. Larvicidal activity of the combination of cryIVA and cryIVD was sevenfold higher than that of cryIVA alone, probably because of the cross-stabilization of the polypeptides or the synergism between their activities. PMID:7751296

  7. Analysis of locus-specific changes in methylation patterns using a COBRA (combined bisulfite restriction analysis) assay.

    PubMed

    Boyko, Alex; Kovalchuk, Igor

    2010-01-01

    DNA methylation is a major mechanism for the reversible control of gene expression, chromatin structure, and genome stability. Methylation analysis at a given locus allows one to evaluate levels of chromatin packaging, gene expression, and even homologous recombination. We have shown that the combined bisulfite restriction analysis (COBRA) assay makes it possible to analyze methylation levels at a defined locus. The major steps are: bisulfite conversion of nonmethylate cytosines to uracils, locus-specific PCR amplification of converted DNA, restriction digestion, and analysis of restriction patterns on the gel. Due to the availability of various restriction enzymes that have cytosines in the restriction recognition sequence, the assay allows analysis of various cytosines, including those potentially targeted for symmetrical and nonsymmetrical methylation.

  8. Gene Coexpression Network Analysis as a Source of Functional Annotation for Rice Genes

    PubMed Central

    Childs, Kevin L.; Davidson, Rebecca M.; Buell, C. Robin

    2011-01-01

    With the existence of large publicly available plant gene expression data sets, many groups have undertaken data analyses to construct gene coexpression networks and functionally annotate genes. Often, a large compendium of unrelated or condition-independent expression data is used to construct gene networks. Condition-dependent expression experiments consisting of well-defined conditions/treatments have also been used to create coexpression networks to help examine particular biological processes. Gene networks derived from either condition-dependent or condition-independent data can be difficult to interpret if a large number of genes and connections are present. However, algorithms exist to identify modules of highly connected and biologically relevant genes within coexpression networks. In this study, we have used publicly available rice (Oryza sativa) gene expression data to create gene coexpression networks using both condition-dependent and condition-independent data and have identified gene modules within these networks using the Weighted Gene Coexpression Network Analysis method. We compared the number of genes assigned to modules and the biological interpretability of gene coexpression modules to assess the utility of condition-dependent and condition-independent gene coexpression networks. For the purpose of providing functional annotation to rice genes, we found that gene modules identified by coexpression analysis of condition-dependent gene expression experiments to be more useful than gene modules identified by analysis of a condition-independent data set. We have incorporated our results into the MSU Rice Genome Annotation Project database as additional expression-based annotation for 13,537 genes, 2,980 of which lack a functional annotation description. These results provide two new types of functional annotation for our database. Genes in modules are now associated with groups of genes that constitute a collective functional annotation of those

  9. PhyloPat: phylogenetic pattern analysis of eukaryotic genes

    PubMed Central

    Hulsen, Tim; de Vlieg, Jacob; Groenen, Peter MA

    2006-01-01

    Background Phylogenetic patterns show the presence or absence of certain genes or proteins in a set of species. They can also be used to determine sets of genes or proteins that occur only in certain evolutionary branches. Phylogenetic patterns analysis has routinely been applied to protein databases such as COG and OrthoMCL, but not upon gene databases. Here we present a tool named PhyloPat which allows the complete Ensembl gene database to be queried using phylogenetic patterns. Description PhyloPat is an easy-to-use webserver, which can be used to query the orthologies of all complete genomes within the EnsMart database using phylogenetic patterns. This enables the determination of sets of genes that occur only in certain evolutionary branches or even single species. We found in total 446,825 genes and 3,164,088 orthologous relationships within the EnsMart v40 database. We used a single linkage clustering algorithm to create 147,922 phylogenetic lineages, using every one of the orthologies provided by Ensembl. PhyloPat provides the possibility of querying with either binary phylogenetic patterns (created by checkboxes) or regular expressions. Specific branches of a phylogenetic tree of the 21 included species can be selected to create a branch-specific phylogenetic pattern. Users can also input a list of Ensembl or EMBL IDs to check which phylogenetic lineage any gene belongs to. The output can be saved in HTML, Excel or plain text format for further analysis. A link to the FatiGO web interface has been incorporated in the HTML output, creating easy access to functional information. Finally, lists of omnipresent, polypresent and oligopresent genes have been included. Conclusion PhyloPat is the first tool to combine complete genome information with phylogenetic pattern querying. Since we used the orthologies generated by the accurate pipeline of Ensembl, the obtained phylogenetic lineages are reliable. The completeness and reliability of these phylogenetic

  10. Selection of optimal combinations of target genes for therapeutic multi-gene silencing based on miRNA co-regulation.

    PubMed

    Malek, A; Gyorffy, B; Catapano, C V; Schäfer, R

    2013-05-01

    Therapeutic gene silencing is a promising approach for treatment of cancer. Despite substantial efforts, however, only few such therapeutic methods have been clinically tested. The heterogeneity in gene expression profiles among malignant tissues and the dynamic control of gene expression in individual tumors makes identifying universal and effective targets a challenge. Further development of gene silencing therapy requires new approaches to comprehend and manage gene expression in cancer cells. In this study, we proposed and evaluated experimentally a new approach to design multi-gene silencing therapy. Using a simplified model of gene expression control, we show that genes commonly regulated by the same microRNA represent optimal combinations of targets for small hairpin RNA/small interfering RNA-based gene silencing. The proposed method of target gene selection and co-silencing can be explored as an algorithm for personalized cancer gene therapy.

  11. Integrative mixture of experts to combine clinical factors and gene markers

    PubMed Central

    Lê Cao, Kim-Anh; Meugnier, Emmanuelle; McLachlan, Geoffrey J.

    2010-01-01

    Motivation: Microarrays are being increasingly used in cancer research to better characterize and classify tumors by selecting marker genes. However, as very few of these genes have been validated as predictive biomarkers so far, it is mostly conventional clinical and pathological factors that are being used as prognostic indicators of clinical course. Combining clinical data with gene expression data may add valuable information, but it is a challenging task due to their categorical versus continuous characteristics. We have further developed the mixture of experts (ME) methodology, a promising approach to tackle complex non-linear problems. Several variants are proposed in integrative ME as well as the inclusion of various gene selection methods to select a hybrid signature. Results: We show on three cancer studies that prediction accuracy can be improved when combining both types of variables. Furthermore, the selected genes were found to be of high relevance and can be considered as potential biomarkers for the prognostic selection of cancer therapy. Availability: Integrative ME is implemented in the R package integrativeME (http://cran.r-project.org/). Contact: k.lecao@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20223834

  12. Combination efficacy of doxorubicin and adenoviral methioninase gene therapy with prodrug selenomethionine.

    PubMed

    Gupta, Anshu; Miki, Kenji; Xu, Mingxu; Yamamoto, Norio; Moossa, A R; Hoffman, R M

    2003-01-01

    We have previously demonstrated an enzyme activation prodrug gene therapy strategy using the methionine alpha,gamma-lyase gene (MET) cloned from Pseudomonas putida, in combination with selenomethionine (SeMET) as a prodrug. MET gene transfer via a recombinant adenovirus (Ad-MET) converts the physiologic compound SeMET to highly toxic methylselenol. In this study, we have developed a combination therapy approach using Ad-MET/SeMET gene therapy and doxorubicin (DOX). The combination significantly delayed the growth of H460, an aggressively-growing human lung cancer cell line, in nude mice. H460 cells were injected intra-dermally in nude mice. Tumor-bearing mice were divided into 12 groups [Control (Ctrl), DOX, SeMET, SeMET + DOX, Ad-Ctrl, Ad-Ctrl + SeMET, Ad-Ctrl + DOX, Ad-Ctrl + SeMET + DOX, Ad-MET, Ad-MET + DOX, Ad-MET + SeMET, and Ad-MET + SeMET + DOX]. DOX (2 mg/kg body weight) was given intra-peritoneally twice at 7-day intervals. SeMET (1 microM/mouse) was given by intra-tumor injection everyday, starting the following day after transfection with adenovirus. Tumor growth in the untreated group showed a 10-fold increase in tumor volume after two weeks. In contrast, the increase was only 2.5-fold in the DOX + Ad-MET/SeMET group. The treatment with DOX alone at the low-dose used showed no effect compared to the control group. There was a 5.8-fold increase in tumor volume in mice treated with Ad-MET/SeMET gene therapy alone. The tumor doubling-time was increased to approximately 10 days with the combination therapy of Ad-MET + SeMET + DOX as opposed to 2-3 days in all other treatment groups.

  13. Combination of gene expression patterns in whole blood discriminate between tuberculosis infection states

    PubMed Central

    2014-01-01

    Background Genetic factors are involved in susceptibility or protection to tuberculosis (TB). Apart from gene polymorphisms and mutations, changes in levels of gene expression, induced by non-genetic factors, may also determine whether individuals progress to active TB. Methods We analysed the expression level of 45 genes in a total of 47 individuals (23 healthy household contacts and 24 new smear-positive pulmonary TB patients) in Addis Ababa using a dual colour multiplex ligation-dependent probe amplification (dcRT-MLPA) technique to assess gene expression profiles that may be used to distinguish TB cases and their contacts and also latently infected (LTBI) and uninfected household contacts. Results The gene expression level of BLR1, Bcl2, IL4d2, IL7R, FCGR1A, MARCO, MMP9, CCL19, and LTF had significant discriminatory power between sputum smear-positive TB cases and household contacts, with AUCs of 0.84, 0.81, 0.79, 0.79, 0.78, 0.76, 0.75, 0.75 and 0.68 respectively. The combination of Bcl2, BLR1, FCGR1A, IL4d2 and MARCO identified 91.66% of active TB cases and 95.65% of household contacts without active TB. The expression of CCL19, TGFB1, and Foxp3 showed significant difference between LTBI and uninfected contacts, with AUCs of 0.85, 0.82, and 0.75, respectively, whereas the combination of BPI, CCL19, FoxP3, FPR1 and TGFB1 identified 90.9% of QFT- and 91.6% of QFT+ household contacts. Conclusions Expression of single and especially combinations of host genes can accurately differentiate between active TB cases and healthy individuals as well as between LTBI and uninfected contacts. PMID:24885723

  14. Marker-assisted combination of major genes for pathogen resistance in potato.

    PubMed

    Gebhardt, C; Bellin, D; Henselewski, H; Lehmann, W; Schwarzfischer, J; Valkonen, J P T

    2006-05-01

    Closely linked PCR-based markers facilitate the tracing and combining of resistance factors that have been introgressed previously into cultivated potato from different sources. Crosses were performed to combine the Ry ( adg ) gene for extreme resistance to Potato virus Y (PVY) with the Gro1 gene for resistance to the root cyst nematode Globodera rostochiensis and the Rx1 gene for extreme resistance to Potato virus X (PVX), or with resistance to potato wart (Synchytrium endobioticum). Marker-assisted selection (MAS) using four PCR-based diagnostic assays was applied to 110 F1 hybrids resulting from four 2x by 4x cross-combinations. Thirty tetraploid plants having the appropriate marker combinations were selected and tested for presence of the corresponding resistance traits. All plants tested showed the expected resistant phenotype. Unexpectedly, the plants segregated for additional resistance to pathotypes 1, 2 and 6 of S. endobioticum, which was subsequently shown to be inherited from the PVY resistant parents of the crosses. The selected plants can be used as sources of multiple resistance traits in pedigree breeding and are available from a potato germplasm bank.

  15. 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.

  16. Combining Multi-modal Features for Social Media Analysis

    NASA Astrophysics Data System (ADS)

    Nikolopoulos, Spiros; Giannakidou, Eirini; Kompatsiaris, Ioannis; Patras, Ioannis; Vakali, Athena

    In this chapter we discuss methods for efficiently modeling the diverse information carried by social media. The problem is viewed as a multi-modal analysis process where specialized techniques are used to overcome the obstacles arising from the heterogeneity of data. Focusing at the optimal combination of low-level features (i.e., early fusion), we present a bio-inspired algorithm for feature selection that weights the features based on their appropriateness to represent a resource. Under the same objective of optimal feature combination we also examine the use of pLSA-based aspect models, as the means to define a latent semantic space where heterogeneous types of information can be effectively combined. Tagged images taken from social sites have been used in the characteristic scenarios of image clustering and retrieval, to demonstrate the benefits of multi-modal analysis in social media.

  17. Data analysis for the CHARA Array CLIMB beam combiner

    NASA Astrophysics Data System (ADS)

    ten Brummelaar, Theo A.; Sturmann, Judit; McAlister, Harold A.; Sturmann, Laszlo; Turner, Nils H.; Farrington, Chris D.; Schaefer, Gail; Goldfinger, P. J.; Kloppenborg, Brian

    2012-07-01

    The CHARA Array is a six telescope optical/IR interferometer run by the Center for High Angular Resolution Astronomy of Georgia State University and is located at Mount Wilson Observatory just to the north of Los Angeles California. The CHARA Array has the largest operational baselines in the world and has been in regular use for scientific observations since 2004. Our most sensitive beam combiner capable of measuring closure phases is the CLassic Interferometry with Multiple Baselines beam combiner known as CLIMB. In this paper we discuss the design and layout of CLIMB with a particular focus on the data analysis methodology. This analysis is presented in a very general form and will have applications in many other beam combiners. We also present examples of on sky data showing the precision and stability of both amplitude and closure phase measurements.

  18. ROC analysis in biomarker combination with covariate adjustment.

    PubMed

    Liu, Danping; Zhou, Xiao-Hua

    2013-07-01

    Receiver operating characteristic (ROC) analysis is often used to find the optimal combination of biomarkers. When the subject level covariates affect the magnitude and/or accuracy of the biomarkers, the combination rule should take into account of the covariate adjustment. The authors propose two new biomarker combination methods that make use of the covariate information. The first method is to maximize the area under the covariate-adjusted ROC curve (AAUC). To overcome the limitations of the AAUC measure, the authors further proposed the area under covariate-standardized ROC curve (SAUC), which is an extension of the covariate-specific ROC curve. With a series of simulation studies, the proposed optimal AAUC and SAUC methods are compared with the optimal AUC method that ignores the covariates. The biomarker combination methods are illustrated by an example from Alzheimer's disease research. The simulation results indicate that the optimal AAUC combination performs well in the current study population. The optimal SAUC method is flexible to choose any reference populations, and allows the results to be generalized to different populations. The proposed optimal AAUC and SAUC approaches successfully address the covariate adjustment problem in estimating the optimal marker combination. The optimal SAUC method is preferred for practical use, because the biomarker combination rule can be easily evaluated for different population of interest. Published by Elsevier Inc.

  19. Cyber security analysis testbed : combining real, emulation, and simulation.

    SciTech Connect

    Villamarin, Charles H.; Eldridge, John M.; Van Leeuwen, Brian P.; Urias, Vincent E.

    2010-07-01

    Cyber security analysis tools are necessary to evaluate the security, reliability, and resilience of networked information systems against cyber attack. It is common practice in modern cyber security analysis to separately utilize real systems of computers, routers, switches, firewalls, computer emulations (e.g., virtual machines) and simulation models to analyze the interplay between cyber threats and safeguards. In contrast, Sandia National Laboratories has developed novel methods to combine these evaluation platforms into a hybrid testbed that combines real, emulated, and simulated components. The combination of real, emulated, and simulated components enables the analysis of security features and components of a networked information system. When performing cyber security analysis on a system of interest, it is critical to realistically represent the subject security components in high fidelity. In some experiments, the security component may be the actual hardware and software with all the surrounding components represented in simulation or with surrogate devices. Sandia National Laboratories has developed a cyber testbed that combines modeling and simulation capabilities with virtual machines and real devices to represent, in varying fidelity, secure networked information system architectures and devices. Using this capability, secure networked information system architectures can be represented in our testbed on a single, unified computing platform. This provides an 'experiment-in-a-box' capability. The result is rapidly-produced, large-scale, relatively low-cost, multi-fidelity representations of networked information systems. These representations enable analysts to quickly investigate cyber threats and test protection approaches and configurations.

  20. Optimizing matching and analysis combinations for estimating causal effects.

    PubMed

    Colson, K Ellicott; Rudolph, Kara E; Zimmerman, Scott C; Goin, Dana E; Stuart, Elizabeth A; Laan, Mark van der; Ahern, Jennifer

    2016-03-16

    Matching methods are common in studies across many disciplines. However, there is limited evidence on how to optimally combine matching with subsequent analysis approaches to minimize bias and maximize efficiency for the quantity of interest. We conducted simulations to compare the performance of a wide variety of matching methods and analysis approaches in terms of bias, variance, and mean squared error (MSE). We then compared these approaches in an applied example of an employment training program. The results indicate that combining full matching with double robust analysis performed best in both the simulations and the applied example, particularly when combined with machine learning estimation methods. To reduce bias, current guidelines advise researchers to select the technique with the best post-matching covariate balance, but this work finds that such an approach does not always minimize mean squared error (MSE). These findings have important implications for future research utilizing matching. To minimize MSE, investigators should consider additional diagnostics, and use of simulations tailored to the study of interest to identify the optimal matching and analysis combination.

  1. Optimizing matching and analysis combinations for estimating causal effects

    PubMed Central

    Colson, K. Ellicott; Rudolph, Kara E.; Zimmerman, Scott C.; Goin, Dana E.; Stuart, Elizabeth A.; Laan, Mark van der; Ahern, Jennifer

    2016-01-01

    Matching methods are common in studies across many disciplines. However, there is limited evidence on how to optimally combine matching with subsequent analysis approaches to minimize bias and maximize efficiency for the quantity of interest. We conducted simulations to compare the performance of a wide variety of matching methods and analysis approaches in terms of bias, variance, and mean squared error (MSE). We then compared these approaches in an applied example of an employment training program. The results indicate that combining full matching with double robust analysis performed best in both the simulations and the applied example, particularly when combined with machine learning estimation methods. To reduce bias, current guidelines advise researchers to select the technique with the best post-matching covariate balance, but this work finds that such an approach does not always minimize mean squared error (MSE). These findings have important implications for future research utilizing matching. To minimize MSE, investigators should consider additional diagnostics, and use of simulations tailored to the study of interest to identify the optimal matching and analysis combination. PMID:26980444

  2. A combined analysis of genome-wide expression profiling of bipolar disorder in human prefrontal cortex.

    PubMed

    Wang, Jinglu; Qu, Susu; Wang, Weixiao; Guo, Liyuan; Zhang, Kunlin; Chang, Suhua; Wang, Jing

    2016-11-01

    Numbers of gene expression profiling studies of bipolar disorder have been published. Besides different array chips and tissues, variety of the data processes in different cohorts aggravated the inconsistency of results of these genome-wide gene expression profiling studies. By searching the gene expression databases, we obtained six data sets for prefrontal cortex (PFC) of bipolar disorder with raw data and combinable platforms. We used standardized pre-processing and quality control procedures to analyze each data set separately and then combined them into a large gene expression matrix with 101 bipolar disorder subjects and 106 controls. A standard linear mixed-effects model was used to calculate the differentially expressed genes (DEGs). Multiple levels of sensitivity analyses and cross validation with genetic data were conducted. Functional and network analyses were carried out on basis of the DEGs. In the result, we identified 198 unique differentially expressed genes in the PFC of bipolar disorder and control. Among them, 115 DEGs were robust to at least three leave-one-out tests or different pre-processing methods; 51 DEGs were validated with genetic association signals. Pathway enrichment analysis showed these DEGs were related with regulation of neurological system, cell death and apoptosis, and several basic binding processes. Protein-protein interaction network further identified one key hub gene. We have contributed the most comprehensive integrated analysis of bipolar disorder expression profiling studies in PFC to date. The DEGs, especially those with multiple validations, may denote a common signature of bipolar disorder and contribute to the pathogenesis of disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Effect of the absolute statistic on gene-sampling gene-set analysis methods.

    PubMed

    Nam, Dougu

    2015-03-02

    Gene-set enrichment analysis and its modified versions have commonly been used for identifying altered functions or pathways in disease from microarray data. In particular, the simple gene-sampling gene-set analysis methods have been heavily used for datasets with only a few sample replicates. The biggest problem with this approach is the highly inflated false-positive rate. In this paper, the effect of absolute gene statistic on gene-sampling gene-set analysis methods is systematically investigated. Thus far, the absolute gene statistic has merely been regarded as a supplementary method for capturing the bidirectional changes in each gene set. Here, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was investigated by power, false-positive rate, and receiver operating curve for a number of simulated and real datasets. The performances of gene-set analysis methods in one-tailed (genome-wide association study) and two-tailed (gene expression data) tests were also compared and discussed.

