Alu sequence involvement in transcriptional insulation of the keratin 18 gene in transgenic mice.

PubMed Central

Thorey, I S; Ceceña, G; Reynolds, W; Oshima, R G

1993-01-01

The human keratin 18 (K18) gene is expressed in a variety of adult simple epithelial tissues, including liver, intestine, lung, and kidney, but is not normally found in skin, muscle, heart, spleen, or most of the brain. Transgenic animals derived from the cloned K18 gene express the transgene in appropriate tissues at levels directly proportional to the copy number and independently of the sites of integration. We have investigated in transgenic mice the dependence of K18 gene expression on the distal 5' and 3' flanking sequences and upon the RNA polymerase III promoter of an Alu repetitive DNA transcription unit immediately upstream of the K18 promoter. Integration site-independent expression of tandemly duplicated K18 transgenes requires the presence of either an 825-bp fragment of the 5' flanking sequence or the 3.5-kb 3' flanking sequence. Mutation of the RNA polymerase III promoter of the Alu element within the 825-bp fragment abolishes copy number-dependent expression in kidney but does not abolish integration site-independent expression when assayed in the absence of the 3' flanking sequence of the K18 gene. The characteristics of integration site-independent expression and copy number-dependent expression are separable. In addition, the formation of the chromatin state of the K18 gene, which likely restricts the tissue-specific expression of this gene, is not dependent upon the distal flanking sequences of the 10-kb K18 gene but rather may depend on internal regulatory regions of the gene. Images PMID:7692231

Integration of High-Risk Human Papillomavirus into Cellular Cancer-Related Genes in Head and Neck Cancer Cell Lines

PubMed Central

Walline, Heather M; Komarck, Christine M; McHugh, Jonathan B; Tang, Alice L; Owen, John H; Teh, Bin T; McKean, Erin; Glover, Thomas; Graham, Martin P; Prince, Mark E; Chepeha, Douglas B; Chinn, Steven B; Ferris, Robert L; Gollin, Susanne M; Hoffmann, Thomas K; Bier, Henning; Brakenhoff, Ruud; Bradford, Carol R; Carey, Thomas E

2017-01-01

Background HPV-positive oropharyngeal cancer is generally associated with excellent response to therapy, but some HPV-positive tumors progress despite aggressive therapy. This study evaluates viral oncogene expression and viral integration sites in HPV16 and HPV18-positive squamous carcinoma cell lines. Methods E6-E7 alternate transcripts were assessed by RT-PCR. Detection of integrated papillomavirus sequences (DIPS-PCR) and sequencing identified viral insertion sites and affected host genes. Cellular gene expression was assessed across viral integration sites. Results All HPV-positive cell lines expressed alternate HPVE6/E7 splicing indicative of active viral oncogenesis. HPV integration occurred within cancer-related genes TP63, DCC, JAK1, TERT, ATR, ETV6, PGR, PTPRN2, and TMEM237 in 8 HNSCC lines but UM-SCC-105 and UM-GCC-1 had only intergenic integration. Conclusions HPV integration into cancer-related genes occurred in 7/9 HPV-positive cell lines and of these six were from tumors that progressed. HPV integration into cancer-related genes may be a secondary carcinogenic driver in HPV-driven tumors. PMID:28236344

Genic insights from integrated human proteomics in GeneCards.

PubMed

Fishilevich, Simon; Zimmerman, Shahar; Kohn, Asher; Iny Stein, Tsippi; Olender, Tsviya; Kolker, Eugene; Safran, Marilyn; Lancet, Doron

2016-01-01

GeneCards is a one-stop shop for searchable human gene annotations (http://www.genecards.org/). Data are automatically mined from ∼120 sources and presented in an integrated web card for every human gene. We report the application of recent advances in proteomics to enhance gene annotation and classification in GeneCards. First, we constructed the Human Integrated Protein Expression Database (HIPED), a unified database of protein abundance in human tissues, based on the publically available mass spectrometry (MS)-based proteomics sources ProteomicsDB, Multi-Omics Profiling Expression Database, Protein Abundance Across Organisms and The MaxQuant DataBase. The integrated database, residing within GeneCards, compares favourably with its individual sources, covering nearly 90% of human protein-coding genes. For gene annotation and comparisons, we first defined a protein expression vector for each gene, based on normalized abundances in 69 normal human tissues. This vector is portrayed in the GeneCards expression section as a bar graph, allowing visual inspection and comparison. These data are juxtaposed with transcriptome bar graphs. Using the protein expression vectors, we further defined a pairwise metric that helps assess expression-based pairwise proximity. This new metric for finding functional partners complements eight others, including sharing of pathways, gene ontology (GO) terms and domains, implemented in the GeneCards Suite. In parallel, we calculated proteome-based differential expression, highlighting a subset of tissues that overexpress a gene and subserving gene classification. This textual annotation allows users of VarElect, the suite's next-generation phenotyper, to more effectively discover causative disease variants. Finally, we define the protein-RNA expression ratio and correlation as yet another attribute of every gene in each tissue, adding further annotative information. The results constitute a significant enhancement of several GeneCards sections and help promote and organize the genome-wide structural and functional knowledge of the human proteome. Database URL:http://www.genecards.org/. © The Author(s) 2016. Published by Oxford University Press.

Simultaneous and Sequential Integration by Cre/loxP Site-Specific Recombination in Saccharomyces cerevisiae.

PubMed

Choi, Ho-Jung; Kim, Yeon-Hee

2018-05-28

A Cre/ loxP -δ-integration system was developed to allow sequential and simultaneous integration of a multiple gene expression cassette in Saccharomyces cerevisiae . To allow repeated integrations, the reusable Candida glabrata MARKER ( CgMARKER ) carrying loxP sequences was used, and the integrated CgMARKER was efficiently removed by inducing Cre recombinase. The XYLP and XYLB genes encoding endoxylanase and β-xylosidase, respectively, were used as model genes for xylan metabolism in this system, and the copy number of these genes was increased to 15.8 and 16.9 copies/cell, respectively, by repeated integration. This integration system is a promising approach for the easy construction of yeast strains with enhanced metabolic pathways through multicopy gene expression.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

PubMed Central

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

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

Kolker, Eugene

Our project focused primarily on analysis of different types of data produced by global high-throughput technologies, data integration of gene annotation, and gene and protein expression information, as well as on getting a better functional annotation of Shewanella genes. Specifically, four of our numerous major activities and achievements include the development of: statistical models for identification and expression proteomics, superior to currently available approaches (including our own earlier ones); approaches to improve gene annotations on the whole-organism scale; standards for annotation, transcriptomics and proteomics approaches; and generalized approaches for data integration of gene annotation, gene and protein expression information.

Promotion of spinosad biosynthesis by chromosomal integration of the Vitreoscilla hemoglobin gene in Saccharopolyspora spinosa.

PubMed

Luo, Yushuang; Kou, Xiaoxiao; Ding, Xuezhi; Hu, Shengbiao; Tang, Ying; Li, Wenping; Huang, Fan; Yang, Qi; Chen, Hanna; Xia, Liqiu

2012-02-01

To promote spinosad biosynthesis by improving the limited oxygen supply during high-density fermentation of Saccharopolyspora spinosa, the open reading frame of the Vitreoscilla hemoglobin gene was placed under the control of the promoter for the erythromycin resistance gene by splicing using overlapping extension PCR. This was cloned into the integrating vector pSET152, yielding the Vitreoscilla hemoglobin gene expression plasmid pSET152EVHB. This was then introduced into S. spinosa SP06081 by conjugal transfer, and integrated into the chromosome by site-specific recombination at the integration site ΦC31 on pSET152EVHB. The resultant conjugant, S. spinosa S078-1101, was genetically stable. The integration was further confirmed by PCR and Southern blotting analysis. A carbon monoxide differential spectrum assay showed that active Vitreoscilla hemoglobin was successfully expressed in S. spinosa S078-1101. Fermentation results revealed that expression of the Vitreoscilla hemoglobin gene significantly promoted spinosad biosynthesis under normal oxygen and moderately oxygen-limiting conditions (P<0.01). These findings demonstrate that integrating expression of the Vitreoscilla hemoglobin gene improves oxygen uptake and is an effective means for the genetic improvement of S. spinosa fermentation.

Broad Integration of Expression Maps and Co-Expression Networks Compassing Novel Gene Functions in the Brain

PubMed Central

Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo

2014-01-01

Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas. PMID:25382412

An Integrated Approach for RNA-seq Data Normalization.

PubMed

Yang, Shengping; Mercante, Donald E; Zhang, Kun; Fang, Zhide

2016-01-01

DNA copy number alteration is common in many cancers. Studies have shown that insertion or deletion of DNA sequences can directly alter gene expression, and significant correlation exists between DNA copy number and gene expression. Data normalization is a critical step in the analysis of gene expression generated by RNA-seq technology. Successful normalization reduces/removes unwanted nonbiological variations in the data, while keeping meaningful information intact. However, as far as we know, no attempt has been made to adjust for the variation due to DNA copy number changes in RNA-seq data normalization. In this article, we propose an integrated approach for RNA-seq data normalization. Comparisons show that the proposed normalization can improve power for downstream differentially expressed gene detection and generate more biologically meaningful results in gene profiling. In addition, our findings show that due to the effects of copy number changes, some housekeeping genes are not always suitable internal controls for studying gene expression. Using information from DNA copy number, integrated approach is successful in reducing noises due to both biological and nonbiological causes in RNA-seq data, thus increasing the accuracy of gene profiling.

Selective elimination of long INterspersed element-1 expressing tumour cells by targeted expression of the HSV-TK suicide gene

PubMed Central

Chendeb, Mariam; Schneider, Robert; Davidson, Irwin; Fadloun, Anas

2017-01-01

In gene therapy, effective and selective suicide gene expression is crucial. We exploited the endogenous Long INterspersed Element-1 (L1) machinery often reactivated in human cancers to integrate the Herpes Simplex Virus Thymidine Kinase (HSV-TK) suicide gene selectively into the genome of cancer cells. We developed a plasmid-based system directing HSV-TK expression only when reverse transcribed and integrated in the host genome via the endogenous L1 ORF1/2 proteins and an Alu element. Delivery of these new constructs into cells followed by Ganciclovir (GCV) treatment selectively induced mortality of L1 ORF1/2 protein expressing cancer cells, but had no effect on primary cells that do not express L1 ORF1/2. This novel strategy for selective targeting of tumour cells provides high tolerability as the HSV-TK gene cannot be expressed without reverse transcription and integration, and high selectivity as these processes take place only in cancer cells expressing high levels of functional L1 ORF1/2. PMID:28415677

Drosophila Araucan and Caupolican Integrate Intrinsic and Signalling Inputs for the Acquisition by Muscle Progenitors of the Lateral Transverse Fate

PubMed Central

Carrasco-Rando, Marta; Tutor, Antonio S.; Prieto-Sánchez, Silvia; González-Pérez, Esther; Barrios, Natalia; Letizia, Annalisa; Martín, Paloma; Campuzano, Sonsoles; Ruiz-Gómez, Mar

2011-01-01

A central issue of myogenesis is the acquisition of identity by individual muscles. In Drosophila, at the time muscle progenitors are singled out, they already express unique combinations of muscle identity genes. This muscle code results from the integration of positional and temporal signalling inputs. Here we identify, by means of loss-of-function and ectopic expression approaches, the Iroquois Complex homeobox genes araucan and caupolican as novel muscle identity genes that confer lateral transverse muscle identity. The acquisition of this fate requires that Araucan/Caupolican repress other muscle identity genes such as slouch and vestigial. In addition, we show that Caupolican-dependent slouch expression depends on the activation state of the Ras/Mitogen Activated Protein Kinase cascade. This provides a comprehensive insight into the way Iroquois genes integrate in muscle progenitors, signalling inputs that modulate gene expression and protein activity. PMID:21811416

Integrative Analysis Reveals Relationships of Genetic and Epigenetic Alterations in Osteosarcoma

PubMed Central

Skårn, Magne; Namløs, Heidi M.; Barragan-Polania, Ana H.; Cleton-Jansen, Anne-Marie; Serra, Massimo; Liestøl, Knut; Hogendoorn, Pancras C. W.; Hovig, Eivind; Myklebost, Ola; Meza-Zepeda, Leonardo A.

2012-01-01

Background Osteosarcomas are the most common non-haematological primary malignant tumours of bone, and all conventional osteosarcomas are high-grade tumours showing complex genomic aberrations. We have integrated genome-wide genetic and epigenetic profiles from the EuroBoNeT panel of 19 human osteosarcoma cell lines based on microarray technologies. Principal Findings The cell lines showed complex patterns of DNA copy number changes, where genomic copy number gains were significantly associated with gene-rich regions and losses with gene-poor regions. By integrating the datasets, 350 genes were identified as having two types of aberrations (gain/over-expression, hypo-methylation/over-expression, loss/under-expression or hyper-methylation/under-expression) using a recurrence threshold of 6/19 (>30%) cell lines. The genes showed in general alterations in either DNA copy number or DNA methylation, both within individual samples and across the sample panel. These 350 genes are involved in embryonic skeletal system development and morphogenesis, as well as remodelling of extracellular matrix. The aberrations of three selected genes, CXCL5, DLX5 and RUNX2, were validated in five cell lines and five tumour samples using PCR techniques. Several genes were hyper-methylated and under-expressed compared to normal osteoblasts, and expression could be reactivated by demethylation using 5-Aza-2′-deoxycytidine treatment for four genes tested; AKAP12, CXCL5, EFEMP1 and IL11RA. Globally, there was as expected a significant positive association between gain and over-expression, loss and under-expression as well as hyper-methylation and under-expression, but gain was also associated with hyper-methylation and under-expression, suggesting that hyper-methylation may oppose the effects of increased copy number for detrimental genes. Conclusions Integrative analysis of genome-wide genetic and epigenetic alterations identified dependencies and relationships between DNA copy number, DNA methylation and mRNA expression in osteosarcomas, contributing to better understanding of osteosarcoma biology. PMID:23144859

Identification of candidate genes in osteoporosis by integrated microarray analysis.

PubMed

Li, J J; Wang, B Q; Fei, Q; Yang, Y; Li, D

2016-12-01

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594-601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1. © 2016 Fei et al.

Integrated analysis of DNA-methylation and gene expression using high-dimensional penalized regression: a cohort study on bone mineral density in postmenopausal women.

PubMed

Lien, Tonje G; Borgan, Ørnulf; Reppe, Sjur; Gautvik, Kaare; Glad, Ingrid Kristine

2018-03-07

Using high-dimensional penalized regression we studied genome-wide DNA-methylation in bone biopsies of 80 postmenopausal women in relation to their bone mineral density (BMD). The women showed BMD varying from severely osteoporotic to normal. Global gene expression data from the same individuals was available, and since DNA-methylation often affects gene expression, the overall aim of this paper was to include both of these omics data sets into an integrated analysis. The classical penalized regression uses one penalty, but we incorporated individual penalties for each of the DNA-methylation sites. These individual penalties were guided by the strength of association between DNA-methylations and gene transcript levels. DNA-methylations that were highly associated to one or more transcripts got lower penalties and were therefore favored compared to DNA-methylations showing less association to expression. Because of the complex pathways and interactions among genes, we investigated both the association between DNA-methylations and their corresponding cis gene, as well as the association between DNA-methylations and trans-located genes. Two integrating penalized methods were used: first, an adaptive group-regularized ridge regression, and secondly, variable selection was performed through a modified version of the weighted lasso. When information from gene expressions was integrated, predictive performance was considerably improved, in terms of predictive mean square error, compared to classical penalized regression without data integration. We found a 14.7% improvement in the ridge regression case and a 17% improvement for the lasso case. Our version of the weighted lasso with data integration found a list of 22 interesting methylation sites. Several corresponded to genes that are known to be important in bone formation. Using BMD as response and these 22 methylation sites as covariates, least square regression analyses resulted in R 2 =0.726, comparable to an average R 2 =0.438 for 10000 randomly selected groups of DNA-methylations with group size 22. Two recent types of penalized regression methods were adapted to integrate DNA-methylation and their association to gene expression in the analysis of bone mineral density. In both cases predictions clearly benefit from including the additional information on gene expressions.

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction.

PubMed

Yu, Yao; Tu, Kang; Zheng, Siyuan; Li, Yun; Ding, Guohui; Ping, Jie; Hao, Pei; Li, Yixue

2009-08-25

In the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches. In our work, we integrated gene expression information from Gene Expression Omnibus (GEO), biomedical ontology from Medical Subject Headings (MeSH) and signaling pathway knowledge from sigPathway entries to develop a context mining tool for gene expression analysis - GEOGLE. GEOGLE offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, GDS IDs, gene IDs, pathway names and signature list. Moreover, GEOGLE summarizes the signature genes from a subset of GDSes and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value. This approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. GEOGLE is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. The web site and user guide of GEOGLE are available at: http://omics.biosino.org:14000/kweb/workflow.jsp?id=00020.

Integrative Analysis Reveals Regulatory Programs in Endometriosis

PubMed Central

Yang, Huan; Kang, Kai; Cheng, Chao; Mamillapalli, Ramanaiah; Taylor, Hugh S.

2015-01-01

Endometriosis is a common gynecological disease found in approximately 10% of reproductive-age women. Gene expression analysis has been performed to explore alterations in gene expression associated with endometriosis; however, the underlying transcription factors (TFs) governing such expression changes have not been investigated in a systematic way. In this study, we propose a method to integrate gene expression with TF binding data and protein–protein interactions to construct an integrated regulatory network (IRN) for endometriosis. The IRN has shown that the most regulated gene in endometriosis is RUNX1, which is targeted by 14 of 26 TFs also involved in endometriosis. Using 2 published cohorts, GSE7305 (Hover, n = 20) and GSE7307 (Roth, n = 36) from the Gene Expression Omnibus database, we identified a network of TFs, which bind to target genes that are differentially expressed in endometriosis. Enrichment analysis based on the hypergeometric distribution allowed us to predict the TFs involved in endometriosis (n = 40). This included known TFs such as androgen receptor (AR) and critical factors in the pathology of endometriosis, estrogen receptor α, and estrogen receptor β. We also identified several new ones from which we selected FOXA2 and TFAP2C, and their regulation was confirmed by quantitative real-time polymerase chain reaction and immunohistochemistry (IHC). Further, our analysis revealed that the function of AR and p53 in endometriosis is regulated by posttranscriptional changes and not by differential gene expression. Our integrative analysis provides new insights into the regulatory programs involved in endometriosis. PMID:26134036

CHESS (CgHExpreSS): a comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome.

PubMed

Lee, Mikyung; Kim, Yangseok

2009-12-16

Genomic alterations frequently occur in many cancer patients and play important mechanistic roles in the pathogenesis of cancer. Furthermore, they can modify the expression level of genes due to altered copy number in the corresponding region of the chromosome. An accumulating body of evidence supports the possibility that strong genome-wide correlation exists between DNA content and gene expression. Therefore, more comprehensive analysis is needed to quantify the relationship between genomic alteration and gene expression. A well-designed bioinformatics tool is essential to perform this kind of integrative analysis. A few programs have already been introduced for integrative analysis. However, there are many limitations in their performance of comprehensive integrated analysis using published software because of limitations in implemented algorithms and visualization modules. To address this issue, we have implemented the Java-based program CHESS to allow integrative analysis of two experimental data sets: genomic alteration and genome-wide expression profile. CHESS is composed of a genomic alteration analysis module and an integrative analysis module. The genomic alteration analysis module detects genomic alteration by applying a threshold based method or SW-ARRAY algorithm and investigates whether the detected alteration is phenotype specific or not. On the other hand, the integrative analysis module measures the genomic alteration's influence on gene expression. It is divided into two separate parts. The first part calculates overall correlation between comparative genomic hybridization ratio and gene expression level by applying following three statistical methods: simple linear regression, Spearman rank correlation and Pearson's correlation. In the second part, CHESS detects the genes that are differentially expressed according to the genomic alteration pattern with three alternative statistical approaches: Student's t-test, Fisher's exact test and Chi square test. By successive operations of two modules, users can clarify how gene expression levels are affected by the phenotype specific genomic alterations. As CHESS was developed in both Java application and web environments, it can be run on a web browser or a local machine. It also supports all experimental platforms if a properly formatted text file is provided to include the chromosomal position of probes and their gene identifiers. CHESS is a user-friendly tool for investigating disease specific genomic alterations and quantitative relationships between those genomic alterations and genome-wide gene expression profiling.

Digoxin reveals a functional connection between HIV-1 integration preference and T-cell activation.

PubMed

Zhyvoloup, Alexander; Melamed, Anat; Anderson, Ian; Planas, Delphine; Lee, Chen-Hsuin; Kriston-Vizi, Janos; Ketteler, Robin; Merritt, Andy; Routy, Jean-Pierre; Ancuta, Petronela; Bangham, Charles R M; Fassati, Ariberto

2017-07-01

HIV-1 integrates more frequently into transcribed genes, however the biological significance of HIV-1 integration targeting has remained elusive. Using a selective high-throughput chemical screen, we discovered that the cardiac glycoside digoxin inhibits wild-type HIV-1 infection more potently than HIV-1 bearing a single point mutation (N74D) in the capsid protein. We confirmed that digoxin repressed viral gene expression by targeting the cellular Na+/K+ ATPase, but this did not explain its selectivity. Parallel RNAseq and integration mapping in infected cells demonstrated that digoxin inhibited expression of genes involved in T-cell activation and cell metabolism. Analysis of >400,000 unique integration sites showed that WT virus integrated more frequently than N74D mutant within or near genes susceptible to repression by digoxin and involved in T-cell activation and cell metabolism. Two main gene networks down-regulated by the drug were CD40L and CD38. Blocking CD40L by neutralizing antibodies selectively inhibited WT virus infection, phenocopying digoxin. Thus the selectivity of digoxin depends on a combination of integration targeting and repression of specific gene networks. The drug unmasked a functional connection between HIV-1 integration and T-cell activation. Our results suggest that HIV-1 evolved integration site selection to couple its early gene expression with the status of target CD4+ T-cells, which may affect latency and viral reactivation.

Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies.

PubMed

Martini, Paolo; Risso, Davide; Sales, Gabriele; Romualdi, Chiara; Lanfranchi, Gerolamo; Cagnin, Stefano

2011-04-11

In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant differentially expressed genes. Later, researchers moved toward the systematic integration of gene expression profiles with additional biological information, such as chromosomal location, ontological annotations or sequence features. The analysis of gene expression linked to physical location of genes on chromosomes allows the identification of transcriptionally imbalanced regions, while, Gene Set Analysis focuses on the detection of coordinated changes in transcriptional levels among sets of biologically related genes. In this field, meta-analysis offers the possibility to compare different studies, addressing the same biological question to fully exploit public gene expression datasets. We describe STEPath, a method that starts from gene expression profiles and integrates the analysis of imbalanced region as an a priori step before performing gene set analysis. The application of STEPath in individual studies produced gene set scores weighted by chromosomal activation. As a final step, we propose a way to compare these scores across different studies (meta-analysis) on related biological issues. One complication with meta-analysis is batch effects, which occur because molecular measurements are affected by laboratory conditions, reagent lots and personnel differences. Major problems occur when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. We evaluated the power of combining chromosome mapping and gene set enrichment analysis, performing the analysis on a dataset of leukaemia (example of individual study) and on a dataset of skeletal muscle diseases (meta-analysis approach). In leukaemia, we identified the Hox gene set, a gene set closely related to the pathology that other algorithms of gene set analysis do not identify, while the meta-analysis approach on muscular disease discriminates between related pathologies and correlates similar ones from different studies. STEPath is a new method that integrates gene expression profiles, genomic co-expressed regions and the information about the biological function of genes. The usage of the STEPath-computed gene set scores overcomes batch effects in the meta-analysis approaches allowing the direct comparison of different pathologies and different studies on a gene set activation level.

Exploring candidate biomarkers for lung and prostate cancers using gene expression and flux variability analysis.

PubMed

Asgari, Yazdan; Khosravi, Pegah; Zabihinpour, Zahra; Habibi, Mahnaz

2018-02-19

Genome-scale metabolic models have provided valuable resources for exploring changes in metabolism under normal and cancer conditions. However, metabolism itself is strongly linked to gene expression, so integration of gene expression data into metabolic models might improve the detection of genes involved in the control of tumor progression. Herein, we considered gene expression data as extra constraints to enhance the predictive powers of metabolic models. We reconstructed genome-scale metabolic models for lung and prostate, under normal and cancer conditions to detect the major genes associated with critical subsystems during tumor development. Furthermore, we utilized gene expression data in combination with an information theory-based approach to reconstruct co-expression networks of the human lung and prostate in both cohorts. Our results revealed 19 genes as candidate biomarkers for lung and prostate cancer cells. This study also revealed that the development of a complementary approach (integration of gene expression and metabolic profiles) could lead to proposing novel biomarkers and suggesting renovated cancer treatment strategies which have not been possible to detect using either of the methods alone.

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis

PubMed Central

Guardia, Gabriela D. A.; Pires, Luís Ferreira; Vêncio, Ricardo Z. N.; Malmegrim, Kelen C. R.; de Farias, Cléver R. G.

2015-01-01

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis. PMID:26207740

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

PubMed

Guardia, Gabriela D A; Pires, Luís Ferreira; Vêncio, Ricardo Z N; Malmegrim, Kelen C R; de Farias, Cléver R G

2015-01-01

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

CGO: utilizing and integrating gene expression microarray data in clinical research and data management.

PubMed

Bumm, Klaus; Zheng, Mingzhong; Bailey, Clyde; Zhan, Fenghuang; Chiriva-Internati, M; Eddlemon, Paul; Terry, Julian; Barlogie, Bart; Shaughnessy, John D

2002-02-01

Clinical GeneOrganizer (CGO) is a novel windows-based archiving, organization and data mining software for the integration of gene expression profiling in clinical medicine. The program implements various user-friendly tools and extracts data for further statistical analysis. This software was written for Affymetrix GeneChip *.txt files, but can also be used for any other microarray-derived data. The MS-SQL server version acts as a data mart and links microarray data with clinical parameters of any other existing database and therefore represents a valuable tool for combining gene expression analysis and clinical disease characteristics.

Finding gene regulatory network candidates using the gene expression knowledge base.

PubMed

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis.

PubMed

Shchetynsky, Klementy; Diaz-Gallo, Lina-Marcella; Folkersen, Lasse; Hensvold, Aase Haj; Catrina, Anca Irinel; Berg, Louise; Klareskog, Lars; Padyukov, Leonid

2017-02-02

Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of "connector" genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA.

Integration of multi-omics data for integrative gene regulatory network inference.

PubMed

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun; Kang, Mingon

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called 'multi-omics data', that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN's capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed.

Integration of multi-omics data for integrative gene regulatory network inference

PubMed Central

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called ‘multi-omics data’, that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN’s capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed. PMID:29354189

Integration of high-risk human papillomavirus into cellular cancer-related genes in head and neck cancer cell lines.

PubMed

Walline, Heather M; Goudsmit, Christine M; McHugh, Jonathan B; Tang, Alice L; Owen, John H; Teh, Bin T; McKean, Erin; Glover, Thomas W; Graham, Martin P; Prince, Mark E; Chepeha, Douglas B; Chinn, Steven B; Ferris, Robert L; Gollin, Susanne M; Hoffmann, Thomas K; Bier, Henning; Brakenhoff, Ruud; Bradford, Carol R; Carey, Thomas E

2017-05-01

Human papillomavirus (HPV)-positive oropharyngeal cancer is generally associated with excellent response to therapy, but some HPV-positive tumors progress despite aggressive therapy. The purpose of this study was to evaluate viral oncogene expression and viral integration sites in HPV16- and HPV18-positive squamous cell carcinoma lines. E6/E7 alternate transcripts were assessed by reverse transcriptase-polymerase chain reaction (RT-PCR). Detection of integrated papillomavirus sequences (DIPS-PCR) and sequencing identified viral insertion sites and affected host genes. Cellular gene expression was assessed across viral integration sites. All HPV-positive cell lines expressed alternate HPVE6/E7 splicing indicative of active viral oncogenesis. HPV integration occurred within cancer-related genes TP63, DCC, JAK1, TERT, ATR, ETV6, PGR, PTPRN2, and TMEM237 in 8 head and neck squamous cell carcinoma (HNSCC) lines but UM-SCC-105 and UM-GCC-1 had only intergenic integration. HPV integration into cancer-related genes occurred in 7 of 9 HPV-positive cell lines and of these 6 were from tumors that progressed. HPV integration into cancer-related genes may be a secondary carcinogenic driver in HPV-driven tumors. © 2017 Wiley Periodicals, Inc. Head Neck 39: 840-852, 2017. © 2017 Wiley Periodicals, Inc.

Gene-specific cell labeling using MiMIC transposons

PubMed Central

Gnerer, Joshua P.; Venken, Koen J. T.; Dierick, Herman A.

2015-01-01

Binary expression systems such as GAL4/UAS, LexA/LexAop and QF/QUAS have greatly enhanced the power of Drosophila as a model organism by allowing spatio-temporal manipulation of gene function as well as cell and neural circuit function. Tissue-specific expression of these heterologous transcription factors relies on random transposon integration near enhancers or promoters that drive the binary transcription factor embedded in the transposon. Alternatively, gene-specific promoter elements are directly fused to the binary factor within the transposon followed by random or site-specific integration. However, such insertions do not consistently recapitulate endogenous expression. We used Minos-Mediated Integration Cassette (MiMIC) transposons to convert host loci into reliable gene-specific binary effectors. MiMIC transposons allow recombinase-mediated cassette exchange to modify the transposon content. We developed novel exchange cassettes to convert coding intronic MiMIC insertions into gene-specific binary factor protein-traps. In addition, we expanded the set of binary factor exchange cassettes available for non-coding intronic MiMIC insertions. We show that binary factor conversions of different insertions in the same locus have indistinguishable expression patterns, suggesting that they reliably reflect endogenous gene expression. We show the efficacy and broad applicability of these new tools by dissecting the cellular expression patterns of the Drosophila serotonin receptor gene family. PMID:25712101

Digoxin reveals a functional connection between HIV-1 integration preference and T-cell activation

PubMed Central

Planas, Delphine; Merritt, Andy; Routy, Jean-Pierre; Ancuta, Petronela; Bangham, Charles R. M.

2017-01-01

HIV-1 integrates more frequently into transcribed genes, however the biological significance of HIV-1 integration targeting has remained elusive. Using a selective high-throughput chemical screen, we discovered that the cardiac glycoside digoxin inhibits wild-type HIV-1 infection more potently than HIV-1 bearing a single point mutation (N74D) in the capsid protein. We confirmed that digoxin repressed viral gene expression by targeting the cellular Na+/K+ ATPase, but this did not explain its selectivity. Parallel RNAseq and integration mapping in infected cells demonstrated that digoxin inhibited expression of genes involved in T-cell activation and cell metabolism. Analysis of >400,000 unique integration sites showed that WT virus integrated more frequently than N74D mutant within or near genes susceptible to repression by digoxin and involved in T-cell activation and cell metabolism. Two main gene networks down-regulated by the drug were CD40L and CD38. Blocking CD40L by neutralizing antibodies selectively inhibited WT virus infection, phenocopying digoxin. Thus the selectivity of digoxin depends on a combination of integration targeting and repression of specific gene networks. The drug unmasked a functional connection between HIV-1 integration and T-cell activation. Our results suggest that HIV-1 evolved integration site selection to couple its early gene expression with the status of target CD4+ T-cells, which may affect latency and viral reactivation. PMID:28727807

Expression of hygromycin B resistance in oyster culinary-medicinal mushroom, Pleurotus ostreatus (Jacq.:Fr.)P. Kumm. (higher Basidiomycetes) using three gene expression systems.

PubMed

Dong, Xiaoya; Zhang, Ke; Gao, Yuqian; Qi, Yuancheng; Shen, Jinwen; Qiu, Liyou

2012-01-01

Three hygromycin B phosphotransferase (hph) gene expression systems for culinary-medicinal Oyster mushroom, Pleurotus ostreatus, plasmid pSHC, pAN7-1, and pBHt1 were evaluated through PEG/CaCl(2)-mediated protoplast transformation. Plasmid pSHC is a newly constructed hph gene expression system, composed of Escherichia coli hph gene, the P. ostreatus sdi promoter, and the CaMV35S terminator. The vector pAN7-1 was commonly used for integrative transformation in filamentous fungi. Plasmid pBHtl is a T-DNA binary vector, usually introduced into fungi by Agrobacterium-mediated transformation. The results showed that plasmids pSHC, pAN7-1, and pBHt1 were all integrated into the host chromosomes and expressed hygromycin B resistance in P. ostreatus. pAN7-1 had the highest transformation efficiency and hph gene expression level, pSHC the second, and pBHt1 the lowest. Growth rates of the transformants on plates containing hygromycin B were in correspondence with their hph gene expression levels. To our knowledge, this is the first report on integrated transformation of plasmid pAN7-1 and pBHt1 in P. ostreatus.

Assessing the potential for AAV vector genotoxicity in a murine model

PubMed Central

Li, Hojun; Malani, Nirav; Hamilton, Shari R.; Schlachterman, Alexander; Bussadori, Giulio; Edmonson, Shyrie E.; Shah, Rachel; Arruda, Valder R.; Mingozzi, Federico; Fraser Wright, J.; Bushman, Frederic D.

2011-01-01

Gene transfer using adeno-associated virus (AAV) vectors has great potential for treating human disease. Recently, questions have arisen about the safety of AAV vectors, specifically, whether integration of vector DNA in transduced cell genomes promotes tumor formation. This study addresses these questions with high-dose liver-directed AAV-mediated gene transfer in the adult mouse as a model (80 AAV-injected mice and 52 controls). After 18 months of follow-up, AAV-injected mice did not show a significantly higher rate of hepatocellular carcinoma compared with controls. Tumors in mice treated with AAV vectors did not have significantly different amounts of vector DNA compared with adjacent normal tissue. A novel high-throughput method for identifying AAV vector integration sites was developed and used to clone 1029 integrants. Integration patterns in tumor tissue and adjacent normal tissue were similar to each other, showing preferences for active genes, cytosine-phosphate-guanosine islands, and guanosine/cysteine-rich regions. Gene expression data showed that genes near integration sites did not show significant changes in expression patterns compared with genes more distal to integration sites. No integration events were identified as causing increased oncogene expression. Thus, we did not find evidence that AAV vectors cause insertional activation of oncogenes and subsequent tumor formation. PMID:21106988

Functional visualization and disruption of targeted genes using CRISPR/Cas9-mediated eGFP reporter integration in zebrafish.

PubMed

Ota, Satoshi; Taimatsu, Kiyohito; Yanagi, Kanoko; Namiki, Tomohiro; Ohga, Rie; Higashijima, Shin-Ichi; Kawahara, Atsuo

2016-10-11

The CRISPR/Cas9 complex, which is composed of a guide RNA (gRNA) and the Cas9 nuclease, is useful for carrying out genome modifications in various organisms. Recently, the CRISPR/Cas9-mediated locus-specific integration of a reporter, which contains the Mbait sequence targeted using Mbait-gRNA, the hsp70 promoter and the eGFP gene, has allowed the visualization of the target gene expression. However, it has not been ascertained whether the reporter integrations at both targeted alleles cause loss-of-function phenotypes in zebrafish. In this study, we have inserted the Mbait-hs-eGFP reporter into the pax2a gene because the disruption of pax2a causes the loss of the midbrain-hindbrain boundary (MHB) in zebrafish. In the heterozygous Tg[pax2a-hs:eGFP] embryos, MHB formed normally and the eGFP expression recapitulated the endogenous pax2a expression, including the MHB. We observed the loss of the MHB in homozygous Tg[pax2a-hs:eGFP] embryos. Furthermore, we succeeded in integrating the Mbait-hs-eGFP reporter into an uncharacterized gene epdr1. The eGFP expression in heterozygous Tg[epdr1-hs:eGFP] embryos overlapped the epdr1 expression, whereas the distribution of eGFP-positive cells was disorganized in the MHB of homozygous Tg[epdr1-hs:eGFP] embryos. We propose that the locus-specific integration of the Mbait-hs-eGFP reporter is a powerful method to investigate both gene expression profiles and loss-of-function phenotypes.

Functional visualization and disruption of targeted genes using CRISPR/Cas9-mediated eGFP reporter integration in zebrafish

PubMed Central

Ota, Satoshi; Taimatsu, Kiyohito; Yanagi, Kanoko; Namiki, Tomohiro; Ohga, Rie; Higashijima, Shin-ichi; Kawahara, Atsuo

2016-01-01

The CRISPR/Cas9 complex, which is composed of a guide RNA (gRNA) and the Cas9 nuclease, is useful for carrying out genome modifications in various organisms. Recently, the CRISPR/Cas9-mediated locus-specific integration of a reporter, which contains the Mbait sequence targeted using Mbait-gRNA, the hsp70 promoter and the eGFP gene, has allowed the visualization of the target gene expression. However, it has not been ascertained whether the reporter integrations at both targeted alleles cause loss-of-function phenotypes in zebrafish. In this study, we have inserted the Mbait-hs-eGFP reporter into the pax2a gene because the disruption of pax2a causes the loss of the midbrain-hindbrain boundary (MHB) in zebrafish. In the heterozygous Tg[pax2a-hs:eGFP] embryos, MHB formed normally and the eGFP expression recapitulated the endogenous pax2a expression, including the MHB. We observed the loss of the MHB in homozygous Tg[pax2a-hs:eGFP] embryos. Furthermore, we succeeded in integrating the Mbait-hs-eGFP reporter into an uncharacterized gene epdr1. The eGFP expression in heterozygous Tg[epdr1-hs:eGFP] embryos overlapped the epdr1 expression, whereas the distribution of eGFP-positive cells was disorganized in the MHB of homozygous Tg[epdr1-hs:eGFP] embryos. We propose that the locus-specific integration of the Mbait-hs-eGFP reporter is a powerful method to investigate both gene expression profiles and loss-of-function phenotypes. PMID:27725766

Plastids Are Major Regulators of Light Signaling in Arabidopsis1[W][OA

PubMed Central

Ruckle, Michael E.; Burgoon, Lyle D.; Lawrence, Lauren A.; Sinkler, Christopher A.; Larkin, Robert M.

2012-01-01

We previously provided evidence that plastid signaling regulates the downstream components of a light signaling network and that this signal integration coordinates chloroplast biogenesis with both the light environment and development by regulating gene expression. We tested these ideas by analyzing light- and plastid-regulated transcriptomes in Arabidopsis (Arabidopsis thaliana). We found that the enrichment of Gene Ontology terms in these transcriptomes is consistent with the integration of light and plastid signaling (1) down-regulating photosynthesis and inducing both repair and stress tolerance in dysfunctional chloroplasts and (2) helping coordinate processes such as growth, the circadian rhythm, and stress responses with the degree of chloroplast function. We then tested whether factors that contribute to this signal integration are also regulated by light and plastid signals by characterizing T-DNA insertion alleles of genes that are regulated by light and plastid signaling and that encode proteins that are annotated as contributing to signaling, transcription, or no known function. We found that a high proportion of these mutant alleles induce chloroplast biogenesis during deetiolation. We quantified the expression of four photosynthesis-related genes in seven of these enhanced deetiolation (end) mutants and found that photosynthesis-related gene expression is attenuated. This attenuation is particularly striking for Photosystem II subunit S expression. We conclude that the integration of light and plastid signaling regulates a number of END genes that help optimize chloroplast function and that at least some END genes affect photosynthesis-related gene expression. PMID:22383539

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

PubMed

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

2015-01-01

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

Stable long-term indigo production by overexpression of dioxygenase genes using a chromosomal integrated cascade expression circuit.

PubMed

Royo, Jose Luis; Moreno-Ruiz, Emilia; Cebolla, Angel; Santero, Eduardo

2005-03-16

In our laboratory we have analyzed different factors to maximize the yield in heterologous protein expression for long-term cultivation, by combination of an efficient cascade expression system and stable integration in the bacterial chromosome. In this work, we have explored this system for the production of indigo dye as a model for biotechnological production, by expressing in Escherichia coli the thnA1A2A3A4 genes from Sphingomonas macrogolitabida strain TFA, which encode the components of a tetralin dioxygenase activity. We compared Ptac, and the Pm-based cascade expression circuit in a multicopy plasmid and stably integrated into the bacterial chromosome. Plasmid-based expression systems resulted in instability of indigo production when serially diluted batch experiments were performed without a selective pressure. This problem was solved by integrating the expression module in the chromosome. Despite the gene dosage reduction, the synergic effect of the cascade expression system produced comparable expression to the dioxygenase activity in the plasmid configuration but could be stably maintained for at least 5 days. Here, we show that the cascade amplification circuit integrated in the chromosome could be an excellent system for tight control and stable production of recombinant products.

SZDB: A Database for Schizophrenia Genetic Research

PubMed Central

Wu, Yong; Yao, Yong-Gang

2017-01-01

Abstract Schizophrenia (SZ) is a debilitating brain disorder with a complex genetic architecture. Genetic studies, especially recent genome-wide association studies (GWAS), have identified multiple variants (loci) conferring risk to SZ. However, how to efficiently extract meaningful biological information from bulk genetic findings of SZ remains a major challenge. There is a pressing need to integrate multiple layers of data from various sources, eg, genetic findings from GWAS, copy number variations (CNVs), association and linkage studies, gene expression, protein–protein interaction (PPI), co-expression, expression quantitative trait loci (eQTL), and Encyclopedia of DNA Elements (ENCODE) data, to provide a comprehensive resource to facilitate the translation of genetic findings into SZ molecular diagnosis and mechanism study. Here we developed the SZDB database (http://www.szdb.org/), a comprehensive resource for SZ research. SZ genetic data, gene expression data, network-based data, brain eQTL data, and SNP function annotation information were systematically extracted, curated and deposited in SZDB. In-depth analyses and systematic integration were performed to identify top prioritized SZ genes and enriched pathways. Multiple types of data from various layers of SZ research were systematically integrated and deposited in SZDB. In-depth data analyses and integration identified top prioritized SZ genes and enriched pathways. We further showed that genes implicated in SZ are highly co-expressed in human brain and proteins encoded by the prioritized SZ risk genes are significantly interacted. The user-friendly SZDB provides high-confidence candidate variants and genes for further functional characterization. More important, SZDB provides convenient online tools for data search and browse, data integration, and customized data analyses. PMID:27451428

An Integrated Bioinformatics Approach Identifies Elevated Cyclin E2 Expression and E2F Activity as Distinct Features of Tamoxifen Resistant Breast Tumors

PubMed Central

Huang, Lei; Zhao, Shuangping; Frasor, Jonna M.; Dai, Yang

2011-01-01

Approximately half of estrogen receptor (ER) positive breast tumors will fail to respond to endocrine therapy. Here we used an integrative bioinformatics approach to analyze three gene expression profiling data sets from breast tumors in an attempt to uncover underlying mechanisms contributing to the development of resistance and potential therapeutic strategies to counteract these mechanisms. Genes that are differentially expressed in tamoxifen resistant vs. sensitive breast tumors were identified from three different publically available microarray datasets. These differentially expressed (DE) genes were analyzed using gene function and gene set enrichment and examined in intrinsic subtypes of breast tumors. The Connectivity Map analysis was utilized to link gene expression profiles of tamoxifen resistant tumors to small molecules and validation studies were carried out in a tamoxifen resistant cell line. Despite little overlap in genes that are differentially expressed in tamoxifen resistant vs. sensitive tumors, a high degree of functional similarity was observed among the three datasets. Tamoxifen resistant tumors displayed enriched expression of genes related to cell cycle and proliferation, as well as elevated activity of E2F transcription factors, and were highly correlated with a Luminal intrinsic subtype. A number of small molecules, including phenothiazines, were found that induced a gene signature in breast cancer cell lines opposite to that found in tamoxifen resistant vs. sensitive tumors and the ability of phenothiazines to down-regulate cyclin E2 and inhibit proliferation of tamoxifen resistant breast cancer cells was validated. Our findings demonstrate that an integrated bioinformatics approach to analyze gene expression profiles from multiple breast tumor datasets can identify important biological pathways and potentially novel therapeutic options for tamoxifen-resistant breast cancers. PMID:21789246

Metabolic Adaptation to Nutrients Involves Coregulation of Gene Expression by the RNA Helicase Dbp2 and the Cyc8 Corepressor in Saccharomyces cerevisiae.

PubMed

Wang, Siwen; Xing, Zheng; Pascuzzi, Pete E; Tran, Elizabeth J

2017-07-05

Cells fine-tune their metabolic programs according to nutrient availability in order to maintain homeostasis. This is achieved largely through integrating signaling pathways and the gene expression program, allowing cells to adapt to nutritional change. Dbp2, a member of the DEAD-box RNA helicase family in Saccharomyces cerevisiae , has been proposed to integrate gene expression with cellular metabolism. Prior work from our laboratory has reported the necessity of DBP2 in proper gene expression, particularly for genes involved in glucose-dependent regulation. Here, by comparing differentially expressed genes in dbp2 ∆ to those of 700 other deletion strains from other studies, we find that CYC8 and TUP1 , which form a complex and inhibit transcription of numerous genes, corepress a common set of genes with DBP2 Gene ontology (GO) annotations reveal that these corepressed genes are related to cellular metabolism, including respiration, gluconeogenesis, and alternative carbon-source utilization genes. Consistent with a direct role in metabolic gene regulation, loss of either DBP2 or CYC8 results in increased cellular respiration rates. Furthermore, we find that corepressed genes have a propensity to be associated with overlapping long noncoding RNAs and that upregulation of these genes in the absence of DBP2 correlates with decreased binding of Cyc8 to these gene promoters. Taken together, this suggests that Dbp2 integrates nutrient availability with energy homeostasis by maintaining repression of glucose-repressed, Cyc8-targeted genes across the genome. Copyright © 2017 Wang et al.

ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

PubMed

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

ICan: An Integrated Co-Alteration Network to Identify Ovarian Cancer-Related Genes

PubMed Central

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Background Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. Results We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). Conclusion In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data. PMID:25803614

Integrating mean and variance heterogeneities to identify differentially expressed genes.

PubMed

Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

2016-12-06

In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment-wide significant MVDE genes. Our results indicate tremendous potential gain of integrating informative variance heterogeneity after adjusting for global confounders and background data structure. The proposed informative integration test better summarizes the impacts of condition change on expression distributions of susceptible genes than do the existent competitors. Therefore, particular attention should be paid to explicitly exploit the variance heterogeneity induced by condition change in functional genomics analysis.

Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells

PubMed Central

Pelleri, Maria Chiara; Cattani, Chiara; Vitale, Lorenza; Antonaros, Francesca; Strippoli, Pierluigi; Locatelli, Chiara; Cocchi, Guido; Piovesan, Allison; Caracausi, Maria

2018-01-01

Down syndrome (DS) is due to the presence of an extra full or partial chromosome 21 (Hsa21). The identification of genes contributing to DS pathogenesis could be the key to any rational therapy of the associated intellectual disability. We aim at generating quantitative transcriptome maps in DS integrating all gene expression profile datasets available for any cell type or tissue, to obtain a complete model of the transcriptome in terms of both expression values for each gene and segmental trend of gene expression along each chromosome. We used the TRAM (Transcriptome Mapper) software for this meta-analysis, comparing transcript expression levels and profiles between DS and normal brain, lymphoblastoid cell lines, blood cells, fibroblasts, thymus and induced pluripotent stem cells, respectively. TRAM combined, normalized, and integrated datasets from different sources and across diverse experimental platforms. The main output was a linear expression value that may be used as a reference for each of up to 37,181 mapped transcripts analyzed, related to both known genes and expression sequence tag (EST) clusters. An independent example in vitro validation of fibroblast transcriptome map data was performed through “Real-Time” reverse transcription polymerase chain reaction showing an excellent correlation coefficient (r = 0.93, p < 0.0001) with data obtained in silico. The availability of linear expression values for each gene allowed the testing of the gene dosage hypothesis of the expected 3:2 DS/normal ratio for Hsa21 as well as other human genes in DS, in addition to listing genes differentially expressed with statistical significance. Although a fraction of Hsa21 genes escapes dosage effects, Hsa21 genes are selectively over-expressed in DS samples compared to genes from other chromosomes, reflecting a decisive role in the pathogenesis of the syndrome. Finally, the analysis of chromosomal segments reveals a high prevalence of Hsa21 over-expressed segments over the other genomic regions, suggesting, in particular, a specific region on Hsa21 that appears to be frequently over-expressed (21q22). Our complete datasets are released as a new framework to investigate transcription in DS for individual genes as well as chromosomal segments in different cell types and tissues. PMID:29740474

Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals.

PubMed

Bourdon-Lacombe, Julie A; Moffat, Ivy D; Deveau, Michelle; Husain, Mainul; Auerbach, Scott; Krewski, Daniel; Thomas, Russell S; Bushel, Pierre R; Williams, Andrew; Yauk, Carole L

2015-07-01

Toxicogenomics promises to be an important part of future human health risk assessment of environmental chemicals. The application of gene expression profiles (e.g., for hazard identification, chemical prioritization, chemical grouping, mode of action discovery, and quantitative analysis of response) is growing in the literature, but their use in formal risk assessment by regulatory agencies is relatively infrequent. Although additional validations for specific applications are required, gene expression data can be of immediate use for increasing confidence in chemical evaluations. We believe that a primary reason for the current lack of integration is the limited practical guidance available for risk assessment specialists with limited experience in genomics. The present manuscript provides basic information on gene expression profiling, along with guidance on evaluating the quality of genomic experiments and data, and interpretation of results presented in the form of heat maps, pathway analyses and other common approaches. Moreover, potential ways to integrate information from gene expression experiments into current risk assessment are presented using published studies as examples. The primary objective of this work is to facilitate integration of gene expression data into human health risk assessments of environmental chemicals. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

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

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

[Development of a mouse cell line containing stably integrated copies of pMCLacI/Neo plasmid: a model for studying mutations in vitro].

PubMed

Lu, Y; Li, H; Fu, J

2000-04-01

To establish a suitable model for studying the different mechanisms of mutation between expressed and non-expressed genes in mammalian cells. The NIH3T3 cells were transfected with the linearized pMCLacI/Neo DNAs by liposome-mediated transfection, and grew in the presence of G418. One drug resistant cell clone was selected to proliferate and to be analyzed with Southern blot and RT-PCR analyses on its genomic DNAs. (1) Multiple copies of pMCLacI/Neo plasmid DNA were intactly integrated in the genomic DNAs of the cell clone. (2) One of lac I target genes in the integrated plasmid could be transcribed in the NIH3T3 cells while the other could not. (3) The pMCLacI/Neo plasmid DNA could be efficiently rescued from the genomic DNAs of the cell clone with the average rescue efficiency of 410 cfu/microg DNA. The NIH3T3 cell line containing copies of a stably integrated pMCLacI/Neo has been established. The two lacI target genes in the cell line could imitate the functional states of expressed and non-expressed genes in mammalian cells respectively. The cell line will be a useful model for studying the different mechanisms of mutation between expressed and non-expressed genes in mammalian cells.

aGEM: an integrative system for analyzing spatial-temporal gene-expression information

PubMed Central

Jiménez-Lozano, Natalia; Segura, Joan; Macías, José Ramón; Vega, Juanjo; Carazo, José María

2009-01-01

Motivation: The work presented here describes the ‘anatomical Gene-Expression Mapping (aGEM)’ Platform, a development conceived to integrate phenotypic information with the spatial and temporal distributions of genes expressed in the mouse. The aGEM Platform has been built by extending the Distributed Annotation System (DAS) protocol, which was originally designed to share genome annotations over the WWW. DAS is a client-server system in which a single client integrates information from multiple distributed servers. Results: The aGEM Platform provides information to answer three main questions. (i) Which genes are expressed in a given mouse anatomical component? (ii) In which mouse anatomical structures are a given gene or set of genes expressed? And (iii) is there any correlation among these findings? Currently, this Platform includes several well-known mouse resources (EMAGE, GXD and GENSAT), hosting gene-expression data mostly obtained from in situ techniques together with a broad set of image-derived annotations. Availability: The Platform is optimized for Firefox 3.0 and it is accessed through a friendly and intuitive display: http://agem.cnb.csic.es Contact: natalia@cnb.csic.es Supplementary information: Supplementary data are available at http://bioweb.cnb.csic.es/VisualOmics/aGEM/home.html and http://bioweb.cnb.csic.es/VisualOmics/index_VO.html and Bioinformatics online. PMID:19592395

Gene-specific cell labeling using MiMIC transposons.

PubMed

Gnerer, Joshua P; Venken, Koen J T; Dierick, Herman A

2015-04-30

Binary expression systems such as GAL4/UAS, LexA/LexAop and QF/QUAS have greatly enhanced the power of Drosophila as a model organism by allowing spatio-temporal manipulation of gene function as well as cell and neural circuit function. Tissue-specific expression of these heterologous transcription factors relies on random transposon integration near enhancers or promoters that drive the binary transcription factor embedded in the transposon. Alternatively, gene-specific promoter elements are directly fused to the binary factor within the transposon followed by random or site-specific integration. However, such insertions do not consistently recapitulate endogenous expression. We used Minos-Mediated Integration Cassette (MiMIC) transposons to convert host loci into reliable gene-specific binary effectors. MiMIC transposons allow recombinase-mediated cassette exchange to modify the transposon content. We developed novel exchange cassettes to convert coding intronic MiMIC insertions into gene-specific binary factor protein-traps. In addition, we expanded the set of binary factor exchange cassettes available for non-coding intronic MiMIC insertions. We show that binary factor conversions of different insertions in the same locus have indistinguishable expression patterns, suggesting that they reliably reflect endogenous gene expression. We show the efficacy and broad applicability of these new tools by dissecting the cellular expression patterns of the Drosophila serotonin receptor gene family. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integration of biological networks and gene expression data using Cytoscape

PubMed Central

Cline, Melissa S; Smoot, Michael; Cerami, Ethan; Kuchinsky, Allan; Landys, Nerius; Workman, Chris; Christmas, Rowan; Avila-Campilo, Iliana; Creech, Michael; Gross, Benjamin; Hanspers, Kristina; Isserlin, Ruth; Kelley, Ryan; Killcoyne, Sarah; Lotia, Samad; Maere, Steven; Morris, John; Ono, Keiichiro; Pavlovic, Vuk; Pico, Alexander R; Vailaya, Aditya; Wang, Peng-Liang; Adler, Annette; Conklin, Bruce R; Hood, Leroy; Kuiper, Martin; Sander, Chris; Schmulevich, Ilya; Schwikowski, Benno; Warner, Guy J; Ideker, Trey; Bader, Gary D

2013-01-01

Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape. PMID:17947979

Integration of somatic mutation, expression and functional data reveals potential driver genes predictive of breast cancer survival.

PubMed

Suo, Chen; Hrydziuszko, Olga; Lee, Donghwan; Pramana, Setia; Saputra, Dhany; Joshi, Himanshu; Calza, Stefano; Pawitan, Yudi

2015-08-15

Genome and transcriptome analyses can be used to explore cancers comprehensively, and it is increasingly common to have multiple omics data measured from each individual. Furthermore, there are rich functional data such as predicted impact of mutations on protein coding and gene/protein networks. However, integration of the complex information across the different omics and functional data is still challenging. Clinical validation, particularly based on patient outcomes such as survival, is important for assessing the relevance of the integrated information and for comparing different procedures. An analysis pipeline is built for integrating genomic and transcriptomic alterations from whole-exome and RNA sequence data and functional data from protein function prediction and gene interaction networks. The method accumulates evidence for the functional implications of mutated potential driver genes found within and across patients. A driver-gene score (DGscore) is developed to capture the cumulative effect of such genes. To contribute to the score, a gene has to be frequently mutated, with high or moderate mutational impact at protein level, exhibiting an extreme expression and functionally linked to many differentially expressed neighbors in the functional gene network. The pipeline is applied to 60 matched tumor and normal samples of the same patient from The Cancer Genome Atlas breast-cancer project. In clinical validation, patients with high DGscores have worse survival than those with low scores (P = 0.001). Furthermore, the DGscore outperforms the established expression-based signatures MammaPrint and PAM50 in predicting patient survival. In conclusion, integration of mutation, expression and functional data allows identification of clinically relevant potential driver genes in cancer. The documented pipeline including annotated sample scripts can be found in http://fafner.meb.ki.se/biostatwiki/driver-genes/. yudi.pawitan@ki.se Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

PubMed Central

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

2015-01-01

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

AlgU controls expression of virulence genes in Pseudomonas syringae pv. tomato DC3000

USDA-ARS?s Scientific Manuscript database

Plant pathogenic bacteria are able to integrate information about their environment and adjust gene expression to provide adaptive functions. AlgU, an ECF sigma factor encoded by Pseudomonas syringae, controls expression of genes for alginate biosynthesis and is active while the bacteria are associa...

GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data.

PubMed

Rue-Albrecht, Kévin; McGettigan, Paul A; Hernández, Belinda; Nalpas, Nicolas C; Magee, David A; Parnell, Andrew C; Gordon, Stephen V; MacHugh, David E

2016-03-11

Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.

Global Characterization of Protein-Altering Mutations in Prostate Cancer

DTIC Science & Technology

2012-08-01

observed, and assess prevalence; (3) Perform integrative analyses of somatic mutation with gene expression and copy number change data collected on the...v) completed CGH assays on 200 prostate cancers; (vi) initiated the integrated analyses of gene expression, copy number and mutation in prostate...histories of individual mutations within the progression of the cancer in which it was observed, and to assess the prevalence of candidate cancer genes

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

PubMed

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

2016-07-14

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.

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

Sleeping Beauty-baculovirus hybrid vectors for long-term gene expression in the eye.

PubMed

Turunen, Tytteli Anni Kaarina; Laakkonen, Johanna Päivikki; Alasaarela, Laura; Airenne, Kari Juhani; Ylä-Herttuala, Seppo

2014-01-01

A baculovirus vector is capable of efficiently transducing many nondiving and diving cell types. However, the potential of baculovirus is restricted for many gene delivery applications as a result of the transient gene expression that it mediates. The plasmid-based Sleeping Beauty (SB) transposon system integrates transgenes into target cell genome efficiently with a genomic integration pattern that is generally considered safer than the integration of many other integrating vectors; yet efficient delivery of therapeutic genes into cells of target tissues in vivo is a major challenge for nonviral gene therapy. In the present study, SB was introduced into baculovirus to obtain novel hybrid vectors that would combine the best features of the two vector systems (i.e. effective gene delivery and efficient integration into the genome), thus circumventing the major limitations of these vectors. We constructed and optimized SB-baculovirus hybrid vectors that bear either SB100x transposase or SB transposon in the forward or reverse orientations with respect to the viral backbone The functionality of the novel hybrid vectors was investigated in cell cultures and in a proof-of-concept study in the mouse eye. The hybrid vectors showed high and sustained transgene expression that remained stable and demonstrated no signs of decline during the 2 months follow-up in vitro. These results were verified in the mouse eye where persistent transgene expression was detected two months after intravitreal injection. Our results confirm that (i) SB-baculovirus hybrid vectors mediate long-term gene expression in vitro and in vivo, and (ii) the hybrid vectors are potential new tools for the treatment of ocular diseases. Copyright © 2014 John Wiley & Sons, Ltd.

Recombinant adeno-associated virus mediates a high level of gene transfer but less efficient integration in the K562 human hematopoietic cell line.

PubMed Central

Malik, P; McQuiston, S A; Yu, X J; Pepper, K A; Krall, W J; Podsakoff, G M; Kurtzman, G J; Kohn, D B

1997-01-01

We tested the ability of a recombinant adeno-associated virus (rAAV) vector to express and integrate exogenous DNA into human hematopoietic cells in the absence of selection. We developed an rAAV vector, AAV-tNGFR, carrying a truncated rat nerve growth factor receptor (tNGFR) cDNA as a cell surface reporter under the control of the Moloney murine leukemia virus (MoMuLV) long terminal repeat. An analogous MoMuLV-based retroviral vector (L-tNGFR) was used in parallel, and gene transfer and expression in human hematopoietic cells were assessed by flow cytometry and DNA analyses. Following gene transfer into K562 cells with AAV-tNGFR at a multiplicity of infection (MOI) of 13 infectious units (IU), 26 to 38% of cells expressed tNGFR on the surface early after transduction, but the proportion of tNGFR expressing cells steadily declined to 3.0 to 3.5% over 1 month of culture. At an MOI of 130 IU, nearly all cells expressed tNGFR immediately posttransduction, but the proportion of cells expressing tNGFR declined to 62% over 2 months of culture. The decline in the proportion of AAV-tNGFR-expressing cells was associated with ongoing losses of vector genomes. In contrast, K562 cells transduced with the retroviral vector L-tNGFR expressed tNGFR in a constant fraction. Integration analyses on clones showed that integration occurred at different sites. Integration frequencies were estimated at about 49% at an MOI of 130 and 2% at an MOI of 1.3. Transduction of primary human CD34+ progenitor cells by AAV-tNGFR was less efficient than with K562 cells and showed a declining percentage of cells expressing tNGFR over 2 weeks of culture. Thus, purified rAAV caused very high gene transfer and expression in human hematopoietic cells early after transduction, which steadily declined during cell passage in the absence of selection. Although the efficiency of integration was low, overall integration was markedly improved at a high MOI. While prolonged episomal persistence may be adequate for gene therapy of nondividing cells, a very high MOI or improvements in basic aspects of AAV-based vectors may be necessary to improve integration frequency in the rapidly dividing hematopoietic cell population. PMID:9032306

Recombinant adeno-associated virus mediates a high level of gene transfer but less efficient integration in the K562 human hematopoietic cell line.

PubMed

Malik, P; McQuiston, S A; Yu, X J; Pepper, K A; Krall, W J; Podsakoff, G M; Kurtzman, G J; Kohn, D B

1997-03-01

We tested the ability of a recombinant adeno-associated virus (rAAV) vector to express and integrate exogenous DNA into human hematopoietic cells in the absence of selection. We developed an rAAV vector, AAV-tNGFR, carrying a truncated rat nerve growth factor receptor (tNGFR) cDNA as a cell surface reporter under the control of the Moloney murine leukemia virus (MoMuLV) long terminal repeat. An analogous MoMuLV-based retroviral vector (L-tNGFR) was used in parallel, and gene transfer and expression in human hematopoietic cells were assessed by flow cytometry and DNA analyses. Following gene transfer into K562 cells with AAV-tNGFR at a multiplicity of infection (MOI) of 13 infectious units (IU), 26 to 38% of cells expressed tNGFR on the surface early after transduction, but the proportion of tNGFR expressing cells steadily declined to 3.0 to 3.5% over 1 month of culture. At an MOI of 130 IU, nearly all cells expressed tNGFR immediately posttransduction, but the proportion of cells expressing tNGFR declined to 62% over 2 months of culture. The decline in the proportion of AAV-tNGFR-expressing cells was associated with ongoing losses of vector genomes. In contrast, K562 cells transduced with the retroviral vector L-tNGFR expressed tNGFR in a constant fraction. Integration analyses on clones showed that integration occurred at different sites. Integration frequencies were estimated at about 49% at an MOI of 130 and 2% at an MOI of 1.3. Transduction of primary human CD34+ progenitor cells by AAV-tNGFR was less efficient than with K562 cells and showed a declining percentage of cells expressing tNGFR over 2 weeks of culture. Thus, purified rAAV caused very high gene transfer and expression in human hematopoietic cells early after transduction, which steadily declined during cell passage in the absence of selection. Although the efficiency of integration was low, overall integration was markedly improved at a high MOI. While prolonged episomal persistence may be adequate for gene therapy of nondividing cells, a very high MOI or improvements in basic aspects of AAV-based vectors may be necessary to improve integration frequency in the rapidly dividing hematopoietic cell population.

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.

PubMed

Liu, Wan-Ting; Wang, Yang; Zhang, Jing; Ye, Fei; Huang, Xiao-Hui; Li, Bin; He, Qing-Yu

2018-07-01

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA + /CDK1 + and CENPA + /CDC20 + were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

PubMed

Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Integrating Membrane Transport with Male Gametophyte Development and Function through Transcriptomics.

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

Bock KW; D Honys; JM. Ward

Male fertility depends on the proper development of the male gametophyte, successful pollen germination, tube growth and delivery of the sperm cells to the ovule. Previous studies have shown that nutrients like boron, and ion gradients or currents of Ca2+, H+, and K+ are critical for pollen tube growth. However, the molecular identities of transporters mediating these fluxes are mostly unknown. As a first step to integrate transport with pollen development and function, a genome-wide analysis of transporter genes expressed in the male gametophyte at four developmental stages was conducted. About 1269 genes encoding classified transporters were collected from themore » Arabidopsis thaliana genome. Of 757 transporter genes expressed in pollen, 16% or 124 genes, including AHA6, CNGC18, TIP1.3 and CHX08, are specifically or preferentially expressed relative to sporophytic tissues. Some genes are highly expressed in microspores and bicellular pollen (COPT3, STP2, OPT9); while others are activated only in tricellular or mature pollen (STP11, LHT7). Analyses of entire gene families showed that a subset of genes, including those expressed in sporophytic tissues, were developmentally-regulated during pollen maturation. Early and late expression patterns revealed by transcriptome analysis are supported by promoter::GUS analyses of CHX genes and by other methods. Recent genetic studies based on a few transporters, including plasma membrane H+ pump AHA3, Ca2+ pump ACA9, and K+ channel SPIK, further support the expression patterns and the inferred functions revealed by our analyses. Thus, revealing the distinct expression patterns of specific transporters and unknown polytopic proteins during microgametogenesis provides new insights for strategic mutant analyses necessary to integrate the roles of transporters and potential receptors with male gametophyte development.« less

Integrating membrane transport with male gametophyte development and function through transcriptomics.