  4. META-GSA: Combining Findings from Gene-Set Analyses across Several Genome-Wide Association Studies

    PubMed Central

    Rosenberger, Albert; Friedrichs, Stefanie; Amos, Christopher I.; Brennan, Paul; Fehringer, Gordon; Heinrich, Joachim; Hung, Rayjean J.; Muley, Thomas; Müller-Nurasyid, Martina; Risch, Angela; Bickeböller, Heike

    2015-01-01

    Introduction Gene-set analysis (GSA) methods are used as complementary approaches to genome-wide association studies (GWASs). The single marker association estimates of a predefined set of genes are either contrasted with those of all remaining genes or with a null non-associated background. To pool the p-values from several GSAs, it is important to take into account the concordance of the observed patterns resulting from single marker association point estimates across any given gene set. Here we propose an enhanced version of Fisher’s inverse χ2-method META-GSA, however weighting each study to account for imperfect correlation between association patterns. Simulation and Power We investigated the performance of META-GSA by simulating GWASs with 500 cases and 500 controls at 100 diallelic markers in 20 different scenarios, simulating different relative risks between 1 and 1.5 in gene sets of 10 genes. Wilcoxon’s rank sum test was applied as GSA for each study. We found that META-GSA has greater power to discover truly associated gene sets than simple pooling of the p-values, by e.g. 59% versus 37%, when the true relative risk for 5 of 10 genes was assume to be 1.5. Under the null hypothesis of no difference in the true association pattern between the gene set of interest and the set of remaining genes, the results of both approaches are almost uncorrelated. We recommend not relying on p-values alone when combining the results of independent GSAs. Application We applied META-GSA to pool the results of four case-control GWASs of lung cancer risk (Central European Study and Toronto/Lunenfeld-Tanenbaum Research Institute Study; German Lung Cancer Study and MD Anderson Cancer Center Study), which had already been analyzed separately with four different GSA methods (EASE; SLAT, mSUMSTAT and GenGen). This application revealed the pathway GO0015291 “transmembrane transporter activity” as significantly enriched with associated genes (GSA-method: EASE, p = 0

  5. META-GSA: Combining Findings from Gene-Set Analyses across Several Genome-Wide Association Studies.

    PubMed

    Rosenberger, Albert; Friedrichs, Stefanie; Amos, Christopher I; Brennan, Paul; Fehringer, Gordon; Heinrich, Joachim; Hung, Rayjean J; Muley, Thomas; Müller-Nurasyid, Martina; Risch, Angela; Bickeböller, Heike

    2015-01-01

    Gene-set analysis (GSA) methods are used as complementary approaches to genome-wide association studies (GWASs). The single marker association estimates of a predefined set of genes are either contrasted with those of all remaining genes or with a null non-associated background. To pool the p-values from several GSAs, it is important to take into account the concordance of the observed patterns resulting from single marker association point estimates across any given gene set. Here we propose an enhanced version of Fisher's inverse χ2-method META-GSA, however weighting each study to account for imperfect correlation between association patterns. We investigated the performance of META-GSA by simulating GWASs with 500 cases and 500 controls at 100 diallelic markers in 20 different scenarios, simulating different relative risks between 1 and 1.5 in gene sets of 10 genes. Wilcoxon's rank sum test was applied as GSA for each study. We found that META-GSA has greater power to discover truly associated gene sets than simple pooling of the p-values, by e.g. 59% versus 37%, when the true relative risk for 5 of 10 genes was assume to be 1.5. Under the null hypothesis of no difference in the true association pattern between the gene set of interest and the set of remaining genes, the results of both approaches are almost uncorrelated. We recommend not relying on p-values alone when combining the results of independent GSAs. We applied META-GSA to pool the results of four case-control GWASs of lung cancer risk (Central European Study and Toronto/Lunenfeld-Tanenbaum Research Institute Study; German Lung Cancer Study and MD Anderson Cancer Center Study), which had already been analyzed separately with four different GSA methods (EASE; SLAT, mSUMSTAT and GenGen). This application revealed the pathway GO0015291 "transmembrane transporter activity" as significantly enriched with associated genes (GSA-method: EASE, p = 0.0315 corrected for multiple testing). Similar results were

  6. Genome-wide analysis of homeobox genes from Mesobuthus martensii reveals Hox gene duplication in scorpions.

    PubMed

    Di, Zhiyong; Yu, Yao; Wu, Yingliang; Hao, Pei; He, Yawen; Zhao, Huabin; Li, Yixue; Zhao, Guoping; Li, Xuan; Li, Wenxin; Cao, Zhijian

    2015-06-01

    Homeobox genes belong to a large gene group, which encodes the famous DNA-binding homeodomain that plays a key role in development and cellular differentiation during embryogenesis in animals. Here, one hundred forty-nine homeobox genes were identified from the Asian scorpion, Mesobuthus martensii (Chelicerata: Arachnida: Scorpiones: Buthidae) based on our newly assembled genome sequence with approximately 248 × coverage. The identified homeobox genes were categorized into eight classes including 82 families: 67 ANTP class genes, 33 PRD genes, 11 LIM genes, five POU genes, six SINE genes, 14 TALE genes, five CUT genes, two ZF genes and six unclassified genes. Transcriptome data confirmed that more than half of the genes were expressed in adults. The homeobox gene diversity of the eight classes is similar to the previously analyzed Mandibulata arthropods. Interestingly, it is hypothesized that the scorpion M. martensii may have two Hox clusters. The first complete genome-wide analysis of homeobox genes in Chelicerata not only reveals the repertoire of scorpion, arachnid and chelicerate homeobox genes, but also shows some insights into the evolution of arthropod homeobox genes.

  7. Lentiviral hematopoietic stem cell gene therapy for X-linked severe combined immunodeficiency.

    PubMed

    De Ravin, Suk See; Wu, Xiaolin; Moir, Susan; Anaya-O'Brien, Sandra; Kwatemaa, Nana; Littel, Patricia; Theobald, Narda; Choi, Uimook; Su, Ling; Marquesen, Martha; Hilligoss, Dianne; Lee, Janet; Buckner, Clarissa M; Zarember, Kol A; O'Connor, Geraldine; McVicar, Daniel; Kuhns, Douglas; Throm, Robert E; Zhou, Sheng; Notarangelo, Luigi D; Hanson, I Celine; Cowan, Mort J; Kang, Elizabeth; Hadigan, Coleen; Meagher, Michael; Gray, John T; Sorrentino, Brian P; Malech, Harry L

    2016-04-20

    X-linked severe combined immunodeficiency (SCID-X1) is a profound deficiency of T, B, and natural killer (NK) cell immunity caused by mutations inIL2RGencoding the common chain (γc) of several interleukin receptors. Gamma-retroviral (γRV) gene therapy of SCID-X1 infants without conditioning restores T cell immunity without B or NK cell correction, but similar treatment fails in older SCID-X1 children. We used a lentiviral gene therapy approach to treat five SCID-X1 patients with persistent immune dysfunction despite haploidentical hematopoietic stem cell (HSC) transplant in infancy. Follow-up data from two older patients demonstrate that lentiviral vector γc transduced autologous HSC gene therapy after nonmyeloablative busulfan conditioning achieves selective expansion of gene-marked T, NK, and B cells, which is associated with sustained restoration of humoral responses to immunization and clinical improvement at 2 to 3 years after treatment. Similar gene marking levels have been achieved in three younger patients, albeit with only 6 to 9 months of follow-up. Lentiviral gene therapy with reduced-intensity conditioning appears safe and can restore humoral immune function to posthaploidentical transplant older patients with SCID-X1.

  8. Transcriptomic analysis in the developing zebrafish embryo after compound exposure: Individual gene expression and pathway regulation

    SciTech Connect

    Hermsen, Sanne A.B.; Pronk, Tessa E.; Brandhof, Evert-Jan van den; Ven, Leo T.M. van der; Piersma, Aldert H.

    2013-10-01

    The zebrafish embryotoxicity test is a promising alternative assay for developmental toxicity. Classically, morphological assessment of the embryos is applied to evaluate the effects of compound exposure. However, by applying differential gene expression analysis the sensitivity and predictability of the test may be increased. For defining gene expression signatures of developmental toxicity, we explored the possibility of using gene expression signatures of compound exposures based on commonly expressed individual genes as well as based on regulated gene pathways. Four developmental toxic compounds were tested in concentration-response design, caffeine, carbamazepine, retinoic acid and valproic acid, and two non-embryotoxic compounds, D-mannitol and saccharin, were included. With transcriptomic analyses we were able to identify commonly expressed genes, which were mostly development related, after exposure to the embryotoxicants. We also identified gene pathways regulated by the embryotoxicants, suggestive of their modes of action. Furthermore, whereas pathways may be regulated by all compounds, individual gene expression within these pathways can differ for each compound. Overall, the present study suggests that the use of individual gene expression signatures as well as pathway regulation may be useful starting points for defining gene biomarkers for predicting embryotoxicity. - Highlights: • The zebrafish embryotoxicity test in combination with transcriptomics was used. • We explored two approaches of defining gene biomarkers for developmental toxicity. • Four compounds in concentration-response design were tested. • We identified commonly expressed individual genes as well as regulated gene pathways. • Both approaches seem suitable starting points for defining gene biomarkers.

  9. Haplotype combination of the bovine CFL2 gene sequence variants and association with growth traits in Qinchuan cattle.

    PubMed

    Sun, Yujia; Lan, Xianyong; Lei, Chuzhao; Zhang, Chunlei; Chen, Hong

    2015-06-01

    The aim of this study was to examine the association of cofilin2 (CFL2) gene polymorphisms with growth traits in Chinese Qinchuan cattle. Three single nucleotide polymorphisms (SNPs) were identified in the bovine CFL2 gene using DNA sequencing and (forced) PCR-RFLP methods. These polymorphisms included a missense mutation (NC_007319.5: g. C 2213 G) in exon 4, one synonymous mutation (NC_007319.5: g. T 1694 A) in exon 4, and a mutation (NC_007319.5: g. G 1500 A) in intron 2, respectively. In addition, we evaluated the haplotype frequency and linkage disequilibrium coefficient of three sequence variants in 488 individuals in QC cattle. All the three SNPs in QC cattle belonged to an intermediate level of genetic diversity (0.25analysis of three SNPs showed that 8 different haplotypes were identified in all, but only 5 haplotypes were listed except for those with a frequency of <0.03. Hap4 (-GTC-) had the highest haplotype frequencies (34.70%). However in the three SNPs there were no significant associations between the 13 combined genotypes of the CFL2 gene and growth traits. LD analysis showed that the SNP T 1694 A and C 2213 G loci had a strong linkage (r(2)>0.33). Association analysis indicated that SNP G 1500 A, T 1694 A and C 2213 G were significantly associated with growth traits in the QC population. The results of our study suggest that the CFL2 gene may be a strong candidate gene that affects growth traits in the QC cattle breeding program.

  10. [Current gene study in etiological analysis of congenital craniofacial abnormalities].

    PubMed

    Feng, Yi-miao; Fang, Bing

    2007-04-01

    The cause of congenital craniofacial abnormalities are very complicated. Understanding of the gene mechanisms of abnormalities taking place are very important for prevention and therapy.DNA sequence analysis provides the fundaments of gene study of the congenital craniofacial abnormalities. Human genome project (HGP) paved the confirmation of candidate gene of the congenital craniofacial abnormalities.Transgenic animal models and gene knockout techniques are effective methods in study of gene function. This paper reviews current gene study in etiopathogenisis analysis of the congenital craniofacial abnormalities.

  11. Integrated analysis of microarray data and gene function information.

    PubMed

    Cui, Yan; Zhou, Mi; Wong, Wing Hung

    2004-01-01

    Microarray data should be interpreted in the context of existing biological knowledge. Here we present integrated analysis of microarray data and gene function classification data using homogeneity analysis. Homogeneity analysis is a graphical multivariate statistical method for analyzing categorical data. It converts categorical data into graphical display. By simultaneously quantifying the microarray-derived gene groups and gene function categories, it captures the complex relations between biological information derived from microarray data and the existing knowledge about the gene function. Thus, homogeneity analysis provides a mathematical framework for integrating the analysis of microarray data and the existing biological knowledge.

  12. Combining classifiers generated by multi-gene genetic programming for protein fold recognition using genetic algorithm.

    PubMed

    Bardsiri, Mahshid Khatibi; Eftekhari, Mahdi; Mousavi, Reza

    2015-01-01

    In this study the problem of protein fold recognition, that is a classification task, is solved via a hybrid of evolutionary algorithms namely multi-gene Genetic Programming (GP) and Genetic Algorithm (GA). Our proposed method consists of two main stages and is performed on three datasets taken from the literature. Each dataset contains different feature groups and classes. In the first step, multi-gene GP is used for producing binary classifiers based on various feature groups for each class. Then, different classifiers obtained for each class are combined via weighted voting so that the weights are determined through GA. At the end of the first step, there is a separate binary classifier for each class. In the second stage, the obtained binary classifiers are combined via GA weighting in order to generate the overall classifier. The final obtained classifier is superior to the previous works found in the literature in terms of classification accuracy.

  13. An evidence-based combining classifier for brain signal analysis.

    PubMed

    Kheradpisheh, Saeed Reza; Nowzari-Dalini, Abbas; Ebrahimpour, Reza; Ganjtabesh, Mohammad

    2014-01-01

    Nowadays, brain signals are employed in various scientific and practical fields such as Medical Science, Cognitive Science, Neuroscience, and Brain Computer Interfaces. Hence, the need for robust signal analysis methods with adequate accuracy and generalizability is inevitable. The brain signal analysis is faced with complex challenges including small sample size, high dimensionality and noisy signals. Moreover, because of the non-stationarity of brain signals and the impacts of mental states on brain function, the brain signals are associated with an inherent uncertainty. In this paper, an evidence-based combining classifiers method is proposed for brain signal analysis. This method exploits the power of combining classifiers for solving complex problems and the ability of evidence theory to model as well as to reduce the existing uncertainty. The proposed method models the uncertainty in the labels of training samples in each feature space by assigning soft and crisp labels to them. Then, some classifiers are employed to approximate the belief function corresponding to each feature space. By combining the evidence raised from each classifier through the evidence theory, more confident decisions about testing samples can be made. The obtained results by the proposed method compared to some other evidence-based and fixed rule combining methods on artificial and real datasets exhibit the ability of the proposed method in dealing with complex and uncertain classification problems.

  14. An Evidence-Based Combining Classifier for Brain Signal Analysis

    PubMed Central

    Kheradpisheh, Saeed Reza; Nowzari-Dalini, Abbas; Ebrahimpour, Reza; Ganjtabesh, Mohammad

    2014-01-01

    Nowadays, brain signals are employed in various scientific and practical fields such as Medical Science, Cognitive Science, Neuroscience, and Brain Computer Interfaces. Hence, the need for robust signal analysis methods with adequate accuracy and generalizability is inevitable. The brain signal analysis is faced with complex challenges including small sample size, high dimensionality and noisy signals. Moreover, because of the non-stationarity of brain signals and the impacts of mental states on brain function, the brain signals are associated with an inherent uncertainty. In this paper, an evidence-based combining classifiers method is proposed for brain signal analysis. This method exploits the power of combining classifiers for solving complex problems and the ability of evidence theory to model as well as to reduce the existing uncertainty. The proposed method models the uncertainty in the labels of training samples in each feature space by assigning soft and crisp labels to them. Then, some classifiers are employed to approximate the belief function corresponding to each feature space. By combining the evidence raised from each classifier through the evidence theory, more confident decisions about testing samples can be made. The obtained results by the proposed method compared to some other evidence-based and fixed rule combining methods on artificial and real datasets exhibit the ability of the proposed method in dealing with complex and uncertain classification problems. PMID:24392125

  15. Polymorphism Interaction Analysis (PIA): a method for investigating complex gene-gene interactions

    PubMed Central

    Mechanic, Leah E; Luke, Brian T; Goodman, Julie E; Chanock, Stephen J; Harris, Curtis C

    2008-01-01

    Background The risk of common diseases is likely determined by the complex interplay between environmental and genetic factors, including single nucleotide polymorphisms (SNPs). Traditional methods of data analysis are poorly suited for detecting complex interactions due to sparseness of data in high dimensions, which often occurs when data are available for a large number of SNPs for a relatively small number of samples. Validation of associations observed using multiple methods should be implemented to minimize likelihood of false-positive associations. Moreover, high-throughput genotyping methods allow investigators to genotype thousands of SNPs at one time. Investigating associations for each individual SNP or interactions between SNPs using traditional approaches is inefficient and prone to false positives. Results We developed the Polymorphism Interaction Analysis tool (PIA version 2.0) to include different approaches for ranking and scoring SNP combinations, to account for imbalances between case and control ratios, stratify on particular factors, and examine associations of user-defined pathways (based on SNP or gene) with case status. PIA v. 2.0 detected 2-SNP interactions as the highest ranking model 77% of the time, using simulated data sets of genetic models of interaction (minor allele frequency = 0.2; heritability = 0.01; N = 1600) generated previously [Velez DR, White BC, Motsinger AA, Bush WS, Ritchie MD, Williams SM, Moore JH: A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction. Genet Epidemiol 2007, 31:306–315.]. Interacting SNPs were detected in both balanced (20 SNPs) and imbalanced data (case:control 1:2 and 1:4, 10 SNPs) in the context of non-interacting SNPs. Conclusion PIA v. 2.0 is a useful tool for exploring gene*gene or gene*environment interactions and identifying a small number of putative associations which may be investigated further using other statistical methods

  16. Isolated and combined dystonia syndromes - an update on new genes and their phenotypes.

    PubMed

    Balint, B; Bhatia, K P

    2015-04-01

    Recent consensus on the definition, phenomenology and classification of dystonia centres around phenomenology and guides our diagnostic approach for the heterogeneous group of dystonias. Current terminology classifies conditions where dystonia is the sole motor feature (apart from tremor) as 'isolated dystonia', while 'combined dystonia' refers to dystonias with other accompanying movement disorders. This review highlights recent advances in the genetics of some isolated and combined dystonic syndromes. Some genes, such as ANO3, GNAL and CIZ1, have been discovered for isolated dystonia, but they are probably not a common cause of classic cervical dystonia. Conversely, the phenotype associated with TUBB4A mutations expanded from that of isolated dystonia to a syndrome of hypomyelination with atrophy of the basal ganglia and cerebellum (H-ABC syndrome). Similarly, ATP1A3 mutations cause a wide phenotypic spectrum ranging from rapid-onset dystonia-parkinsonism to alternating hemiplegia of childhood. Other entities entailing dystonia-parkinsonism include dopamine transporter deficiency syndrome (SLC63 mutations); dopa-responsive dystonias; young-onset parkinsonism (PARKIN, PINK1 and DJ-1 mutations); PRKRA mutations; and X-linked TAF1 mutations, which rarely can also manifest in women. Clinical and genetic heterogeneity also characterizes myoclonus-dystonia, which includes not only the classical phenotype associated with epsilon-sarcoglycan mutations but rarely also presentation of ANO3 gene mutations, TITF1 gene mutations typically underlying benign hereditary chorea, and some dopamine synthesis pathway conditions due to GCH1 and TH mutations. Thus, new genes are being recognized for isolated dystonia, and the phenotype of known genes is broadening and now involves different combined dystonia syndromes.

  17. Selecting supplier combination based on fuzzy multicriteria analysis

    NASA Astrophysics Data System (ADS)

    Han, Zhi-Qiu; Luo, Xin-Xing; Chen, Xiao-Hong; Yang, Wu-E.

    2015-07-01

    Existing multicriteria analysis (MCA) methods are probably ineffective in selecting a supplier combination. Thus, an MCA-based fuzzy 0-1 programming method is introduced. The programming relates to a simple MCA matrix that is used to select a single supplier. By solving the programming, the most feasible combination of suppliers is selected. Importantly, this result differs from selecting suppliers one by one according to a single-selection order, which is used to rank sole suppliers in existing MCA methods. An example highlights such difference and illustrates the proposed method.

  18. Analysis of a combined refrigerator-generator space power system

    NASA Technical Reports Server (NTRS)

    Klann, J. L.

    1973-01-01

    Description of a single-shaft and a two-shaft rotating machinery arrangements using neon for application in a combined refrigerator-generator power system for space missions. The arrangements consist of combined assemblies of a power turbine, alternator, compressor, and cry-turbine with a single-stage radial-flow design. A computer program was prepared to study the thermodynamics of the dual system in the evaluation of its cryocooling/electric capacity and appropriate weight. A preliminary analysis showed that a two-shaft arrangement of the power- and refrigeration-loop rotating machinery provided better output capacities than a single-shaft arrangement, without prohibitive operating compromises.

  19. Frequency of the severe combined immunodeficiency disease gene among horses in Morocco.

    PubMed

    Piro, M; Benjouad, A; Tligui, N S; El Allali, K; El Kohen, M; Nabich, A; Ouragh, L

    2008-09-01

    Severe combined immunodeficiency disease (SCID) of horses is an autosomal, recessive hereditary disease occurring among Arabian or crossbred Arabian horses. The genetic defect responsible was previously identified as a 5-base pair deletion in the gene encoding the catalytic subunit of the DNA dependant protein kinase (DNA-PKcs). This study was carried out to determine the frequency of SCID and identify horses carrying the gene for SCID among Arabian and Arabian crossbred stallions and mares in Morocco using a DNA-based test. Twenty-one horses were SCID carriers: 14 (7%) Arabians, 6 (4%) Arab-Barbs and one (33%) Anglo-Arab. After analysing their genealogy, 3 imported stallions were identified that disseminated the mutant gene of DNA-PKcs in Morocco.

  20. Modeling Human Severe Combined Immunodeficiency and Correction by CRISPR/Cas9-Enhanced Gene Targeting.

    PubMed

    Chang, Chia-Wei; Lai, Yi-Shin; Westin, Erik; Khodadadi-Jamayran, Alireza; Pawlik, Kevin M; Lamb, Lawrence S; Goldman, Frederick D; Townes, Tim M

    2015-09-08

    Mutations of the Janus family kinase JAK3 gene cause severe combined immunodeficiency (SCID). JAK3 deficiency in humans is characterized by the absence of circulating T cells and natural killer (NK) cells with normal numbers of poorly functioning B cells (T(-)B(+)NK(-)). Using SCID patient-specific induced pluripotent stem cells (iPSCs) and a T cell in vitro differentiation system, we demonstrate a complete block in early T cell development of JAK3-deficient cells. Correction of the JAK3 mutation by CRISPR/Cas9-enhanced gene targeting restores normal T cell development, including the production of mature T cell populations with a broad T cell receptor (TCR) repertoire. Whole-genome sequencing of corrected cells demonstrates no CRISPR/Cas9 off-target modifications. These studies describe an approach for the study of human lymphopoiesis and provide a foundation for gene correction therapy in humans with immunodeficiencies.

  1. Combining qPCR and functional gene microarrays to directly link changes in the expression of the nirS gene to denitrification rates in aquatic sediment mesocosms

    NASA Astrophysics Data System (ADS)

    Bowen, J. L.; Babbin, A. R.; Ward, B. B.

    2010-12-01

    Molecular methods for the investigation of biogeochemical processes, including denitrification, are being developed at an astonishing rate, but it remains difficult to use the molecular information to understand the regulation and variation in biogeochemical transformation rates. By combining information on gene abundance and expression for nirS, a key gene in denitrification, with quantitative modeling of nitrogen fluxes, we can begin to understand the scales on which genetic signals vary in space and time, and how they relate to biogeochemical function. We used quantitative PCR, a functional gene microarray, and biogeochemical modeling to assess how denitrifier community composition (evaluated by DNA and cDNA of the nirS gene) changed over time in estuarine sediment mesocosms. Sediments and water were collected from coastal Massachusetts and maintained in replicated 20 L mesocosm experiments for 45 days. Sediments were collected for microbial analysis at weekly intervals throughout the experiment. Concentrations of all major nitrogen species were measured daily and used to derive rates of nitrification and denitrification from a Monte Carlo-based nonnegative least-squares analysis of finite difference equations. Denitrification rates peaked between day 18 and day 22, slightly after the peaks in nitrite concentration that were generated from oxidization of remineralized ammonium. In most mesocosms the peak in denitrification rates coincided with the peak in nirS gene abundance (DNA). Peaks in the expression of the nirS gene (cDNA), however, did not always correlate with peaks in the denitrification rates. The nirS microarray contained 39 archetype probes, three of which accounted for more than 60% of the DNA hybridization signal. Two of these clades also dominated the hybridization signal in cDNA, indicating that those organisms that are actively expressing nirS are not always the dominant members of the community. Fifteen of the 39 probes accounted for less than

  2. Key genes and pathways in thyroid cancer based on gene set enrichment analysis.

    PubMed

    He, Wenwu; Qi, Bin; Zhou, Qiuxi; Lu, Chuansen; Huang, Qi; Xian, Lei; Chen, Mingwu

    2013-09-01

    The incidence of thyroid cancer and its associated morbidity has shown the most rapid increase among all cancers since 1982, but the mechanisms involved in thyroid cancer, particularly significant key genes induced in thyroid cancer, remain undefined. In many studies, gene probes have been used to search for key genes involved in causing and facilitating thyroid cancer. As a result, many possible virulence genes and pathways have been identified. However, these studies lack a case contrast for selecting the most possible virulence genes and pathways, as well as conclusive results with which to clarify the mechanisms of cancer development. In the present study, we used gene set enrichment and meta-analysis to select key genes and pathways. Based on gene set enrichment, we identified 5 downregulated and 4 upregulated mixed pathways in 6 tissue datasets. Based on the meta-analysis, there were 17 common pathways in the tissue datasets. One pathway, the p53 signaling pathway, which includes 13 genes, was identified by both the gene set enrichment analysis and meta-analysis. Genes are important elements that form key pathways. These pathways can induce the development of thyroid cancer later in life. The key pathways and genes identified in the present study can be used in the next stage of research, which will involve gene elimination and other methods of experimentation.

  3. An Estimation of Erinaceidae Phylogeny: A Combined Analysis Approach

    PubMed Central

    Yamaguchi, Nobuyuki; Ai, Huai-Sen; Wang, Ying-Xiang; Zhang, Ya-Ping; Jiang, Xue-Long

    2012-01-01

    Background Erinaceidae is a family of small mammals that include the spiny hedgehogs (Erinaceinae) and the silky-furred moonrats and gymnures (Galericinae). These animals are widely distributed across Eurasia and Africa, from the tundra to the tropics and the deserts to damp forests. The importance of these animals lies in the fact that they are the oldest known living placental mammals, which are well represented in the fossil record, a rarity fact given their size and vulnerability to destruction during fossilization. Although the Family has been well studied, their phylogenetic relationships remain controversial. To test previous phylogenetic hypotheses, we combined molecular and morphological data sets, including representatives of all the genera. Methodology and Principal Findings We included in the analyses 3,218 bp mitochondrial genes, one hundred and thirty-five morphological characters, twenty-two extant erinaceid taxa, and five outgroup taxa. Phylogenetic relationships were reconstructed using both partitioned and combined data sets. As in previous analyses, our results strongly support the monophyly of both subfamilies (Galericinae and Erinaceinae), the Hylomys group (to include Neotetracus and Neohylomys), and a sister-relationship of Atelerix and Erinaceus. As well, we verified that the extremely long branch lengths within the Galericinae are consistent with their fossil records. Not surprisingly, we found significant incongruence between the phylogenetic signals of the genes and the morphological characters, specifically in the case of Hylomys parvus, Mesechinus, and relationships between Hemiechinus and Paraechinus. Conclusions Although we discovered new clues to understanding the evolutionary relationships within the Erinaceidae, our results nonetheless, strongly suggest that more robust analyses employing more complete taxon sampling (to include fossils) and multiple unlinked genes would greatly enhance our understanding of the Erinaceidae. Until

  4. Renal tissue thawed for 30 minutes is still suitable for gene expression analysis.

    PubMed

    Ma, Yi; Kang, Xiao-Nan; Ding, Wen-Bin; Yang, Hao-Zheng; Wang, Ye; Zhang, Jin; Huang, Yi-Ran; Dai, Hui-Li

    2014-01-01

    Some biosamples obtained from biobanks may go through thawing before processing. We aim to evaluate the effects of thawing at room temperature for different time periods on gene expression analysis. A time course study with four time points was conducted to investigate the expression profiling on 10 thawed normal mice renal tissue samples through Affymetrix GeneChip mouse gene 2.0 st array. Microarray results were validated by quantitative real time polymerase chain reactions (qPCR) on 6 candidate reference genes and 11 target genes. Additionally, we used geNorm plus and NormFinder to identify the most stably expressed reference genes over time. The results showed RNA degraded more after longer incubation at room temperature. However, microarray results showed only 240 genes (0.91%) altered significantly in response to thawing at room temperature. The signal of majority altered probe sets decreased with thawing time, and the crossing point (Cp) values of all candidate reference genes correlated positively with the thawing time (p<0.05). The combination of B2M, ACTB and PPIA was identified as the best choice for qPCR normalization. We found most target genes were stable by using this normalization method. However, serious gene quantification errors were resulted from improper reference genes. In conclusion, thirty minutes of thawing at room temperature has a limited impact on microarray and qPCR analysis, gene expression variations due to RNA degradation in early period after thawing can be largely reduced by proper normalization.

  5. Renal Tissue Thawed for 30 Minutes Is Still Suitable for Gene Expression Analysis

    PubMed Central

    Ding, Wen-Bin; Yang, Hao-Zheng; Wang, Ye; Zhang, Jin; Huang, Yi-Ran; Dai, Hui-Li

    2014-01-01

    Some biosamples obtained from biobanks may go through thawing before processing. We aim to evaluate the effects of thawing at room temperature for different time periods on gene expression analysis. A time course study with four time points was conducted to investigate the expression profiling on 10 thawed normal mice renal tissue samples through Affymetrix GeneChip mouse gene 2.0 st array. Microarray results were validated by quantitative real time polymerase chain reactions (qPCR) on 6 candidate reference genes and 11 target genes. Additionally, we used geNorm plus and NormFinder to identify the most stably expressed reference genes over time. The results showed RNA degraded more after longer incubation at room temperature. However, microarray results showed only 240 genes (0.91%) altered significantly in response to thawing at room temperature. The signal of majority altered probe sets decreased with thawing time, and the crossing point (Cp) values of all candidate reference genes correlated positively with the thawing time (p<0.05). The combination of B2M, ACTB and PPIA was identified as the best choice for qPCR normalization. We found most target genes were stable by using this normalization method. However, serious gene quantification errors were resulted from improper reference genes. In conclusion, thirty minutes of thawing at room temperature has a limited impact on microarray and qPCR analysis, gene expression variations due to RNA degradation in early period after thawing can be largely reduced by proper normalization. PMID:24687048

  6. Programmable control of bacterial gene expression with the combined CRISPR and antisense RNA system.

    PubMed

    Lee, Young Je; Hoynes-O'Connor, Allison; Leong, Matthew C; Moon, Tae Seok

    2016-03-18

    A central goal of synthetic biology is to implement diverse cellular functions by predictably controlling gene expression. Though research has focused more on protein regulators than RNA regulators, recent advances in our understanding of RNA folding and functions have motivated the use of RNA regulators. RNA regulators provide an advantage because they are easier to design and engineer than protein regulators, potentially have a lower burden on the cell and are highly orthogonal. Here, we combine the CRISPR system from Streptococcus pyogenes and synthetic antisense RNAs (asRNAs) in Escherichia coli strains to repress or derepress a target gene in a programmable manner. Specifically, we demonstrate for the first time that the gene target repressed by the CRISPR system can be derepressed by expressing an asRNA that sequesters a small guide RNA (sgRNA). Furthermore, we demonstrate that tunable levels of derepression can be achieved (up to 95%) by designing asRNAs that target different regions of a sgRNA and by altering the hybridization free energy of the sgRNA-asRNA complex. This new system, which we call the combined CRISPR and asRNA system, can be used to reversibly repress or derepress multiple target genes simultaneously, allowing for rational reprogramming of cellular functions.

  7. Combining Disease Models to Test for Gene-Environment Interaction in Nuclear Families

    PubMed Central

    Hoffmann, Thomas J.; Vansteelandt, Stijn; Lange, Christoph; Silverman, Edwin K.; DeMeo, Dawn L.; Laird, Nan M.

    2011-01-01

    Summary It is useful to have robust gene-environment interaction tests that can utilize a variety of family structures in an efficient way. This paper focuses on tests for gene-environment interaction in the presence of main genetic and environmental effects. The objective is to develop powerful tests that can combine trio data with parental genotypes and discordant sibships when parents genotypes are missing. We first make a modest improvement on a method for discordant sibs (discordant on phenotype), but the approach does not allow one to use families when all offspring are affected, e.g. trios. We then make a modest improvement on a Mendelian transmission-based approach that is inefficient when discordant sibs are available, but can be applied to any nuclear family. Finally, we propose a hybrid approach that utilizes the most efficient method for a specific family type, then combines over families. We utilize this hybrid approach to analyze a chronic obstructive pulmonary disorder dataset to test for gene-environment interaction in the Serpine2 gene with smoking. The methods are freely available in the R package fbati. PMID:21401569

  8. Combination Gene Therapy for Liver Metastasis of Colon Carcinoma in vivo

    NASA Astrophysics Data System (ADS)

    Chen, Shu-Hsai; Chen, X. H. Li; Wang, Yibin; Kosai, Ken-Ichiro; Finegold, Milton J.; Rich, Susan S.

    1995-03-01

    The efficacy of combination therapy with a "suicide gene" and a cytokine gene to treat metastatic colon carcinoma in the liver was investigated. Tumor in the liver was generated by intrahepatic injection of a colon carcinoma cell line (MCA-26) in syngeneic BALB/c mice. Recombinant adenoviral vectors containing various control and therapeutic genes were injected directly into the solid tumors, followed by treatment with ganciclovir. While the tumors continued to grow in all animals treated with a control vector or a mouse interleukin 2 vector, those treated with a herpes simplex virus thymidine kinase vector, with or without the coadministration of the mouse interleukin 2 vector, exhibited dramatic necrosis and regression. However, only animals treated with both vectors developed an effective systemic antitumoral immunity against challenges of tumorigenic doses of parental tumor cells inoculated at distant sites. The antitumoral immunity was associated with the presence of MCA-26 tumor-specific cytolytic CD8^+ T lymphocytes. The results suggest that combination suicide and cytokine gene therapy in vivo can be a powerful approach for treatment of metastatic colon carcinoma in the liver.

  9. Combining sequence and Gene Ontology for protein module detection in the Weighted Network.

    PubMed

    Yu, Yang; Liu, Jie; Feng, Nuan; Song, Bo; Zheng, Zeyu

    2017-01-07

    Studies of protein modules in a Protein-Protein Interaction (PPI) network contribute greatly to the understanding of biological mechanisms. With the development of computing science, computational approaches have played an important role in locating protein modules. In this paper, a new approach combining Gene Ontology and amino acid background frequency is introduced to detect the protein modules in the weighted PPI networks. The proposed approach mainly consists of three parts: the feature extraction, the weighted graph construction and the protein complex detection. Firstly, the topology-sequence information is utilized to present the feature of protein complex. Secondly, six types of the weighed graph are constructed by combining PPI network and Gene Ontology information. Lastly, protein complex algorithm is applied to the weighted graph, which locates the clusters based on three conditions, including density, network diameter and the included angle cosine. Experiments have been conducted on two protein complex benchmark sets for yeast and the results show that the approach is more effective compared to five typical algorithms with the performance of f-measure and precision. The combination of protein interaction network with sequence and gene ontology data is helpful to improve the performance and provide a optional method for protein module detection. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Combining Sequence and Gene Ontology for Protein Module Detection in the Weighted Network.

    PubMed

    Yu, Yang; Liu, Jie; Feng, Nuan; Song, Bo; Zheng, Zeyu

    2016-10-29

    Studies of protein modules in a Protein-Protein Interaction (PPI) network contribute greatly to the understanding of biological mechanisms. With the development of computing science, computational approaches have played an important role in locating protein modules. In this paper, a new approach combining Gene Ontology and amino acid background frequency is introduced to detect the protein modules in the weighted PPI networks. The proposed approach mainly consists of three parts: the feature extraction, the weighted graph construction and the protein complex detection. Firstly, the topology-sequence information is utilized to present the feature of protein complex. Secondly, six types of the weighed graph are constructed by combining PPI network and Gene Ontology information. Lastly, protein complex algorithm is applied to the weighted graph, which locates the clusters based on three conditions, including density, network diameter and the included angle cosine. Experiments have been conducted on two protein complex benchmark sets for yeast and the results show that the approach is more effective compared to five typical algorithms with the performance of f-measure and precision. The combination of protein interaction network with sequence and gene ontology data is helpful to improve the performance and provide a optional method for protein module detection.

  11. Combined sequence-based and genetic mapping analysis of complex traits in outbred rats.

    PubMed

    Baud, Amelie; Hermsen, Roel; Guryev, Victor; Stridh, Pernilla; Graham, Delyth; McBride, Martin W; Foroud, Tatiana; Calderari, Sophie; Diez, Margarita; Ockinger, Johan; Beyeen, Amennai D; Gillett, Alan; Abdelmagid, Nada; Guerreiro-Cacais, Andre Ortlieb; Jagodic, Maja; Tuncel, Jonatan; Norin, Ulrika; Beattie, Elisabeth; Huynh, Ngan; Miller, William H; Koller, Daniel L; Alam, Imranul; Falak, Samreen; Osborne-Pellegrin, Mary; Martinez-Membrives, Esther; Canete, Toni; Blazquez, Gloria; Vicens-Costa, Elia; Mont-Cardona, Carme; Diaz-Moran, Sira; Tobena, Adolf; Hummel, Oliver; Zelenika, Diana; Saar, Kathrin; Patone, Giannino; Bauerfeind, Anja; Bihoreau, Marie-Therese; Heinig, Matthias; Lee, Young-Ae; Rintisch, Carola; Schulz, Herbert; Wheeler, David A; Worley, Kim C; Muzny, Donna M; Gibbs, Richard A; Lathrop, Mark; Lansu, Nico; Toonen, Pim; Ruzius, Frans Paul; de Bruijn, Ewart; Hauser, Heidi; Adams, David J; Keane, Thomas; Atanur, Santosh S; Aitman, Tim J; Flicek, Paul; Malinauskas, Tomas; Jones, E Yvonne; Ekman, Diana; Lopez-Aumatell, Regina; Dominiczak, Anna F; Johannesson, Martina; Holmdahl, Rikard; Olsson, Tomas; Gauguier, Dominique; Hubner, Norbert; Fernandez-Teruel, Alberto; Cuppen, Edwin; Mott, Richard; Flint, Jonathan

    2013-07-01

    Genetic mapping on fully sequenced individuals is transforming understanding of the relationship between molecular variation and variation in complex traits. Here we report a combined sequence and genetic mapping analysis in outbred rats that maps 355 quantitative trait loci for 122 phenotypes. We identify 35 causal genes involved in 31 phenotypes, implicating new genes in models of anxiety, heart disease and multiple sclerosis. The relationship between sequence and genetic variation is unexpectedly complex: at approximately 40% of quantitative trait loci, a single sequence variant cannot account for the phenotypic effect. Using comparable sequence and mapping data from mice, we show that the extent and spatial pattern of variation in inbred rats differ substantially from those of inbred mice and that the genetic variants in orthologous genes rarely contribute to the same phenotype in both species.

  12. Combined sequence-based and genetic mapping analysis of complex traits in outbred rats

    PubMed Central

    Baud, Amelie; Hermsen, Roel; Guryev, Victor; Stridh, Pernilla; Graham, Delyth; McBride, Martin W.; Foroud, Tatiana; Calderari, Sophie; Diez, Margarita; Ockinger, Johan; Beyeen, Amennai D.; Gillett, Alan; Abdelmagid, Nada; Guerreiro-Cacais, Andre Ortlieb; Jagodic, Maja; Tuncel, Jonatan; Norin, Ulrika; Beattie, Elisabeth; Huynh, Ngan; Miller, William H.; Koller, Daniel L.; Alam, Imranul; Falak, Samreen; Osborne-Pellegrin, Mary; Martinez-Membrives, Esther; Canete, Toni; Blazquez, Gloria; Vicens-Costa, Elia; Mont-Cardona, Carme; Diaz-Moran, Sira; Tobena, Adolf; Hummel, Oliver; Zelenika, Diana; Saar, Kathrin; Patone, Giannino; Bauerfeind, Anja; Bihoreau, Marie-Therese; Heinig, Matthias; Lee, Young-Ae; Rintisch, Carola; Schulz, Herbert; Wheeler, David A.; Worley, Kim C.; Muzny, Donna M.; Gibbs, Richard A.; Lathrop, Mark; Lansu, Nico; Toonen, Pim; Ruzius, Frans Paul; de Bruijn, Ewart; Hauser, Heidi; Adams, David J.; Keane, Thomas; Atanur, Santosh S.; Aitman, Tim J.; Flicek, Paul; Malinauskas, Tomas; Jones, E. Yvonne; Ekman, Diana; Lopez-Aumatell, Regina; Dominiczak, Anna F; Johannesson, Martina; Holmdahl, Rikard; Olsson, Tomas; Gauguier, Dominique; Hubner, Norbert; Fernandez-Teruel, Alberto; Cuppen, Edwin; Mott, Richard; Flint, Jonathan

    2013-01-01

    Genetic mapping on fully sequenced individuals is transforming our understanding of the relationship between molecular variation and variation in complex traits. Here we report a combined sequence and genetic mapping analysis in outbred rats that maps 355 quantitative trait loci for 122 phenotypes. We identify 35 causal genes involved in 31 phenotypes, implicating novel genes in models of anxiety, heart disease and multiple sclerosis. The relation between sequence and genetic variation is unexpectedly complex: at approximately 40% of quantitative trait loci a single sequence variant cannot account for the phenotypic effect. Using comparable sequence and mapping data from mice, we show the extent and spatial pattern of variation in inbred rats differ significantly from those of inbred mice, and that the genetic variants in orthologous genes rarely contribute to the same phenotype in both species. PMID:23708188

  13. Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells.

    PubMed

    de Luis Balaguer, Maria Angels; Fisher, Adam P; Clark, Natalie M; Fernandez-Espinosa, Maria Guadalupe; Möller, Barbara K; Weijers, Dolf; Lohmann, Jan U; Williams, Cranos; Lorenzo, Oscar; Sozzani, Rosangela

    2017-09-05

    Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is essential for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. To accomplish this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network inference algorithm that combines clustering with dynamic Bayesian network inference. We leveraged the topology of our networks to infer potential major regulators. Specifically, through mathematical modeling and experimental validation, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center function. The results presented in this work show that our combination of molecular biology, computational biology, and mathematical modeling is an efficient approach to identify candidate factors that function in the stem cells.

  14. Gene Expression Profile Analysis of Type 2 Diabetic Mouse Liver

    PubMed Central

    Zhang, Fang; Xu, Xiang; Zhang, Yi; Zhou, Ben; He, Zhishui; Zhai, Qiwei

    2013-01-01

    Liver plays a key role in glucose metabolism and homeostasis, and impaired hepatic glucose metabolism contributes to the development of type 2 diabetes. However, the precise gene expression profile of diabetic liver and its association with diabetes and related diseases are yet to be further elucidated. In this study, we detected the gene expression profile by high-throughput sequencing in 9-week-old normal and type 2 diabetic db/db mouse liver. Totally 12132 genes were detected, and 2627 genes were significantly changed in diabetic mouse liver. Biological process analysis showed that the upregulated genes in diabetic mouse liver were mainly enriched in metabolic processes. Surprisingly, the downregulated genes in diabetic mouse liver were mainly enriched in immune-related processes, although all the altered genes were still mainly enriched in metabolic processes. Similarly, KEGG pathway analysis showed that metabolic pathways were the major pathways altered in diabetic mouse liver, and downregulated genes were enriched in immune and cancer pathways. Analysis of the key enzyme genes in fatty acid and glucose metabolism showed that some key enzyme genes were significantly increased and none of the detected key enzyme genes were decreased. In addition, FunDo analysis showed that liver cancer and hepatitis were most likely to be associated with diabetes. Taken together, this study provides the digital gene expression profile of diabetic mouse liver, and demonstrates the main diabetes-associated hepatic biological processes, pathways, key enzyme genes in fatty acid and glucose metabolism and potential hepatic diseases. PMID:23469233

  15. Gene expression profile analysis of type 2 diabetic mouse liver.

    PubMed

    Zhang, Fang; Xu, Xiang; Zhang, Yi; Zhou, Ben; He, Zhishui; Zhai, Qiwei

    2013-01-01

    Liver plays a key role in glucose metabolism and homeostasis, and impaired hepatic glucose metabolism contributes to the development of type 2 diabetes. However, the precise gene expression profile of diabetic liver and its association with diabetes and related diseases are yet to be further elucidated. In this study, we detected the gene expression profile by high-throughput sequencing in 9-week-old normal and type 2 diabetic db/db mouse liver. Totally 12132 genes were detected, and 2627 genes were significantly changed in diabetic mouse liver. Biological process analysis showed that the upregulated genes in diabetic mouse liver were mainly enriched in metabolic processes. Surprisingly, the downregulated genes in diabetic mouse liver were mainly enriched in immune-related processes, although all the altered genes were still mainly enriched in metabolic processes. Similarly, KEGG pathway analysis showed that metabolic pathways were the major pathways altered in diabetic mouse liver, and downregulated genes were enriched in immune and cancer pathways. Analysis of the key enzyme genes in fatty acid and glucose metabolism showed that some key enzyme genes were significantly increased and none of the detected key enzyme genes were decreased. In addition, FunDo analysis showed that liver cancer and hepatitis were most likely to be associated with diabetes. Taken together, this study provides the digital gene expression profile of diabetic mouse liver, and demonstrates the main diabetes-associated hepatic biological processes, pathways, key enzyme genes in fatty acid and glucose metabolism and potential hepatic diseases.

  16. The distribution of Escherichia coli serovars, virulence genes, gene association and combinations and virulence genes encoding serotypes in pathogenic E. coli recovered from diarrhoeic calves, sheep and goat.

    PubMed

    Osman, K M; Mustafa, A M; Elhariri, M; Abdelhamed, G S

    2013-02-01

    Ruminants, especially cattle, have been implicated as a principal reservoir of one of the enterovirulent Escherichia coli pathotypes. The detection of the virulence genes in diarrhoeic calves and small ruminants has not been studied in Egypt. To determine the occurrence, serotypes and the virulence gene markers, stx1, stx2, hylA, Flic(h7) , stb, F41, K99, sta, F17, LT-I, LT-II and eae, rectal swabs were taken from diarrhoeic calves, sheep and goats and subjected to bacterial culture and PCR. The E. coli prevalence rate in the diarrhoeic animals was 63.6% in calves, 27.3% in goat and 9.1% in sheep. The 102 E. coli strains isolated from the calves, goat and sheep were 100% haemolytic non-verotoxic and fitted into the Eagg group. The isolates belonged to seven O serogroups (O25, O78, O86, O119, O158, O164 and O157). The eae gene was detected in six of the strains isolated from the calves. The 102 bovine, ovine and caprine E. coli strains isolated in this study were negative for stx1, stx2, F41, LT-I and Flic(h7) genes. The highest gene combinations were found to occur in the form of 24/102 isolates (23.5%) that carried the F17 gene predominantly associated with eaeA, hylA, K99 and Stb genes in the calves, while the hylA, K99 and Sta were the only genes found to be in conjunction in both calves and goats (6/102; 5.9% each). Our data show that in Egypt, large and small ruminants could be a potential source of infection in humans.

  17. Gene set analysis of purine and pyrimidine antimetabolites cancer therapies.

    PubMed

    Fridley, Brooke L; Batzler, Anthony; Li, Liang; Li, Fang; Matimba, Alice; Jenkins, Gregory D; Ji, Yuan; Wang, Liewei; Weinshilboum, Richard M

    2011-11-01

    Responses to therapies, either with regard to toxicities or efficacy, are expected to involve complex relationships of gene products within the same molecular pathway or functional gene set. Therefore, pathways or gene sets, as opposed to single genes, may better reflect the true underlying biology and may be more appropriate units for analysis of pharmacogenomic studies. Application of such methods to pharmacogenomic studies may enable the detection of more subtle effects of multiple genes in the same pathway that may be missed by assessing each gene individually. A gene set analysis of 3821 gene sets is presented assessing the association between basal messenger RNA expression and drug cytotoxicity using ethnically defined human lymphoblastoid cell lines for two classes of drugs: pyrimidines [gemcitabine (dFdC) and arabinoside] and purines [6-thioguanine and 6-mercaptopurine]. The gene set nucleoside-diphosphatase activity was found to be significantly associated with both dFdC and arabinoside, whereas gene set γ-aminobutyric acid catabolic process was associated with dFdC and 6-thioguanine. These gene sets were significantly associated with the phenotype even after adjusting for multiple testing. In addition, five associated gene sets were found in common between the pyrimidines and two gene sets for the purines (3',5'-cyclic-AMP phosphodiesterase activity and γ-aminobutyric acid catabolic process) with a P value of less than 0.0001. Functional validation was attempted with four genes each in gene sets for thiopurine and pyrimidine antimetabolites. All four genes selected from the pyrimidine gene sets (PSME3, CANT1, ENTPD6, ADRM1) were validated, but only one (PDE4D) was validated for the thiopurine gene sets. In summary, results from the gene set analysis of pyrimidine and purine therapies, used often in the treatment of various cancers, provide novel insight into the relationship between genomic variation and drug response.