PubMed

Bock, Kevin W; Honys, David; Ward, John M; Padmanaban, Senthilkumar; Nawrocki, Eric P; Hirschi, Kendal D; Twell, David; Sze, Heven

2006-04-01

Male fertility depends on the proper development of the male gametophyte, successful pollen germination, tube growth, and delivery of the sperm cells to the ovule. Previous studies have shown that nutrients like boron, and ion gradients or currents of Ca2+, H+, and K+ are critical for pollen tube growth. However, the molecular identities of transporters mediating these fluxes are mostly unknown. As a first step to integrate transport with pollen development and function, a genome-wide analysis of transporter genes expressed in the male gametophyte at four developmental stages was conducted. Approximately 1,269 genes encoding classified transporters were collected from the Arabidopsis (Arabidopsis thaliana) genome. Of 757 transporter genes expressed in pollen, 16% or 124 genes, including AHA6, CNGC18, TIP1.3, and CHX08, are specifically or preferentially expressed relative to sporophytic tissues. Some genes are highly expressed in microspores and bicellular pollen (COPT3, STP2, OPT9), while others are activated only in tricellular or mature pollen (STP11, LHT7). Analyses of entire gene families showed that a subset of genes, including those expressed in sporophytic tissues, was developmentally regulated during pollen maturation. Early and late expression patterns revealed by transcriptome analysis are supported by promoter::beta-glucuronidase analyses of CHX genes and by other methods. Recent genetic studies based on a few transporters, including plasma membrane H+ pump AHA3, Ca2+ pump ACA9, and K+ channel SPIK, further support the expression patterns and the inferred functions revealed by our analyses. Thus, revealing the distinct expression patterns of specific transporters and unknown polytopic proteins during microgametogenesis provides new insights for strategic mutant analyses necessary to integrate the roles of transporters and potential receptors with male gametophyte development.

Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

PubMed

Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

2016-06-01

Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Robustness, evolvability, and the logic of genetic regulation.

PubMed

Payne, Joshua L; Moore, Jason H; Wagner, Andreas

2014-01-01

In gene regulatory circuits, the expression of individual genes is commonly modulated by a set of regulating gene products, which bind to a gene's cis-regulatory region. This region encodes an input-output function, referred to as signal-integration logic, that maps a specific combination of regulatory signals (inputs) to a particular expression state (output) of a gene. The space of all possible signal-integration functions is vast and the mapping from input to output is many-to-one: For the same set of inputs, many functions (genotypes) yield the same expression output (phenotype). Here, we exhaustively enumerate the set of signal-integration functions that yield identical gene expression patterns within a computational model of gene regulatory circuits. Our goal is to characterize the relationship between robustness and evolvability in the signal-integration space of regulatory circuits, and to understand how these properties vary between the genotypic and phenotypic scales. Among other results, we find that the distributions of genotypic robustness are skewed, so that the majority of signal-integration functions are robust to perturbation. We show that the connected set of genotypes that make up a given phenotype are constrained to specific regions of the space of all possible signal-integration functions, but that as the distance between genotypes increases, so does their capacity for unique innovations. In addition, we find that robust phenotypes are (i) evolvable, (ii) easily identified by random mutation, and (iii) mutationally biased toward other robust phenotypes. We explore the implications of these latter observations for mutation-based evolution by conducting random walks between randomly chosen source and target phenotypes. We demonstrate that the time required to identify the target phenotype is independent of the properties of the source phenotype.

Transient GFP expression in Nicotiana plumbaginifolia suspension cells: the role of gene silencing, cell death and T-DNA loss.

PubMed

Weld, R; Heinemann, J; Eady, C

2001-03-01

The transient nature of T-DNA expression was studied with a gfp reporter gene transferred to Nicotiana plumbaginifolia suspension cells from Agrobacterium tumefaciens. Individual GFP-expressing protoplasts were isolated after 4 days' co-cultivation. The protoplasts were cultured without selection and 4 weeks later the surviving proto-calluses were again screened for GFP expression. Of the proto-calluses initially expressing GFP, 50% had lost detectable GFP activity during the first 4 weeks of culture. Multiple T-DNA copies of the gfp gene were detected in 10 of 17 proto-calluses lacking visible GFP activity. The remaining 7 cell lines contained no gfp sequences. Our results confirm that transiently expressed T-DNAs can be lost during growth of somatic cells and demonstrate that transiently expressing cells frequently integrate multiple T-DNAs that become silenced. In cells competent for DNA uptake, cell death and gene silencing were more important barriers to the recovery of stably expressing transformants than lack of T-DNA integration.

Global Characterization of Protein Altering Mutations in Prostate Cancer

DTIC Science & Technology

2011-08-01

integrative analyses of somatic mutation with gene expression and copy number change data collected on the same samples. To date, we have performed...implications for resistance to cancer therapeutics. We have also identified a subset of genes that appear to be recurrently mutated in our discovery set, and...integrative analyses of somatic mutation with gene expression and copy number change data collected on the same samples. Body This is a “synergy” project

cGRNB: a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets.

PubMed

Xu, Huayong; Yu, Hui; Tu, Kang; Shi, Qianqian; Wei, Chaochun; Li, Yuan-Yuan; Li, Yi-Xue

2013-01-01

We are witnessing rapid progress in the development of methodologies for building the combinatorial gene regulatory networks involving both TFs (Transcription Factors) and miRNAs (microRNAs). There are a few tools available to do these jobs but most of them are not easy to use and not accessible online. A web server is especially needed in order to allow users to upload experimental expression datasets and build combinatorial regulatory networks corresponding to their particular contexts. In this work, we compiled putative TF-gene, miRNA-gene and TF-miRNA regulatory relationships from forward-engineering pipelines and curated them as built-in data libraries. We streamlined the R codes of our two separate forward-and-reverse engineering algorithms for combinatorial gene regulatory network construction and formalized them as two major functional modules. As a result, we released the cGRNB (combinatorial Gene Regulatory Networks Builder): a web server for constructing combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. The cGRNB enables two major network-building modules, one for MPGE (miRNA-perturbed gene expression) datasets and the other for parallel miRNA/mRNA expression datasets. A miRNA-centered two-layer combinatorial regulatory cascade is the output of the first module and a comprehensive genome-wide network involving all three types of combinatorial regulations (TF-gene, TF-miRNA, and miRNA-gene) are the output of the second module. In this article we propose cGRNB, a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. Since parallel miRNA/mRNA expression datasets are rapidly accumulated by the advance of next-generation sequencing techniques, cGRNB will be very useful tool for researchers to build combinatorial gene regulatory networks based on expression datasets. The cGRNB web-server is free and available online at http://www.scbit.org/cgrnb.

Integrated data analysis reveals potential drivers and pathways disrupted by DNA methylation in papillary thyroid carcinomas.

PubMed

Beltrami, Caroline Moraes; Dos Reis, Mariana Bisarro; Barros-Filho, Mateus Camargo; Marchi, Fabio Albuquerque; Kuasne, Hellen; Pinto, Clóvis Antônio Lopes; Ambatipudi, Srikant; Herceg, Zdenko; Kowalski, Luiz Paulo; Rogatto, Silvia Regina

2017-01-01

Papillary thyroid carcinoma (PTC) is a common endocrine neoplasm with a recent increase in incidence in many countries. Although PTC has been explored by gene expression and DNA methylation studies, the regulatory mechanisms of the methylation on the gene expression was poorly clarified. In this study, DNA methylation profile (Illumina HumanMethylation 450K) of 41 PTC paired with non-neoplastic adjacent tissues (NT) was carried out to identify and contribute to the elucidation of the role of novel genic and intergenic regions beyond those described in the promoter and CpG islands (CGI). An integrative and cross-validation analysis were performed aiming to identify molecular drivers and pathways that are PTC-related. The comparisons between PTC and NT revealed 4995 methylated probes (88% hypomethylated in PTC) and 1446 differentially expressed transcripts cross-validated by the The Cancer Genome Atlas data. The majority of these probes was found in non-promoters regions, distant from CGI and enriched by enhancers. The integrative analysis between gene expression and DNA methylation revealed 185 and 38 genes (mainly in the promoter and body regions, respectively) with negative and positive correlation, respectively. Genes showing negative correlation underlined FGF and retinoic acid signaling as critical canonical pathways disrupted by DNA methylation in PTC. BRAF mutation was detected in 68% (28 of 41) of the tumors, which presented a higher level of demethylation (95% hypomethylated probes) compared with BRAF wild-type tumors. A similar integrative analysis uncovered 40 of 254 differentially expressed genes, which are potentially regulated by DNA methylation in BRAF V600E-positive tumors. The methylation and expression pattern of six selected genes ( ERBB3 , FGF1 , FGFR2 , GABRB2 , HMGA2 , and RDH5 ) were confirmed as altered by pyrosequencing and RT-qPCR. DNA methylation loss in non-promoter, poor CGI and enhancer-enriched regions was a significant event in PTC, especially in tumors harboring BRAF V600E. In addition to the promoter region, gene body and 3'UTR methylation have also the potential to influence the gene expression levels (both, repressing and inducing). The integrative analysis revealed genes potentially regulated by DNA methylation pointing out potential drivers and biomarkers related to PTC development.

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

PubMed

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

2017-03-02

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

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can improve detection power and discovery consistency through a concordant integrative analysis of multiple large-scale two-sample gene expression data sets.

Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples.

PubMed

Reiman, Mario; Laan, Maris; Rull, Kristiina; Sõber, Siim

2017-08-01

RNA degradation is a ubiquitous process that occurs in living and dead cells, as well as during handling and storage of extracted RNA. Reduced RNA quality caused by degradation is an established source of uncertainty for all RNA-based gene expression quantification techniques. RNA sequencing is an increasingly preferred method for transcriptome analyses, and dependence of its results on input RNA integrity is of significant practical importance. This study aimed to characterize the effects of varying input RNA integrity [estimated as RNA integrity number (RIN)] on transcript level estimates and delineate the characteristic differences between transcripts that differ in degradation rate. The study used ribodepleted total RNA sequencing data from a real-life clinically collected set ( n = 32) of human solid tissue (placenta) samples. RIN-dependent alterations in gene expression profiles were quantified by using DESeq2 software. Our results indicate that small differences in RNA integrity affect gene expression quantification by introducing a moderate and pervasive bias in expression level estimates that significantly affected 8.1% of studied genes. The rapidly degrading transcript pool was enriched in pseudogenes, short noncoding RNAs, and transcripts with extended 3' untranslated regions. Typical slowly degrading transcripts (median length, 2389 nt) represented protein coding genes with 4-10 exons and high guanine-cytosine content.-Reiman, M., Laan, M., Rull, K., Sõber, S. Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples. © FASEB.

Integrating Multiple Data Sources for Combinatorial Marker Discovery: A Study in Tumorigenesis.

PubMed

Bandyopadhyay, Sanghamitra; Mallik, Saurav

2018-01-01

Identification of combinatorial markers from multiple data sources is a challenging task in bioinformatics. Here, we propose a novel computational framework for identifying significant combinatorial markers ( s) using both gene expression and methylation data. The gene expression and methylation data are integrated into a single continuous data as well as a (post-discretized) boolean data based on their intrinsic (i.e., inverse) relationship. A novel combined score of methylation and expression data (viz., ) is introduced which is computed on the integrated continuous data for identifying initial non-redundant set of genes. Thereafter, (maximal) frequent closed homogeneous genesets are identified using a well-known biclustering algorithm applied on the integrated boolean data of the determined non-redundant set of genes. A novel sample-based weighted support ( ) is then proposed that is consecutively calculated on the integrated boolean data of the determined non-redundant set of genes in order to identify the non-redundant significant genesets. The top few resulting genesets are identified as potential s. Since our proposed method generates a smaller number of significant non-redundant genesets than those by other popular methods, the method is much faster than the others. Application of the proposed technique on an expression and a methylation data for Uterine tumor or Prostate Carcinoma produces a set of significant combination of markers. We expect that such a combination of markers will produce lower false positives than individual markers.

OpenFlyData: an exemplar data web integrating gene expression data on the fruit fly Drosophila melanogaster.

PubMed

Miles, Alistair; Zhao, Jun; Klyne, Graham; White-Cooper, Helen; Shotton, David

2010-10-01

Integrating heterogeneous data across distributed sources is a major requirement for in silico bioinformatics supporting translational research. For example, genome-scale data on patterns of gene expression in the fruit fly Drosophila melanogaster are widely used in functional genomic studies in many organisms to inform candidate gene selection and validate experimental results. However, current data integration solutions tend to be heavy weight, and require significant initial and ongoing investment of effort. Development of a common Web-based data integration infrastructure (a.k.a. data web), using Semantic Web standards, promises to alleviate these difficulties, but little is known about the feasibility, costs, risks or practical means of migrating to such an infrastructure. We describe the development of OpenFlyData, a proof-of-concept system integrating gene expression data on D. melanogaster, combining Semantic Web standards with light-weight approaches to Web programming based on Web 2.0 design patterns. To support researchers designing and validating functional genomic studies, OpenFlyData includes user-facing search applications providing intuitive access to and comparison of gene expression data from FlyAtlas, the BDGP in situ database, and FlyTED, using data from FlyBase to expand and disambiguate gene names. OpenFlyData's services are also openly accessible, and are available for reuse by other bioinformaticians and application developers. Semi-automated methods and tools were developed to support labour- and knowledge-intensive tasks involved in deploying SPARQL services. These include methods for generating ontologies and relational-to-RDF mappings for relational databases, which we illustrate using the FlyBase Chado database schema; and methods for mapping gene identifiers between databases. The advantages of using Semantic Web standards for biomedical data integration are discussed, as are open issues. In particular, although the performance of open source SPARQL implementations is sufficient to query gene expression data directly from user-facing applications such as Web-based data fusions (a.k.a. mashups), we found open SPARQL endpoints to be vulnerable to denial-of-service-type problems, which must be mitigated to ensure reliability of services based on this standard. These results are relevant to data integration activities in translational bioinformatics. The gene expression search applications and SPARQL endpoints developed for OpenFlyData are deployed at http://openflydata.org. FlyUI, a library of JavaScript widgets providing re-usable user-interface components for Drosophila gene expression data, is available at http://flyui.googlecode.com. Software and ontologies to support transformation of data from FlyBase, FlyAtlas, BDGP and FlyTED to RDF are available at http://openflydata.googlecode.com. SPARQLite, an implementation of the SPARQL protocol, is available at http://sparqlite.googlecode.com. All software is provided under the GPL version 3 open source license.

Genome-wide DNA methylation profiling integrated with gene expression profiling identifies PAX9 as a novel prognostic marker in chronic lymphocytic leukemia.

PubMed

Rani, Lata; Mathur, Nitin; Gupta, Ritu; Gogia, Ajay; Kaur, Gurvinder; Dhanjal, Jaspreet Kaur; Sundar, Durai; Kumar, Lalit; Sharma, Atul

2017-01-01

In chronic lymphocytic leukemia (CLL), epigenomic and genomic studies have expanded the existing knowledge about the disease biology and led to the identification of potential biomarkers relevant for implementation of personalized medicine. In this study, an attempt has been made to examine and integrate the global DNA methylation changes with gene expression profile and their impact on clinical outcome in early stage CLL patients. The integration of DNA methylation profile ( n  = 14) with the gene expression profile ( n  = 21) revealed 142 genes as hypermethylated-downregulated and; 62 genes as hypomethylated-upregulated in early stage CLL patients compared to CD19+ B-cells from healthy individuals. The mRNA expression levels of 17 genes identified to be differentially methylated and/or differentially expressed was further examined in early stage CLL patients ( n  = 93) by quantitative real time PCR (RQ-PCR). Significant differences were observed in the mRNA expression of MEIS1 , PMEPA1 , SOX7 , SPRY1 , CDK6 , TBX2 , and SPRY2 genes in CLL cells as compared to B-cells from healthy individuals. The analysis in the IGHV mutation based categories (Unmutated = 39, Mutated = 54) revealed significantly higher mRNA expression of CRY1 and PAX9 genes in the IGHV unmutated subgroup ( p  < 0.001). The relative risk of treatment initiation was significantly higher among patients with high expression of CRY1 (RR = 1.91, p  = 0.005) or PAX9 (RR = 1.87, p  = 0.001). High expression of CRY1 (HR: 3.53, p  < 0.001) or PAX9 (HR: 3.14, p  < 0.001) gene was significantly associated with shorter time to first treatment. The high expression of PAX9 gene (HR: 3.29, 95% CI 1.172-9.272, p  = 0.016) was also predictive of shorter overall survival in CLL. The DNA methylation changes associated with mRNA expression of CRY1 and PAX9 genes allow risk stratification of early stage CLL patients. This comprehensive analysis supports the concept that the epigenetic changes along with the altered expression of genes have the potential to predict clinical outcome in early stage CLL patients.

Transcriptional insulation of the human keratin 18 gene in transgenic mice.

PubMed Central

Neznanov, N; Thorey, I S; Ceceña, G; Oshima, R G

1993-01-01

Expression of the 10-kb human keratin 18 (K18) gene in transgenic mice results in efficient and appropriate tissue-specific expression in a variety of internal epithelial organs, including liver, lung, intestine, kidney, and the ependymal epithelium of brain, but not in spleen, heart, or skeletal muscle. Expression at the RNA level is directly proportional to the number of integrated K18 transgenes. These results indicate that the K18 gene is able to insulate itself both from the commonly observed cis-acting effects of the sites of integration and from the potential complications of duplicated copies of the gene arranged in head-to-tail fashion. To begin to identify the K18 gene sequences responsible for this property of transcriptional insulation, additional transgenic mouse lines containing deletions of either the 5' or 3' distal end of the K18 gene have been characterized. Deletion of 1.5 kb of the distal 5' flanking sequence has no effect upon either the tissue specificity or the copy number-dependent behavior of the transgene. In contrast, deletion of the 3.5-kb 3' flanking sequence of the gene results in the loss of the copy number-dependent behavior of the gene in liver and intestine. However, expression in kidney, lung, and brain remains efficient and copy number dependent in these transgenic mice. Furthermore, herpes simplex virus thymidine kinase gene expression is copy number dependent in transgenic mice when the gene is located between the distal 5'- and 3'-flanking sequences of the K18 gene. Each adult transgenic male expressed the thymidine kinase gene in testes and brain and proportionally to the number of integrated transgenes. We conclude that the characteristic of copy number-dependent expression of the K18 gene is tissue specific because the sequence requirements for transcriptional insulation in adult liver and intestine are different from those for lung and kidney. In addition, the behavior of the transgenic thymidine kinase gene in testes and brain suggests that the property of transcriptional insulation of the K18 gene may be conferred by the distal flanking sequences of the K18 gene and, additionally, may function for other genes. Images PMID:7681143

Quantitative analysis of lentiviral transgene expression in mice over seven generations.

PubMed

Wang, Yong; Song, Yong-tao; Liu, Qin; Liu, Cang'e; Wang, Lu-lu; Liu, Yu; Zhou, Xiao-yang; Wu, Jun; Wei, Hong

2010-10-01

Lentiviral transgenesis is now recognized as an extremely efficient and cost-effective method to produce transgenic animals. Transgenes delivered by lentiviral vectors exhibited inheritable expression in many species including those which are refractory to genetic modification such as non-human primates. However, epigenetic modification was frequently observed in lentiviral integrants, and transgene expression found to be inversely correlated with methylation density. Recent data showed that about one-third lentiviral integrants exhibited hypermethylation and low expression, but did not demonstrate whether those integrants with high expression could remain constant expression and hypomethylated during long term germline transmission. In this study, using lentiviral eGFP transgenic mice as the experimental animals, lentiviral eGFP expression levels and its integrant numbers in genome were quantitatively analyzed by fluorescent quantitative polymerase-chain reaction (FQ-PCR), using the house-keeping gene ribosomal protein S18 (Rps18) and the single copy gene fatty acid binding protein of the intestine (Fabpi) as the internal controls respectively. The methylation densities of the integrants were quantitatively analyzed by bisulfite sequencing. We found that the lentiviral integrants with high expression exhibited a relative constant expression level per integrant over at least seven generations. Besides, the individuals containing these integrants exhibited eGFP expression levels which were positively and almost linearly correlated with the integrant numbers in their genomes, suggesting that no remarkable position effect on transgene expression of the integrants analyzed was observed. In addition, over seven generations the methylation density of these integrants did not increase, but rather decreased remarkably, indicating that these high expressing integrants were not subjected to de novo methylation during at least seven generations of germline transmission. Taken together, these data suggested that transgenic lines with long term stable expression and no position effect can be established by lentiviral transgenesis.

Assessment of nematode resistance in wheat transgenic plants expressing potato proteinase inhibitor (PIN2) gene.

PubMed

Vishnudasan, Dalia; Tripathi, M N; Rao, Uma; Khurana, Paramjit

2005-10-01

Serine proteinase inhibitors (IP's) are proteins found naturally in a wide range of plants with a significant role in the natural defense system of plants against herbivores. The question addressed in the present study involves assessing the ability of the serine proteinase inhibitor in combating nematode infestation. The present study involves engineering a plant serine proteinase inhibitor (pin2) gene into T. durum PDW215 by Agrobacterium-mediated transformation to combat cereal cyst nematode (Heterodera avenae) infestation. Putative T(0) transformants were screened and positive segregating lines analysed further for the study of the stable integration, expression and segregation of the genes. PCR, Southern analysis along with bar gene expression studies corroborate the stable integration pattern of the respective genes. The transformation efficiency is 3%, while the frequency of escapes was 35.71%. chi(2) analysis reveals the stable integration and segregation of the genes in both the T(1) and T(2) progeny lines. The PIN2 systemic expression confers satisfactory nematode resistance. The correlation analysis suggests that at p < 0.05 level of significance the relative proteinase inhibitor (PI) values show a direct positive correlation vis-à-vis plant height, plant seed weight and also the seed number.

Integrated Analysis of Alzheimer's Disease and Schizophrenia Dataset Revealed Different Expression Pattern in Learning and Memory.

PubMed

Li, Wen-Xing; Dai, Shao-Xing; Liu, Jia-Qian; Wang, Qian; Li, Gong-Hua; Huang, Jing-Fei

2016-01-01

Alzheimer's disease (AD) and schizophrenia (SZ) are both accompanied by impaired learning and memory functions. This study aims to explore the expression profiles of learning or memory genes between AD and SZ. We downloaded 10 AD and 10 SZ datasets from GEO-NCBI for integrated analysis. These datasets were processed using RMA algorithm and a global renormalization for all studies. Then Empirical Bayes algorithm was used to find the differentially expressed genes between patients and controls. The results showed that most of the differentially expressed genes were related to AD whereas the gene expression profile was little affected in the SZ. Furthermore, in the aspects of the number of differentially expressed genes, the fold change and the brain region, there was a great difference in the expression of learning or memory related genes between AD and SZ. In AD, the CALB1, GABRA5, and TAC1 were significantly downregulated in whole brain, frontal lobe, temporal lobe, and hippocampus. However, in SZ, only two genes CRHBP and CX3CR1 were downregulated in hippocampus, and other brain regions were not affected. The effect of these genes on learning or memory impairment has been widely studied. It was suggested that these genes may play a crucial role in AD or SZ pathogenesis. The different gene expression patterns between AD and SZ on learning and memory functions in different brain regions revealed in our study may help to understand the different mechanism between two diseases.

Molecular Profile of Peripheral Blood Mononuclear Cells from Patients with Rheumatoid Arthritis

PubMed Central

Edwards, Christopher J; Feldman, Jeffrey L; Beech, Jonathan; Shields, Kathleen M; Stover, Jennifer A; Trepicchio, William L; Larsen, Glenn; Foxwell, Brian MJ; Brennan, Fionula M; Feldmann, Marc; Pittman, Debra D

2007-01-01

Rheumatoid arthritis (RA) is a chronic inflammatory arthritis. Currently, diagnosis of RA may take several weeks, and factors used to predict a poor prognosis are not always reliable. Gene expression in RA may consist of a unique signature. Gene expression analysis has been applied to synovial tissue to define molecularly distinct forms of RA; however, expression analysis of tissue taken from a synovial joint is invasive and clinically impractical. Recent studies have demonstrated that unique gene expression changes can be identified in peripheral blood mononuclear cells (PBMCs) from patients with cancer, multiple sclerosis, and lupus. To identify RA disease-related genes, we performed a global gene expression analysis. RNA from PBMCs of 9 RA patients and 13 normal volunteers was analyzed on an oligonucleotide array. Compared with normal PBMCs, 330 transcripts were differentially expressed in RA. The differentially regulated genes belong to diverse functional classes and include genes involved in calcium binding, chaperones, cytokines, transcription, translation, signal transduction, extracellular matrix, integral to plasma membrane, integral to intracellular membrane, mitochondrial, ribosomal, structural, enzymes, and proteases. A k-nearest neighbor analysis identified 29 transcripts that were preferentially expressed in RA. Ten genes with increased expression in RA PBMCs compared with controls mapped to a RA susceptibility locus, 6p21.3. These results suggest that analysis of RA PBMCs at the molecular level may provide a set of candidate genes that could yield an easily accessible gene signature to aid in early diagnosis and treatment. PMID:17515956

The Competence of Maize Shoot Meristems for Integrative Transformation and Inherited Expression of Transgenes.

PubMed Central

Zhong, H.; Sun, B.; Warkentin, D.; Zhang, S.; Wu, R.; Wu, T.; Sticklen, M. B.

1996-01-01

We have developed a novel and reproducible system for recovery of fertile transgenic maize (Zea mays L.) plants. The transformation was performed using microprojectile bombardment of cultured shoot apices of maize with a plasmid carrying two linked genes, the Streptomyces hygroscopicus phosphinothricin acetyltransferase gene (bar) and the potato proteinase inhibitor II gene, either alone or in combination with another plasmid containing the 5[prime] region of the rice actin 1 gene fused to the Escherichia coli [beta]-glucuronidase gene (gus). Bombarded shoot apices were subsequently multiplied and selected under 3 to 5 mg/L glufosinate ammonium. Co-transformation frequency was 100% (146/146) for linked genes and 80% (41/51) for unlinked genes. Co-expression frequency of the bar and gus genes was 57% (29/51). The co-integration, co-inheritance, and co-expression of bar, the potato proteinase inhibitor II gene, and gus in transgenic R0, R1, and R2 plants were confirmed. Localized expression of the actin 1-GUS protein in the R0 and R1 plants was extensively analyzed by histochemical and fluorometric assays. PMID:12226244

The oncogenic potential of BK-polyomavirus is linked to viral integration into the human genome.

PubMed

Kenan, Daniel J; Mieczkowski, Piotr A; Burger-Calderon, Raquel; Singh, Harsharan K; Nickeleit, Volker

2015-11-01

It has been suggested that BK-polyomavirus is linked to oncogenesis via high expression levels of large T-antigen in some urothelial neoplasms arising following kidney transplantation. However, a causal association between BK-polyomavirus, large T-antigen expression and oncogenesis has never been demonstrated in humans. Here we describe an investigation using high-throughput sequencing of tumour DNA obtained from an urothelial carcinoma arising in a renal allograft. We show that a novel BK-polyomavirus strain, named CH-1, is integrated into exon 26 of the myosin-binding protein C1 gene (MYBPC1) on chromosome 12 in tumour cells but not in normal renal cells. Integration of the BK-polyomavirus results in a number of discrete alterations in viral gene expression, including: (a) disruption of VP1 protein expression and robust expression of large T-antigen; (b) preclusion of viral replication; and (c) deletions in the non-coding control region (NCCR), with presumed alterations in promoter feedback loops. Viral integration disrupts one MYBPC1 gene copy and likely alters its expression. Circular episomal BK-polyomavirus gene sequences are not found, and the renal allograft shows no productive polyomavirus infection or polyomavirus nephropathy. These findings support the hypothesis that integration of polyomaviruses is essential to tumourigenesis. It is likely that dysregulation of large T-antigen, with persistent over-expression in non-lytic cells, promotes cell growth, genetic instability and neoplastic transformation. © 2015 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

The Plant Genome Integrative Explorer Resource: PlantGenIE.org.

PubMed

Sundell, David; Mannapperuma, Chanaka; Netotea, Sergiu; Delhomme, Nicolas; Lin, Yao-Cheng; Sjödin, Andreas; Van de Peer, Yves; Jansson, Stefan; Hvidsten, Torgeir R; Street, Nathaniel R

2015-12-01

Accessing and exploring large-scale genomics data sets remains a significant challenge to researchers without specialist bioinformatics training. We present the integrated PlantGenIE.org platform for exploration of Populus, conifer and Arabidopsis genomics data, which includes expression networks and associated visualization tools. Standard features of a model organism database are provided, including genome browsers, gene list annotation, Blast homology searches and gene information pages. Community annotation updating is supported via integration of WebApollo. We have produced an RNA-sequencing (RNA-Seq) expression atlas for Populus tremula and have integrated these data within the expression tools. An updated version of the ComPlEx resource for performing comparative plant expression analyses of gene coexpression network conservation between species has also been integrated. The PlantGenIE.org platform provides intuitive access to large-scale and genome-wide genomics data from model forest tree species, facilitating both community contributions to annotation improvement and tools supporting use of the included data resources to inform biological insight. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Linear Lepidopteran ambidensovirus 1 sequences drive random integration of a reporter gene in transfected Spodoptera frugiperda cells.

PubMed

Rizk, Francine; Laverdure, Sylvain; d'Alençon, Emmanuelle; Bossin, Hervé; Dupressoir, Thierry

2018-01-01

The Lepidopteran ambidensovirus 1 isolated from Junonia coenia (hereafter JcDV) is an invertebrate parvovirus considered as a viral transduction vector as well as a potential tool for the biological control of insect pests. Previous works showed that JcDV-based circular plasmids experimentally integrate into insect cells genomic DNA. In order to approach the natural conditions of infection and possible integration, we generated linear JcDV- gfp based molecules which were transfected into non permissive Spodoptera frugiperda ( Sf9 ) cultured cells. Cells were monitored for the expression of green fluorescent protein (GFP) and DNA was analyzed for integration of transduced viral sequences. Non-structural protein modulation of the VP-gene cassette promoter activity was additionally assayed. We show that linear JcDV-derived molecules are capable of long term genomic integration and sustained transgene expression in Sf9 cells. As expected, only the deletion of both inverted terminal repeats (ITR) or the polyadenylation signals of NS and VP genes dramatically impairs the global transduction/expression efficiency. However, all the integrated viral sequences we characterized appear "scrambled" whatever the viral content of the transfected vector. Despite a strong GFP expression, we were unable to recover any full sequence of the original constructs and found rearranged viral and non-viral sequences as well. Cellular flanking sequences were identified as non-coding ones. On the other hand, the kinetics of GFP expression over time led us to investigate the apparent down-regulation by non-structural proteins of the VP-gene cassette promoter. Altogether, our results show that JcDV-derived sequences included in linear DNA molecules are able to drive efficiently the integration and expression of a foreign gene into the genome of insect cells, whatever their composition, provided that at least one ITR is present. However, the transfected sequences were extensively rearranged with cellular DNA during or after random integration in the host cell genome. Lastly, the non-structural proteins seem to participate in the regulation of p9 promoter activity rather than to the integration of viral sequences.

Integrating T7 RNA Polymerase and Its Cognate Transcriptional Units for a Host-Independent and Stable Expression System in Single Plasmid.

PubMed

Liang, Xiao; Li, Chenmeng; Wang, Wenya; Li, Qiang

2018-05-18

Metabolic engineering and synthetic biology usually require universal expression systems for stable and efficient gene expression in various organisms. In this study, a host-independent and stable T7 expression system had been developed by integrating T7 RNA polymerase and its cognate transcriptional units in single plasmid. The expression of T7 RNA polymerase was restricted below its lethal threshold using a T7 RNA polymerase antisense gene cassette, which allowed long periods of cultivation and protein production. In addition, by designing ribosome binding sites, we further tuned the expression capacity of this novel T7 system within a wide range. This host-independent expression system efficiently expressed genes in five different Gram-negative strains and one Gram-positive strain and was also shown to be applicable in a real industrial d- p-hydroxyphenylglycine production system.

Integration of a splicing regulatory network within the meiotic gene expression program of Saccharomyces cerevisiae

PubMed Central

Munding, Elizabeth M.; Igel, A. Haller; Shiue, Lily; Dorighi, Kristel M.; Treviño, Lisa R.; Ares, Manuel

2010-01-01

Splicing regulatory networks are essential components of eukaryotic gene expression programs, yet little is known about how they are integrated with transcriptional regulatory networks into coherent gene expression programs. Here we define the MER1 splicing regulatory network and examine its role in the gene expression program during meiosis in budding yeast. Mer1p splicing factor promotes splicing of just four pre-mRNAs. All four Mer1p-responsive genes also require Nam8p for splicing activation by Mer1p; however, other genes require Nam8p but not Mer1p, exposing an overlapping meiotic splicing network controlled by Nam8p. MER1 mRNA and three of the four Mer1p substrate pre-mRNAs are induced by the transcriptional regulator Ume6p. This unusual arrangement delays expression of Mer1p-responsive genes relative to other genes under Ume6p control. Products of Mer1p-responsive genes are required for initiating and completing recombination and for activation of Ndt80p, the activator of the transcriptional network required for subsequent steps in the program. Thus, the MER1 splicing regulatory network mediates the dependent relationship between the UME6 and NDT80 transcriptional regulatory networks in the meiotic gene expression program. This study reveals how splicing regulatory networks can be interlaced with transcriptional regulatory networks in eukaryotic gene expression programs. PMID:21123654

Data-Driven Asthma Endotypes Defined from Blood Biomarker and Gene Expression Data

PubMed Central

George, Barbara Jane; Reif, David M.; Gallagher, Jane E.; Williams-DeVane, ClarLynda R.; Heidenfelder, Brooke L.; Hudgens, Edward E.; Jones, Wendell; Neas, Lucas; Hubal, Elaine A. Cohen; Edwards, Stephen W.

2015-01-01

The diagnosis and treatment of childhood asthma is complicated by its mechanistically distinct subtypes (endotypes) driven by genetic susceptibility and modulating environmental factors. Clinical biomarkers and blood gene expression were collected from a stratified, cross-sectional study of asthmatic and non-asthmatic children from Detroit, MI. This study describes four distinct asthma endotypes identified via a purely data-driven method. Our method was specifically designed to integrate blood gene expression and clinical biomarkers in a way that provides new mechanistic insights regarding the different asthma endotypes. For example, we describe metabolic syndrome-induced systemic inflammation as an associated factor in three of the four asthma endotypes. Context provided by the clinical biomarker data was essential in interpreting gene expression patterns and identifying putative endotypes, which emphasizes the importance of integrated approaches when studying complex disease etiologies. These synthesized patterns of gene expression and clinical markers from our research may lead to development of novel serum-based biomarker panels. PMID:25643280

Integrative analysis of gut microbiota composition, host colonic gene expression and intraluminal metabolites in aging C57BL/6J mice.

PubMed

van der Lugt, Benthe; Rusli, Fenni; Lute, Carolien; Lamprakis, Andreas; Salazar, Ethel; Boekschoten, Mark V; Hooiveld, Guido J; Müller, Michael; Vervoort, Jacques; Kersten, Sander; Belzer, Clara; Kok, Dieuwertje E G; Steegenga, Wilma T

2018-05-16

The aging process is associated with diminished colonic health. In this study, we applied an integrative approach to reveal potential interactions between determinants of colonic health in aging C57BL/6J mice. Analysis of gut microbiota composition revealed an enrichment of various potential pathobionts, including Desulfovibrio spp . , and a decline of the health-promoting Akkermansia spp . and Lactobacillus spp. during aging. Intraluminal concentrations of various metabolites varied between ages and we found evidence for an increased gut permeability at higher age. Colonic gene expression analysis suggested that during the early phase of aging (between 6 and 12 months), expression of genes involved in epithelial-to-mesenchymal transition and (re)organization of the extracellular matrix were increased. Differential expression of these genes was strongly correlated with Bifidobacterium spp. During the later phase of aging (between 12 and 28 months), gene expression profiles pointed towards a diminished antimicrobial defense and were correlated with an uncultured Gastranaerophilales spp. This study demonstrates that aging is associated with pronounced changes in gut microbiota composition and colonic gene expression. Furthermore, the strong correlations between specific bacterial genera and host gene expression may imply that orchestrated interactions take place in the vicinity of the colonic wall and potentially mediate colonic health during aging.

Integrative analysis of micro-RNA, gene expression, and survival of glioblastoma multiforme.

PubMed

Huang, Yen-Tsung; Hsu, Thomas; Kelsey, Karl T; Lin, Chien-Ling

2015-02-01

Glioblastoma multiforme (GBM), the most common type of malignant brain tumor, is highly fatal. Limited understanding of its rapid progression necessitates additional approaches that integrate what is known about the genomics of this cancer. Using a discovery set (n = 348) and a validation set (n = 174) of GBM patients, we performed genome-wide analyses that integrated mRNA and micro-RNA expression data from GBM as well as associated survival information, assessing coordinated variability in each as this reflects their known mechanistic functions. Cox proportional hazards models were used for the survival analyses, and nonparametric permutation tests were performed for the micro-RNAs to investigate the association between the number of associated genes and its prognostication. We also utilized mediation analyses for micro-RNA-gene pairs to identify their mediation effects. Genome-wide analyses revealed a novel pattern: micro-RNAs related to more gene expressions are more likely to be associated with GBM survival (P = 4.8 × 10(-5)). Genome-wide mediation analyses for the 32,660 micro-RNA-gene pairs with strong association (false discovery rate [FDR] < 0.01%) identified 51 validated pairs with significant mediation effect. Of the 51 pairs, miR-223 had 16 mediation genes. These 16 mediation genes of miR-223 were also highly associated with various other micro-RNAs and mediated their prognostic effects as well. We further constructed a gene signature using the 16 genes, which was highly associated with GBM survival in both the discovery and validation sets (P = 9.8 × 10(-6)). This comprehensive study discovered mediation effects of micro-RNA to gene expression and GBM survival and provided a new analytic framework for integrative genomics. © 2014 WILEY PERIODICALS, INC.

Gene Expression Analysis to Assess the Relevance of Rodent Models to Human Lung Injury.

PubMed

Sweeney, Timothy E; Lofgren, Shane; Khatri, Purvesh; Rogers, Angela J

2017-08-01

The relevance of animal models to human diseases is an area of intense scientific debate. The degree to which mouse models of lung injury recapitulate human lung injury has never been assessed. Integrating data from both human and animal expression studies allows for increased statistical power and identification of conserved differential gene expression across organisms and conditions. We sought comprehensive integration of gene expression data in experimental acute lung injury (ALI) in rodents compared with humans. We performed two separate gene expression multicohort analyses to determine differential gene expression in experimental animal and human lung injury. We used correlational and pathway analyses combined with external in vitro gene expression data to identify both potential drivers of underlying inflammation and therapeutic drug candidates. We identified 21 animal lung tissue datasets and three human lung injury bronchoalveolar lavage datasets. We show that the metasignatures of animal and human experimental ALI are significantly correlated despite these widely varying experimental conditions. The gene expression changes among mice and rats across diverse injury models (ozone, ventilator-induced lung injury, LPS) are significantly correlated with human models of lung injury (Pearson r = 0.33-0.45, P < 1E -16 ). Neutrophil signatures are enriched in both animal and human lung injury. Predicted therapeutic targets, peptide ligand signatures, and pathway analyses are also all highly overlapping. Gene expression changes are similar in animal and human experimental ALI, and provide several physiologic and therapeutic insights to the disease.

Integrative analysis of copy number alteration and gene expression profiling in ovarian clear cell adenocarcinoma.

PubMed

Sung, Chang Ohk; Choi, Chel Hun; Ko, Young-Hyeh; Ju, Hyunjeong; Choi, Yoon-La; Kim, Nyunsu; Kang, So Young; Ha, Sang Yun; Choi, Kyusam; Bae, Duk-Soo; Lee, Jeong-Won; Kim, Tae-Joong; Song, Sang Yong; Kim, Byoung-Gie

2013-05-01

Ovarian clear cell adenocarcinoma (Ov-CCA) is a distinctive subtype of ovarian epithelial carcinoma. In this study, we performed array comparative genomic hybridization (aCGH) and paired gene expression microarray of 19 fresh-frozen samples and conducted integrative analysis. For the copy number alterations, significantly amplified regions (false discovery rate [FDR] q <0.05) were 1q21.3 and 8q24.3, and significantly deleted regions were 3p21.31, 4q12, 5q13.2, 5q23.2, 5q31.1, 7p22.1, 7q11.23, 8p12, 9p22.1, 11p15.1, 12p13.31, 15q11.2, 15q21.2, 18p11.31, and 22q11.21 using the Genomic Identification of Significant Targets in Cancer (GISTIC) analysis. Integrative analysis revealed 94 genes demonstrating frequent copy number alterations (>25% of samples) that correlated with gene expression (FDR <0.05). These genes were mainly located on 8p11.21, 8p21.2-p21.3, 8q22.1, 8q24.3, 17q23.2-q23.3, 19p13.3, and 19p13.11. Among the regions, 8q24.3 was found to contain the most genes (30 of 94 genes) including PTK2. The 8q24.3 region was indicated as the most significant region, as supported by copy number, GISTIC, and integrative analysis. Pathway analysis using differentially expressed genes on 8q24.3 revealed several major nodes, including PTK2. In conclusion, we identified a set of 94 candidate genes with frequent copy number alterations that correlated with gene expression. Specific chromosomal alterations, such as the 8q24.3 gain containing PTK2, could be a therapeutic target in a subset of Ov-CCAs. Copyright © 2013. Published by Elsevier Inc.

Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages.

PubMed

Taminau, Jonatan; Meganck, Stijn; Lazar, Cosmin; Steenhoff, David; Coletta, Alain; Molter, Colin; Duque, Robin; de Schaetzen, Virginie; Weiss Solís, David Y; Bersini, Hugues; Nowé, Ann

2012-12-24

With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].

Human Papillomavirus Type 18 E6 and E7 Genes Integrate into Human Hepatoma Derived Cell Line Hep G2

PubMed Central

Ma, Tianzhong; Su, Zhongjing; Chen, Ling; Liu, Shuyan; Zhu, Ningxia; Wen, Lifeng; Yuan, Yan; Lv, Leili; Chen, Xiancai; Huang, Jianmin; Chen, Haibin

2012-01-01

Background and Objectives Human papillomaviruses have been linked causally to some human cancers such as cervical carcinoma, but there is very little research addressing the effect of HPV infection on human liver cells. We chose the human hepatoma derived cell line Hep G2 to investigate whether HPV gene integration took place in liver cells as well. Methods We applied PCR to detect the possible integration of HPV genes in Hep G2 cells. We also investigated the expression of the integrated E6 and E7 genes by using RT-PCR and Western blotting. Then, we silenced E6 and E7 expression and checked the cell proliferation and apoptosis in Hep G2 cells. Furthermore, we analyzed the potential genes involved in cell cycle and apoptosis regulatory pathways. Finally, we used in situ hybridization to detect HPV 16/18 in hepatocellular carcinoma samples. Results Hep G2 cell line contains integrated HPV 18 DNA, leading to the expression of the E6 and E7 oncogenic proteins. Knockdown of the E7 and E6 genes expression reduced cell proliferation, caused the cell cycle arrest at the S phase, and increased apoptosis. The human cell cycle and apoptosis real-time PCR arrays analysis demonstrated E6 and E7-mediated regulation of some genes such as Cyclin H, UBA1, E2F4, p53, p107, FASLG, NOL3 and CASP14. HPV16/18 was found in only 9% (9/100) of patients with hepatocellular carcinoma. Conclusion Our investigations showed that HPV 18 E6 and E7 genes can be integrated into the Hep G2, and we observed a low prevalence of HPV 16/18 in hepatocellular carcinoma samples. However, the precise risk of HPV as causative agent of hepatocellular carcinoma needs further study. PMID:22655088

Robustness, Evolvability, and the Logic of Genetic Regulation

PubMed Central

Moore, Jason H.; Wagner, Andreas

2014-01-01

In gene regulatory circuits, the expression of individual genes is commonly modulated by a set of regulating gene products, which bind to a gene’s cis-regulatory region. This region encodes an input-output function, referred to as signal-integration logic, that maps a specific combination of regulatory signals (inputs) to a particular expression state (output) of a gene. The space of all possible signal-integration functions is vast and the mapping from input to output is many-to-one: for the same set of inputs, many functions (genotypes) yield the same expression output (phenotype). Here, we exhaustively enumerate the set of signal-integration functions that yield idential gene expression patterns within a computational model of gene regulatory circuits. Our goal is to characterize the relationship between robustness and evolvability in the signal-integration space of regulatory circuits, and to understand how these properties vary between the genotypic and phenotypic scales. Among other results, we find that the distributions of genotypic robustness are skewed, such that the majority of signal-integration functions are robust to perturbation. We show that the connected set of genotypes that make up a given phenotype are constrained to specific regions of the space of all possible signal-integration functions, but that as the distance between genotypes increases, so does their capacity for unique innovations. In addition, we find that robust phenotypes are (i) evolvable, (ii) easily identified by random mutation, and (iii) mutationally biased toward other robust phenotypes. We explore the implications of these latter observations for mutation-based evolution by conducting random walks between randomly chosen source and target phenotypes. We demonstrate that the time required to identify the target phenotype is independent of the properties of the source phenotype. PMID:23373974

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

PubMed Central

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

2009-01-01

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

Alpharetroviral Self-inactivating Vectors: Long-term Transgene Expression in Murine Hematopoietic Cells and Low Genotoxicity

PubMed Central

Suerth, Julia D; Maetzig, Tobias; Brugman, Martijn H; Heinz, Niels; Appelt, Jens-Uwe; Kaufmann, Kerstin B; Schmidt, Manfred; Grez, Manuel; Modlich, Ute; Baum, Christopher; Schambach, Axel

2012-01-01

Comparative integrome analyses have highlighted alpharetroviral vectors with a relatively neutral, and thus favorable, integration spectrum. However, previous studies used alpharetroviral vectors harboring viral coding sequences and intact long-terminal repeats (LTRs). We recently developed self-inactivating (SIN) alpharetroviral vectors with an advanced split-packaging design. In a murine bone marrow (BM) transplantation model we now compared alpharetroviral, gammaretroviral, and lentiviral SIN vectors and showed that all vectors transduced hematopoietic stem cells (HSCs), leading to comparable, sustained multilineage transgene expression in primary and secondary transplanted mice. Alpharetroviral integrations were decreased near transcription start sites, CpG islands, and potential cancer genes compared with gammaretroviral, and decreased in genes compared with lentiviral integrations. Analyzing the transcriptome and intragenic integrations in engrafting cells, we observed stronger correlations between in-gene integration targeting and transcriptional activity for gammaretroviral and lentiviral vectors than for alpharetroviral vectors. Importantly, the relatively “extragenic” alpharetroviral integration pattern still supported long-term transgene expression upon serial transplantation. Furthermore, sensitive genotoxicity studies revealed a decreased immortalization incidence compared with gammaretroviral and lentiviral SIN vectors. We conclude that alpharetroviral SIN vectors have a favorable integration pattern which lowers the risk of insertional mutagenesis while supporting long-term transgene expression in the progeny of transplanted HSCs. PMID:22334016

Multilevel Regulation of Bacterial Gene Expression with the Combined STAR and Antisense RNA System.

PubMed

Lee, Young Je; Kim, Soo-Jung; Moon, Tae Seok

2018-03-16

Synthetic small RNA regulators have emerged as a versatile tool to predictably control bacterial gene expression. Owing to their simple design principles, small size, and highly orthogonal behavior, these engineered genetic parts have been incorporated into genetic circuits. However, efforts to achieve more sophisticated cellular functions using RNA regulators have been hindered by our limited ability to integrate different RNA regulators into complex circuits. Here, we present a combined RNA regulatory system in Escherichia coli that uses small transcription activating RNA (STAR) and antisense RNA (asRNA) to activate or deactivate target gene expression in a programmable manner. Specifically, we demonstrated that the activated target output by the STAR system can be deactivated by expressing two different types of asRNAs: one binds to and sequesters the STAR regulator, affecting the transcription process, while the other binds to the target mRNA, affecting the translation process. We improved deactivation efficiencies (up to 96%) by optimizing each type of asRNA and then integrating the two optimized asRNAs into a single circuit. Furthermore, we demonstrated that the combined STAR and asRNA system can control gene expression in a reversible way and can regulate expression of a gene in the genome. Lastly, we constructed and simultaneously tested two A AND NOT B logic gates in the same cell to show sophisticated multigene regulation by the combined system. Our approach establishes a methodology for integrating multiple RNA regulators to rationally control multiple genes.

MethHC: a database of DNA methylation and gene expression in human cancer.

PubMed

Huang, Wei-Yun; Hsu, Sheng-Da; Huang, Hsi-Yuan; Sun, Yi-Ming; Chou, Chih-Hung; Weng, Shun-Long; Huang, Hsien-Da

2015-01-01

We present MethHC (http://MethHC.mbc.nctu.edu.tw), a database comprising a systematic integration of a large collection of DNA methylation data and mRNA/microRNA expression profiles in human cancer. DNA methylation is an important epigenetic regulator of gene transcription, and genes with high levels of DNA methylation in their promoter regions are transcriptionally silent. Increasing numbers of DNA methylation and mRNA/microRNA expression profiles are being published in different public repositories. These data can help researchers to identify epigenetic patterns that are important for carcinogenesis. MethHC integrates data such as DNA methylation, mRNA expression, DNA methylation of microRNA gene and microRNA expression to identify correlations between DNA methylation and mRNA/microRNA expression from TCGA (The Cancer Genome Atlas), which includes 18 human cancers in more than 6000 samples, 6548 microarrays and 12 567 RNA sequencing data. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Search for sarcoidosis candidate genes by integration of data from genomic, transcriptomic and proteomic studies.

PubMed

Maver, Ales; Medica, Igor; Peterlin, Borut

2009-12-01

The search for gene candidates in multifactorial diseases such as sarcoidosis can be based on the integration of linkage association data, gene expression data, and protein profile data from genomic, transcriptomic and proteomic studies, respectively. In this study we performed a literature-based search for studies reporting such data, followed by integration of collected information. Different databases were examined--Medline, HugGE Navigator, ArrayExpress and Gene Expression Omnibus (GEO). Candidate genes were defined as genes which were reported in at least 2 different types of omics studies. Genes previously investigated in sarcoidosis were excluded from further analyses. We identified 177 genes associated with sarcoidosis as potential new candidate genes. Subsequently, 9 gene candidates identified to overlap in 2 different types of studies (genomic, transcriptomic and/or proteomic) were consistently reported in at least 3 studies: SERPINB1, FABP4, S100A8, HBEGF, IL7R, LRIG1, PTPN23, DPM2 and NUP214. These genes are involved in regulation of immune response, cellular proliferation, apoptosis, inhibition of protease activity, lipid metabolism. Exact biological functions of HBEGF, LRIG1, PTPN23, DPM2 and NUP214 remain to be completely elucidated. We propose 9 candidate genes: SERPINB1, FABP4, S100A8, HBEGF, IL7R, LRIG1, PTPN23, DPM2 and NUP214, as genes with high potential for association with sarcoidosis.

Functional relevance for type 1 diabetes mellitus-associated genetic variants by using integrative analyses.

PubMed

Qiu, Ying-Hua; Deng, Fei-Yan; Tang, Zai-Xiang; Jiang, Zhen-Huan; Lei, Shu-Feng

2015-10-01

Type 1 diabetes mellitus (type 1 DM) is an autoimmune disease. Although genome-wide association studies (GWAS) and meta-analyses have successfully identified numerous type 1 DM-associated susceptibility loci, the underlying mechanisms for these susceptibility loci are currently largely unclear. Based on publicly available datasets, we performed integrative analyses (i.e., integrated gene relationships among implicated loci, differential gene expression analysis, functional prediction and functional annotation clustering analysis) and combined with expression quantitative trait loci (eQTL) results to further explore function mechanisms underlying the associations between genetic variants and type 1 DM. Among a total of 183 type 1 DM-associated SNPs, eQTL analysis showed that 17 SNPs with cis-regulated eQTL effects on 9 genes. All the 9 eQTL genes enrich in immune-related pathways or Gene Ontology (GO) terms. Functional prediction analysis identified 5 SNPs located in transcription factor (TF) binding sites. Of the 9 eQTL genes, 6 (TAP2, HLA-DOB, HLA-DQB1, HLA-DQA1, HLA-DRB5 and CTSH) were differentially expressed in type 1 DM-associated related cells. Especially, rs3825932 in CTSH has integrative functional evidence supporting the association with type 1 DM. These findings indicated that integrative analyses can yield important functional information to link genetic variants and type 1 DM. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Gene expression profiling in multiple myeloma--reporting of entities, risk, and targets in clinical routine.

PubMed

Meissner, Tobias; Seckinger, Anja; Rème, Thierry; Hielscher, Thomas; Möhler, Thomas; Neben, Kai; Goldschmidt, Hartmut; Klein, Bernard; Hose, Dirk

2011-12-01

Multiple myeloma is an incurable malignant plasma cell disease characterized by survival ranging from several months to more than 15 years. Assessment of risk and underlying molecular heterogeneity can be excellently done by gene expression profiling (GEP), but its way into clinical routine is hampered by the lack of an appropriate reporting tool and the integration with other prognostic factors into a single "meta" risk stratification. The GEP-report (GEP-R) was built as an open-source software developed in R for gene expression reporting in clinical practice using Affymetrix microarrays. GEP-R processes new samples by applying a documentation-by-value strategy to the raw data to be able to assign thresholds and grouping algorithms defined on a reference cohort of 262 patients with multiple myeloma. Furthermore, we integrated expression-based and conventional prognostic factors within one risk stratification (HM-metascore). The GEP-R comprises (i) quality control, (ii) sample identity control, (iii) biologic classification, (iv) risk stratification, and (v) assessment of target genes. The resulting HM-metascore is defined as the sum over the weighted factors gene expression-based risk-assessment (UAMS-, IFM-score), proliferation, International Staging System (ISS) stage, t(4;14), and expression of prognostic target genes (AURKA, IGF1R) for which clinical grade inhibitors exist. The HM-score delineates three significantly different groups of 13.1%, 72.1%, and 14.7% of patients with a 6-year survival rate of 89.3%, 60.6%, and 18.6%, respectively. GEP reporting allows prospective assessment of risk and target gene expression and integration of current prognostic factors in clinical routine, being customizable about novel parameters or other cancer entities. ©2011 AACR.

An integrated approach to reconstructing genome-scale transcriptional regulatory networks

DOE PAGES

Imam, Saheed; Noguera, Daniel R.; Donohue, Timothy J.; ...

2015-02-27

Transcriptional regulatory networks (TRNs) program cells to dynamically alter their gene expression in response to changing internal or environmental conditions. In this study, we develop a novel workflow for generating large-scale TRN models that integrates comparative genomics data, global gene expression analyses, and intrinsic properties of transcription factors (TFs). An assessment of this workflow using benchmark datasets for the well-studied γ-proteobacterium Escherichia coli showed that it outperforms expression-based inference approaches, having a significantly larger area under the precision-recall curve. Further analysis indicated that this integrated workflow captures different aspects of the E. coli TRN than expression-based approaches, potentially making themmore » highly complementary. We leveraged this new workflow and observations to build a large-scale TRN model for the α-Proteobacterium Rhodobacter sphaeroides that comprises 120 gene clusters, 1211 genes (including 93 TFs), 1858 predicted protein-DNA interactions and 76 DNA binding motifs. We found that ~67% of the predicted gene clusters in this TRN are enriched for functions ranging from photosynthesis or central carbon metabolism to environmental stress responses. We also found that members of many of the predicted gene clusters were consistent with prior knowledge in R. sphaeroides and/or other bacteria. Experimental validation of predictions from this R. sphaeroides TRN model showed that high precision and recall was also obtained for TFs involved in photosynthesis (PpsR), carbon metabolism (RSP_0489) and iron homeostasis (RSP_3341). In addition, this integrative approach enabled generation of TRNs with increased information content relative to R. sphaeroides TRN models built via other approaches. We also show how this approach can be used to simultaneously produce TRN models for each related organism used in the comparative genomics analysis. Our results highlight the advantages of integrating comparative genomics of closely related organisms with gene expression data to assemble large-scale TRN models with high-quality predictions.« less

Meta-Analysis of DNA Tumor-Viral Integration Site Selection Indicates a Role for Repeats, Gene Expression and Epigenetics

PubMed Central

Doolittle-Hall, Janet M.; Cunningham Glasspoole, Danielle L.; Seaman, William T.; Webster-Cyriaque, Jennifer

2015-01-01

Oncoviruses cause tremendous global cancer burden. For several DNA tumor viruses, human genome integration is consistently associated with cancer development. However, genomic features associated with tumor viral integration are poorly understood. We sought to define genomic determinants for 1897 loci prone to hosting human papillomavirus (HPV), hepatitis B virus (HBV) or Merkel cell polyomavirus (MCPyV). These were compared to HIV, whose enzyme-mediated integration is well understood. A comprehensive catalog of integration sites was constructed from the literature and experimentally-determined HPV integration sites. Features were scored in eight categories (genes, expression, open chromatin, histone modifications, methylation, protein binding, chromatin segmentation and repeats) and compared to random loci. Random forest models determined loci classification and feature selection. HPV and HBV integrants were not fragile site associated. MCPyV preferred integration near sensory perception genes. Unique signatures of integration-associated predictive genomic features were detected. Importantly, repeats, actively-transcribed regions and histone modifications were common tumor viral integration signatures. PMID:26569308

BioVLAB-MMIA: a cloud environment for microRNA and mRNA integrated analysis (MMIA) on Amazon EC2.

PubMed

Lee, Hyungro; Yang, Youngik; Chae, Heejoon; Nam, Seungyoon; Choi, Donghoon; Tangchaisin, Patanachai; Herath, Chathura; Marru, Suresh; Nephew, Kenneth P; Kim, Sun

2012-09-01

MicroRNAs, by regulating the expression of hundreds of target genes, play critical roles in developmental biology and the etiology of numerous diseases, including cancer. As a vast amount of microRNA expression profile data are now publicly available, the integration of microRNA expression data sets with gene expression profiles is a key research problem in life science research. However, the ability to conduct genome-wide microRNA-mRNA (gene) integration currently requires sophisticated, high-end informatics tools, significant expertise in bioinformatics and computer science to carry out the complex integration analysis. In addition, increased computing infrastructure capabilities are essential in order to accommodate large data sets. In this study, we have extended the BioVLAB cloud workbench to develop an environment for the integrated analysis of microRNA and mRNA expression data, named BioVLAB-MMIA. The workbench facilitates computations on the Amazon EC2 and S3 resources orchestrated by the XBaya Workflow Suite. The advantages of BioVLAB-MMIA over the web-based MMIA system include: 1) readily expanded as new computational tools become available; 2) easily modifiable by re-configuring graphic icons in the workflow; 3) on-demand cloud computing resources can be used on an "as needed" basis; 4) distributed orchestration supports complex and long running workflows asynchronously. We believe that BioVLAB-MMIA will be an easy-to-use computing environment for researchers who plan to perform genome-wide microRNA-mRNA (gene) integrated analysis tasks.

Penalized differential pathway analysis of integrative oncogenomics studies.

PubMed

van Wieringen, Wessel N; van de Wiel, Mark A

2014-04-01

Through integration of genomic data from multiple sources, we may obtain a more accurate and complete picture of the molecular mechanisms underlying tumorigenesis. We discuss the integration of DNA copy number and mRNA gene expression data from an observational integrative genomics study involving cancer patients. The two molecular levels involved are linked through the central dogma of molecular biology. DNA copy number aberrations abound in the cancer cell. Here we investigate how these aberrations affect gene expression levels within a pathway using observational integrative genomics data of cancer patients. In particular, we aim to identify differential edges between regulatory networks of two groups involving these molecular levels. Motivated by the rate equations, the regulatory mechanism between DNA copy number aberrations and gene expression levels within a pathway is modeled by a simultaneous-equations model, for the one- and two-group case. The latter facilitates the identification of differential interactions between the two groups. Model parameters are estimated by penalized least squares using the lasso (L1) penalty to obtain a sparse pathway topology. Simulations show that the inclusion of DNA copy number data benefits the discovery of gene-gene interactions. In addition, the simulations reveal that cis-effects tend to be over-estimated in a univariate (single gene) analysis. In the application to real data from integrative oncogenomic studies we show that inclusion of prior information on the regulatory network architecture benefits the reproducibility of all edges. Furthermore, analyses of the TP53 and TGFb signaling pathways between ER+ and ER- samples from an integrative genomics breast cancer study identify reproducible differential regulatory patterns that corroborate with existing literature.

Targeted transgene insertion into the CHO cell genome using Cre recombinase-incorporating integrase-defective retroviral vectors.

PubMed

Kawabe, Yoshinori; Shimomura, Takuya; Huang, Shuohao; Imanishi, Suguru; Ito, Akira; Kamihira, Masamichi

2016-07-01

Retroviral vectors have served as efficient gene delivery tools in various biotechnology fields. However, viral DNA is randomly inserted into the genome, which can cause problems, such as insertional mutagenesis and gene silencing. Previously, we reported a site-specific gene integration system, in which a transgene is integrated into a predetermined chromosomal locus of Chinese hamster ovary (CHO) cells using integrase-defective retroviral vectors (IDRVs) and Cre recombinase. In this system, a Cre expression plasmid is transfected into founder cells before retroviral transduction. In practical applications of site-specific gene modification such as for hard-to-transfect cells or for in vivo gene delivery, both the transgene and the Cre protein into retroviral virions should be encapsulate. Here, we generated novel hybrid IDRVs in which viral genome and enzymatically active Cre can be delivered (Cre-IDRVs). Cre-IDRVs encoding marker genes, neomycin resistance and enhanced green fluorescent protein (EGFP), flanked by wild-type and mutated loxP sites were produced using an expression plasmid for a chimeric protein of Cre and retroviral gag-pol. After analyzing the incorporation of the Cre protein into retroviral virions by Western blotting, the Cre-IDRV was infected into founder CHO cells, in which marker genes (hygromycin resistance and red fluorescent protein) flanked with corresponding loxP sites are introduced into the genome. G418-resistant colonies expressing GFP appeared and the site-specific integration of the transgene into the expected chromosomal site was confirmed by PCR and sequencing of amplicons. Moreover, when Cre-IDRV carried a gene expression unit for a recombinant antibody, the recombinant cells in which the antibody expression cassette was integrated in a site-specific manner were generated and the cells produced the recombinant antibody. This method may provide a promising tool to perform site-specific gene modification according to Cre-based cell engineering. Biotechnol. Bioeng. 2016;113: 1600-1610. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis.

PubMed

He, Fei; Fromion, Vincent; Westerhoff, Hans V

2013-11-21

Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. This study integrates control engineering and classical MCA augmented with supply-demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the 'integral control' (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of 'integral control' should rarely be expected to lead to the 'perfect adaptation': although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the 'perfect' regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering.

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

PubMed Central

2013-01-01

Background Metabolic control analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results This study integrates control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral control’ (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the ‘perfect’ regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering. PMID:24261908

BioVLAB-mCpG-SNP-EXPRESS: A system for multi-level and multi-perspective analysis and exploration of DNA methylation, sequence variation (SNPs), and gene expression from multi-omics data.