  18. Gene set analysis of purine and pyrimidine antimetabolites cancer therapies

    PubMed Central

    Fridley, Brooke L.; Batzler, Anthony; Li, Liang; Li, Fang; Matimba, Alice; Jenkins, Gregory D.; Ji, Yuan; Wang, Liewei; Weinshilboum, Richard M.

    2011-01-01

    Objective Responses to therapies, either with regards to toxicities or efficacy, are expected to involve complex relationships of gene products within the same molecular pathway or functional gene set. Therefore, pathways or gene sets, as opposed to single genes, may better reflect the true underlying biology and may be more appropriate units for analysis of pharmacogenomic studies. Application of such methods to pharmacogenomic studies may enable the detection of more subtle effects of multiple genes in the same pathway that may be missed by assessing each gene individually. Methods A gene set analysis of 3,821 gene sets is presented assessing the association between basal mRNA expression and drug cytotoxicity using ethnically defined human lymphoblastoid cell lines for two classes of drugs: pyrimidines (dFdC and AraC) and purines (6-TG and 6-MP). Results The gene set nucleoside-diphosphatase activity was found to be significantly associated with both dFdC and AraC, while gene set gamma-aminobutyric acid catabolic process was associated with dFdC and 6-TG. These gene sets were significantly associated with the phenotype even after adjusting for multiple testing. In addition, five associated gene sets were found in common between the pyrimidines and two gene sets for the purines (3′,5′-cyclic-AMP phosphodiesterase activity and gamma-aminobutyric acid catabolic process) with p < 0.0001. Functional validation was attempted with 4 genes each in gene sets for thiopurine and pyrimidine anti-metabolites. All four genes selected from the pyrimidine gene sets (PSME3, CANT1, ENTPD6, ADRM1) were validated, but only one (PDE4D) was validated for the thiopurine gene sets. Conclusions In summary, results from the gene set analysis of pyrimidine and purine therapies, used often in the treatment of various cancers, provide novel insight into the relationship between genomic variation and drug response. PMID:21869733

  19. An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

    PubMed

    Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

    2014-06-01

    In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both

  20. Combination of adenovirus and cross-linked low molecular weight PEI improves efficiency of gene transduction

    NASA Astrophysics Data System (ADS)

    Han, Jianfeng; Zhao, Dong; Zhong, Zhirong; Zhang, Zhirong; Gong, Tao; Sun, Xun

    2010-03-01

    Recombinant adenovirus (Ad)-mediated gene therapy is an exciting novel strategy in cancer treatment. However, poor infection efficiency with coxsackievirus and adenovirus receptor (CAR) down-regulated cancer cell lines is one of the major challenges for its practical and extensive application. As an alternative method of viral gene delivery, a non-viral carrier using cationic materials could compensate for the limitation of adenovirus. In our study, adenovectors were complexed with a new synthetic polymer PEI-DEG-bis-NPC (PDN) based on polyethylenimine (PEI), and then the properties of the vehicle were characterized by measurement of size distribution, zeta potential and transmission electron microscopy (TEM). Enhancement of gene transduction by Ad/PDN complexes was observed in both CAR-overexpressing cell lines (A549) and CAR-lacking cell lines (MDCK, CHO, LLC), as a result of facilitating binding and cell uptake of adenoviral particles by the cationic component. Ad/PDN complexes also promoted the inhibition of tumor growth in vivo and prolonged the survival time of tumor-bearing mice. These data suggest that a combination of viral and non-viral gene delivery methods may offer a new approach to successful cancer gene therapy.

  1. Combinational Spinal GAD65 Gene Delivery and Systemic GABA-Mimetic Treatment for Modulation of Spasticity

    PubMed Central

    Kakinohana, Osamu; Hefferan, Michael P.; Miyanohara, Atsushi; Nejime, Tetsuya; Marsala, Silvia; Juhas, Stefan; Juhasova, Jana; Motlik, Jan; Kucharova, Karolina; Strnadel, Jan; Platoshyn, Oleksandr; Lazar, Peter; Galik, Jan; Vinay, Laurent; Marsala, Martin

    2012-01-01

    Background Loss of GABA-mediated pre-synaptic inhibition after spinal injury plays a key role in the progressive increase in spinal reflexes and the appearance of spasticity. Clinical studies show that the use of baclofen (GABAB receptor agonist), while effective in modulating spasticity is associated with major side effects such as general sedation and progressive tolerance development. The goal of the present study was to assess if a combined therapy composed of spinal segment-specific upregulation of GAD65 (glutamate decarboxylase) gene once combined with systemic treatment with tiagabine (GABA uptake inhibitor) will lead to an antispasticity effect and whether such an effect will only be present in GAD65 gene over-expressing spinal segments. Methods/Principal Findings Adult Sprague-Dawley (SD) rats were exposed to transient spinal ischemia (10 min) to induce muscle spasticity. Animals then received lumbar injection of HIV1-CMV-GAD65 lentivirus (LVs) targeting ventral α-motoneuronal pools. At 2–3 weeks after lentivirus delivery animals were treated systemically with tiagabine (4, 10, 20 or 40 mg/kg or vehicle) and the degree of spasticity response measured. In a separate experiment the expression of GAD65 gene after spinal parenchymal delivery of GAD65-lentivirus in naive minipigs was studied. Spastic SD rats receiving spinal injections of the GAD65 gene and treated with systemic tiagabine showed potent and tiagabine-dose-dependent alleviation of spasticity. Neither treatment alone (i.e., GAD65-LVs injection only or tiagabine treatment only) had any significant antispasticity effect nor had any detectable side effect. Measured antispasticity effect correlated with increase in spinal parenchymal GABA synthesis and was restricted to spinal segments overexpressing GAD65 gene. Conclusions/Significance These data show that treatment with orally bioavailable GABA-mimetic drugs if combined with spinal-segment-specific GAD65 gene overexpression can represent a novel

  2. Study of the combined treatment of lung cancer using gene-loaded immunomagnetic albumin nanospheres in vitro and in vivo.

    PubMed

    Zhang, Hao; Liang, Chen; Hou, Xinxin; Wang, Ling; Zhang, Dongsheng

    2016-01-01

    Combination therapy for lung cancer has garnered widespread attention. Radiation therapy, gene therapy, and molecular targeted therapy for lung cancer have certain effects, but the disadvantages of these treatment methods are evident. Combining these methods can decrease their side effects and increase their curative effects. In this study, we constructed a pYr-ads-8-5HRE-cfosp-iNOS-IFNG plasmid (a gene circuit that can express IFNγ), which is a gene circuit, and used that plasmid together with C225 (cetuximab) to prepare gene-loaded immunomagnetic albumin nanospheres (IMANS). Moreover, we investigated the therapeutic effects of gene-loaded IMANS in combination with radiation therapy on human lung cancer in vitro and in vivo. The results showed that this gene circuit was successively constructed and confirmed that the expression of INFγ was increased due to the gene circuit. Gene-loaded IMANS combined with radiation therapy demonstrated improved results in vitro and in vivo. In conclusion, gene-loaded IMANS enhanced the efficacy of combination therapy, solved problems related to gene transfer, and specifically targeted lung cancer cells.

  3. Study of the combined treatment of lung cancer using gene-loaded immunomagnetic albumin nanospheres in vitro and in vivo

    PubMed Central

    Zhang, Hao; Liang, Chen; Hou, Xinxin; Wang, Ling; Zhang, Dongsheng

    2016-01-01

    Combination therapy for lung cancer has garnered widespread attention. Radiation therapy, gene therapy, and molecular targeted therapy for lung cancer have certain effects, but the disadvantages of these treatment methods are evident. Combining these methods can decrease their side effects and increase their curative effects. In this study, we constructed a pYr-ads-8-5HRE-cfosp-iNOS-IFNG plasmid (a gene circuit that can express IFNγ), which is a gene circuit, and used that plasmid together with C225 (cetuximab) to prepare gene-loaded immunomagnetic albumin nanospheres (IMANS). Moreover, we investigated the therapeutic effects of gene-loaded IMANS in combination with radiation therapy on human lung cancer in vitro and in vivo. The results showed that this gene circuit was successively constructed and confirmed that the expression of INFγ was increased due to the gene circuit. Gene-loaded IMANS combined with radiation therapy demonstrated improved results in vitro and in vivo. In conclusion, gene-loaded IMANS enhanced the efficacy of combination therapy, solved problems related to gene transfer, and specifically targeted lung cancer cells. PMID:27042059

  4. A combination test for detection of gene-environment interaction in cohort studies.

    PubMed

    Coombes, Brandon; Basu, Saonli; McGue, Matt

    2017-07-01

    Identifying gene-environment (G-E) interactions can contribute to a better understanding of disease etiology, which may help researchers develop disease prevention strategies and interventions. One big criticism of studying G-E interaction is the lack of power due to sample size. Studies often restrict the interaction search to the top few hundred hits from a genome-wide association study or focus on potential candidate genes. In this paper, we test interactions between a candidate gene and an environmental factor to improve power by analyzing multiple variants within a gene. We extend recently developed score statistic based genetic association testing approaches to the G-E interaction testing problem. We also propose tests for interaction using gene-based summary measures that pool variants together. Although it has recently been shown that these summary measures can be biased and may lead to inflated type I error, we show that under several realistic scenarios, we can still provide valid tests of interaction. These tests use significantly less degrees of freedom and thus can have much higher power to detect interaction. Additionally, we demonstrate that the iSeq-aSum-min test, which combines a gene-based summary measure test, iSeq-aSum-G, and an interaction-based summary measure test, iSeq-aSum-I, provides a powerful alternative to test G-E interaction. We demonstrate the performance of these approaches using simulation studies and illustrate their performance to study interaction between the SNPs in several candidate genes and family climate environment on alcohol consumption using the Minnesota Center for Twin and Family Research dataset. © 2017 WILEY PERIODICALS, INC.

  5. Combining small molecules for cell reprogramming through an interatomic analysis.

    PubMed

    Feltes, Bruno César; Bonatto, Diego

    2013-11-01

    The knowledge available about the application and generation of induced pluripotent stem cells (iPSC) has grown since their discovery, and new techniques to enhance the reprogramming process have been described. Among the new approaches to induce iPSC that have gained great attention is the use of small molecules for reprogramming. The application of small molecules, unlike genetic manipulation, provides for control of the reprogramming process through the shifting of concentrations and the combination of different molecules. However, different researchers have reported the use of "reprogramming cocktails" with variable results and drug combinations. Thus, the proper combination of small molecules for successful and enhanced reprogramming is a matter for discussion. However, testing all potential drug combinations in different cell lineages is very costly and time-consuming. Therefore, in this article, we discuss the use of already employed molecules for iPSC generation, followed by the application of systems chemo-biology tools to create different data sets of protein-protein (PPI) and chemical-protein (CPI) interaction networks based on the knowledge of already used and new reprogramming cocktail combinations. We further analyzed the biological processes associated with PPI-CPI networks and provided new potential protein targets to be inhibited or expressed for stem cell reprogramming. In addition, we applied a new interference analysis to prospective targets that could negatively affect the classical pluripotency-associated factors (SOX2, NANOG, KLF4 and OCT4) and thus potentially improve reprogramming protocols.

  6. Treatment of medullary thyroid carcinoma by combined expression of suicide and interleukin-2 genes.

    PubMed

    Soler, M N; Milhaud, G; Lekmine, F; Treilhou-Lahille, F; Klatzmann, D; Lausson, S

    1999-01-01

    Inherited medullary thyroid carcinomas (MTC) are aggressive and resistant to conventional chemo- and radiotherapies. We evaluated a novel strategy for treatment of MTC, combining "suicide" and interleukin-2 (IL-2) gene therapies. Tumors were produced in Wag/Rij rats by orthotopic injection of the rMTC 6-23 cell line, and/or derivatives expressing the herpes simplex virus 1 thymidine kinase (HSV1-TK) gene (rMTC-TK). Ganciclovir, a nucleoside analog selectively transformed to a toxic metabolite by HSV1-TK, totally eradicated rMTC-TK tumors in 60% of the animals. 1:1 rMTC and rMTC-TK mixed tumors were also strongly inhibited by ganciclovir (P < 0.05), indicating the occurrence of an efficient "bystander" effect in vivo. Double labelling of rMTC cell membranes and apoptotic nuclei revealed that, as with the TK+ cells, some TK- cells died by apoptosis. A 1:1 mixture of rMTC and rMTC-TK cells was administered to produce established tumors and then rMTC cells, transfected to express the IL-2 gene (rMTC-IL2), were inoculated. Combined ganciclovir and IL-2 treatment improved the inhibition of tumor growth compared to that following ganciclovir alone (86% compared to 54%, P < 0.05). This treatment also significantly enhanced macrophage activation and tumor infiltration by CD8+ and CD4+ T lymphocytes. These results open an avenue for combining suicide and immunoregulatory gene therapies for MTC management in man.

  7. Combined folate gene MTHFD and TC polymorphisms as maternal risk factors for Down syndrome in China.

    PubMed

    Liao, Y P; Zhang, D; Zhou, W; Meng, F M; Bao, M S; Xiang, P; Liu, C Q

    2014-03-17

    We examined whether polymorphisms in the methylenetetrahydrofolate dehydrogenase (MTHFD) and transcobalamin (TC) genes, which are involved in folate metabolism, affect maternal risk for Down syndrome. We investigated 76 Down syndrome mothers and 115 control mothers from Bengbu, China. Genomic DNA was isolated from the peripheral lymphocytes. Polymerase chain reaction and restriction fragment length polymorphism were used to examine the polymorphisms of MTHFD G1958A and TC C776G. The frequencies of the polymorphic alleles were 24.3 and 19.1% for MTHFD 1958A, 53.9 and 54.2% for TC 776G, in the case and control groups, respectively. No significant differences were found between two groups in relation to either the allele or the genotype frequency for both polymorphisms. However, when gene-gene interactions between these two polymorphisms together with previous studied C677T and A1298C polymorphisms in the methylenetetrahydrofolate reductase (MTHFR) gene were analyzed, the combined MTHFR 677CT/TT and MTHFD 1958AA/GA genotype was found to be significantly associated with the risk of having a Down syndrome child [odds ratio (OR) = 3.11; 95% confidence interval (95%CI) = 1.07-9.02]. In addition, the combined TC 776CG and MTHFR 677TT genotype increased the risk of having a child with Down syndrome 3.64-fold (OR = 3.64; 95%CI = 1.28-10.31). In conclusion, neither MTHFD G1958A nor TC C776G polymorphisms are an independent risk factor for Down syndrome. However, the combined MTHFD/MTHFR, TC/MTHFR genotypes play a role in the risk of bearing a Down syndrome child in the Chinese population.

  8. The gene for severe combined immunodeficiency disease in Athabascan-speaking Native Americans is located on chromosome 10p.

    PubMed Central

    Li, L; Drayna, D; Hu, D; Hayward, A; Gahagan, S; Pabst, H; Cowan, M J

    1998-01-01

    Severe combined immunodeficiency disease (SCID) consists of a group of heterogeneous genetic disorders. The most severe phenotype, T-B- SCID, is inherited as an autosomal recessive trait and is characterized by a profound deficiency of both T cell and B cell immunity. There is a uniquely high frequency of T-B- SCID among Athabascan-speaking Native Americans (A-SCID). To localize the A-SCID gene, we conducted a genomewide search, using linkage analysis of approximately 300 microsatellite markers in 14 affected Athabascan-speaking Native American families. We obtained conclusive evidence for linkage of the A-SCID locus to markers on chromosome 10p. The maximum pairwise LOD scores 4.53 and 4.60 were obtained from two adjacent markers, D10S191 and D10S1653, respectively, at a recombination fraction of straight theta=.00. Recombination events placed the gene in an interval of approximately 6.5 cM flanked by D10S1664 and D10S674. Multipoint analysis positioned the gene for the A-SCID phenotype between D10S191 and D10S1653, with a peak LOD score of 5.10 at D10S191. Strong linkage disequilibrium was found in five linked markers spanning approximately 6.5 cM in the candidate region, suggesting a founder effect with an ancestral mutation that occurred sometime before 1300 A.D. PMID:9443881

  9. Combined linkage and association mapping reveals CYCD5;1 as a quantitative trait gene for endoreduplication in Arabidopsis

    PubMed Central

    Sterken, Roel; Kiekens, Raphaël; Boruc, Joanna; Zhang, Fanghong; Vercauteren, Annelies; Vercauteren, Ilse; De Smet, Lien; Dhondt, Stijn; Inzé, Dirk; De Veylder, Lieven; Russinova, Eugenia; Vuylsteke, Marnik

    2012-01-01

    Endoreduplication is the process where a cell replicates its genome without mitosis and cytokinesis, often followed by cell differentiation. This alternative cell cycle results in various levels of endoploidy, reaching 4× or higher one haploid set of chromosomes. Endoreduplication is found in animals and is widespread in plants, where it plays a major role in cellular differentiation and plant development. Here, we show that variation in endoreduplication between Arabidopsis thaliana accessions Columbia-0 and Kashmir is controlled by two major quantitative trait loci, ENDO-1 and ENDO-2. A local candidate gene association analysis in a set of 87 accessions, combined with expression analysis, identified CYCD5;1 as the most likely candidate gene underlying ENDO-2, operating as a rate-determining factor of endoreduplication. In accordance, both the overexpression and silencing of CYCD5;1 were effective in changing DNA ploidy levels, confirming CYCD5;1 to be a previously undescribed quantitative trait gene underlying endoreduplication in Arabidopsis. PMID:22392991

  10. Combined linkage and association mapping reveals CYCD5;1 as a quantitative trait gene for endoreduplication in Arabidopsis.

    PubMed

    Sterken, Roel; Kiekens, Raphaël; Boruc, Joanna; Zhang, Fanghong; Vercauteren, Annelies; Vercauteren, Ilse; De Smet, Lien; Dhondt, Stijn; Inzé, Dirk; De Veylder, Lieven; Russinova, Eugenia; Vuylsteke, Marnik

    2012-03-20

    Endoreduplication is the process where a cell replicates its genome without mitosis and cytokinesis, often followed by cell differentiation. This alternative cell cycle results in various levels of endoploidy, reaching 4× or higher one haploid set of chromosomes. Endoreduplication is found in animals and is widespread in plants, where it plays a major role in cellular differentiation and plant development. Here, we show that variation in endoreduplication between Arabidopsis thaliana accessions Columbia-0 and Kashmir is controlled by two major quantitative trait loci, ENDO-1 and ENDO-2. A local candidate gene association analysis in a set of 87 accessions, combined with expression analysis, identified CYCD5;1 as the most likely candidate gene underlying ENDO-2, operating as a rate-determining factor of endoreduplication. In accordance, both the overexpression and silencing of CYCD5;1 were effective in changing DNA ploidy levels, confirming CYCD5;1 to be a previously undescribed quantitative trait gene underlying endoreduplication in Arabidopsis.

  11. Comparison of microarray and sage techniques in gene expression analysis of human glioblastoma.

    PubMed

    Kavsan, V M; Dmitrenko, V V; Shostak, K O; Bukreieva, T V; Vitak, N Y; Simirenko, O E; Malisheva, T A; Shamayev, M I; Rozumenko, V D; Zozulya, Y A

    2007-01-01

    To enhance glioblastoma (GB) marker discovery we compared gene expression in GB with human normal brain (NB) by accessing SAGE Genie web site and compared obtained results with published data. Nine GB and five NB SAGE-libraries were analyzed using the Digital Gene Expression Displayer (DGED), the results of DGED were tested by Northern blot analysis and RT-PCR of arbitrary selected genes. Review of available data from the articles on gene expression profiling by microarray-based hybridization showed as few as 35 overlapped genes with increased expression in GB. Some of them were identified in four articles, but most genes in three or even in two investigations. There was found also some differences between SAGE results of GB analysis. Digital Gene Expression Displayer approach revealed 676 genes differentially expressed in GB vs. NB with cut-off ratio: twofold change and P < or = 0.05. Differential expression of selectedgenes obtained by DGED was confirmed by Northern analysis and RT-PCR. Altogether, only 105 of 955 genes presented in published investigations were among the genes obtained by DGED. Comparison of the results obtained by microarrays and SAGE is very complicated because authors present only the most prominent differentially expressed genes. However, even available data give quite poor overlapping of genes revealed by microarrays. Some differences between results obtained by SAGE in different investigations can be explained by high dependence on the statistical methods used. As for now, the best solution to search for molecular tumor markers is to compare all available results and to select only those genes, which significant expression in tumor combined with very low expression in normal tissues was reproduced in several articles. 105 differentially expressed genes, common to both methods, can be included in the list of candidates for the molecular typing of GBs. Some genes, encoded cell surface or extra-cellular proteins may be useful for targeting

  12. Relationship between Expression of Chalcone Synthase Genes and Chromones in Artificial Agarwood induced by Formic Acid Stimulation Combined with Fusarium sp. A2 Inoculation.

    PubMed

    Chen, Xiaodong; Zhu, Xiaoling; Feng, Meirou; Zhong, Zhaojian; Zhou, Xin; Chen, Xiaoying; Ye, Wei; Zhang, Weimin; Gao, Xiaoxia

    2017-04-25

    Agarwood (gaharu) is a fragrant resin produced in the heartwood of resinous Gyrinops and Aquilaria species. Artificial agarwood samples were obtained from Aquilaria sinensis (Lour.) Gilg using formic acid (FA) stimulation combined with Fusarium sp. A2 inoculation. The relationship between the expression of chalcone synthase genes (CHS) and dynamic changes in chromone content was explored in resin-deposited parts of the trunks of A. sinensis. CHS gene expression levels were detected by qRT-PCR analysis. The chemical composition of agarwood obtained from the heartwood of A. sinensis before and within 1 year after induction was determined by GC-MS. After induction with FA stimulation combined with F. sp. A2 inoculation, the CHS1 gene showed relatively high expression, whereas the CHS2 gene showed low expression. The relative gene expression level of CHS1 peaked at 12 months, with a 153.1-fold increase, and the dominant period of the CHS2 gene expression was 10 months with a 14.13-fold increase. Moreover, chromones were not detected until after 2 months, and a large proportion of chromone compounds were detected after 4 months. Chromone content increased with time and peaked at 12 months. CHS1 gene expression was significantly correlated with 6-hydroxy-2-(2-phenylethyl)chromone accumulation, and CHS2 gene expression was significantly correlated with 5-hydroxy-6-methoxy-2-(2-phenylethyl)chromone accumulation. CHS gene expression was extremely sensitive to FA stimulation combined with F. sp. A2 inoculation and responded to late-onset injury. CHS genes expression also preceded the chromone accumulation. This work laid the foundation for studies on the mechanism by which genes regulate chromone biosynthesis pathways during the formation of agarwood resin in A. sinensis.

  13. Identification of human HK genes and gene expression regulation study in cancer from transcriptomics data analysis.

    PubMed

    Chen, Meili; Xiao, Jingfa; Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

    2013-01-01

    The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer.

  14. Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

    PubMed Central

    Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

    2013-01-01

    The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

  15. Comprehensive analysis of plant rapid alkalization factor (RALF) genes.

    PubMed

    Sharma, Arti; Hussain, Adil; Mun, Bong-Gyu; Imran, Qari Muhammad; Falak, Noreen; Lee, Sang-Uk; Kim, Jae Young; Hong, Jeum Kyu; Loake, Gary John; Ali, Asad; Yun, Byung-Wook

    2016-09-01

    Receptor mediated signal carriers play a critical role in the regulation of plant defense and development. Rapid alkalization factor (RALF) proteins potentially comprise important signaling components which may have a key role in plant biology. The RALF gene family contains large number of genes in several plant species, however, only a few RALF genes have been characterized to date. In this study, an extensive database search identified 39, 43, 34 and 18 RALF genes in Arabidopsis, rice, maize and soybean, respectively. These RALF genes were found to be highly conserved across the 4 plant species. A comprehensive analysis including the chromosomal location, gene structure, subcellular location, conserved motifs, protein structure, protein-ligand interaction and promoter analysis was performed. RALF genes from four plant species were divided into 7 groups based on phylogenetic analysis. In silico expression analysis of these genes, using microarray and EST data, revealed that these genes exhibit a variety of expression patterns. Furthermore, RALF genes showed distinct expression patterns of transcript accumulation in vivo following nitrosative and oxidative stresses in Arabidopsis. Predicted interaction between RALF and heme ligand also showed that RALF proteins may contribute towards transporting or scavenging oxygen moieties. This suggests a possible role for RALF genes during changes in cellular redox status. Collectively, our data provides a valuable resource to prime future research in the role of RALF genes in plant growth and development. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  16. A novel cancer vaccine strategy with combined IL-18 and HSV-TK gene therapy driven by the hTERT promoter in a murine colorectal cancer model.

    PubMed

    Higashi, Kosuke; Hazama, Shoichi; Araki, Atsuhiro; Yoshimura, Kiyoshi; Iizuka, Norio; Yoshino, Shigefumi; Noma, Takafumi; Oka, Masaaki

    2014-10-01

    A therapeutic vaccine against minimal residual cancer cells is needed for the treatment of patients with colorectal cancer. Several gene therapy studies have revealed that the combination of a suicide gene and cytokine gene might induce effective antitumor immunity. In this study, we constructed an interleukin (IL)-18 and herpes simplex virus-thymidine kinase (HSV-TK) expression vector driven by the human telomerase reverse transcriptase (hTERT) promoter to study the efficacy of combination gene therapy with IL-18 and the HSV-TK suicide gene. Low immunogenic colon 26 cells were used for transfection and inoculation into syngeneic BALB/c mice. Large established tumors of colon 26 transfectants expressing IL-18 and HSV-TK driven by the hTERT promoter were completely eradicated after GCV administration in syngeneic BALB/c mice. Immunohistochemical analysis at the tumor rejection sites revealed enormous infiltrations of CD8+ T lymphocytes as well as CD4+ T lymphocytes and CD11b+ monocytes. Moreover, established distant tumors were completely eradicated by vaccination with the IL-18 and HSV-TK transfectants in combination with GCV. These data suggest that the IL-18 and suicide gene therapy can elicit antitumor specific immunity. In conclusion, gene therapy with IL-18 and HSV-TK plasmid vector driven by the hTERT promoter may be useful for cancer vaccination.

  17. GeConT: gene context analysis.

    PubMed

    Ciria, R; Abreu-Goodger, C; Morett, E; Merino, E

    2004-09-22

    The fact that adjacent genes in bacteria are often functionally related is widely known. GeConT (Gene Context Tool) is a web interface designed to visualize genome context of a gene or a group of genes and their orthologs in all the completely sequenced genomes. The graphical information of GeConT can be used to analyze genome annotation, functional ortholog identification or to verify the genomic context congruence of any set of genes that share a common property. http://www.ibt.unam.mx/biocomputo/gecont.html

  18. Forest structure analysis combining laser scanning with digital airborne photogrammetry

    NASA Astrophysics Data System (ADS)

    Lissak, Candide; Onda, Yuichi; Kato, Hiroaki

    2017-04-01

    The interest of Light Detection and Ranging (LiDAR) for vegetation structure analysis has been demonstrated in several research context. Indeed, airborne or ground Lidar surveys can provide detailed three-dimensional data of the forest structure from understorey forest to the canopy. To characterize at different timescale the vegetation components in dense cedar forests we can combine several sources point clouds from Lidar survey and photogrammetry data. For our study, Terrestrial Laser Scanning (TLS-Leica ScanStation C10 processed with Cyclone software) have been lead in three forest areas (≈ 200m2 each zone) mainly composed of japanese cedar (Japonica cryptomeria), in the region of Fukushima (Japan). The study areas are characterized by various vegetation densities. For the 3 areas, Terrestrial laser scanning has been performed from several location points and several heights. Various floors shootings (ground, 4m, 6m and 18m high) were able with the use of a several meters high tower implanted to study the canopy evolution following the Fukushima Daiishi nuclear power plant accident. The combination of all scanners provides a very dense 3D point cloud of ground and canopy structure (average 300 000 000 points). For the Tochigi forest area, a first test of a low-cost Unmanned Aerial Vehicle (UAV) photogrammetry has been lead and calibrated by ground GPS measurements to determine the coordinates of points. TLS combined to UAV photogrammetry make it possible to obtain information on vertical and horizontal structure of the Tochigi forest. This combination of technologies will allow the forest structure mapping, morphometry analysis and the assessment of biomass volume evolution from multi-temporal point clouds. In our research, we used a low-cost UAV 3 Advanced (200 m2 cover, 1300 pictures...). Data processing were performed using PotoScan Pro software to obtain a very dense point clouds to combine to TLS data set. This low-cost UAV photogrammetry data has been

  19. Random forests-based differential analysis of gene sets for gene expression data.

    PubMed

    Hsueh, Huey-Miin; Zhou, Da-Wei; Tsai, Chen-An

    2013-04-10

    In DNA microarray studies, gene-set analysis (GSA) has become the focus of gene expression data analysis. GSA utilizes the gene expression profiles of functionally related gene sets in Gene Ontology (GO) categories or priori-defined biological classes to assess the significance of gene sets associated with clinical outcomes or phenotypes. Many statistical approaches have been proposed to determine whether such functionally related gene sets express differentially (enrichment and/or deletion) in variations of phenotypes. However, little attention has been given to the discriminatory power of gene sets and classification of patients. In this study, we propose a method of gene set analysis, in which gene sets are used to develop classifications of patients based on the Random Forest (RF) algorithm. The corresponding empirical p-value of an observed out-of-bag (OOB) error rate of the classifier is introduced to identify differentially expressed gene sets using an adequate resampling method. In addition, we discuss the impacts and correlations of genes within each gene set based on the measures of variable importance in the RF algorithm. Significant classifications are reported and visualized together with the underlying gene sets and their contribution to the phenotypes of interest. Numerical studies using both synthesized data and a series of publicly available gene expression data sets are conducted to evaluate the performance of the proposed methods. Compared with other hypothesis testing approaches, our proposed methods are reliable and successful in identifying enriched gene sets and in discovering the contributions of genes within a gene set. The classification results of identified gene sets can provide an valuable alternative to gene set testing to reveal the unknown, biologically relevant classes of samples or patients. In summary, our proposed method allows one to simultaneously assess the discriminatory ability of gene sets and the importance of genes for

  20. Self-Contained Statistical Analysis of Gene Sets

    PubMed Central

    Cannon, Judy L.; Ricoy, Ulises M.; Johnson, Christopher

    2016-01-01

    Microarrays are a powerful tool for studying differential gene expression. However, lists of many differentially expressed genes are often generated, and unraveling meaningful biological processes from the lists can be challenging. For this reason, investigators have sought to quantify the statistical probability of compiled gene sets rather than individual genes. The gene sets typically are organized around a biological theme or pathway. We compute correlations between different gene set tests and elect to use Fisher’s self-contained method for gene set analysis. We improve Fisher’s differential expression analysis of a gene set by limiting the p-value of an individual gene within the gene set to prevent a small percentage of genes from determining the statistical significance of the entire set. In addition, we also compute dependencies among genes within the set to determine which genes are statistically linked. The method is applied to T-ALL (T-lineage Acute Lymphoblastic Leukemia) to identify differentially expressed gene sets between T-ALL and normal patients and T-ALL and AML (Acute Myeloid Leukemia) patients. PMID:27711232

  1. Cross-Ontological Analytics: Combining Associative and Hierarchical Relations in the Gene Ontologies to Assess Gene Product Similarity

    SciTech Connect

    Posse, Christian; Sanfilippo, Antonio P.; Gopalan, Banu; Riensche, Roderick M.; Beagley, Nathaniel; Baddeley, Bob L.

    2006-05-28

    Gene and gene product similarity is a fundamental diagnostic measure in analyzing biological data and constructing predictive models for functional genomics. With the rising influence of the gene ontologies, two complementary approaches have emerged where the similarity between two genes/gene products is obtained by comparing gene ontology (GO) annotations associated with the gene/gene products. One approach captures GO-based similarity in terms of hierarchical relations within each gene ontology. The other approach identifies GO-based similarity in terms of associative relations across the three gene ontologies. We propose a novel methodology where the two approaches can be merged with ensuing benefits in coverage and accuracy.

  2. Combining SSH and cDNA microarrays for rapid identification of differentially expressed genes.

    PubMed

    Yang, G P; Ross, D T; Kuang, W W; Brown, P O; Weigel, R J

    1999-03-15

    Comparing patterns of gene expression in cell lines and tissues has important applications in a variety of biological systems. In this study we have examined whether the emerging technology of cDNA microarrays will allow a high throughput analysis of expression of cDNA clones generated by suppression subtractive hybridization (SSH). A set of cDNA clones including 332 SSH inserts amplified by PCR was arrayed using robotic printing. The cDNA arrays were hybridized with fluorescent labeled probes prepared from RNA from ER-positive (MCF7 and T47D) and ER-negative (MDA-MB-231 and HBL-100) breast cancer cell lines. Ten clones were identified that were over-expressed by at least a factor of five in the ER-positive cell lines. Northern blot analysis confirmed over-expression of these 10 cDNAs. Sequence analysis identified four of these clones as cytokeratin 19, GATA-3, CD24 and glutathione-S-transferase mu-3. Of the remaining six cDNA clones, four clones matched EST sequences from two different genes and two clones were novel sequences. Flow cytometry and immunofluorescence confirmed that CD24 protein was over-expressed in the ER-positive cell lines. We conclude that SSH and microarray technology can be successfully applied to identify differentially expressed genes. This approach allowed the identification of differentially expressed genes without the need to obtain previously cloned cDNAs.

  3. Individual and combined influence of ACE and ACTN3 genes on muscle phenotypes in Polish athletes.

    PubMed

    Orysiak, Joanna; Mazur-Różycka, Joanna; Busko, Krzysztof; Gajewski, Jan; Szczepanska, Beata; Malczewska-Lenczowska, Jadwiga

    2017-02-08

    The aim of this study was to examine the association between ACE and ACTN3 genes, independently or in combination, and muscle strength and power in male and female athletes. The study involved 398 young male (n=266) and female (n=132) athletes representing various sport disciplines (ice hockey, canoeing, swimming, volleyball). All were Caucasians. The following measurements were taken: height of jump and mechanical power in countermovement jump (CMJ) and spike jump (SPJ), and muscle strength of 10 muscle groups (flexors and extensors of the elbow, shoulder, hip, knee and trunk). The ID polymorphism of ACE and the R577X polymorphism of ACTN3 were typed using PCR (polymerase chain reaction) and PCR-RFLP (polymerase chain reaction - restriction fragment length polymorphism), respectively. The genotype distribution of the ACE and ACTN3 genes did not differ significantly between groups of athletes for either sex. There was no association between ACE and ACTN3 genotypes (alone or in combination) and sum of muscle strength, height of jump or mechanical power in both jump tests (CMJ and SPJ) for male and female athletes. These findings do not support an influential role of the ACE and ACTN3 genes in determining power/strength performance of elite athletes.

  4. Treatment of cancer using pulsed electric field in combination with chemotherapeutic agents or genes.

    PubMed

    Nishi, T; Dev, S B; Yoshizato, K; Kuratsu, J; Ushio, Y

    1997-03-01

    Electroporation is a standard laboratory technique originally developed for in vitro transfer of molecules into cells. It involves application of electrical pulses ranging from micro- to milliseconds that create transient pores in the cell membrane allowing intracellular access of exogenous molecules. This technique has been successfully applied to regress tumors in animal models by combining electroporation with chemotherapeutic agents--a process known as electrochemotherapy (ECT) which substantially enhance cytotoxicity of some antineoplastic agents. Recently ECT has moved into clinical arena and patients with cutaneous tumors and head and neck cancers have been treated very effectively with ECT. Parallel to ECT, a technique has also been developed which makes it possible to inject plasmid DNA and combine it with in vivo electroporation--electro--genetherapy (EGT)--to deliver in a highly efficient manner both marker and functional genes into target tissue and achieve gene expression. Thus, in vivo electroporation is contributing to the development of a new strategy for cancer treatment with both drugs and genes.

  5. A note on joint versus gene-specific mixed model analysis of microarray gene expression data.

    PubMed

    Hoeschele, Ina; Li, Hua

    2005-04-01

    Currently, linear mixed model analyses of expression microarray experiments are performed either in a gene-specific or global mode. The joint analysis provides more flexibility in terms of how parameters are fitted and estimated and tends to be more powerful than the gene-specific analysis. Here we show how to implement the gene-specific linear mixed model analysis as an exact algorithm for the joint linear mixed model analysis. The gene-specific algorithm is exact, when the mixed model equations can be partitioned into unrelated components: One for all global fixed and random effects and the others for the gene-specific fixed and random effects for each gene separately. This unrelatedness holds under three conditions: (1) any gene must have the same number of replicates or probes on all arrays, but these numbers can differ among genes; (2) the residual variance of the (transformed) expression data must be homogeneous or constant across genes (other variance components need not be homogeneous) and (3) the number of genes in the experiment is large. When these conditions are violated, the gene-specific algorithm is expected to be nearly exact.

  6. Method for combined biometric and chemical analysis of human fingerprints.

    PubMed

    Staymates, Jessica L; Orandi, Shahram; Staymates, Matthew E; Gillen, Greg

    This paper describes a method for combining direct chemical analysis of latent fingerprints with subsequent biometric analysis within a single sample. The method described here uses ion mobility spectrometry (IMS) as a chemical detection method for explosives and narcotics trace contamination. A collection swab coated with a high-temperature adhesive has been developed to lift latent fingerprints from various surfaces. The swab is then directly inserted into an IMS instrument for a quick chemical analysis. After the IMS analysis, the lifted print remains intact for subsequent biometric scanning and analysis using matching algorithms. Several samples of explosive-laden fingerprints were successfully lifted and the explosives detected with IMS. Following explosive detection, the lifted fingerprints remained of sufficient quality for positive match scores using a prepared gallery consisting of 60 fingerprints. Based on our results (n = 1200), there was no significant decrease in the quality of the lifted print post IMS analysis. In fact, for a small subset of lifted prints, the quality was improved after IMS analysis. The described method can be readily applied to domestic criminal investigations, transportation security, terrorist and bombing threats, and military in-theatre settings.

  7. A combination of transcriptome and methylation analyses reveals embryologically-relevant candidate genes in MRKH patients.

    PubMed

    Rall, Katharina; Barresi, Gianmaria; Walter, Michael; Poths, Sven; Haebig, Karina; Schaeferhoff, Karin; Schoenfisch, Birgitt; Riess, Olaf; Wallwiener, Diethelm; Bonin, Michael; Brucker, Sara

    2011-05-28

    The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is present in at least 1 out of 4,500 female live births and is the second most common cause for primary amenorrhea. It is characterized by vaginal and uterine aplasia in an XX individual with normal secondary characteristics. It has long been considered a sporadic anomaly, but familial clustering occurs. Several candidate genes have been studied although no single factor has yet been identified. Cases of discordant monozygotic twins suggest that the involvement of epigenetic factors is more likely. Differences in gene expression and methylation patterns of uterine tissue between eight MRKH patients and eight controls were identified using whole-genome microarray analyses. Results obtained by expression and methylation arrays were confirmed by qRT-PCR and pyrosequencing. We delineated 293 differentially expressed and 194 differentially methylated genes of which nine overlap in both groups. These nine genes are mainly embryologically relevant for the development of the female genital tract. Our study used, for the first time, a combined whole-genome expression and methylation approach to reveal the etiology of the MRKH syndrome. The findings suggest that either deficient estrogen receptors or the ectopic expression of certain HOXA genes might lead to abnormal development of the female reproductive tract. In utero exposure to endocrine disruptors or abnormally high maternal hormone levels might cause ectopic expression or anterior transformation of HOXA genes. It is, however, also possible that different factors influence the anti-Mullerian hormone promoter activity during embryological development causing regression of the Müllerian ducts. Thus, our data stimulate new research directions to decipher the pathogenic basis of MRKH syndrome.

  8. A combination of transcriptome and methylation analyses reveals embryologically-relevant candidate genes in MRKH patients

    PubMed Central

    2011-01-01

    Background The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is present in at least 1 out of 4,500 female live births and is the second most common cause for primary amenorrhea. It is characterized by vaginal and uterine aplasia in an XX individual with normal secondary characteristics. It has long been considered a sporadic anomaly, but familial clustering occurs. Several candidate genes have been studied although no single factor has yet been identified. Cases of discordant monozygotic twins suggest that the involvement of epigenetic factors is more likely. Methods Differences in gene expression and methylation patterns of uterine tissue between eight MRKH patients and eight controls were identified using whole-genome microarray analyses. Results obtained by expression and methylation arrays were confirmed by qRT-PCR and pyrosequencing. Results We delineated 293 differentially expressed and 194 differentially methylated genes of which nine overlap in both groups. These nine genes are mainly embryologically relevant for the development of the female genital tract. Conclusion Our study used, for the first time, a combined whole-genome expression and methylation approach to reveal the etiology of the MRKH syndrome. The findings suggest that either deficient estrogen receptors or the ectopic expression of certain HOXA genes might lead to abnormal development of the female reproductive tract. In utero exposure to endocrine disruptors or abnormally high maternal hormone levels might cause ectopic expression or anterior transformation of HOXA genes. It is, however, also possible that different factors influence the anti-Mullerian hormone promoter activity during embryological development causing regression of the Müllerian ducts. Thus, our data stimulate new research directions to decipher the pathogenic basis of MRKH syndrome. PMID:21619687

  9. Early Evolution of Vertebrate Mybs: An Integrative Perspective Combining Synteny, Phylogenetic, and Gene Expression Analyses.

    PubMed

    Campanini, Emeline B; Vandewege, Michael W; Pillai, Nisha E; Tay, Boon-Hui; Jones, Justin L; Venkatesh, Byrappa; Hoffmann, Federico G

    2015-10-15

    The genes in the Myb superfamily encode for three related transcription factors in most vertebrates, A-, B-, and c-Myb, with functionally distinct roles, whereas most invertebrates have a single Myb. B-Myb plays an essential role in cell division and cell cycle progression, c-Myb is involved in hematopoiesis, and A-Myb is involved in spermatogenesis and regulating expression of pachytene PIWI interacting RNAs, a class of small RNAs involved in posttranscriptional gene regulation and the maintenance of reproductive tissues. Comparisons between teleost fish and tetrapods suggest that the emergence and functional divergence of the Myb genes were linked to the two rounds of whole-genome duplication early in vertebrate evolution. We combined phylogenetic, synteny, structural, and gene expression analyses of the Myb paralogs from elephant shark and lampreys with data from 12 bony vertebrates to reconstruct the early evolution of vertebrate Mybs. Phylogenetic and synteny analyses suggest that the elephant shark and Japanese lamprey have copies of the A-, B-, and c-Myb genes, implying their origin could be traced back to the common ancestor of lampreys and gnathostomes. However, structural and gene expression analyses suggest that their functional roles diverged between gnathostomes and cyclostomes. In particular, we did not detect A-Myb expression in testis suggesting that the involvement of A-Myb in the pachytene PIWI interacting RNA pathway is probably a gnathostome-specific innovation. We speculate that the secondary loss of a central domain in lamprey A-Myb underlies the functional differences between the cyclostome and gnathostome A-Myb proteins.

  10. Efficacy of Gene Therapy for X-Linked Severe Combined Immunodeficiency

    PubMed Central

    Hacein-Bey-Abina, Salima; Hauer, Julia; Lim, Annick; Picard, Capucine; Wang, Gary P.; Berry, Charles C.; Martinache, Chantal; Rieux-Laucat, Frédéric; Latour, Sylvain; Belohradsky, Bernd H.; Leiva, Lily; Sorensen, Ricardo; Debré, Marianne; Casanova, Jean Laurent; Blanche, Stephane; Durandy, Anne; Bushman, Frederic D.; Fischer, Alain; Cavazzana-Calvo, Marina

    2010-01-01

    BACKGROUND The outcomes of gene therapy to correct congenital immunodeficiencies are unknown. We reviewed long-term outcomes after gene therapy in nine patients with X-linked severe combined immunodeficiency (SCID-X1), which is characterized by the absence of the cytokine receptor common γ chain. METHODS The nine patients, who lacked an HLA-identical donor, underwent ex vivo retrovirus-mediated transfer of γ chain to autologous CD34+ bone marrow cells between 1999 and 2002. We assessed clinical events and immune function on long-term follow-up. RESULTS Eight patients were alive after a median follow-up period of 9 years (range, 8 to 11). Gene therapy was initially successful at correcting immune dysfunction in eight of the nine patients. However, acute leukemia developed in four patients, and one died. Transduced T cells were detected for up to 10.7 years after gene therapy. Seven patients, including the three survivors of leukemia, had sustained immune reconstitution; three patients required immunoglobulin-replacement therapy. Sustained thymopoiesis was established by the persistent presence of naive T cells, even after chemotherapy in three patients. The T-cell–receptor repertoire was diverse in all patients. Transduced B cells were not detected. Correction of the immunodeficiency improved the patients’ health. CONCLUSIONS After nearly 10 years of follow-up, gene therapy was shown to have corrected the immunodeficiency associated with SCID-X1. Gene therapy may be an option for patients who do not have an HLA-identical donor for hematopoietic stem-cell transplantation and for whom the risks are deemed acceptable. This treatment is associated with a risk of acute leukemia. (Funded by INSERM and others.) PMID:20660403

  11. Evolutionary Analysis of Sequence Divergence and Diversity of Duplicate Genes in Aspergillus fumigatus

    PubMed Central

    Yang, Ence; Hulse, Amanda M.; Cai, James J.