PubMed

Chae, Heejoon; Lee, Sangseon; Seo, Seokjun; Jung, Daekyoung; Chang, Hyeonsook; Nephew, Kenneth P; Kim, Sun

2016-12-01

Measuring gene expression, DNA sequence variation, and DNA methylation status is routinely done using high throughput sequencing technologies. To analyze such multi-omics data and explore relationships, reliable bioinformatics systems are much needed. Existing systems are either for exploring curated data or for processing omics data in the form of a library such as R. Thus scientists have much difficulty in investigating relationships among gene expression, DNA sequence variation, and DNA methylation using multi-omics data. In this study, we report a system called BioVLAB-mCpG-SNP-EXPRESS for the integrated analysis of DNA methylation, sequence variation (SNPs), and gene expression for distinguishing cellular phenotypes at the pairwise and multiple phenotype levels. The system can be deployed on either the Amazon cloud or a publicly available high-performance computing node, and the data analysis and exploration of the analysis result can be conveniently done using a web-based interface. In order to alleviate analysis complexity, all the process are fully automated, and graphical workflow system is integrated to represent real-time analysis progression. The BioVLAB-mCpG-SNP-EXPRESS system works in three stages. First, it processes and analyzes multi-omics data as input in the form of the raw data, i.e., FastQ files. Second, various integrated analyses such as methylation vs. gene expression and mutation vs. methylation are performed. Finally, the analysis result can be explored in a number of ways through a web interface for the multi-level, multi-perspective exploration. Multi-level interpretation can be done by either gene, gene set, pathway or network level and multi-perspective exploration can be explored from either gene expression, DNA methylation, sequence variation, or their relationship perspective. The utility of the system is demonstrated by performing analysis of phenotypically distinct 30 breast cancer cell line data set. BioVLAB-mCpG-SNP-EXPRESS is available at http://biohealth.snu.ac.kr/software/biovlab_mcpg_snp_express/. Copyright © 2016 Elsevier Inc. All rights reserved.

A Novel System for Simultaneous or Sequential Integration of Multiple Gene-Loading Vectors into a Defined Site of a Human Artificial Chromosome

PubMed Central

Suzuki, Teruhiko; Kazuki, Yasuhiro; Oshimura, Mitsuo; Hara, Takahiko

2014-01-01

Human artificial chromosomes (HACs) are gene-delivery vectors suitable for introducing large DNA fragments into mammalian cells. Although a HAC theoretically incorporates multiple gene expression cassettes of unlimited DNA size, its application has been limited because the conventional gene-loading system accepts only one gene-loading vector (GLV) into a HAC. We report a novel method for the simultaneous or sequential integration of multiple GLVs into a HAC vector (designated as the SIM system) via combined usage of Cre, FLP, Bxb1, and φC31 recombinase/integrase. As a proof of principle, we first attempted simultaneous integration of three GLVs encoding EGFP, Venus, and TdTomato into a gene-loading site of a HAC in CHO cells. These cells successfully expressed all three fluorescent proteins. Furthermore, microcell-mediated transfer of HACs enabled the expression of those fluorescent proteins in recipient cells. We next demonstrated that GLVs could be introduced into a HAC one-by-one via reciprocal usage of recombinase/integrase. Lastly, we introduced a fourth GLV into a HAC after simultaneous integration of three GLVs by FLP-mediated DNA recombination. The SIM system expands the applicability of HAC vectors and is useful for various biomedical studies, including cell reprogramming. PMID:25303219

A novel system for simultaneous or sequential integration of multiple gene-loading vectors into a defined site of a human artificial chromosome.

PubMed

Suzuki, Teruhiko; Kazuki, Yasuhiro; Oshimura, Mitsuo; Hara, Takahiko

2014-01-01

Human artificial chromosomes (HACs) are gene-delivery vectors suitable for introducing large DNA fragments into mammalian cells. Although a HAC theoretically incorporates multiple gene expression cassettes of unlimited DNA size, its application has been limited because the conventional gene-loading system accepts only one gene-loading vector (GLV) into a HAC. We report a novel method for the simultaneous or sequential integration of multiple GLVs into a HAC vector (designated as the SIM system) via combined usage of Cre, FLP, Bxb1, and φC31 recombinase/integrase. As a proof of principle, we first attempted simultaneous integration of three GLVs encoding EGFP, Venus, and TdTomato into a gene-loading site of a HAC in CHO cells. These cells successfully expressed all three fluorescent proteins. Furthermore, microcell-mediated transfer of HACs enabled the expression of those fluorescent proteins in recipient cells. We next demonstrated that GLVs could be introduced into a HAC one-by-one via reciprocal usage of recombinase/integrase. Lastly, we introduced a fourth GLV into a HAC after simultaneous integration of three GLVs by FLP-mediated DNA recombination. The SIM system expands the applicability of HAC vectors and is useful for various biomedical studies, including cell reprogramming.

Snail1 transcription factor controls telomere transcription and integrity

PubMed Central

Mazzolini, Rocco; Gonzàlez, Núria; Garcia-Garijo, Andrea; Millanes-Romero, Alba; Peiró, Sandra; Smith, Susan

2018-01-01

Abstract Besides controlling epithelial-to-mesenchymal transition (EMT) and cell invasion, the Snail1 transcriptional factor also provides cells with cancer stem cell features. Since telomere maintenance is essential for stemness, we have examined the control of telomere integrity by Snail1. Fluorescence in situ hybridization (FISH) analysis indicates that Snail1-depleted mouse mesenchymal stem cells (MSC) have both a dramatic increase of telomere alterations and shorter telomeres. Remarkably, Snail1-deficient MSC present higher levels of both telomerase activity and the long non-coding RNA called telomeric repeat-containing RNA (TERRA), an RNA that controls telomere integrity. Accordingly, Snail1 expression downregulates expression of the telomerase gene (TERT) as well as of TERRA 2q, 11q and 18q. TERRA and TERT are transiently downregulated during TGFβ-induced EMT in NMuMG cells, correlating with Snail1 expression. Global transcriptome analysis indicates that ectopic expression of TERRA affects the transcription of some genes induced during EMT, such as fibronectin, whereas that of TERT does not modify those genes. We propose that Snail1 repression of TERRA is required not only for telomere maintenance but also for the expression of a subset of mesenchymal genes. PMID:29059385

Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles.

PubMed

Lu, Chenqi; Liu, Xiaoqin; Wang, Lin; Jiang, Ning; Yu, Jun; Zhao, Xiaobo; Hu, Hairong; Zheng, Saihua; Li, Xuelian; Wang, Guiying

2017-01-10

Due to genetic heterogeneity and variable diagnostic criteria, genetic studies of polycystic ovary syndrome are particularly challenging. Furthermore, lack of sufficiently large cohorts limits the identification of susceptibility genes contributing to polycystic ovary syndrome. Here, we carried out a systematic search of studies deposited in the Gene Expression Omnibus database through August 31, 2016. The present analyses included studies with: 1) patients with polycystic ovary syndrome and normal controls, 2) gene expression profiling of messenger RNA, and 3) sufficient data for our analysis. Ultimately, a total of 9 studies with 13 datasets met the inclusion criteria and were performed for the subsequent integrated analyses. Through comprehensive analyses, there were 13 genetic factors overlapped in all datasets and identified as significant specific genes for polycystic ovary syndrome. After quality control assessment, there were six datasets remained. Further gene ontology enrichment and pathway analyses suggested that differentially expressed genes mainly enriched in oocyte pathways. These findings provide potential molecular markers for diagnosis and prognosis of polycystic ovary syndrome, and need in-depth studies on the exact function and mechanism in polycystic ovary syndrome.

Precise integration of inducible transcriptional elements (PrIITE) enables absolute control of gene expression.

PubMed

Pinto, Rita; Hansen, Lars; Hintze, John; Almeida, Raquel; Larsen, Sylvester; Coskun, Mehmet; Davidsen, Johanne; Mitchelmore, Cathy; David, Leonor; Troelsen, Jesper Thorvald; Bennett, Eric Paul

2017-07-27

Tetracycline-based inducible systems provide powerful methods for functional studies where gene expression can be controlled. However, the lack of tight control of the inducible system, leading to leakiness and adverse effects caused by undesirable tetracycline dosage requirements, has proven to be a limitation. Here, we report that the combined use of genome editing tools and last generation Tet-On systems can resolve these issues. Our principle is based on precise integration of inducible transcriptional elements (coined PrIITE) targeted to: (i) exons of an endogenous gene of interest (GOI) and (ii) a safe harbor locus. Using PrIITE cells harboring a GFP reporter or CDX2 transcription factor, we demonstrate discrete inducibility of gene expression with complete abrogation of leakiness. CDX2 PrIITE cells generated by this approach uncovered novel CDX2 downstream effector genes. Our results provide a strategy for characterization of dose-dependent effector functions of essential genes that require absence of endogenous gene expression. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.

PubMed

Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang

2017-08-23

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.

Identification of miRNA-Mediated Core Gene Module for Glioma Patient Prediction by Integrating High-Throughput miRNA, mRNA Expression and Pathway Structure

PubMed Central

Han, Junwei; Shang, Desi; Zhang, Yunpeng; Zhang, Wei; Yao, Qianlan; Han, Lei; Xu, Yanjun; Yan, Wei; Bao, Zhaoshi; You, Gan; Jiang, Tao; Kang, Chunsheng; Li, Xia

2014-01-01

The prognosis of glioma patients is usually poor, especially in patients with glioblastoma (World Health Organization (WHO) grade IV). The regulatory functions of microRNA (miRNA) on genes have important implications in glioma cell survival. However, there are not many studies that have investigated glioma survival by integrating miRNAs and genes while also considering pathway structure. In this study, we performed sample-matched miRNA and mRNA expression profilings to systematically analyze glioma patient survival. During this analytical process, we developed pathway-based random walk to identify a glioma core miRNA-gene module, simultaneously considering pathway structure information and multi-level involvement of miRNAs and genes. The core miRNA-gene module we identified was comprised of four apparent sub-modules; all four sub-modules displayed a significant correlation with patient survival in the testing set (P-values≤0.001). Notably, one sub-module that consisted of 6 miRNAs and 26 genes also correlated with survival time in the high-grade subgroup (WHO grade III and IV), P-value = 0.0062. Furthermore, the 26-gene expression signature from this sub-module had robust predictive power in four independent, publicly available glioma datasets. Our findings suggested that the expression signatures, which were identified by integration of miRNA and gene level, were closely associated with overall survival among the glioma patients with various grades. PMID:24809850

Systems analysis of transcriptome data provides new hypotheses about Arabidopsis root response to nitrate treatments

PubMed Central

Canales, Javier; Moyano, Tomás C.; Villarroel, Eva; Gutiérrez, Rodrigo A.

2014-01-01

Nitrogen (N) is an essential macronutrient for plant growth and development. Plants adapt to changes in N availability partly by changes in global gene expression. We integrated publicly available root microarray data under contrasting nitrate conditions to identify new genes and functions important for adaptive nitrate responses in Arabidopsis thaliana roots. Overall, more than 2000 genes exhibited changes in expression in response to nitrate treatments in Arabidopsis thaliana root organs. Global regulation of gene expression by nitrate depends largely on the experimental context. However, despite significant differences from experiment to experiment in the identity of regulated genes, there is a robust nitrate response of specific biological functions. Integrative gene network analysis uncovered relationships between nitrate-responsive genes and 11 highly co-expressed gene clusters (modules). Four of these gene network modules have robust nitrate responsive functions such as transport, signaling, and metabolism. Network analysis hypothesized G2-like transcription factors are key regulatory factors controlling transport and signaling functions. Our meta-analysis highlights the role of biological processes not studied before in the context of the nitrate response such as root hair development and provides testable hypothesis to advance our understanding of nitrate responses in plants. PMID:24570678

A single EBV-based vector for stable episomal maintenance and expression of GFP in human embryonic stem cells.

PubMed

Thyagarajan, Bhaskar; Scheyhing, Kelly; Xue, Haipeng; Fontes, Andrew; Chesnut, Jon; Rao, Mahendra; Lakshmipathy, Uma

2009-03-01

Stable expression of transgenes in stem cells has been a challenge due to the nonavailability of efficient transfection methods and the inability of transgenes to support sustained gene expression. Several methods have been reported to stably modify both embryonic and adult stem cells. These methods rely on integration of the transgene into the genome of the host cell, which could result in an expression pattern dependent on the number of integrations and the genomic locus of integration. To overcome this issue, site-specific integration methods mediated by integrase, adeno-associated virus or via homologous recombination have been used to generate stable human embryonic stem cell (hESC) lines. In this study, we describe a vector that is maintained episomally in hESCs. The vector used in this study is based on components derived from the Epstein-Barr virus, containing the Epstein-Barr virus nuclear antigen 1 expression cassette and the OriP origin of replication. The vector also expresses the drug-resistance marker gene hygromycin, which allows for selection and long-term maintenance of cells harboring the plasmid. Using this vector system, we show sustained expression of green fluorescent protein in undifferentiated hESCs and their differentiating embryoid bodies. In addition, the stable hESC clones show comparable expression with and without drug selection. Consistent with this observation, bulk-transfected adipose tissue-derived mesenchymal stem cells showed persistent marker gene expression as they differentiate into adipocytes, osteoblasts and chondroblasts. Episomal vectors offer a fast and efficient method to create hESC reporter lines, which in turn allows one to test the effect of overexpression of various genes on stem cell growth, proliferation and differentiation.

Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information.

PubMed

Hieke, Stefanie; Benner, Axel; Schlenl, Richard F; Schumacher, Martin; Bullinger, Lars; Binder, Harald

2016-08-30

High-throughput technology allows for genome-wide measurements at different molecular levels for the same patient, e.g. single nucleotide polymorphisms (SNPs) and gene expression. Correspondingly, it might be beneficial to also integrate complementary information from different molecular levels when building multivariable risk prediction models for a clinical endpoint, such as treatment response or survival. Unfortunately, such a high-dimensional modeling task will often be complicated by a limited overlap of molecular measurements at different levels between patients, i.e. measurements from all molecular levels are available only for a smaller proportion of patients. We propose a sequential strategy for building clinical risk prediction models that integrate genome-wide measurements from two molecular levels in a complementary way. To deal with partial overlap, we develop an imputation approach that allows us to use all available data. This approach is investigated in two acute myeloid leukemia applications combining gene expression with either SNP or DNA methylation data. After obtaining a sparse risk prediction signature e.g. from SNP data, an automatically selected set of prognostic SNPs, by componentwise likelihood-based boosting, imputation is performed for the corresponding linear predictor by a linking model that incorporates e.g. gene expression measurements. The imputed linear predictor is then used for adjustment when building a prognostic signature from the gene expression data. For evaluation, we consider stability, as quantified by inclusion frequencies across resampling data sets. Despite an extremely small overlap in the application example with gene expression and SNPs, several genes are seen to be more stably identified when taking the (imputed) linear predictor from the SNP data into account. In the application with gene expression and DNA methylation, prediction performance with respect to survival also indicates that the proposed approach might work well. We consider imputation of linear predictor values to be a feasible and sensible approach for dealing with partial overlap in complementary integrative analysis of molecular measurements at different levels. More generally, these results indicate that a complementary strategy for integrating different molecular levels can result in more stable risk prediction signatures, potentially providing a more reliable insight into the underlying biology.

Integrated analysis of miRNA and mRNA expression data identifies multiple miRNAs regulatory networks for the tumorigenesis of colorectal cancer.

PubMed

Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-06-15

Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.

Sox17 drives functional engraftment of endothelium converted from non-vascular cells.

PubMed

Schachterle, William; Badwe, Chaitanya R; Palikuqi, Brisa; Kunar, Balvir; Ginsberg, Michael; Lis, Raphael; Yokoyama, Masataka; Elemento, Olivier; Scandura, Joseph M; Rafii, Shahin

2017-01-16

Transplanting vascular endothelial cells (ECs) to support metabolism and express regenerative paracrine factors is a strategy to treat vasculopathies and to promote tissue regeneration. However, transplantation strategies have been challenging to develop, because ECs are difficult to culture and little is known about how to direct them to stably integrate into vasculature. Here we show that only amniotic cells could convert to cells that maintain EC gene expression. Even so, these converted cells perform sub-optimally in transplantation studies. Constitutive Akt signalling increases expression of EC morphogenesis genes, including Sox17, shifts the genomic targeting of Fli1 to favour nearby Sox consensus sites and enhances the vascular function of converted cells. Enforced expression of Sox17 increases expression of morphogenesis genes and promotes integration of transplanted converted cells into injured vessels. Thus, Ets transcription factors specify non-vascular, amniotic cells to EC-like cells, whereas Sox17 expression is required to confer EC function.

Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

USDA-ARS?s Scientific Manuscript database

The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

iGC-an integrated analysis package of gene expression and copy number alteration.

PubMed

Lai, Yi-Pin; Wang, Liang-Bo; Wang, Wei-An; Lai, Liang-Chuan; Tsai, Mong-Hsun; Lu, Tzu-Pin; Chuang, Eric Y

2017-01-14

With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual. We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance. The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .

[Application of dhfr gene negative Chinese hamster ovary cell line to express hepatitis B virus surface antigen].

PubMed

Yi, Y; Zhang, M; Liu, C

2001-06-01

To set up an efficient expressing system for recombinant hepatitis B virus surface antigen (HBsAg) in dhfr gene negative CHO cell line. HBsAg gene expressing plasmid pCI-dhfr-S was constructed by integrating HBsAg gene into plasmid pCI which carries dhfr gene. The HBsAg expressing cell line was set up by transfection of plasmid pCI-dhfr-S into dhfr gene negative CHO cell line in the way of lipofectin. Under the selective pressure of MTX, 18 of 28 clonized cell lines expressed HBsAg, 4 of them reached a high titer of 1:32 and protein content 1-3 micrograms/ml. In this study, the high level expression of HBsAg demonstrated that the dhfr negative mammalian cell line when recombined with plasmid harboring the corresponding deleted gene can efficiently express the foreign gene. The further steps toward building optimum conditions of the expressing system and the increase of expressed product are under study.

Premethylation of Foreign DNA Improves Integrative Transformation Efficiency in Synechocystis sp. Strain PCC 6803

PubMed Central

Wang, Bo; Yu, Jianping

2015-01-01

Restriction digestion of foreign DNA is one of the key biological barriers against genetic transformation in microorganisms. To establish a high-efficiency transformation protocol in the model cyanobacterium, Synechocystis sp. strain PCC 6803 (Synechocystis 6803), we investigated the effects of premethylation of foreign DNA on the integrative transformation of this strain. In this study, two type II methyltransferase-encoding genes, i.e., sll0729 (gene M) and slr0214 (gene C), were cloned from the chromosome of Synechocystis 6803 and expressed in Escherichia coli harboring an integration plasmid. After premethylation treatment in E. coli, the integration plasmid was extracted and used for transformation of Synechocystis 6803. The results showed that although expression of methyltransferase M had little impact on the transformation of Synechocystis 6803, expression of methyltransferase C resulted in 11- to 161-fold-higher efficiency in the subsequent integrative transformation of Synechocystis 6803. Effective expression of methyltransferase C, which could be achieved by optimizing the 5′ untranslated region, was critical to efficient premethylation of the donor DNA and thus high transformation efficiency in Synechocystis 6803. Since premethylating foreign DNA prior to transforming Synechocystis avoids changing the host genetic background, the study thus provides an improved method for high-efficiency integrative transformation of Synechocystis 6803. PMID:26452551

Identification of diagnostic markers in colorectal cancer via integrative epigenomics and genomics data

PubMed Central

KOK-SIN, TEOW; MOKHTAR, NORFILZA MOHD; HASSAN, NUR ZARINA ALI; SAGAP, ISMAIL; ROSE, ISA MOHAMED; HARUN, ROSLAN; JAMAL, RAHMAN

2015-01-01

Apart from genetic mutations, epigenetic alteration is a common phenomenon that contributes to neoplastic transformation in colorectal cancer. Transcriptional silencing of tumor-suppressor genes without changes in the DNA sequence is explained by the existence of promoter hypermethylation. To test this hypothesis, we integrated the epigenome and transcriptome data from a similar set of colorectal tissue samples. Methylation profiling was performed using the Illumina InfiniumHumanMethylation27 BeadChip on 55 paired cancer and adjacent normal epithelial cells. Fifteen of the 55 paired tissues were used for gene expression profiling using the Affymetrix GeneChip Human Gene 1.0 ST array. Validation was carried out on 150 colorectal tissues using the methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) technique. PCA and supervised hierarchical clustering in the two microarray datasets showed good separation between cancer and normal samples. Significant genes from the two analyses were obtained based on a ≥2-fold change and a false discovery rate (FDR) P-value of <0.05. We identified 1,081 differentially hypermethylated CpG sites and 36 hypomethylated CpG sites. We also found 709 upregulated and 699 downregulated genes from the gene expression profiling. A comparison of the two datasets revealed 32 overlapping genes with 27 being hypermethylated with downregulated expression and 4 hypermethylated with upregulated expression. One gene was found to be hypomethylated and downregulated. The most enriched molecular pathway identified was cell adhesion molecules that involved 4 overlapped genes, JAM2, NCAM1, ITGA8 and CNTN1. In the present study, we successfully identified a group of genes that showed methylation and gene expression changes in well-defined colorectal cancer tissues with high purity. The integrated analysis gives additional insight regarding the regulation of colorectal cancer-associated genes and their underlying mechanisms that contribute to colorectal carcinogenesis. PMID:25997610

Complex genomic rearrangement in CCS-LacZ transgenic mice.

PubMed

Stroud, Dina Myers; Darrow, Bruce J; Kim, Sang Do; Zhang, Jie; Jongbloed, Monique R M; Rentschler, Stacey; Moskowitz, Ivan P G; Seidman, Jonathan; Fishman, Glenn I

2007-02-01

The cardiac conduction system (CCS)-lacZ insertional mouse mutant strain genetically labels the developing and mature CCS. This pattern of expression is presumed to reflect the site of transgene integration rather than regulatory elements within the transgene proper. We sought to characterize the genomic structure of the integration locus and identify nearby gene(s) that might potentially confer the observed CCS-specific transcription. We found rearrangement of chromosome 7 between regions D1 and E1 with altered transcription of multiple genes in the D1 region. Several lines of evidence suggested that regulatory elements from at least one gene, Slco3A1, influenced CCS-restricted reporter gene expression. In embryonic hearts, Slco3A1 was expressed in a spatial pattern similar to the CCS-lacZ transgene and was similarly neuregulin-responsive. At later stages, however, expression patterns of the transgene and Slco3A1 diverged, suggesting that the Slco3A1 locus may be necessary, but not sufficient to confer CCS-specific transgene expression in the CCS-lacZ line. (c) 2007 Wiley-Liss, Inc.

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis

DOE PAGES

Wang, Jack P.; Matthews, Megan L.; Williams, Cranos M.; ...

2018-04-20

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux,more » metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.« less

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis

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

Wang, Jack P.; Matthews, Megan L.; Williams, Cranos M.

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux,more » metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.« less

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis.

PubMed

Wang, Jack P; Matthews, Megan L; Williams, Cranos M; Shi, Rui; Yang, Chenmin; Tunlaya-Anukit, Sermsawat; Chen, Hsi-Chuan; Li, Quanzi; Liu, Jie; Lin, Chien-Yuan; Naik, Punith; Sun, Ying-Hsuan; Loziuk, Philip L; Yeh, Ting-Feng; Kim, Hoon; Gjersing, Erica; Shollenberger, Todd; Shuford, Christopher M; Song, Jina; Miller, Zachary; Huang, Yung-Yun; Edmunds, Charles W; Liu, Baoguang; Sun, Yi; Lin, Ying-Chung Jimmy; Li, Wei; Chen, Hao; Peszlen, Ilona; Ducoste, Joel J; Ralph, John; Chang, Hou-Min; Muddiman, David C; Davis, Mark F; Smith, Chris; Isik, Fikret; Sederoff, Ronald; Chiang, Vincent L

2018-04-20

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux, metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.

Depletion of HPV16 early genes induces autophagy and senescence in a cervical carcinogenesis model, regardless of viral physical state.

PubMed

Hanning, Jennifer E; Saini, Harpreet K; Murray, Matthew J; Caffarel, Maria M; van Dongen, Stijn; Ward, Dawn; Barker, Emily M; Scarpini, Cinzia G; Groves, Ian J; Stanley, Margaret A; Enright, Anton J; Pett, Mark R; Coleman, Nicholas

2013-11-01

In cervical carcinomas, high-risk human papillomavirus (HR-HPV) may be integrated into host chromosomes or remain extra-chromosomal (episomal). We used the W12 cervical keratinocyte model to investigate the effects of HPV16 early gene depletion on in vitro cervical carcinogenesis pathways, particularly effects shared by cells with episomal versus integrated HPV16 DNA. Importantly, we were able to study the specific cellular consequences of viral gene depletion by using short interfering RNAs known not to cause phenotypic or transcriptional off-target effects in keratinocytes. We found that while cervical neoplastic progression in vitro was characterized by dynamic changes in HPV16 transcript levels, viral early gene expression was required for cell survival at all stages of carcinogenesis, regardless of viral physical state, levels of early gene expression or histology in organotypic tissue culture. Moreover, HPV16 early gene depletion induced changes in host gene expression that were common to both episome-containing and integrant-containing cells. In particular, we observed up-regulation of autophagy genes, associated with enrichment of senescence and innate immune-response pathways, including the senescence-associated secretory phenotype (SASP). In keeping with these observations, HPV16 early gene depletion induced autophagy in both episome-containing and integrant-containing W12 cells, as evidenced by the appearance of autophagosomes, punctate expression of the autophagy marker LC3, conversion of LC3B-I to LC3B-II, and reduced levels of the autophagy substrate p62. Consistent with the reported association between autophagy and senescence pathways, HPV16 early gene depletion induced expression of the senescence marker beta-galactosidase and increased secretion of the SASP-related protein IGFBP3. Together, these data indicate that depleting HR-HPV early genes would be of potential therapeutic benefit in all cervical carcinogenesis pathways, regardless of viral physical state. In addition, the senescence/SASP response associated with autophagy induction may promote beneficial immune effects in bystander cells. Copyright © 2013 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Integrative Approach to Pain Genetics Identifies Pain Sensitivity Loci across Diseases

PubMed Central

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

2012-01-01

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

Integration Site and Clonal Expansion in Human Chronic Retroviral Infection and Gene Therapy

PubMed Central

Niederer, Heather A.; Bangham, Charles R. M.

2014-01-01

Retroviral vectors have been successfully used therapeutically to restore expression of genes in a range of single-gene diseases, including several primary immunodeficiency disorders. Although clinical trials have shown remarkable results, there have also been a number of severe adverse events involving malignant outgrowth of a transformed clonal population. This clonal expansion is influenced by the integration site profile of the viral integrase, the transgene expressed, and the effect of the viral promoters on the neighbouring host genome. Infection with the pathogenic human retrovirus HTLV-1 also causes clonal expansion of cells containing an integrated HTLV-1 provirus. Although the majority of HTLV-1-infected people remain asymptomatic, up to 5% develop an aggressive T cell malignancy. In this review we discuss recent findings on the role of the genomic integration site in determining the clonality and the potential for malignant transformation of cells carrying integrated HTLV-1 or gene therapy vectors, and how these results have contributed to the understanding of HTLV-1 pathogenesis and to improvements in gene therapy vector safety. PMID:25365582

Integration Host Factor Is Required for RpoN-Dependent hrpL Gene Expression and Controls Motility by Positively Regulating rsmB sRNA in Erwinia amylovora.

PubMed

Lee, Jae Hoon; Zhao, Youfu

2016-01-01

Erwinia amylovora requires an hrp-type III secretion system (T3SS) to cause disease. It has been reported that HrpL, the master regulator of T3SS, is transcriptionally regulated by sigma factor 54 (RpoN), YhbH, and HrpS. In this study, the role of integration host factor (IHF) in regulating hrpL and T3SS gene expression was investigated. IHF is a nucleoid-associated protein that regulates gene expression by influencing nucleoid structure and DNA bending. Our results showed that both ihfA and ihfB mutants of E. amylovora did not induce necrotic lesions on pear fruits. Growth of both mutants was greatly reduced, and expression of the hrpL and T3SS genes was significantly down-regulated as compared with those of the wild type. In addition, expression of the ihfA, but not the ihfB gene, was under auto-suppression by IHF. Furthermore, both ihfA and ihfB mutants were hypermotile, due to significantly reduced expression of small RNA (sRNA) rsmB. Electrophoresis mobility shift assay further confirmed that IHF binds to the promoters of the hrpL and ihfA genes, as well as the rsmB sRNA gene. These results indicate that IHF is required for RpoN-dependent hrpL gene expression and virulence, and controls motility by positively regulating the rsmB sRNA in E. amylovora.

Long-distance interaction of the integrated HPV fragment with MYC gene and 8q24.22 region upregulating the allele-specific MYC expression in HeLa cells.

PubMed

Shen, Congle; Liu, Yongzhen; Shi, Shu; Zhang, Ruiyang; Zhang, Ting; Xu, Qiang; Zhu, Pengfei; Chen, Xiangmei; Lu, Fengmin

2017-08-01

Human papillomavirus (HPV) infection is the most important risk factor for cervical cancer development. In HeLa cell line, the HPV viral genome is integrated at 8q24 in one allele of chromosome 8. It has been reported that the HPV fragment integrated in HeLa genome can cis-activate the expression of proto-oncogene MYC, which is located at 500 kb downstream of the integrated site. However, the underlying molecular mechanism of this regulation is unknown. A recent study reported that MYC was highly expressed exclusively from the HPV-integrated haplotype, and a long-range chromatin interaction between the integrated HPV fragment and MYC gene has been hypothesized. In this study, we provided the experimental evidences supporting this long-range chromatin interaction in HeLa cells by using Chromosome Conformation Capture (3C) method. We found that the integrated HPV fragment, MYC and 8q24.22 was close to each other and might form a trimer in spatial location. When knocking out the integrated HPV fragment or 8q24.22 region from chromosome 8 by CRISPR/Cas9 system, the expression of MYC reduced dramatically in HeLa cells. Interestingly, decreased expression was only observed in three from eight cell clones, when only one 8q24.22 allele was knocked out. Functionally, HPV knockout caused senescence-associated acidic β-gal activity in HeLa cells. These data indicate a long-distance interaction of the integrated HPV fragment with MYC gene and 8q24.22 region, providing an alternative mechanism relevant to the carcinogenicity of HPV integration. © 2017 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

Long‐distance interaction of the integrated HPV fragment with MYC gene and 8q24.22 region upregulating the allele‐specific MYC expression in HeLa cells

PubMed Central

Shen, Congle; Liu, Yongzhen; Shi, Shu; Zhang, Ruiyang; Zhang, Ting; Xu, Qiang; Zhu, Pengfei; Lu, Fengmin

2017-01-01

Human papillomavirus (HPV) infection is the most important risk factor for cervical cancer development. In HeLa cell line, the HPV viral genome is integrated at 8q24 in one allele of chromosome 8. It has been reported that the HPV fragment integrated in HeLa genome can cis‐activate the expression of proto‐oncogene MYC, which is located at 500 kb downstream of the integrated site. However, the underlying molecular mechanism of this regulation is unknown. A recent study reported that MYC was highly expressed exclusively from the HPV‐integrated haplotype, and a long‐range chromatin interaction between the integrated HPV fragment and MYC gene has been hypothesized. In this study, we provided the experimental evidences supporting this long‐range chromatin interaction in HeLa cells by using Chromosome Conformation Capture (3C) method. We found that the integrated HPV fragment, MYC and 8q24.22 was close to each other and might form a trimer in spatial location. When knocking out the integrated HPV fragment or 8q24.22 region from chromosome 8 by CRISPR/Cas9 system, the expression of MYC reduced dramatically in HeLa cells. Interestingly, decreased expression was only observed in three from eight cell clones, when only one 8q24.22 allele was knocked out. Functionally, HPV knockout caused senescence‐associated acidic β‐gal activity in HeLa cells. These data indicate a long‐distance interaction of the integrated HPV fragment with MYC gene and 8q24.22 region, providing an alternative mechanism relevant to the carcinogenicity of HPV integration. PMID:28470669

Genetic improvement of Escherichia coli for ethanol production: Chromosomal integration of Zymomonas mobilis genes encoding pyruvate decarboxylase and alcohol dehydrogenase II

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

Ohta, Kazuyoshi; Beall, D.S.; Mejia, J.P.

1991-04-01

Zymomonas mobilis genes for pyruvate decarboxylase (pdc) and alcohol dehydrogenase II (adhB) were integrated into the Escherichia coli chromosome within or near the pyruvate formate-lyase gene (pfl). Integration improved the stability of the Z. mobilis genes in E. coli, but further selection was required to increase expression. Spontaneous mutants were selected for resistance to high levels of chloramphenicol that also expressed high levels of the Z. mobilis genes. Analogous mutants were selected for increased expression of alcohol dehydrogenase on aldehyde indicator plates. These mutants were functionally equivalent to the previous plasmid-based strains for the fermentation of xylose and glucose tomore » ethanol. Ethanol concentrations of 54.4 and 41.6 g/liter were obtained from 10% glucose and 8% xylose, respectively. The efficiency of conversion exceeded theoretical limits (0.51 g of ethanol/g of sugar) on the basis of added sugars because of the additional production of ethanol from the catabolism of complex nutrients. Further mutations were introduced to inactivate succinate production (frd) and to block homologous recombination (recA).« less

Efficacy and site-specificity of adenoviral vector integration mediated by the phage φC31 integrase.

PubMed

Robert, Marc-André; Zeng, Yue; Raymond, Benoît; Desfossé, Laurie; Mairey, Emilie; Tremblay, Jacques P; Massie, Bernard; Gilbert, Rénald

2012-12-01

Adenoviral vectors deleted of all their viral genes (helper-dependent [HD]) are efficient gene-transfer vehicles. Because transgene expression is rapidly lost in actively dividing cells, we investigated the feasibility of using phage φC31 integrase (φC31-Int) to integrate an HD carrying an attB site and the puromycin resistance gene into human cells (HeLa) and murine myoblasts (C2C12) by co-infection with a second HD-expressing φC31-Int. Because the HD genome is linear, we also investigated whether its circularization, through expression of Cre using a third HD, affects integration. Efficacy and specificity were determined by scoring the number of puromycin-resistant colonies and by sequencing integration sites. Unexpectedly, circularization of HD was unnecessary and it even reduced the integration efficacy. The maximum integration efficacy achieved was 0.5% in HeLa cells and 0.1% in C2C12 myoblasts. Up to 76% of the integration events occurred at pseudo attP sites and previously characterized hotspots were found. A small (two- to three-fold) increase in the number of γ-H2AX positive foci, accompanied by no noticeable change in γ-H2AX expression, indicated the low genotoxicity of φC31-Int. In conclusion, integration of HD mediated by φC31-Int is an attractive alternative to engineer cells, because it permits site-specific integration of large DNA fragments with low genotoxicity.

Delimiting regulatory sequences of the Drosophila melanogaster Ddc gene.

PubMed Central

Hirsh, J; Morgan, B A; Scholnick, S B

1986-01-01

We delimited sequences necessary for in vivo expression of the Drosophila melanogaster dopa decarboxylase gene Ddc. The expression of in vitro-altered genes was assayed following germ line integration via P-element vectors. Sequences between -209 and -24 were necessary for normally regulated expression, although genes lacking these sequences could be expressed at 10 to 50% of wild-type levels at specific developmental times. These genes showed components of normal developmental expression, which suggests that they retain some regulatory elements. All Ddc genes lacking the normal immediate 5'-flanking sequences were grossly deficient in larval central nervous system expression. Thus, this upstream region must contain at least one element necessary for this expression. A mutated Ddc gene without a normal TATA boxlike sequence used the normal RNA start points, indicating that this sequences is not required for start point specificity. Images PMID:3099170

Effects of a petunia scaffold/matrix attachment region on copy number dependency and stability of transgene expression in Nicotiana tabacum.

PubMed

Dietz-Pfeilstetter, Antje; Arndt, Nicola; Manske, Ulrike

2016-04-01

Transgenes in genetically modified plants are often not reliably expressed during development or in subsequent generations. Transcriptional gene silencing (TGS) as well as post-transcriptional gene silencing (PTGS) have been shown to occur in transgenic plants depending on integration pattern, copy number and integration site. In an effort to reduce position effects, to prevent read-through transcription and to provide a more accessible chromatin structure, a P35S-ß-glucuronidase (P35S-gus) transgene flanked by a scaffold/matrix attachment region from petunia (Petun-SAR), was introduced in Nicotiana tabacum plants by Agrobacterium tumefaciens mediated transformation. It was found that Petun-SAR mediates enhanced expression and copy number dependency up to 2 gene copies, but did not prevent gene silencing in transformants with multiple and rearranged gene copies. However, in contrast to the non-SAR transformants where silencing was irreversible and proceeded during long-term vegetative propagation and in progeny plants, gus expression in Petun-SAR plants was re-established in the course of development. Gene silencing was not necessarily accompanied by DNA methylation, while the gus transgene could still be expressed despite considerable CG methylation within the coding region.

Integrating toxin gene expression, growth and fumonisin B1 and B2 production by a strain of Fusarium verticillioides under different environmental factors

PubMed Central

Medina, Angel; Schmidt-Heydt, Markus; Cárdenas-Chávez, Diana L.; Parra, Roberto; Geisen, Rolf; Magan, Naresh

2013-01-01

The objective of this study was to integrate data on the effect of water activity (aw; 0.995–0.93) and temperature (20–35°C) on activation of the biosynthetic FUM genes, growth and the mycotoxins fumonisin (FB1, FB2) by Fusarium verticillioides in vitro. The relative expression of nine biosynthetic cluster genes (FUM1, FUM7, FUM10, FUM11, FUM12, FUM13, FUM14, FUM16 and FUM19) in relation to the environmental factors was determined using a microarray analysis. The expression was related to growth and phenotypic FB1 and FB2 production. These data were used to develop a mixed-growth-associated product formation model and link this to a linear combination of the expression data for the nine genes. The model was then validated by examining datasets outside the model fitting conditions used (35°C). The relationship between the key gene (FUM1) and other genes in the cluster (FUM11, FUM13, FUM9, FUM14) were examined in relation to aw, temperature, FB1 and FB2 production by developing ternary diagrams of relative expression. This model is important in developing an integrated systems approach to develop prevention strategies to control fumonisin biosynthesis in staple food commodities and could also be used to predict the potential impact that climate change factors may have on toxin production. PMID:23697716

Singing-driven gene expression in the developing songbird brain

PubMed Central

Johnson, Frank; Whitney, Osceola

2014-01-01

Neural and behavioral development arises from an integration of genetic and environmental influences, yet specifying the nature of this interaction remains a primary problem in neuroscience. Here, we review molecular and behavioral studies that focus on the role of singing-driven gene expression during neural and vocal development in the male zebra finch (Taeniopygia guttata), a songbird that learns a species-typical vocal pattern during juvenile development by imitating an adult male tutor. A primary aim of our lab has been to identify naturally-occurring environmental influences that shape the propensity to sing. This ethological approach underlies our theoretical perspective, which is to integrate the significance of singing-driven gene expression into a broader ecological context. PMID:16129463

MEPD: a Medaka gene expression pattern database

PubMed Central

Henrich, Thorsten; Ramialison, Mirana; Quiring, Rebecca; Wittbrodt, Beate; Furutani-Seiki, Makoto; Wittbrodt, Joachim; Kondoh, Hisato

2003-01-01

The Medaka Expression Pattern Database (MEPD) stores and integrates information of gene expression during embryonic development of the small freshwater fish Medaka (Oryzias latipes). Expression patterns of genes identified by ESTs are documented by images and by descriptions through parameters such as staining intensity, category and comments and through a comprehensive, hierarchically organized dictionary of anatomical terms. Sequences of the ESTs are available and searchable through BLAST. ESTs in the database are clustered upon entry and have been blasted against public data-bases. The BLAST results are updated regularly, stored within the database and searchable. The MEPD is a project within the Medaka Genome Initiative (MGI) and entries will be interconnected to integrated genomic map databases. MEPD is accessible through the WWW at http://medaka.dsp.jst.go.jp/MEPD. PMID:12519950

Network-based differential gene expression analysis suggests cell cycle related genes regulated by E2F1 underlie the molecular difference between smoker and non-smoker lung adenocarcinoma

PubMed Central

2013-01-01

Background Differential gene expression (DGE) analysis is commonly used to reveal the deregulated molecular mechanisms of complex diseases. However, traditional DGE analysis (e.g., the t test or the rank sum test) tests each gene independently without considering interactions between them. Top-ranked differentially regulated genes prioritized by the analysis may not directly relate to the coherent molecular changes underlying complex diseases. Joint analyses of co-expression and DGE have been applied to reveal the deregulated molecular modules underlying complex diseases. Most of these methods consist of separate steps: first to identify gene-gene relationships under the studied phenotype then to integrate them with gene expression changes for prioritizing signature genes, or vice versa. It is warrant a method that can simultaneously consider gene-gene co-expression strength and corresponding expression level changes so that both types of information can be leveraged optimally. Results In this paper, we develop a gene module based method for differential gene expression analysis, named network-based differential gene expression (nDGE) analysis, a one-step integrative process for prioritizing deregulated genes and grouping them into gene modules. We demonstrate that nDGE outperforms existing methods in prioritizing deregulated genes and discovering deregulated gene modules using simulated data sets. When tested on a series of smoker and non-smoker lung adenocarcinoma data sets, we show that top differentially regulated genes identified by the rank sum test in different sets are not consistent while top ranked genes defined by nDGE in different data sets significantly overlap. nDGE results suggest that a differentially regulated gene module, which is enriched for cell cycle related genes and E2F1 targeted genes, plays a role in the molecular differences between smoker and non-smoker lung adenocarcinoma. Conclusions In this paper, we develop nDGE to prioritize deregulated genes and group them into gene modules by simultaneously considering gene expression level changes and gene-gene co-regulations. When applied to both simulated and empirical data, nDGE outperforms the traditional DGE method. More specifically, when applied to smoker and non-smoker lung cancer sets, nDGE results illustrate the molecular differences between smoker and non-smoker lung cancer. PMID:24341432

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

PubMed

Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

2013-01-01

With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

Dynamic Visualization of Co-expression in Systems Genetics Data

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

New, Joshua Ryan; Huang, Jian; Chesler, Elissa J

2008-01-01

Biologists hope to address grand scientific challenges by exploring the abundance of data made available through modern microarray technology and other high-throughput techniques. The impact of this data, however, is limited unless researchers can effectively assimilate such complex information and integrate it into their daily research; interactive visualization tools are called for to support the effort. Specifically, typical studies of gene co-expression require novel visualization tools that enable the dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These tools should allow biologists to develop an intuitive understanding of the structure of biologicalmore » networks and discover genes which reside in critical positions in networks and pathways. By using a graph as a universal data representation of correlation in gene expression data, our novel visualization tool employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool for interacting with gene co-expression data integrates techniques such as: graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by querying an optimized b-tree, dynamic level-of-detail graph abstraction, and template-based fuzzy classification using neural networks. We demonstrate our system using a real-world workflow from a large-scale, systems genetics study of mammalian gene co-expression.« less

Significant differences in genotoxicity induced by retrovirus integration in human T cells and induced pluripotent stem cells.

PubMed

Zheng, Weiyan; Wang, Yingjia; Chang, Tammy; Huang, He; Yee, Jiing-Kuan

2013-04-25

Retrovirus is frequently used in the genetic modification of mammalian cells and the establishment of induced pluripotent stem cells (iPSCs) via cell reprogramming. Vector-induced genotoxicity could induce profound effect on the physiology and function of these stem cells and their differentiated progeny. We analyzed retrovirus-induced genotoxicity in somatic cell Jurkat and two iPSC lines. In Jurkat cells, retrovirus frequently activated host gene expression and gene activation was not dependent on the distance between the integration site and the transcription start site of the host gene. In contrast, retrovirus frequently down-regulated host gene expression in iPSCs, possibly due to the action of chromatin silencing that spreads from the provirus to the nearby host gene promoter. Our data raises the issue that some of the phenotypic variability observed among iPSC clones derived from the same parental cell line may be caused by retrovirus-induced gene expression changes rather than by the reprogramming process itself. It also underscores the importance of characterizing retrovirus integration and carrying out risk assessment of iPSCs before they can be applied in basic research and clinics. Copyright © 2013 Elsevier B.V. All rights reserved.

Immuno-Navigator, a batch-corrected coexpression database, reveals cell type-specific gene networks in the immune system

PubMed Central

Vandenbon, Alexis; Dinh, Viet H.; Mikami, Norihisa; Kitagawa, Yohko; Teraguchi, Shunsuke; Ohkura, Naganari; Sakaguchi, Shimon

2016-01-01

High-throughput gene expression data are one of the primary resources for exploring complex intracellular dynamics in modern biology. The integration of large amounts of public data may allow us to examine general dynamical relationships between regulators and target genes. However, obstacles for such analyses are study-specific biases or batch effects in the original data. Here we present Immuno-Navigator, a batch-corrected gene expression and coexpression database for 24 cell types of the mouse immune system. We systematically removed batch effects from the underlying gene expression data and showed that this removal considerably improved the consistency between inferred correlations and prior knowledge. The data revealed widespread cell type-specific correlation of expression. Integrated analysis tools allow users to use this correlation of expression for the generation of hypotheses about biological networks and candidate regulators in specific cell types. We show several applications of Immuno-Navigator as examples. In one application we successfully predicted known regulators of importance in naturally occurring Treg cells from their expression correlation with a set of Treg-specific genes. For one high-scoring gene, integrin β8 (Itgb8), we confirmed an association between Itgb8 expression in forkhead box P3 (Foxp3)-positive T cells and Treg-specific epigenetic remodeling. Our results also suggest that the regulation of Treg-specific genes within Treg cells is relatively independent of Foxp3 expression, supporting recent results pointing to a Foxp3-independent component in the development of Treg cells. PMID:27078110

Integrated network analysis identifies fight-club nodes as a class of hubs encompassing key putative switch genes that induce major transcriptome reprogramming during grapevine development.

PubMed

Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

2014-12-01

We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named "fight-club hubs" characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named "switch genes" was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. © 2014 American Society of Plant Biologists. All rights reserved.

Integration of Genome-Wide Computation DRE Search, AhR ChIP-chip and Gene Expression Analyses of TCDD-Elicited Responses in the Mouse Liver

PubMed Central

2011-01-01

Background The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor (TF) that mediates responses to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Integration of TCDD-induced genome-wide AhR enrichment, differential gene expression and computational dioxin response element (DRE) analyses further elucidate the hepatic AhR regulatory network. Results Global ChIP-chip and gene expression analyses were performed on hepatic tissue from immature ovariectomized mice orally gavaged with 30 μg/kg TCDD. ChIP-chip analysis identified 14,446 and 974 AhR enriched regions (1% false discovery rate) at 2 and 24 hrs, respectively. Enrichment density was greatest in the proximal promoter, and more specifically, within ± 1.5 kb of a transcriptional start site (TSS). AhR enrichment also occurred distal to a TSS (e.g. intergenic DNA and 3' UTR), extending the potential gene expression regulatory roles of the AhR. Although TF binding site analyses identified over-represented DRE sequences within enriched regions, approximately 50% of all AhR enriched regions lacked a DRE core (5'-GCGTG-3'). Microarray analysis identified 1,896 number of TCDD-responsive genes (|fold change| ≥ 1.5, P1(t) > 0.999). Integrating this gene expression data with our ChIP-chip and DRE analyses only identified 625 differentially expressed genes that involved an AhR interaction at a DRE. Functional annotation analysis of differentially regulated genes associated with AhR enrichment identified overrepresented processes related to fatty acid and lipid metabolism and transport, and xenobiotic metabolism, which are consistent with TCDD-elicited steatosis in the mouse liver. Conclusions Details of the AhR regulatory network have been expanded to include AhR-DNA interactions within intragenic and intergenic genomic regions. Moreover, the AhR can interact with DNA independent of a DRE core suggesting there are alternative mechanisms of AhR-mediated gene regulation. PMID:21762485

A regulatory toolbox of MiniPromoters to drive selective expression in the brain.

PubMed

Portales-Casamar, Elodie; Swanson, Douglas J; Liu, Li; de Leeuw, Charles N; Banks, Kathleen G; Ho Sui, Shannan J; Fulton, Debra L; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J; Babyak, Nazar; Black, Sonia F; Bonaguro, Russell J; Brauer, Erich; Candido, Tara R; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C Y; Chopra, Vik; Docking, T Roderick; Dreolini, Lisa; D'Souza, Cletus A; Flynn, Erin K; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y; Lim, Jonathan S; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L; Schmouth, Jean-François; Swanson, Magdalena I; Tam, Bonny; Ticoll, Amy; Turner, Jenna L; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F; Wilson, Gary; Wong, Bibiana K Y; Wong, Siaw H; Wong, Tony Y T; Yang, George S; Ypsilanti, Athena R; Jones, Steven J M; Holt, Robert A; Goldowitz, Daniel; Wasserman, Wyeth W; Simpson, Elizabeth M

2010-09-21

The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination "knockins" in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5' of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type-specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies.

Integrative ChIP-seq/Microarray Analysis Identifies a CTNNB1 Target Signature Enriched in Intestinal Stem Cells and Colon Cancer

PubMed Central

Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L.; Roberts, Brian S.; Arthur, William T.; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Background Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. Results We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Conclusion Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells. PMID:24651522

Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

PubMed

Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

Environment-dependent striatal gene expression in the BACHD rat model for Huntington disease.

PubMed

Novati, Arianna; Hentrich, Thomas; Wassouf, Zinah; Weber, Jonasz J; Yu-Taeger, Libo; Déglon, Nicole; Nguyen, Huu Phuc; Schulze-Hentrich, Julia M

2018-04-11

Huntington disease (HD) is an autosomal dominant neurodegenerative disorder caused by a mutation in the huntingtin (HTT) gene which results in progressive neurodegeneration in the striatum, cortex, and eventually most brain areas. Despite being a monogenic disorder, environmental factors influence HD characteristics. Both human and mouse studies suggest that mutant HTT (mHTT) leads to gene expression changes that harbor potential to be modulated by the environment. Yet, the underlying mechanisms integrating environmental cues into the gene regulatory program have remained largely unclear. To better understand gene-environment interactions in the context of mHTT, we employed RNA-seq to examine effects of maternal separation (MS) and environmental enrichment (EE) on striatal gene expression during development of BACHD rats. We integrated our results with striatal consensus modules defined on HTT-CAG length and age-dependent co-expression gene networks to relate the environmental factors with disease progression. While mHTT was the main determinant of expression changes, both MS and EE were capable of modulating these disturbances, resulting in distinctive and in several cases opposing effects of MS and EE on consensus modules. This bivalent response to maternal separation and environmental enrichment may aid in explaining their distinct effects observed on disease phenotypes in animal models of HD and related neurodegenerative disorders.

LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures.

PubMed

Duan, Qiaonan; Flynn, Corey; Niepel, Mario; Hafner, Marc; Muhlich, Jeremy L; Fernandez, Nicolas F; Rouillard, Andrew D; Tan, Christopher M; Chen, Edward Y; Golub, Todd R; Sorger, Peter K; Subramanian, Aravind; Ma'ayan, Avi

2014-07-01

For the Library of Integrated Network-based Cellular Signatures (LINCS) project many gene expression signatures using the L1000 technology have been produced. The L1000 technology is a cost-effective method to profile gene expression in large scale. LINCS Canvas Browser (LCB) is an interactive HTML5 web-based software application that facilitates querying, browsing and interrogating many of the currently available LINCS L1000 data. LCB implements two compacted layered canvases, one to visualize clustered L1000 expression data, and the other to display enrichment analysis results using 30 different gene set libraries. Clicking on an experimental condition highlights gene-sets enriched for the differentially expressed genes from the selected experiment. A search interface allows users to input gene lists and query them against over 100 000 conditions to find the top matching experiments. The tool integrates many resources for an unprecedented potential for new discoveries in systems biology and systems pharmacology. The LCB application is available at http://www.maayanlab.net/LINCS/LCB. Customized versions will be made part of the http://lincscloud.org and http://lincs.hms.harvard.edu websites. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integrated analyses of microRNAs demonstrate their widespread influence on gene expression in high-grade serous ovarian carcinoma.

PubMed

Creighton, Chad J; Hernandez-Herrera, Anadulce; Jacobsen, Anders; Levine, Douglas A; Mankoo, Parminder; Schultz, Nikolaus; Du, Ying; Zhang, Yiqun; Larsson, Erik; Sheridan, Robert; Xiao, Weimin; Spellman, Paul T; Getz, Gad; Wheeler, David A; Perou, Charles M; Gibbs, Richard A; Sander, Chris; Hayes, D Neil; Gunaratne, Preethi H

2012-01-01

The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets. Integration of miRNA and gene patterns yielded evidence that proximal pairs of miRNAs are processed from polycistronic primary transcripts, and that intronic miRNAs and their host gene mRNAs derive from common transcripts. Patterns of miRNA expression revealed multiple tumor subtypes and a set of 34 miRNAs predictive of overall patient survival. In a global analysis, miRNA:mRNA pairs anti-correlated in expression across tumors showed a higher frequency of in silico predicted target sites in the mRNA 3'-untranslated region (with less frequency observed for coding sequence and 5'-untranslated regions). The miR-29 family and predicted target genes were among the most strongly anti-correlated miRNA:mRNA pairs; over-expression of miR-29a in vitro repressed several anti-correlated genes (including DNMT3A and DNMT3B) and substantially decreased ovarian cancer cell viability. This study establishes miRNAs as having a widespread impact on gene expression programs in ovarian cancer, further strengthening our understanding of miRNA biology as it applies to human cancer. As with gene transcripts, miRNAs exhibit high diversity reflecting the genomic heterogeneity within a clinically homogeneous disease population. Putative miRNA:mRNA interactions, as identified using integrative analysis, can be validated. TCGA data are a valuable resource for the identification of novel tumor suppressive miRNAs in ovarian as well as other cancers.

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

Site-specific recombination in the chicken genome using Flipase recombinase-mediated cassette exchange.

PubMed

Lee, Hong Jo; Lee, Hyung Chul; Kim, Young Min; Hwang, Young Sun; Park, Young Hyun; Park, Tae Sub; Han, Jae Yong

2016-02-01

Targeted genome recombination has been applied in diverse research fields and has a wide range of possible applications. In particular, the discovery of specific loci in the genome that support robust and ubiquitous expression of integrated genes and the development of genome-editing technology have facilitated rapid advances in various scientific areas. In this study, we produced transgenic (TG) chickens that can induce recombinase-mediated gene cassette exchange (RMCE), one of the site-specific recombination technologies, and confirmed RMCE in TG chicken-derived cells. As a result, we established TG chicken lines that have, Flipase (Flp) recognition target (FRT) pairs in the chicken genome, mediated by piggyBac transposition. The transgene integration patterns were diverse in each TG chicken line, and the integration diversity resulted in diverse levels of expression of exogenous genes in each tissue of the TG chickens. In addition, the replaced gene cassette was expressed successfully and maintained by RMCE in the FRT predominant loci of TG chicken-derived cells. These results indicate that targeted genome recombination technology with RMCE could be adaptable to TG chicken models and that the technology would be applicable to specific gene regulation by cis-element insertion and customized expression of functional proteins at predicted levels without epigenetic influence. © FASEB.

Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

PubMed

Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S

2014-11-01

COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Arabidopsis thaliana gonidialess A/Zuotin related factors (GlsA/ZRF) are essential for maintenance of meristem integrity.

PubMed

Guzmán-López, José Alfredo; Abraham-Juárez, María Jazmín; Lozano-Sotomayor, Paulina; de Folter, Stefan; Simpson, June

2016-05-01

Observation of a differential expression pattern, including strong expression in meristematic tissue of an Agave tequilana GlsA/ZRF ortholog suggested an important role for this gene during bulbil formation and developmental changes in this species. In order to better understand this role, the two GlsA/ZFR orthologs present in the genome of Arabidopsis thaliana were functionally characterized by analyzing expression patterns, double mutant phenotypes, promoter-GUS fusions and expression of hormone related or meristem marker genes. Patterns of expression for A. thaliana show that GlsA/ZFR genes are strongly expressed in SAMs and RAMs in mature plants and developing embryos and double mutants showed multiple changes in morphology related to both SAM and RAM tissues. Typical double mutants showed stunted growth of aerial and root tissue, formation of multiple ectopic meristems and effects on cotyledons, leaves and flowers. The KNOX genes STM and BP were overexpressed in double mutants whereas CLV3, WUSCHEL and AS1 were repressed and lack of AtGlsA expression was also associated with changes in localization of auxin and cytokinin. These results suggest that GlsA/ZFR is an essential component of the machinery that maintains the integrity of SAM and RAM tissue and underline the potential to identify new genes or gene functions based on observations in non-model plants.

Integrated Analysis of the Effects of Cold and Dehydration on Rice Metabolites, Phytohormones, and Gene Transcripts1[W][OPEN

PubMed Central

Maruyama, Kyonoshin; Urano, Kaoru; Yoshiwara, Kyouko; Morishita, Yoshihiko; Sakurai, Nozomu; Suzuki, Hideyuki; Kojima, Mikiko; Sakakibara, Hitoshi; Shibata, Daisuke; Saito, Kazuki; Shinozaki, Kazuo; Yamaguchi-Shinozaki, Kazuko

2014-01-01

Correlations between gene expression and metabolite/phytohormone levels under abiotic stress conditions have been reported for Arabidopsis (Arabidopsis thaliana). However, little is known about these correlations in rice (Oryza sativa ‘Nipponbare’), despite its importance as a model monocot. We performed an integrated analysis to clarify the relationships among cold- and dehydration-responsive metabolites, phytohormones, and gene transcription in rice. An integrated analysis of metabolites and gene expression indicated that several genes encoding enzymes involved in starch degradation, sucrose metabolism, and the glyoxylate cycle are up-regulated in rice plants exposed to cold or dehydration and that these changes are correlated with the accumulation of glucose (Glc), fructose, and sucrose. In particular, high expression levels of genes encoding isocitrate lyase and malate synthase in the glyoxylate cycle correlate with increased Glc levels in rice, but not in Arabidopsis, under dehydration conditions, indicating that the regulation of the glyoxylate cycle may be involved in Glc accumulation under dehydration conditions in rice but not Arabidopsis. An integrated analysis of phytohormones and gene transcripts revealed an inverse relationship between abscisic acid (ABA) signaling and cytokinin (CK) signaling under cold and dehydration stresses; these stresses increase ABA signaling and decrease CK signaling. High levels of Oryza sativa 9-cis-epoxycarotenoid dioxygenase transcripts correlate with ABA accumulation, and low levels of Cytochrome P450 (CYP) 735A transcripts correlate with decreased levels of a CK precursor in rice. This reduced expression of CYP735As occurs in rice but not Arabidopsis. Therefore, transcriptional regulation of CYP735As might be involved in regulating CK levels under cold and dehydration conditions in rice but not Arabidopsis. PMID:24515831

Integrated annotation and analysis of in situ hybridization images using the ImAnno system: application to the ear and sensory organs of the fetal mouse.

PubMed

Romand, Raymond; Ripp, Raymond; Poidevin, Laetitia; Boeglin, Marcel; Geffers, Lars; Dollé, Pascal; Poch, Olivier

2015-01-01

An in situ hybridization (ISH) study was performed on 2000 murine genes representing around 10% of the protein-coding genes present in the mouse genome using data generated by the EURExpress consortium. This study was carried out in 25 tissues of late gestation embryos (E14.5), with a special emphasis on the developing ear and on five distinct developing sensory organs, including the cochlea, the vestibular receptors, the sensory retina, the olfactory organ, and the vibrissae follicles. The results obtained from an analysis of more than 11,000 micrographs have been integrated in a newly developed knowledgebase, called ImAnno. In addition to managing the multilevel micrograph annotations performed by human experts, ImAnno provides public access to various integrated databases and tools. Thus, it facilitates the analysis of complex ISH gene expression patterns, as well as functional annotation and interaction of gene sets. It also provides direct links to human pathways and diseases. Hierarchical clustering of expression patterns in the 25 tissues revealed three main branches corresponding to tissues with common functions and/or embryonic origins. To illustrate the integrative power of ImAnno, we explored the expression, function and disease traits of the sensory epithelia of the five presumptive sensory organs. The study identified 623 genes (out of 2000) concomitantly expressed in the five embryonic epithelia, among which many (∼12%) were involved in human disorders. Finally, various multilevel interaction networks were characterized, highlighting differential functional enrichments of directly or indirectly interacting genes. These analyses exemplify an under-represention of "sensory" functions in the sensory gene set suggests that E14.5 is a pivotal stage between the developmental stage and the functional phase that will be fully reached only after birth.

Snail1 transcription factor controls telomere transcription and integrity.

PubMed

Mazzolini, Rocco; Gonzàlez, Núria; Garcia-Garijo, Andrea; Millanes-Romero, Alba; Peiró, Sandra; Smith, Susan; García de Herreros, Antonio; Canudas, Sílvia

2018-01-09

Besides controlling epithelial-to-mesenchymal transition (EMT) and cell invasion, the Snail1 transcriptional factor also provides cells with cancer stem cell features. Since telomere maintenance is essential for stemness, we have examined the control of telomere integrity by Snail1. Fluorescence in situ hybridization (FISH) analysis indicates that Snail1-depleted mouse mesenchymal stem cells (MSC) have both a dramatic increase of telomere alterations and shorter telomeres. Remarkably, Snail1-deficient MSC present higher levels of both telomerase activity and the long non-coding RNA called telomeric repeat-containing RNA (TERRA), an RNA that controls telomere integrity. Accordingly, Snail1 expression downregulates expression of the telomerase gene (TERT) as well as of TERRA 2q, 11q and 18q. TERRA and TERT are transiently downregulated during TGFβ-induced EMT in NMuMG cells, correlating with Snail1 expression. Global transcriptome analysis indicates that ectopic expression of TERRA affects the transcription of some genes induced during EMT, such as fibronectin, whereas that of TERT does not modify those genes. We propose that Snail1 repression of TERRA is required not only for telomere maintenance but also for the expression of a subset of mesenchymal genes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Clustering cancer gene expression data by projective clustering ensemble

PubMed Central

Yu, Xianxue; Yu, Guoxian

2017-01-01

Gene expression data analysis has paramount implications for gene treatments, cancer diagnosis and other domains. Clustering is an important and promising tool to analyze gene expression data. Gene expression data is often characterized by a large amount of genes but with limited samples, thus various projective clustering techniques and ensemble techniques have been suggested to combat with these challenges. However, it is rather challenging to synergy these two kinds of techniques together to avoid the curse of dimensionality problem and to boost the performance of gene expression data clustering. In this paper, we employ a projective clustering ensemble (PCE) to integrate the advantages of projective clustering and ensemble clustering, and to avoid the dilemma of combining multiple projective clusterings. Our experimental results on publicly available cancer gene expression data show PCE can improve the quality of clustering gene expression data by at least 4.5% (on average) than other related techniques, including dimensionality reduction based single clustering and ensemble approaches. The empirical study demonstrates that, to further boost the performance of clustering cancer gene expression data, it is necessary and promising to synergy projective clustering with ensemble clustering. PCE can serve as an effective alternative technique for clustering gene expression data. PMID:28234920

Tolerant industrial yeast Saccharomyces cerevisiae posses a more robust cell wall integrity signaling pathway against 2-furaldehyde and 5-(hydroxymethyl)-2-furaldehyde.

PubMed

Liu, Z Lewis; Wang, Xu; Weber, Scott A

2018-06-20

Cell wall integrity signaling pathway in Saccharomyces cerevisiae is a conserved function for detecting and responding to cell stress conditions but less understood for industrial yeast. We examined gene expression dynamics for a tolerant industrial yeast strain NRRL Y-50049 in response to challenges of furfural and HMF through comparative quantitative gene expression analysis using pathway-based qRT-PCR array assays. All tested genes from Y-50049, except for MLP2, demonstrated more resistant and significantly increased gene expression than that from a laboratory strain BY4741. While all five sensor encoding genes WSC1, WSC2, WSC3, MID2 and MTL1 from both strains were activated in response to the furfural-HMF treatment, WSC3 from Y-50049 demonstrated the most increased expression over time compared with any other sensor genes. These results suggested the industrial yeast poses more robust cell wall integrity pathway, and gene WSC3 could have the special capability for signal transmission against furfural and HMF. Among five single nucleotide variations discovered in WSC3 from Y-50049, three were found to be non-synonymous mutations resulting in amino acid alterations of Ser 158  → Tyr 158 , Val 186  → Ile 186 , and Glu 430  → Asp 430 . Our results suggest the industrial yeast as a more desirable delivery vehicle for the next-generation biocatalyst development. Published by Elsevier B.V.

Public data mining plus domestic experimental study defined involvement of the old-yet-uncharacterized gene matrix-remodeling associated 7 (MXRA7) in physiopathology of the eye.