    2012-01-01

    Gene duplication as a major source of novel genetic material plays an important role in evolution. In this study, we focus on duplicate genes in Aspergillus fumigatus, a ubiquitous filamentous fungus causing life-threatening human infections. We characterize the extent and evolutionary patterns of the duplicate genes in the genome of A. fumigatus. Our results show that A. fumigatus contains a large amount of duplicate genes with pronounced sequence divergence between two copies, and approximately 10% of them diverge asymmetrically, i.e. two copies of a duplicate gene pair diverge at significantly different rates. We use a Bayesian approach of the McDonald-Kreitman test to infer distributions of selective coefficients γ(=2Nes) and find that (1) the values of γ for two copies of duplicate genes co-vary positively and (2) the average γ for the two copies differs between genes from different gene families. This analysis highlights the usefulness of combining divergence and diversity data in studying the evolution of duplicate genes. Taken together, our results provide further support and refinement to the theories of gene duplication. Through characterizing the duplicate genes in the genome of A. fumigatus, we establish a computational framework, including parameter settings and methods, for comparative study of genetic redundancy and gene duplication between different fungal species. PMID:23225993

  12. Phylogeny of Drosophilinae (Diptera: Drosophilidae), with comments on combined analysis and character support.

    PubMed

    Remsen, James; O'Grady, Patrick

    2002-08-01

    Drosophilidae (Diptera) is a diverse, cosmopolitan family of flies. Here, we present a combined analysis phylogeny of Drosophilinae, one of the two subfamilies of Drosophilidae, based on data from six different data partitions, including both molecular and morphological characters. Although our data show support for the monophyly of the Hawaiian Drosophilidae, and the subgenus Sophophora, neither the genus Drosophila nor the subgenus Drosophila is monophyletic. Partitioned Bremer support (PBS) indicates that morphological data taken from Grimaldi's monograph (Grimaldi, 1990a), as well as sequences from the mitochondrial (mt) 16S rDNA and the nuclear Adh gene, lend much support to our tree's topology. This is particularly interesting in the case of Grimaldi's data, since his published hypothesis conflicts with ours in significant ways. Our combined analysis cladogram phylogeny reflects the catch-all designation that the name Drosophila has become, in that the cladogram does not support the monophyly of either the genus or subgenus Drosophila.

  13. Combined segregation and linkage analysis of Graves disease with a thyroid autoantibody diathesis.

    PubMed Central

    Shields, D. C.; Ratanachaiyavong, S.; McGregor, A. M.; Collins, A.; Morton, N. E.

    1994-01-01

    Combined segregation and linkage analysis is a powerful technique for modeling linkage to diseases whose etiology is more complex than the effect of a well-described single genetic locus and for investigating the influence of single genes on various aspects of the disease phenotype. Graves disease is familial and is associated with human leukocyte antigen (HLA) allele DR3. Probands with Graves disease, as well as close relatives, have raised levels of thyroid autoantibodies. This phenotypic information additional to affection status may be considered by the computer program COMDS for combined segregation and linkage analysis, when normals are classified into diathesis classes of increasing thyroid autoantibody titer. The ordinal model considers the cumulative odds of lying in successive classes, and a single additional parameter is introduced for each gene modeled. Distributional assumptions are avoided by providing estimates of the population frequencies of each class. Evidence for linkage was increased by considering the thyroid autoantibody diathesis and by testing two-locus models. The analysis revealed evidence for linkage to HLA-DR when the strong coupling of the linked locus to allele DR3 was considered (lod score of 6.6). Linkage analysis of the residual variation revealed no evidence of linkage to Gm, but a suggestion of linkage to Km. PMID:8079993

  14. Combined segregation and linkage analysis of Graves disease with a thyroid autoantibody diathesis

    SciTech Connect

    Shields, D.C.; Ratanachaiyavong, S.; McGregor, A.M.; Collins, A.; Morton, N.E.

    1994-09-01

    Combined segregation and linkage analysis is a powerful technique for modeling linkage to diseases whose etiology is more complex than the effect of a well-described single genetic locus and for investigating the influence of single genes on various aspects of the disease phenotype. Graves disease is familial and is associated with human leukocyte antigen (HLA) allele DR3. Probands with Graves disease, as well as close relatives, have raised levels of thyroid autoantibodies. This phenotypic information additional to affection status may be considered by the computer program COMDS for combined segregation and linkage analysis, when normals are classified into diathesis classes of increasing thyroid autoantibody titer. The ordinal model considers the cumulative odds of lying in successive classes, and a single additional parameter is introduced for each gene modeled. Distributional assumptions are avoided by providing estimates of the population frequencies of each class. Evidence for linkage was increased by considering the thyroid autoantibody diathesis and by testing two-locus models. The analysis revealed evidence for linkage to HLA-DR when the strong coupling of the linked locus to allele DR3 was considered (lod score of 6.6). Linkage analysis of the residual variation revealed no evidence of linkage to Gm, but a suggestion of linkage to Km. 32 refs., 10 tabs.

  15. Integrated analysis of gene expression by association rules discovery

    PubMed Central

    Carmona-Saez, Pedro; Chagoyen, Monica; Rodriguez, Andres; Trelles, Oswaldo; Carazo, Jose M; Pascual-Montano, Alberto

    2006-01-01

    Background Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process. Results In this study we present a method for the integrative analysis of microarray data based on the Association Rules Discovery data mining technique. The approach integrates gene annotations and expression data to discover intrinsic associations among both data sources based on co-occurrence patterns. We applied the proposed methodology to the analysis of gene expression datasets in which genes were annotated with metabolic pathways, transcriptional regulators and Gene Ontology categories. Automatically extracted associations revealed significant relationships among these gene attributes and expression patterns, where many of them are clearly supported by recently reported work. Conclusion The integration of external biological information and gene expression data can provide insights about the biological processes associated to gene expression programs. In this paper we show that the proposed methodology is able to integrate multiple gene annotations and expression data in the same analytic framework and extract meaningful associations among heterogeneous sources of data. An implementation of the method is included in the Engene software package. PMID:16464256

  16. Phylogenetic analysis of cubilin (CUBN) gene

    PubMed Central

    Shaik, Abjal Pasha; Alsaeed, Abbas H; Kiranmayee, S; Bammidi, VK; Sultana, Asma

    2013-01-01

    Cubilin, (CUBN; also known as intrinsic factor-cobalamin receptor [Homo sapiens Entrez Pubmed ref NM_001081.3; NG_008967.1; GI: 119606627]), located in the epithelium of intestine and kidney acts as a receptor for intrinsic factor – vitamin B12 complexes. Mutations in CUBN may play a role in autosomal recessive megaloblastic anemia. The current study investigated the possible role of CUBN in evolution using phylogenetic testing. A total of 588 BLAST hits were found for the cubilin query sequence and these hits showed putative conserved domain, CUB superfamily (as on 27th Nov 2012). A first-pass phylogenetic tree was constructed to identify the taxa which most often contained the CUBN sequences. Following this, we narrowed down the search by manually deleting sequences which were not CUBN. A repeat phylogenetic analysis of 25 taxa was performed using PhyML, RAxML and TreeDyn softwares to confirm that CUBN is a conserved protein emphasizing its importance as an extracellular domain and being present in proteins mostly known to be involved in development in many chordate taxa but not found in prokaryotes, plants and yeast.. No horizontal gene transfers have been found between different taxa. PMID:23390341

  17. Phylogenetic analysis of cubilin (CUBN) gene.

    PubMed

    Shaik, Abjal Pasha; Alsaeed, Abbas H; Kiranmayee, S; Bammidi, Vk; Sultana, Asma

    2013-01-01

    Cubilin, (CUBN; also known as intrinsic factor-cobalamin receptor [Homo sapiens Entrez Pubmed ref NM_001081.3; NG_008967.1; GI: 119606627]), located in the epithelium of intestine and kidney acts as a receptor for intrinsic factor - vitamin B12 complexes. Mutations in CUBN may play a role in autosomal recessive megaloblastic anemia. The current study investigated the possible role of CUBN in evolution using phylogenetic testing. A total of 588 BLAST hits were found for the cubilin query sequence and these hits showed putative conserved domain, CUB superfamily (as on 27(th) Nov 2012). A first-pass phylogenetic tree was constructed to identify the taxa which most often contained the CUBN sequences. Following this, we narrowed down the search by manually deleting sequences which were not CUBN. A repeat phylogenetic analysis of 25 taxa was performed using PhyML, RAxML and TreeDyn softwares to confirm that CUBN is a conserved protein emphasizing its importance as an extracellular domain and being present in proteins mostly known to be involved in development in many chordate taxa but not found in prokaryotes, plants and yeast.. No horizontal gene transfers have been found between different taxa.

  18. Combining ray-trace and diffraction analysis: A design example

    NASA Technical Reports Server (NTRS)

    Milster, Tom D.; Treptau, Jeffrey P.

    1992-01-01

    An example is presented of using a combined ray trace and diffraction modeling code to simulate effects of objective-lens tilt in an optical data storage device. In some cases, neither ray-trace analysis nor diffraction analysis can give an adequate description of an optical system. The designer that is faced with the problem of analyzing such a system is forced to use a ray-trace program to determine aberrations in the exit pupil and then introduce aberration coefficients into a diffraction model that simulate the propagation. This approach was found rather awkward, especially if complicated aberrations are present. Our approach is to integrate a diffraction analysis and a ray-trace description of an optical path into one program. Our design is taken from a data storage application, where we must analyze the effects of objective-lens tilt.

  19. Sand Compositional Analysis Using a Combined Geological and Spectroscopic Approach

    NASA Astrophysics Data System (ADS)

    Smith, Molly Elizabeth

    Many minerals, such as calcite and magnetite, show diagnostic overtone and combination bands in the 350-2500 nm window. Sand, though an important unconsolidated material with great abundance on the Earth's surface, is largely overlooked in spectroscopic studies. Over 100 sand samples were analyzed through traditional microscopic methods and compared to spectral reflectance collected via an ASD Spectroradiometer. Multiple methods were chosen to compare spectroscopic data to sand composition and grain size: 1) existing spectral indices, 2) continuum removal, 3) derivative analysis, and 4) correlation analysis. Particular focus was given to carbonate content. Results from derivative and correlation analysis showed strong correlations in the 2180-2240 nm and 2300-2360 nm windows to carbonate content. Proposed here is the Normalized Difference Carbonate Sand Index (NDCSI), which showed Pearson correlations of r=-0.78 for light-colored samples and r=-0.77 for all samples used. This index is viable for use with carbonate-rich sands.

  20. [Oro-maxillofacial bone tissue engineering combining biomaterials, stem cells, and gene therapy].

    PubMed

    Myon, L; Ferri, J; Chai, F; Blanchemain, N; Raoul, G

    2011-09-01

    Improvements have been made in regenerative medicine, due to the development of tissue engineering and cellular therapy. Bone regeneration is an ambitious project, leading to many applications involving skull, maxillofacial, and orthopaedic surgery. Scaffolds, stem cells, and signals support bone tissue engineering. The scaffold physical and chemical properties promote cell invasion, guide their differentiation, and enable signal transmission. Scaffold may be inorganic or organic. Their conception was improved by the use of new techniques: self-assembled nanofibres, electrospinning, solution-phase separation, micropatterned hydrogels, bioprinting, and rapid prototyping. Cellular biology processes allow us to choose between embryonic stem cells or adult stem cells for regenerative medicine. Finally, communication between cells and their environment is essential; they use various signals to do so. The study of signals and their transmission led to the discovery and the use of Bone Morphogenetic Protein (BMP). The development of cellular therapy led to the emergence of a specific field: gene therapy. It relies on viral vectors, which include: retroviruses, adenoviruses and adeno-associated vectors (AAV). Non-viral vectors include plasmids and lipoplex. Some BMP genes have successfully been transfected. The ability to control transfected cells and the capacity to combine and transfect many genes involved in osseous healing will improve gene therapy. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

  1. Gene Therapy for X-Linked Severe Combined Immunodeficiency: Where Do We Stand?

    PubMed Central

    Cavazzana, Marina; Six, Emmanuelle; Lagresle-Peyrou, Chantal; André-Schmutz, Isabelle; Hacein-Bey-Abina, Salima

    2016-01-01

    More than 20 years ago, X-linked severe combined immunodeficiency (SCID-X1) appeared to be the best condition to test the feasibility of hematopoietic stem cell gene therapy. The seminal SCID-X1 clinical studies, based on first-generation gammaretroviral vectors, demonstrated good long-term immune reconstitution in most treated patients despite the occurrence of vector-related leukemia in a few of them. This gene therapy has successfully enabled correction of the T cell defect. Natural killer and B cell defects were only partially restored, most likely due to the absence of a conditioning regimen. The success of these pioneering trials paved the way for the extension of gene-based treatment to many other diseases of the hematopoietic system, but the unfortunate serious adverse events led to extensive investigations to define the retrovirus integration profiles. This review puts into perspective the clinical experience of gene therapy for SCID-X1, with the development and implementation of new generations of safer vectors such as self-inactivating gammaretroviral or lentiviral vectors as well as major advances in integrome knowledge. PMID:26790362

  2. Combined congenital dysfibrinogenemia and factor VII deficiency from mutations in the FGB and F7 genes.

    PubMed

    Woo, Hye In; Park, In-Ae; Lee, Ki-O; Kim, Sun-Hee; Kim, Hee-Jin

    2012-07-01

    Dysfibrinogenemia and factor VII (FVII) deficiency are rare congenital coagulopathies. In this report, the authors describe a man with both defects confirmed by molecular genetic tests. The patient was a 51-year-old man referred for prolonged prothrombin time (PT) that had been accidentally detected on preoperative screening. He had no history of bleeding tendency even on occasions of surgery. Routine coagulation studies revealed prolonged PT (1.53 INR) and thrombin time (42.2 s), and decreased fibrinogen level (57 mg/dl) and FVII activity (44%). Direct sequencing analyses were performed on FGA, FGB, and FGG genes to confirm dysfibrinogenemia and on the F7 gene to confirm FVII deficiency. As a result, the patient was shown to be heterozygous for a point mutation in exon 8 of the FGB gene (c.1475A > G, p.*492Trpext*12; Fibrinogen Magdeburg II) and for a missense mutation in exon 6 of the F7 gene (c.466G  > A, p.Gly156Ser). To our knowledge, this is the first report on a case of combined dysfibrinogenemia and FVII deficiency confirmed by molecular genetic tests.

  3. Comparative analysis of essential genes in prokaryotic genomic islands

    PubMed Central

    Zhang, Xi; Peng, Chong; Zhang, Ge; Gao, Feng

    2015-01-01

    Essential genes are thought to encode proteins that carry out the basic functions to sustain a cellular life, and genomic islands (GIs) usually contain clusters of horizontally transferred genes. It has been assumed that essential genes are not likely to be located in GIs, but systematical analysis of essential genes in GIs has not been explored before. Here, we have analyzed the essential genes in 28 prokaryotes by statistical method and reached a conclusion that essential genes in GIs are significantly fewer than those outside GIs. The function of 362 essential genes found in GIs has been explored further by BLAST against the Virulence Factor Database (VFDB) and the phage/prophage sequence database of PHAge Search Tool (PHAST). Consequently, 64 and 60 eligible essential genes are found to share the sequence similarity with the virulence factors and phage/prophages-related genes, respectively. Meanwhile, we find several toxin-related proteins and repressors encoded by these essential genes in GIs. The comparative analysis of essential genes in genomic islands will not only shed new light on the development of the prediction algorithm of essential genes, but also give a clue to detect the functionality of essential genes in genomic islands. PMID:26223387

  4. Transcriptome Analysis of Sunflower Genotypes with Contrasting Oxidative Stress Tolerance Reveals Individual- and Combined- Biotic and Abiotic Stress Tolerance Mechanisms.

    PubMed

    Ramu, Vemanna S; Paramanantham, Anjugam; Ramegowda, Venkategowda; Mohan-Raju, Basavaiah; Udayakumar, Makarla; Senthil-Kumar, Muthappa

    2016-01-01

    In nature plants are often simultaneously challenged by different biotic and abiotic stresses. Although the mechanisms underlying plant responses against single stress have been studied considerably, plant tolerance mechanisms under combined stress is not understood. Also, the mechanism used to combat independently and sequentially occurring many number of biotic and abiotic stresses has also not systematically studied. From this context, in this study, we attempted to explore the shared response of sunflower plants to many independent stresses by using meta-analysis of publically available transcriptome data and transcript profiling by quantitative PCR. Further, we have also analyzed the possible role of the genes so identified in contributing to combined stress tolerance. Meta-analysis of transcriptomic data from many abiotic and biotic stresses indicated the common representation of oxidative stress responsive genes. Further, menadione-mediated oxidative stress in sunflower seedlings showed similar pattern of changes in the oxidative stress related genes. Based on this a large scale screening of 55 sunflower genotypes was performed under menadione stress and those contrasting in oxidative stress tolerance were identified. Further to confirm the role of genes identified in individual and combined stress tolerance the contrasting genotypes were individually and simultaneously challenged with few abiotic and biotic stresses. The tolerant hybrid showed reduced levels of stress damage both under combined stress and few independent stresses. Transcript profiling of the genes identified from meta-analysis in the tolerant hybrid also indicated that the selected genes were up-regulated under individual and combined stresses. Our results indicate that menadione-based screening can identify genotypes not only tolerant to multiple number of individual biotic and abiotic stresses, but also the combined stresses.

  5. Transcriptome Analysis of Sunflower Genotypes with Contrasting Oxidative Stress Tolerance Reveals Individual- and Combined- Biotic and Abiotic Stress Tolerance Mechanisms

    PubMed Central

    Ramu, Vemanna S.; Paramanantham, Anjugam; Ramegowda, Venkategowda; Mohan-Raju, Basavaiah; Udayakumar, Makarla

    2016-01-01

    In nature plants are often simultaneously challenged by different biotic and abiotic stresses. Although the mechanisms underlying plant responses against single stress have been studied considerably, plant tolerance mechanisms under combined stress is not understood. Also, the mechanism used to combat independently and sequentially occurring many number of biotic and abiotic stresses has also not systematically studied. From this context, in this study, we attempted to explore the shared response of sunflower plants to many independent stresses by using meta-analysis of publically available transcriptome data and transcript profiling by quantitative PCR. Further, we have also analyzed the possible role of the genes so identified in contributing to combined stress tolerance. Meta-analysis of transcriptomic data from many abiotic and biotic stresses indicated the common representation of oxidative stress responsive genes. Further, menadione-mediated oxidative stress in sunflower seedlings showed similar pattern of changes in the oxidative stress related genes. Based on this a large scale screening of 55 sunflower genotypes was performed under menadione stress and those contrasting in oxidative stress tolerance were identified. Further to confirm the role of genes identified in individual and combined stress tolerance the contrasting genotypes were individually and simultaneously challenged with few abiotic and biotic stresses. The tolerant hybrid showed reduced levels of stress damage both under combined stress and few independent stresses. Transcript profiling of the genes identified from meta-analysis in the tolerant hybrid also indicated that the selected genes were up-regulated under individual and combined stresses. Our results indicate that menadione-based screening can identify genotypes not only tolerant to multiple number of individual biotic and abiotic stresses, but also the combined stresses. PMID:27314499

  6. Integrated Analysis of SNP, CNV and Gene Expression Data in Genetic Association Studies.

    PubMed

    Momtaz, Rana; Ghanem, Nagia M; El-Makky, Nagwa M; Ismail, Mohamed A

    2017-07-07

    Integrative approaches that combine multiple forms of data can more accurately capture CGEway associations and so provide a comprehensive understanding of the molecular mechanisms that cause complex diseases. Association analyses based on SNP genotypes, CNV genotypes, and gene expression profiles are the three most common paradigms used for gene set/ CGEway enrichment analyses. Many work has been done to leverage information from two types of data from these three paradigms. However, to the best of our knowledge, there is no work done before to integrate the three paradigms all together. In this paper, we present an integrated analysis that combine SNP, CNV, and gene expression data to generate a single gene list. We present different methods to compare this gene list with the other three possible lists that result from the combinations of the following pairs of data: SNP genotype with gene expression, CNV genotype with gene expression, and SNP genotype with CNV genotype. The comparison is done using three different cancer datasets and two different methods of comparison. Our results show that integrating SNP, CNV, and gene expression data give better association results than integrating any pair of three data. This article is protected by copyright. All rights reserved.

  7. Meta-analysis of differentially expressed genes in ankylosing spondylitis.

    PubMed

    Lee, Y H; Song, G G

    2015-05-18

    The purpose of this study was to identify differentially expressed (DE) genes and biological processes associated with changes in gene expression in ankylosing spondylitis (AS). We performed a meta-analysis using the integrative meta-analysis of expression data program on publicly available microarray AS Gene Expression Omnibus (GEO) datasets. We performed Gene Ontology (GO) enrichment analyses and pathway analysis using the Kyoto Encyclopedia of Genes and Genomes. Four GEO datasets, including 31 patients with AS and 39 controls, were available for the meta-analysis. We identified 65 genes across the studies that were consistently DE in patients with AS vs controls (23 upregulated and 42 downregulated). The upregulated gene with the largest effect size (ES; -1.2628, P = 0.020951) was integral membrane protein 2A (ITM2A), which is expressed by CD4+ T cells and plays a role in activation of T cells. The downregulated gene with the largest ES (1.2299, P = 0.040075) was mitochondrial ribosomal protein S11 (MRPS11). The most significant GO enrichment was in the respiratory electron transport chain category (P = 1.67 x 10-9). Therefore, our meta-analysis identified genes that were consistently DE as well as biological pathways associated with gene expression changes in AS.

  8. Functional Module Analysis for Gene Coexpression Networks with Network Integration

    PubMed Central

    Zhang, Shuqin; Zhao, Hongyu

    2015-01-01

    Network has been a general tool for studying the complex interactions between different genes, proteins and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with 3 complete subgraphs, and 11 modules with 2 complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally. PMID:26451826

  9. Molecular characterization and combined genotype association study of bovine cluster of differentiation 14 gene with clinical mastitis in crossbred dairy cattle.