PubMed

Jia, Changkai; Zhang, Feng; Zhu, Ying; Qi, Xia; Wang, Yiqiang

2017-10-20

Matrix-remodeling associated 7 (MXRA7) gene was first reported in 2002 and named so for its co-expression with several genes known to relate with matrix-remodeling. However, not any studies had been intentionally performed to characterize this gene. We started defining the functions of MXRA7 by integrating bioinformatics analysis and experimental study. Data mining of MXRA7 expression in BioGPS, Gene Expression Omnibus and EurExpress platforms highlighted high level expression of Mxra7 in murine ocular tissues. Real-time PCR was employed to measure Mxra7 mRNA in tissues of adult C57BL/6 mice and demonstrated that Mxra7 was preferentially expressed at higher level in retina, corneas and lens than in other tissues. Then the inflammatory corneal neovascularization (CorNV) model and fungal corneal infections were induced in Balb/c mice, and mRNA levels of Mxra7 as well as several matrix-remodeling related genes (Mmp3, Mmp13, Ecm1, Timp1) were monitored with RT-PCR. The results demonstrated a time-dependent Mxra7 under-expression pattern (U-shape curve along timeline), while all other matrix-remodeling related genes manifested an opposite changes pattern (dome-shape curve). When limited data from BioGPS concerning human MXRA7 gene expression in human tissues were looked at, it was found that ocular tissue was also the one expressing highest level of MXRA7. To conclude, integrative assay of MXRA7 gene expression in public databank as well as domestic animal models revealed a selective high expression MXRA7 in murine and human ocular tissues, and its change patterns in two corneal disease models implied that MXRA7 might play a role in pathological processes or diseases involving injury, neovascularization and would healing. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-12-23

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

Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

PubMed

Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

2014-05-01

Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Combinatorial Screening for Transgenic Yeasts with High Cellulase Activities in Combination with a Tunable Expression System

PubMed Central

Ito, Yoichiro; Yamanishi, Mamoru; Ikeuchi, Akinori; Imamura, Chie; Matsuyama, Takashi

2015-01-01

Combinatorial screening used together with a broad library of gene expression cassettes is expected to produce a powerful tool for the optimization of the simultaneous expression of multiple enzymes. Recently, we proposed a highly tunable protein expression system that utilized multiple genome-integrated target genes to fine-tune enzyme expression in yeast cells. This tunable system included a library of expression cassettes each composed of three gene-expression control elements that in different combinations produced a wide range of protein expression levels. In this study, four gene expression cassettes with graded protein expression levels were applied to the expression of three cellulases: cellobiohydrolase 1, cellobiohydrolase 2, and endoglucanase 2. After combinatorial screening for transgenic yeasts simultaneously secreting these three cellulases, we obtained strains with higher cellulase expressions than a strain harboring three cellulase-expression constructs within one high-performance gene expression cassette. These results show that our method will be of broad use throughout the field of metabolic engineering. PMID:26692026

Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

PubMed

Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

2018-01-01

Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited. Therefore, this work proposes a novel methodological approach involving the integration of several heterogeneous skin cancer series, and a later multiclass classifier design. This approach is thus a way to provide the clinicians with an intelligent diagnosis support tool based on the use of a robust set of selected biomarkers, which simultaneously distinguishes among different cancer-related skin states. To achieve this, a multi-platform combination of microarray datasets from Affymetrix and Illumina manufacturers was carried out. This integration is expected to strengthen the statistical robustness of the study as well as the finding of highly-reliable skin cancer biomarkers. Specifically, the designed operation pipeline has allowed the identification of a small subset of 17 differentially expressed genes (DEGs) from which to distinguish among 7 involved skin states. These genes were obtained from the assessment of a number of potential batch effects on the gene expression data. The biological interpretation of these genes was inspected in the specific literature to understand their underlying information in relation to skin cancer. Finally, in order to assess their possible effectiveness in cancer diagnosis, a cross-validation Support Vector Machines (SVM)-based classification including feature ranking was performed. The accuracy attained exceeded the 92% in overall recognition of the 7 different cancer-related skin states. The proposed integration scheme is expected to allow the co-integration with other state-of-the-art technologies such as RNA-seq.

Plant Omics Data Center: An Integrated Web Repository for Interspecies Gene Expression Networks with NLP-Based Curation

PubMed Central

Ohyanagi, Hajime; Takano, Tomoyuki; Terashima, Shin; Kobayashi, Masaaki; Kanno, Maasa; Morimoto, Kyoko; Kanegae, Hiromi; Sasaki, Yohei; Saito, Misa; Asano, Satomi; Ozaki, Soichi; Kudo, Toru; Yokoyama, Koji; Aya, Koichiro; Suwabe, Keita; Suzuki, Go; Aoki, Koh; Kubo, Yasutaka; Watanabe, Masao; Matsuoka, Makoto; Yano, Kentaro

2015-01-01

Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources. PMID:25505034

Integrated Network Analysis Identifies Fight-Club Nodes as a Class of Hubs Encompassing Key Putative Switch Genes That Induce Major Transcriptome Reprogramming during Grapevine Development[W][OPEN

PubMed Central

Palumbo, Maria Concetta; Zenoni, Sara; Fasoli, Marianna; Massonnet, Mélanie; Farina, Lorenzo; Castiglione, Filippo; Pezzotti, Mario; Paci, Paola

2014-01-01

We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named “fight-club hubs” characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named “switch genes” was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops. PMID:25490918

Integrating Colon Cancer Microarray Data: Associating Locus-Specific Methylation Groups to Gene Expression-Based Classifications.

PubMed

Barat, Ana; Ruskin, Heather J; Byrne, Annette T; Prehn, Jochen H M

2015-11-23

Recently, considerable attention has been paid to gene expression-based classifications of colorectal cancers (CRC) and their association with patient prognosis. In addition to changes in gene expression, abnormal DNA-methylation is known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Large-scale technologies, such as methylation microarray assays and specific sequencing of methylated DNA, have been used to determine whole genome profiles of CpG island methylation in tissue samples. In this article, publicly available microarray-based gene expression and methylation data sets are used to characterize expression subtypes with respect to locus-specific methylation. A major objective was to determine whether integration of these data types improves previously characterized subtypes, or provides evidence for additional subtypes. We used unsupervised clustering techniques to determine methylation-based subgroups, which are subsequently annotated with three published expression-based classifications, comprising from three to six subtypes. Our results showed that, while methylation profiles provide a further basis for segregation of certain (Inflammatory and Goblet-like) finer-grained expression-based subtypes, they also suggest that other finer-grained subtypes are not distinctive and can be considered as a single subtype.

Integrating Colon Cancer Microarray Data: Associating Locus-Specific Methylation Groups to Gene Expression-Based Classifications

PubMed Central

Barat, Ana; Ruskin, Heather J.; Byrne, Annette T.; Prehn, Jochen H. M.

2015-01-01

Recently, considerable attention has been paid to gene expression-based classifications of colorectal cancers (CRC) and their association with patient prognosis. In addition to changes in gene expression, abnormal DNA-methylation is known to play an important role in cancer onset and development, and colon cancer is no exception to this rule. Large-scale technologies, such as methylation microarray assays and specific sequencing of methylated DNA, have been used to determine whole genome profiles of CpG island methylation in tissue samples. In this article, publicly available microarray-based gene expression and methylation data sets are used to characterize expression subtypes with respect to locus-specific methylation. A major objective was to determine whether integration of these data types improves previously characterized subtypes, or provides evidence for additional subtypes. We used unsupervised clustering techniques to determine methylation-based subgroups, which are subsequently annotated with three published expression-based classifications, comprising from three to six subtypes. Our results showed that, while methylation profiles provide a further basis for segregation of certain (Inflammatory and Goblet-like) finer-grained expression-based subtypes, they also suggest that other finer-grained subtypes are not distinctive and can be considered as a single subtype. PMID:27600244

Identification of differentially expressed genes in childhood asthma.

PubMed

Zhang, Nian-Zhen; Chen, Xiu-Juan; Mu, Yu-Hua; Wang, Hewen

2018-05-01

Asthma has been the most common chronic disease in children that places a major burden for affected people and their families.An integrated analysis of microarrays studies was performed to identify differentially expressed genes (DEGs) in childhood asthma compared with normal control. We also obtained the differentially methylated genes (DMGs) in childhood asthma according to GEO. The genes that were both differentially expressed and differentially methylated were identified. Functional annotation and protein-protein interaction network construction were performed to interpret biological functions of DEGs. We performed q-RT-PCR to verify the expression of selected DEGs.One DNA methylation and 3 gene expression datasets were obtained. Four hundred forty-one DEGs and 1209 DMGs in childhood asthma were identified. Among which, 16 genes were both differentially expressed and differentially methylated in childhood asthma. Natural killer cell mediated cytotoxicity pathway, Jak-STAT signaling pathway, and Wnt signaling pathway were 3 significantly enriched pathways in childhood asthma according to our KEGG enrichment analysis. The PPI network of top 20 up- and downregulated DEGs consisted of 822 nodes and 904 edges and 2 hub proteins (UBQLN4 and MID2) were identified. The expression of 8 DEGs (GZMB, FGFBP2, CLC, TBX21, ALOX15, IL12RB2, UBQLN4) was verified by qRT-PCR and only the expression of GZMB and FGFBP2 was inconsistent with our integrated analysis.Our finding was helpful to elucidate the underlying mechanism of childhood asthma and develop new potential diagnostic biomarker and provide clues for drug design.

PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

PubMed Central

Yue, Zongliang; Zheng, Qi; Neylon, Michael T; Yoo, Minjae; Shin, Jimin; Zhao, Zhiying; Tan, Aik Choon

2018-01-01

Abstract Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug–gene, miRNA–gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/. PMID:29126216

A regulatory sequence from the retinoid X receptor γ gene directs expression to horizontal cells and photoreceptors in the embryonic chicken retina.

PubMed

Blixt, Maria K E; Hallböök, Finn

2016-01-01

Combining techniques of episomal vector gene-specific Cre expression and genomic integration using the piggyBac transposon system enables studies of gene expression-specific cell lineage tracing in the chicken retina. In this work, we aimed to target the retinal horizontal cell progenitors. A 208 bp gene regulatory sequence from the chicken retinoid X receptor γ gene (RXRγ208) was used to drive Cre expression. RXRγ is expressed in progenitors and photoreceptors during development. The vector was combined with a piggyBac "donor" vector containing a floxed STOP sequence followed by enhanced green fluorescent protein (EGFP), as well as a piggyBac helper vector for efficient integration into the host cell genome. The vectors were introduced into the embryonic chicken retina with in ovo electroporation. Tissue electroporation targets specific developmental time points and in specific structures. Cells that drove Cre expression from the regulatory RXRγ208 sequence excised the floxed STOP-sequence and expressed GFP. The approach generated a stable lineage with robust expression of GFP in retinal cells that have activated transcription from the RXRγ208 sequence. Furthermore, GFP was expressed in cells that express horizontal or photoreceptor markers when electroporation was performed between developmental stages 22 and 28. Electroporation of a stage 12 optic cup gave multiple cell types in accordance with RXRγ gene expression in the early retina. In this study, we describe an easy, cost-effective, and time-efficient method for testing regulatory sequences in general. More specifically, our results open up the possibility for further studies of the RXRγ-gene regulatory network governing the formation of photoreceptor and horizontal cells. In addition, the method presents approaches to target the expression of effector genes, such as regulators of cell fate or cell cycle progression, to these cells and their progenitor.

A novel, broad-range, CTXΦ-derived stable integrative expression vector for functional studies.

PubMed

Das, Bhabatosh; Kumari, Reena; Pant, Archana; Sen Gupta, Sourav; Saxena, Shruti; Mehta, Ojasvi; Nair, Gopinath Balakrish

2014-12-01

CTXΦ, a filamentous vibriophage encoding cholera toxin, uses a unique strategy for its lysogeny. The single-stranded phage genome forms intramolecular base-pairing interactions between two inversely oriented XerC and XerD binding sites (XBS) and generates a functional phage attachment site, attP(+), for integration. The attP(+) structure is recognized by the host-encoded tyrosine recombinases XerC and XerD (XerCD), which enables irreversible integration of CTXΦ into the chromosome dimer resolution site (dif) of Vibrio cholerae. The dif site and the XerCD recombinases are widely conserved in bacteria. We took advantage of these conserved attributes to develop a broad-host-range integrative expression vector that could irreversibly integrate into the host chromosome using XerCD recombinases without altering the function of any known open reading frame (ORF). In this study, we engineered two different arabinose-inducible expression vectors, pBD62 and pBD66, using XBS of CTXΦ. pBD62 replicates conditionally and integrates efficiently into the dif of the bacterial chromosome by site-specific recombination using host-encoded XerCD recombinases. The expression level of the gene of interest could be controlled through the PBAD promoter by modulating the functions of the vector-encoded transcriptional factor AraC. We validated the irreversible integration of pBD62 into a wide range of pathogenic and nonpathogenic bacteria, such as V. cholerae, Vibrio fluvialis, Vibrio parahaemolyticus, Escherichia coli, Salmonella enterica, and Klebsiella pneumoniae. Gene expression from the PBAD promoter of integrated vectors was confirmed in V. cholerae using the well-studied reporter genes mCherry, eGFP, and lacZ. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Transient Expression of an LEDGF/p75 Chimera Retargets Lentivector Integration and Functionally Rescues in a Model for X-CGD

PubMed Central

Vets, Sofie; De Rijck, Jan; Brendel, Christian; Grez, Manuel; Bushman, Frederic; Debyser, Zeger; Gijsbers, Rik

2013-01-01

Retrovirus-based vectors are commonly used as delivery vehicles to correct genetic diseases because of their ability to integrate new sequences stably. However, adverse events in which vector integration activates proto-oncogenes, leading to clonal expansion and leukemogenesis hamper their application. The host cell-encoded lens epithelium-derived growth factor (LEDGF/p75) binds lentiviral integrase and targets integration to active transcription units. We demonstrated earlier that replacing the LEDGF/p75 chromatin interaction domain with an alternative DNA-binding protein could retarget integration. Here, we show that transient expression of the chimeric protein using mRNA electroporation efficiently redirects lentiviral vector (LV) integration in wild-type (WT) cells. We then employed this technology in a model for X-linked chronic granulomatous disease (X-CGD) using myelomonocytic PLB-985 gp91−/− cells. Following electroporation with mRNA encoding the LEDGF-chimera, the cells were treated with a therapeutic lentivector encoding gp91phox. Integration site analysis revealed retargeted integration away from genes and towards heterochromatin-binding protein 1β (CBX1)-binding sites, in regions enriched in marks associated with gene silencing. Nevertheless, gp91phox expression was stable for at least 6 months after electroporation and NADPH-oxidase activity was restored to normal levels as determined by superoxide production. Together, these data provide proof-of-principle that transient expression of engineered LEDGF-chimera can retarget lentivector integration and rescues the disease phenotype in a cell model, opening perspectives for safer gene therapy. PMID:23462964

Advanced Design of Dumbbell-shaped Genetic Minimal Vectors Improves Non-coding and Coding RNA Expression.

PubMed

Jiang, Xiaoou; Yu, Han; Teo, Cui Rong; Tan, Genim Siu Xian; Goh, Sok Chin; Patel, Parasvi; Chua, Yiqiang Kevin; Hameed, Nasirah Banu Sahul; Bertoletti, Antonio; Patzel, Volker

2016-09-01

Dumbbell-shaped DNA minimal vectors lacking nontherapeutic genes and bacterial sequences are considered a stable, safe alternative to viral, nonviral, and naked plasmid-based gene-transfer systems. We investigated novel molecular features of dumbbell vectors aiming to reduce vector size and to improve the expression of noncoding or coding RNA. We minimized small hairpin RNA (shRNA) or microRNA (miRNA) expressing dumbbell vectors in size down to 130 bp generating the smallest genetic expression vectors reported. This was achieved by using a minimal H1 promoter with integrated transcriptional terminator transcribing the RNA hairpin structure around the dumbbell loop. Such vectors were generated with high conversion yields using a novel protocol. Minimized shRNA-expressing dumbbells showed accelerated kinetics of delivery and transcription leading to enhanced gene silencing in human tissue culture cells. In primary human T cells, minimized miRNA-expressing dumbbells revealed higher stability and triggered stronger target gene suppression as compared with plasmids and miRNA mimics. Dumbbell-driven gene expression was enhanced up to 56- or 160-fold by implementation of an intron and the SV40 enhancer compared with control dumbbells or plasmids. Advanced dumbbell vectors may represent one option to close the gap between durable expression that is achievable with integrating viral vectors and short-term effects triggered by naked RNA.

Patterns of expression of position-dependent integrated transgenes in mouse embryo.

PubMed Central

Bonnerot, C; Grimber, G; Briand, P; Nicolas, J F

1990-01-01

The abilities to introduce foreign DNA into the genome of mice and to visualize gene expression at the single-cell level underlie a method for defining individual elements of a genetic program. We describe the use of an Escherichia coli lacZ reporter gene fused to the promoter of the gene for hypoxanthine phosphoribosyl transferase that is expressed in all tissues. Most transgenic mice (six of seven) obtained with this construct express the lacZ gene from the hypoxanthine phosphoribosyltransferase promoter. Unexpectedly, however, the expression is temporally and spatially regulated. Each transgenic line is characterized by a specific, highly reproducible pattern of lacZ expression. These results show that, for expression, the integrated construct must be complemented by elements of the genome. These elements exert dominant developmental control on the hypoxanthine phosphoribosyltransferase promoter. The expression patterns in some transgenic mice conform to a typological marker and in others to a subtle combination of typology and topography. These observations define discrete heterogeneities of cell types and of certain structures, particularly in the nervous system and in the mesoderm. This system opens opportunities for developmental studies by providing cellular, molecular, and genetic markers of cell types, cell states, and cells from developmental compartments. Finally this method illustrates that genes transduced or transposed to a different position in the genome acquire different spatiotemporal specificities, a result that has implications for evolution. Images PMID:1696727

Sox17 drives functional engraftment of endothelium converted from non-vascular cells

PubMed Central

Schachterle, William; Badwe, Chaitanya R.; Palikuqi, Brisa; Kunar, Balvir; Ginsberg, Michael; Lis, Raphael; Yokoyama, Masataka; Elemento, Olivier; Scandura, Joseph M.; Rafii, Shahin

2017-01-01

Transplanting vascular endothelial cells (ECs) to support metabolism and express regenerative paracrine factors is a strategy to treat vasculopathies and to promote tissue regeneration. However, transplantation strategies have been challenging to develop, because ECs are difficult to culture and little is known about how to direct them to stably integrate into vasculature. Here we show that only amniotic cells could convert to cells that maintain EC gene expression. Even so, these converted cells perform sub-optimally in transplantation studies. Constitutive Akt signalling increases expression of EC morphogenesis genes, including Sox17, shifts the genomic targeting of Fli1 to favour nearby Sox consensus sites and enhances the vascular function of converted cells. Enforced expression of Sox17 increases expression of morphogenesis genes and promotes integration of transplanted converted cells into injured vessels. Thus, Ets transcription factors specify non-vascular, amniotic cells to EC-like cells, whereas Sox17 expression is required to confer EC function. PMID:28091527

Stable integration and expression of heterologous genes in several lactobacilli using an integration vector constructed from the integrase and attP sequences of phage ΦAT3 isolated from Lactobacillus casei ATCC 393.

PubMed

Lin, Chao-Fen; Lo, Ta-Chun; Kuo, Yang-Cheng; Lin, Thy-Hou

2013-04-01

An integration vector capable of stably integrating and maintaining in the chromosomes of several lactobacilli over hundreds of generations has been constructed. The major integration machinery used is based on the ΦAT3 integrase (int) and attP sequences determined previously. A novel core sequence located at the 3' end of the tRNA(leu) gene is identified in Lactobacillus fermentum ATCC 14931 as the integration target by the integration vector though most of such sequences found in other lactobacilli are similar to that determined previously. Due to the lack of an appropriate attB site in Lactococcus lactis MG1363, the integration vector is found to be unable to integrate into the chromosome of the strain. However, such integration can be successfully restored by cotransforming the integration vector with a replicative one harboring both attB and erythromycin resistance sequences into the strain. Furthermore, the integration vector constructed carries a promoter region of placT from the chromosome of Lactobacillus rhamnosus TCELL-1 which is used to express green fluorescence and luminance protein genes in the lactobacilli studied.

Validation of housekeeping genes as an internal control for gene expression studies in Giardia lamblia using quantitative real-time PCR.

PubMed

Marcial-Quino, Jaime; Fierro, Francisco; De la Mora-De la Mora, Ignacio; Enríquez-Flores, Sergio; Gómez-Manzo, Saúl; Vanoye-Carlo, America; Garcia-Torres, Itzhel; Sierra-Palacios, Edgar; Reyes-Vivas, Horacio

2016-04-25

The analysis of transcript levels of specific genes is important for understanding transcriptional regulation and for the characterization of gene function. Real-time quantitative reverse transcriptase PCR (RT-qPCR) has become a powerful tool to quantify gene expression. The objective of this study was to identify reliable housekeeping genes in Giardia lamblia. Twelve genes were selected for this purpose, and their expression was analyzed in the wild type WB strain and in two strains with resistance to nitazoxanide (NTZ) and metronidazole (MTZ), respectively. RefFinder software analysis showed that the expression of the genes is different in the three strains. The integrated data from the four analyses showed that the NADH oxidase (NADH) and aldolase (ALD) genes were the most steadily expressed genes, whereas the glyceraldehyde-3-phosphate dehydrogenase gene was the most unstable. Additionally, the relative expression of seven genes were quantified in the NTZ- and MTZ-resistant strains by RT-qPCR, using the aldolase gene as the internal control, and the results showed a consistent differential pattern of expression in both strains. The housekeeping genes found in this work will facilitate the analysis of mRNA expression levels of other genes of interest in G. lamblia. Copyright © 2016 Elsevier B.V. All rights reserved.

Breast cancer: integrating the patient with her genome.

PubMed

Angrist, Misha

2005-01-01

Increasingly, gene expression data are becoming the currency of the realm in assessing disease prognosis. This has been especially evident in cancer, particularly those malignancies for which tumor samples are fairly accessible and understanding prognostic factors has clear implications for treatment decisions. Recently, Pittman et al. demonstrated substantially increased accuracy of personalized disease outcome prediction in breast cancer by integrating gene-expression profile data with traditional clinical risk factors in a set of 158 breast cancer patients.

MAGIA2: from miRNA and genes expression data integrative analysis to microRNA–transcription factor mixed regulatory circuits (2012 update)

PubMed Central

Bisognin, Andrea; Sales, Gabriele; Coppe, Alessandro; Bortoluzzi, Stefania; Romualdi, Chiara

2012-01-01

MAGIA2 (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA2 performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA2 tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target. PMID:22618880

Hepatic circadian clock oscillators and nuclear receptors integrate microbiome-derived signals

PubMed Central

Montagner, Alexandra; Korecka, Agata; Polizzi, Arnaud; Lippi, Yannick; Blum, Yuna; Canlet, Cécile; Tremblay-Franco, Marie; Gautier-Stein, Amandine; Burcelin, Rémy; Yen, Yi-Chun; Je, Hyunsoo Shawn; Maha, Al-Asmakh; Mithieux, Gilles; Arulampalam, Velmurugesan; Lagarrigue, Sandrine; Guillou, Hervé; Pettersson, Sven; Wahli, Walter

2016-01-01

The liver is a key organ of metabolic homeostasis with functions that oscillate in response to food intake. Although liver and gut microbiome crosstalk has been reported, microbiome-mediated effects on peripheral circadian clocks and their output genes are less well known. Here, we report that germ-free (GF) mice display altered daily oscillation of clock gene expression with a concomitant change in the expression of clock output regulators. Mice exposed to microbes typically exhibit characterized activities of nuclear receptors, some of which (PPARα, LXRβ) regulate specific liver gene expression networks, but these activities are profoundly changed in GF mice. These alterations in microbiome-sensitive gene expression patterns are associated with daily alterations in lipid, glucose, and xenobiotic metabolism, protein turnover, and redox balance, as revealed by hepatic metabolome analyses. Moreover, at the systemic level, daily changes in the abundance of biomarkers such as HDL cholesterol, free fatty acids, FGF21, bilirubin, and lactate depend on the microbiome. Altogether, our results indicate that the microbiome is required for integration of liver clock oscillations that tune output activators and their effectors, thereby regulating metabolic gene expression for optimal liver function. PMID:26879573

Global Characterization of Protein Altering Mutations in Prostate Cancer

DTIC Science & Technology

2011-08-01

prevalence of candidate cancer genes observed here in prostate cancer. (3) Perform integrative analyses of somatic mutation with gene expression and copy...analyses of somatic mutation with gene expression and copy number change data collected on the same samples. Body This is a “synergy” project between...However, to perform initial verification/validation studies, we have evaluated the mutation calls for several genes discovered initially by the

Recombinant cells that highly express chromosomally-integrated heterologous genes

DOEpatents

Ingram, L.O.; Ohta, Kazuyoshi; Wood, B.E.

1998-10-13

Recombinant host cells are obtained that comprise (A) a heterologous, polypeptide-encoding polynucleotide segment, stably integrated into a chromosome, which is under transcriptional control of an endogenous promoter and (B) a mutation that effects increased expression of the heterologous segment, resulting in enhanced production by the host cells of each polypeptide encoded by that segment, relative to production of each polypeptide by the host cells in the absence of the mutation. The increased expression thus achieved is retained in the absence of conditions that select for cells displaying such increased expression. When the integrated segment comprises, for example, ethanol-production genes from an efficient ethanol producer like Zymomonas mobilis, recombinant Escherichia coli and other enteric bacterial cells within the present invention are capable of converting a wide range of biomass-derived sugars efficiently to ethanol. 13 figs.

Recombinant cells that highly express chromosomally-integrated heterologous genes

DOEpatents

Ingram, Lonnie O.; Ohta, Kazuyoshi; Wood, Brent E.

1998-01-01

Recombinant host cells are obtained that comprise (A) a heterologous, polypeptide-encoding polynucleotide segment, stably integrated into a chromosome, which is under transcriptional control of an endogenous promoter and (B) a mutation that effects increased expression of the heterologous segment, resulting in enhanced production by the host cells of each polypeptide encoded by that segment, relative to production of each polypeptide by the host cells in the absence of the mutation. The increased expression thus achieved is retained in the absence of conditions that select for cells displaying such increased expression. When the integrated segment comprises, for example, ethanol-production genes from an efficient ethanol producer like Zymomonas mobilis, recombinant Escherichia coli and other enteric bacterial cells within the present invention are capable of converting a wide range of biomass-derived sugars efficiently to ethanol.

Recombinant cells that highly express chromosomally-integrated heterologous gene

DOEpatents

Ingram, Lonnie O.; Ohta, Kazuyoshi; Wood, Brent E.

2007-03-20

Recombinant host cells are obtained that comprise (A) a heterologous, polypeptide-encoding polynucleotide segment, stably integrated into a chromosome, which is under transcriptional control of an endogenous promoter and (B) a mutation that effects increased expression of the heterologous segment, resulting in enhanced production by the host cells of each polypeptide encoded by that segment, relative to production of each polypeptide by the host cells in the absence of the mutation. The increased expression thus achieved is retained in the absence of conditions that select for cells displaying such increased expression. When the integrated segment comprises, for example, ethanol-production genes from an efficient ethanol producer like Zymomonas mobilis, recombinant Escherichia coli and other enteric bacterial cells within the present invention are capable of converting a wide range of biomass-derived sugars efficiently to ethanol.

Recombinant cells that highly express chromosomally-integrated heterologous genes

DOEpatents

Ingram, Lonnie O.; Ohta, Kazuyoshi; Wood, Brent E.

2000-08-22

Recombinant host cells are obtained that comprise (A) a heterologous, polypeptide-encoding polynucleotide segment, stably integrated into a chromosome, which is under transcriptional control of an endogenous promoter and (B) a mutation that effects increased expression of the heterologous segment, resulting in enhanced production by the host cells of each polypeptide encoded by that segment, relative to production of each polypeptide by the host cells in the absence of the mutation. The increased expression thus achieved is retained in the absence of conditions that select for cells displaying such increased expression. When the integrated segment comprises, for example, ethanol-production genes from an efficient ethanol producer like Zymomonas mobilis, recombinant Escherichia coli and other enteric bacterial cells within the present invention are capable of converting a wide range of biomass-derived sugars efficiently to ethanol.

The Zebrafish Model Organism Database: new support for human disease models, mutation details, gene expression phenotypes and searching

PubMed Central

Howe, Douglas G.; Bradford, Yvonne M.; Eagle, Anne; Fashena, David; Frazer, Ken; Kalita, Patrick; Mani, Prita; Martin, Ryan; Moxon, Sierra Taylor; Paddock, Holly; Pich, Christian; Ramachandran, Sridhar; Ruzicka, Leyla; Schaper, Kevin; Shao, Xiang; Singer, Amy; Toro, Sabrina; Van Slyke, Ceri; Westerfield, Monte

2017-01-01

The Zebrafish Model Organism Database (ZFIN; http://zfin.org) is the central resource for zebrafish (Danio rerio) genetic, genomic, phenotypic and developmental data. ZFIN curators provide expert manual curation and integration of comprehensive data involving zebrafish genes, mutants, transgenic constructs and lines, phenotypes, genotypes, gene expressions, morpholinos, TALENs, CRISPRs, antibodies, anatomical structures, models of human disease and publications. We integrate curated, directly submitted, and collaboratively generated data, making these available to zebrafish research community. Among the vertebrate model organisms, zebrafish are superbly suited for rapid generation of sequence-targeted mutant lines, characterization of phenotypes including gene expression patterns, and generation of human disease models. The recent rapid adoption of zebrafish as human disease models is making management of these data particularly important to both the research and clinical communities. Here, we describe recent enhancements to ZFIN including use of the zebrafish experimental conditions ontology, ‘Fish’ records in the ZFIN database, support for gene expression phenotypes, models of human disease, mutation details at the DNA, RNA and protein levels, and updates to the ZFIN single box search. PMID:27899582

Hypoxia-induced HIF1α targets in melanocytes reveal a molecular profile associated with poor melanoma prognosis

PubMed Central

Loftus, Stacie K.; Baxter, Laura L.; Cronin, Julia C.; Fufa, Temesgen D.; Pavan, William J.

2017-01-01

Summary Hypoxia and HIF1α signaling direct tissue-specific gene responses regulating tumor progression, invasion and metastasis. By integrating HIF1α knockdown and hypoxia-induced gene expression changes, this study identifies a melanocyte-specific, HIF1α-dependent/hypoxia-responsive gene expression signature. Integration of these gene expression changes with HIF1α ChIP-Seq analysis identifies 81 HIF1α direct target genes in melanocytes. The expression levels for ten of the HIF1α direct targets – GAPDH, PKM, PPAT, DARS, DTWD1, SEH1L, ZNF292, RLF, AGTRAP, and GPC6 – are significantly correlated with reduced time of Disease Free Status (DFS) in melanoma by logistic regression (P-value =0.0013) and ROC curve analysis (AUC= 0.826, P-value<0.0001). This HIF1α-regulated profile defines a melanocyte-specific response under hypoxia, and demonstrates the role of HIF1α as an invasive cell state gatekeeper in regulating cellular metabolism, chromatin and transcriptional regulation, vascularization and invasion. PMID:28168807

Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

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

Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark

Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchersmore » the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.« less

Applications of lentiviral vectors in molecular imaging.

PubMed

Chatterjee, Sushmita; De, Abhijit

2014-06-01

Molecular imaging provides the ability of simultaneous visual and quantitative estimation of long term gene expression directly from living organisms. To reveal the kinetics of gene expression by imaging method, often sustained expression of the transgene is required. Lentiviral vectors have been extensively used over last fifteen years for delivery of a transgene in a wide variety of cell types. Lentiviral vectors have the well known advantages such as sustained transgene delivery through stable integration into the host genome, the capability of infecting non-dividing and dividing cells, broad tissue tropism, a reasonably large carrying capacity for delivering therapeutic and reporter gene combinations. Additionally, they do not express viral proteins during transduction, have a potentially safe integration site profile, and a relatively easy system for vector manipulation and infective viral particle production. As a result, lentiviral vector mediated therapeutic and imaging reporter gene delivery to various target organs holds promise for the future treatment. In this review, we have conducted a brief survey of important lentiviral vector developments in diverse biomedical fields including reproductive biology.

SpidermiR: An R/Bioconductor Package for Integrative Analysis with miRNA Data.

PubMed

Cava, Claudia; Colaprico, Antonio; Bertoli, Gloria; Graudenzi, Alex; Silva, Tiago C; Olsen, Catharina; Noushmehr, Houtan; Bontempi, Gianluca; Mauri, Giancarlo; Castiglioni, Isabella

2017-01-27

Gene Regulatory Networks (GRNs) control many biological systems, but how such network coordination is shaped is still unknown. GRNs can be subdivided into basic connections that describe how the network members interact e.g., co-expression, physical interaction, co-localization, genetic influence, pathways, and shared protein domains. The important regulatory mechanisms of these networks involve miRNAs. We developed an R/Bioconductor package, namely SpidermiR, which offers an easy access to both GRNs and miRNAs to the end user, and integrates this information with differentially expressed genes obtained from The Cancer Genome Atlas. Specifically, SpidermiR allows the users to: (i) query and download GRNs and miRNAs from validated and predicted repositories; (ii) integrate miRNAs with GRNs in order to obtain miRNA-gene-gene and miRNA-protein-protein interactions, and to analyze miRNA GRNs in order to identify miRNA-gene communities; and (iii) graphically visualize the results of the analyses. These analyses can be performed through a single interface and without the need for any downloads. The full data sets are then rapidly integrated and processed locally.

Promoter sequence of 3-phosphoglycerate kinase gene 1 of lactic acid-producing fungus rhizopus oryzae and a method of expressing a gene of interest in fungal species

DOEpatents

Gao, Johnway [Richland, WA; Skeen, Rodney S [Pendleton, OR

2002-10-15

The present invention provides the promoter clone discovery of phosphoglycerate kinase gene 1 of a lactic acid-producing filamentous fungal strain, Rhizopus oryzae. The isolated promoter can constitutively regulate gene expression under various carbohydrate conditions. In addition, the present invention also provides a design of an integration vector for the transformation of a foreign gene in Rhizopus oryzae.

Promoter sequence of 3-phosphoglycerate kinase gene 2 of lactic acid-producing fungus rhizopus oryzae and a method of expressing a gene of interest in fungal species

DOEpatents

Gao, Johnway [Richland, WA; Skeen, Rodney S [Pendleton, OR

2003-03-04

The present invention provides the promoter clone discovery of phosphoglycerate kinase gene 2 of a lactic acid-producing filamentous fungal strain, Rhizopus oryzae. The isolated promoter can constitutively regulate gene expression under various carbohydrate conditions. In addition, the present invention also provides a design of an integration vector for the transformation of a foreign gene in Rhizopus oryzae.

Integrating gene and protein expression data with genome-scale metabolic networks to infer functional pathways.

PubMed

Pey, Jon; Valgepea, Kaspar; Rubio, Angel; Beasley, John E; Planes, Francisco J

2013-12-08

The study of cellular metabolism in the context of high-throughput -omics data has allowed us to decipher novel mechanisms of importance in biotechnology and health. To continue with this progress, it is essential to efficiently integrate experimental data into metabolic modeling. We present here an in-silico framework to infer relevant metabolic pathways for a particular phenotype under study based on its gene/protein expression data. This framework is based on the Carbon Flux Path (CFP) approach, a mixed-integer linear program that expands classical path finding techniques by considering additional biophysical constraints. In particular, the objective function of the CFP approach is amended to account for gene/protein expression data and influence obtained paths. This approach is termed integrative Carbon Flux Path (iCFP). We show that gene/protein expression data also influences the stoichiometric balancing of CFPs, which provides a more accurate picture of active metabolic pathways. This is illustrated in both a theoretical and real scenario. Finally, we apply this approach to find novel pathways relevant in the regulation of acetate overflow metabolism in Escherichia coli. As a result, several targets which could be relevant for better understanding of the phenomenon leading to impaired acetate overflow are proposed. A novel mathematical framework that determines functional pathways based on gene/protein expression data is presented and validated. We show that our approach is able to provide new insights into complex biological scenarios such as acetate overflow in Escherichia coli.

New methods for tightly regulated gene expression and highly efficient chromosomal integration of cloned genes for Methanosarcina species

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

Guss, Adam M.; Rother, Michael; Zhang, Jun Kai

A highly efficient method for chromosomal integration of cloned DNA into Methanosarcina spp. was developed utilizing the site-specific recombination system from the Streptomyces phage φC31. Host strains expressing the φC31 integrase gene and carrying an appropriate recombination site can be transformed with non-replicating plasmids carrying the complementary recombination site at efficiencies similar to those obtained with self-replicating vectors. We have also constructed a series of hybrid promoters that combine the highly expressed M. barkeri P mcrB promoter with binding sites for the tetracycline-responsive, bacterial TetR protein. These promoters are tightly regulated by the presence or absence of tetracycline in strainsmore » that express the tetR gene. The hybrid promoters can be used in genetic experiments to test gene essentiality by placing a gene of interest under their control. Thus, growth of strains with tetR -regulated essential genes becomes tetracycline-dependent. A series of plasmid vectors that utilize the site-specific recombination system for construction of reporter gene fusions and for tetracycline regulated expression of cloned genes are reported. These vectors were used to test the efficiency of translation at a variety of start codons. Fusions using an ATG start site were the most active, whereas those using GTG and TTG were approximately one half or one fourth as active, respectively. The CTG fusion was 95% less active than the ATG fusion.« less

New methods for tightly regulated gene expression and highly efficient chromosomal integration of cloned genes for Methanosarcina species

DOE PAGES

Guss, Adam M.; Rother, Michael; Zhang, Jun Kai; ...

2008-01-01

A highly efficient method for chromosomal integration of cloned DNA into Methanosarcina spp. was developed utilizing the site-specific recombination system from the Streptomyces phage φC31. Host strains expressing the φC31 integrase gene and carrying an appropriate recombination site can be transformed with non-replicating plasmids carrying the complementary recombination site at efficiencies similar to those obtained with self-replicating vectors. We have also constructed a series of hybrid promoters that combine the highly expressed M. barkeri P mcrB promoter with binding sites for the tetracycline-responsive, bacterial TetR protein. These promoters are tightly regulated by the presence or absence of tetracycline in strainsmore » that express the tetR gene. The hybrid promoters can be used in genetic experiments to test gene essentiality by placing a gene of interest under their control. Thus, growth of strains with tetR -regulated essential genes becomes tetracycline-dependent. A series of plasmid vectors that utilize the site-specific recombination system for construction of reporter gene fusions and for tetracycline regulated expression of cloned genes are reported. These vectors were used to test the efficiency of translation at a variety of start codons. Fusions using an ATG start site were the most active, whereas those using GTG and TTG were approximately one half or one fourth as active, respectively. The CTG fusion was 95% less active than the ATG fusion.« less

Detection of changes in gene regulatory patterns, elicited by perturbations of the Hsp90 molecular chaperone complex, by visualizing multiple experiments with an animation

PubMed Central

2011-01-01

Background To make sense out of gene expression profiles, such analyses must be pushed beyond the mere listing of affected genes. For example, if a group of genes persistently display similar changes in expression levels under particular experimental conditions, and the proteins encoded by these genes interact and function in the same cellular compartments, this could be taken as very strong indicators for co-regulated protein complexes. One of the key requirements is having appropriate tools to detect such regulatory patterns. Results We have analyzed the global adaptations in gene expression patterns in the budding yeast when the Hsp90 molecular chaperone complex is perturbed either pharmacologically or genetically. We integrated these results with publicly accessible expression, protein-protein interaction and intracellular localization data. But most importantly, all experimental conditions were simultaneously and dynamically visualized with an animation. This critically facilitated the detection of patterns of gene expression changes that suggested underlying regulatory networks that a standard analysis by pairwise comparison and clustering could not have revealed. Conclusions The results of the animation-assisted detection of changes in gene regulatory patterns make predictions about the potential roles of Hsp90 and its co-chaperone p23 in regulating whole sets of genes. The simultaneous dynamic visualization of microarray experiments, represented in networks built by integrating one's own experimental with publicly accessible data, represents a powerful discovery tool that allows the generation of new interpretations and hypotheses. PMID:21672238

Disclosing the Parameters Leading to High Productivity of Retroviral Producer Cells Lines: Evaluating Random Versus Targeted Integration.

PubMed

Bandeira, Vanessa S; Tomás, Hélio A; Alici, Evren; Carrondo, Manuel J T; Coroadinha, Ana S

2017-04-01

Gammaretrovirus and lentivirus are the preferred viral vectors to genetically modify T and natural killer cells to be used in immune cell therapies. The transduction efficiency of hematopoietic and T cells is more efficient using gibbon ape leukemia virus (GaLV) pseudotyping. In this context gammaretroviral vector producer cells offer competitive higher titers than transient lentiviral vectors productions. The main aim of this work was to identify the key parameters governing GaLV-pseudotyped gammaretroviral vector productivity in stable producer cells, using a retroviral vector expression cassette enabling positive (facilitating cell enrichment) and negative cell selection (allowing cell elimination). The retroviral vector contains a thymidine kinase suicide gene fused with a ouabain-resistant Na + ,K + -ATPase gene, a potential safer and faster marker. The establishment of retroviral vector producer cells is traditionally performed by randomly integrating the retroviral vector expression cassette codifying the transgene. More recently, recombinase-mediated cassette exchange methodologies have been introduced to achieve targeted integration. Herein we compared random and targeted integration of the retroviral vector transgene construct. Two retroviral producer cell lines, 293 OuaS and 293 FlexOuaS, were generated by random and targeted integration, respectively, producing high titers (on the order of 10 7 infectious particles·ml -1 ). Results showed that the retroviral vector transgene cassette is the key retroviral vector component determining the viral titers notwithstanding, single-copy integration is sufficient to provide high titers. The expression levels of the three retroviral constructs (gag-pol, GaLV env, and retroviral vector transgene) were analyzed. Although gag-pol and GaLV env gene expression levels should surpass a minimal threshold, we found that relatively modest expression levels of these two expression cassettes are required. Their levels of expression should not be maximized. We concluded, to establish a high producer retroviral vector cell line only the expression level of the genomic retroviral RNA, that is, the retroviral vector transgene cassette, should be maximized, both through (1) the optimization of its design (i.e., genetic elements composition) and (2) the selection of high expressing chromosomal locus for its integration. The use of methodologies identifying and promoting integration into high-expression loci, as targeted integration or high-throughput screening are in this perspective highly valuable.

Integrated systems analysis reveals a molecular network underlying autism spectrum disorders

PubMed Central

Li, Jingjing; Shi, Minyi; Ma, Zhihai; Zhao, Shuchun; Euskirchen, Ghia; Ziskin, Jennifer; Urban, Alexander; Hallmayer, Joachim; Snyder, Michael

2014-01-01

Autism is a complex disease whose etiology remains elusive. We integrated previously and newly generated data and developed a systems framework involving the interactome, gene expression and genome sequencing to identify a protein interaction module with members strongly enriched for autism candidate genes. Sequencing of 25 patients confirmed the involvement of this module in autism, which was subsequently validated using an independent cohort of over 500 patients. Expression of this module was dichotomized with a ubiquitously expressed subcomponent and another subcomponent preferentially expressed in the corpus callosum, which was significantly affected by our identified mutations in the network center. RNA-sequencing of the corpus callosum from patients with autism exhibited extensive gene mis-expression in this module, and our immunochemical analysis showed that the human corpus callosum is predominantly populated by oligodendrocyte cells. Analysis of functional genomic data further revealed a significant involvement of this module in the development of oligodendrocyte cells in mouse brain. Our analysis delineates a natural network involved in autism, helps uncover novel candidate genes for this disease and improves our understanding of its molecular pathology. PMID:25549968

Differentiating disease subtypes by using pathway patterns constructed from gene expressions and protein networks.

PubMed

Hung, Fei-Hung; Chiu, Hung-Wen

2015-01-01

Gene expression profiles differ in different diseases. Even if diseases are at the same stage, such diseases exhibit different gene expressions, not to mention the different subtypes at a single lesion site. Distinguishing different disease subtypes at a single lesion site is difficult. In early cases, subtypes were initially distinguished by doctors. Subsequently, further differences were found through pathological experiments. For example, a brain tumor can be classified according to its origin, its cell-type origin, or the tumor site. Because of the advancements in bioinformatics and the techniques for accumulating gene expressions, researchers can use gene expression data to classify disease subtypes. Because the operation of a biopathway is closely related to the disease mechanism, the application of gene expression profiles for clustering disease subtypes is insufficient. In this study, we collected gene expression data of healthy and four myelodysplastic syndrome subtypes and applied a method that integrated protein-protein interaction and gene expression data to identify different patterns of disease subtypes. We hope it is efficient for the classification of disease subtypes in adventure.

Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce.

PubMed

Lamara, Mebarek; Raherison, Elie; Lenz, Patrick; Beaulieu, Jean; Bousquet, Jean; MacKay, John

2016-04-01

Association studies are widely utilized to analyze complex traits but their ability to disclose genetic architectures is often limited by statistical constraints, and functional insights are usually minimal in nonmodel organisms like forest trees. We developed an approach to integrate association mapping results with co-expression networks. We tested single nucleotide polymorphisms (SNPs) in 2652 candidate genes for statistical associations with wood density, stiffness, microfibril angle and ring width in a population of 1694 white spruce trees (Picea glauca). Associations mapping identified 229-292 genes per wood trait using a statistical significance level of P < 0.05 to maximize discovery. Over-representation of genes associated for nearly all traits was found in a xylem preferential co-expression group developed in independent experiments. A xylem co-expression network was reconstructed with 180 wood associated genes and several known MYB and NAC regulators were identified as network hubs. The network revealed a link between the gene PgNAC8, wood stiffness and microfibril angle, as well as considerable within-season variation for both genetic control of wood traits and gene expression. Trait associations were distributed throughout the network suggesting complex interactions and pleiotropic effects. Our findings indicate that integration of association mapping and co-expression networks enhances our understanding of complex wood traits. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Combined lineage mapping and gene expression profiling of embryonic brain patterning using ultrashort pulse microscopy and image registration

NASA Astrophysics Data System (ADS)

Gibbs, Holly C.; Dodson, Colin R.; Bai, Yuqiang; Lekven, Arne C.; Yeh, Alvin T.

2014-12-01

During embryogenesis, presumptive brain compartments are patterned by dynamic networks of gene expression. The spatiotemporal dynamics of these networks, however, have not been characterized with sufficient resolution for us to understand the regulatory logic resulting in morphogenetic cellular behaviors that give the brain its shape. We have developed a new, integrated approach using ultrashort pulse microscopy [a high-resolution, two-photon fluorescence (2PF)-optical coherence microscopy (OCM) platform using 10-fs pulses] and image registration to study brain patterning and morphogenesis in zebrafish embryos. As a demonstration, we used time-lapse 2PF to capture midbrain-hindbrain boundary morphogenesis and a wnt1 lineage map from embryos during brain segmentation. We then performed in situ hybridization to deposit NBT/BCIP, where wnt1 remained actively expressed, and reimaged the embryos with combined 2PF-OCM. When we merged these datasets using morphological landmark registration, we found that the mechanism of boundary formation differs along the dorsoventral axis. Dorsally, boundary sharpening is dominated by changes in gene expression, while ventrally, sharpening may be accomplished by lineage sorting. We conclude that the integrated visualization of lineage reporter and gene expression domains simultaneously with brain morphology will be useful for understanding how changes in gene expression give rise to proper brain compartmentalization and structure.

Combined lineage mapping and gene expression profiling of embryonic brain patterning using ultrashort pulse microscopy and image registration.

PubMed

Gibbs, Holly C; Dodson, Colin R; Bai, Yuqiang; Lekven, Arne C; Yeh, Alvin T

2014-12-01

During embryogenesis, presumptive brain compartments are patterned by dynamic networks of gene expression. The spatiotemporal dynamics of these networks, however, have not been characterized with sufficient resolution for us to understand the regulatory logic resulting in morphogenetic cellular behaviors that give the brain its shape. We have developed a new, integrated approach using ultrashort pulse microscopy [a high-resolution, two-photon fluorescence (2PF)-optical coherence microscopy (OCM) platform using 10-fs pulses] and image registration to study brain patterning and morphogenesis in zebrafish embryos. As a demonstration, we used time-lapse 2PF to capture midbrain-hindbrain boundary morphogenesis and a wnt1 lineage map from embryos during brain segmentation. We then performed in situ hybridization to deposit NBT/BCIP, where wnt1 remained actively expressed, and reimaged the embryos with combined 2PF-OCM. When we merged these datasets using morphological landmark registration, we found that the mechanism of boundary formation differs along the dorsoventral axis. Dorsally, boundary sharpening is dominated by changes in gene expression, while ventrally, sharpening may be accomplished by lineage sorting. We conclude that the integrated visualization of lineage reporter and gene expression domains simultaneously with brain morphology will be useful for understanding how changes in gene expression give rise to proper brain compartmentalization and structure.

An Integrated Cell Purification and Genomics Strategy Reveals Multiple Regulators of Pancreas Development

PubMed Central

Benitez, Cecil M.; Qu, Kun; Sugiyama, Takuya; Pauerstein, Philip T.; Liu, Yinghua; Tsai, Jennifer; Gu, Xueying; Ghodasara, Amar; Arda, H. Efsun; Zhang, Jiajing; Dekker, Joseph D.; Tucker, Haley O.; Chang, Howard Y.; Kim, Seung K.

2014-01-01

The regulatory logic underlying global transcriptional programs controlling development of visceral organs like the pancreas remains undiscovered. Here, we profiled gene expression in 12 purified populations of fetal and adult pancreatic epithelial cells representing crucial progenitor cell subsets, and their endocrine or exocrine progeny. Using probabilistic models to decode the general programs organizing gene expression, we identified co-expressed gene sets in cell subsets that revealed patterns and processes governing progenitor cell development, lineage specification, and endocrine cell maturation. Purification of Neurog3 mutant cells and module network analysis linked established regulators such as Neurog3 to unrecognized gene targets and roles in pancreas development. Iterative module network analysis nominated and prioritized transcriptional regulators, including diabetes risk genes. Functional validation of a subset of candidate regulators with corresponding mutant mice revealed that the transcription factors Etv1, Prdm16, Runx1t1 and Bcl11a are essential for pancreas development. Our integrated approach provides a unique framework for identifying regulatory genes and functional gene sets underlying pancreas development and associated diseases such as diabetes mellitus. PMID:25330008

Vector modifications to eliminate transposase expression following piggyBac-mediated transgenesis

PubMed Central

Chakraborty, Syandan; Ji, HaYeun; Chen, Jack; Gersbach, Charles A.; Leong, Kam W.

2014-01-01

Transgene insertion plays an important role in gene therapy and in biological studies. Transposon-based systems that integrate transgenes by transposase-catalyzed “cut-and-paste” mechanism have emerged as an attractive system for transgenesis. Hyperactive piggyBac transposon is particularly promising due to its ability to integrate large transgenes with high efficiency. However, prolonged expression of transposase can become a potential source of genotoxic effects due to uncontrolled transposition of the integrated transgene from one chromosomal locus to another. In this study we propose a vector design to decrease post-transposition expression of transposase and to eliminate the cells that have residual transposase expression. We design a single plasmid construct that combines the transposase and the transpositioning transgene element to share a single polyA sequence for termination. Consequently, the separation of the transposase element from the polyA sequence after transposition leads to its deactivation. We also co-express Herpes Simplex Virus thymidine kinase (HSV-tk) with the transposase. Therefore, cells having residual transposase expression can be eliminated by the administration of ganciclovir. We demonstrate the utility of this combination transposon system by integrating and expressing a model therapeutic gene, human coagulation Factor IX, in HEK293T cells. PMID:25492703

EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles.

PubMed

Dittmar, W James; McIver, Lauren; Michalak, Pawel; Garner, Harold R; Valdez, Gregorio

2014-07-01

The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes. This server is easy to use and freely available at http://pilot-hmm.vbi.vt.edu/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integrated analysis of HPV-mediated immune alterations in cervical cancer.

PubMed

Chen, Long; Luan, Shaohong; Xia, Baoguo; Liu, Yansheng; Gao, Yuan; Yu, Hongyan; Mu, Qingling; Zhang, Ping; Zhang, Weina; Zhang, Shengmiao; Wei, Guopeng; Yang, Min; Li, Ke

2018-05-01

Human papillomavirus (HPV) infection is the primary cause of cervical cancer. HPV-mediated immune alterations are known to play crucial roles in determining viral persistence and host cell transformation. We sought to thoroughly understand HPV-directed immune alterations in cervical cancer by exploring publically available datasets. 130 HPV positive and 7 HPV negative cervical cancer cases from The Cancer Genome Atlas were compared for differences in gene expression levels and functional enrichment. Analyses for copy number variation (CNV) and genetic mutation were conducted for differentially expressed immune genes. Kaplan-Meier analysis was performed to assess survival and relapse differences across cases with or without alterations of the identified immune signature genes. Genes up-regulated in HPV positive cervical cancer were enriched for various gene ontology terms of immune processes (P=1.05E-14~1.00E-05). Integrated analysis of the differentially expressed immune genes identified 9 genes that displayed either CNV, genetic mutation and/or gene expression changes in at least 10% of the cases of HPV positive cervical cancer. Genomic amplification may cause elevated levels of these genes in some HPV positive cases. Finally, patients with alterations in at least one of the nine signature genes overall had earlier relapse compared to those without any alterations. The altered expression of either TFRC or MMP13 may indicate poor survival for a subset of cervical cancer patients (P=1.07E-07). We identified a novel immune gene signature for HPV positive cervical cancer that is potentially associated with early relapse of cervical cancer. Copyright © 2018. Published by Elsevier Inc.

An Integrated Analysis of MicroRNA and mRNA Expression Profiles to Identify RNA Expression Signatures in Lambskin Hair Follicles in Hu Sheep

PubMed Central

Lv, Xiaoyang; Sun, Wei; Yin, Jinfeng; Ni, Rong; Su, Rui; Wang, Qingzeng; Gao, Wen; Bao, Jianjun; Yu, Jiarui; Wang, Lihong; Chen, Ling

2016-01-01

Wave patterns in lambskin hair follicles are an important factor determining the quality of sheep’s wool. Hair follicles in lambskin from Hu sheep, a breed unique to China, have 3 types of waves, designated as large, medium, and small. The quality of wool from small wave follicles is excellent, while the quality of large waves is considered poor. Because no molecular and biological studies on hair follicles of these sheep have been conducted to date, the molecular mechanisms underlying the formation of different wave patterns is currently unknown. The aim of this article was to screen the candidate microRNAs (miRNA) and genes for the development of hair follicles in Hu sheep. Two-day-old Hu lambs were selected from full-sib individuals that showed large, medium, and small waves. Integrated analysis of microRNA and mRNA expression profiles employed high-throughout sequencing technology. Approximately 13, 24, and 18 differentially expressed miRNAs were found between small and large waves, small and medium waves, and medium and large waves, respectively. A total of 54, 190, and 81 differentially expressed genes were found between small and large waves, small and medium waves, and medium and large waves, respectively, by RNA sequencing (RNA-seq) analysis. Differentially expressed genes were classified using gene ontology and pathway analyses. They were found to be mainly involved in cell differentiation, proliferation, apoptosis, growth, immune response, and ion transport, and were associated with MAPK and the Notch signaling pathway. Reverse transcription-polymerase chain reaction (RT-PCR) analyses of differentially-expressed miRNA and genes were consistent with sequencing results. Integrated analysis of miRNA and mRNA expression indicated that, compared to small waves, large waves included 4 downregulated miRNAs that had regulatory effects on 8 upregulated genes and 3 upregulated miRNAs, which in turn influenced 13 downregulated genes. Compared to small waves, medium waves included 13 downregulated miRNAs that had regulatory effects on 64 upregulated genes and 4 upregulated miRNAs, which in turn had regulatory effects on 22 downregulated genes. Compared to medium waves, large waves consisted of 13 upregulated miRNAs that had regulatory effects on 48 downregulated genes. These differentially expressed miRNAs and genes may play a significant role in forming different patterns, and provide evidence for the molecular mechanisms underlying the formation of hair follicles of varying patterns. PMID:27404636

UniVIO: A Multiple Omics Database with Hormonome and Transcriptome Data from Rice

PubMed Central

Sakurai, Tetsuya; Sakakibara, Hitoshi

2013-01-01

Plant hormones play important roles as signaling molecules in the regulation of growth and development by controlling the expression of downstream genes. Since the hormone signaling system represents a complex network involving functional cross-talk through the mutual regulation of signaling and metabolism, a comprehensive and integrative analysis of plant hormone concentrations and gene expression is important for a deeper understanding of hormone actions. We have developed a database named Uniformed Viewer for Integrated Omics (UniVIO: http://univio.psc.riken.jp/), which displays hormone-metabolome (hormonome) and transcriptome data in a single formatted (uniformed) heat map. At the present time, hormonome and transcriptome data obtained from 14 organ parts of rice plants at the reproductive stage and seedling shoots of three gibberellin signaling mutants are included in the database. The hormone concentration and gene expression data can be searched by substance name, probe ID, gene locus ID or gene description. A correlation search function has been implemented to enable users to obtain information of correlated substance accumulation and gene expression. In the correlation search, calculation method, range of correlation coefficient and plant samples can be selected freely. PMID:23314752

RELATIVE EXPRESSION AND STABILITY OF A CHROMOSOMALLY INTEGRATED AND PLASMID-BORNE MARKER GENE FUSION IN ENVIRONMENTALLY COMPETENT BACTERIA

EPA Science Inventory

A xyIE-iceC transcriptional fusion was created by ligating a DNA fragment harboring the cloned xyIE structural gene from the TOL plasmid of Pseudomonas putida mt-2 into the cloned iceC gene of Pseudomonas syringae Cit7. This fusion construct was integrated into chromosome of Pseu...

Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes

PubMed Central

Gong, Bin-Sheng; Zhang, Qing-Pu; Zhang, Guang-Mei; Zhang, Shao-Jun; Zhang, Wei; Lv, Hong-Chao; Zhang, Fan; Lv, Sa-Li; Li, Chuan-Xing; Rao, Shao-Qi; Li, Xia

2007-01-01

Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by some genetical genomics approaches. In this study, gene expression profiles were used as expression traits. And relationships among the genes, which were co-linked to a common SNP(s), were identified by integrating the two types of information. Further research on the co-expressions among the co-linked genes was carried out after the gene-SNP relationships were established using the Haseman-Elston sib-pair regression. The results showed that the co-expressions among the co-linked genes were significantly higher if the number of connections between the genes and a SNP(s) was more than six. Then, the genes were interconnected via one or more SNP co-linkers to construct a gene-SNP intermixed network. The genes sharing more SNPs tended to have a stronger correlation. Finally, a gene-gene network was constructed with their intensities of relationships (the number of SNP co-linkers shared) as the weights for the edges. PMID:18466544

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles.

PubMed

Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui

2014-01-01

Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection.

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles

PubMed Central

Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui

2014-01-01

Objectives: Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. Methods: MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. Results: A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. Conclusions: We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection. PMID:25664019

Developing molecular tools for Chlamydomonas reinhardtii

NASA Astrophysics Data System (ADS)

Noor-Mohammadi, Samaneh

Microalgae have garnered increasing interest over the years for their ability to produce compounds ranging from biofuels to neutraceuticals. A main focus of researchers has been to use microalgae as a natural bioreactor for the production of valuable and complex compounds. Recombinant protein expression in the chloroplasts of green algae has recently become more routine; however, the heterologous expression of multiple proteins or complete biosynthetic pathways remains a significant challenge. To take full advantage of these organisms' natural abilities, sophisticated molecular tools are needed to be able to introduce and functionally express multiple gene biosynthetic pathways in its genome. To achieve the above objective, we have sought to establish a method to construct, integrate and express multigene operons in the chloroplast and nuclear genome of the model microalgae Chlamydomonas reinhardtii. Here we show that a modified DNA Assembler approach can be used to rapidly assemble multiple-gene biosynthetic pathways in yeast and then integrate these assembled pathways at a site-specific location in the chloroplast, or by random integration in the nuclear genome of C. reinhardtii. As a proof of concept, this method was used to successfully integrate and functionally express up to three reporter proteins (AphA6, AadA, and GFP) in the chloroplast of C. reinhardtii and up to three reporter proteins (Ble, AphVIII, and GFP) in its nuclear genome. An analysis of the relative gene expression of the engineered strains showed significant differences in the mRNA expression levels of the reporter genes and thus highlights the importance of proper promoter/untranslated-region selection when constructing a target pathway. In addition, this work focuses on expressing the cofactor regeneration enzyme phosphite dehydrogenase (PTDH) in the chloroplast and nuclear genomes of C. reinhardtii. The PTDH enzyme converts phosphite into phosphate and NAD(P)+ into NAD(P)H. The reduced nicotinamide cofactor NAD(P)H plays a pivotal role in many biochemical oxidation and reduction reactions, thus this enzyme would allow regeneration of NAD(P)H in a microalgae strain over-expressing a NAD(P)H-dependent oxidoreductase. A phosphite dehydrogenase gene was introduced into the chloroplast genome (codon optimized) and nuclear genome of C. reinhardtii by biolistic transformation and electroporation in separate events, respectively. Successful expression of the heterologous protein was confirmed by transcript analysis and protein analysis. In conclusion, this new method represents a useful genetic tool in the construction and integration of complex biochemical pathways into the chloroplast or nuclear genome of microalgae, and this should aid current efforts to engineer algae for recombinant protein expression, biofuels production and production of other desirable natural products.