    PubMed

    Selvan, A Sakthivel; Gupta, I D; Verma, A; Chaudhari, M V; Magotra, A

    2016-07-01

    The present study was undertaken with the objectives to characterize and to analyze combined genotypes of cluster of differentiation 14 (CD14) gene to explore its association with clinical mastitis in Karan Fries (KF) cows maintained in the National Dairy Research Institute herd, Karnal. Genomic DNA was extracted using blood of randomly selected 94 KF lactating cattle by phenol-chloroform method. After checking its quality and quantity, polymerase chain reaction (PCR) was carried out using six sets of reported gene-specific primers to amplify complete KF CD14 gene. The forward and reverse sequences for each PCR fragments were assembled to form complete sequence for the respective region of KF CD14 gene. The multiple sequence alignments of the edited sequence with the corresponding reference with reported Bos taurus sequence (EU148610.1) were performed with ClustalW software to identify single nucleotide polymorphisms (SNPs). Basic Local Alignment Search Tool analysis was performed to compare the sequence identity of KF CD14 gene with other species. The restriction fragment length polymorphism (RFLP) analysis was carried out in all KF cows using Helicobacter pylori 188I (Hpy188I) (contig 2) and Haemophilus influenzae I (HinfI) (contig 4) restriction enzyme (RE). Cows were assigned genotypes obtained by PCR-RFLP analysis, and association study was done using Chi-square (χ (2)) test. The genotypes of both contigs (loci) number 2 and 4 were combined with respect to each animal to construct combined genotype patterns. Two types of sequences of KF were obtained: One with 2630 bp having one insertion at 616 nucleotide (nt) position and one deletion at 1117 nt position, and the another sequence was of 2629 bp having only one deletion at 615 nt position. ClustalW, multiple alignments of KF CD14 gene sequence with B. taurus cattle sequence (EU148610.1), revealed 24 nt changes (SNPs). Cows were also screened using PCR-RFLP with Hpy188I (contig 2) and HinfI (contig 4) RE

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

    PubMed

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

    2017-08-01

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

  11. An Application of Sequential Meta-Analysis to Gene Expression Studies.

    PubMed

    Novianti, Putri W; van der Tweel, Ingeborg; Jong, Victor L; Roes, Kit Cb; Eijkemans, Marinus Jc

    2015-01-01

    Most of the discoveries from gene expression data are driven by a study claiming an optimal subset of genes that play a key role in a specific disease. Meta-analysis of the available datasets can help in getting concordant results so that a real-life application may be more successful. Sequential meta-analysis (SMA) is an approach for combining studies in chronological order while preserving the type I error and pre-specifying the statistical power to detect a given effect size. We focus on the application of SMA to find gene expression signatures across experiments in acute myeloid leukemia. SMA of seven raw datasets is used to evaluate whether the accumulated samples show enough evidence or more experiments should be initiated. We found 313 differentially expressed genes, based on the cumulative information of the experiments. SMA offers an alternative to existing methods in generating a gene list by evaluating the adequacy of the cumulative information.

  12. An Application of Sequential Meta-Analysis to Gene Expression Studies

    PubMed Central

    Novianti, Putri W; van der Tweel, Ingeborg; Jong, Victor L; Roes, Kit CB; Eijkemans, Marinus JC

    2015-01-01

    Most of the discoveries from gene expression data are driven by a study claiming an optimal subset of genes that play a key role in a specific disease. Meta-analysis of the available datasets can help in getting concordant results so that a real-life application may be more successful. Sequential meta-analysis (SMA) is an approach for combining studies in chronological order while preserving the type I error and pre-specifying the statistical power to detect a given effect size. We focus on the application of SMA to find gene expression signatures across experiments in acute myeloid leukemia. SMA of seven raw datasets is used to evaluate whether the accumulated samples show enough evidence or more experiments should be initiated. We found 313 differentially expressed genes, based on the cumulative information of the experiments. SMA offers an alternative to existing methods in generating a gene list by evaluating the adequacy of the cumulative information. PMID:26401096

  13. Turning publicly available gene expression data into discoveries using gene set context analysis.

    PubMed

    Ji, Zhicheng; Vokes, Steven A; Dang, Chi V; Ji, Hongkai

    2016-01-08

    Gene Set Context Analysis (GSCA) is an open source software package to help researchers use massive amounts of publicly available gene expression data (PED) to make discoveries. Users can interactively visualize and explore gene and gene set activities in 25,000+ consistently normalized human and mouse gene expression samples representing diverse biological contexts (e.g. different cells, tissues and disease types, etc.). By providing one or multiple genes or gene sets as input and specifying a gene set activity pattern of interest, users can query the expression compendium to systematically identify biological contexts associated with the specified gene set activity pattern. In this way, researchers with new gene sets from their own experiments may discover previously unknown contexts of gene set functions and hence increase the value of their experiments. GSCA has a graphical user interface (GUI). The GUI makes the analysis convenient and customizable. Analysis results can be conveniently exported as publication quality figures and tables. GSCA is available at https://github.com/zji90/GSCA. This software significantly lowers the bar for biomedical investigators to use PED in their daily research for generating and screening hypotheses, which was previously difficult because of the complexity, heterogeneity and size of the data.

  14. Discovery of putative capsaicin biosynthetic genes by RNA-Seq and digital gene expression analysis of pepper.

    PubMed

    Zhang, Zi-Xin; Zhao, Shu-Niu; Liu, Gao-Feng; Huang, Zu-Mei; Cao, Zhen-Mu; Cheng, Shan-Han; Lin, Shi-Sen

    2016-10-19

    The Indian pepper 'Guijiangwang' (Capsicum frutescens L.), one of the world's hottest chili peppers, is rich in capsaicinoids. The accumulation of the alkaloid capsaicin and its analogs in the epidermal cells of the placenta contribute to the pungency of Capsicum fruits. To identify putative genes involved in capsaicin biosynthesis, RNA-Seq was used to analyze the pepper's expression profiles over five developmental stages. Five cDNA libraries were constructed from the total RNA of placental tissue and sequenced using an Illumina HiSeq 2000. More than 19 million clean reads were obtained from each library, and greater than 50% of the reads were assignable to reference genes. Digital gene expression (DGE) profile analysis using Solexa sequencing was performed at five fruit developmental stages and resulted in the identification of 135 genes of known function; their expression patterns were compared to the capsaicin accumulation pattern. Ten genes of known function were identified as most likely to be involved in regulating capsaicin synthesis. Additionally, 20 new candidate genes were identified related to capsaicin synthesis. We use a combination of RNA-Seq and DGE analyses to contribute to the understanding of the biosynthetic regulatory mechanism(s) of secondary metabolites in a nonmodel plant and to identify candidate enzyme-encoding genes.

  15. Classification of Genes: Standardized Clinical Validity Assessment of Gene-Disease Associations Aids Diagnostic Exome Analysis and Reclassifications.

    PubMed

    Smith, Erica D; Radtke, Kelly; Rossi, Mari; Shinde, Deepali N; Darabi, Sourat; El-Khechen, Dima; Powis, Zöe; Helbig, Katherine; Waller, Kendra; Grange, Dorothy K; Tang, Sha; Farwell Hagman, Kelly D

    2017-05-01

    Ascertaining a diagnosis through exome sequencing can provide potential benefits to patients, insurance companies, and the healthcare system. Yet, as diagnostic sequencing is increasingly employed, vast amounts of human genetic data are produced that need careful curation. We discuss methods for accurately assessing the clinical validity of gene-disease relationships to interpret new research findings in a clinical context and increase the diagnostic rate. The specifics of a gene-disease scoring system adapted for use in a clinical laboratory are described. In turn, clinical validity scoring of gene-disease relationships can inform exome reporting for the identification of new or the upgrade of previous, clinically relevant gene findings. Our retrospective analysis of all reclassification reports from the first 4 years of diagnostic exome sequencing showed that 78% were due to new gene-disease discoveries published in the literature. Among all exome positive/likely positive findings in characterized genes, 32% were in genetic etiologies that were discovered after 2010. Our data underscore the importance and benefits of active and up-to-date curation of a gene-disease database combined with critical clinical validity scoring and proactive reanalysis in the clinical genomics era. © 2017 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

  16. Discovery of putative capsaicin biosynthetic genes by RNA-Seq and digital gene expression analysis of pepper

    PubMed Central

    Zhang, Zi-Xin; Zhao, Shu-Niu; Liu, Gao-Feng; Huang, Zu-Mei; Cao, Zhen-Mu; Cheng, Shan-Han; Lin, Shi-Sen

    2016-01-01

    The Indian pepper ‘Guijiangwang’ (Capsicum frutescens L.), one of the world’s hottest chili peppers, is rich in capsaicinoids. The accumulation of the alkaloid capsaicin and its analogs in the epidermal cells of the placenta contribute to the pungency of Capsicum fruits. To identify putative genes involved in capsaicin biosynthesis, RNA-Seq was used to analyze the pepper’s expression profiles over five developmental stages. Five cDNA libraries were constructed from the total RNA of placental tissue and sequenced using an Illumina HiSeq 2000. More than 19 million clean reads were obtained from each library, and greater than 50% of the reads were assignable to reference genes. Digital gene expression (DGE) profile analysis using Solexa sequencing was performed at five fruit developmental stages and resulted in the identification of 135 genes of known function; their expression patterns were compared to the capsaicin accumulation pattern. Ten genes of known function were identified as most likely to be involved in regulating capsaicin synthesis. Additionally, 20 new candidate genes were identified related to capsaicin synthesis. We use a combination of RNA-Seq and DGE analyses to contribute to the understanding of the biosynthetic regulatory mechanism(s) of secondary metabolites in a nonmodel plant and to identify candidate enzyme-encoding genes. PMID:27756914

  17. Combining Cell and Gene Therapy in an Effort to Eradicate HIV.

    PubMed

    Wagner, Thor A

    2016-12-01

    More than 30 million people are infected with HIV, and HIV remains the fifth leading cause of disability-adjusted life years worldwide. Antiretroviral therapy (ART) dramatically decreases mortality rate, but there are side effects, long-term toxicities, expenses, stigmas, and inconveniences associated with chronic treatment, and HIV-infected individuals on ART have an increased risk of malignancies, cardiovascular disease, neurologic disease, and shortened life expectancy. Therefore, a cure for HIV remains an important goal. Combining new cell and gene therapy technology is an exciting approach that appears promising in vitro. Animal testing and careful clinical trials will be needed to determine if these strategies are clinically useful.

  18. ExAtlas: An interactive online tool for meta-analysis of gene expression data.

    PubMed

    Sharov, Alexei A; Schlessinger, David; Ko, Minoru S H

    2015-12-01

    We have developed ExAtlas, an on-line software tool for meta-analysis and visualization of gene expression data. In contrast to existing software tools, ExAtlas compares multi-component data sets and generates results for all combinations (e.g. all gene expression profiles versus all Gene Ontology annotations). ExAtlas handles both users' own data and data extracted semi-automatically from the public repository (GEO/NCBI database). ExAtlas provides a variety of tools for meta-analyses: (1) standard meta-analysis (fixed effects, random effects, z-score, and Fisher's methods); (2) analyses of global correlations between gene expression data sets; (3) gene set enrichment; (4) gene set overlap; (5) gene association by expression profile; (6) gene specificity; and (7) statistical analysis (ANOVA, pairwise comparison, and PCA). ExAtlas produces graphical outputs, including heatmaps, scatter-plots, bar-charts, and three-dimensional images. Some of the most widely used public data sets (e.g. GNF/BioGPS, Gene Ontology, KEGG, GAD phenotypes, BrainScan, ENCODE ChIP-seq, and protein-protein interaction) are pre-loaded and can be used for functional annotations.

  19. A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

    PubMed Central

    Hajduk, Joanna; Klupczynska, Agnieszka; Dereziński, Paweł; Matysiak, Jan; Kokot, Piotr; Nowak, Dorota M.; Gajęcka, Marzena; Nowak-Markwitz, Ewa; Kokot, Zenon J.

    2015-01-01

    The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44%) and specificity (84.62%), as well as the total group membership classification value (90.32%) calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases. PMID:26694367

  20. The bivariate combined model for spatial data analysis.

    PubMed

    Neyens, Thomas; Lawson, Andrew B; Kirby, Russell S; Faes, Christel

    2016-08-15

    To describe the spatial distribution of diseases, a number of methods have been proposed to model relative risks within areas. Most models use Bayesian hierarchical methods, in which one models both spatially structured and unstructured extra-Poisson variance present in the data. For modelling a single disease, the conditional autoregressive (CAR) convolution model has been very popular. More recently, a combined model was proposed that 'combines' ideas from the CAR convolution model and the well-known Poisson-gamma model. The combined model was shown to be a good alternative to the CAR convolution model when there was a large amount of uncorrelated extra-variance in the data. Less solutions exist for modelling two diseases simultaneously or modelling a disease in two sub-populations simultaneously. Furthermore, existing models are typically based on the CAR convolution model. In this paper, a bivariate version of the combined model is proposed in which the unstructured heterogeneity term is split up into terms that are shared and terms that are specific to the disease or subpopulation, while spatial dependency is introduced via a univariate or multivariate Markov random field. The proposed method is illustrated by analysis of disease data in Georgia (USA) and Limburg (Belgium) and in a simulation study. We conclude that the bivariate combined model constitutes an interesting model when two diseases are possibly correlated. As the choice of the preferred model differs between data sets, we suggest to use the new and existing modelling approaches together and to choose the best model via goodness-of-fit statistics. Copyright © 2016 John Wiley & Sons, Ltd.

  1. Combining Cytotoxic and Immune-Mediated Gene Therapy to Treat Brain Tumors

    PubMed Central

    Curtin, James F.; King, Gwendalyn D.; Candolfi, Marianela; Greeno, Remy B.; Kroeger, Kurt M.; Lowenstein, Pedro R.; Castro, Maria G.

    2006-01-01

    Glioblastoma (GBM) is a type of intracranial brain tumor, for which there is no cure. In spite of advances in surgery, chemotherapy and radiotherapy, patients die within a year of diagnosis. Therefore, there is a critical need to develop novel therapeutic approaches for this disease. Gene therapy, which is the use of genes or other nucleic acids as drugs, is a powerful new treatment strategy which can be developed to treat GBM. Several treatment modalities are amenable for gene therapy implementation, e.g. conditional cytotoxic approaches, targeted delivery of toxins into the tumor mass, immune stimulatory strategies, and these will all be the focus of this review. Both conditional cytotoxicity and targeted toxin mediated tumor death, are aimed at eliminating an established tumor mass and preventing further growth. Tumors employ several defensive strategies that suppress and inhibit anti-tumor immune responses. A better understanding of the mechanisms involved in eliciting anti-tumor immune responses has identified promising targets for immunotherapy. Immunotherapy is designed to aid the immune system to recognize and destroy tumor cells in order to eliminate the tumor burden. Also, immune-therapeutic strategies have the added advantage that an activated immune system has the capability of recognizing tumor cells at distant sites from the primary tumor, therefore targeting metastasis distant from the primary tumor locale. Pre-clinical models and clinical trials have demonstrated that in spite of their location within the central nervous system (CNS), a tissue described as ‘immune privileged’, brain tumors can be effectively targeted by the activated immune system following various immunotherapeutic strategies. This review will highlight recent advances in brain tumor immunotherapy, with particular emphasis on advances made using gene therapy strategies, as well as reviewing other novel therapies that can be used in combination with immunotherapy. Another

  2. Combining cytotoxic and immune-mediated gene therapy to treat brain tumors.

    PubMed

    Curtin, James F; King, Gwendalyn D; Candolfi, Marianela; Greeno, Remy B; Kroeger, Kurt M; Lowenstein, Pedro R; Castro, Maria G

    2005-01-01

    Glioblastoma (GBM) is a type of intracranial brain tumor, for which there is no cure. In spite of advances in surgery, chemotherapy and radiotherapy, patients die within a year of diagnosis. Therefore, there is a critical need to develop novel therapeutic approaches for this disease. Gene therapy, which is the use of genes or other nucleic acids as drugs, is a powerful new treatment strategy which can be developed to treat GBM. Several treatment modalities are amenable for gene therapy implementation, e.g. conditional cytotoxic approaches, targeted delivery of toxins into the tumor mass, immune stimulatory strategies, and these will all be the focus of this review. Both conditional cytotoxicity and targeted toxin mediated tumor death, are aimed at eliminating an established tumor mass and preventing further growth. Tumors employ several defensive strategies that suppress and inhibit anti-tumor immune responses. A better understanding of the mechanisms involved in eliciting anti-tumor immune responses has identified promising targets for immunotherapy. Immunotherapy is designed to aid the immune system to recognize and destroy tumor cells in order to eliminate the tumor burden. Also, immune-therapeutic strategies have the added advantage that an activated immune system has the capability of recognizing tumor cells at distant sites from the primary tumor, therefore targeting metastasis distant from the primary tumor locale. Pre-clinical models and clinical trials have demonstrated that in spite of their location within the central nervous system (CNS), a tissue described as 'immune privileged', brain tumors can be effectively targeted by the activated immune system following various immunotherapeutic strategies. This review will highlight recent advances in brain tumor immunotherapy, with particular emphasis on advances made using gene therapy strategies, as well as reviewing other novel therapies that can be used in combination with immunotherapy. Another important

  3. Combining suppressive subtractive hybridization and cDNA microarrays to identify dietary phosphorus-responsive genes of the rainbow trout (Oncorhynchus mykiss) kidney.

    PubMed

    Lake, Jennifer; Gravel, Catherine; Koko, Gabriel Koffi D; Robert, Claude; Vandenberg, Grant W

    2010-03-01

    Phosphorus (P)-responsive genes and how they regulate renal adaptation to phosphorous-deficient diets in animals, including fish, are not well understood. RNA abundance profiling using cDNA microarrays is an efficient approach to study nutrient-gene interactions and identify these dietary P-responsive genes. To test the hypothesis that dietary P-responsive genes are differentially expressed in fish fed varying P levels, rainbow trout were fed a practical high-P diet (R20: 0.96% P) or a low-P diet (R0: 0.38% P) for 7 weeks. The differentially-expressed genes between dietary groups were identified and compared from the kidney by combining suppressive subtractive hybridization (SSH) with cDNA microarray analysis. A number of genes were confirmed by real-time PCR, and correlated with plasma and bone P concentrations. Approximately 54 genes were identified as potential dietary P-responsive after 7 weeks on a diet deficient in P according to cDNA microarray analysis. Of 18 selected genes, 13 genes were confirmed to be P-responsive at 7 weeks by real-time PCR analysis, including: iNOS, cytochrome b, cytochrome c oxidase subunit II , alpha-globin I, beta-globin, ATP synthase, hyperosmotic protein 21, COL1A3, Nkef, NDPK, glucose phosphate isomerase 1, Na+/H+ exchange protein and GDP dissociation inhibitor 2. Many of these dietary P-responsive genes responded in a moderate way (R0/R20 ratio: <2-3 or >0.5) and in a transient manner to dietary P limitation. In summary, renal adaptation to dietary P deficiency in trout involves changes in the expression of several genes, suggesting a profile of metabolic stress, since many of these differentially-expressed candidates are associated with the cellular adaptative responses.

  4. Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems.

    PubMed

    Schilling, C H; Edwards, J S; Letscher, D; Palsson, B Ø

    The elucidation of organism-scale metabolic networks necessitates the development of integrative methods to analyze and interpret the systemic properties of cellular metabolism. A shift in emphasis from single metabolic reactions to systemically defined pathways is one consequence of such an integrative analysis of metabolic systems. The constraints of systemic stoichiometry, and limited thermodynamics have led to the definition of the flux space within the context of convex analysis. The flux space of the metabolic system, containing all allowable flux distributions, is constrained to a convex polyhedral cone in a high-dimensional space. From metabolic pathway analysis, the edges of the high-dimensional flux cone are vectors that correspond to systemically defined "extreme pathways" spanning the capabilities of the system. The addition of maximum flux capacities of individual metabolic reactions serves to further constrain the flux space and has led to the development of flux balance analysis using linear optimization to calculate optimal flux distributions. Here we provide the precise theoretical connections between pathway analysis and flux balance analysis allowing for their combined application to study integrated metabolic function. Shifts in metabolic behavior are calculated using linear optimization and are then interpreted using the extreme pathways to demonstrate the concept of pathway utilization. Changes to the reaction network, such as the removal of a reaction, can lead to the generation of suboptimal phenotypes that can be directly attributed to the loss of pathway function and capabilities. Optimal growth phenotypes are calculated as a function of environmental variables, such as the availability of substrate and oxygen, leading to the definition of phenotypic phase planes. It is illustrated how optimality properties of the computed flux distributions can be interpreted in terms of the extreme pathways. Together these developments are applied to an

  5. A Monte Carlo method for combined segregation and linkage analysis

    SciTech Connect

    Guo, S.W. ); Thompson, E.A. )

    1992-11-01

    The authors introduce a Monte Carlo approach to combined segregation and linkage analysis of a quantitative trait observed in an extended pedigree. In conjunction with the Monte Carlo method of likelihood-ratio evaluation proposed by Thompson and Guo, the method provides for estimation and hypothesis testing. The greatest attraction of this approach is its ability to handle complex genetic models and large pedigrees. Two examples illustrate the practicality of the method. One is of simulated data on a large pedigree; the other is a reanalysis of published data previously analyzed by other methods. 40 refs, 5 figs., 5 tabs.

  6. Co-expression network analysis and genetic algorithms for gene prioritization in preeclampsia.

    PubMed

    Tejera, Eduardo; Bernardes, João; Rebelo, Irene

    2013-11-12

    In this study, we explored the gene prioritization in preeclampsia, combining co-expression network analysis and genetic algorithms optimization approaches. We analysed five public projects obtaining 1,146 significant genes after cross-platform and processing of 81 and 149 microarrays in preeclamptic and normal conditions, respectively. After co-expression network construction, modular and node analysis were performed using several approaches. Moreover, genetic algorithms were also applied in combination with the nearest neighbour and discriminant analysis classification methods. Significant differences were found in the genes connectivity distribution, both in normal and preeclampsia conditions pointing to the need and importance of examining connectivity alongside expression for prioritization. We discuss the global as well as intra-modular connectivity for hubs detection and also the utility of genetic algorithms in combination with the network information. FLT1, LEP, INHA and ENG genes were identified according to the literature, however, we also found other genes as FLNB, INHBA, NDRG1 and LYN highly significant but underexplored during normal pregnancy or preeclampsia. Weighted genes co-expression network analysis reveals a similar distribution along the modules detected both in normal and preeclampsia conditions. However, major differences were obtained by analysing the nodes connectivity. All models obtained by genetic algorithm procedures were consistent with a correct classification, higher than 90%, restricting to 30 variables in both classification methods applied.Combining the two methods we identified well known genes related to preeclampsia, but also lead us to propose new candidates poorly explored or completely unknown in the pathogenesis of preeclampsia, which may have to be validated experimentally.