A Novel mRNA Level Subtraction Method for Quick Identification of Target-Orientated Uniquely Expressed Genes Between Peanut Immature Pod and Leaf

PubMed Central

2010-01-01

Subtraction technique has been broadly applied for target gene discovery. However, most current protocols apply relative differential subtraction and result in great amount clone mixtures of unique and differentially expressed genes. This makes it more difficult to identify unique or target-orientated expressed genes. In this study, we developed a novel method for subtraction at mRNA level by integrating magnetic particle technology into driver preparation and tester–driver hybridization to facilitate uniquely expressed gene discovery between peanut immature pod and leaf through a single round subtraction. The resulting target clones were further validated through polymerase chain reaction screening using peanut immature pod and leaf cDNA libraries as templates. This study has resulted in identifying several genes expressed uniquely in immature peanut pod. These target genes can be used for future peanut functional genome and genetic engineering research. PMID:21406066

Classification of Time Series Gene Expression in Clinical Studies via Integration of Biological Network

PubMed Central

Qian, Liwei; Zheng, Haoran; Zhou, Hong; Qin, Ruibin; Li, Jinlong

2013-01-01

The increasing availability of time series expression datasets, although promising, raises a number of new computational challenges. Accordingly, the development of suitable classification methods to make reliable and sound predictions is becoming a pressing issue. We propose, here, a new method to classify time series gene expression via integration of biological networks. We evaluated our approach on 2 different datasets and showed that the use of a hidden Markov model/Gaussian mixture models hybrid explores the time-dependence of the expression data, thereby leading to better prediction results. We demonstrated that the biclustering procedure identifies function-related genes as a whole, giving rise to high accordance in prognosis prediction across independent time series datasets. In addition, we showed that integration of biological networks into our method significantly improves prediction performance. Moreover, we compared our approach with several state-of–the-art algorithms and found that our method outperformed previous approaches with regard to various criteria. Finally, our approach achieved better prediction results on early-stage data, implying the potential of our method for practical prediction. PMID:23516469

Evolution of Daily Gene Co-expression Patterns from Algae to Plants

PubMed Central

de los Reyes, Pedro; Romero-Campero, Francisco J.; Ruiz, M. Teresa; Romero, José M.; Valverde, Federico

2017-01-01

Daily rhythms play a key role in transcriptome regulation in plants and microalgae orchestrating responses that, among other processes, anticipate light transitions that are essential for their metabolism and development. The recent accumulation of genome-wide transcriptomic data generated under alternating light:dark periods from plants and microalgae has made possible integrative and comparative analysis that could contribute to shed light on the evolution of daily rhythms in the green lineage. In this work, RNA-seq and microarray data generated over 24 h periods in different light regimes from the eudicot Arabidopsis thaliana and the microalgae Chlamydomonas reinhardtii and Ostreococcus tauri have been integrated and analyzed using gene co-expression networks. This analysis revealed a reduction in the size of the daily rhythmic transcriptome from around 90% in Ostreococcus, being heavily influenced by light transitions, to around 40% in Arabidopsis, where a certain independence from light transitions can be observed. A novel Multiple Bidirectional Best Hit (MBBH) algorithm was applied to associate single genes with a family of potential orthologues from evolutionary distant species. Gene duplication, amplification and divergence of rhythmic expression profiles seems to have played a central role in the evolution of gene families in the green lineage such as Pseudo Response Regulators (PRRs), CONSTANS-Likes (COLs), and DNA-binding with One Finger (DOFs). Gene clustering and functional enrichment have been used to identify groups of genes with similar rhythmic gene expression patterns. The comparison of gene clusters between species based on potential orthologous relationships has unveiled a low to moderate level of conservation of daily rhythmic expression patterns. However, a strikingly high conservation was found for the gene clusters exhibiting their highest and/or lowest expression value during the light transitions. PMID:28751903

Amyloid protein-mediated differential DNA methylation status regulates gene expression in Alzheimer's disease model cell line

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

Sung, Hye Youn; Choi, Eun Nam; Ahn Jo, Sangmee

2011-11-04

Highlights: Black-Right-Pointing-Pointer Genome-wide DNA methylation pattern in Alzheimer's disease model cell line. Black-Right-Pointing-Pointer Integrated analysis of CpG methylation and mRNA expression profiles. Black-Right-Pointing-Pointer Identify three Swedish mutant target genes; CTIF, NXT2 and DDR2 gene. Black-Right-Pointing-Pointer The effect of Swedish mutation on alteration of DNA methylation and gene expression. -- Abstract: The Swedish mutation of amyloid precursor protein (APP-sw) has been reported to dramatically increase beta amyloid production through aberrant cleavage at the beta secretase site, causing early-onset Alzheimer's disease (AD). DNA methylation has been reported to be associated with AD pathogenesis, but the underlying molecular mechanism of APP-sw-mediated epigenetic alterationsmore » in AD pathogenesis remains largely unknown. We analyzed genome-wide interplay between promoter CpG DNA methylation and gene expression in an APP-sw-expressing AD model cell line. To identify genes whose expression was regulated by DNA methylation status, we performed integrated analysis of CpG methylation and mRNA expression profiles, and identified three target genes of the APP-sw mutant; hypomethylated CTIF (CBP80/CBP20-dependent translation initiation factor) and NXT2 (nuclear exporting factor 2), and hypermethylated DDR2 (discoidin domain receptor 2). Treatment with the demethylating agent 5-aza-2 Prime -deoxycytidine restored mRNA expression of these three genes, implying methylation-dependent transcriptional regulation. The profound alteration in the methylation status was detected at the -435, -295, and -271 CpG sites of CTIF, and at the -505 to -341 region in the promoter of DDR2. In the promoter region of NXT2, only one CpG site located at -432 was differentially unmethylated in APP-sw cells. Thus, we demonstrated the effect of the APP-sw mutation on alteration of DNA methylation and subsequent gene expression. This epigenetic regulatory mechanism may contribute to the pathogenesis of AD.« less

Impact of Ischemia and Procurement Conditions on Gene Expression in Renal Cell Carcinoma

PubMed Central

Liu, Nick W.; Sanford, Thomas; Srinivasan, Ramaprasad; Liu, Jack L.; Khurana, Kiranpreet; Aprelikova, Olga; Valero, Vladimir; Bechert, Charles; Worrell, Robert; Pinto, Peter A.; Yang, Youfeng; Merino, Maria; Linehan, W. Marston; Bratslavsky, Gennady

2013-01-01

Purpose Previous studies have shown that ischemia alters gene expression in normal and malignant tissues. There are no studies that evaluated effects of ischemia in renal tumors. This study examines the impact of ischemia and tissue procurement conditions on RNA integrity and gene expression in renal cell carcinoma. Experimental Design Ten renal tumors were resected without renal hilar clamping from 10 patients with renal clear cell carcinoma. Immediately after tumor resection, a piece of tumor was snap frozen. Remaining tumor samples were stored at 4C, 22C and 37C and frozen at 5, 30, 60, 120, and 240 minutes. Histopathologic evaluation was performed on all tissue samples, and only those with greater than 80% tumor were selected for further analysis. RNA integrity was confirmed by electropherograms and quantitated using RIN index. Altered gene expression was assessed by paired, two-sample t-test between the zero time point and aliquots from various conditions obtained from the same tumor. Results One hundred and forty microarrays were performed. Some RNA degradation was observed 240 mins after resection at 37C. The expression of over 4,000 genes was significantly altered by ischemia times or storage conditions. The greatest gene expression changes were observed with longer ischemia time and warmer tissue procurement conditions. Conclusion RNA from kidney cancer remains intact for up to 4 hours post surgical resection regardless of storage conditions. Despite excellent RNA preservation, time after resection and procurement conditions significantly influence gene expression profiles. Meticulous attention to pre-acquisition variables is of paramount importance for accurate tumor profiling. PMID:23136194

Integral Light-Harvesting Complex Expression In Symbiodinium Within The Coral Acropora aspera Under Thermal Stress

NASA Astrophysics Data System (ADS)

Gierz, Sarah L.; Gordon, Benjamin R.; Leggat, William

2016-04-01

Coral reef success is largely dependent on the symbiosis between coral hosts and dinoflagellate symbionts belonging to the genus Symbiodinium. Elevated temperatures can result in the expulsion of Symbiodinium or loss of their photosynthetic pigments and is known as coral bleaching. It has been postulated that the expression of light-harvesting protein complexes (LHCs), which bind chlorophylls (chl) and carotenoids, are important in photobleaching. This study explored the effect a sixteen-day thermal stress (increasing daily from 25-34 °C) on integral LHC (chlorophyll a-chlorophyll c2-peridinin protein complex (acpPC)) gene expression in Symbiodinium within the coral Acropora aspera. Thermal stress leads to a decrease in Symbiodinium photosynthetic efficiency by day eight, while symbiont density was significantly lower on day sixteen. Over this time period, the gene expression of five Symbiodinium acpPC genes was quantified. Three acpPC genes exhibited up-regulated expression when corals were exposed to temperatures above 31.5 °C (acpPCSym_1:1, day sixteen; acpPCSym_15, day twelve; and acpPCSym_18, day ten and day sixteen). In contrast, the expression of acpPCSym_5:1 and acpPCSym_10:1 was unchanged throughout the experiment. Interestingly, the three acpPC genes with increased expression cluster together in a phylogenetic analysis of light-harvesting complexes.

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis.

PubMed

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-11-07

To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis

PubMed Central

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-01-01

Background To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. Results We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. Conclusion PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s). PMID:14604444

Identification of pathogenic genes and upstream regulators in age-related macular degeneration.

PubMed

Zhao, Bin; Wang, Mengya; Xu, Jing; Li, Min; Yu, Yuhui

2017-06-26

Age-related macular degeneration (AMD) is the leading cause of irreversible blindness in older individuals. Our study aims to identify the key genes and upstream regulators in AMD. To screen pathogenic genes of AMD, an integrated analysis was performed by using the microarray datasets in AMD derived from the Gene Expression Omnibus (GEO) database. The functional annotation and potential pathways of differentially expressed genes (DEGs) were further discovered by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. We constructed the AMD-specific transcriptional regulatory network to find the crucial transcriptional factors (TFs) which target the DEGs in AMD. Quantitative real time polymerase chain reaction (qRT-PCR) was performed to verify the DEGs and TFs obtained by integrated analysis. From two GEO datasets obtained, we identified 1280 DEGs (730 up-regulated and 550 down-regulated genes) between AMD and normal control (NC). After KEGG analysis, steroid biosynthesis is a significantly enriched pathway for DEGs. The expression of 8 genes (TNC, GRP, TRAF6, ADAMTS5, GPX3, FAP, DHCR7 and FDFT1) was detected. Except for TNC and GPX3, the other 6 genes in qRT-PCR played the same pattern with that in our integrated analysis. The dysregulation of these eight genes may involve with the process of AMD. Two crucial transcription factors (c-rel and myogenin) were concluded to play a role in AMD. Especially, myogenin was associated with AMD by regulating TNC, GRP and FAP. Our finding can contribute to developing new potential biomarkers, revealing the underlying pathogenesis, and further raising new therapeutic targets for AMD.

Dual Luciferase Assay System for Rapid Assessment of Gene Expression in Saccharomyces cerevisiae

PubMed Central

McNabb, David S.; Reed, Robin; Marciniak, Robert A.

2005-01-01

A new reporter system has been developed for quantifying gene expression in the yeast Saccharomyces cerevisiae. The system relies on two different reporter genes, Renilla and firefly luciferase, to evaluate regulated gene expression. The gene encoding Renilla luciferase is fused to a constitutive promoter (PGK1 or SPT15) and integrated into the yeast genome at the CAN1 locus as a control for normalizing the assay. The firefly luciferase gene is fused to the test promoter and integrated into the yeast genome at the ura3 or leu2 locus. The dual luciferase assay is performed by sequentially measuring the firefly and Renilla luciferase activities of the same sample, with the results expressed as the ratio of firefly to Renilla luciferase activity (Fluc/Rluc). The yeast dual luciferase reporter (DLR) was characterized and shown to be very efficient, requiring approximately 1 minute to complete each assay, and has proven to yield data that accurately and reproducibly reflect promoter activity. A series of integrating plasmids were generated that contain either the firefly or Renilla luciferase gene preceded by a multicloning region in two different orientations and the three reading frames to make possible the generation of translational fusions. Additionally, each set of plasmids contains either the URA3 or LEU2 marker for genetic selection in yeast. A series of S288C-based yeast strains, including a two-hybrid strain, were developed to facilitate the use of the yeast DLR assay. This assay can be readily adapted to a high-throughput platform for studies requiring numerous measurements. PMID:16151247

Co-expression network with protein-protein interaction and transcription regulation in malaria parasite Plasmodium falciparum.

PubMed

Yu, Fu-Dong; Yang, Shao-You; Li, Yuan-Yuan; Hu, Wei

2013-04-10

Malaria continues to be one of the most severe global infectious diseases, as a major threat to human health and economic development. Network-based biological analysis is a promising approach to uncover key genes and biological processes from a network viewpoint, which could not be recognized from individual gene-based signatures. We integrated gene co-expression profile with protein-protein interaction and transcriptional regulation information to construct a comprehensive gene co-expression network of Plasmodium falciparum. Based on this network, we identified 10 core modules by using ICE (Iterative Clique Enumeration) algorithm, which were essential for malaria parasite development in intraerythrocytic developmental cycle (IDC) stages. In each module, all genes were highly correlated probably due to co-regulation or formation of a protein complex. Some of these genes were recognized to be differentially coexpressed among three close-by IDC stages. The gene of prpf8 (PFD0265w) encoding pre-mRNA processing splicing factor 8 product was identified as DCGs (differentially co-expressed genes) among IDC stages, although this gene function was seldom reported in previous researches. Integrating the species-specific gene prediction and differential co-expression gene detection, we found some modules could perform species-specific functions according to some of genes in these modules were species-specific genes, like the module 10. Furthermore, in order to reveal the underlying mechanisms of the erythrocyte invasion by P. falciparum, Steiner Tree algorithm was employed to identify the invasion subnetwork from our gene co-expression network. The subnetwork-based analysis indicated that some important Plasmodium parasite specific genes could corporate with each other and be co-regulated during the parasite invasion process, which including a head-to-head gene pair of PfRH2a (PF13_0198) and PfRH2b (MAL13P1.176). This study based on gene co-expression network could shed new insights on the mechanisms of pathogenesis, even virulence and P. falciparum development. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

A regulatory toolbox of MiniPromoters to drive selective expression in the brain

PubMed Central

Portales-Casamar, Elodie; Swanson, Douglas J.; Liu, Li; de Leeuw, Charles N.; Banks, Kathleen G.; Ho Sui, Shannan J.; Fulton, Debra L.; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J.; Babyak, Nazar; Black, Sonia F.; Bonaguro, Russell J.; Brauer, Erich; Candido, Tara R.; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C. Y.; Chopra, Vik; Docking, T. Roderick; Dreolini, Lisa; D'Souza, Cletus A.; Flynn, Erin K.; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G.; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y.; Lim, Jonathan S.; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J.; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L.; Schmouth, Jean-François; Swanson, Magdalena I.; Tam, Bonny; Ticoll, Amy; Turner, Jenna L.; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F.; Wilson, Gary; Wong, Bibiana K. Y.; Wong, Siaw H.; Wong, Tony Y. T.; Yang, George S.; Ypsilanti, Athena R.; Jones, Steven J. M.; Holt, Robert A.; Goldowitz, Daniel; Wasserman, Wyeth W.; Simpson, Elizabeth M.

2010-01-01

The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination “knockins” in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5′ of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type–specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies. PMID:20807748

Pathogenesis of human papillomavirus-associated mucosal disease.

PubMed

Groves, Ian J; Coleman, Nicholas

2015-03-01

Human papillomaviruses (HPVs) are a necessary cause of carcinoma of the cervix and other mucosal epithelia. Key events in high-risk HPV (HRHPV)-associated neoplastic progression include persistent infection, deregulated expression of virus early genes in basal epithelial cells and genomic instability causing secondary host genomic imbalances. There are multiple mechanisms by which deregulated virus early gene expression may be achieved. Integration of virus DNA into host chromosomes is observed in the majority of cervical squamous cell carcinomas (SCCs), although in ∼15% of cases the virus remains extrachromosomal (episomal). Interestingly, not all integration events provide a growth advantage to basal cervical epithelial cells or lead to increased levels of the virus oncogenes E6 and E7, when compared with episome-containing basal cells. The factors that provide a competitive advantage to some integrants, but not others, are complex and include virus and host contributions. Gene expression from integrated and episomal HRHPV is regulated through host epigenetic mechanisms affecting the virus long control region (LCR), which appear to be of functional importance. New approaches to treating HRHPV-associated mucosal neoplasia include knockout of integrated HRHPV DNA, depletion of virus transcripts and inhibition of virus early gene transcription through targeting or use of epigenetic modifiers. Copyright © 2014 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2014 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Integrating microRNA and mRNA expression profiles of acute promyelocytic leukemia cells to explore the occurrence mechanisms of differentiation syndrome

PubMed Central

Ge, Fei; Cao, Fenglin; Li, Haitao; Wang, Ping; Xu, Mengyuan; Song, Peng; Li, Xiaoxia; Wang, Shuye; Li, Jinmei; Han, Xueying; Zhao, Yanhong; Su, Yanhua; Li, Yinghua; Fan, Shengjin; Li, Limin; Zhou, Jin

2016-01-01

The pathogenesis of therapy-induced differentiation syndrome (DS) in patients with acute promyelocytic leukemia (APL) remains unclear. In this study, mRNA and microRNA (miRNA) expression profiling of peripheral blood APL cells from patients complicated with vs. without DS were integratively analyzed to explore the mechanisms underlying arsenic trioxide treatment-associated DS. By integrating the differentially expressed data with the data of differentially expressed microRNAs and their computationally predicted target genes, as well as the data of transcription factors and differentially expressed target microRNAs obtained from a literature search, a DS-related genetic regulatory network was constructed. Then using an EAGLE algorithm in clusterViz, the network was subdivided into 10 modules. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database the modules were annotated functionally, and three functionally active modules were recognized. The further in-depth analyses on the annotated functions of the three modules and the expression and roles of the related genes revealed that proliferation, differentiation, apoptosis and infiltration capability of APL cells might play important roles in the DS pathogenesis. The results could improve our understanding of DS pathogenesis from a more overall perspective, and could provide new clues for future research. PMID:27634874

Integrative Genomics Reveals Mechanisms of Copy Number Alterations Responsible for Transcriptional Deregulation in Colorectal Cancer

PubMed Central

Camps, Jordi; Nguyen, Quang Tri; Padilla-Nash, Hesed M.; Knutsen, Turid; McNeil, Nicole E.; Wangsa, Danny; Hummon, Amanda B.; Grade, Marian; Ried, Thomas; Difilippantonio, Michael J.

2016-01-01

To evaluate the mechanisms and consequences of chromosomal aberrations in colorectal cancer (CRC), we used a combination of spectral karyotyping, array comparative genomic hybridization (aCGH), and array-based global gene expression profiling on 31 primary carcinomas and 15 established cell lines. Importantly, aCGH showed that the genomic profiles of primary tumors are recapitulated in the cell lines. We revealed a preponderance of chromosome breakpoints at sites of copy number variants (CNVs) in the CRC cell lines, a novel mechanism of DNA breakage in cancer. The integration of gene expression and aCGH led to the identification of 157 genes localized within high-level copy number changes whose transcriptional deregulation was significantly affected across all of the samples, thereby suggesting that these genes play a functional role in CRC. Genomic amplification at 8q24 was the most recurrent event and led to the overexpression of MYC and FAM84B. Copy number dependent gene expression resulted in deregulation of known cancer genes such as APC, FGFR2, and ERBB2. The identification of only 36 genes whose localization near a breakpoint could account for their observed deregulated expression demonstrates that the major mechanism for transcriptional deregulation in CRC is genomic copy number changes resulting from chromosomal aberrations. PMID:19691111

Plant Omics Data Center: an integrated web repository for interspecies gene expression networks with NLP-based curation.

PubMed

Ohyanagi, Hajime; Takano, Tomoyuki; Terashima, Shin; Kobayashi, Masaaki; Kanno, Maasa; Morimoto, Kyoko; Kanegae, Hiromi; Sasaki, Yohei; Saito, Misa; Asano, Satomi; Ozaki, Soichi; Kudo, Toru; Yokoyama, Koji; Aya, Koichiro; Suwabe, Keita; Suzuki, Go; Aoki, Koh; Kubo, Yasutaka; Watanabe, Masao; Matsuoka, Makoto; Yano, Kentaro

2015-01-01

Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

A study of structural properties of gene network graphs for mathematical modeling of integrated mosaic gene networks.

PubMed

Petrovskaya, Olga V; Petrovskiy, Evgeny D; Lavrik, Inna N; Ivanisenko, Vladimir A

2017-04-01

Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals. An automatic modeling of 10,000 synthetic mosaic gene regulatory networks was carried out using computer experiments on gene knockdowns/knockouts. Structural analysis of graphs of generated mosaic gene regulatory networks has revealed that the most important factor for building accurate integrated mathematical models, among those analyzed in the study, is data on expression of genes corresponding to the vertices with high properties of centrality.

MARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures.

PubMed

Vazquez, Miguel; Nogales-Cadenas, Ruben; Arroyo, Javier; Botías, Pedro; García, Raul; Carazo, Jose M; Tirado, Francisco; Pascual-Montano, Alberto; Carmona-Saez, Pedro

2010-07-01

The enormous amount of data available in public gene expression repositories such as Gene Expression Omnibus (GEO) offers an inestimable resource to explore gene expression programs across several organisms and conditions. This information can be used to discover experiments that induce similar or opposite gene expression patterns to a given query, which in turn may lead to the discovery of new relationships among diseases, drugs or pathways, as well as the generation of new hypotheses. In this work, we present MARQ, a web-based application that allows researchers to compare a query set of genes, e.g. a set of over- and under-expressed genes, against a signature database built from GEO datasets for different organisms and platforms. MARQ offers an easy-to-use and integrated environment to mine GEO, in order to identify conditions that induce similar or opposite gene expression patterns to a given experimental condition. MARQ also includes additional functionalities for the exploration of the results, including a meta-analysis pipeline to find genes that are differentially expressed across different experiments. The application is freely available at http://marq.dacya.ucm.es.

Reconstructing regulatory networks from the dynamic plasticity of gene expression by mutual information

PubMed Central

Wang, Jianxin; Chen, Bo; Wang, Yaqun; Wang, Ningtao; Garbey, Marc; Tran-Son-Tay, Roger; Berceli, Scott A.; Wu, Rongling

2013-01-01

The capacity of an organism to respond to its environment is facilitated by the environmentally induced alteration of gene and protein expression, i.e. expression plasticity. The reconstruction of gene regulatory networks based on expression plasticity can gain not only new insights into the causality of transcriptional and cellular processes but also the complex regulatory mechanisms that underlie biological function and adaptation. We describe an approach for network inference by integrating expression plasticity into Shannon’s mutual information. Beyond Pearson correlation, mutual information can capture non-linear dependencies and topology sparseness. The approach measures the network of dependencies of genes expressed in different environments, allowing the environment-induced plasticity of gene dependencies to be tested in unprecedented details. The approach is also able to characterize the extent to which the same genes trigger different amounts of expression in response to environmental changes. We demonstrated the usefulness of this approach through analysing gene expression data from a rabbit vein graft study that includes two distinct blood flow environments. The proposed approach provides a powerful tool for the modelling and analysis of dynamic regulatory networks using gene expression data from distinct environments. PMID:23470995

iGWAS: Integrative Genome-Wide Association Studies of Genetic and Genomic Data for Disease Susceptibility Using Mediation Analysis.

PubMed

Huang, Yen-Tsung; Liang, Liming; Moffatt, Miriam F; Cookson, William O C M; Lin, Xihong

2015-07-01

Genome-wide association studies (GWAS) have been a standard practice in identifying single nucleotide polymorphisms (SNPs) for disease susceptibility. We propose a new approach, termed integrative GWAS (iGWAS) that exploits the information of gene expressions to investigate the mechanisms of the association of SNPs with a disease phenotype, and to incorporate the family-based design for genetic association studies. Specifically, the relations among SNPs, gene expression, and disease are modeled within the mediation analysis framework, which allows us to disentangle the genetic effect on a disease phenotype into two parts: an effect mediated through a gene expression (mediation effect, ME) and an effect through other biological mechanisms or environment-mediated mechanisms (alternative effect, AE). We develop omnibus tests for the ME and AE that are robust to underlying true disease models. Numerical studies show that the iGWAS approach is able to facilitate discovering genetic association mechanisms, and outperforms the SNP-only method for testing genetic associations. We conduct a family-based iGWAS of childhood asthma that integrates genetic and genomic data. The iGWAS approach identifies six novel susceptibility genes (MANEA, MRPL53, LYCAT, ST8SIA4, NDFIP1, and PTCH1) using the omnibus test with false discovery rate less than 1%, whereas no gene using SNP-only analyses survives with the same cut-off. The iGWAS analyses further characterize that genetic effects of these genes are mostly mediated through their gene expressions. In summary, the iGWAS approach provides a new analytic framework to investigate the mechanism of genetic etiology, and identifies novel susceptibility genes of childhood asthma that were biologically meaningful. © 2015 WILEY PERIODICALS, INC.

In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

PubMed Central

Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-01

Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

Transient Expression of an LEDGF/p75 Chimera Retargets Lentivector Integration and Functionally Rescues in a Model for X-CGD.

PubMed

Vets, Sofie; De Rijck, Jan; Brendel, Christian; Grez, Manuel; Bushman, Frederic; Debyser, Zeger; Gijsbers, Rik

2013-03-05

Retrovirus-based vectors are commonly used as delivery vehicles to correct genetic diseases because of their ability to integrate new sequences stably. However, adverse events in which vector integration activates proto-oncogenes, leading to clonal expansion and leukemogenesis hamper their application. The host cell-encoded lens epithelium-derived growth factor (LEDGF/p75) binds lentiviral integrase and targets integration to active transcription units. We demonstrated earlier that replacing the LEDGF/p75 chromatin interaction domain with an alternative DNA-binding protein could retarget integration. Here, we show that transient expression of the chimeric protein using mRNA electroporation efficiently redirects lentiviral vector (LV) integration in wild-type (WT) cells. We then employed this technology in a model for X-linked chronic granulomatous disease (X-CGD) using myelomonocytic PLB-985 gp91(-/-) cells. Following electroporation with mRNA encoding the LEDGF-chimera, the cells were treated with a therapeutic lentivector encoding gp91(phox). Integration site analysis revealed retargeted integration away from genes and towards heterochromatin-binding protein 1β (CBX1)-binding sites, in regions enriched in marks associated with gene silencing. Nevertheless, gp91(phox) expression was stable for at least 6 months after electroporation and NADPH-oxidase activity was restored to normal levels as determined by superoxide production. Together, these data provide proof-of-principle that transient expression of engineered LEDGF-chimera can retarget lentivector integration and rescues the disease phenotype in a cell model, opening perspectives for safer gene therapy.Molecular Therapy - Nucleic Acids (2013) 2, e77; doi:10.1038/mtna.2013.4; published online 5 March 2013.

Optimized Sleeping Beauty transposons rapidly generate stable transgenic cell lines.

PubMed

Kowarz, Eric; Löscher, Denise; Marschalek, Rolf

2015-04-01

Stable gene expression in mammalian cells is a prerequisite for many in vitro and in vivo experiments. However, either the integration of plasmids into mammalian genomes or the use of retro-/lentiviral systems have intrinsic limitations. The use of transposable elements, e.g. the Sleeping Beauty system (SB), circumvents most of these drawbacks (integration sites, size limitations) and allows the quick generation of stable cell lines. The integration process of SB is catalyzed by a transposase and the handling of this gene transfer system is easy, fast and safe. Here, we report our improvements made to the existing SB vector system and present two new vector types for robust constitutive or inducible expression of any gene of interest. Both types are available in 16 variants with different selection marker (puromycin, hygromycin, blasticidin, neomycin) and fluorescent protein expression (GFP, RFP, BFP) to fit most experimental requirements. With this system it is possible to generate cell lines from stable transfected cells quickly and reliably in a medium-throughput setting (three to five days). Cell lines robustly express any gene-of-interest, either constitutively or tightly regulated by doxycycline. This allows many laboratory experiments to speed up generation of data in a rapid and robust manner. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

PubMed

Liu, Jian; Cheng, Yuhu; Wang, Xuesong; Zhang, Lin; Liu, Hui

2017-08-17

It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1 -norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.

Understanding the mechanisms of ATPase beta family genes for cellular thermotolerance in crossbred bulls

NASA Astrophysics Data System (ADS)

Deb, Rajib; Sajjanar, Basavaraj; Singh, Umesh; Alex, Rani; Raja, T. V.; Alyethodi, Rafeeque R.; Kumar, Sushil; Sengar, Gyanendra; Sharma, Sheetal; Singh, Rani; Prakash, B.

2015-12-01

Na+/K+-ATPase is an integral membrane protein composed of a large catalytic subunit (alpha), a smaller glycoprotein subunit (beta), and gamma subunit. The beta subunit is essential for ion recognition as well as maintenance of the membrane integrity. Present study was aimed to analyze the expression pattern of ATPase beta subunit genes (ATPase B1, ATPase B2, and ATPase B3) among the crossbred bulls under different ambient temperatures (20-44 °C). The present study was also aimed to look into the relationship of HSP70 with the ATPase beta family genes. Our results demonstrated that among beta family genes, transcript abundance of ATPase B1 and ATPase B2 is significantly ( P < 0.05) higher during the thermal stress. Pearson correlation coefficient analysis revealed that the expression of ATPase Β1, ATPase B2, and ATPase B3 is highly correlated ( P < 0.01) with HSP70, representing that the change in the expression pattern of these genes is positive and synergistic. These may provide a foundation for understanding the mechanisms of ATPase beta family genes for cellular thermotolerance in cattle.

Integrating genetic and toxicogenomic information for determining underlying susceptibility to developmental disorders.

PubMed

Robinson, Joshua F; Port, Jesse A; Yu, Xiaozhong; Faustman, Elaine M

2010-10-01

To understand the complex etiology of developmental disorders, an understanding of both genetic and environmental risk factors is needed. Human and rodent genetic studies have identified a multitude of gene candidates for specific developmental disorders such as neural tube defects (NTDs). With the emergence of toxicogenomic-based assessments, scientists now also have the ability to compare and understand the expression of thousands of genes simultaneously across strain, time, and exposure in developmental models. Using a systems-based approach in which we are able to evaluate information from various parts and levels of the developing organism, we propose a framework for integrating genetic information with toxicogenomic-based studies to better understand gene-environmental interactions critical for developmental disorders. This approach has allowed us to characterize candidate genes in the context of variables critical for determining susceptibility such as strain, time, and exposure. Using a combination of toxicogenomic studies and complementary bioinformatic tools, we characterize NTD candidate genes during normal development by function (gene ontology), linked phenotype (disease outcome), location, and expression (temporally and strain-dependent). In addition, we show how environmental exposures (cadmium, methylmercury) can influence expression of these genes in a strain-dependent manner. Using NTDs as an example of developmental disorder, we show how simple integration of genetic information from previous studies into the standard microarray design can enhance analysis of gene-environment interactions to better define environmental exposure-disease pathways in sensitive and resistant mouse strains. © Wiley-Liss, Inc.

Prediction of epigenetically regulated genes in breast cancer cell lines.

PubMed

Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria E H; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram

2010-06-04

Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

The gene expression database for mouse development (GXD): putting developmental expression information at your fingertips.

PubMed

Smith, Constance M; Finger, Jacqueline H; Kadin, James A; Richardson, Joel E; Ringwald, Martin

2014-10-01

Because molecular mechanisms of development are extraordinarily complex, the understanding of these processes requires the integration of pertinent research data. Using the Gene Expression Database for Mouse Development (GXD) as an example, we illustrate the progress made toward this goal, and discuss relevant issues that apply to developmental databases and developmental research in general. Since its first release in 1998, GXD has served the scientific community by integrating multiple types of expression data from publications and electronic submissions and by making these data freely and widely available. Focusing on endogenous gene expression in wild-type and mutant mice and covering data from RNA in situ hybridization, in situ reporter (knock-in), immunohistochemistry, reverse transcriptase-polymerase chain reaction, Northern blot, and Western blot experiments, the database has grown tremendously over the years in terms of data content and search utilities. Currently, GXD includes over 1.4 million annotated expression results and over 260,000 images. All these data and images are readily accessible to many types of database searches. Here we describe the data and search tools of GXD; explain how to use the database most effectively; discuss how we acquire, curate, and integrate developmental expression information; and describe how the research community can help in this process. Copyright © 2014 The Authors Developmental Dynamics published by Wiley Periodicals, Inc. on behalf of American Association of Anatomists.

Integrated computational biology analysis to evaluate target genes for chronic myelogenous leukemia.

PubMed

Zheng, Yu; Wang, Yu-Ping; Cao, Hongbao; Chen, Qiusheng; Zhang, Xi

2018-06-05

Although hundreds of genes have been linked to chronic myelogenous leukemia (CML), many of the results lack reproducibility. In the present study, data across multiple modalities were integrated to evaluate 579 CML candidate genes, including literature‑based CML‑gene relation data, Gene Expression Omnibus RNA expression data and pathway‑based gene‑gene interaction data. The expression data included samples from 76 patients with CML and 73 healthy controls. For each target gene, four metrics were proposed and tested with case/control classification. The effectiveness of the four metrics presented was demonstrated by the high classification accuracy (94.63%; P<2x10‑4). Cross metric analysis suggested nine top candidate genes for CML: Epidermal growth factor receptor, tumor protein p53, catenin β 1, janus kinase 2, tumor necrosis factor, abelson murine leukemia viral oncogene homolog 1, vascular endothelial growth factor A, B‑cell lymphoma 2 and proto‑oncogene tyrosine‑protein kinase. In addition, 145 CML candidate pathways enriched with 485 out of 579 genes were identified (P<8.2x10‑11; q=0.005). In conclusion, weighted genetic networks generated using computational biology may be complementary to biological experiments for the evaluation of known or novel CML target genes.

Successful downstream application of the Paxgene Blood RNA system from small blood samples in paediatric patients for quantitative PCR analysis

PubMed Central

Carrol, Enitan D; Salway, Fiona; Pepper, Stuart D; Saunders, Emma; Mankhambo, Limangeni A; Ollier, William E; Hart, C Anthony; Day, Phillip

2007-01-01

Background The challenge of gene expression studies is to reliably quantify levels of transcripts, but this is hindered by a number of factors including sample availability, handling and storage. The PAXgene™ Blood RNA System includes a stabilizing additive in a plastic evacuated tube, but requires 2.5 mL blood, which makes routine implementation impractical for paediatric use. The aim of this study was to modify the PAXgene™ Blood RNA System kit protocol for application to small, sick chidren, without compromising RNA integrity, and subsequently to perform quantitative analysis of ICAM and interleukin-6 gene expression. Aliquots of 0.86 mL PAXgene™ reagent were put into microtubes and 0.3 mL whole blood added to maintain the same recommended proportions as in the PAXgene™ evacuated tube system. RNA quality was assessed using the Agilent BioAnalyser 2100 and an in-house TaqMan™ assay which measures GAPDH transcript integrity by determining 3' to 5' ratios. qPCR analysis was performed on an additional panel of 7 housekeeping genes. Three reference genes (HPRT1, YWHAZ and GAPDH) were identified using the GeNORM algorithm, which were subsequently used to normalising target gene expression levels. ICAM-1 and IL-6 gene expression were measured in 87 Malawian children with invasive pneumococcal disease. Results Total RNA yield was between 1,114 and 2,950 ng and the BioAnalyser 2100 demonstrated discernible 18s and 28s bands. The cycle threshold values obtained for the seven housekeeping genes were between 15 and 30 and showed good consistency. Median relative ICAM and IL-6 gene expression were significantly reduced in non-survivors compared to survivors (ICAM: 3.56 vs 4.41, p = 0.04, and IL-6: 2.16 vs 6.73, p = 0.02). Conclusion We have successfully modified the PAXgene™ blood collection system for use in small children and demonstrated preservation of RNA integrity and successful quantitative real-time PCR analysis. PMID:17850649

Integrated Analyses of microRNAs Demonstrate Their Widespread Influence on Gene Expression in High-Grade Serous Ovarian Carcinoma

PubMed Central

Levine, Douglas A.; Mankoo, Parminder; Schultz, Nikolaus; Du, Ying; Zhang, Yiqun; Larsson, Erik; Sheridan, Robert; Xiao, Weimin; Spellman, Paul T.; Getz, Gad; Wheeler, David A.; Perou, Charles M.; Gibbs, Richard A.; Sander, Chris; Hayes, D. Neil; Gunaratne, Preethi H.

2012-01-01

Background The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets. Methods and Results Integration of miRNA and gene patterns yielded evidence that proximal pairs of miRNAs are processed from polycistronic primary transcripts, and that intronic miRNAs and their host gene mRNAs derive from common transcripts. Patterns of miRNA expression revealed multiple tumor subtypes and a set of 34 miRNAs predictive of overall patient survival. In a global analysis, miRNA:mRNA pairs anti-correlated in expression across tumors showed a higher frequency of in silico predicted target sites in the mRNA 3′-untranslated region (with less frequency observed for coding sequence and 5′-untranslated regions). The miR-29 family and predicted target genes were among the most strongly anti-correlated miRNA:mRNA pairs; over-expression of miR-29a in vitro repressed several anti-correlated genes (including DNMT3A and DNMT3B) and substantially decreased ovarian cancer cell viability. Conclusions This study establishes miRNAs as having a widespread impact on gene expression programs in ovarian cancer, further strengthening our understanding of miRNA biology as it applies to human cancer. As with gene transcripts, miRNAs exhibit high diversity reflecting the genomic heterogeneity within a clinically homogeneous disease population. Putative miRNA:mRNA interactions, as identified using integrative analysis, can be validated. TCGA data are a valuable resource for the identification of novel tumor suppressive miRNAs in ovarian as well as other cancers. PMID:22479643

Identification of hypertension-related genes through an integrated genomic-transcriptomic approach.

PubMed

Yagil, Chana; Hubner, Norbert; Monti, Jan; Schulz, Herbert; Sapojnikov, Marina; Luft, Friedrich C; Ganten, Detlev; Yagil, Yoram

2005-04-01

In search for the genetic basis of hypertension, we applied an integrated genomic-transcriptomic approach to identify genes involved in the pathogenesis of hypertension in the Sabra rat model of salt-susceptibility. In the genomic arm of the project, we previously detected in male rats two salt-susceptibility QTLs on chromosome 1, SS1a (D1Mgh2-D1Mit11; span 43.1 cM) and SS1b (D1Mit11-D1Mit4; span 18 cM). In the transcriptomic arm, we studied differential gene expression in kidneys of SBH/y and SBN/y rats that had been fed regular diet or salt-loaded. We used the Affymetrix Rat Genome RAE230 GeneChip and probed >30,000 transcripts. The research algorithm called for an initial genome-wide screen for differentially expressed transcripts between the study groups. This step was followed by cluster analysis based on 2x2 ANOVA to identify transcripts that were of relevance specifically to salt-sensitivity and hypertension and to salt-resistance. The two arms of the project were integrated by identifying those differentially expressed transcripts that showed an allele-specific hypertensive effect on salt-loading and that mapped within the defined boundaries of the salt-susceptibility QTLs on chromosome 1. The differentially expressed transcripts were confirmed by RT-PCR. Of the 2933 genes annotated to rat chromosome 1, 1102 genes were identified within the boundaries of the two blood pressure QTLs. The microarray identified 2470 transcripts that were differentially expressed between the study groups. Cluster analysis identified genome-wide 192 genes that were relevant to salt-susceptibility and/or hypertension, 19 of which mapped to chromosome 1. Eight of these genes mapped within the boundaries of QTLs SS1a and SS1b. RT-PCR confirmed 7 genes, leaving TcTex1, Myadm, Lisch7, Axl-like, Fah, PRC1-like, and Serpinh1. None of these genes has been implicated in hypertension before. These genes become henceforth targets for our continuing search for the genetic basis of hypertension.

Development of an antibiotic marker-free platform for heterologous protein production in Streptomyces.

PubMed

Sevillano, Laura; Díaz, Margarita; Santamaría, Ramón I

2017-09-26

The industrial use of enzymes produced by microorganisms is continuously growing due to the need for sustainable solutions. Nevertheless, many of the plasmids used for recombinant production of proteins in bacteria are based on the use of antibiotic resistance genes as selection markers. The safety concerns and legal requirements surrounding the increased use of antibiotic resistance genes have made the development of new antibiotic-free approaches essential. In this work, a system completely free of antibiotic resistance genes and useful for the production of high yields of proteins in Streptomyces is described. This system is based on the separation of the two components of the yefM/yoeBsl (antitoxin/toxin) operon; the toxin (yoeBsl) gene, responsible for host death, is integrated into the genome and the antitoxin gene (yefMsl), which inactivates the toxin, is located in the expression plasmid. To develop this system, the toxin gene was integrated into the genome of a strain lacking the complete operon, and the antibiotic resistance gene integrated along with the toxin was eliminated by Cre recombinase to generate a final host strain free of any antibiotic resistance marker. In the same way, the antibiotic resistance gene from the final expression plasmid was removed by Dre recombinase. The usefulness of this system was analysed by checking the production of two hydrolases from different Streptomyces. Production of both proteins, with potential industrial use, was high and stable over time after strain storage and after serial subcultures. These results support the robustness and stability of the positive selection system developed. The total absence of antibiotic resistance genes makes this system a powerful tool for using Streptomyces as a host to produce proteins at the industrial level. This work is the first Streptomyces antibiotic marker-free system to be described. Graphical abstract Antibiotic marker-free platform for protein expression in Streptomyces. The antitoxin gene present in the expression plasmid counteracts the effect of the toxin gene in the genome. In absence of the expression plasmid, the toxin causes cell death ensuring that only plasmid-containing cells persist.

Production of Candida antaractica Lipase B Gene Open Reading Frame using Automated PCR Gene Assembly Protocol on Robotic Workcell & Expression in Ethanologenic Yeast for use as Resin-Bound Biocatalyst in Biodiesel Production

USDA-ARS?s Scientific Manuscript database

A synthetic Candida antarctica lipase B (CALB) gene open reading frame (ORF) for expression in yeast was produced using an automated PCR assembly and DNA purification protocol on an integrated robotic workcell. The lycotoxin-1 (Lyt-1) C3 variant gene ORF was added in-frame with the CALB ORF to pote...

A framework for analyzing the relationship between gene expression and morphological, topological, and dynamical patterns in neuronal networks.

PubMed

de Arruda, Henrique Ferraz; Comin, Cesar Henrique; Miazaki, Mauro; Viana, Matheus Palhares; Costa, Luciano da Fontoura

2015-04-30

A key point in developmental biology is to understand how gene expression influences the morphological and dynamical patterns that are observed in living beings. In this work we propose a methodology capable of addressing this problem that is based on estimating the mutual information and Pearson correlation between the intensity of gene expression and measurements of several morphological properties of the cells. A similar approach is applied in order to identify effects of gene expression over the system dynamics. Neuronal networks were artificially grown over a lattice by considering a reference model used to generate artificial neurons. The input parameters of the artificial neurons were determined according to two distinct patterns of gene expression and the dynamical response was assessed by considering the integrate-and-fire model. As far as single gene dependence is concerned, we found that the interaction between the gene expression and the network topology, as well as between the former and the dynamics response, is strongly affected by the gene expression pattern. In addition, we observed a high correlation between the gene expression and some topological measurements of the neuronal network for particular patterns of gene expression. To our best understanding, there are no similar analyses to compare with. A proper understanding of gene expression influence requires jointly studying the morphology, topology, and dynamics of neurons. The proposed framework represents a first step towards predicting gene expression patterns from morphology and connectivity. Copyright © 2015. Published by Elsevier B.V.

Plasmid-Encoded Tetracycline Efflux Pump Protein Alters Bacterial Stress Responses and Ecological Fitness of Acinetobacter oleivorans

PubMed Central

Hong, Hyerim; Jung, Jaejoon; Park, Woojun

2014-01-01

Acquisition of the extracellular tetracycline (TC) resistance plasmid pAST2 affected host gene expression and phenotype in the oil-degrading soil bacterium, Acinetobacter oleivorans DR1. Whole-transcriptome profiling of DR1 cells harboring pAST2 revealed that all the plasmid genes were highly expressed under TC conditions, and the expression levels of many host chromosomal genes were modulated by the presence of pAST2. The host energy burden imposed by replication of pAST2 led to (i) lowered ATP concentrations, (ii) downregulated expression of many genes involved in cellular growth, and (iii) reduced growth rate. Interestingly, some phenotypes were restored by deleting the plasmid-encoded efflux pump gene tetH, suggesting that the membrane integrity changes resulting from the incorporation of efflux pump proteins also resulted in altered host response under the tested conditions. Alteration of membrane integrity by tetH deletion was shown by measuring permeability of fluorescent probe and membrane hydrophobicity. The presence of the plasmid conferred peroxide and superoxide resistance to cells, but only peroxide resistance was diminished by tetH gene deletion, suggesting that the plasmid-encoded membrane-bound efflux pump protein provided peroxide resistance. The downregulation of fimbriae-related genes presumably led to reduced swimming motility, but this phenotype was recovered by tetH gene deletion. Our data suggest that not only the plasmid replication burden, but also its encoded efflux pump protein altered host chromosomal gene expression and phenotype, which also alters the ecological fitness of the host in the environment. PMID:25229538

Plasmid-encoded tetracycline efflux pump protein alters bacterial stress responses and ecological fitness of Acinetobacter oleivorans.

PubMed

Hong, Hyerim; Jung, Jaejoon; Park, Woojun

2014-01-01

Acquisition of the extracellular tetracycline (TC) resistance plasmid pAST2 affected host gene expression and phenotype in the oil-degrading soil bacterium, Acinetobacter oleivorans DR1. Whole-transcriptome profiling of DR1 cells harboring pAST2 revealed that all the plasmid genes were highly expressed under TC conditions, and the expression levels of many host chromosomal genes were modulated by the presence of pAST2. The host energy burden imposed by replication of pAST2 led to (i) lowered ATP concentrations, (ii) downregulated expression of many genes involved in cellular growth, and (iii) reduced growth rate. Interestingly, some phenotypes were restored by deleting the plasmid-encoded efflux pump gene tetH, suggesting that the membrane integrity changes resulting from the incorporation of efflux pump proteins also resulted in altered host response under the tested conditions. Alteration of membrane integrity by tetH deletion was shown by measuring permeability of fluorescent probe and membrane hydrophobicity. The presence of the plasmid conferred peroxide and superoxide resistance to cells, but only peroxide resistance was diminished by tetH gene deletion, suggesting that the plasmid-encoded membrane-bound efflux pump protein provided peroxide resistance. The downregulation of fimbriae-related genes presumably led to reduced swimming motility, but this phenotype was recovered by tetH gene deletion. Our data suggest that not only the plasmid replication burden, but also its encoded efflux pump protein altered host chromosomal gene expression and phenotype, which also alters the ecological fitness of the host in the environment.

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana

PubMed Central

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants. PMID:29692794

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana.

PubMed

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants.

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis

PubMed Central

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T.

2016-01-01

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan–Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. PMID:26507857

Identification of Differentially Expressed Genes through Integrated Study of Alzheimer's Disease Affected Brain Regions.

PubMed

Puthiyedth, Nisha; Riveros, Carlos; Berretta, Regina; Moscato, Pablo

2016-01-01

Alzheimer's disease (AD) is the most common form of dementia in older adults that damages the brain and results in impaired memory, thinking and behaviour. The identification of differentially expressed genes and related pathways among affected brain regions can provide more information on the mechanisms of AD. In the past decade, several studies have reported many genes that are associated with AD. This wealth of information has become difficult to follow and interpret as most of the results are conflicting. In that case, it is worth doing an integrated study of multiple datasets that helps to increase the total number of samples and the statistical power in detecting biomarkers. In this study, we present an integrated analysis of five different brain region datasets and introduce new genes that warrant further investigation. The aim of our study is to apply a novel combinatorial optimisation based meta-analysis approach to identify differentially expressed genes that are associated to AD across brain regions. In this study, microarray gene expression data from 161 samples (74 non-demented controls, 87 AD) from the Entorhinal Cortex (EC), Hippocampus (HIP), Middle temporal gyrus (MTG), Posterior cingulate cortex (PC), Superior frontal gyrus (SFG) and visual cortex (VCX) brain regions were integrated and analysed using our method. The results are then compared to two popular meta-analysis methods, RankProd and GeneMeta, and to what can be obtained by analysing the individual datasets. We find genes related with AD that are consistent with existing studies, and new candidate genes not previously related with AD. Our study confirms the up-regualtion of INFAR2 and PTMA along with the down regulation of GPHN, RAB2A, PSMD14 and FGF. Novel genes PSMB2, WNK1, RPL15, SEMA4C, RWDD2A and LARGE are found to be differentially expressed across all brain regions. Further investigation on these genes may provide new insights into the development of AD. In addition, we identified the presence of 23 non-coding features, including four miRNA precursors (miR-7, miR570, miR-1229 and miR-6821), dysregulated across the brain regions. Furthermore, we compared our results with two popular meta-analysis methods RankProd and GeneMeta to validate our findings and performed a sensitivity analysis by removing one dataset at a time to assess the robustness of our results. These new findings may provide new insights into the disease mechanisms and thus make a significant contribution in the near future towards understanding, prevention and cure of AD.

Uncovering Hidden Layers of Cell Cycle Regulation through Integrative Multi-omic Analysis

PubMed Central

Aviner, Ranen; Shenoy, Anjana; Elroy-Stein, Orna; Geiger, Tamar

2015-01-01

Studying the complex relationship between transcription, translation and protein degradation is essential to our understanding of biological processes in health and disease. The limited correlations observed between mRNA and protein abundance suggest pervasive regulation of post-transcriptional steps and support the importance of profiling mRNA levels in parallel to protein synthesis and degradation rates. In this work, we applied an integrative multi-omic approach to study gene expression along the mammalian cell cycle through side-by-side analysis of mRNA, translation and protein levels. Our analysis sheds new light on the significant contribution of both protein synthesis and degradation to the variance in protein expression. Furthermore, we find that translation regulation plays an important role at S-phase, while progression through mitosis is predominantly controlled by changes in either mRNA levels or protein stability. Specific molecular functions are found to be co-regulated and share similar patterns of mRNA, translation and protein expression along the cell cycle. Notably, these include genes and entire pathways not previously implicated in cell cycle progression, demonstrating the potential of this approach to identify novel regulatory mechanisms beyond those revealed by traditional expression profiling. Through this three-level analysis, we characterize different mechanisms of gene expression, discover new cycling gene products and highlight the importance and utility of combining datasets generated using different techniques that monitor distinct steps of gene expression. PMID:26439921

Integrated Analysis of Genome-wide Copy Number Alterations and Gene Expression in MSS, CIMP-negative Colon Cancer

PubMed Central

Loo, Lenora WM; Tiirikainen, Maarit; Cheng, Iona; Lum-Jones, Annette; Seifried, Ann; Church, James M; Gryfe, Robert; Weisenberger, Daniel J; Lindor, Noralane M; Gallinger, Steven; Haile, Robert W; Duggan, David J; Thibodeau, Stephen N; Casey, Graham; Le Marchand, Loïc

2014-01-01

Microsatellite stable (MSS), CpG island methylator phenotype (CIMP)-negative colorectal tumors, the most prevalent molecular subtype of colorectal cancer, are associated with extensive copy number alteration (CNA) events and aneuploidy. We report on the identification of characteristic recurrent CNA (with frequency >25%) events and associated gene expression profiles for a total of 40 paired tumor and adjacent normal colon tissues using genome-wide microarrays. We observed recurrent CNAs, namely gains at 1q, 7p, 7q, 8p12-11, 8q, 12p13, 13q, 20p, 20q, Xp, and Xq and losses at 1p36, 1p31, 1p21, 4p15-12, 4q12-35, 5q21-22, 6q26, 8p, 14q, 15q11-12, 17p, 18p, 18q, 21q21-22, and 22q. Within these genomic regions we identified 356 genes with significant differential expression (P<0.0001 and ±1.5 fold change) in the tumor compared to adjacent normal tissue. Gene ontology and pathway analyses indicated that many of these genes were involved in functional mechanisms that regulate cell cycle, cell death, and metabolism. An amplicon present in >70% of the tumor samples at 20q11-20q13 contained several cancer-related genes (AHCY, POFUT1, RPN2, TH1L and PRPF6) that were up-regulated and demonstrated a significant linear correlation (P<0.05) for gene dosage and gene expression. Copy number loss at 8p, a CNA associated with adenocarcinoma and poor prognosis, was observed in >50% of the tumor samples and demonstrated a significant linear correlation for gene dosage and gene expression for two potential tumor suppressor genes, MTUS1 (8p22) and PPP2CB (8p12). The results from our integration analysis illustrate the complex relationship between genomic alterations and gene expression in colon cancer. PMID:23341073

Suppression of HPV E6 and E7 expression by BAF53 depletion in cervical cancer cells

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

Lee, Kiwon; Lee, Ah-Young; Kwon, Yunhee Kim

Highlights: {yields} Integration of HPV into host genome critical for activation of E6 and E7 oncogenes. {yields} BAF53 is essential for higher-order chromatin structure. {yields} BAF53 knockdown suppresses E6 and E7 from HPV integrants, but not from episomal HPVs. {yields} BAF53 knockdown decreases H3K9Ac and H4K12Ac on P105 promoter of integrated HPV 18. {yields} BAF53 knockdown restores the p53-dependent signaling pathway in HeLa and SiHa cells. -- Abstract: Deregulation of the expression of human papillomavirus (HPV) oncogenes E6 and E7 plays a pivotal role in cervical carcinogenesis because the E6 and E7 proteins neutralize p53 and Rb tumor suppressor pathways,more » respectively. In approximately 90% of all cervical carcinomas, HPVs are found to be integrated into the host genome. Following integration, the core-enhancer element and P105 promoter that control expression of E6 and E7 adopt a chromatin structure that is different from that of episomal HPV, and this has been proposed to contribute to activation of E6 and E7 expression. However, the molecular basis underlying this chromatin structural change remains unknown. Previously, BAF53 has been shown to be essential for the integrity of higher-order chromatin structure and interchromosomal interactions. Here, we examined whether BAF53 is required for activated expression of E6 and E7 genes. We found that BAF53 knockdown led to suppression of expression of E6 and E7 genes from HPV integrants in cervical carcinoma cell lines HeLa and SiHa. Conversely, expression of transiently transfected HPV18-LCR-Luciferase was not suppressed by BAF53 knockdown. The level of the active histone marks H3K9Ac and H4K12Ac on the P105 promoter of integrated HPV 18 was decreased in BAF53 knockdown cells. BAF53 knockdown restored the p53-dependent signaling pathway in HeLa and SiHa cells. These results suggest that activated expression of the E6 and E7 genes of integrated HPV is dependent on BAF53-dependent higher-order chromatin structure or nuclear motor activity.« less

Integration of adeno-associated virus vectors in CD34+ human hematopoietic progenitor cells after transduction.

PubMed

Fisher-Adams, G; Wong, K K; Podsakoff, G; Forman, S J; Chatterjee, S

1996-07-15

Gene transfer vectors based on adeno-associated virus (AAV) appear promising because of their high transduction frequencies regardless of cell cycle status and ability to integrate into chromosomal DNA. We tested AAV-mediated gene transfer into a panel of human bone marrow or umbilical cord-derived CD34+ hematopoietic progenitor cells, using vectors encoding several transgenes under the control of viral and cellular promoters. Gene transfer was evaluated by (1) chromosomal integration of vector sequences and (2) analysis of transgene expression. Southern hybridization and fluorescence in situ hybridization analysis of transduced CD34 genomic DNA showed the presence of integrated vector sequences in chromosomal DNA in a portion of transduced cells and showed that integrated vector sequences were replicated along with cellular DNA during mitosis. Transgene expression in transduced CD34 cells in suspension cultures and in myeloid colonies differentiating in vitro from transduced CD34 cells approximated that predicted by the multiplicity of transduction. This was true in CD34 cells from different donors, regardless of the transgene or selective pressure. Comparisons of CD34 cell transduction either before or after cytokine stimulation showed similar gene transfer frequencies. Our findings suggest that AAV transduction of CD34+ hematopoietic progenitor cells is efficient, can lead to stable integration in a population of transduced cells, and may therefore provide the basis for safe and efficient ex vivo gene therapy of the hematopoietic system.

Characterizing mutation-expression network relationships in multiple cancers.

PubMed

Ghazanfar, Shila; Yang, Jean Yee Hwa

2016-08-01

Data made available through large cancer consortia like The Cancer Genome Atlas make for a rich source of information to be studied across and between cancers. In recent years, network approaches have been applied to such data in uncovering the complex interrelationships between mutational and expression profiles, but lack direct testing for expression changes via mutation. In this pan-cancer study we analyze mutation and gene expression information in an integrative manner by considering the networks generated by testing for differences in expression in direct association with specific mutations. We relate our findings among the 19 cancers examined to identify commonalities and differences as well as their characteristics. Using somatic mutation and gene expression information across 19 cancers, we generated mutation-expression networks per cancer. On evaluation we found that our generated networks were significantly enriched for known cancer-related genes, such as skin cutaneous melanoma (p<0.01 using Network of Cancer Genes 4.0). Our framework identified that while different cancers contained commonly mutated genes, there was little concordance between associated gene expression changes among cancers. Comparison between cancers showed a greater overlap of network nodes for cancers with higher overall non-silent mutation load, compared to those with a lower overall non-silent mutation load. This study offers a framework that explores network information through co-analysis of somatic mutations and gene expression profiles. Our pan-cancer application of this approach suggests that while mutations are frequently common among cancer types, the impact they have on the surrounding networks via gene expression changes varies. Despite this finding, there are some cancers for which mutation-associated network behaviour appears to be similar: suggesting a potential framework for uncovering related cancers for which similar therapeutic strategies may be applicable. Our framework for understanding relationships among cancers has been integrated into an interactive R Shiny application, PAn Cancer Mutation Expression Networks (PACMEN), containing dynamic and static network visualization of the mutation-expression networks. PACMEN also features tools for further examination of network topology characteristics among cancers. Copyright © 2016 Elsevier Ltd. All rights reserved.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer.

PubMed

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC. Copyright © 2013 Elsevier Inc. All rights reserved.

Integration of transcriptomic and cytoarchitectonic data implicates a role for MAOA and TAC1 in the limbic-cortical network.

PubMed

Bludau, Sebastian; Mühleisen, Thomas W; Eickhoff, Simon B; Hawrylycz, Michael J; Cichon, Sven; Amunts, Katrin

2018-06-01

Decoding the chain from genes to cognition requires detailed insights how areas with specific gene activities and microanatomical architectures contribute to brain function and dysfunction. The Allen Human Brain Atlas contains regional gene expression data, while the JuBrain Atlas offers three-dimensional cytoarchitectonic maps reflecting interindividual variability. To date, an integrated framework that combines the analytical benefits of both scientific platforms towards a multi-level brain atlas of adult humans was not available. We have, therefore, developed JuGEx, a new method for integrating tissue transcriptome and cytoarchitectonic segregation. We investigated differential gene expression in two JuBrain areas of the frontal pole that we have structurally and functionally characterized in previous studies. Our results show a significant upregulation of MAOA and TAC1 in the medial area frontopolaris which is a node in the limbic-cortical network and known to be susceptible for gray matter loss and behavioral dysfunction in patients with depression. The MAOA gene encodes an enzyme which is involved in the catabolism of dopamine, norepinephrine, serotonin, and other monoaminergic neurotransmitters. The TAC1 locus generates hormones that play a role in neuron excitations and behavioral responses. Overall, JuGEx provides a new tool for the scientific community that empowers research from basic, cognitive and clinical neuroscience in brain regions and disease models with regard to gene expression.

EMAGE mouse embryo spatial gene expression database: 2010 update

PubMed Central

Richardson, Lorna; Venkataraman, Shanmugasundaram; Stevenson, Peter; Yang, Yiya; Burton, Nicholas; Rao, Jianguo; Fisher, Malcolm; Baldock, Richard A.; Davidson, Duncan R.; Christiansen, Jeffrey H.

2010-01-01

EMAGE (http://www.emouseatlas.org/emage) is a freely available online database of in situ gene expression patterns in the developing mouse embryo. Gene expression domains from raw images are extracted and integrated spatially into a set of standard 3D virtual mouse embryos at different stages of development, which allows data interrogation by spatial methods. An anatomy ontology is also used to describe sites of expression, which allows data to be queried using text-based methods. Here, we describe recent enhancements to EMAGE including: the release of a completely re-designed website, which offers integration of many different search functions in HTML web pages, improved user feedback and the ability to find similar expression patterns at the click of a button; back-end refactoring from an object oriented to relational architecture, allowing associated SQL access; and the provision of further access by standard formatted URLs and a Java API. We have also increased data coverage by sourcing from a greater selection of journals and developed automated methods for spatial data annotation that are being applied to spatially incorporate the genome-wide (∼19 000 gene) ‘EURExpress’ dataset into EMAGE. PMID:19767607

Protein-DNA binding dynamics predict transcriptional response to nutrients in archaea.

PubMed

Todor, Horia; Sharma, Kriti; Pittman, Adrianne M C; Schmid, Amy K

2013-10-01

Organisms across all three domains of life use gene regulatory networks (GRNs) to integrate varied stimuli into coherent transcriptional responses to environmental pressures. However, inferring GRN topology and regulatory causality remains a central challenge in systems biology. Previous work characterized TrmB as a global metabolic transcription factor in archaeal extremophiles. However, it remains unclear how TrmB dynamically regulates its ∼100 metabolic enzyme-coding gene targets. Using a dynamic perturbation approach, we elucidate the topology of the TrmB metabolic GRN in the model archaeon Halobacterium salinarum. Clustering of dynamic gene expression patterns reveals that TrmB functions alone to regulate central metabolic enzyme-coding genes but cooperates with various regulators to control peripheral metabolic pathways. Using a dynamical model, we predict gene expression patterns for some TrmB-dependent promoters and infer secondary regulators for others. Our data suggest feed-forward gene regulatory topology for cobalamin biosynthesis. In contrast, purine biosynthesis appears to require TrmB-independent regulators. We conclude that TrmB is an important component for mediating metabolic modularity, integrating nutrient status and regulating gene expression dynamics alone and in concert with secondary regulators.

Integrated automation for continuous high-throughput synthetic chromosome assembly and transformation to identify improved yeast strains for industrial production of peptide sweetener brazzein

USDA-ARS?s Scientific Manuscript database

Production and recycling of recombinant sweetener peptides in industrial biorefineries involves the evaluation of large numbers of genes and proteins. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly synthesize, clone, and express heterologous gene ope...

ICE Afe 1, an actively excising genetic element from the biomining bacterium Acidithiobacillus ferrooxidans.

PubMed

Bustamante, Paula; Covarrubias, Paulo C; Levicán, Gloria; Katz, Assaf; Tapia, Pablo; Holmes, David; Quatrini, Raquel; Orellana, Omar

2012-01-01

Integrative conjugative elements (ICEs) are self-transferred mobile genetic elements that contribute to horizontal gene transfer. An ICE (ICEAfe1) was identified in the genome of Acidithiobacillus ferrooxidans ATCC 23270. Excision of the element and expression of relevant genes under normal and DNA-damaging growth conditions was analyzed. Bioinformatic tools and DNA amplification methods were used to identify and to assess the excision and expression of genes related to the mobility of the element. Both basal and mitomycin C-inducible excision as well as expression and induction of the genes for integration/excision are demonstrated, suggesting that ICEAfe1 is an actively excising SOS-regulated mobile genetic element. The presence of a complete set of genes encoding self-transfer functions that are induced in response to DNA damage caused by mitomycin C additionally suggests that this element is capable of conjugative transfer to suitable recipient strains. Transfer of ICEAfe1 may provide selective advantages to other acidophiles in this ecological niche through dissemination of gene clusters expressing transfer RNAs, CRISPRs, and exopolysaccharide biosynthesis enzymes, probably by modification of translation efficiency, resistance to bacteriophage infection and biofilm formation, respectively. These data open novel avenues of research on conjugative transformation of biotechnologically relevant microorganisms recalcitrant to genetic manipulation. Copyright © 2013 S. Karger AG, Basel.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

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

Pandi, Narayanan Sathiya, E-mail: sathiyapandi@gmail.com; Suganya, Sivagurunathan; Rajendran, Suriliyandi

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However,more » the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC.« less

An integrated systems genetics screen reveals the transcriptional structure of inherited predisposition to metastatic disease

PubMed Central

Faraji, Farhoud; Hu, Ying; Wu, Gang; Goldberger, Natalie E.; Walker, Renard C.; Zhang, Jinghui; Hunter, Kent W.

2014-01-01

Metastasis is the result of stochastic genomic and epigenetic events leading to gene expression profiles that drive tumor dissemination. Here we exploit the principle that metastatic propensity is modified by the genetic background to generate prognostic gene expression signatures that illuminate regulators of metastasis. We also identify multiple microRNAs whose germline variation is causally linked to tumor progression and metastasis. We employ network analysis of global gene expression profiles in tumors derived from a panel of recombinant inbred mice to identify a network of co-expressed genes centered on Cnot2 that predicts metastasis-free survival. Modulating Cnot2 expression changes tumor cell metastatic potential in vivo, supporting a functional role for Cnot2 in metastasis. Small RNA sequencing of the same tumor set revealed a negative correlation between expression of the Mir216/217 cluster and tumor progression. Expression quantitative trait locus analysis (eQTL) identified cis-eQTLs at the Mir216/217 locus, indicating that differences in expression may be inherited. Ectopic expression of Mir216/217 in tumor cells suppressed metastasis in vivo. Finally, small RNA sequencing and mRNA expression profiling data were integrated to reveal that miR-3470a/b target a high proportion of network transcripts. In vivo analysis of Mir3470a/b demonstrated that both promote metastasis. Moreover, Mir3470b is a likely regulator of the Cnot2 network as its overexpression down-regulated expression of network hub genes and enhanced metastasis in vivo, phenocopying Cnot2 knockdown. The resulting data from this strategy identify Cnot2 as a novel regulator of metastasis and demonstrate the power of our systems-level approach in identifying modifiers of metastasis. PMID:24322557

An integrative approach to inferring biologically meaningful gene modules.

PubMed

Cho, Ji-Hoon; Wang, Kai; Galas, David J

2011-07-26

The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

Gene therapy using retrovirus vectors: vector development and biosafety at clinical trials.

PubMed

Doi, Knayo; Takeuchi, Yasuhiro

2015-01-01

Retrovirus vectors (gammaretroviral and lentiviral vectors) have been considered as promising tools to transfer therapeutic genes into patient cells because they can permanently integrate into host cellular genome. To treat monogenic, inherited diseases, retroviral vectors have been used to add correct genes into patient cells. Conventional gammaretroviral vectors achieved successful results in clinical trials: treated patients had therapeutic gene expression in target cells and had improved symptoms of diseases. However, serious side-effects of leukemia occurred, caused by retroviral insertional mutagenesis (IM). These incidences stressed the importance of monitoring vector integration sites in patient cells as well as of re-consideration on safer vectors. More recently lentiviral vectors which can deliver genes into non-dividing cells started to be used in clinical trials including neurological disorders, showing their efficacy. Vector integration site analysis revealed that lentiviruses integrate less likely to near promoter regions of oncogenes than gammaretroviruses and no adverse events have been reported in lentiviral vector-mediated gene therapy clinical trials. Therefore lentiviral vectors have promises to be applied to a wide range of common diseases in near future. For example, T cells from cancer patients were transduced to express chimeric T cell receptors recognizing their tumour cells enhancing patients' anti-cancer immunity.

High-resolution gene expression data from blastoderm embryos of the scuttle fly Megaselia abdita

PubMed Central

Wotton, Karl R; Jiménez-Guri, Eva; Crombach, Anton; Cicin-Sain, Damjan; Jaeger, Johannes

2015-01-01

Gap genes are involved in segment determination during early development in dipteran insects (flies, midges, and mosquitoes). We carried out a systematic quantitative comparative analysis of the gap gene network across different dipteran species. Our work provides mechanistic insights into the evolution of this pattern-forming network. As a central component of our project, we created a high-resolution quantitative spatio-temporal data set of gap and maternal co-ordinate gene expression in the blastoderm embryo of the non-drosophilid scuttle fly, Megaselia abdita. Our data include expression patterns in both wild-type and RNAi-treated embryos. The data—covering 10 genes, 10 time points, and over 1,000 individual embryos—consist of original embryo images, quantified expression profiles, extracted positions of expression boundaries, and integrated expression patterns, plus metadata and intermediate processing steps. These data provide a valuable resource for researchers interested in the comparative study of gene regulatory networks and pattern formation, an essential step towards a more quantitative and mechanistic understanding of developmental evolution. PMID:25977812

FISH-Based Analysis of Clonally Derived CHO Cell Populations Reveals High Probability for Transgene Integration in a Terminal Region of Chromosome 1 (1q13).

PubMed

Li, Shengwei; Gao, Xiaoping; Peng, Rui; Zhang, Sheng; Fu, Wei; Zou, Fangdong

A basic goal in the development of recombinant proteins is the generation of cell lines that express the desired protein stably over many generations. Here, we constructed engineered Chinese hamster ovary cell lines (CHO-S) with a pCHO-hVR1 vector that carried an extracellular domain of a VEGF receptor (VR) fusion gene. Forty-five clones with high hVR1 expression were selected for karyotype analysis. Using fluorescence in situ hybridization (FISH) and G-banding, we found that pCHO-hVR1 was integrated into three chromosomes, including chromosomes 1, Z3 and Z4. Four clones were selected to evaluate their productivity under non-fed, non-optimized shake flask conditions. The results showed that clones 1 and 2 with integration sites on chromosome 1 revealed high levels of hVR1 products (shake flask of approximately 800 mg/L), whereas clones 3 and 4 with integration sites on chromosomes Z3 or Z4 had lower levels of hVR1 products. Furthermore, clones 1 and 2 maintained their productivity stabilities over a continuous period of 80 generations, and clones 3 and 4 showed significant declines in their productivities in the presence of selection pressure. Finally, pCHO-hVR1 localized to the same region at chromosome 1q13, the telomere region of normal chromosome 1. In this study, these results demonstrate that the integration of exogenous hVR1 gene on chromosome 1, band q13, may create a high protein-producing CHO-S cell line, suggesting that chromosome 1q13 may contain a useful target site for the high expression of exogenous protein. This study shows that the integration into the target site of chromosome 1q13 may avoid the problems of random integration that cause gene silencing or also overcome position effects, facilitating exogenous gene expression in CHO-S cells.

MMP-9 gene silencing by a Quantum Dot-siRNA nanoplex delivery to maintain the integrity of the blood brain barrier

PubMed Central

Bonoiu, Adela; Mahajan, Supriya D.; Ye, Ling; Kumar, Rajiv; Ding, Hong; Yong, Ken-Tye; Roy, Indrajit; Aalinkeel, Ravikumar; Nair, Bindukumar; Reynolds, Jessica L; Sykes, Donald E; Imperiale, Marco A; Bergey, Earl J.; Schwartz, Stanley A.; Prasad, Paras N.

2009-01-01

The matrix-degrading metalloproteinases (MMPs), particularly MMP-9, are involved in the neuroinflammation processes leading to disrupting of the blood brain barrier (BBB), thereby exacerbating neurological diseases such as HIV-1 AIDS dementia and cerebral ischemia. Nanoparticles have been proposed to act as non-viral gene delivery vectors and have great potential for therapeutic applications in several disease states. In this study, we evaluated the specificity and efficiency of quantum dot (QD) complexed with MMP-9-siRNA (nanoplex) in downregulating the expression of MMP-9 gene in brain microvascular endothelial cells (BMVEC) that constitute the BBB. We hypothesize that silencing MMP-9 gene expression in BMVECs and other cells such as leukocytes may help prevent breakdown of the BBB and inhibit subsequent invasion of the central nervous system (CNS) by infected and inflammatory cells. Our results show that silencing of MMP-9 gene expression resulted in the upregulation of extracellular matrix (ECM) proteins like collagen I, IV, V and a decrease in endothelial permeability, as reflected by reduction of transendothelial resistance across the BBB in a well validated in-vitro BBB model. MMP-9 gene silencing also resulted in an increase in expression of the gene tissue inhibitor of metalloproteinase-1 (TIMP-1). This indicates the importance of a balance between the levels of MMP-9 and its natural inhibitor TIMP-1 in maintaining the basement membrane integrity. These studies promise the application of a novel nanoparticle based siRNA delivery system in modulating the MMP-9 activity in BMVECs and other MMP-9 producing cells. This will prevent neuroinflammation and maintain the integrity of the BBB. PMID:19477169

RNA-Seq Reveals Extensive Transcriptional Response to Heat Stress in the Stony Coral Galaxea fascicularis

PubMed Central

Hou, Jing; Xu, Tao; Su, Dingjia; Wu, Ying; Cheng, Li; Wang, Jun; Zhou, Zhi; Wang, Yan

2018-01-01

Galaxea fascicularis, a stony coral belonging to family Oculinidae, is widely distributed in Red Sea, the Gulf of Aden and large areas of the Indo-Pacific oceans. So far there is a lack of gene expression knowledge concerning this massive coral. In the present study, G. fascicularis was subjected to heat stress at 32.0 ± 0.5°C in the lab, we found that the density of symbiotic zooxanthellae decreased significantly; meanwhile apparent bleaching and tissue lysing were observed at 10 h and 18 h after heat stress. The transcriptome responses were investigated in the stony coral G. fascicularis during heat bleaching using RNA-seq. A total of 42,028 coral genes were assembled from over 439 million reads. Gene expressions were compared at 10 and 18 h after heat stress. The significantly upregulated genes found in the Control_10h vs. Heat_10h comparison, presented mainly in GO terms related with DNA integration and unfolded protein response; and for the Control_18h vs. Heat_18h comparison, the GO terms include DNA integration. In addition, comparison between groups of Control_10h vs. Heat_10h and Control_18h vs. Heat_18h revealed that 125 genes were significantly upregulated in common between the two groups, whereas 21 genes were significantly downregulated in common, all these differentially expressed genes were found to be involved in stress response, DNA integration and unfolded protein response. Taken together, our results suggest that high temperature could activate the stress response at the early stage, and subsequently induce the bleaching and lysing through DNA integration and unfolded protein response, which are able to disrupt the balance of coral-zooxanthella symbiosis in the stony coral G. fascicularis. PMID:29487614

Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

PubMed

Liu, Tianming; Lu, Jianfeng; Wang, Ye; Campbell, William A; Huang, Ling; Zhu, Jinmin; Xia, Weiming; Wong, Stephen T C

2006-06-15

An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.

Combined SOM-portrayal of gene expression and DNA methylation landscapes disentangles modes of epigenetic regulation in glioblastoma.

PubMed

Hopp, Lydia; Löffler-Wirth, Henry; Galle, Jörg; Binder, Hans

2018-06-11

We present here a novel method that enables unraveling the interplay between gene expression and DNA methylation in complex diseases such as cancer. The method is based on self-organizing maps and allows for analysis of data landscapes from 'governed by methylation' to 'governed by expression'. We identified regulatory modules of coexpressed and comethylated genes in high-grade gliomas: two modes are governed by genes hypermethylated and underexpressed in IDH-mutated cases, while two other modes reflect immune and stromal signatures in the classical and mesenchymal subtypes. A fifth mode with proneural characteristics comprises genes of repressed and poised chromatin states active in healthy brain. Two additional modes enrich genes either in active or repressed chromatin states. The method disentangles the interplay between gene expression and methylation. It has the potential to integrate also mutation and copy number data and to apply to large sample cohorts.

Molecular imaging of the biological effects of quercetin and quercetin-rich foods.

PubMed

Moskaug, Jan Øivind; Carlsen, Harald; Myhrstad, Mari; Blomhoff, Rune

2004-04-01

The human diet contains several thousands of organic plant molecules (i.e. phytochemicals), many of which have significant bioactivities. The specific physiological effects of these compounds are impossible to predict from in vitro studies using cell cultures and cell-free model systems. Nutrigenomics, which may be defined as the application of genomic tools to study the integrated effects of nutrients on gene regulation, however, holds great promise in increasing the understanding of how nutrients affect molecular events in an organism. Quercetin, a phytochemical belonging to the flavonoids, has antioxidant activities, inhibit protein kinases, inhibit DNA topoisomerases and regulate gene expression. The aim of the present review is to describe some of the many effects of quercetin, and how molecular imaging using transgenic reporter mice may serve as a tool to study the integrated influence of quercetin and other dietary phytochemicals on gene expression in vivo. We are using the bioluminescence emitted from firefly luciferase as the reporter since light originating from the inside of a cell or organism can be detected externally in an intact living organism. Molecular imaging using reporter models is therefore a unique technology to study the integrated effects of environmental insults and dietary substances on the influence of gene expression in disease development. We utilize these in vivo models to elucidate the role of various flavonoids, such as quercetin, for modulating gene expression related to oxidative stress and the antioxidant defence system.

Effect of Plasmid Design and Type of Integration Event on Recombinant Protein Expression in Pichia pastoris.

PubMed

Vogl, Thomas; Gebbie, Leigh; Palfreyman, Robin W; Speight, Robert

2018-03-15

Pichia pastoris (syn. Komagataella phaffii ) is one of the most common eukaryotic expression systems for heterologous protein production. Expression cassettes are typically integrated in the genome to obtain stable expression strains. In contrast to Saccharomyces cerevisiae , where short overhangs are sufficient to target highly specific integration, long overhangs are more efficient in P. pastoris and ectopic integration of foreign DNA can occur. Here, we aimed to elucidate the influence of ectopic integration by high-throughput screening of >700 transformants and whole-genome sequencing of 27 transformants. Different vector designs and linearization approaches were used to mimic the most common integration events targeted in P. pastoris Fluorescence of an enhanced green fluorescent protein (eGFP) reporter protein was highly uniform among transformants when the expression cassettes were correctly integrated in the targeted locus. Surprisingly, most nonspecifically integrated transformants showed highly uniform expression that was comparable to specific integration, suggesting that nonspecific integration does not necessarily influence expression. However, a few clones (<10%) harboring ectopically integrated cassettes showed a greater variation spanning a 25-fold range, surpassing specifically integrated reference strains up to 6-fold. High-expression strains showed a correlation between increased gene copy numbers and high reporter protein fluorescence levels. Our results suggest that for comparing expression levels between strains, the integration locus can be neglected as long as a sufficient numbers of transformed strains are compared. For expression optimization of highly expressible proteins, increasing copy number appears to be the dominant positive influence rather than the integration locus, genomic rearrangements, deletions, or single-nucleotide polymorphisms (SNPs). IMPORTANCE Yeasts are commonly used as biotechnological production hosts for proteins and metabolites. In the yeast Saccharomyces cerevisiae , expression cassettes carrying foreign genes integrate highly specifically at the targeted sites in the genome. In contrast, cassettes often integrate at random genomic positions in nonconventional yeasts, such as Pichia pastoris (syn. Komagataella phaffii ). Hence, cells from the same transformation event often behave differently, with significant clonal variation necessitating the screening of large numbers of strains. The importance of this study is that we systematically investigated the influence of integration events in more than 700 strains. Our findings provide novel insight into clonal variation in P. pastoris and, thus, how to avoid pitfalls and obtain reliable results. The underlying mechanisms may also play a role in other yeasts and hence could be generally relevant for recombinant yeast protein production strains. Copyright © 2018 American Society for Microbiology.

Selection for avian leukosis virus integration sites determines the clonal progression of B-cell lymphomas

PubMed Central

Malhotra, Sanandan; Justice, James; Morgan, Robin

2017-01-01

Avian leukosis virus (ALV) is a simple retrovirus that causes a wide range of tumors in chickens, the most common of which are B-cell lymphomas. The viral genome integrates into the host genome and uses its strong promoter and enhancer sequences to alter the expression of nearby genes, frequently inducing tumors. In this study, we compare the preferences for ALV integration sites in cultured cells and in tumors, by analysis of over 87,000 unique integration sites. In tissue culture we observed integration was relatively random with slight preferences for genes, transcription start sites and CpG islands. We also observed a preference for integrations in or near expressed and spliced genes. The integration pattern in cultured cells changed over the course of selection for oncogenic characteristics in tumors. In comparison to tissue culture, ALV integrations are more highly selected for proximity to transcription start sites in tumors. There is also a significant selection of ALV integrations away from CpG islands in the highly clonally expanded cells in tumors. Additionally, we utilized a high throughput method to quantify the magnitude of clonality in different stages of tumorigenesis. An ALV-induced tumor carries between 700 and 3000 unique integrations, with an average of 2.3 to 4 copies of proviral DNA per infected cell. We observed increasing tumor clonality during progression of B-cell lymphomas and identified gene players (especially TERT and MYB) and biological processes involved in tumor progression. PMID:29099869

Integration of multiple stimuli-sensing systems to regulate HrpS and type III secretion system in Erwinia amylovora.

PubMed

Lee, Jae Hoon; Zhao, Youfu

2018-02-01

The bacterial enhancer binding protein (bEBP) HrpS is essential for Erwinia amylovora virulence by activating the type III secretion system (T3SS). However, how the hrpS gene is regulated remains poorly understood in E. amylovora. In this study, 5' rapid amplification of cDNA ends and promoter deletion analyses showed that the hrpS gene contains two promoters driven by HrpX/HrpY and the Rcs phosphorelay system, respectively. Electrophoretic mobility shift and gene expression assays demonstrated that integration host factor IHF positively regulates hrpS expression through directly binding the hrpX promoter and positively regulating hrpX/hrpY expression. Moreover, hrpX expression was down-regulated in the relA/spoT ((p)ppGpp-deficient) mutant and the dksA mutant, but up-regulated when the wild-type strain was treated with serine hydroxamate, which induced (p)ppGpp-mediated stringent response. Furthermore, the csrA mutant showed significantly reduced transcripts of major hrpS activators, including the hrpX/hrpY, rcsA and rcsB genes, indicating that CsrA is required for full hrpS expression. On the other hand, the csrB mutant exhibited up-regulation of the rcsA and rcsB genes, and hrpS expression was largely diminished in the csrB/rcsB mutant, indicating that the Rcs system is mainly responsible for the increased hrpS expression in the csrB mutant. These findings suggest that E. amylovora recruits multiple stimuli-sensing systems, including HrpX/HrpY, the Rcs phosphorelay system and the Gac-Csr system, to regulate hrpS and T3SS gene expression.

From Saccharomyces cerevisiae to human: The important gene co-expression modules.

PubMed

Liu, Wei; Li, Li; Ye, Hua; Chen, Haiwei; Shen, Weibiao; Zhong, Yuexian; Tian, Tian; He, Huaqin

2017-08-01

Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Yeast has long been a popular model organism for biomedical research. In the current study, a weighted gene co-expression network analysis algorithm was applied to construct a gene co-expression network in Saccharomyces cerevisiae . Seventeen stable gene co-expression modules were detected from 2,814 S. cerevisiae microarray data. Further characterization of these modules with the Database for Annotation, Visualization and Integrated Discovery tool indicated that these modules were associated with certain biological processes, such as heat response, cell cycle, translational regulation, mitochondrion oxidative phosphorylation, amino acid metabolism and autophagy. Hub genes were also screened by intra-modular connectivity. Finally, the module conservation was evaluated in a human disease microarray dataset. Functional modules were identified in budding yeast, some of which are associated with patient survival. The current study provided a paradigm for single cell microorganisms and potentially other organisms.

Reconstruction of an Integrated Genome-Scale Co-Expression Network Reveals Key Modules Involved in Lung Adenocarcinoma

PubMed Central

Hosseini Ashtiani, Saman; Moeini, Ali; Nowzari-Dalini, Abbas; Masoudi-Nejad, Ali

2013-01-01

Our goal of this study was to reconstruct a “genome-scale co-expression network” and find important modules in lung adenocarcinoma so that we could identify the genes involved in lung adenocarcinoma. We integrated gene mutation, GWAS, CGH, array-CGH and SNP array data in order to identify important genes and loci in genome-scale. Afterwards, on the basis of the identified genes a co-expression network was reconstructed from the co-expression data. The reconstructed network was named “genome-scale co-expression network”. As the next step, 23 key modules were disclosed through clustering. In this study a number of genes have been identified for the first time to be implicated in lung adenocarcinoma by analyzing the modules. The genes EGFR, PIK3CA, TAF15, XIAP, VAPB, Appl1, Rab5a, ARF4, CLPTM1L, SP4, ZNF124, LPP, FOXP1, SOX18, MSX2, NFE2L2, SMARCC1, TRA2B, CBX3, PRPF6, ATP6V1C1, MYBBP1A, MACF1, GRM2, TBXA2R, PRKAR2A, PTK2, PGF and MYO10 are among the genes that belong to modules 1 and 22. All these genes, being implicated in at least one of the phenomena, namely cell survival, proliferation and metastasis, have an over-expression pattern similar to that of EGFR. In few modules, the genes such as CCNA2 (Cyclin A2), CCNB2 (Cyclin B2), CDK1, CDK5, CDC27, CDCA5, CDCA8, ASPM, BUB1, KIF15, KIF2C, NEK2, NUSAP1, PRC1, SMC4, SYCE2, TFDP1, CDC42 and ARHGEF9 are present that play a crucial role in cell cycle progression. In addition to the mentioned genes, there are some other genes (i.e. DLGAP5, BIRC5, PSMD2, Src, TTK, SENP2, PSMD2, DOK2, FUS and etc.) in the modules. PMID:23874428

Reconstruction of an integrated genome-scale co-expression network reveals key modules involved in lung adenocarcinoma.

PubMed

Bidkhori, Gholamreza; Narimani, Zahra; Hosseini Ashtiani, Saman; Moeini, Ali; Nowzari-Dalini, Abbas; Masoudi-Nejad, Ali

2013-01-01

Our goal of this study was to reconstruct a "genome-scale co-expression network" and find important modules in lung adenocarcinoma so that we could identify the genes involved in lung adenocarcinoma. We integrated gene mutation, GWAS, CGH, array-CGH and SNP array data in order to identify important genes and loci in genome-scale. Afterwards, on the basis of the identified genes a co-expression network was reconstructed from the co-expression data. The reconstructed network was named "genome-scale co-expression network". As the next step, 23 key modules were disclosed through clustering. In this study a number of genes have been identified for the first time to be implicated in lung adenocarcinoma by analyzing the modules. The genes EGFR, PIK3CA, TAF15, XIAP, VAPB, Appl1, Rab5a, ARF4, CLPTM1L, SP4, ZNF124, LPP, FOXP1, SOX18, MSX2, NFE2L2, SMARCC1, TRA2B, CBX3, PRPF6, ATP6V1C1, MYBBP1A, MACF1, GRM2, TBXA2R, PRKAR2A, PTK2, PGF and MYO10 are among the genes that belong to modules 1 and 22. All these genes, being implicated in at least one of the phenomena, namely cell survival, proliferation and metastasis, have an over-expression pattern similar to that of EGFR. In few modules, the genes such as CCNA2 (Cyclin A2), CCNB2 (Cyclin B2), CDK1, CDK5, CDC27, CDCA5, CDCA8, ASPM, BUB1, KIF15, KIF2C, NEK2, NUSAP1, PRC1, SMC4, SYCE2, TFDP1, CDC42 and ARHGEF9 are present that play a crucial role in cell cycle progression. In addition to the mentioned genes, there are some other genes (i.e. DLGAP5, BIRC5, PSMD2, Src, TTK, SENP2, PSMD2, DOK2, FUS and etc.) in the modules.

Remodeling a tissue: subtraction adds insight.

PubMed

Axelrod, Jeffrey D

2012-11-27

Sculpting a body plan requires both patterning of gene expression and translating that pattern into morphogenesis. Developmental biologists have made remarkable strides in understanding gene expression patterning, but despite a long history of fascination with the mechanics of morphogenesis, knowledge of how patterned gene expression drives the emergence of even simple shapes and forms has grown at a slower pace. The successful merging of approaches from cell biology, developmental biology, imaging, engineering, and mathematical and computational sciences is now accelerating progress toward a fuller and better integrated understanding of the forces shaping morphogenesis.

Integrative sparse principal component analysis of gene expression data.

PubMed

Liu, Mengque; Fan, Xinyan; Fang, Kuangnan; Zhang, Qingzhao; Ma, Shuangge

2017-12-01

In the analysis of gene expression data, dimension reduction techniques have been extensively adopted. The most popular one is perhaps the PCA (principal component analysis). To generate more reliable and more interpretable results, the SPCA (sparse PCA) technique has been developed. With the "small sample size, high dimensionality" characteristic of gene expression data, the analysis results generated from a single dataset are often unsatisfactory. Under contexts other than dimension reduction, integrative analysis techniques, which jointly analyze the raw data of multiple independent datasets, have been developed and shown to outperform "classic" meta-analysis and other multidatasets techniques and single-dataset analysis. In this study, we conduct integrative analysis by developing the iSPCA (integrative SPCA) method. iSPCA achieves the selection and estimation of sparse loadings using a group penalty. To take advantage of the similarity across datasets and generate more accurate results, we further impose contrasted penalties. Different penalties are proposed to accommodate different data conditions. Extensive simulations show that iSPCA outperforms the alternatives under a wide spectrum of settings. The analysis of breast cancer and pancreatic cancer data further shows iSPCA's satisfactory performance. © 2017 WILEY PERIODICALS, INC.

Understanding Transcription Factor Regulation by Integrating Gene Expression and DNase I Hypersensitive Sites.

PubMed

Wang, Guohua; Wang, Fang; Huang, Qian; Li, Yu; Liu, Yunlong; Wang, Yadong

2015-01-01

Transcription factors are proteins that bind to DNA sequences to regulate gene transcription. The transcription factor binding sites are short DNA sequences (5-20 bp long) specifically bound by one or more transcription factors. The identification of transcription factor binding sites and prediction of their function continue to be challenging problems in computational biology. In this study, by integrating the DNase I hypersensitive sites with known position weight matrices in the TRANSFAC database, the transcription factor binding sites in gene regulatory region are identified. Based on the global gene expression patterns in cervical cancer HeLaS3 cell and HelaS3-ifnα4h cell (interferon treatment on HeLaS3 cell for 4 hours), we present a model-based computational approach to predict a set of transcription factors that potentially cause such differential gene expression. Significantly, 6 out 10 predicted functional factors, including IRF, IRF-2, IRF-9, IRF-1 and IRF-3, ICSBP, belong to interferon regulatory factor family and upregulate the gene expression levels responding to the interferon treatment. Another factor, ISGF-3, is also a transcriptional activator induced by interferon alpha. Using the different transcription factor binding sites selected criteria, the prediction result of our model is consistent. Our model demonstrated the potential to computationally identify the functional transcription factors in gene regulation.

Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis

PubMed Central

Yang, Fang; Wang, Yumei

2018-01-01

Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis. PMID:29805480

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

DOE PAGES

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.; ...

2015-03-27

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termedmore » as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.« less

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

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

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termedmore » as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.« less

A network-based, integrative study to identify core biological pathways that drive breast cancer clinical subtypes

PubMed Central

Dutta, B; Pusztai, L; Qi, Y; André, F; Lazar, V; Bianchini, G; Ueno, N; Agarwal, R; Wang, B; Shiang, C Y; Hortobagyi, G N; Mills, G B; Symmans, W F; Balázsi, G

2012-01-01

Background: The rapid collection of diverse genome-scale data raises the urgent need to integrate and utilise these resources for biological discovery or biomedical applications. For example, diverse transcriptomic and gene copy number variation data are currently collected for various cancers, but relatively few current methods are capable to utilise the emerging information. Methods: We developed and tested a data-integration method to identify gene networks that drive the biology of breast cancer clinical subtypes. The method simultaneously overlays gene expression and gene copy number data on protein–protein interaction, transcriptional-regulatory and signalling networks by identifying coincident genomic and transcriptional disturbances in local network neighborhoods. Results: We identified distinct driver-networks for each of the three common clinical breast cancer subtypes: oestrogen receptor (ER)+, human epidermal growth factor receptor 2 (HER2)+, and triple receptor-negative breast cancers (TNBC) from patient and cell line data sets. Driver-networks inferred from independent datasets were significantly reproducible. We also confirmed the functional relevance of a subset of randomly selected driver-network members for TNBC in gene knockdown experiments in vitro. We found that TNBC driver-network members genes have increased functional specificity to TNBC cell lines and higher functional sensitivity compared with genes selected by differential expression alone. Conclusion: Clinical subtype-specific driver-networks identified through data integration are reproducible and functionally important. PMID:22343619

Dynamic genome wide expression profiling of Drosophila head development reveals a novel role of Hunchback in retinal glia cell development and blood-brain barrier integrity

PubMed Central

Torres-Oliva, Montserrat; Schneider, Julia; Wiegleb, Gordon

2018-01-01

Drosophila melanogaster head development represents a valuable process to study the developmental control of various organs, such as the antennae, the dorsal ocelli and the compound eyes from a common precursor, the eye-antennal imaginal disc. While the gene regulatory network underlying compound eye development has been extensively studied, the key transcription factors regulating the formation of other head structures from the same imaginal disc are largely unknown. We obtained the developmental transcriptome of the eye-antennal discs covering late patterning processes at the late 2nd larval instar stage to the onset and progression of differentiation at the end of larval development. We revealed the expression profiles of all genes expressed during eye-antennal disc development and we determined temporally co-expressed genes by hierarchical clustering. Since co-expressed genes may be regulated by common transcriptional regulators, we combined our transcriptome dataset with publicly available ChIP-seq data to identify central transcription factors that co-regulate genes during head development. Besides the identification of already known and well-described transcription factors, we show that the transcription factor Hunchback (Hb) regulates a significant number of genes that are expressed during late differentiation stages. We confirm that hb is expressed in two polyploid subperineurial glia cells (carpet cells) and a thorough functional analysis shows that loss of Hb function results in a loss of carpet cells in the eye-antennal disc. Additionally, we provide for the first time functional data indicating that carpet cells are an integral part of the blood-brain barrier. Eventually, we combined our expression data with a de novo Hb motif search to reveal stage specific putative target genes of which we find a significant number indeed expressed in carpet cells. PMID:29360820

Optimization of Streptomyces bacteriophage phi C31 integrase system to prevent post integrative gene silencing in pulmonary type II cells.

PubMed

Aneja, Manish Kumar; Geiger, Johannes; Imker, Rabea; Uzgun, Senta; Kormann, Michael; Hasenpusch, Guenther; Maucksch, Christof; Rudolph, Carsten

2009-12-31

phi C31 integrase has emerged as a potent tool for achieving long-term gene expression in different tissues. The present study aimed at optimizing elements of phi C31 integrase system for alveolar type II cells. Luciferase and beta-galactosidase activities were measured at different time points post transfection. 5-Aza-2'deoxycytidine (AZA) and trichostatin A (TSA) were used to inhibit DNA methyltransferase and histone deacetylase complex (HDAC) respectively. In A549 cells, expression of the integrase using a CMV promoter resulted in highest integrase activity, whereas in MLE12 cells, both CAG and CMV promoter were equally effective. Effect of polyA site was observed only in A549 cells, where replacement of SV40 polyA by bovine growth hormone (BGH) polyA site resulted in an enhancement of integrase activity. Addition of a C-terminal SV40 nuclear localization signal (NLS) did not result in any significant increase in integrase activity. Long-term expression studies with AZA and TSA, provided evidence for post-integrative gene silencing. In MLE12 cells, both DNA methylases and HDACs played a significant role in silencing, whereas in A549 cells, it could be attributed majorly to HDAC activity. Donor plasmids comprising cellular promoters ubiquitin B (UBB), ubiquitin C (UCC) and elongation factor 1 alpha (EF1 alpha) in an improved backbone prevented post-integrative gene silencing. In contrast to A549 and MLE12 cells, no silencing could be observed in human bronchial epithelial cells, BEAS-2B. Donor plasmid coding for murine erythropoietin under the EF1 alpha promoter when combined with phi C31 integrase resulted in higher long-term erythropoietin expression and subsequently higher hematocrit levels in mice after intravenous delivery to the lungs. These results provide evidence for cell specific post integrative gene silencing with C31 integrase and demonstrate the pivotal role of donor plasmid in long-term expression attained with this system.

Lotus Base: An integrated information portal for the model legume Lotus japonicus

PubMed Central

Mun, Terry; Bachmann, Asger; Gupta, Vikas; Stougaard, Jens; Andersen, Stig U.

2016-01-01

Lotus japonicus is a well-characterized model legume widely used in the study of plant-microbe interactions. However, datasets from various Lotus studies are poorly integrated and lack interoperability. We recognize the need for a comprehensive repository that allows comprehensive and dynamic exploration of Lotus genomic and transcriptomic data. Equally important are user-friendly in-browser tools designed for data visualization and interpretation. Here, we present Lotus Base, which opens to the research community a large, established LORE1 insertion mutant population containing an excess of 120,000 lines, and serves the end-user tightly integrated data from Lotus, such as the reference genome, annotated proteins, and expression profiling data. We report the integration of expression data from the L. japonicus gene expression atlas project, and the development of tools to cluster and export such data, allowing users to construct, visualize, and annotate co-expression gene networks. Lotus Base takes advantage of modern advances in browser technology to deliver powerful data interpretation for biologists. Its modular construction and publicly available application programming interface enable developers to tap into the wealth of integrated Lotus data. Lotus Base is freely accessible at: https://lotus.au.dk. PMID:28008948

Translating standards into practice - one Semantic Web API for Gene Expression.

PubMed

Deus, Helena F; Prud'hommeaux, Eric; Miller, Michael; Zhao, Jun; Malone, James; Adamusiak, Tomasz; McCusker, Jim; Das, Sudeshna; Rocca Serra, Philippe; Fox, Ronan; Marshall, M Scott

2012-08-01

Sharing and describing experimental results unambiguously with sufficient detail to enable replication of results is a fundamental tenet of scientific research. In today's cluttered world of "-omics" sciences, data standards and standardized use of terminologies and ontologies for biomedical informatics play an important role in reporting high-throughput experiment results in formats that can be interpreted by both researchers and analytical tools. Increasing adoption of Semantic Web and Linked Data technologies for the integration of heterogeneous and distributed health care and life sciences (HCLSs) datasets has made the reuse of standards even more pressing; dynamic semantic query federation can be used for integrative bioinformatics when ontologies and identifiers are reused across data instances. We present here a methodology to integrate the results and experimental context of three different representations of microarray-based transcriptomic experiments: the Gene Expression Atlas, the W3C BioRDF task force approach to reporting Provenance of Microarray Experiments, and the HSCI blood genomics project. Our approach does not attempt to improve the expressivity of existing standards for genomics but, instead, to enable integration of existing datasets published from microarray-based transcriptomic experiments. SPARQL Construct is used to create a posteriori mappings of concepts and properties and linking rules that match entities based on query constraints. We discuss how our integrative approach can encourage reuse of the Experimental Factor Ontology (EFO) and the Ontology for Biomedical Investigations (OBIs) for the reporting of experimental context and results of gene expression studies. Copyright © 2012 Elsevier Inc. All rights reserved.

The transcriptional control machinery as well as the cell wall integrity and its regulation are involved in the detoxification of the organic solvent dimethyl sulfoxide in Saccharomyces cerevisiae.

PubMed

Zhang, Lilin; Liu, Ningning; Ma, Xiao; Jiang, Linghuo

2013-03-01

In the present study, we have identified 339 dimethyl sulfoxide (DMSO)-sensitive and nine DMSO-tolerant gene mutations in Saccharomyces cerevisiae through a functional genomics approach. Twelve of these identified DMSO-sensitive mutations are of genes involved in the general control of gene expression mediated by the SWR1 complex and the RNA polymerase II mediator complex, whereas 71 of them are of genes involved in the protein trafficking and vacuolar sorting processes. In addition, twelve of these DMSO-sensitive mutations are of genes involved in the cell wall integrity (CWI) and its regulation. DMSO-tolerant mutations are of genes mainly involved in the metabolism and the gene expression control. Therefore, the transcriptional control machinery, the CWI and its regulation as well as the protein trafficking and sorting process play critical roles in the DMSO detoxification in yeast cells. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

A transcriptional dynamic network during Arabidopsis thaliana pollen development.

PubMed

Wang, Jigang; Qiu, Xiaojie; Li, Yuhua; Deng, Youping; Shi, Tieliu

2011-01-01

To understand transcriptional regulatory networks (TRNs), especially the coordinated dynamic regulation between transcription factors (TFs) and their corresponding target genes during development, computational approaches would represent significant advances in the genome-wide expression analysis. The major challenges for the experiments include monitoring the time-specific TFs' activities and identifying the dynamic regulatory relationships between TFs and their target genes, both of which are currently not yet available at the large scale. However, various methods have been proposed to computationally estimate those activities and regulations. During the past decade, significant progresses have been made towards understanding pollen development at each development stage under the molecular level, yet the regulatory mechanisms that control the dynamic pollen development processes remain largely unknown. Here, we adopt Networks Component Analysis (NCA) to identify TF activities over time course, and infer their regulatory relationships based on the coexpression of TFs and their target genes during pollen development. We carried out meta-analysis by integrating several sets of gene expression data related to Arabidopsis thaliana pollen development (stages range from UNM, BCP, TCP, HP to 0.5 hr pollen tube and 4 hr pollen tube). We constructed a regulatory network, including 19 TFs, 101 target genes and 319 regulatory interactions. The computationally estimated TF activities were well correlated to their coordinated genes' expressions during the development process. We clustered the expression of their target genes in the context of regulatory influences, and inferred new regulatory relationships between those TFs and their target genes, such as transcription factor WRKY34, which was identified that specifically expressed in pollen, and regulated several new target genes. Our finding facilitates the interpretation of the expression patterns with more biological relevancy, since the clusters corresponding to the activity of specific TF or the combination of TFs suggest the coordinated regulation of TFs to their target genes. Through integrating different resources, we constructed a dynamic regulatory network of Arabidopsis thaliana during pollen development with gene coexpression and NCA. The network illustrated the relationships between the TFs' activities and their target genes' expression, as well as the interactions between TFs, which provide new insight into the molecular mechanisms that control the pollen development.

Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies.

PubMed

Yang, Tsun-Po; Beazley, Claude; Montgomery, Stephen B; Dimas, Antigone S; Gutierrez-Arcelus, Maria; Stranger, Barbara E; Deloukas, Panos; Dermitzakis, Emmanouil T

2010-10-01

Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols. http://www.sanger.ac.uk/resources/software/genevar.

Expression analysis of dihydroflavonol 4-reductase genes in Petunia hybrida.

PubMed

Chu, Y X; Chen, H R; Wu, A Z; Cai, R; Pan, J S

2015-05-12

Dihydroflavonol 4-reductase (DFR) genes from Rosa chinensis (Asn type) and Calibrachoa hybrida (Asp type), driven by a CaMV 35S promoter, were integrated into the petunia (Petunia hybrida) cultivar 9702. Exogenous DFR gene expression characteristics were similar to flower-color changes, and effects on anthocyanin concentration were observed in both types of DFR gene transformants. Expression analysis showed that exogenous DFR genes were expressed in all of the tissues, but the expression levels were significantly different. However, both of them exhibited a high expression level in petals that were starting to open. The introgression of DFR genes may significantly change DFR enzyme activity. Anthocyanin ultra-performance liquid chromatography results showed that anthocyanin concentrations changed according to DFR enzyme activity. Therefore, the change in flower color was probably the result of a DFR enzyme change. Pelargonidin 3-O-glucoside was found in two different transgenic petunias, indicating that both CaDFR and RoDFR could catalyze dihydrokaempferol. Our results also suggest that transgenic petunias with DFR gene of Asp type could biosynthesize pelargonidin 3-O-glucoside.

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions.

PubMed

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-11-26

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets.

PubMed

Salem, Saeed; Ozcaglar, Cagri

2014-01-01

Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways.

ICG: a wiki-driven knowledgebase of internal control genes for RT-qPCR normalization.

PubMed

Sang, Jian; Wang, Zhennan; Li, Man; Cao, Jiabao; Niu, Guangyi; Xia, Lin; Zou, Dong; Wang, Fan; Xu, Xingjian; Han, Xiaojiao; Fan, Jinqi; Yang, Ye; Zuo, Wanzhu; Zhang, Yang; Zhao, Wenming; Bao, Yiming; Xiao, Jingfa; Hu, Songnian; Hao, Lili; Zhang, Zhang

2018-01-04

Real-time quantitative PCR (RT-qPCR) has become a widely used method for accurate expression profiling of targeted mRNA and ncRNA. Selection of appropriate internal control genes for RT-qPCR normalization is an elementary prerequisite for reliable expression measurement. Here, we present ICG (http://icg.big.ac.cn), a wiki-driven knowledgebase for community curation of experimentally validated internal control genes as well as their associated experimental conditions. Unlike extant related databases that focus on qPCR primers in model organisms (mainly human and mouse), ICG features harnessing collective intelligence in community integration of internal control genes for a variety of species. Specifically, it integrates a comprehensive collection of more than 750 internal control genes for 73 animals, 115 plants, 12 fungi and 9 bacteria, and incorporates detailed information on recommended application scenarios corresponding to specific experimental conditions, which, collectively, are of great help for researchers to adopt appropriate internal control genes for their own experiments. Taken together, ICG serves as a publicly editable and open-content encyclopaedia of internal control genes and accordingly bears broad utility for reliable RT-qPCR normalization and gene expression characterization in both model and non-model organisms. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Punctual Transcriptional Regulation by the Rice Circadian Clock under Fluctuating Field Conditions[OPEN

PubMed Central

Matsuzaki, Jun; Kawahara, Yoshihiro; Izawa, Takeshi

2015-01-01

Plant circadian clocks that oscillate autonomously with a roughly 24-h period are entrained by fluctuating light and temperature and globally regulate downstream genes in the field. However, it remains unknown how punctual internal time produced by the circadian clock in the field is and how it is affected by environmental fluctuations due to weather or daylength. Using hundreds of samples of field-grown rice (Oryza sativa) leaves, we developed a statistical model for the expression of circadian clock-related genes integrating diurnally entrained circadian clock with phase setting by light, both responses to light and temperature gated by the circadian clock. We show that expression of individual genes was strongly affected by temperature. However, internal time estimated from expression of multiple genes, which may reflect transcriptional regulation of downstream genes, is punctual to 22 min and not affected by weather, daylength, or plant developmental age in the field. We also revealed perturbed progression of internal time under controlled environment or in a mutant of the circadian clock gene GIGANTEA. Thus, we demonstrated that the circadian clock is a regulatory network of multiple genes that retains accurate physical time of day by integrating the perturbations on individual genes under fluctuating environments in the field. PMID:25757473

Design and construction of a first-generation high-throughput integrated robotic molecular biology platform for bioenergy applications.

PubMed

Hughes, Stephen R; Butt, Tauseef R; Bartolett, Scott; Riedmuller, Steven B; Farrelly, Philip

2011-08-01

The molecular biological techniques for plasmid-based assembly and cloning of gene open reading frames are essential for elucidating the function of the proteins encoded by the genes. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly clone and express heterologous gene open reading frames in bacteria and yeast and to screen large numbers of expressed proteins for optimized function are an important technology for improving microbial strains for biofuel production. The process involves the production of full-length complementary DNA libraries as a source of plasmid-based clones to express the desired proteins in active form for determination of their functions. Proteins that were identified by high-throughput screening as having desired characteristics are overexpressed in microbes to enable them to perform functions that will allow more cost-effective and sustainable production of biofuels. Because the plasmid libraries are composed of several thousand unique genes, automation of the process is essential. This review describes the design and implementation of an automated integrated programmable robotic workcell capable of producing complementary DNA libraries, colony picking, isolating plasmid DNA, transforming yeast and bacteria, expressing protein, and performing appropriate functional assays. These operations will allow tailoring microbial strains to use renewable feedstocks for production of biofuels, bioderived chemicals, fertilizers, and other coproducts for profitable and sustainable biorefineries. Published by Elsevier Inc.

Identification and validation of suitable reference genes for RT-qPCR analysis in mouse testis development.

PubMed

Gong, Zu-Kang; Wang, Shuang-Jie; Huang, Yong-Qi; Zhao, Rui-Qiang; Zhu, Qi-Fang; Lin, Wen-Zhen

2014-12-01

RT-qPCR is a commonly used method for evaluating gene expression; however, its accuracy and reliability are dependent upon the choice of appropriate reference gene(s), and there is limited information available on suitable reference gene(s) that can be used in mouse testis at different stages. In this study, using the RT-qPCR method, we investigated the expression variations of six reference genes representing different functional classes (Actb, Gapdh, Ppia, Tbp, Rps29, Hprt1) in mice testis during embryonic and postnatal development. The expression stabilities of putative reference genes were evaluated using five algorithms: geNorm, NormFinder, Bestkeeper, the comparative delta C(t) method and integrated tool RefFinder. Analysis of the results showed that Ppia, Gapdh and Actb were identified as the most stable genes and the geometric mean of Ppia, Gapdh and Actb constitutes an appropriate normalization factor for gene expression studies. The mRNA expression of AT1 as a test gene of interest varied depending upon which of the reference gene(s) was used as an internal control(s). This study suggested that Ppia, Gapdh and Actb are suitable reference genes among the six genes used for RT-qPCR normalization and provide crucial information for transcriptional analyses in future studies of gene expression in the developing mouse testis.

RNAP II Processivity is a Limiting Step for HIV-1 Transcription Independent of Orientation to and Activity of Endogenous Neighboring Promoters

PubMed Central

Michaels, Katarzyna Kaczmarek; Wolschendorf, Frank; Schiralli Lester, Gillian M.; Natarajan, Malini; Kutsch, Olaf; Henderson, Andrew J.

2015-01-01

Since HIV-1 has a propensity to integrate into actively expressed genes, transcriptional interference from neighboring host promoters has been proposed to contribute to the establishment and maintenance HIV-1 latency. To gain insights into how endogenous promoters influence HIV-1 transcription we utilized a set of inducible T cell lines and characterized whether there were correlations between expression of endogenous genes, provirus and long terminal repeat architecture. We show that neighboring promoters are active but have minimal impact on HIV-1 transcription, in particular, expression of the endogenous gene did not prevent expression of HIV-1 following induction of latent provirus. We also demonstrate that releasing paused RNAP II by diminishing negative elongation factor (NELF) is sufficient to reactivate transcriptionally repressed HIV-1 provirus regardless of the integration site and orientation of the provirus suggesting that NELF-mediated RNAP II pausing is a common mechanism of maintaining HIV-1 latency. PMID:26379089

Chromosomal integration of adenoviral vector DNA in vivo.

PubMed

Stephen, Sam Laurel; Montini, Eugenio; Sivanandam, Vijayshankar Ganesh; Al-Dhalimy, Muhseen; Kestler, Hans A; Finegold, Milton; Grompe, Markus; Kochanek, Stefan

2010-10-01

So far there has been no report of any clinical or preclinical evidence for chromosomal vector integration following adenovirus (Ad) vector-mediated gene transfer in vivo. We used liver gene transfer with high-capacity Ad vectors in the FAH(Deltaexon5) mouse model to analyze homologous and heterologous recombination events between vector and chromosomal DNA. Intravenous injection of Ad vectors either expressing a fumarylacetoacetate hydrolase (FAH) cDNA or carrying part of the FAH genomic locus resulted in liver nodules of FAH-expressing hepatocytes, demonstrating chromosomal vector integration. Analysis of junctions between vector and chromosomal DNA following heterologous recombination indicated integration of the vector genome through its termini. Heterologous recombination occurred with a median frequency of 6.72 x 10(-5) per transduced hepatocyte, while homologous recombination occurred more rarely with a median frequency of 3.88 x 10(-7). This study has established quantitative and qualitative data on recombination of adenoviral vector DNA with genomic DNA in vivo, contributing to a risk-benefit assessment of the biosafety of Ad vector-mediated gene transfer.

Cell-type specific features of circular RNA expression.

PubMed

Salzman, Julia; Chen, Raymond E; Olsen, Mari N; Wang, Peter L; Brown, Patrick O

2013-01-01

Thousands of loci in the human and mouse genomes give rise to circular RNA transcripts; at many of these loci, the predominant RNA isoform is a circle. Using an improved computational approach for circular RNA identification, we found widespread circular RNA expression in Drosophila melanogaster and estimate that in humans, circular RNA may account for 1% as many molecules as poly(A) RNA. Analysis of data from the ENCODE consortium revealed that the repertoire of genes expressing circular RNA, the ratio of circular to linear transcripts for each gene, and even the pattern of splice isoforms of circular RNAs from each gene were cell-type specific. These results suggest that biogenesis of circular RNA is an integral, conserved, and regulated feature of the gene expression program.

Moving Toward Integrating Gene Expression Profiling into High-throughput Testing:A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

EPA Science Inventory

Microarray profiling of chemical-induced effects is being increasingly used in medium and high-throughput formats. In this study, we describe computational methods to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), ...

MOPED 2.5—An Integrated Multi-Omics Resource: Multi-Omics Profiling Expression Database Now Includes Transcriptomics Data

PubMed Central

Montague, Elizabeth; Stanberry, Larissa; Higdon, Roger; Janko, Imre; Lee, Elaine; Anderson, Nathaniel; Choiniere, John; Stewart, Elizabeth; Yandl, Gregory; Broomall, William; Kolker, Natali

2014-01-01

Abstract Multi-omics data-driven scientific discovery crucially rests on high-throughput technologies and data sharing. Currently, data are scattered across single omics repositories, stored in varying raw and processed formats, and are often accompanied by limited or no metadata. The Multi-Omics Profiling Expression Database (MOPED, http://moped.proteinspire.org) version 2.5 is a freely accessible multi-omics expression database. Continual improvement and expansion of MOPED is driven by feedback from the Life Sciences Community. In order to meet the emergent need for an integrated multi-omics data resource, MOPED 2.5 now includes gene relative expression data in addition to protein absolute and relative expression data from over 250 large-scale experiments. To facilitate accurate integration of experiments and increase reproducibility, MOPED provides extensive metadata through the Data-Enabled Life Sciences Alliance (DELSA Global, http://delsaglobal.org) metadata checklist. MOPED 2.5 has greatly increased the number of proteomics absolute and relative expression records to over 500,000, in addition to adding more than four million transcriptomics relative expression records. MOPED has an intuitive user interface with tabs for querying different types of omics expression data and new tools for data visualization. Summary information including expression data, pathway mappings, and direct connection between proteins and genes can be viewed on Protein and Gene Details pages. These connections in MOPED provide a context for multi-omics expression data exploration. Researchers are encouraged to submit omics data which will be consistently processed into expression summaries. MOPED as a multi-omics data resource is a pivotal public database, interdisciplinary knowledge resource, and platform for multi-omics understanding. PMID:24910945

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

PubMed Central

He, Hao; Zhang, Lei; Li, Jian; Wang, Yu-Ping; Zhang, Ji-Gang; Shen, Jie; Guo, Yan-Fang

2014-01-01

Context: To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk. Methods: First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa. Results: In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value <.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation. Conclusion: We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis. PMID:25119315

Biallelic insertion of a transcriptional terminator via the CRISPR/Cas9 system efficiently silences expression of protein-coding and non-coding RNA genes.

PubMed

Liu, Yangyang; Han, Xiao; Yuan, Junting; Geng, Tuoyu; Chen, Shihao; Hu, Xuming; Cui, Isabelle H; Cui, Hengmi

2017-04-07

The type II bacterial CRISPR/Cas9 system is a simple, convenient, and powerful tool for targeted gene editing. Here, we describe a CRISPR/Cas9-based approach for inserting a poly(A) transcriptional terminator into both alleles of a targeted gene to silence protein-coding and non-protein-coding genes, which often play key roles in gene regulation but are difficult to silence via insertion or deletion of short DNA fragments. The integration of 225 bp of bovine growth hormone poly(A) signals into either the first intron or the first exon or behind the promoter of target genes caused efficient termination of expression of PPP1R12C , NSUN2 (protein-coding genes), and MALAT1 (non-protein-coding gene). Both NeoR and PuroR were used as markers in the selection of clonal cell lines with biallelic integration of a poly(A) signal. Genotyping analysis indicated that the cell lines displayed the desired biallelic silencing after a brief selection period. These combined results indicate that this CRISPR/Cas9-based approach offers an easy, convenient, and efficient novel technique for gene silencing in cell lines, especially for those in which gene integration is difficult because of a low efficiency of homology-directed repair. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

PubMed Central

Wang, Zichen; Monteiro, Caroline D.; Jagodnik, Kathleen M.; Fernandez, Nicolas F.; Gundersen, Gregory W.; Rouillard, Andrew D.; Jenkins, Sherry L.; Feldmann, Axel S.; Hu, Kevin S.; McDermott, Michael G.; Duan, Qiaonan; Clark, Neil R.; Jones, Matthew R.; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M R.; Szeto, Gregory L.; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M.; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M.; Kruth, Candice D.; Bongio, Nicholas J.; Mathur, Vaibhav; Todoric, Radmila D; Rubin, Udi E.; Malatras, Apostolos; Fulp, Carl T.; Galindo, John A.; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C.; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H.; Allison, Lindsey R.; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'ayan, Avi

2016-01-01

Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization. PMID:27667448

Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd.

PubMed

Wang, Zichen; Monteiro, Caroline D; Jagodnik, Kathleen M; Fernandez, Nicolas F; Gundersen, Gregory W; Rouillard, Andrew D; Jenkins, Sherry L; Feldmann, Axel S; Hu, Kevin S; McDermott, Michael G; Duan, Qiaonan; Clark, Neil R; Jones, Matthew R; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M R; Szeto, Gregory L; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M; Kruth, Candice D; Bongio, Nicholas J; Mathur, Vaibhav; Todoric, Radmila D; Rubin, Udi E; Malatras, Apostolos; Fulp, Carl T; Galindo, John A; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H; Allison, Lindsey R; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'ayan, Avi

2016-09-26

Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.

Correlated gene expression and anatomical communication support synchronized brain activity in the mouse functional connectome.

PubMed

Mills, Brian D; Grayson, David S; Shunmugavel, Anandakumar; Miranda-Dominguez, Oscar; Feczko, Eric; Earl, Eric; Neve, Kim; Fair, Damien A

2018-05-22

Cognition and behavior depend on synchronized intrinsic brain activity that is organized into functional networks across the brain. Research has investigated how anatomical connectivity both shapes and is shaped by these networks, but not how anatomical connectivity interacts with intra-areal molecular properties to drive functional connectivity. Here, we present a novel linear model to explain functional connectivity by integrating systematically obtained measurements of axonal connectivity, gene expression, and resting state functional connectivity MRI in the mouse brain. The model suggests that functional connectivity arises from both anatomical links and inter-areal similarities in gene expression. By estimating these effects, we identify anatomical modules in which correlated gene expression and anatomical connectivity support functional connectivity. Along with providing evidence that not all genes equally contribute to functional connectivity, this research establishes new insights regarding the biological underpinnings of coordinated brain activity measured by BOLD fMRI. SIGNIFICANCE STATEMENT Efforts at characterizing the functional connectome with fMRI have risen exponentially over the last decade. Yet despite this rise, the biological underpinnings of these functional measurements are still largely unknown. The current report begins to fill this void by investigating the molecular underpinnings of the functional connectome through an integration of systematically obtained structural information and gene expression data throughout the rodent brain. We find that both white matter connectivity and similarity in regional gene expression relate to resting state functional connectivity. The current report furthers our understanding of the biological underpinnings of the functional connectome and provides a linear model that can be utilized to streamline preclinical animal studies of disease. Copyright © 2018 the authors.

Defining the gene expression signature of rhabdomyosarcoma by meta-analysis

PubMed Central

Romualdi, Chiara; De Pittà, Cristiano; Tombolan, Lucia; Bortoluzzi, Stefania; Sartori, Francesca; Rosolen, Angelo; Lanfranchi, Gerolamo

2006-01-01

Background Rhabdomyosarcoma is a highly malignant soft tissue sarcoma in childhood and arises as a consequence of regulatory disruption of the growth and differentiation pathways of myogenic precursor cells. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of RMS gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets have opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated. Results In this work we performed a meta-analysis on four microarray and two SAGE datasets of gene expression data on RMS in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Regulatory pathways and biological processes significantly enriched has been investigated and a list of differentially meta-profiles have been identified as possible candidate of aggressiveness of RMS. Conclusion Our results point to a general down regulation of the energy production pathways, suggesting a hypoxic physiology for RMS cells. This result agrees with the high malignancy of RMS and with its resistance to most of the therapeutic treatments. In this context, different isoforms of the ANT gene have been consistently identified for the first time as differentially expressed in RMS. This gene is involved in anti-apoptotic processes when cells grow in low oxygen conditions. These new insights in the biological processes responsible of RMS growth and development demonstrate the effective advantage of the use of integrated analysis of gene expression studies. PMID:17090319

Systematic Integration of Brain eQTL and GWAS Identifies ZNF323 as a Novel Schizophrenia Risk Gene and Suggests Recent Positive Selection Based on Compensatory Advantage on Pulmonary Function

PubMed Central

Luo, Xiong-Jian; Mattheisen, Manuel; Li, Ming; Huang, Liang; Rietschel, Marcella; Børglum, Anders D.; Als, Thomas D.; van den Oord, Edwin J.; Aberg, Karolina A.; Mors, Ole; Mortensen, Preben Bo; Luo, Zhenwu; Degenhardt, Franziska; Cichon, Sven; Schulze, Thomas G.; Nöthen, Markus M.; Su, Bing; Zhao, Zhongming; Gan, Lin; Yao, Yong-Gang

2015-01-01

Genome-wide association studies have identified multiple risk variants and loci that show robust association with schizophrenia. Nevertheless, it remains unclear how these variants confer risk to schizophrenia. In addition, the driving force that maintains the schizophrenia risk variants in human gene pool is poorly understood. To investigate whether expression-associated genetic variants contribute to schizophrenia susceptibility, we systematically integrated brain expression quantitative trait loci and genome-wide association data of schizophrenia using Sherlock, a Bayesian statistical framework. Our analyses identified ZNF323 as a schizophrenia risk gene (P = 2.22×10–6). Subsequent analyses confirmed the association of the ZNF323 and its expression-associated single nucleotide polymorphism rs1150711 in independent samples (gene-expression: P = 1.40×10–6; single-marker meta-analysis in the combined discovery and replication sample comprising 44123 individuals: P = 6.85×10−10). We found that the ZNF323 was significantly downregulated in hippocampus and frontal cortex of schizophrenia patients (P = .0038 and P = .0233, respectively). Evidence for pleiotropic effects was detected (association of rs1150711 with lung function and gene expression of ZNF323 in lung: P = 6.62×10–5 and P = 9.00×10–5, respectively) with the risk allele (T allele) for schizophrenia acting as protective allele for lung function. Subsequent population genetics analyses suggest that the risk allele (T) of rs1150711 might have undergone recent positive selection in human population. Our findings suggest that the ZNF323 is a schizophrenia susceptibility gene whose expression may influence schizophrenia risk. Our study also illustrates a possible mechanism for maintaining schizophrenia risk variants in the human gene pool. PMID:25759474

Prediction of epigenetically regulated genes in breast cancer cell lines

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

Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen

Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines,more » which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fxed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically signifcant negative correlation between methylation profles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identifed 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.« less

Genome-Wide Survey on Genomic Variation, Expression Divergence, and Evolution in Two Contrasting Rice Genotypes under High Salinity Stress

PubMed Central

Jiang, Shu-Ye; Ma, Ali; Ramamoorthy, Rengasamy; Ramachandran, Srinivasan

2013-01-01

Expression profiling is one of the most important tools for dissecting biological functions of genes and the upregulation or downregulation of gene expression is sufficient for recreating phenotypic differences. Expression divergence of genes significantly contributes to phenotypic variations. However, little is known on the molecular basis of expression divergence and evolution among rice genotypes with contrasting phenotypes. In this study, we have implemented an integrative approach using bioinformatics and experimental analyses to provide insights into genomic variation, expression divergence, and evolution between salinity-sensitive rice variety Nipponbare and tolerant rice line Pokkali under normal and high salinity stress conditions. We have detected thousands of differentially expressed genes between these two genotypes and thousands of up- or downregulated genes under high salinity stress. Many genes were first detected with expression evidence using custom microarray analysis. Some gene families were preferentially regulated by high salinity stress and might play key roles in stress-responsive biological processes. Genomic variations in promoter regions resulted from single nucleotide polymorphisms, indels (1–10 bp of insertion/deletion), and structural variations significantly contributed to the expression divergence and regulation. Our data also showed that tandem and segmental duplication, CACTA and hAT elements played roles in the evolution of gene expression divergence and regulation between these two contrasting genotypes under normal or high salinity stress conditions. PMID:24121498

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans.

PubMed

Gottlieb, Assaf; Daneshjou, Roxana; DeGorter, Marianne; Bourgeois, Stephane; Svensson, Peter J; Wadelius, Mia; Deloukas, Panos; Montgomery, Stephen B; Altman, Russ B

2017-11-24

Genome-wide association studies are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into "gene level" effects. Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression-on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis.

PubMed

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T

2016-01-04

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan-Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Heterologous expression of pikromycin biosynthetic gene cluster using Streptomyces artificial chromosome system.

PubMed

Pyeon, Hye-Rim; Nah, Hee-Ju; Kang, Seung-Hoon; Choi, Si-Sun; Kim, Eung-Soo

2017-05-31

Heterologous expression of biosynthetic gene clusters of natural microbial products has become an essential strategy for titer improvement and pathway engineering of various potentially-valuable natural products. A Streptomyces artificial chromosomal conjugation vector, pSBAC, was previously successfully applied for precise cloning and tandem integration of a large polyketide tautomycetin (TMC) biosynthetic gene cluster (Nah et al. in Microb Cell Fact 14(1):1, 2015), implying that this strategy could be employed to develop a custom overexpression scheme of natural product pathway clusters present in actinomycetes. To validate the pSBAC system as a generally-applicable heterologous overexpression system for a large-sized polyketide biosynthetic gene cluster in Streptomyces, another model polyketide compound, the pikromycin biosynthetic gene cluster, was preciously cloned and heterologously expressed using the pSBAC system. A unique HindIII restriction site was precisely inserted at one of the border regions of the pikromycin biosynthetic gene cluster within the chromosome of Streptomyces venezuelae, followed by site-specific recombination of pSBAC into the flanking region of the pikromycin gene cluster. Unlike the previous cloning process, one HindIII site integration step was skipped through pSBAC modification. pPik001, a pSBAC containing the pikromycin biosynthetic gene cluster, was directly introduced into two heterologous hosts, Streptomyces lividans and Streptomyces coelicolor, resulting in the production of 10-deoxymethynolide, a major pikromycin derivative. When two entire pikromycin biosynthetic gene clusters were tandemly introduced into the S. lividans chromosome, overproduction of 10-deoxymethynolide and the presence of pikromycin, which was previously not detected, were both confirmed. Moreover, comparative qRT-PCR results confirmed that the transcription of pikromycin biosynthetic genes was significantly upregulated in S. lividans containing tandem clusters of pikromycin biosynthetic gene clusters. The 60 kb pikromycin biosynthetic gene cluster was isolated in a single integration pSBAC vector. Introduction of the pikromycin biosynthetic gene cluster into the pikromycin non-producing strains resulted in higher pikromycin production. The utility of the pSBAC system as a precise cloning tool for large-sized biosynthetic gene clusters was verified through heterologous expression of the pikromycin biosynthetic gene cluster. Moreover, this pSBAC-driven heterologous expression strategy was confirmed to be an ideal approach for production of low and inconsistent natural products such as pikromycin in S. venezuelae, implying that this strategy could be employed for development of a custom overexpression scheme of natural product biosynthetic gene clusters in actinomycetes.

Evaluation of RNA from human trabecular bone and identification of stable reference genes.

PubMed

Cepollaro, Simona; Della Bella, Elena; de Biase, Dario; Visani, Michela; Fini, Milena

2018-06-01

The isolation of good quality RNA from tissues is an essential prerequisite for gene expression analysis to study pathophysiological processes. This study evaluated the RNA isolated from human trabecular bone and defined a set of stable reference genes. After pulverization, RNA was extracted with a phenol/chloroform method and then purified using silica columns. The A260/280 ratio, A260/230 ratio, RIN, and ribosomal ratio were measured to evaluate RNA quality and integrity. Moreover, the expression of six candidates was analyzed by qPCR and different algorithms were applied to assess reference gene stability. A good purity and quality of RNA was achieved according to A260/280 and A260/230 ratios, and RIN values. TBP, YWHAZ, and PGK1 were the most stable reference genes that should be used for gene expression analysis. In summary, the method proposed is suitable for gene expression evaluation in human bone and a set of reliable reference genes has been identified. © 2017 Wiley Periodicals, Inc.

Systematic identification of an integrative network module during senescence from time-series gene expression.

PubMed

Park, Chihyun; Yun, So Jeong; Ryu, Sung Jin; Lee, Soyoung; Lee, Young-Sam; Yoon, Youngmi; Park, Sang Chul

2017-03-15

Cellular senescence irreversibly arrests growth of human diploid cells. In addition, recent studies have indicated that senescence is a multi-step evolving process related to important complex biological processes. Most studies analyzed only the genes and their functions representing each senescence phase without considering gene-level interactions and continuously perturbed genes. It is necessary to reveal the genotypic mechanism inferred by affected genes and their interaction underlying the senescence process. We suggested a novel computational approach to identify an integrative network which profiles an underlying genotypic signature from time-series gene expression data. The relatively perturbed genes were selected for each time point based on the proposed scoring measure denominated as perturbation scores. Then, the selected genes were integrated with protein-protein interactions to construct time point specific network. From these constructed networks, the conserved edges across time point were extracted for the common network and statistical test was performed to demonstrate that the network could explain the phenotypic alteration. As a result, it was confirmed that the difference of average perturbation scores of common networks at both two time points could explain the phenotypic alteration. We also performed functional enrichment on the common network and identified high association with phenotypic alteration. Remarkably, we observed that the identified cell cycle specific common network played an important role in replicative senescence as a key regulator. Heretofore, the network analysis from time series gene expression data has been focused on what topological structure was changed over time point. Conversely, we focused on the conserved structure but its context was changed in course of time and showed it was available to explain the phenotypic changes. We expect that the proposed method will help to elucidate the biological mechanism unrevealed by the existing approaches.

Regulated expression of the Ren-2 gene in transgenic mice derived from parental strains carrying only the Ren-1 gene.

PubMed Central

Tronik, D; Dreyfus, M; Babinet, C; Rougeon, F

1987-01-01

The Ren-2 gene encoding the mouse submaxillary gland (SMG) renin was microinjected into the pronuclei of fertilized eggs from mice carrying only the Ren-1 gene. In addition to the whole transcription unit, the injected DNA contained 2.5 and 3 kb of upstream and downstream flanking sequences, respectively. Three independent transgenic mice lines were obtained; two of them had integrated one copy of the Ren-2 gene, the last one had integrated five and eleven copies at two independent sites. Independently of the number of Ren-2 copies integrated, the pattern of Ren-2 gene expression in all the transgenic mice was identical to that observed in wild-type animals in which Ren-1 and Ren-2 are closely linked on chromosome 1. In particular, the exogenous Ren-2 gene was only transcribed in the kidney and in the SMG. In the kidney, Ren-1 and Ren-2 mRNAs were present at a comparable level, whereas in the SMG Ren-2 mRNA was at least 100-fold more abundant than Ren-1 mRNA. Moreover, Ren-2 expression in the SMG was positively regulated by androgens. Only one difference between transgenic mice and wild-type mice carrying the Ren-2 gene has been observed: the basal level of Ren-2 transcription in the SMG of transgenic females was lower than in two-gene strain females. Androgen treatment of transgenic females induced SMG renin mRNA to a level identical to that of transgenic males. This suggests that the basal level of SMG renin mRNA is dependent upon cis-acting elements which are not present in the microinjected fragment. Images Fig. 1. Fig. 2. Fig. 3. PMID:3297677

Calcium Signaling Pathway Genes RUNX2 and CACNA1C Are Associated With Calcific Aortic Valve Disease

PubMed Central

Guauque-Olarte, Sandra; Messika-Zeitoun, David; Droit, Arnaud; Lamontagne, Maxime; Tremblay-Marchand, Joël; Lavoie-Charland, Emilie; Gaudreault, Nathalie; Arsenault, Benoit J.; Dubé, Marie-Pierre; Tardif, Jean-Claude; Body, Simon C.; Seidman, Jonathan G.; Boileau, Catherine; Mathieu, Patrick; Pibarot, Philippe; Bossé, Yohan

2016-01-01

Background Calcific aortic valve stenosis (AS) is a life-threatening disease with no medical therapy. The genetic architecture of AS remains elusive. This study combines genome-wide association studies, gene expression, and expression quantitative trait loci mapping in human valve tissues to identify susceptibility genes of AS. Methods and Results A meta-analysis was performed combining the results of 2 genome-wide association studies in 474 and 486 cases from Quebec City (Canada) and Paris (France), respectively. Corresponding controls consisted of 2988 and 1864 individuals with European ancestry from the database of genotypes and phenotypes. mRNA expression levels were evaluated in 9 calcified and 8 normal aortic valves by RNA sequencing. The results were integrated with valve expression quantitative trait loci data obtained from 22 AS patients. Twenty-five single-nucleotide polymorphisms had P<5×10−6 in the genome-wide association studies meta-analysis. The calcium signaling pathway was the top gene set enriched for genes mapped to moderately AS-associated single-nucleotide polymorphisms. Genes in this pathway were found differentially expressed in valves with and without AS. Two single-nucleotide polymorphisms located in RUNX2 (runt-related transcription factor 2), encoding an osteogenic transcription factor, demonstrated some association with AS (genome-wide association studies P=5.33×10−5). The mRNA expression levels of RUNX2 were upregulated in calcified valves and associated with eQTL-SNPs. CACNA1C encoding a subunit of a voltage-dependent calcium channel was upregulated in calcified valves. The eQTL-SNP with the most significant association with AS located in CACNA1C was associated with higher expression of the gene. Conclusions This integrative genomic study confirmed the role of RUNX2 as a potential driver of AS and identified a new AS susceptibility gene, CACNA1C, belonging to the calcium signaling pathway. PMID:26553695

Spatially coordinated dynamic gene transcription in living pituitary tissue

PubMed Central

Featherstone, Karen; Hey, Kirsty; Momiji, Hiroshi; McNamara, Anne V; Patist, Amanda L; Woodburn, Joanna; Spiller, David G; Christian, Helen C; McNeilly, Alan S; Mullins, John J; Finkenstädt, Bärbel F; Rand, David A; White, Michael RH; Davis, Julian RE

2016-01-01

Transcription at individual genes in single cells is often pulsatile and stochastic. A key question emerges regarding how this behaviour contributes to tissue phenotype, but it has been a challenge to quantitatively analyse this in living cells over time, as opposed to studying snap-shots of gene expression state. We have used imaging of reporter gene expression to track transcription in living pituitary tissue. We integrated live-cell imaging data with statistical modelling for quantitative real-time estimation of the timing of switching between transcriptional states across a whole tissue. Multiple levels of transcription rate were identified, indicating that gene expression is not a simple binary ‘on-off’ process. Immature tissue displayed shorter durations of high-expressing states than the adult. In adult pituitary tissue, direct cell contacts involving gap junctions allowed local spatial coordination of prolactin gene expression. Our findings identify how heterogeneous transcriptional dynamics of single cells may contribute to overall tissue behaviour. DOI: http://dx.doi.org/10.7554/eLife.08494.001 PMID:26828110

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 prognostic marker. Together, we provided a novel framework that successfully integrated the TCGA and ENCODE data in revealing AML-specific regulatory program at global level. PMID:25340776

Cell Culture Systems To Study Human Herpesvirus 6A/B Chromosomal Integration.