  7. Different SNP combinations in the GCH1 gene and use of labor analgesia

    PubMed Central

    2010-01-01

    Background The aim of this study was to investigate if there is an association between different SNP combinations in the guanosine triphosphate cyclohydrolase (GCH1) gene and a number of pain behavior related outcomes during labor. A population-based sample of pregnant women (n = 814) was recruited at gestational week 18. A plasma sample was collected from each subject. Genotyping was performed and three single nucleotide polymorphisms (SNP) previously defined as a pain-protective SNP combination of GCH1 were used. Results Homozygous carriers of the pain-protective SNP combination of GCH1 arrived to the delivery ward with a more advanced stage of cervical dilation compared to heterozygous carriers and non-carriers. However, homozygous carriers more often used second line labor analgesia compared to the others. Conclusion The pain-protective SNP combination of GCH1 may be of importance in the limited number of homozygous carriers during the initial dilation of cervix but upon arrival at the delivery unit these women are more inclined to use second line labor analgesia. PMID:20633294

  8. The combined effect of drought stress and heat shock on gene expression in tobacco.

    PubMed

    Rizhsky, Ludmila; Liang, Hongjian; Mittler, Ron

    2002-11-01

    In nature, plants encounter a combination of environmental conditions that may include stresses such as drought or heat shock. Although drought and heat shock have been extensively studied, little is known about how their combination affect plants. We used cDNA arrays, coupled with physiological measurements, to study the effect of drought and heat shock on tobacco (Nicotiana tabacum) plants. A combination of drought and heat shock resulted in the closure of stomata, suppression of photosynthesis, enhancement of respiration, and increased leaf temperature. Some transcripts induced during drought, e.g. those encoding dehydrin, catalase, and glycolate oxidase, and some transcripts induced during heat shock, e.g. thioredoxin peroxidase, and ascorbate peroxidase, were suppressed during a combination of drought and heat shock. In contrast, the expression of other transcripts, including alternative oxidase, glutathione peroxidase, phenylalanine ammonia lyase, pathogenesis-related proteins, a WRKY transcription factor, and an ethylene response transcriptional co-activator, was specifically induced during a combination of drought and heat shock. Photosynthetic genes were suppressed, whereas transcripts encoding some glycolysis and pentose phosphate pathway enzymes were induced, suggesting the utilization of sugars through these pathways during stress. Our results demonstrate that the response of plants to a combination of drought and heat shock, similar to the conditions in many natural environments, is different from the response of plants to each of these stresses applied individually, as typically tested in the laboratory. This response was also different from the response of plants to other stresses such as cold, salt, or pathogen attack. Therefore, improving stress tolerance of plants and crops may require a reevaluation, taking into account the effect of multiple stresses on plant metabolism and defense.

  9. MAVTgsa: An R Package for Gene Set (Enrichment) Analysis

    DOE PAGES

    Chien, Chih-Yi; Chang, Ching-Wei; Tsai, Chen-An; ...

    2014-01-01

    Gene semore » t analysis methods aim to determine whether an a priori defined set of genes shows statistically significant difference in expression on either categorical or continuous outcomes. Although many methods for gene set analysis have been proposed, a systematic analysis tool for identification of different types of gene set significance modules has not been developed previously. This work presents an R package, called MAVTgsa, which includes three different methods for integrated gene set enrichment analysis. (1) The one-sided OLS (ordinary least squares) test detects coordinated changes of genes in gene set in one direction, either up- or downregulation. (2) The two-sided MANOVA (multivariate analysis variance) detects changes both up- and downregulation for studying two or more experimental conditions. (3) A random forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes. MAVTgsa computes the P values and FDR (false discovery rate) q -value for all gene sets in the study. Furthermore, MAVTgsa provides several visualization outputs to support and interpret the enrichment results. This package is available online.« less

  10. Pathway level analysis of gene expression using singular value decomposition

    PubMed Central

    Tomfohr, John; Lu, Jun; Kepler, Thomas B

    2005-01-01

    Background A promising direction in the analysis of gene expression focuses on the changes in expression of specific predefined sets of genes that are known in advance to be related (e.g., genes coding for proteins involved in cellular pathways or complexes). Such an analysis can reveal features that are not easily visible from the variations in the individual genes and can lead to a picture of expression that is more biologically transparent and accessible to interpretation. In this article, we present a new method of this kind that operates by quantifying the level of 'activity' of each pathway in different samples. The activity levels, which are derived from singular value decompositions, form the basis for statistical comparisons and other applications. Results We demonstrate our approach using expression data from a study of type 2 diabetes and another of the influence of cigarette smoke on gene expression in airway epithelia. A number of interesting pathways are identified in comparisons between smokers and non-smokers including ones related to nicotine metabolism, mucus production, and glutathione metabolism. A comparison with results from the related approach, 'gene-set enrichment analysis', is also provided. Conclusion Our method offers a flexible basis for identifying differentially expressed pathways from gene expression data. The results of a pathway-based analysis can be complementary to those obtained from one more focused on individual genes. A web program PLAGE (Pathway Level Analysis of Gene Expression) for performing the kinds of analyses described here is accessible at . PMID:16156896

  11. Database for exchangeable gene trap clones: pathway and gene ontology analysis of exchangeable gene trap clone mouse lines.

    PubMed

    Araki, Masatake; Nakahara, Mai; Muta, Mayumi; Itou, Miharu; Yanai, Chika; Yamazoe, Fumika; Miyake, Mikiko; Morita, Ayaka; Araki, Miyuki; Okamoto, Yoshiyuki; Nakagata, Naomi; Yoshinobu, Kumiko; Yamamura, Ken-ichi; Araki, Kimi

    2014-02-01

    Gene trapping in embryonic stem (ES) cells is a proven method for large-scale random insertional mutagenesis in the mouse genome. We have established an exchangeable gene trap system, in which a reporter gene can be exchanged for any other DNA of interest through Cre/mutant lox-mediated recombination. We isolated trap clones, analyzed trapped genes, and constructed the database for Exchangeable Gene Trap Clones (EGTC) [http://egtc.jp]. The number of registered ES cell lines was 1162 on 31 August 2013. We also established 454 mouse lines from trap ES clones and deposited them in the mouse embryo bank at the Center for Animal Resources and Development, Kumamoto University, Japan. The EGTC database is the most extensive academic resource for gene-trap mouse lines. Because we used a promoter-trap strategy, all trapped genes were expressed in ES cells. To understand the general characteristics of the trapped genes in the EGTC library, we used Kyoto Encyclopedia of Genes and Genomes (KEGG) for pathway analysis and found that the EGTC ES clones covered a broad range of pathways. We also used Gene Ontology (GO) classification data provided by Mouse Genome Informatics (MGI) to compare the functional distribution of genes in each GO term between trapped genes in the EGTC mouse lines and total genes annotated in MGI. We found the functional distributions for the trapped genes in the EGTC mouse lines and for the RefSeq genes for the whole mouse genome were similar, indicating that the EGTC mouse lines had trapped a wide range of mouse genes. © 2014 The Authors Development, Growth & Differentiation © 2014 Japanese Society of Developmental Biologists.

  12. MINER: exploratory analysis of gene interaction networks by machine learning from expression data

    PubMed Central

    2009-01-01

    Background The reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies. Results We have developed MINER (Microarray Interactive Network Exploration and Representation), an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations. MINER allows biologists to explore the dependencies influencing the expression of individual genes in a gene expression data set in the form of decision, model or regression trees, using their domain knowledge to guide the exploration and formulate hypotheses. Multiple trees can then be summarised in the form of a gene network diagram. MINER is being adopted by several of our collaborators and has already led to the discovery of a new significant regulatory relationship with subsequent experimental validation. Conclusion Unlike most gene regulatory network inference methods, MINER allows the user to start from genes of interest and build the network gene-by-gene, incorporating domain expertise in the process. This approach has been used successfully with RNA microarray data but is applicable to other quantitative data produced by high-throughput technologies such as proteomics and "next generation" DNA sequencing. PMID:19958480

  13. MINER: exploratory analysis of gene interaction networks by machine learning from expression data.

    PubMed

    Kadupitige, Sidath Randeni; Leung, Kin Chun; Sellmeier, Julia; Sivieng, Jane; Catchpoole, Daniel R; Bain, Michael E; Gaëta, Bruno A

    2009-12-03

    The reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies. We have developed MINER (Microarray Interactive Network Exploration and Representation), an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations. MINER allows biologists to explore the dependencies influencing the expression of individual genes in a gene expression data set in the form of decision, model or regression trees, using their domain knowledge to guide the exploration and formulate hypotheses. Multiple trees can then be summarised in the form of a gene network diagram. MINER is being adopted by several of our collaborators and has already led to the discovery of a new significant regulatory relationship with subsequent experimental validation. Unlike most gene regulatory network inference methods, MINER allows the user to start from genes of interest and build the network gene-by-gene, incorporating domain expertise in the process. This approach has been used successfully with RNA microarray data but is applicable to other quantitative data produced by high-throughput technologies such as proteomics and "next generation" DNA sequencing.

  14. Identification and Validation of Reference Genes for the Normalization of Gene Expression Data in qRT-PCR Analysis in Aphis gossypii (Hemiptera: Aphididae).

    PubMed

    Ma, Kang-Sheng; Li, Fen; Liang, Ping-Zhuo; Chen, Xue-Wei; Liu, Ying; Gao, Xi-Wu

    2016-01-01

    To obtain accurate and reliable results from quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) analysis, it is necessary to select suitable reference genes as standards for normalizing target gene expression data. QRT-PCR is a popular analytical methodology for studying gene expression and it has been used widely in studies of Aphis gossypii Glover in recent years. However, there is absence of study on the stability of the expression of reference genes in A. gossypii. In this study, eight commonly used candidate reference genes, including 18S, 28S, β-ACT, GAPDH, EF1α, RPL7, α-TUB, and TBP, were evaluated under various experimental conditions to assess their suitability for use in the normalization of qRT-PCR data. The optimal number of reference genes was determined using the geNorm program, and the suitability of particular reference genes was empirically validated by performing normalizations of expression data for the HSP70 gene. The results showed the most suitable combinations of reference genes for the different experimental conditions. For experiments based on divergent developmental stages, EF1α, β-ACT, and RPL7 are the optimal reference gene combination, both EF1α and β-ACT are the optimal combination used in the experiments of different geographical populations, whereas for experiments of the temperature changes, the combination of GAPDH and RPL7 is optimal, both 18S and β-ACT are an optimal combination for feeding assay experiments. These research results should be useful for the selection of the suitable reference genes to obtain reliable qRT-PCR data in the gene expression study of A. gossypii.

  15. Global Gene Expression Analysis for the Assessment of Nanobiomaterials.

    PubMed

    Hanagata, Nobutaka

    2015-01-01

    Using global gene expression analysis, the effects of biomaterials and nanomaterials can be analyzed at the genetic level. Even though information obtained from global gene expression analysis can be useful for the evaluation and design of biomaterials and nanomaterials, its use for these purposes is not widespread. This is due to the difficulties involved in data analysis. Because the expression data of about 20,000 genes can be obtained at once with global gene expression analysis, the data must be analyzed using bioinformatics. A method of bioinformatic analysis called gene ontology can estimate the kinds of changes on cell functions caused by genes whose expression level is changed by biomaterials and nanomaterials. Also, by applying a statistical analysis technique called hierarchical clustering to global gene expression data between a variety of biomaterials, the effects of the properties of materials on cell functions can be estimated. In this chapter, these theories of analysis and examples of applications to nanomaterials and biomaterials are described. Furthermore, global microRNA analysis, a method that has gained attention in recent years, and its application to nanomaterials are introduced.

  16. The impact of sodium nitroprusside and ozone in kiwifruit ripening physiology: a combined gene and protein expression profiling approach

    PubMed Central

    Tanou, Georgia; Minas, Ioannis S.; Karagiannis, Evangelos; Tsikou, Daniela; Audebert, Stéphane; Papadopoulou, Kalliope K.; Molassiotis, Athanassios

    2015-01-01

    Background and Aims Despite their importance in many aspects of plant physiology, information about the function of oxidative and, particularly, of nitrosative signalling in fruit biology is limited. This study examined the possible implications of O3 and sodium nitroprusside (SNP) in kiwifruit ripening, and their interacting effects. It also aimed to investigate changes in the kiwifruit proteome in response to SNP and O3 treatments, together with selected transcript analysis, as a way to enhance our understanding of the fruit ripening syndrome. Methods Kiwifruits following harvest were pre-treated with 100 μm SNP, then cold-stored (0 °C, relative humidity 95 %) for either 2 or 6 months in the absence or in the presence of O3 (0·3 μL L–1), and subsequently were allowed to ripen at 20 °C. The ripening behaviour of fruit was characterized using several approaches: together with ethylene production, several genes, enzymes and metabolites involved in ethylene biosynthesis were analysed. Kiwifruit proteins were identified using 2-D electrophoresis coupled with nanoliquid chromatography–tandem mass spectrometry (LC-MS/MS) analysis. Expression patterns of kiwifruit ripening-related genes were also analysed using real-time quantitative reverse transcription–PCR (RT–qPCR). Key Results O3 treatment markedly delayed fruit softening and depressed the ethylene biosynthetic mechanism. Although SNP alone was relatively ineffective in regulating ripening, SNP treatment prior to O3 exposure attenuated the O3-induced ripening inhibition. Proteomic analysis revealed a considerable overlap between proteins affected by both SNP and O3. Consistent with this, the temporal dynamics in the expression of selected kiwifruit ripening-related genes were noticeably different between individual O3 and combined SNP and O3 treatments. Conclusions This study demonstrates that O3-induced ripening inhibition could be reversed by SNP and provides insights into the interaction

  17. Genome-wide analysis of homeobox gene family in legumes: identification, gene duplication and expression profiling.

    PubMed

    Bhattacharjee, Annapurna; Ghangal, Rajesh; Garg, Rohini; Jain, Mukesh

    2015-01-01

    Homeobox genes encode transcription factors that are known to play a major role in different aspects of plant growth and development. In the present study, we identified homeobox genes belonging to 14 different classes in five legume species, including chickpea, soybean, Medicago, Lotus and pigeonpea. The characteristic differences within homeodomain sequences among various classes of homeobox gene family were quite evident. Genome-wide expression analysis using publicly available datasets (RNA-seq and microarray) indicated that homeobox genes are differentially expressed in various tissues/developmental stages and under stress conditions in different legumes. We validated the differential expression of selected chickpea homeobox genes via quantitative reverse transcription polymerase chain reaction. Genome duplication analysis in soybean indicated that segmental duplication has significantly contributed in the expansion of homeobox gene family. The Ka/Ks ratio of duplicated homeobox genes in soybean showed that several members of this family have undergone purifying selection. Moreover, expression profiling indicated that duplicated genes might have been retained due to sub-functionalization. The genome-wide identification and comprehensive gene expression profiling of homeobox gene family members in legumes will provide opportunities for functional analysis to unravel their exact role in plant growth and development.

  18. The limitations of simple gene set enrichment analysis assuming gene independence.

    PubMed

    Tamayo, Pablo; Steinhardt, George; Liberzon, Arthur; Mesirov, Jill P

    2016-02-01

    Since its first publication in 2003, the Gene Set Enrichment Analysis method, based on the Kolmogorov-Smirnov statistic, has been heavily used, modified, and also questioned. Recently a simplified approach using a one-sample t-test score to assess enrichment and ignoring gene-gene correlations was proposed by Irizarry et al. 2009 as a serious contender. The argument criticizes Gene Set Enrichment Analysis's nonparametric nature and its use of an empirical null distribution as unnecessary and hard to compute. We refute these claims by careful consideration of the assumptions of the simplified method and its results, including a comparison with Gene Set Enrichment Analysis's on a large benchmark set of 50 datasets. Our results provide strong empirical evidence that gene-gene correlations cannot be ignored due to the significant variance inflation they produced on the enrichment scores and should be taken into account when estimating gene set enrichment significance. In addition, we discuss the challenges that the complex correlation structure and multi-modality of gene sets pose more generally for gene set enrichment methods. © The Author(s) 2012.

  19. Genome-Wide Analysis of Homeobox Gene Family in Legumes: Identification, Gene Duplication and Expression Profiling

    PubMed Central

    Garg, Rohini; Jain, Mukesh

    2015-01-01

    Homeobox genes encode transcription factors that are known to play a major role in different aspects of plant growth and development. In the present study, we identified homeobox genes belonging to 14 different classes in five legume species, including chickpea, soybean, Medicago, Lotus and pigeonpea. The characteristic differences within homeodomain sequences among various classes of homeobox gene family were quite evident. Genome-wide expression analysis using publicly available datasets (RNA-seq and microarray) indicated that homeobox genes are differentially expressed in various tissues/developmental stages and under stress conditions in different legumes. We validated the differential expression of selected chickpea homeobox genes via quantitative reverse transcription polymerase chain reaction. Genome duplication analysis in soybean indicated that segmental duplication has significantly contributed in the expansion of homeobox gene family. The Ka/Ks ratio of duplicated homeobox genes in soybean showed that several members of this family have undergone purifying selection. Moreover, expression profiling indicated that duplicated genes might have been retained due to sub-functionalization. The genome-wide identification and comprehensive gene expression profiling of homeobox gene family members in legumes will provide opportunities for functional analysis to unravel their exact role in plant growth and development. PMID:25745864

  20. GO2MSIG, an automated GO based multi-species gene set generator for gene set enrichment analysis.

    PubMed

    Powell, Justin Andrew Christiaan

    2014-05-17

    Despite the widespread use of high throughput expression platforms and the availability of a desktop implementation of Gene Set Enrichment Analysis (GSEA) that enables non-experts to perform gene set based analyses, the availability of the necessary precompiled gene sets is rare for species other than human. A software tool (GO2MSIG) was implemented that combines data from various publicly available sources and uses the Gene Ontology (GO) project term relationships to produce GSEA compatible hierarchical GO based gene sets for all species for which association data is available. Annotation sources include the GO association database (which contains data for over 200000 species), the Entrez gene2go table, and various manufacturers' array annotation files. This enables the creation of gene sets from the most up-to-date annotation data available. Additional features include the ability to restrict by evidence code, to remap gene descriptors, to filter by set size and to speed up repeat queries by caching the GO term hierarchy. Synonymous GO terms are remapped to the version preferred by the GO ontology supplied. The tool can be used in standalone form, or via a web interface. Prebuilt gene set collections constructed from the September 2013 GO release are also available for common species including human. In contrast human GO based sets available from the Broad Institute itself date from 2008. GO2MSIG enables the bioinformatician and non-bioinformatician alike to generate gene sets required for GSEA analysis for almost any organism for which GO term association data exists. The output gene sets may be used directly within GSEA and do not require knowledge of programming languages such as Perl, R or Python. The output sets can also be used with other analysis software such as ErmineJ that accept gene sets in the same format. Source code can be downloaded and installed locally from http://www.bioinformatics.org/go2msig/releases/ or used via the web interface at http

  1. Transcriptomic Analysis of Trout Gill Ionocytes in Fresh Water and Sea Water Using Laser Capture Microdissection Combined with Microarray Analysis.

    PubMed

    Leguen, Isabelle; Le Cam, Aurélie; Montfort, Jérôme; Peron, Sandrine; Fautrel, Alain

    2015-01-01

    Fish gills represent a complex organ composed of several cell types that perform multiple physiological functions. Among these cells, ionocytes are implicated in the maintenance of ion homeostasis. However, because the ionocyte represents only a small percent of whole gill tissue, its specific transcriptome can be overlooked among the numerous cell types included in the gill. The objective of this study is to better understand ionocyte functions by comparing the RNA expression of this cell type in freshwater and seawater acclimated rainbow trout. To realize this objective, ionocytes were captured from gill cryosections using laser capture microdissection after immunohistochemistry. Then, transcriptome analyses were performed on an Agilent trout oligonucleotide microarray. Gene expression analysis identified 108 unique annotated genes differentially expressed between freshwater and seawater ionocytes, with a fold change higher than 3. Most of these genes were up-regulated in freshwater cells. Interestingly, several genes implicated in ion transport, extracellular matrix and structural cellular proteins appeared up-regulated in freshwater ionocytes. Among them, several ion transporters, such as CIC2, SLC26A6, and NBC, were validated by qPCR and/or in situ hybridization. The latter technique allowed us to localize the transcripts of these ion transporters in only ionocytes and more particularly in the freshwater cells. Genes involved in metabolism and also several genes implicated in transcriptional regulation, cell signaling and the cell cycle were also enhanced in freshwater ionocytes. In conclusion, laser capture microdissection combined with microarray analysis allowed for the determination of the transcriptional signature of scarce cells in fish gills, such as ionocytes, and aided characterization of the transcriptome of these cells in freshwater and seawater acclimated trout.

  2. Multi-layered nanoparticles for combination gene and drug delivery to tumors

    PubMed Central

    Ediriwickrema, Asiri; Zhou, Jiangbing; Deng, Yang; Saltzman, Mark

    2014-01-01

    Drug resistance and toxicity are major obstacles in cancer chemotherapy. Combination therapies can overcome resistance, and synergies can minimize dosing. Polymer nanocarriers are interesting vehicles for cancer therapeutics for their delivery and tumor targeting abilities. We synthesized a multilayered polymer nanoparticle (MLNP), comprising of poly(lactic-co-glycolic acid) with surface polyethyleneimine and functional peptides, for targeted drug and gene delivery. We confirmed the particle’s ability to inhibit tumor growth through synergistic action of the drug and gene product. MLNPs achieved transfection levels similar to lipofectamine, while maintaining minimal cytotoxicity. The particles delivered camptothecin (CPT), and plasmid encoding TNF related apoptosis inducing ligand (pTRAIL) (CT MLNPs), and synergistically inhibited growth of multiple cancer cells in vitro. The synergy of co-delivering CPT and pTRAIL via CT MLNPs was confirmed using the Chou-Talalay method: the combination index (CI) values at 50% inhibition ranged between 0.31–0.53 for all cell lines. Further, co-delivery with MLNPs resulted in a 3.1–15 fold reduction in CPT and 4.7–8.0 fold reduction in pTRAIL dosing. CT MLNPs obtained significant HCT116 growth inhibition in vivo compared to monotherapy. These results support our hypothesis that MLNPs can deliver both small molecules and genetic agents towards synergistically inhibiting tumor growth. PMID:25112935

  3. Combined Tbet and IL12 gene therapy elicits and recruits superior antitumor immunity in vivo.

    PubMed

    Qu, Yanyan; Chen, Lu; Lowe, Devin B; Storkus, Walter J; Taylor, Jennifer L

    2012-03-01

    We have recently shown that intratumor (i.t.) injection of syngenic dendritic cells (DC) engineered to express the transcription factor Tbet (TBX21) promotes protective type-1 T cell-mediated immunity via a mechanism that is largely interleukin (IL)-12p70-independent. Since IL-12 is a classical promoter of type-1 immunity, the current study was undertaken to determine whether gene therapy using combined Tbet and IL-12 complementary DNA (cDNA) would yield improved antitumor efficacy based on the complementary/synergistic action of these biologic modifiers. Mice bearing established subcutaneous (s.c.) tumors injected with DC concomitantly expressing ectopic Tbet and IL12 (i.e., DC.Tbet/IL12) displayed superior (i) rates of tumor rejection and extended overall survival, (ii) cross-priming of Tc1 reactive against antigens expressed within the tumor microenvironment, and (iii) infiltration of CD8(+) T cells into treated tumors in association with elevated locoregional production of CXCR3 ligand chemokines. In established bilateral tumor models, i.t. delivery of DC.Tbet/IL12 into a single lesion led to slowed growth or regression at both tumor sites. Furthermore, DC.Tbet/IL12 pulsed with tumor antigen-derived peptides and injected as a therapy distal to the tumor site prevented tumor growth and activated robust antigen-specific Tc1 responses. These data support the translation use of combined Tbet and IL-12p70 gene therapy in the cancer setting.

  4. Analysis of bHLH coding genes using gene co-expression network approach.

    PubMed

    Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

    2016-07-01

    Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes wer