PubMed

Gravel, Annie; Dubuc, Isabelle; Wallaschek, Nina; Gilbert-Girard, Shella; Collin, Vanessa; Hall-Sedlak, Ruth; Jerome, Keith R; Mori, Yasuko; Carbonneau, Julie; Boivin, Guy; Kaufer, Benedikt B; Flamand, Louis

2017-07-15

Human herpesviruses 6A/B (HHV-6A/B) can integrate their viral genomes in the telomeres of human chromosomes. The viral and cellular factors contributing to HHV-6A/B integration remain largely unknown, mostly due to the lack of efficient and reproducible cell culture models to study HHV-6A/B integration. In this study, we characterized the HHV-6A/B integration efficiencies in several human cell lines using two different approaches. First, after a short-term infection (5 h), cells were processed for single-cell cloning and analyzed for chromosomally integrated HHV-6A/B (ciHHV-6A/B). Second, cells were infected with HHV-6A/B and allowed to grow in bulk for 4 weeks or longer and then analyzed for the presence of ciHHV-6. Using quantitative PCR (qPCR), droplet digital PCR, and fluorescent in situ hybridization, we could demonstrate that HHV-6A/B integrated in most human cell lines tested, including telomerase-positive (HeLa, MCF-7, HCT-116, and HEK293T) and telomerase-negative cell lines (U2OS and GM847). Our results also indicate that inhibition of DNA replication, using phosphonoacetic acid, did not affect HHV-6A/B integration. Certain clones harboring ciHHV-6A/B spontaneously express viral genes and proteins. Treatment of cells with phorbol ester or histone deacetylase inhibitors triggered the expression of many viral genes, including U39 , U90 , and U100 , without the production of infectious virus, suggesting that the tested stimuli were not sufficient to trigger full reactivation. In summary, both integration models yielded comparable results and should enable the identification of viral and cellular factors contributing to HHV-6A/B integration and the screening of drugs influencing viral gene expression, as well as the release of infectious HHV-6A/B from the integrated state. IMPORTANCE The analysis and understanding of HHV-6A/B genome integration into host DNA is currently limited due to the lack of reproducible and efficient viral integration systems. In the present study, we describe two quantitative cell culture viral integration systems. These systems can be used to define cellular and viral factors that play a role in HHV-6A/B integration. Furthermore, these systems will allow us to decipher the conditions resulting in virus gene expression and excision of the integrated viral genome resulting in reactivation. Copyright © 2017 American Society for Microbiology.

Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

NASA Astrophysics Data System (ADS)

Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed that the device identified influenza A hemagglutinin and neuraminidase subtypes and sequenced portions of both genes, demonstrating the potential of integrated microfluidic and microarray technology for multiple virus detection. The device provides a cost-effective solution to eliminate labor-intensive and time-consuming fluidic handling steps and allows microarray-based DNA analysis in a rapid and automated fashion.

An ontology-driven semantic mash-up of gene and biological pathway information: Application to the domain of nicotine dependence

PubMed Central

Sahoo, Satya S.; Bodenreider, Olivier; Rutter, Joni L.; Skinner, Karen J.; Sheth, Amit P.

2008-01-01

Objectives This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. Methods We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Results Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Conclusion Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. Resource page http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/ PMID:18395495

An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence.

PubMed

Sahoo, Satya S; Bodenreider, Olivier; Rutter, Joni L; Skinner, Karen J; Sheth, Amit P

2008-10-01

This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. RESOURCE PAGE: http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/

BiGGEsTS: integrated environment for biclustering analysis of time series gene expression data

PubMed Central

Gonçalves, Joana P; Madeira, Sara C; Oliveira, Arlindo L

2009-01-01

Background The ability to monitor changes in expression patterns over time, and to observe the emergence of coherent temporal responses using expression time series, is critical to advance our understanding of complex biological processes. Biclustering has been recognized as an effective method for discovering local temporal expression patterns and unraveling potential regulatory mechanisms. The general biclustering problem is NP-hard. In the case of time series this problem is tractable, and efficient algorithms can be used. However, there is still a need for specialized applications able to take advantage of the temporal properties inherent to expression time series, both from a computational and a biological perspective. Findings BiGGEsTS makes available state-of-the-art biclustering algorithms for analyzing expression time series. Gene Ontology (GO) annotations are used to assess the biological relevance of the biclusters. Methods for preprocessing expression time series and post-processing results are also included. The analysis is additionally supported by a visualization module capable of displaying informative representations of the data, including heatmaps, dendrograms, expression charts and graphs of enriched GO terms. Conclusion BiGGEsTS is a free open source graphical software tool for revealing local coexpression of genes in specific intervals of time, while integrating meaningful information on gene annotations. It is freely available at: . We present a case study on the discovery of transcriptional regulatory modules in the response of Saccharomyces cerevisiae to heat stress. PMID:19583847

Stress and salicylic acid induce the expression of PnFT2 in the regulation of the stress-induced flowering of Pharbitis nil.

PubMed

Yamada, Mizuki; Takeno, Kiyotoshi

2014-02-15

Poor nutrition and low temperature stress treatments induced flowering in the Japanese morning glory Pharbitis nil (synonym Ipomoea nil) cv. Violet. The expression of PnFT2, one of two homologs of the floral pathway integrator gene FLOWERING LOCUS T (FT), was induced by stress, whereas the expression of both PnFT1 and PnFT2 was induced by a short-day treatment. There was no positive correlation between the flowering response and the homolog expression of another floral pathway integrator gene SUPPRESSOR OF OVEREXPRESSION OF CO1 and genes upstream of PnFT, such as CONSTANS. In another cultivar, Tendan, flowering and PnFT2 expression were not induced by poor nutrition stress. Aminooxyacetic acid (AOA), a phenylalanine ammonia-lyase inhibitor, inhibited the flowering and PnFT2 expression induced by poor nutrition stress in Violet. Salicylic acid (SA) eliminated the inhibitory effects of AOA. SA enhanced PnFT2 expression under the poor nutrition stress but not under non-stress conditions. These results suggest that SA induces PnFT2 expression, which in turn induces flowering; SA on its own, however, may not be sufficient for induction. Copyright © 2013 Elsevier GmbH. All rights reserved.

Gene silencing in Escherichia coli using antisense RNAs expressed from doxycycline-inducible vectors.

PubMed

Nakashima, N; Tamura, T

2013-06-01

Here, we report on the construction of doxycycline (tetracycline analogue)-inducible vectors that express antisense RNAs in Escherichia coli. Using these vectors, the expression of genes of interest can be silenced conditionally. The expression of antisense RNAs from the vectors was more tightly regulated than the previously constructed isopropyl-β-D-galactopyranoside-inducible vectors. Furthermore, expression levels of antisense RNAs were enhanced by combining the doxycycline-inducible promoter with the T7 promoter-T7 RNA polymerase system; the T7 RNA polymerase gene, under control of the doxycycline-inducible promoter, was integrated into the lacZ locus of the genome without leaving any antibiotic marker. These vectors are useful for investigating gene functions or altering cell phenotypes for biotechnological and industrial applications. A gene silencing method using antisense RNAs in Escherichia coli is described, which facilitates the investigation of bacterial gene function. In particular, the method is suitable for comprehensive analyses or phenotypic analyses of genes essential for growth. Here, we describe expansion of vector variations for expressing antisense RNAs, allowing choice of a vector appropriate for the target genes or experimental purpose. © 2013 The Society for Applied Microbiology.

Identifying candidate driver genes by integrative ovarian cancer genomics data

NASA Astrophysics Data System (ADS)

Lu, Xinguo; Lu, Jibo

2017-08-01

Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

Toxicity of algicidal extracts from Mangrovimonas yunxiaonensis strain LY01 on a HAB causing Alexandrium tamarense.

PubMed

Li, Yi; Zhu, Hong; Zhang, Huajun; Chen, Zhangran; Tian, Yun; Xu, Hong; Zheng, Tianling; Zheng, Wei

2014-08-15

Toxicity of algicidal extracts from Mangrovimonas yunxiaonensis strain LY01 on Alexandrium tamarense were measured through studying the algicidal procedure, nuclear damage and transcription of related genes. Medium components were optimized to improve algicidal activity, and characteristics of algicidal extracts were determined. Transmission electron microscope analysis revealed that the cell structure was broken. Cell membrane integrity destruction and nuclear structure degradation were monitored using confocal laser scanning microscope, and the rbcS, hsp and proliferating cell nuclear antigen (PCNA) gene expressions were studied. Results showed that 1.0% tryptone, 0.4% glucose and 0.8% MgCl2 were the optimal nutrient sources. The algicidal extracts were heat and pH stable, non-protein and less than 1kD. Cell membrane and nuclear structure integrity were lost, and the transcription of the rbcS and PCNA genes were significantly inhibited and there was up-regulation of hsp gene expression during the exposure procedure. The algicidal extracts destroyed the cell membrane and nuclear structure integrity, inhibited related gene expression and, eventually, lead to the inhibition of algal growth. All the results may elaborate firstly the cell death process and nuclear damage in A. tamarense which was induced by algicidal extracts, and the algicidal extracts could be potentially used as bacterial control of HABs in future. Copyright © 2014 Elsevier B.V. All rights reserved.

An integrative approach to inferring biologically meaningful gene modules

PubMed Central

2011-01-01

Background The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. Results We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. Conclusions The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level. PMID:21791051

Heterologous expression of the mevalonic acid pathway in cyanobacteria enhances endogenous carbon partitioning to isoprene.

PubMed

Bentley, Fiona K; Zurbriggen, Andreas; Melis, Anastasios

2014-01-01

Heterologous expression of the isoprene synthase gene in the cyanobacterium Synechocystis PCC 6803 conferred upon these microorganisms the property of photosynthetic isoprene (C₅H₈) hydrocarbons production. Continuous production of isoprene from CO₂ and H₂O was achieved in the light, occurring via the endogenous methylerythritol-phosphate (MEP) pathway, in tandem with the growth of Synechocystis. This work addressed the issue of photosynthetic carbon partitioning between isoprene and biomass in Synechocystis. Evidence is presented to show heterologous genomic integration and cellular expression of the mevalonic acid (MVA) pathway genes in Synechocystis endowing a non-native pathway for carbon flux amplification to isopentenyl-diphosphate (IPP) and dimethylallyl-diphosphate (DMAPP) precursors of isoprene. Heterologous expression of the isoprene synthase in combination with the MVA pathway enzymes resulted in photosynthetic isoprene yield improvement by approximately 2.5-fold, compared with that measured in cyanobacteria transformed with the isoprene synthase gene only. These results suggest that the MVA pathway introduces a bypass in the flux of endogenous cellular substrate in Synechocystis to IPP and DMAPP, overcoming flux limitations of the native MEP pathway. The work employed a novel chromosomal integration and expression of synthetic gene operons in Synechocystis, comprising up to four genes under the control of a single promoter, and expressing three operons simultaneously. This is the first time an entire biosynthetic pathway with seven recombinant enzymes has been heterologously expressed in a photosynthetic microorganism. It constitutes contribution to the genetic engineering toolkit of photosynthetic microorganisms and a paradigm in the pursuit of photosynthetic approaches for the renewable generation of high-impact products.

Discovering perturbation of modular structure in HIV progression by integrating multiple data sources through non-negative matrix factorization.

PubMed

Ray, Sumanta; Maulik, Ujjwal

2016-12-20

Detecting perturbation in modular structure during HIV-1 disease progression is an important step to understand stage specific infection pattern of HIV-1 virus in human cell. In this article, we proposed a novel methodology on integration of multiple biological information to identify such disruption in human gene module during different stages of HIV-1 infection. We integrate three different biological information: gene expression information, protein-protein interaction information and gene ontology information in single gene meta-module, through non negative matrix factorization (NMF). As the identified metamodules inherit those information so, detecting perturbation of these, reflects the changes in expression pattern, in PPI structure and in functional similarity of genes during the infection progression. To integrate modules of different data sources into strong meta-modules, NMF based clustering is utilized here. Perturbation in meta-modular structure is identified by investigating the topological and intramodular properties and putting rank to those meta-modules using a rank aggregation algorithm. We have also analyzed the preservation structure of significant GO terms in which the human proteins of the meta-modules participate. Moreover, we have performed an analysis to show the change of coregulation pattern of identified transcription factors (TFs) over the HIV progression stages.

Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders

PubMed Central

Jha, Prabhash Kumar; Vijay, Aatira; Sahu, Anita; Ashraf, Mohammad Zahid

2016-01-01

Thrombosis is a leading cause of morbidity and mortality in patients with myeloproliferative disorders (MPDs), particularly polycythemia vera (PV) and essential thrombocythemia (ET). Despite the attempts to establish a link between them, the shared biological mechanisms are yet to be characterized. An integrated gene expression meta-analysis of five independent publicly available microarray data of the three diseases was conducted to identify shared gene expression signatures and overlapping biological processes. Using INMEX bioinformatic tool, based on combined Effect Size (ES) approaches, we identified a total of 1,157 differentially expressed genes (DEGs) (697 overexpressed and 460 underexpressed genes) shared between the three diseases. EnrichR tool’s rich library was used for comprehensive functional enrichment and pathway analysis which revealed “mRNA Splicing” and “SUMO E3 ligases SUMOylate target proteins” among the most enriched terms. Network based meta-analysis identified MYC and FN1 to be the most highly ranked hub genes. Our results reveal that the alterations in biomarkers of the coagulation cascade like F2R, PROS1, SELPLG and ITGB2 were common between the three diseases. Interestingly, the study has generated a novel database of candidate genetic markers, pathways and transcription factors shared between thrombosis and MPDs, which might aid in the development of prognostic therapeutic biomarkers. PMID:27892526

Integrating Microarray Data and GRNs.

PubMed

Koumakis, L; Potamias, G; Tsiknakis, M; Zervakis, M; Moustakis, V

2016-01-01

With the completion of the Human Genome Project and the emergence of high-throughput technologies, a vast amount of molecular and biological data are being produced. Two of the most important and significant data sources come from microarray gene-expression experiments and respective databanks (e,g., Gene Expression Omnibus-GEO (http://www.ncbi.nlm.nih.gov/geo)), and from molecular pathways and Gene Regulatory Networks (GRNs) stored and curated in public (e.g., Kyoto Encyclopedia of Genes and Genomes-KEGG (http://www.genome.jp/kegg/pathway.html), Reactome (http://www.reactome.org/ReactomeGWT/entrypoint.html)) as well as in commercial repositories (e.g., Ingenuity IPA (http://www.ingenuity.com/products/ipa)). The association of these two sources aims to give new insight in disease understanding and reveal new molecular targets in the treatment of specific phenotypes.Three major research lines and respective efforts that try to utilize and combine data from both of these sources could be identified, namely: (1) de novo reconstruction of GRNs, (2) identification of Gene-signatures, and (3) identification of differentially expressed GRN functional paths (i.e., sub-GRN paths that distinguish between different phenotypes). In this chapter, we give an overview of the existing methods that support the different types of gene-expression and GRN integration with a focus on methodologies that aim to identify phenotype-discriminant GRNs or subnetworks, and we also present our methodology.

Identification of Differentially Expressed Genes through Integrated Study of Alzheimer’s Disease Affected Brain Regions

PubMed Central

Berretta, Regina; Moscato, Pablo

2016-01-01

Background Alzheimer’s disease (AD) is the most common form of dementia in older adults that damages the brain and results in impaired memory, thinking and behaviour. The identification of differentially expressed genes and related pathways among affected brain regions can provide more information on the mechanisms of AD. In the past decade, several studies have reported many genes that are associated with AD. This wealth of information has become difficult to follow and interpret as most of the results are conflicting. In that case, it is worth doing an integrated study of multiple datasets that helps to increase the total number of samples and the statistical power in detecting biomarkers. In this study, we present an integrated analysis of five different brain region datasets and introduce new genes that warrant further investigation. Methods The aim of our study is to apply a novel combinatorial optimisation based meta-analysis approach to identify differentially expressed genes that are associated to AD across brain regions. In this study, microarray gene expression data from 161 samples (74 non-demented controls, 87 AD) from the Entorhinal Cortex (EC), Hippocampus (HIP), Middle temporal gyrus (MTG), Posterior cingulate cortex (PC), Superior frontal gyrus (SFG) and visual cortex (VCX) brain regions were integrated and analysed using our method. The results are then compared to two popular meta-analysis methods, RankProd and GeneMeta, and to what can be obtained by analysing the individual datasets. Results We find genes related with AD that are consistent with existing studies, and new candidate genes not previously related with AD. Our study confirms the up-regualtion of INFAR2 and PTMA along with the down regulation of GPHN, RAB2A, PSMD14 and FGF. Novel genes PSMB2, WNK1, RPL15, SEMA4C, RWDD2A and LARGE are found to be differentially expressed across all brain regions. Further investigation on these genes may provide new insights into the development of AD. In addition, we identified the presence of 23 non-coding features, including four miRNA precursors (miR-7, miR570, miR-1229 and miR-6821), dysregulated across the brain regions. Furthermore, we compared our results with two popular meta-analysis methods RankProd and GeneMeta to validate our findings and performed a sensitivity analysis by removing one dataset at a time to assess the robustness of our results. These new findings may provide new insights into the disease mechanisms and thus make a significant contribution in the near future towards understanding, prevention and cure of AD. PMID:27050411

Molecular Imaging of Human Embryonic Stem Cells Stably Expressing Human PET Reporter Genes After Zinc Finger Nuclease-Mediated Genome Editing.

PubMed

Wolfs, Esther; Holvoet, Bryan; Ordovas, Laura; Breuls, Natacha; Helsen, Nicky; Schönberger, Matthias; Raitano, Susanna; Struys, Tom; Vanbilloen, Bert; Casteels, Cindy; Sampaolesi, Maurilio; Van Laere, Koen; Lambrichts, Ivo; Verfaillie, Catherine M; Deroose, Christophe M

2017-10-01

Molecular imaging is indispensable for determining the fate and persistence of engrafted stem cells. Standard strategies for transgene induction involve the use of viral vectors prone to silencing and insertional mutagenesis or the use of nonhuman genes. Methods: We used zinc finger nucleases to induce stable expression of human imaging reporter genes into the safe-harbor locus adeno-associated virus integration site 1 in human embryonic stem cells. Plasmids were generated carrying reporter genes for fluorescence, bioluminescence imaging, and human PET reporter genes. Results: In vitro assays confirmed their functionality, and embryonic stem cells retained differentiation capacity. Teratoma formation assays were performed, and tumors were imaged over time with PET and bioluminescence imaging. Conclusion: This study demonstrates the application of genome editing for targeted integration of human imaging reporter genes in human embryonic stem cells for long-term molecular imaging. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Retrotransposons as regulators of gene expression

PubMed Central

Elbarbary, Reyad A.; Lucas, Bronwyn A.; Maquat, Lynne E.

2016-01-01

Transposable elements (TEs) are both a boon and a bane to eukaryotic organisms, depending on where they integrate into the genome and how their sequences function once integrated. We focus on two types of TEs: long interspersed elements (LINEs) and short interspersed elements (SINEs). LINEs and SINEs are retrotransposons; that is, they transpose via an RNA intermediate. We discuss how LINEs and SINEs have expanded in eukaryotic genomes and contribute to genome evolution. An emerging body of evidence indicates that LINEs and SINEs function to regulate gene expression by affecting chromatin structure, gene transcription, pre-mRNA processing, or aspects of mRNA metabolism. We also describe how adenosine-to-inosine editing influences SINE function and how ongoing retrotransposition is countered by the body’s defense mechanisms. PMID:26912865

RNAi-dependent and -independent antiviral phenotypes of chromosomally integrated shRNA clones: role of VASP in respiratory syncytial virus growth.

PubMed

Musiyenko, Alla; Bitko, Vira; Barik, Sailen

2007-07-01

Stable RNA interference (RNAi) is commonly achieved by recombinant expression of short hairpin RNA (shRNA). To generate virus-resistant cell lines, we cloned a shRNA cassette against the phosphoprotein gene of respiratory syncytial virus (RSV) into a polIII-driven plasmid vector. Analysis of individual stable transfectants showed a spectrum of RSV resistance correlating with the levels of shRNA expressed from different chromosomal locations. Interestingly, resistance in a minority of clones was due to mono-allelic disruption of the cellular gene for vasodilator-stimulated phosphoprotein (VASP). Thus, pure clones of chromosomally integrated DNA-directed RNAi can exhibit gene disruption phenotypes resembling but unrelated to RNAi.

oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes

PubMed Central

Ho Sui, Shannan J.; Mortimer, James R.; Arenillas, David J.; Brumm, Jochen; Walsh, Christopher J.; Kennedy, Brian P.; Wasserman, Wyeth W.

2005-01-01

Targeted transcript profiling studies can identify sets of co-expressed genes; however, identification of the underlying functional mechanism(s) is a significant challenge. Established methods for the analysis of gene annotations, particularly those based on the Gene Ontology, can identify functional linkages between genes. Similar methods for the identification of over-represented transcription factor binding sites (TFBSs) have been successful in yeast, but extension to human genomics has largely proved ineffective. Creation of a system for the efficient identification of common regulatory mechanisms in a subset of co-expressed human genes promises to break a roadblock in functional genomics research. We have developed an integrated system that searches for evidence of co-regulation by one or more transcription factors (TFs). oPOSSUM combines a pre-computed database of conserved TFBSs in human and mouse promoters with statistical methods for identification of sites over-represented in a set of co-expressed genes. The algorithm successfully identified mediating TFs in control sets of tissue-specific genes and in sets of co-expressed genes from three transcript profiling studies. Simulation studies indicate that oPOSSUM produces few false positives using empirically defined thresholds and can tolerate up to 50% noise in a set of co-expressed genes. PMID:15933209

NEIBank: Genomics and bioinformatics resources for vision research

PubMed Central

Peterson, Katherine; Gao, James; Buchoff, Patee; Jaworski, Cynthia; Bowes-Rickman, Catherine; Ebright, Jessica N.; Hauser, Michael A.; Hoover, David

2008-01-01

NEIBank is an integrated resource for genomics and bioinformatics in vision research. It includes expressed sequence tag (EST) data and sequence-verified cDNA clones for multiple eye tissues of several species, web-based access to human eye-specific SAGE data through EyeSAGE, and comprehensive, annotated databases of known human eye disease genes and candidate disease gene loci. All expression- and disease-related data are integrated in EyeBrowse, an eye-centric genome browser. NEIBank provides a comprehensive overview of current knowledge of the transcriptional repertoires of eye tissues and their relation to pathology. PMID:18648525

CHD8 regulates neurodevelopmental pathways associated with autism spectrum disorder in neural progenitors

PubMed Central

Sugathan, Aarathi; Biagioli, Marta; Golzio, Christelle; Erdin, Serkan; Blumenthal, Ian; Manavalan, Poornima; Ragavendran, Ashok; Brand, Harrison; Lucente, Diane; Miles, Judith; Sheridan, Steven D.; Stortchevoi, Alexei; Kellis, Manolis; Haggarty, Stephen J.; Katsanis, Nicholas; Gusella, James F.; Talkowski, Michael E.

2014-01-01

Truncating mutations of chromodomain helicase DNA-binding protein 8 (CHD8), and of many other genes with diverse functions, are strong-effect risk factors for autism spectrum disorder (ASD), suggesting multiple mechanisms of pathogenesis. We explored the transcriptional networks that CHD8 regulates in neural progenitor cells (NPCs) by reducing its expression and then integrating transcriptome sequencing (RNA sequencing) with genome-wide CHD8 binding (ChIP sequencing). Suppressing CHD8 to levels comparable with the loss of a single allele caused altered expression of 1,756 genes, 64.9% of which were up-regulated. CHD8 showed widespread binding to chromatin, with 7,324 replicated sites that marked 5,658 genes. Integration of these data suggests that a limited array of direct regulatory effects of CHD8 produced a much larger network of secondary expression changes. Genes indirectly down-regulated (i.e., without CHD8-binding sites) reflect pathways involved in brain development, including synapse formation, neuron differentiation, cell adhesion, and axon guidance, whereas CHD8-bound genes are strongly associated with chromatin modification and transcriptional regulation. Genes associated with ASD were strongly enriched among indirectly down-regulated loci (P < 10−8) and CHD8-bound genes (P = 0.0043), which align with previously identified coexpression modules during fetal development. We also find an intriguing enrichment of cancer-related gene sets among CHD8-bound genes (P < 10−10). In vivo suppression of chd8 in zebrafish produced macrocephaly comparable to that of humans with inactivating mutations. These data indicate that heterozygous disruption of CHD8 precipitates a network of gene-expression changes involved in neurodevelopmental pathways in which many ASD-associated genes may converge on shared mechanisms of pathogenesis. PMID:25294932

Warehousing re-annotated cancer genes for biomarker meta-analysis.

PubMed

Orsini, M; Travaglione, A; Capobianco, E

2013-07-01

Translational research in cancer genomics assigns a fundamental role to bioinformatics in support of candidate gene prioritization with regard to both biomarker discovery and target identification for drug development. Efforts in both such directions rely on the existence and constant update of large repositories of gene expression data and omics records obtained from a variety of experiments. Users who interactively interrogate such repositories may have problems in retrieving sample fields that present limited associated information, due for instance to incomplete entries or sometimes unusable files. Cancer-specific data sources present similar problems. Given that source integration usually improves data quality, one of the objectives is keeping the computational complexity sufficiently low to allow an optimal assimilation and mining of all the information. In particular, the scope of integrating intraomics data can be to improve the exploration of gene co-expression landscapes, while the scope of integrating interomics sources can be that of establishing genotype-phenotype associations. Both integrations are relevant to cancer biomarker meta-analysis, as the proposed study demonstrates. Our approach is based on re-annotating cancer-specific data available at the EBI's ArrayExpress repository and building a data warehouse aimed to biomarker discovery and validation studies. Cancer genes are organized by tissue with biomedical and clinical evidences combined to increase reproducibility and consistency of results. For better comparative evaluation, multiple queries have been designed to efficiently address all types of experiments and platforms, and allow for retrieval of sample-related information, such as cell line, disease state and clinical aspects. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Brain region-specific gene expression changes after chronic intermittent ethanol exposure and early withdrawal in C57BL/6J mice

PubMed Central

Melendez, Roberto I.; McGinty, Jacqueline F.; Kalivas, Peter W.; Becker, Howard C.

2014-01-01

Neuroadaptations that participate in the ontogeny of alcohol dependence are likely a result of altered gene expression in various brain regions. The present study investigated brain region-specific changes in the pattern and magnitude of gene expression immediately following chronic intermittent ethanol (CIE) exposure and 8 hours following final ethanol exposure [i.e. early withdrawal (EWD)]. High-density oligonucleotide microarrays (Affymetrix 430A 2.0, Affymetrix, Santa Clara, CA, USA) and bioinformatics analysis were used to characterize gene expression and function in the prefrontal cortex (PFC), hippocampus (HPC) and nucleus accumbens (NAc) of C57BL/6J mice (Jackson Laboratories, Bar Harbor, ME, USA). Gene expression levels were determined using gene chip robust multi-array average followed by statistical analysis of microarrays and validated by quantitative real-time reverse transcription polymerase chain reaction and Western blot analysis. Results indicated that immediately following CIE exposure, changes in gene expression were strikingly greater in the PFC (284 genes) compared with the HPC (16 genes) and NAc (32 genes). Bioinformatics analysis revealed that most of the transcriptionally responsive genes in the PFC were involved in Ras/MAPK signaling, notch signaling or ubiquitination. In contrast, during EWD, changes in gene expression were greatest in the HPC (139 genes) compared with the PFC (four genes) and NAc (eight genes). The most transcriptionally responsive genes in the HPC were involved in mRNA processing or actin dynamics. Of the few genes detected in the NAc, the most representatives were involved in circadian rhythms. Overall, these findings indicate that brain region-specific and time-dependent neuroadaptive alterations in gene expression play an integral role in the development of alcohol dependence and withdrawal. PMID:21812870

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

PubMed

Ishikawa, Akira

2017-11-27

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

Sho-saiko-to, a traditional herbal medicine, regulates gene expression and biological function by way of microRNAs in primary mouse hepatocytes

PubMed Central

2014-01-01

Background Sho-saiko-to (SST) (also known as so-shi-ho-tang or xiao-chai-hu-tang) has been widely prescribed for chronic liver diseases in traditional Oriental medicine. Despite the substantial amount of clinical evidence for SST, its molecular mechanism has not been clearly identified at a genome-wide level. Methods By using a microarray, we analyzed the temporal changes of messenger RNA (mRNA) and microRNA expression in primary mouse hepatocytes after SST treatment. The pattern of genes regulated by SST was identified by using time-series microarray analysis. The biological function of genes was measured by pathway analysis. For the identification of the exact targets of the microRNAs, a permutation-based correlation method was implemented in which the temporal expression of mRNAs and microRNAs were integrated. The similarity of the promoter structure between temporally regulated genes was measured by analyzing the transcription factor binding sites in the promoter region. Results The SST-regulated gene expression had two major patterns: (1) a temporally up-regulated pattern (463 genes) and (2) a temporally down-regulated pattern (177 genes). The integration of the genes and microRNA demonstrated that 155 genes could be the targets of microRNAs from the temporally up-regulated pattern and 19 genes could be the targets of microRNAs from the temporally down-regulated pattern. The temporally up-regulated pattern by SST was associated with signaling pathways such as the cell cycle pathway, whereas the temporally down-regulated pattern included drug metabolism-related pathways and immune-related pathways. All these pathways could be possibly associated with liver regenerative activity of SST. Genes targeted by microRNA were moreover associated with different biological pathways from the genes not targeted by microRNA. An analysis of promoter similarity indicated that co-expressed genes after SST treatment were clustered into subgroups, depending on the temporal expression patterns. Conclusions We are the first to identify that SST regulates temporal gene expression by way of microRNA. MicroRNA targets and non-microRNA targets moreover have different biological roles. This functional segregation by microRNA would be critical for the elucidation of the molecular activities of SST. PMID:24410935

Sho-saiko-to, a traditional herbal medicine, regulates gene expression and biological function by way of microRNAs in primary mouse hepatocytes.

PubMed

Song, Kwang Hoon; Kim, Yun Hee; Kim, Bu-Yeo

2014-01-11

Sho-saiko-to (SST) (also known as so-shi-ho-tang or xiao-chai-hu-tang) has been widely prescribed for chronic liver diseases in traditional Oriental medicine. Despite the substantial amount of clinical evidence for SST, its molecular mechanism has not been clearly identified at a genome-wide level. By using a microarray, we analyzed the temporal changes of messenger RNA (mRNA) and microRNA expression in primary mouse hepatocytes after SST treatment. The pattern of genes regulated by SST was identified by using time-series microarray analysis. The biological function of genes was measured by pathway analysis. For the identification of the exact targets of the microRNAs, a permutation-based correlation method was implemented in which the temporal expression of mRNAs and microRNAs were integrated. The similarity of the promoter structure between temporally regulated genes was measured by analyzing the transcription factor binding sites in the promoter region. The SST-regulated gene expression had two major patterns: (1) a temporally up-regulated pattern (463 genes) and (2) a temporally down-regulated pattern (177 genes). The integration of the genes and microRNA demonstrated that 155 genes could be the targets of microRNAs from the temporally up-regulated pattern and 19 genes could be the targets of microRNAs from the temporally down-regulated pattern. The temporally up-regulated pattern by SST was associated with signaling pathways such as the cell cycle pathway, whereas the temporally down-regulated pattern included drug metabolism-related pathways and immune-related pathways. All these pathways could be possibly associated with liver regenerative activity of SST. Genes targeted by microRNA were moreover associated with different biological pathways from the genes not targeted by microRNA. An analysis of promoter similarity indicated that co-expressed genes after SST treatment were clustered into subgroups, depending on the temporal expression patterns. We are the first to identify that SST regulates temporal gene expression by way of microRNA. MicroRNA targets and non-microRNA targets moreover have different biological roles. This functional segregation by microRNA would be critical for the elucidation of the molecular activities of SST.

Mutation of the murC and murB Genes Impairs Heterocyst Differentiation in Anabaena sp. Strain PCC 7120

PubMed Central

Videau, Patrick; Rivers, Orion S.; Ushijima, Blake; Oshiro, Reid T.; Kim, Min Joo; Philmus, Benjamin

2016-01-01

ABSTRACT To stabilize cellular integrity in the face of environmental perturbations, most bacteria, including cyanobacteria, synthesize and maintain a strong, flexible, three-dimensional peptidoglycan lattice. Anabaena sp. strain PCC 7120 is a filamentous cyanobacterium capable of differentiating morphologically distinct nitrogen-fixing heterocyst cells in a periodic pattern. While heterocyst development has been shown to require proper peptidoglycan remodeling, the role of peptidoglycan synthesis has remained unclear. Here we report the identification of two peptidoglycan synthesis genes, murC (alr5065) and murB (alr5066), as required for heterocyst development. The murC and murB genes are predicted to encode a UDP-N-acetylmuramate:l-alanine ligase and a UDP-N-acetylenolpyruvoylglucosamine reductase, respectively, and we confirm enzymatic function through complementation of Escherichia coli strains deficient for these enzymes. Cells depleted of either murC or murB expression failed to differentiate heterocysts under normally inducing conditions and displayed decreased filament integrity. To identify the stage(s) of development affected by murC or murB depletion, the spatial distribution of expression of the patterning marker gene, patS, was examined. Whereas murB depletion did not affect the pattern of patS expression, murC depletion led to aberrant expression of patS in all cells of the filament. Finally, expression of gfp controlled by the region of DNA immediately upstream of murC was enriched in differentiating cells and was repressed by the transcription factor NtcA. Collectively, the data in this work provide evidence for a direct link between peptidoglycan synthesis and the maintenance of a biological pattern in a multicellular organism. IMPORTANCE Multicellular organisms that differentiate specialized cells must regulate morphological changes such that both cellular integrity and the dissemination of developmental signals are preserved. Here we show that the multicellular bacterium Anabaena, which differentiates a periodic pattern of specialized heterocyst cells, requires peptidoglycan synthesis by the murine ligase genes murC (alr5065) and murB (alr5066) for maintenance of patterned gene expression, filament integrity, and overall development. This work highlights the significant influence that intracellular structure and intercellular connections can have on the execution of a developmental program. PMID:26811320

Mutation of the murC and murB Genes Impairs Heterocyst Differentiation in Anabaena sp. Strain PCC 7120.

PubMed

Videau, Patrick; Rivers, Orion S; Ushijima, Blake; Oshiro, Reid T; Kim, Min Joo; Philmus, Benjamin; Cozy, Loralyn M

2016-04-01

To stabilize cellular integrity in the face of environmental perturbations, most bacteria, including cyanobacteria, synthesize and maintain a strong, flexible, three-dimensional peptidoglycan lattice. Anabaena sp. strain PCC 7120 is a filamentous cyanobacterium capable of differentiating morphologically distinct nitrogen-fixing heterocyst cells in a periodic pattern. While heterocyst development has been shown to require proper peptidoglycan remodeling, the role of peptidoglycan synthesis has remained unclear. Here we report the identification of two peptidoglycan synthesis genes, murC (alr5065) and murB (alr5066), as required for heterocyst development. The murC and murB genes are predicted to encode a UDP-N-acetylmuramate:L-alanine ligase and a UDP-N-acetylenolpyruvoylglucosamine reductase, respectively, and we confirm enzymatic function through complementation of Escherichia coli strains deficient for these enzymes. Cells depleted of either murC or murB expression failed to differentiate heterocysts under normally inducing conditions and displayed decreased filament integrity. To identify the stage(s) of development affected by murC or murB depletion, the spatial distribution of expression of the patterning marker gene, patS, was examined. Whereas murB depletion did not affect the pattern of patS expression, murC depletion led to aberrant expression of patS in all cells of the filament. Finally, expression of gfp controlled by the region of DNA immediately upstream of murC was enriched in differentiating cells and was repressed by the transcription factor NtcA. Collectively, the data in this work provide evidence for a direct link between peptidoglycan synthesis and the maintenance of a biological pattern in a multicellular organism. Multicellular organisms that differentiate specialized cells must regulate morphological changes such that both cellular integrity and the dissemination of developmental signals are preserved. Here we show that the multicellular bacterium Anabaena, which differentiates a periodic pattern of specialized heterocyst cells, requires peptidoglycan synthesis by the murine ligase genes murC (alr5065) and murB (alr5066) for maintenance of patterned gene expression, filament integrity, and overall development. This work highlights the significant influence that intracellular structure and intercellular connections can have on the execution of a developmental program. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Identification and comprehensive evaluation of reference genes for RT-qPCR analysis of host gene-expression in Brassica juncea-aphid interaction using microarray data.

PubMed

Ram, Chet; Koramutla, Murali Krishna; Bhattacharya, Ramcharan

2017-07-01

Brassica juncea is a chief oil yielding crop in many parts of the world including India. With advancement of molecular techniques, RT-qPCR based study of gene-expression has become an integral part of experimentations in crop breeding. In RT-qPCR, use of appropriate reference gene(s) is pivotal. The virtue of the reference genes, being constant in expression throughout the experimental treatments, needs to be validated case by case. Appropriate reference gene(s) for normalization of gene-expression data in B. juncea during the biotic stress of aphid infestation is not known. In the present investigation, 11 reference genes identified from microarray database of Arabidopsis-aphid interaction at a cut off FDR ≤0.1, along with two known reference genes of B. juncea, were analyzed for their expression stability upon aphid infestation. These included 6 frequently used and 5 newly identified reference genes. Ranking orders of the reference genes in terms of expression stability were calculated using advanced statistical approaches such as geNorm, NormFinder, delta Ct and BestKeeper. The analysis suggested CAC, TUA and DUF179 as the most suitable reference genes. Further, normalization of the gene-expression data of STP4 and PR1 by the most and the least stable reference gene, respectively has demonstrated importance and applicability of the recommended reference genes in aphid infested samples of B. juncea. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Common Viral Integration Sites Identified in Avian Leukosis Virus-Induced B-Cell Lymphomas

PubMed Central

Justice, James F.; Morgan, Robin W.

2015-01-01

ABSTRACT Avian leukosis virus (ALV) induces B-cell lymphoma and other neoplasms in chickens by integrating within or near cancer genes and perturbing their expression. Four genes—MYC, MYB, Mir-155, and TERT—have previously been identified as common integration sites in these virus-induced lymphomas and are thought to play a causal role in tumorigenesis. In this study, we employ high-throughput sequencing to identify additional genes driving tumorigenesis in ALV-induced B-cell lymphomas. In addition to the four genes implicated previously, we identify other genes as common integration sites, including TNFRSF1A, MEF2C, CTDSPL, TAB2, RUNX1, MLL5, CXorf57, and BACH2. We also analyze the genome-wide ALV integration landscape in vivo and find increased frequency of ALV integration near transcriptional start sites and within transcripts. Previous work has shown ALV prefers a weak consensus sequence for integration in cultured human cells. We confirm this consensus sequence for ALV integration in vivo in the chicken genome. PMID:26670384

Differential Sensitivity of Target Genes to Translational Repression by miR-17~92

PubMed Central

Jin, Hyun Yong; Oda, Hiroyo; Chen, Pengda; Kang, Seung Goo; Valentine, Elizabeth; Liao, Lujian; Zhang, Yaoyang; Gonzalez-Martin, Alicia; Shepherd, Jovan; Head, Steven R.; Kim, Pyeung-Hyeun; Fu, Guo; Liu, Wen-Hsien; Han, Jiahuai

2017-01-01

MicroRNAs (miRNAs) are thought to exert their functions by modulating the expression of hundreds of target genes and each to a small degree, but it remains unclear how small changes in hundreds of target genes are translated into the specific function of a miRNA. Here, we conducted an integrated analysis of transcriptome and translatome of primary B cells from mutant mice expressing miR-17~92 at three different levels to address this issue. We found that target genes exhibit differential sensitivity to miRNA suppression and that only a small fraction of target genes are actually suppressed by a given concentration of miRNA under physiological conditions. Transgenic expression and deletion of the same miRNA gene regulate largely distinct sets of target genes. miR-17~92 controls target gene expression mainly through translational repression and 5’UTR plays an important role in regulating target gene sensitivity to miRNA suppression. These findings provide molecular insights into a model in which miRNAs exert their specific functions through a small number of key target genes. PMID:28241004

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study

PubMed Central

Ross-Adams, H.; Lamb, A.D.; Dunning, M.J.; Halim, S.; Lindberg, J.; Massie, C.M.; Egevad, L.A.; Russell, R.; Ramos-Montoya, A.; Vowler, S.L.; Sharma, N.L.; Kay, J.; Whitaker, H.; Clark, J.; Hurst, R.; Gnanapragasam, V.J.; Shah, N.C.; Warren, A.Y.; Cooper, C.S.; Lynch, A.G.; Stark, R.; Mills, I.G.; Grönberg, H.; Neal, D.E.

2015-01-01

Background Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts. PMID:26501111

Androgen-responsive gene database: integrated knowledge on androgen-responsive genes.

PubMed

Jiang, Mei; Ma, Yunsheng; Chen, Congcong; Fu, Xuping; Yang, Shu; Li, Xia; Yu, Guohua; Mao, Yumin; Xie, Yi; Li, Yao

2009-11-01

Androgen signaling plays an important role in many biological processes. Androgen Responsive Gene Database (ARGDB) is devoted to providing integrated knowledge on androgen-controlled genes. Gene records were collected on the basis of PubMed literature collections. More than 6000 abstracts and 950 original publications were manually screened, leading to 1785 human genes, 993 mouse genes, and 583 rat genes finally included in the database. All the collected genes were experimentally proved to be regulated by androgen at the expression level or to contain androgen-responsive regions. For each gene important details of the androgen regulation experiments were collected from references, such as expression change, androgen-responsive sequence, response time, tissue/cell type, experimental method, ligand identity, and androgen amount, which will facilitate further evaluation by researchers. Furthermore, the database was integrated with multiple annotation resources, including National Center for Biotechnology Information, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathway, to reveal the biological characteristics and significance of androgen-regulated genes. The ARGDB web site is mainly composed of the Browse, Search, Element Scan, and Submission modules. It is user friendly and freely accessible at http://argdb.fudan.edu.cn. Preliminary analysis of the collected data was performed. Many disease pathways, such as prostate carcinogenesis, were found to be enriched in androgen-regulated genes. The discovered androgen-response motifs were similar to those in previous reports. The analysis results are displayed in the web site. In conclusion, ARGDB provides a unified gateway to storage, retrieval, and update of information on androgen-regulated genes.

Gene Trapping Using Gal4 in Zebrafish

PubMed Central

Balciuniene, Jorune; Balciunas, Darius

2013-01-01

Large clutch size and external development of optically transparent embryos make zebrafish an exceptional vertebrate model system for in vivo insertional mutagenesis using fluorescent reporters to tag expression of mutated genes. Several laboratories have constructed and tested enhancer- and gene-trap vectors in zebrafish, using fluorescent proteins, Gal4- and lexA- based transcriptional activators as reporters 1-7. These vectors had two potential drawbacks: suboptimal stringency (e.g. lack of ability to differentiate between enhancer- and gene-trap events) and low mutagenicity (e.g. integrations into genes rarely produced null alleles). Gene Breaking Transposon (GBTs) were developed to address these drawbacks 8-10. We have modified one of the first GBT vectors, GBT-R15, for use with Gal4-VP16 as the primary gene trap reporter and added UAS:eGFP as the secondary reporter for direct detection of gene trap events. Application of Gal4-VP16 as the primary gene trap reporter provides two main advantages. First, it increases sensitivity for genes expressed at low expression levels. Second, it enables researchers to use gene trap lines as Gal4 drivers to direct expression of other transgenes in very specific tissues. This is especially pertinent for genes with non-essential or redundant functions, where gene trap integration may not result in overt phenotypes. The disadvantage of using Gal4-VP16 as the primary gene trap reporter is that genes coding for proteins with N-terminal signal sequences are not amenable to trapping, as the resulting Gal4-VP16 fusion proteins are unlikely to be able to enter the nucleus and activate transcription. Importantly, the use of Gal4-VP16 does not pre-select for nuclear proteins: we recovered gene trap mutations in genes encoding proteins which function in the nucleus, the cytoplasm and the plasma membrane. PMID:24121167

Unveiling network-based functional features through integration of gene expression into protein networks.

PubMed

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

High copy and stable expression of the xylanase XynHB in Saccharomyces cerevisiae by rDNA-mediated integration.

PubMed

Fang, Cheng; Wang, Qinhong; Selvaraj, Jonathan Nimal; Zhou, Yuling; Ma, Lixin; Zhang, Guimin; Ma, Yanhe

2017-08-18

Xylanase is a widely-used additive in baking industry for enhancing dough and bread quality. Several xylanases used in baking industry were expressed in different systems, but their expression in antibiotic free vector system is highly essential and safe. In the present study, an alternative rDNA-mediated technology was developed to increase the copy number of target gene by integrating it into Saccharomyces cerevisiae genome. A xylanase-encoding gene xynHB from Bacillus sp. was cloned into pHBM367H and integrated into S. cerevisiae genome through rDNA-mediated recombination. Exogenous XynHB expressed by recombinant S. cerevisiae strain A13 exhibited higher degradation activity towards xylan than other transformants. The real-time PCR analysis on A13 genome revealed the presence of 13.64 copies of xynHB gene. Though no antibiotics have been used, the genetic stability and the xylanase activity of xynHB remained stable up to 1,011 generations of cultivation. S. cerevisiae strain A13 expressing xylanase reduced the required kneading time and increased the height and diameter of the dough size, which would be safe and effective in baking industry as no antibiotics-resistance risk. The new effective rDNA-mediated technology without using antibiotics here provides a way to clone other food related industrial enzymes for applications.

Emergence of the self-similar property in gene expression dynamics

NASA Astrophysics Data System (ADS)

Ochiai, T.; Nacher, J. C.; Akutsu, T.

2007-08-01

Many theoretical models have recently been proposed to understand the structure of cellular systems composed of various types of elements (e.g., proteins, metabolites and genes) and their interactions. However, the cell is a highly dynamic system with thousands of functional elements fluctuating across temporal states. Therefore, structural analysis alone is not sufficient to reproduce the cell's observed behavior. In this article, we analyze the gene expression dynamics (i.e., how the amount of mRNA molecules in cell fluctuate in time) by using a new constructive approach, which reveals a symmetry embedded in gene expression fluctuations and characterizes the dynamical equation of gene expression (i.e., a specific stochastic differential equation). First, by using experimental data of human and yeast gene expression time series, we found a symmetry in short-time transition probability from time t to time t+1. We call it self-similarity symmetry (i.e., the gene expression short-time fluctuations contain a repeating pattern of smaller and smaller parts that are like the whole, but different in size). Secondly, we reconstruct the global behavior of the observed distribution of gene expression (i.e., scaling-law) and the local behavior of the power-law tail of this distribution. This approach may represent a step forward toward an integrated image of the basic elements of the whole cell.

Bovine sperm separation by Swim-up and density gradients (Percoll and BoviPure): Effect on sperm quality, function and gene expression.

PubMed

Arias, María Elena; Andara, Katherine; Briones, Evelyn; Felmer, Ricardo

2017-06-01

This study assesses the effect of bovine sperm (obtained from three bulls) separation using density gradients (Percoll and BoviPure) and Swim-up on sperm function and gene expression. Sperm evaluations included the plasma membrane integrity (SYBR14/PI), acrosomal integrity (PNA-FITC/PI), oxidative stress (ROS; CH2FDDA), DNA fragmentation (TUNEL assay) and mitochondrial membrane potential (ΔYm; TMRM) using flow cytometry. Sperm motility was evaluated by computer-assisted sperm analysis (CASA) and gene expression using RT-qPCR. The results showed that separation by Percoll achieves a higher proportion of sperm with intact plasma and acrosomal membranes (89.8 and 87.5%, respectively) than the unseparated control (70.3 and 62.4%, respectively), as well as by Swim-up (74.9 and 63.3%, respectively) and BoviPure (83.3 and 80.4%, respectively). No differences were observed in the proportion of spermatozoa with high ΔΨm between Percoll and BoviPure (84.3% and 83.5%, respectively), which were higher than Swim-up and the unseparated control (72.8% and 43.8%, respectively). The ROS levels were higher in the spermatozoa separated by Percoll and no differences were observed in the sperm DNA integrity between all groups. The motility analysis showed that the separation methods improve (p<0.05) total and progressive motility compared to the control, with Percoll proving the most efficient in this regard. Finally, the gene expression analysis of leptin (LEP), aromatase cytochrome P450 (CYP19) and protamine I (PRM1), after validation of 6 reference genes, showed no differences between groups. In conclusion, bovine sperm separation using density gradient improves the parameters of motility and sperm function without affecting the gene expression. Copyright © 2017 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish Academy of Sciences in Olsztyn. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors.

PubMed

Walter, Vonn; Du, Ying; Danilova, Ludmila; Hayward, Michele C; Hayes, D Neil

2018-06-15

Integrated analyses of multiple genomic datatypes are now common in cancer profiling studies. Such data present opportunities for numerous computational experiments, yet analytic pipelines are limited. Tools such as the cBioPortal and Regulome Explorer, although useful, are not easy to access programmatically or to implement locally. Here, we introduce the MVisAGe R package, which allows users to quantify gene-level associations between two genomic datatypes to investigate the effect of genomic alterations (e.g., DNA copy number changes on gene expression). Visualizing Pearson/Spearman correlation coefficients according to the genomic positions of the underlying genes provides a powerful yet novel tool for conducting exploratory analyses. We demonstrate its utility by analyzing three publicly available cancer datasets. Our approach highlights canonical oncogenes in chr11q13 that displayed the strongest associations between expression and copy number, including CCND1 and CTTN , genes not identified by copy number analysis in the primary reports. We demonstrate highly concordant usage of shared oncogenes on chr3q, yet strikingly diverse oncogene usage on chr11q as a function of HPV infection status. Regions of chr19 that display remarkable associations between methylation and gene expression were identified, as were previously unreported miRNA-gene expression associations that may contribute to the epithelial-to-mesenchymal transition. Significance: This study presents an important bioinformatics tool that will enable integrated analyses of multiple genomic datatypes. Cancer Res; 78(12); 3375-85. ©2018 AACR . ©2018 American Association for Cancer Research.

Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies

PubMed Central

Yang, Tsun-Po; Beazley, Claude; Montgomery, Stephen B.; Dimas, Antigone S.; Gutierrez-Arcelus, Maria; Stranger, Barbara E.; Deloukas, Panos; Dermitzakis, Emmanouil T.

2010-01-01

Summary: Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols. Availability: http://www.sanger.ac.uk/resources/software/genevar Contact: emmanouil.dermitzakis@unige.ch PMID:20702402

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

PubMed

Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs.

PubMed

Jouffe, Vincent; Rowe, Suzanne; Liaubet, Laurence; Buitenhuis, Bart; Hornshøj, Henrik; SanCristobal, Magali; Mormède, Pierre; de Koning, D J

2009-07-16

Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide a limited selection of candidate genes. Here we provide a case study where we explore ways to integrate QTL data and microarray data for the pig, which has only a partial genome sequence. We outline various procedures to localize differentially expressed genes on the pig genome and link this with information on published QTL. The starting point is a set of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH). Different approaches to localize the differentially expressed (DE) genes to the pig genome showed different levels of success and a clear lack of concordance for some genes between the various approaches. For a focused analysis on 12 genes, overlapping QTL from the public domain were presented. Also, differentially expressed genes underlying QTL for ACTH response were described. Using the latest version of the draft sequence, the differentially expressed genes were mapped to the pig genome. This enabled co-location of DE genes and previously studied QTL regions, but the draft genome sequence is still incomplete and will contain many errors. A further step to explore links between DE genes and QTL at the pathway level was largely unsuccessful due to the lack of annotation of the pig genome. This could be improved by further comparative mapping analyses but this would be time consuming. This paper provides a case study for the integration of QTL data and microarray data for a species with limited genome sequence information and annotation. The results illustrate the challenges that must be addressed but also provide a roadmap for future work that is applicable to other non-model species.

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging.

PubMed

Gryglewski, Gregor; Seiger, René; James, Gregory Miles; Godbersen, Godber Mathis; Komorowski, Arkadiusz; Unterholzner, Jakob; Michenthaler, Paul; Hahn, Andreas; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert

2018-08-01

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl- 11 C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level. Copyright © 2018 Elsevier Inc. All rights reserved.

HisB as novel selection marker for gene targeting approaches in Aspergillus niger.

PubMed

Fiedler, Markus R M; Gensheimer, Tarek; Kubisch, Christin; Meyer, Vera

2017-03-08

For Aspergillus niger, a broad set of auxotrophic and dominant resistance markers is available. However, only few offer targeted modification of a gene of interest into or at a genomic locus of choice, which hampers functional genomics studies. We thus aimed to extend the available set by generating a histidine auxotrophic strain with a characterized hisB locus for targeted gene integration and deletion in A. niger. A histidine-auxotrophic strain was established via disruption of the A. niger hisB gene by using the counterselectable pyrG marker. After curing, a hisB - , pyrG - strain was obtained, which served as recipient strain for further studies. We show here that both hisB orthologs from A. nidulans and A. niger can be used to reestablish histidine prototrophy in this recipient strain. Whereas the hisB gene from A. nidulans was suitable for efficient gene targeting at different loci in A. niger, the hisB gene from A. niger allowed efficient integration of a Tet-on driven luciferase reporter construct at the endogenous non-functional hisB locus. Subsequent analysis of the luciferase activity revealed that the hisB locus is tight under non-inducing conditions and allows even higher luciferase expression levels compared to the pyrG integration locus. Taken together, we provide here an alternative selection marker for A. niger, hisB, which allows efficient homologous integration rates as well as high expression levels which compare favorably to the well-established pyrG selection marker.

Cell-Type Specific Features of Circular RNA Expression

PubMed Central

Salzman, Julia; Chen, Raymond E.; Olsen, Mari N.; Wang, Peter L.; Brown, Patrick O.

2013-01-01

Thousands of loci in the human and mouse genomes give rise to circular RNA transcripts; at many of these loci, the predominant RNA isoform is a circle. Using an improved computational approach for circular RNA identification, we found widespread circular RNA expression in Drosophila melanogaster and estimate that in humans, circular RNA may account for 1% as many molecules as poly(A) RNA. Analysis of data from the ENCODE consortium revealed that the repertoire of genes expressing circular RNA, the ratio of circular to linear transcripts for each gene, and even the pattern of splice isoforms of circular RNAs from each gene were cell-type specific. These results suggest that biogenesis of circular RNA is an integral, conserved, and regulated feature of the gene expression program. PMID:24039610

Integrating mRNA and miRNA Weighted Gene Co-Expression Networks with eQTLs in the Nucleus Accumbens of Subjects with Alcohol Dependence

PubMed Central

Blevins, Tana; Aliev, Fazil; Adkins, Amy; Hack, Laura; Bigdeli, Tim; D. van der Vaart, Andrew; Web, Bradley Todd; Bacanu, Silviu-Alin; Kalsi, Gursharan; Kendler, Kenneth S.; Miles, Michael F.; Dick, Danielle; Riley, Brien P.; Dumur, Catherine; Vladimirov, Vladimir I.

2015-01-01

Alcohol consumption is known to lead to gene expression changes in the brain. After performing weighted gene co-expression network analyses (WGCNA) on genome-wide mRNA and microRNA (miRNA) expression in Nucleus Accumbens (NAc) of subjects with alcohol dependence (AD; N = 18) and of matched controls (N = 18), six mRNA and three miRNA modules significantly correlated with AD were identified (Bonferoni-adj. p≤ 0.05). Cell-type-specific transcriptome analyses revealed two of the mRNA modules to be enriched for neuronal specific marker genes and downregulated in AD, whereas the remaining four mRNA modules were enriched for astrocyte and microglial specific marker genes and upregulated in AD. Gene set enrichment analysis demonstrated that neuronal specific modules were enriched for genes involved in oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling. Glial-specific modules were predominantly enriched for genes involved in processes related to immune functions, i.e. cytokine signaling (all adj. p≤ 0.05). In mRNA and miRNA modules, 461 and 25 candidate hub genes were identified, respectively. In contrast to the expected biological functions of miRNAs, correlation analyses between mRNA and miRNA hub genes revealed a higher number of positive than negative correlations (χ2 test p≤ 0.0001). Integration of hub gene expression with genome-wide genotypic data resulted in 591 mRNA cis-eQTLs and 62 miRNA cis-eQTLs. mRNA cis-eQTLs were significantly enriched for AD diagnosis and AD symptom counts (adj. p = 0.014 and p = 0.024, respectively) in AD GWAS signals in a large, independent genetic sample from the Collaborative Study on Genetics of Alcohol (COGA). In conclusion, our study identified putative gene network hubs coordinating mRNA and miRNA co-expression changes in the NAc of AD subjects, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD. PMID:26381263

Expression of Duplicate msa Genes in the Salmonid Pathogen Renibacterium salmoninarum

PubMed Central

Rhodes, Linda D.; Coady, Alison M.; Strom, Mark S.

2002-01-01

Renibacterium salmoninarum is a gram-positive bacterium responsible for bacterial kidney disease of salmon and trout. R. salmoninarum has two identical copies of the gene encoding major soluble antigen (MSA), an immunodominant, extracellular protein. To determine whether one or both copies of msa are expressed, reporter plasmids encoding a fusion of MSA and green fluorescent protein controlled by 0.6 kb of promoter region from msa1 or msa2 were constructed and introduced into R. salmoninarum. Single copies of the reporter plasmids integrated into the chromosome by homologous recombination. Expression of mRNA and protein from the integrated plasmids was detected, and transformed cells were fluorescent, demonstrating that both msa1 and msa2 are expressed under in vitro conditions. This is the first report of successful transformation and homologous recombination in R. salmoninarum. PMID:12406741

Expressing genes do not forget their LINEs: transposable elements and gene expression

PubMed Central

Kines, Kristine J.; Belancio, Victoria P.

2012-01-01

1. ABSTRACT Historically the accumulated mass of mammalian transposable elements (TEs), particularly those located within gene boundaries, was viewed as a genetic burden potentially detrimental to the genomic landscape. This notion has been strengthened by the discovery that transposable sequences can alter the architecture of the transcriptome, not only through insertion, but also long after the integration process is completed. Insertions previously considered harmless are now known to impact the expression of host genes via modification of the transcript quality or quantity, transcriptional interference, or by the control of pathways that affect the mRNA life-cycle. Conversely, several examples of the evolutionary advantageous impact of TEs on the host gene structure that diversified the cellular transcriptome are reported. TE-induced changes in gene expression can be tissue-or disease-specific, raising the possibility that the impact of TE sequences may vary during development, among normal cell types, and between normal and disease-affected tissues. The understanding of the rules and abundance of TE-interference with gene expression is in its infancy, and its contribution to human disease and/or evolution remains largely unexplored. PMID:22201807

Strategies used for genetically modifying bacterial genome: ite-directed mutagenesis, gene inactivation, and gene over-expression*

PubMed Central

Xu, Jian-zhong; Zhang, Wei-guo

2016-01-01

With the availability of the whole genome sequence of Escherichia coli or Corynebacterium glutamicum, strategies for directed DNA manipulation have developed rapidly. DNA manipulation plays an important role in understanding the function of genes and in constructing novel engineering bacteria according to requirement. DNA manipulation involves modifying the autologous genes and expressing the heterogenous genes. Two alternative approaches, using electroporation linear DNA or recombinant suicide plasmid, allow a wide variety of DNA manipulation. However, the over-expression of the desired gene is generally executed via plasmid-mediation. The current review summarizes the common strategies used for genetically modifying E. coli and C. glutamicum genomes, and discusses the technical problem of multi-layered DNA manipulation. Strategies for gene over-expression via integrating into genome are proposed. This review is intended to be an accessible introduction to DNA manipulation within the bacterial genome for novices and a source of the latest experimental information for experienced investigators. PMID:26834010

Transgenesis in fish.

PubMed

Houdebine, L M; Chourrout, D

1991-09-15

Gene transfer into fish embryo is being performed in several species (trout, salmon, carps, tilapia, medaka, goldfish, zebrafish, loach, catfish, etc.). In most cases, pronuclei are not visible and microinjection must be done into the cytoplasm of early embryos. Several million copies of the gene are generally injected. In medaka, transgenesis was attempted by injection of the foreign gene into the nucleus of oocyte. Several reports indicate that the injected DNA was rapidly replicated in the early phase of embryo development, regardless of the origin and the sequence of the foreign DNA. The survival of the injected embryos was reasonably good and a large number reached maturity. The proportion of transgenic animals ranged from 1 to 50% or more, according to species and to experimentators. The reasons for this discrepancy have not been elucidated. In all species, the transgenic animals were mosaic. The copy number of the foreign DNA was different in the various tissues of an animal and a proportion lower than 50% of F1 offsprings received the gene from their parents. This suggests that the foreign DNA was integrated into the fish genome at the two cells stage or later. An examination of the integrated DNA in different cell types of an animal revealed that integration occurred mainly during early development. The transgene was found essentially unrearranged in the fish genome of the founders and offsprings. The transgenes were therefore stably transmitted to progeny in a Mendelian fashion. Southern blot analysis revealed the presence of possible junction fragments and also of minor bands which may result from a rearrangement of the injected DNA. In all species, the integrated DNA appeared mainly as random end-to-end concatemers. In adult trout blood cells, a small proportion of the foreign DNA was maintained in the form of non-integrated concatemers, as judged by the existence of end fragments. The transgenes were generally only poorly expressed. The majority of the injected gene constructs contained essentially mammalian or higher vertebrates sequences. The comparison of the expression efficiency of these constructs in transfected fish and mammalian cells indicates that some of the mammalian DNA sequences are most efficiently understood by the fish cell machinery. Chloramphenicol acetyl transferase gene under the control of promoters from Rous sarcoma virus, and human cytomegalovirus, was expressed in several tissues of transgenic fish. Chicken delta-crystallin gene was expressed in several tissues of transgenic fish.(ABSTRACT TRUNCATED AT 400 WORDS)

Integrated molecular portrait of non-small cell lung cancers

PubMed Central

2013-01-01

Background Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC. Methods Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC. Results At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of ~800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944. Conclusions Integrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes. PMID:24299561

A direct comparison of two nonviral gene therapy vectors for somatic integration: in vivo evaluation of the bacteriophage integrase phiC31 and the Sleeping Beauty transposase.

PubMed

Ehrhardt, Anja; Xu, Hui; Huang, Zan; Engler, Jeffrey A; Kay, Mark A

2005-05-01

In this study we performed a head-to-head comparison of the integrase phiC31 derived from a Streptomyces phage and the Sleeping Beauty (SB) transposase, a member of the TC1/mariner superfamily of transposable elements. Mouse liver was cotransfused with a vector containing our most robust human coagulation factor IX expression cassette and the appropriate recombinase recognition site and either a phiC31- or a SB transposase-expressing vector. To analyze transgene persistence and to prove somatic integration in vivo we induced cell cycling of mouse hepatocytes and found that the transgene expression levels dropped by only 16 to 21% and 56 to 66% in mice that received phiC31 and SB, respectively. Notably, no difference in the toxicity profile was detected in mice treated with either recombinase. Moreover we observed that with the integrase-mediated gene transfer, transgene expression levels were dependent on the remaining noncoding vector sequences, which also integrate into the host genome. Further analyses of a hot spot of integration after phiC31-mediated integration revealed small chromosomal deletions at the target site and that the recombination process was not dependent on the orientation in which the phiC31 recognition site attached to the pseudo-recognition sites in the host genome. Coupled together with ongoing improvements in both systems this study suggests that both nonviral vector systems will have important roles in achieving stable gene transfer in vivo.

A big data pipeline: Identifying dynamic gene regulatory networks from time-course Gene Expression Omnibus data with applications to influenza infection.

PubMed

Carey, Michelle; Ramírez, Juan Camilo; Wu, Shuang; Wu, Hulin

2018-07-01

A biological host response to an external stimulus or intervention such as a disease or infection is a dynamic process, which is regulated by an intricate network of many genes and their products. Understanding the dynamics of this gene regulatory network allows us to infer the mechanisms involved in a host response to an external stimulus, and hence aids the discovery of biomarkers of phenotype and biological function. In this article, we propose a modeling/analysis pipeline for dynamic gene expression data, called Pipeline4DGEData, which consists of a series of statistical modeling techniques to construct dynamic gene regulatory networks from the large volumes of high-dimensional time-course gene expression data that are freely available in the Gene Expression Omnibus repository. This pipeline has a consistent and scalable structure that allows it to simultaneously analyze a large number of time-course gene expression data sets, and then integrate the results across different studies. We apply the proposed pipeline to influenza infection data from nine studies and demonstrate that interesting biological findings can be discovered with its implementation.

CGI: Java Software for Mapping and Visualizing Data from Array-based Comparative Genomic Hybridization and Expression Profiling

PubMed Central

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H.; Lau, Ching C.; Behl, Sanjiv; Man, Tsz-Kwong

2007-01-01

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License. PMID:19936083

CGI: Java software for mapping and visualizing data from array-based comparative genomic hybridization and expression profiling.

PubMed

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H; Lau, Ching C; Behl, Sanjiv; Man, Tsz-Kwong

2007-10-06

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.

Binary Gene Expression Patterning of the Molt Cycle: The Case of Chitin Metabolism

PubMed Central

Abehsera, Shai; Glazer, Lilah; Tynyakov, Jenny; Plaschkes, Inbar; Chalifa-Caspi, Vered; Khalaila, Isam; Aflalo, Eliahu D.; Sagi, Amir

2015-01-01

In crustaceans, like all arthropods, growth is accompanied by a molting cycle. This cycle comprises major physiological events in which mineralized chitinous structures are built and degraded. These events are in turn governed by genes whose patterns of expression are presumably linked to the molting cycle. To study these genes we performed next generation sequencing and constructed a molt-related transcriptomic library from two exoskeletal-forming tissues of the crayfish Cherax quadricarinatus, namely the gastrolith and the mandible cuticle-forming epithelium. To simplify the study of such a complex process as molting, a novel approach, binary patterning of gene expression, was employed. This approach revealed that key genes involved in the synthesis and breakdown of chitin exhibit a molt-related pattern in the gastrolith-forming epithelium. On the other hand, the same genes in the mandible cuticle-forming epithelium showed a molt-independent pattern of expression. Genes related to the metabolism of glucosamine-6-phosphate, a chitin precursor synthesized from simple sugars, showed a molt-related pattern of expression in both tissues. The binary patterning approach unfolds typical patterns of gene expression during the molt cycle of a crustacean. The use of such a simplifying integrative tool for assessing gene patterning seems appropriate for the study of complex biological processes. PMID:25919476

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

PubMed

Dumas, Marc-Emmanuel; Domange, Céline; Calderari, Sophie; Martínez, Andrea Rodríguez; Ayala, Rafael; Wilder, Steven P; Suárez-Zamorano, Nicolas; Collins, Stephan C; Wallis, Robert H; Gu, Quan; Wang, Yulan; Hue, Christophe; Otto, Georg W; Argoud, Karène; Navratil, Vincent; Mitchell, Steve C; Lindon, John C; Holmes, Elaine; Cazier, Jean-Baptiste; Nicholson, Jeremy K; Gauguier, Dominique

2016-09-30

The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. We used systematic metabotyping by 1 H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing. These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.

Integrative topological analysis of mass spectrometry data reveals molecular features with clinical relevance in esophageal squamous cell carcinoma

PubMed Central

Gao, She-Gan; Liu, Rui-Min; Zhao, Yun-Gang; Wang, Pei; Ward, Douglas G.; Wang, Guang-Chao; Guo, Xiang-Qian; Gu, Juan; Niu, Wan-Bin; Zhang, Tian; Martin, Ashley; Guo, Zhi-Peng; Feng, Xiao-Shan; Qi, Yi-Jun; Ma, Yuan-Fang

2016-01-01

Combining MS-based proteomic data with network and topological features of such network would identify more clinically relevant molecules and meaningfully expand the repertoire of proteins derived from MS analysis. The integrative topological indexes representing 95.96% information of seven individual topological measures of node proteins were calculated within a protein-protein interaction (PPI) network, built using 244 differentially expressed proteins (DEPs) identified by iTRAQ 2D-LC-MS/MS. Compared with DEPs, differentially expressed genes (DEGs) and comprehensive features (CFs), structurally dominant nodes (SDNs) based on integrative topological index distribution produced comparable classification performance in three different clinical settings using five independent gene expression data sets. The signature molecules of SDN-based classifier for distinction of early from late clinical TNM stages were enriched in biological traits of protein synthesis, intracellular localization and ribosome biogenesis, which suggests that ribosome biogenesis represents a promising therapeutic target for treating ESCC. In addition, ITGB1 expression selected exclusively by integrative topological measures correlated with clinical stages and prognosis, which was further validated with two independent cohorts of ESCC samples. Thus the integrative topological analysis of PPI networks proposed in this study provides an alternative approach to identify potential biomarkers and therapeutic targets from MS/MS data with functional insights in ESCC. PMID:26898710

Transcriptomic correlates of neuron electrophysiological diversity

PubMed Central

Li, Brenna; Crichlow, Cindy-Lee; Mancarci, B. Ogan; Pavlidis, Paul

2017-01-01

How neuronal diversity emerges from complex patterns of gene expression remains poorly understood. Here we present an approach to understand electrophysiological diversity through gene expression by integrating pooled- and single-cell transcriptomics with intracellular electrophysiology. Using neuroinformatics methods, we compiled a brain-wide dataset of 34 neuron types with paired gene expression and intrinsic electrophysiological features from publically accessible sources, the largest such collection to date. We identified 420 genes whose expression levels significantly correlated with variability in one or more of 11 physiological parameters. We next trained statistical models to infer cellular features from multivariate gene expression patterns. Such models were predictive of gene-electrophysiological relationships in an independent collection of 12 visual cortex cell types from the Allen Institute, suggesting that these correlations might reflect general principles relating expression patterns to phenotypic diversity across very different cell types. Many associations reported here have the potential to provide new insights into how neurons generate functional diversity, and correlations of ion channel genes like Gabrd and Scn1a (Nav1.1) with resting potential and spiking frequency are consistent with known causal mechanisms. Our work highlights the promise and inherent challenges in using cell type-specific transcriptomics to understand the mechanistic origins of neuronal diversity. PMID:29069078

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

PubMed Central

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

2005-01-01

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

Integrating Molecular Imaging Approaches to Monitor Prostate Targeted Suicide and Anti-angiogenic Gene Therapy

DTIC Science & Technology

2005-02-01

tissue-specific expression of prostate-specific antigen. Cancer Res. 57: 495–499. 11. Schuur, E. R ., Henderson, G . A., Kmetec, L. A., Miller, J. D...Lamparski, H. G ., and Henderson, D. R . (1996). Prostate-specific antigen expression is regulated by an up- stream enhancer. J. Biol. Chem. 271: 7043...5: 223–232. 29. Blasberg, R . G ., and Tjuvajev, J. G . (1999). Herpes simplex virus thymidine kinase as a marker/reporter gene for PET imaging of gene

A transcriptome-based examination of blood group expression

PubMed Central

Noh, S.-J.; Lee, Y.T.; Byrnes, C.; Miller, J.L.

2011-01-01

Over the last two decades, red cell biologists witnessed a vast expansion of genetic-based information pertaining to blood group antigens and their carrier molecules. Genetic progress has led to a better comprehension of the associated antigens. To assist with studies concerning the integrated regulation and function of blood groups, transcript levels for each of the 36 associated genes were studied. Profiles using mRNA from directly sampled reticulocytes and cultured primary erythroblasts are summarized in this report. Transcriptome profiles suggest a highly regulated pattern of blood group gene expression during erythroid differentiation and ontogeny. Approximately one-third of the blood group carrier genes are transcribed in an erythroid-specific fashion. Low-level and indistinct expression was noted for most of the carbohydrate-associated genes. Methods are now being developed to further explore and manipulate expression of the blood group genes at all stages of human erythropoiesis. PMID:20685146

Transgenic tobacco expressing Pinellia ternata agglutinin confers enhanced resistance to aphids.

PubMed

Yao, Jianhong; Pang, Yongzhen; Qi, Huaxiong; Wan, Bingliang; Zhao, Xiuyun; Kong, Weiwen; Sun, Xiaofen; Tang, Kexuan

2003-12-01

Tobacco leaf discs were transformed with a plasmid, pBIPTA, containing the selectable marker neomycin phosphotransferase gene (nptII) and Pinellia ternata agglutinin gene (pta) via Agrobacterium tumefaciens-mediated transformation. Thirty-two independent transgenic tobacco plants were regenerated. PCR and Southern blot analyses confirmed that the pta gene had integrated into the plant genome and northern blot analysis revealed transgene expression at various levels in transgenic plants. Genetic analysis confirmed Mendelian segregation of the transgene in T1 progeny. Insect bioassays showed that transgenic plants expressing PTA inhibited significantly the growth of peach potato aphid (Myzus persicae Sulzer). This is the first report that transgenic plants expressing pta confer enhanced resistance to aphids. Our study indicates that the pta gene can be used as a supplement to the snowdrop (Galanthus nivalis) lectin gene (gna) in the control of aphids, a sap-sucking insect pest causing significant yield losses of crops.

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

PubMed Central

Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel

2013-01-01

Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213

Epigenomics and bolting tolerance in sugar beet genotypes.

PubMed

Hébrard, Claire; Peterson, Daniel G; Willems, Glenda; Delaunay, Alain; Jesson, Béline; Lefèbvre, Marc; Barnes, Steve; Maury, Stéphane

2016-01-01

In sugar beet (Beta vulgaris altissima), bolting tolerance is an essential agronomic trait reflecting the bolting response of genotypes after vernalization. Genes involved in induction of sugar beet bolting have now been identified, and evidence suggests that epigenetic factors are involved in their control. Indeed, the time course and amplitude of DNA methylation variations in the shoot apical meristem have been shown to be critical in inducing sugar beet bolting, and a few functional targets of DNA methylation during vernalization have been identified. However, molecular mechanisms controlling bolting tolerance levels among genotypes are still poorly understood. Here, gene expression and DNA methylation profiles were compared in shoot apical meristems of three bolting-resistant and three bolting-sensitive genotypes after vernalization. Using Cot fractionation followed by 454 sequencing of the isolated low-copy DNA, 6231 contigs were obtained that were used along with public sugar beet DNA sequences to design custom Agilent microarrays for expression (56k) and methylation (244k) analyses. A total of 169 differentially expressed genes and 111 differentially methylated regions were identified between resistant and sensitive vernalized genotypes. Fourteen sequences were both differentially expressed and differentially methylated, with a negative correlation between their methylation and expression levels. Genes involved in cold perception, phytohormone signalling, and flowering induction were over-represented and collectively represent an integrative gene network from environmental perception to bolting induction. Altogether, the data suggest that the genotype-dependent control of DNA methylation and expression of an integrative gene network participate in bolting tolerance in sugar beet, opening up perspectives for crop improvement. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

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

PubMed

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

2018-06-01

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

Exact time-dependent solutions for a self-regulating gene.

PubMed

Ramos, A F; Innocentini, G C P; Hornos, J E M

2011-06-01

The exact time-dependent solution for the stochastic equations governing the behavior of a binary self-regulating gene is presented. Using the generating function technique to rephrase the master equations in terms of partial differential equations, we show that the model is totally integrable and the analytical solutions are the celebrated confluent Heun functions. Self-regulation plays a major role in the control of gene expression, and it is remarkable that such a microscopic model is completely integrable in terms of well-known complex functions.

Dendrobium nobile Lindl. alkaloids regulate metabolism gene expression in livers of mice.

PubMed

Xu, Yun-Yan; Xu, Ya-Sha; Wang, Yuan; Wu, Qin; Lu, Yuan-Fu; Liu, Jie; Shi, Jing-Shan

2017-10-01

In our previous studies, Dendrobium nobile Lindl. alkaloids (DNLA) has been shown to have glucose-lowering and antihyperlipidaemia effects in diabetic rats, in rats fed with high-fat diets, and in mice challenged with adrenaline. This study aimed to examine the effects of DNLA on the expression of glucose and lipid metabolism genes in livers of mice. Mice were given DNLA at doses of 10-80 mg/kg, po for 8 days, and livers were removed for total RNA and protein isolation to perform real-time RT-PCR and Western blot analysis. Dendrobium nobile Lindl. alkaloids increased PGC1α at mRNA and protein levels and increased glucose metabolism gene Glut2 and FoxO1 expression. DNLA also increased the expression of fatty acid β-oxidation genes Acox1 and Cpt1a. The lipid synthesis regulator Srebp1 (sterol regulatory element-binding protein-1) was decreased, while the lipolysis gene ATGL was increased. Interestingly, DNLA increased the expression of antioxidant gene metallothionein-1 and NADPH quinone oxidoreductase-1 (Nqo1) in livers of mice. Western blot on selected proteins confirmed these changes including the increased expression of GLUT4 and PPARα. DNLA has beneficial effects on liver glucose and lipid metabolism gene expressions, and enhances the Nrf2-antioxidant pathway gene expressions, which could play integrated roles in regulating metabolic disorders. © 2017 Royal Pharmaceutical Society.

Integrative analysis for identification of shared markers from various functional cells/tissues for rheumatoid arthritis.

PubMed

Xia, Wei; Wu, Jian; Deng, Fei-Yan; Wu, Long-Fei; Zhang, Yong-Hong; Guo, Yu-Fan; Lei, Shu-Feng

2017-02-01

Rheumatoid arthritis (RA) is a systemic autoimmune disease. So far, it is unclear whether there exist common RA-related genes shared in different tissues/cells. In this study, we conducted an integrative analysis on multiple datasets to identify potential shared genes that are significant in multiple tissues/cells for RA. Seven microarray gene expression datasets representing various RA-related tissues/cells were downloaded from the Gene Expression Omnibus (GEO). Statistical analyses, testing both marginal and joint effects, were conducted to identify significant genes shared in various samples. Followed-up analyses were conducted on functional annotation clustering analysis, protein-protein interaction (PPI) analysis, gene-based association analysis, and ELISA validation analysis in in-house samples. We identified 18 shared significant genes, which were mainly involved in the immune response and chemokine signaling pathway. Among the 18 genes, eight genes (PPBP, PF4, HLA-F, S100A8, RNASEH2A, P2RY6, JAG2, and PCBP1) interact with known RA genes. Two genes (HLA-F and PCBP1) are significant in gene-based association analysis (P = 1.03E-31, P = 1.30E-2, respectively). Additionally, PCBP1 also showed differential protein expression levels in in-house case-control plasma samples (P = 2.60E-2). This study represented the first effort to identify shared RA markers from different functional cells or tissues. The results suggested that one of the shared genes, i.e., PCBP1, is a promising biomarker for RA.

Function, dynamics and evolution of network motif modules in integrated gene regulatory networks of worm and plant.

PubMed

Defoort, Jonas; Van de Peer, Yves; Vermeirssen, Vanessa

2018-06-05

Gene regulatory networks (GRNs) consist of different molecular interactions that closely work together to establish proper gene expression in time and space. Especially in higher eukaryotes, many questions remain on how these interactions collectively coordinate gene regulation. We study high quality GRNs consisting of undirected protein-protein, genetic and homologous interactions, and directed protein-DNA, regulatory and miRNA-mRNA interactions in the worm Caenorhabditis elegans and the plant Arabidopsis thaliana. Our data-integration framework integrates interactions in composite network motifs, clusters these in biologically relevant, higher-order topological network motif modules, overlays these with gene expression profiles and discovers novel connections between modules and regulators. Similar modules exist in the integrated GRNs of worm and plant. We show how experimental or computational methodologies underlying a certain data type impact network topology. Through phylogenetic decomposition, we found that proteins of worm and plant tend to functionally interact with proteins of a similar age, while at the regulatory level TFs favor same age, but also older target genes. Despite some influence of the duplication mode difference, we also observe at the motif and module level for both species a preference for age homogeneity for undirected and age heterogeneity for directed interactions. This leads to a model where novel genes are added together to the GRNs in a specific biological functional context, regulated by one or more TFs that also target older genes in the GRNs. Overall, we detected topological, functional and evolutionary properties of GRNs that are potentially universal in all species.

General theory for integrated analysis of growth, gene, and protein expression in biofilms.

PubMed

Zhang, Tianyu; Pabst, Breana; Klapper, Isaac; Stewart, Philip S

2013-01-01

A theory for analysis and prediction of spatial and temporal patterns of gene and protein expression within microbial biofilms is derived. The theory integrates phenomena of solute reaction and diffusion, microbial growth, mRNA or protein synthesis, biomass advection, and gene transcript or protein turnover. Case studies illustrate the capacity of the theory to simulate heterogeneous spatial patterns and predict microbial activities in biofilms that are qualitatively different from those of planktonic cells. Specific scenarios analyzed include an inducible GFP or fluorescent protein reporter, a denitrification gene repressed by oxygen, an acid stress response gene, and a quorum sensing circuit. It is shown that the patterns of activity revealed by inducible stable fluorescent proteins or reporter unstable proteins overestimate the region of activity. This is due to advective spreading and finite protein turnover rates. In the cases of a gene induced by either limitation for a metabolic substrate or accumulation of a metabolic product, maximal expression is predicted in an internal stratum of the biofilm. A quorum sensing system that includes an oxygen-responsive negative regulator exhibits behavior that is distinct from any stage of a batch planktonic culture. Though here the analyses have been limited to simultaneous interactions of up to two substrates and two genes, the framework applies to arbitrarily large networks of genes and metabolites. Extension of reaction-diffusion modeling in biofilms to the analysis of individual genes and gene networks is an important advance that dovetails with the growing toolkit of molecular and genetic experimental techniques.

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction

PubMed Central

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Objective Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Methods Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Results Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Conclusions Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. PMID:25002459

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction.

PubMed

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Genexpi: a toolset for identifying regulons and validating gene regulatory networks using time-course expression data.

PubMed

Modrák, Martin; Vohradský, Jiří

2018-04-13

Identifying regulons of sigma factors is a vital subtask of gene network inference. Integrating multiple sources of data is essential for correct identification of regulons and complete gene regulatory networks. Time series of expression data measured with microarrays or RNA-seq combined with static binding experiments (e.g., ChIP-seq) or literature mining may be used for inference of sigma factor regulatory networks. We introduce Genexpi: a tool to identify sigma factors by combining candidates obtained from ChIP experiments or literature mining with time-course gene expression data. While Genexpi can be used to infer other types of regulatory interactions, it was designed and validated on real biological data from bacterial regulons. In this paper, we put primary focus on CyGenexpi: a plugin integrating Genexpi with the Cytoscape software for ease of use. As a part of this effort, a plugin for handling time series data in Cytoscape called CyDataseries has been developed and made available. Genexpi is also available as a standalone command line tool and an R package. Genexpi is a useful part of gene network inference toolbox. It provides meaningful information about the composition of regulons and delivers biologically interpretable results.

GTA: a game theoretic approach to identifying cancer subnetwork markers.

PubMed

Farahmand, S; Goliaei, S; Ansari-Pour, N; Razaghi-Moghadam, Z

2016-03-01

The identification of genetic markers (e.g. genes, pathways and subnetworks) for cancer has been one of the most challenging research areas in recent years. A subset of these studies attempt to analyze genome-wide expression profiles to identify markers with high reliability and reusability across independent whole-transcriptome microarray datasets. Therefore, the functional relationships of genes are integrated with their expression data. However, for a more accurate representation of the functional relationships among genes, utilization of the protein-protein interaction network (PPIN) seems to be necessary. Herein, a novel game theoretic approach (GTA) is proposed for the identification of cancer subnetwork markers by integrating genome-wide expression profiles and PPIN. The GTA method was applied to three distinct whole-transcriptome breast cancer datasets to identify the subnetwork markers associated with metastasis. To evaluate the performance of our approach, the identified subnetwork markers were compared with gene-based, pathway-based and network-based markers. We show that GTA is not only capable of identifying robust metastatic markers, it also provides a higher classification performance. In addition, based on these GTA-based subnetworks, we identified a new bonafide candidate gene for breast cancer susceptibility.

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer.

PubMed

White-Al Habeeb, Nicole M A; Ho, Linh T; Olkhov-Mitsel, Ekaterina; Kron, Ken; Pethe, Vaijayanti; Lehman, Melanie; Jovanovic, Lidija; Fleshner, Neil; van der Kwast, Theodorus; Nelson, Colleen C; Bapat, Bharati

2014-09-15

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2'-deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.

Network Security via Biometric Recognition of Patterns of Gene Expression

NASA Technical Reports Server (NTRS)

Shaw, Harry C.

2016-01-01

Molecular biology provides the ability to implement forms of information and network security completely outside the bounds of legacy security protocols and algorithms. This paper addresses an approach which instantiates the power of gene expression for security. Molecular biology provides a rich source of gene expression and regulation mechanisms, which can be adopted to use in the information and electronic communication domains. Conventional security protocols are becoming increasingly vulnerable due to more intensive, highly capable attacks on the underlying mathematics of cryptography. Security protocols are being undermined by social engineering and substandard implementations by IT organizations. Molecular biology can provide countermeasures to these weak points with the current security approaches. Future advances in instruments for analyzing assays will also enable this protocol to advance from one of cryptographic algorithms to an integrated system of cryptographic algorithms and real-time expression and assay of gene expression products.

Prediction of gene expression in embryonic structures of Drosophila melanogaster.

PubMed

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-07-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster

PubMed Central

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-01-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms. PMID:17658945

Identification of optimal reference genes for RT-qPCR in the rat hypothalamus and intestine for the study of obesity.

PubMed

Li, B; Matter, E K; Hoppert, H T; Grayson, B E; Seeley, R J; Sandoval, D A

2014-02-01

Obesity has a complicated metabolic pathology, and defining the underlying mechanisms of obesity requires integrative studies with molecular end points. Real-time quantitative PCR (RT-qPCR) is a powerful tool that has been widely utilized. However, the importance of using carefully validated reference genes in RT-qPCR seems to have been overlooked in obesity-related research. The objective of this study was to select a set of reference genes with stable expressions to be used for RT-qPCR normalization in rats under fasted vs re-fed and chow vs high-fat diet (HFD) conditions. Male long-Evans rats were treated under four conditions: chow/fasted, chow/re-fed, HFD/fasted and HFD/re-fed. Expression stabilities of 13 candidate reference genes were evaluated in the rat hypothalamus, duodenum, jejunum and ileum using the ReFinder software program. The optimal number of reference genes needed for RT-qPCR analyses was determined using geNorm. Using geNorm analysis, we found that it was sufficient to use the two most stably expressed genes as references in RT-qPCR analyses for each tissue under specific experimental conditions. B2M and RPLP0 in the hypothalamus, RPS18 and HMBS in the duodenum, RPLP2 and RPLP0 in the jejunum and RPS18 and YWHAZ in the ileum were the most suitable pairs for a normalization study when the four aforementioned experimental conditions were considered. Our study demonstrates that gene expression levels of reference genes commonly used in obesity-related studies, such as ACTB or RPS18, are altered by changes in acute or chronic energy status. These findings underline the importance of using reference genes that are stable in expression across experimental conditions when studying the rat hypothalamus and intestine, because these tissues have an integral role in the regulation of energy homeostasis. It is our hope that this study will raise awareness among obesity researchers on the essential need for reference gene validation in gene expression studies.

SR proteins in Vertical Integration of Gene Expression from Transcription to RNA Processing to Translation

PubMed Central

Zhong, Xiang-Yang; Wang, Pingping; Han, Joonhee; Rosenfeld, Michael G.; Fu, Xiang-Dong

2009-01-01

Summary SR proteins have been studied extensively as a family of RNA binding proteins that participate in both constitutive and regulated pre-mRNA splicing in mammalian cells. However, SR proteins were first discovered as factors that interact with transcriptionally active chromatin. Recent studies have now uncovered properties that connect these once apparently disparate functions, showing that a subset of SR proteins seem to bind directly to the histone 3 tail, play an active role in transcriptional elongation, and co-localize with genes that are engaged in specific intra- and inter-chromosome interactions for coordinated regulation of gene expression in the nucleus. These transcription-related activities are also coupled with a further expansion of putative functions of specific SR protein family members in RNA metabolism downstream of mRNA splicing, from RNA export to stability control to translation. These findings therefore highlight the broader roles of SR proteins in vertical integration of gene expression and provide mechanistic insights into their contributions to genome stability and proper cell cycle progression in higher eukaryotic cells. PMID:19595711

SR proteins in vertical integration of gene expression from transcription to RNA processing to translation.

PubMed

Zhong, Xiang-Yang; Wang, Pingping; Han, Joonhee; Rosenfeld, Michael G; Fu, Xiang-Dong

2009-07-10

SR proteins have been studied extensively as a family of RNA-binding proteins that participate in both constitutive and regulated pre-mRNA splicing in mammalian cells. However, SR proteins were first discovered as factors that interact with transcriptionally active chromatin. Recent studies have now uncovered properties that connect these once apparently disparate functions, showing that a subset of SR proteins seem to bind directly to the histone 3 tail, play an active role in transcriptional elongation, and colocalize with genes that are engaged in specific intra- and interchromosome interactions for coordinated regulation of gene expression in the nucleus. These transcription-related activities are also coupled with a further expansion of putative functions of specific SR protein family members in RNA metabolism downstream of mRNA splicing, from RNA export to stability control to translation. These findings, therefore, highlight the broader roles of SR proteins in vertical integration of gene expression and provide mechanistic insights into their contributions to genome stability and proper cell-cycle progression in higher eukaryotic cells.

Bioluminescent bioreporter integrated circuit devices and methods for detecting estrogen

DOEpatents

Simpson, Michael L.; Paulus, Michael J.; Sayler, Gary S.; Applegate, Bruce M.; Ripp, Steven A.

2006-08-15

Bioelectronic devices for the detection of estrogen include a collection of eukaryotic cells which harbor a recombinant lux gene from a high temperature microorganism wherein the gene is operably linked with a heterologous promoter gene. A detectable light-emitting lux gene product is expressed in the presence of the estrogen and detected by the device.

TALEN/CRISPR-mediated engineering of a promoterless anti-viral RNAi hairpin into an endogenous miRNA locus

PubMed Central

Senís, Elena; Mockenhaupt, Stefan; Rupp, Daniel; Bauer, Tobias; Paramasivam, Nagarajan; Knapp, Bettina; Gronych, Jan; Grosse, Stefanie; Windisch, Marc P.; Schmidt, Florian; Theis, Fabian J.; Eils, Roland; Lichter, Peter; Schlesner, Matthias; Bartenschlager, Ralf; Grimm, Dirk

2017-01-01

Successful RNAi applications depend on strategies allowing robust and persistent expression of minimal gene silencing triggers without perturbing endogenous gene expression. Here, we propose a novel avenue which is integration of a promoterless shmiRNA, i.e. a shRNA embedded in a micro-RNA (miRNA) scaffold, into an engineered genomic miRNA locus. For proof-of-concept, we used TALE or CRISPR/Cas9 nucleases to site-specifically integrate an anti-hepatitis C virus (HCV) shmiRNA into the liver-specific miR-122/hcr locus in hepatoma cells, with the aim to obtain cellular clones that are genetically protected against HCV infection. Using reporter assays, Northern blotting and qRT-PCR, we confirmed anti-HCV shmiRNA expression as well as miR-122 integrity and functionality in selected cellular progeny. Moreover, we employed a comprehensive battery of PCR, cDNA/miRNA profiling and whole genome sequencing analyses to validate targeted integration of a single shmiRNA molecule at the expected position, and to rule out deleterious effects on the genomes or transcriptomes of the engineered cells. Importantly, a subgenomic HCV replicon and a full-length reporter virus, but not a Dengue virus control, were significantly impaired in the modified cells. Our original combination of DNA engineering and RNAi expression technologies benefits numerous applications, from miRNA, genome and transgenesis research, to human gene therapy. PMID:27614072

A prior-based integrative framework for functional transcriptional regulatory network inference

PubMed Central

Siahpirani, Alireza F.

2017-01-01

Abstract Transcriptional regulatory networks specify regulatory proteins controlling the context-specific expression levels of genes. Inference of genome-wide regulatory networks is central to understanding gene regulation, but remains an open challenge. Expression-based network inference is among the most popular methods to infer regulatory networks, however, networks inferred from such methods have low overlap with experimentally derived (e.g. ChIP-chip and transcription factor (TF) knockouts) networks. Currently we have a limited understanding of this discrepancy. To address this gap, we first develop a regulatory network inference algorithm, based on probabilistic graphical models, to integrate expression with auxiliary datasets supporting a regulatory edge. Second, we comprehensively analyze our and other state-of-the-art methods on different expression perturbation datasets. Networks inferred by integrating sequence-specific motifs with expression have substantially greater agreement with experimentally derived networks, while remaining more predictive of expression than motif-based networks. Our analysis suggests natural genetic variation as the most informative perturbation for network inference, and, identifies core TFs whose targets are predictable from expression. Multiple reasons make the identification of targets of other TFs difficult, including network architecture and insufficient variation of TF mRNA level. Finally, we demonstrate the utility of our inference algorithm to infer stress-specific regulatory networks and for regulator prioritization. PMID:27794550

Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets

PubMed Central

2014-01-01

Background Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. Results We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways. PMID:25221624

A-MADMAN: Annotation-based microarray data meta-analysis tool

PubMed Central

Bisognin, Andrea; Coppe, Alessandro; Ferrari, Francesco; Risso, Davide; Romualdi, Chiara; Bicciato, Silvio; Bortoluzzi, Stefania

2009-01-01

Background Publicly available datasets of microarray gene expression signals represent an unprecedented opportunity for extracting genomic relevant information and validating biological hypotheses. However, the exploitation of this exceptionally rich mine of information is still hampered by the lack of appropriate computational tools, able to overcome the critical issues raised by meta-analysis. Results This work presents A-MADMAN, an open source web application which allows the retrieval, annotation, organization and meta-analysis of gene expression datasets obtained from Gene Expression Omnibus. A-MADMAN addresses and resolves several open issues in the meta-analysis of gene expression data. Conclusion A-MADMAN allows i) the batch retrieval from Gene Expression Omnibus and the local organization of raw data files and of any related meta-information, ii) the re-annotation of samples to fix incomplete, or otherwise inadequate, metadata and to create user-defined batches of data, iii) the integrative analysis of data obtained from different Affymetrix platforms through custom chip definition files and meta-normalization. Software and documentation are available on-line at . PMID:19563634

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions

PubMed Central

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-01-01

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field. DOI: http://dx.doi.org/10.7554/eLife.08411.001 PMID:26609814

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

NASA Technical Reports Server (NTRS)

Eichler, Gabriel S.; Huang, Sui; Ingber, Donald E.

2003-01-01

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/ge/gedihome.html Supplementary information: http://www.chip.org/ge/gedihome.html.

Integrative genomics identifies molecular alterations that challenge the linear model of melanoma progression.

PubMed

Rose, Amy E; Poliseno, Laura; Wang, Jinhua; Clark, Michael; Pearlman, Alexander; Wang, Guimin; Vega Y Saenz de Miera, Eleazar C; Medicherla, Ratna; Christos, Paul J; Shapiro, Richard; Pavlick, Anna; Darvishian, Farbod; Zavadil, Jiri; Polsky, David; Hernando, Eva; Ostrer, Harry; Osman, Iman

2011-04-01

Superficial spreading melanoma (SSM) and nodular melanoma (NM) are believed to represent sequential phases of linear progression from radial to vertical growth. Several lines of clinical, pathologic, and epidemiologic evidence suggest, however, that SSM and NM might be the result of independent pathways of tumor development. We utilized an integrative genomic approach that combines single nucleotide polymorphism array (6.0; Affymetrix) with gene expression array (U133A 2.0; Affymetrix) to examine molecular differences between SSM and NM. Pathway analysis of the most differentially expressed genes between SSM and NM (N = 114) revealed significant differences related to metabolic processes. We identified 8 genes (DIS3, FGFR1OP, G3BP2, GALNT7, MTAP, SEC23IP, USO1, and ZNF668) in which NM/SSM-specific copy number alterations correlated with differential gene expression (P < 0.05; Spearman's rank). SSM-specific genomic deletions in G3BP2, MTAP, and SEC23IP were independently verified in two external data sets. Forced overexpression of metabolism-related gene MTAP (methylthioadenosine phosphorylase) in SSM resulted in reduced cell growth. The differential expression of another metabolic-related gene, aldehyde dehydrogenase 7A1 (ALDH7A1), was validated at the protein level by using tissue microarrays of human melanoma. In addition, we show that the decreased ALDH7A1 expression in SSM may be the result of epigenetic modifications. Our data reveal recurrent genomic deletions in SSM not present in NM, which challenge the linear model of melanoma progression. Furthermore, our data suggest a role for altered regulation of metabolism-related genes as a possible cause of the different clinical behavior of SSM and NM.

Integrative genomics identifies molecular alterations that challenge the linear model of melanoma progression

PubMed Central

Rose, Amy E.; Poliseno, Laura; Wang, Jinhua; Clark, Michael; Pearlman, Alexander; Wang, Guimin; Vega y Saenz de Miera, Eleazar C.; Medicherla, Ratna; Christos, Paul J.; Shapiro, Richard; Pavlick, Anna; Darvishian, Farbod; Zavadil, Jiri; Polsky, David; Hernando, Eva; Ostrer, Harry; Osman, Iman

2011-01-01

Superficial spreading melanoma (SSM) and nodular melanoma (NM) are believed to represent sequential phases of linear progression from radial to vertical growth. Several lines of clinical, pathological and epidemiologic evidence suggest, however, that SSM and NM might be the result of independent pathways of tumor development. We utilized an integrative genomic approach that combines single nucleotide polymorphism array (SNP 6.0, Affymetrix) with gene expression array (U133A 2.0, Affymetrix) to examine molecular differences between SSM and NM. Pathway analysis of the most differentially expressed genes between SSM and NM (N=114) revealed significant differences related to metabolic processes. We identified 8 genes (DIS3, FGFR1OP, G3BP2, GALNT7, MTAP, SEC23IP, USO1, ZNF668) in which NM/SSM-specific copy number alterations correlated with differential gene expression (P<0.05, Spearman’s rank). SSM-specific genomic deletions in G3BP2, MTAP, and SEC23IP were independently verified in two external data sets. Forced overexpression of metabolism-related gene methylthioadenosine phosphorylase (MTAP) in SSM resulted in reduced cell growth. The differential expression of another metabolic related gene, aldehyde dehydrogenase 7A1 (ALDH7A1), was validated at the protein level using tissue microarrays of human melanoma. In addition, we show that the decreased ALDH7A1 expression in SSM may be the result of epigenetic modifications. Our data reveal recurrent genomic deletions in SSM not present in NM, which challenge the linear model of melanoma progression. Furthermore, our data suggest a role for altered regulation of metabolism-related genes as a possible cause of the different clinical behavior of SSM and NM. PMID:21343389

Dynamic modelling of microRNA regulation during mesenchymal stem cell differentiation.

PubMed

Weber, Michael; Sotoca, Ana M; Kupfer, Peter; Guthke, Reinhard; van Zoelen, Everardus J

2013-11-12

Network inference from gene expression data is a typical approach to reconstruct gene regulatory networks. During chondrogenic differentiation of human mesenchymal stem cells (hMSCs), a complex transcriptional network is active and regulates the temporal differentiation progress. As modulators of transcriptional regulation, microRNAs (miRNAs) play a critical role in stem cell differentiation. Integrated network inference aimes at determining interrelations between miRNAs and mRNAs on the basis of expression data as well as miRNA target predictions. We applied the NetGenerator tool in order to infer an integrated gene regulatory network. Time series experiments were performed to measure mRNA and miRNA abundances of TGF-beta1+BMP2 stimulated hMSCs. Network nodes were identified by analysing temporal expression changes, miRNA target gene predictions, time series correlation and literature knowledge. Network inference was performed using NetGenerator to reconstruct a dynamical regulatory model based on the measured data and prior knowledge. The resulting model is robust against noise and shows an optimal trade-off between fitting precision and inclusion of prior knowledge. It predicts the influence of miRNAs on the expression of chondrogenic marker genes and therefore proposes novel regulatory relations in differentiation control. By analysing the inferred network, we identified a previously unknown regulatory effect of miR-524-5p on the expression of the transcription factor SOX9 and the chondrogenic marker genes COL2A1, ACAN and COL10A1. Genome-wide exploration of miRNA-mRNA regulatory relationships is a reasonable approach to identify miRNAs which have so far not been associated with the investigated differentiation process. The NetGenerator tool is able to identify valid gene regulatory networks on the basis of miRNA and mRNA time series data.

Physiologically Shrinking the Solution Space of a Saccharomyces cerevisiae Genome-Scale Model Suggests the Role of the Metabolic Network in Shaping Gene Expression Noise.

PubMed

Chi, Baofang; Tao, Shiheng; Liu, Yanlin

2015-01-01

Sampling the solution space of genome-scale models is generally conducted to determine the feasible region for metabolic flux distribution. Because the region for actual metabolic states resides only in a small fraction of the entire space, it is necessary to shrink the solution space to improve the predictive power of a model. A common strategy is to constrain models by integrating extra datasets such as high-throughput datasets and C13-labeled flux datasets. However, studies refining these approaches by performing a meta-analysis of massive experimental metabolic flux measurements, which are closely linked to cellular phenotypes, are limited. In the present study, experimentally identified metabolic flux data from 96 published reports were systematically reviewed. Several strong associations among metabolic flux phenotypes were observed. These phenotype-phenotype associations at the flux level were quantified and integrated into a Saccharomyces cerevisiae genome-scale model as extra physiological constraints. By sampling the shrunken solution space of the model, the metabolic flux fluctuation level, which is an intrinsic trait of metabolic reactions determined by the network, was estimated and utilized to explore its relationship to gene expression noise. Although no correlation was observed in all enzyme-coding genes, a relationship between metabolic flux fluctuation and expression noise of genes associated with enzyme-dosage sensitive reactions was detected, suggesting that the metabolic network plays a role in shaping gene expression noise. Such correlation was mainly attributed to the genes corresponding to non-essential reactions, rather than essential ones. This was at least partially, due to regulations underlying the flux phenotype-phenotype associations. Altogether, this study proposes a new approach in shrinking the solution space of a genome-scale model, of which sampling provides new insights into gene expression noise.

Guanylate-binding protein-1 is a potential new therapeutic target for triple-negative breast cancer.

PubMed

Quintero, Melissa; Adamoski, Douglas; Reis, Larissa Menezes Dos; Ascenção, Carolline Fernanda Rodrigues; Oliveira, Krishina Ratna Sousa de; Gonçalves, Kaliandra de Almeida; Dias, Marília Meira; Carazzolle, Marcelo Falsarella; Dias, Sandra Martha Gomes

2017-11-07

Triple-negative breast cancer (TNBC) is characterized by a lack of estrogen and progesterone receptor expression (ESR and PGR, respectively) and an absence of human epithelial growth factor receptor (ERBB2) amplification. Approximately 15-20% of breast malignancies are TNBC. Patients with TNBC often have an unfavorable prognosis. In addition, TNBC represents an important clinical challenge since it does not respond to hormone therapy. In this work, we integrated high-throughput mRNA sequencing (RNA-Seq) data from normal and tumor tissues (obtained from The Cancer Genome Atlas, TCGA) and cell lines obtained through in-house sequencing or available from the Gene Expression Omnibus (GEO) to generate a unified list of differentially expressed (DE) genes. Methylome and proteomic data were integrated to our analysis to give further support to our findings. Genes that were overexpressed in TNBC were then curated to retain new potentially druggable targets based on in silico analysis. Knocking-down was used to assess gene importance for TNBC cell proliferation. Our pipeline analysis generated a list of 243 potential new targets for treating TNBC. We finally demonstrated that knock-down of Guanylate-Binding Protein 1 (GBP1 ), one of the candidate genes, selectively affected the growth of TNBC cell lines. Moreover, we showed that GBP1 expression was controlled by epidermal growth factor receptor (EGFR) in breast cancer cell lines. We propose that GBP1 is a new potential druggable therapeutic target for treating TNBC with enhanced EGFR expression.

Biocontrol of the Sugarcane Borer Eldana saccharina by Expression of the Bacillus thuringiensis cry1Ac7 and Serratia marcescens chiA Genes in Sugarcane-Associated Bacteria

PubMed Central

Downing, Katrina J.; Leslie, Graeme; Thomson, Jennifer A.

2000-01-01

The cry1Ac7 gene of Bacillus thuringiensis strain 234, showing activity against the sugarcane borer Eldana saccharina, was cloned under the control of the tac promoter. The fusion was introduced into the broad-host-range plasmid pKT240 and the integration vector pJFF350 and without the tac promoter into the broad-host-range plasmids pML122 and pKmM0. These plasmids were introduced into a Pseudomonas fluorescens strain isolated from the phylloplane of sugarcane and the endophytic bacterium Herbaspirillum seropedicae found in sugarcane. The ptac-cry1Ac7 construct was introduced into the chromosome of P. fluorescens using the integration vector pJFF350 carrying the artificial interposon Omegon-Km. Western blot analysis showed that the expression levels of the integrated cry1Ac7 gene were much higher under the control of the tac promoter than under the control of its endogenous promoter. It was also determined that multicopy expression in P. fluorescens and H. seropedicae of ptac-cry1Ac7 carried on pKT240 caused plasmid instability with no detectable protein expression. In H. seropedicae, more Cry1Ac7 toxin was produced when the gene was cloned under the control of the Nmr promoter on pML122 than in the opposite orientation and bioassays showed that the former resulted in higher mortality of E. saccharina larvae than the latter. P. fluorescens 14::ptac-tox resulted in higher mortality of larvae than did P. fluorescens 14::tox. An increased toxic effect was observed when P. fluorescens 14::ptac-tox was combined with P. fluorescens carrying the Serratia marcescens chitinase gene chiA, under the control of the tac promoter, integrated into the chromosome. PMID:10877771

Genome-wide identification, evolutionary and expression analysis of the aspartic protease gene superfamily in grape

PubMed Central

2013-01-01

Background Aspartic proteases (APs) are a large family of proteolytic enzymes found in almost all organisms. In plants, they are involved in many biological processes, such as senescence, stress responses, programmed cell death, and reproduction. Prior to the present study, no grape AP gene(s) had been reported, and their research on woody species was very limited. Results In this study, a total of 50 AP genes (VvAP) were identified in the grape genome, among which 30 contained the complete ASP domain. Synteny analysis within grape indicated that segmental and tandem duplication events contributed to the expansion of the grape AP family. Additional analysis between grape and Arabidopsis demonstrated that several grape AP genes were found in the corresponding syntenic blocks of Arabidopsis, suggesting that these genes arose before the divergence of grape and Arabidopsis. Phylogenetic relationships of the 30 VvAPs with the complete ASP domain and their Arabidopsis orthologs, as well as their gene and protein features were analyzed and their cellular localization was predicted. Moreover, expression profiles of VvAP genes in six different tissues were determined, and their transcript abundance under various stresses and hormone treatments were measured. Twenty-seven VvAP genes were expressed in at least one of the six tissues examined; nineteen VvAPs responded to at least one abiotic stress, 12 VvAPs responded to powdery mildew infection, and most of the VvAPs responded to SA and ABA treatments. Furthermore, integrated synteny and phylogenetic analysis identified orthologous AP genes between grape and Arabidopsis, providing a unique starting point for investigating the function of grape AP genes. Conclusions The genome-wide identification, evolutionary and expression analyses of grape AP genes provide a framework for future analysis of AP genes in defining their roles during stress response. Integrated synteny and phylogenetic analyses provide novel insight into the functions of less well-studied genes using information from their better understood orthologs. PMID:23945092

Alterations in gene expression and DNA methylation during murine and human lung alveolar septation.

PubMed

Cuna, Alain; Halloran, Brian; Faye-Petersen, Ona; Kelly, David; Crossman, David K; Cui, Xiangqin; Pandit, Kusum; Kaminski, Naftali; Bhattacharya, Soumyaroop; Ahmad, Ausaf; Mariani, Thomas J; Ambalavanan, Namasivayam

2015-07-01

DNA methylation, a major epigenetic mechanism, may regulate coordinated expression of multiple genes at specific time points during alveolar septation in lung development. The objective of this study was to identify genes regulated by methylation during normal septation in mice and during disordered septation in bronchopulmonary dysplasia. In mice, newborn lungs (preseptation) and adult lungs (postseptation) were evaluated by microarray analysis of gene expression and immunoprecipitation of methylated DNA followed by sequencing (MeDIP-Seq). In humans, microarray gene expression data were integrated with genome-wide DNA methylation data from bronchopulmonary dysplasia versus preterm and term lung. Genes with reciprocal changes in expression and methylation, suggesting regulation by DNA methylation, were identified. In mice, 95 genes with inverse correlation between expression and methylation during normal septation were identified. In addition to genes known to be important in lung development (Wnt signaling, Angpt2, Sox9, etc.) and its extracellular matrix (Tnc, Eln, etc.), genes involved with immune and antioxidant defense (Stat4, Sod3, Prdx6, etc.) were also observed. In humans, 23 genes were differentially methylated with reciprocal changes in expression in bronchopulmonary dysplasia compared with preterm or term lung. Genes of interest included those involved with detoxifying enzymes (Gstm3) and transforming growth factor-β signaling (bone morphogenetic protein 7 [Bmp7]). In terms of overlap, 20 genes and three pathways methylated during mouse lung development also demonstrated changes in methylation between preterm and term human lung. Changes in methylation correspond to altered expression of a number of genes associated with lung development, suggesting that DNA methylation of these genes may regulate normal and abnormal alveolar septation.

Expression atlas and comparative coexpression network analyses reveal important genes involved in the formation of lignified cell wall in Brachypodium distachyon.

PubMed

Sibout, Richard; Proost, Sebastian; Hansen, Bjoern Oest; Vaid, Neha; Giorgi, Federico M; Ho-Yue-Kuang, Severine; Legée, Frédéric; Cézart, Laurent; Bouchabké-Coussa, Oumaya; Soulhat, Camille; Provart, Nicholas; Pasha, Asher; Le Bris, Philippe; Roujol, David; Hofte, Herman; Jamet, Elisabeth; Lapierre, Catherine; Persson, Staffan; Mutwil, Marek

2017-08-01

While Brachypodium distachyon (Brachypodium) is an emerging model for grasses, no expression atlas or gene coexpression network is available. Such tools are of high importance to provide insights into the function of Brachypodium genes. We present a detailed Brachypodium expression atlas, capturing gene expression in its major organs at different developmental stages. The data were integrated into a large-scale coexpression database ( www.gene2function.de), enabling identification of duplicated pathways and conserved processes across 10 plant species, thus allowing genome-wide inference of gene function. We highlight the importance of the atlas and the platform through the identification of duplicated cell wall modules, and show that a lignin biosynthesis module is conserved across angiosperms. We identified and functionally characterised a putative ferulate 5-hydroxylase gene through overexpression of it in Brachypodium, which resulted in an increase in lignin syringyl units and reduced lignin content of mature stems, and led to improved saccharification of the stem biomass. Our Brachypodium expression atlas thus provides a powerful resource to reveal functionally related genes, which may advance our understanding of important biological processes in grasses. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Retrotransposons as regulators of gene expression.

PubMed

Elbarbary, Reyad A; Lucas, Bronwyn A; Maquat, Lynne E

2016-02-12

Transposable elements (TEs) are both a boon and a bane to eukaryotic organisms, depending on where they integrate into the genome and how their sequences function once integrated. We focus on two types of TEs: long interspersed elements (LINEs) and short interspersed elements (SINEs). LINEs and SINEs are retrotransposons; that is, they transpose via an RNA intermediate. We discuss how LINEs and SINEs have expanded in eukaryotic genomes and contribute to genome evolution. An emerging body of evidence indicates that LINEs and SINEs function to regulate gene expression by affecting chromatin structure, gene transcription, pre-mRNA processing, or aspects of mRNA metabolism. We also describe how adenosine-to-inosine editing influences SINE function and how ongoing retrotransposition is countered by the body's defense mechanisms. Copyright © 2016, American Association for the Advancement of Science.

Differentially expressed microRNAs in lung adenocarcinoma invert effects of copy number aberrations of prognostic genes

PubMed Central

Tokar, Tomas; Pastrello, Chiara; Ramnarine, Varune R.; Zhu, Chang-Qi; Craddock, Kenneth J.; Pikor, Larrisa A.; Vucic, Emily A.; Vary, Simon; Shepherd, Frances A.; Tsao, Ming-Sound; Lam, Wan L.; Jurisica, Igor

2018-01-01

In many cancers, significantly down- or upregulated genes are found within chromosomal regions with DNA copy number alteration opposite to the expression changes. Generally, this paradox has been overlooked as noise, but can potentially be a consequence of interference of epigenetic regulatory mechanisms, including microRNA-mediated control of mRNA levels. To explore potential associations between microRNAs and paradoxes in non-small-cell lung cancer (NSCLC) we curated and analyzed lung adenocarcinoma (LUAD) data, comprising gene expressions, copy number aberrations (CNAs) and microRNA expressions. We integrated data from 1,062 tumor samples and 241 normal lung samples, including newly-generated array comparative genomic hybridization (aCGH) data from 63 LUAD samples. We identified 85 “paradoxical” genes whose differential expression consistently contrasted with aberrations of their copy numbers. Paradoxical status of 70 out of 85 genes was validated on sample-wise basis using The Cancer Genome Atlas (TCGA) LUAD data. Of these, 41 genes are prognostic and form a clinically relevant signature, which we validated on three independent datasets. By meta-analysis of results from 9 LUAD microRNA expression studies we identified 24 consistently-deregulated microRNAs. Using TCGA-LUAD data we showed that deregulation of 19 of these microRNAs explains differential expression of the paradoxical genes. Our results show that deregulation of paradoxical genes is crucial in LUAD and their expression pattern is maintained epigenetically, defying gene copy number status. PMID:29507679

A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

PubMed

Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

2015-03-01

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Spectral biclustering of microarray data: coclustering genes and conditions.

PubMed

Kluger, Yuval; Basri, Ronen; Chang, Joseph T; Gerstein, Mark

2003-04-01

Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, and one wants to find "marker genes" that are differentially expressed in particular sets of "conditions." We have developed a method that simultaneously clusters genes and conditions, finding distinctive "checkerboard" patterns in matrices of gene expression data, if they exist. In a cancer context, these checkerboards correspond to genes that are markedly up- or downregulated in patients with particular types of tumors. Our method, spectral biclustering, is based on the observation that checkerboard structures in matrices of expression data can be found in eigenvectors corresponding to characteristic expression patterns across genes or conditions. In addition, these eigenvectors can be readily identified by commonly used linear algebra approaches, in particular the singular value decomposition (SVD), coupled with closely integrated normalization steps. We present a number of variants of the approach, depending on whether the normalization over genes and conditions is done independently or in a coupled fashion. We then apply spectral biclustering to a selection of publicly available cancer expression data sets, and examine the degree to which the approach is able to identify checkerboard structures. Furthermore, we compare the performance of our biclustering methods against a number of reasonable benchmarks (e.g., direct application of SVD or normalized cuts to raw data).

Transcriptome profiling of a Saccharomyces cerevisiae mutant with a constitutively activated Ras/cAMP pathway.

PubMed

Jones, D L; Petty, J; Hoyle, D C; Hayes, A; Ragni, E; Popolo, L; Oliver, S G; Stateva, L I

2003-12-16

Often changes in gene expression levels have been considered significant only when above/below some arbitrarily chosen threshold. We investigated the effect of applying a purely statistical approach to microarray analysis and demonstrated that small changes in gene expression have biological significance. Whole genome microarray analysis of a pde2Delta mutant, constructed in the Saccharomyces cerevisiae reference strain FY23, revealed altered expression of approximately 11% of protein encoding genes. The mutant, characterized by constitutive activation of the Ras/cAMP pathway, has increased sensitivity to stress, reduced ability to assimilate nonfermentable carbon sources, and some cell wall integrity defects. Applying the Munich Information Centre for Protein Sequences (MIPS) functional categories revealed increased expression of genes related to ribosome biogenesis and downregulation of genes in the cell rescue, defense, cell death and aging category, suggesting a decreased response to stress conditions. A reduced level of gene expression in the unfolded protein response pathway (UPR) was observed. Cell wall genes whose expression was affected by this mutation were also identified. Several of the cAMP-responsive orphan genes, upon further investigation, revealed cell wall functions; others had previously unidentified phenotypes assigned to them. This investigation provides a statistical global transcriptome analysis of the cellular response to constitutive activation of the Ras/cAMP pathway.

Improvement of Blood-Brain Barrier Integrity in Traumatic Brain Injury and Hemorrhagic Shock Following Treatment With Valproic Acid and Fresh Frozen Plasma.

PubMed

Nikolian, Vahagn C; Dekker, Simone E; Bambakidis, Ted; Higgins, Gerald A; Dennahy, Isabel S; Georgoff, Patrick E; Williams, Aaron M; Andjelkovic, Anuska V; Alam, Hasan B

2018-01-01

Combined traumatic brain injury and hemorrhagic shock are highly lethal. Following injuries, the integrity of the blood-brain barrier can be impaired, contributing to secondary brain insults. The status of the blood-brain barrier represents a potential factor impacting long-term neurologic outcomes in combined injuries. Treatment strategies involving plasma-based resuscitation and valproic acid therapy have shown efficacy in this setting. We hypothesize that a component of this beneficial effect is related to blood-brain barrier preservation. Following controlled traumatic brain injury, hemorrhagic shock, various resuscitation and treatment strategies were evaluated for their association with blood-brain barrier integrity. Analysis of gene expression profiles was performed using Porcine Gene ST 1.1 microarray. Pathway analysis was completed using network analysis tools (Gene Ontology, Ingenuity Pathway Analysis, and Parametric Gene Set Enrichment Analysis). Female Yorkshire swine were subjected to controlled traumatic brain injury and 2 hours of hemorrhagic shock (40% blood volume, mean arterial pressure 30-35 mmHg). Subjects were resuscitated with 1) normal saline, 2) fresh frozen plasma, 3) hetastarch, 4) fresh frozen plasma + valproic acid, or 5) hetastarch + valproic acid (n = 5 per group). After 6 hours of observation, brains were harvested for evaluation. Immunofluoroscopic evaluation of the traumatic brain injury site revealed significantly increased expression of tight-junction associated proteins (zona occludin-1, claudin-5) following combination therapy (fresh frozen plasma + valproic acid and hetastarch + valproic acid). The extracellular matrix protein laminin was found to have significantly improved expression with combination therapies. Pathway analysis indicated that valproic acid significantly modulated pathways involved in endothelial barrier function and cell signaling. Resuscitation with fresh frozen plasma results in improved expression of proteins essential for blood-brain barrier integrity. The addition of valproic acid provides significant improvement to these protein expression profiles. This is likely secondary to activation of key pathways related to endothelial functions.

Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis.

PubMed

van Dam, Jesse C J; Schaap, Peter J; Martins dos Santos, Vitor A P; Suárez-Diez, María

2014-09-26

Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each separate set has an intrinsic value that is diluted and partly lost when building a consensus network. Here we present a methodology to generate co-expression networks and, instead of a consensus network, we propose an integration framework where the different networks are kept and analysed with additional tools to efficiently combine the information extracted from each network. We developed a workflow to efficiently analyse information generated by different inference and prediction methods. Our methodology relies on providing the user the means to simultaneously visualise and analyse the coexisting networks generated by different algorithms, heterogeneous datasets, and a suite of analysis tools. As a show case, we have analysed the gene co-expression networks of Mycobacterium tuberculosis generated using over 600 expression experiments. Regarding DNA damage repair, we identified SigC as a key control element, 12 new targets for LexA, an updated LexA binding motif, and a potential mismatch repair system. We expanded the DevR regulon with 27 genes while identifying 9 targets wrongly assigned to this regulon. We discovered 10 new genes linked to zinc uptake and a new regulatory mechanism for ZuR. The use of co-expression networks to perform system level analysis allows the development of custom made methodologies. As show cases we implemented a pipeline to integrate ChIP-seq data and another method to uncover multiple regulatory layers. Our workflow is based on representing the multiple types of information as network representations and presenting these networks in a synchronous framework that allows their simultaneous visualization while keeping specific associations from the different networks. By simultaneously exploring these networks and metadata, we gained insights into regulatory mechanisms in M. tuberculosis that could not be obtained through the separate analysis of each data type.

Integration of HPV6 and Downregulation of AKR1C3 Expression Mark Malignant Transformation in a Patient with Juvenile-Onset Laryngeal Papillomatosis

PubMed Central

Kolligs, Jutta; Vent, Julia; Stenner, Markus; Wieland, Ulrike; Silling, Steffi; Drebber, Uta; Speel, Ernst-Jan M.; Klussmann, Jens Peter

2013-01-01

Juvenile-onset recurrent respiratory papillomatosis (RRP) is associated with low risk human papillomavirus (HPV) types 6 and 11. Malignant transformation has been reported solely for HPV11-associated RRP in 2–4% of all RRP-cases, but not for HPV6. The molecular mechanisms in the carcinogenesis of low risk HPV-associated cancers are to date unknown. We report of a female patient, who presented with a laryngeal carcinoma at the age of 24 years. She had a history of juvenile-onset RRP with an onset at the age of three and subsequently several hundred surgical interventions due to multiple recurrences of RRP. Polymerase chain reaction (PCR) or bead-based hybridization followed by direct sequencing identified HPV6 in tissue sections of previous papilloma and the carcinoma. P16INK4A, p53 and pRb immunostainings were negative in all lesions. HPV6 specific fluorescence in situ hybridization (FISH) revealed nuclear staining suggesting episomal virus in the papilloma and a single integration site in the carcinoma. Integration-specific amplification of papillomavirus oncogene transcripts PCR (APOT-PCR) showed integration in the aldo-keto reductase 1C3 gene (AKR1C3) on chromosome 10p15.1. ArrayCGH detected loss of the other gene copy as part of a deletion at 10p14-p15.2. Western blot analysis and immunohistochemistry of the protein AKR1C3 showed a marked reduction of its expression in the carcinoma. In conclusion, we identified a novel molecular mechanism underlying a first case of HPV6-associated laryngeal carcinoma in juvenile-onset RRP, i.e. that HPV6 integration in the AKR1C3 gene resulted in loss of its expression. Alterations of AKR1C gene expression have previously been implicated in the tumorigenesis of other (HPV-related) malignancies. PMID:23437342

Molecular characterization and expression analysis of Triticum aestivum squamosa-promoter binding protein-box genes involved in ear development.

PubMed

Zhang, Bin; Liu, Xia; Zhao, Guangyao; Mao, Xinguo; Li, Ang; Jing, Ruilian

2014-06-01

Wheat (Triticum aestivum L.) is one of the most important crops in the world. Squamosa-promoter binding protein (SBP)-box genes play a critical role in regulating flower and fruit development. In this study, 10 novel SBP-box genes (TaSPL genes) were isolated from wheat ((Triticum aestivum L.) cultivar Yanzhan 4110). Phylogenetic analysis classified the TaSPL genes into five groups (G1-G5). The motif combinations and expression patterns of the TaSPL genes varied among the five groups with each having own distinctive characteristics: TaSPL20/21 in G1 and TaSPL17 in G2 mainly expressed in the shoot apical meristem and the young ear, and their expression levels responded to development of the ear; TaSPL6/15 belonging to G3 were upregulated and TaSPL1/23 in G4 were downregulated during grain development; the gene in G5 (TaSPL3) expressed constitutively. Thus, the consistency of the phylogenetic analysis, motif compositions, and expression patterns of the TaSPL genes revealed specific gene structures and functions. On the other hand, the diverse gene structures and different expression patterns suggested that wheat SBP-box genes have a wide range of functions. The results also suggest a potential role for wheat SBP-box genes in ear development. This study provides a significant beginning of functional analysis of SBP-box genes in wheat. © 2014 The Authors. Journal of Integrative Plant Biology Published by Wiley Publishing Asia Pty Ltd on behalf of Institute of Botany, Chinese Academy of Sciences.

Directed chromosomal integration and expression of porcine rotavirus outer capsid protein VP4 in Lactobacillus casei ATCC393.

PubMed

Yin, Ji-Yuan; Guo, Chao-Qun; Wang, Zi; Yu, Mei-Ling; Gao, Shuai; Bukhari, Syed M; Tang, Li-Jie; Xu, Yi-Gang; Li, Yi-Jing

2016-11-01

Using two-step plasmid integration in the presence of 5-fluorouracil (5-FU), we developed a stable and markerless Lactobacillus casei strain for vaccine antigen expression. The upp of L. casei, which encodes uracil phosphoribosyltransferase (UPRTase), was used as a counterselection marker. We employed the Δupp isogenic mutant, which is resistant to 5-FU, as host and a temperature-sensitive suicide plasmid bearing upp expression cassette as counterselectable integration vector. Extrachromosomal expression of UPRTase complemented the mutated chromosomal upp allele and restored sensitivity to 5-FU. The resultant genotype can either be wild type or recombinant. The efficacy of the system was demonstrated by insertion and expression of porcine rotavirus (PRV) VP4. To improve VP4 expression, we analyzed L. casei transcriptional profiles and selected the constitutive highly expressed enolase gene (eno). The VP4 inserted after the eno termination codon were screened in the presence of 5-FU. Using genomic PCR amplification, we confirmed that VP4 was successfully integrated and stably inherited for at least 50 generations. Western blot demonstrated that VP4 was steadily expressed in medium with different carbohydrates. RT-qPCR and ELISA analysis showed that VP4 expression from the chromosomal location was similar to that achieved by a plasmid expression system. Applying the recombinant strain to immunize BALB/c mice via oral administration revealed that the VP4-expressing L. casei could induce both specific local and systemic humoral immune responses in mice. Overall, the improved gene replacement system represents an efficient method for chromosome recombination in L. casei and provides a safe tool for vaccine production.

Integrative analyses of conserved WNT clusters and their co-operative behaviour in human breast cancer

PubMed Central

Qurrat-ul-Ain; Seemab, Umair; Nawaz, Sulaman; Rashid, Sajid

2011-01-01

In human, WNT gene clusters are highly conserved at specie level and associated with carcinogenesis. Among them, WNT-10A and WNT-6 genes clustered in chromosome 2q35 are homologous to WNT-10B and WNT-1 located in chromosome 12q13, respectively. In an attempt to study co-regulation, the coordinated expression of these genes was monitored in human breast cancer tissues. As compared to normal tissue, both WNT-10A and WNT-10B genes exhibited lower expression while WNT-6 and WNT-1 showed increased expression in breast cancer tissues. The co-expression pattern was elaborated by detailed phylogenetic and syntenic analyses. Moreover, the intergenic and intragenic regions for these gene clusters were analyzed for studying the transcriptional regulation. In this context, adequate conserved binding sites for SOX and TCF family of transcriptional factors were observed. We propose that SOX9 and TCF4 may compete for binding at the promoters of WNT family genes thus regulating the disease phenotype. PMID:22355234

Molecular cloning and characterization of a gene regulating flowering time from Alfalfa (Medicago sativa L.).

PubMed

Zhang, Tiejun; Chao, Yuehui; Kang, Junmei; Ding, Wang; Yang, Qingchuan

2013-07-01

Genes that regulate flowering time play crucial roles in plant development and biomass formation. Based on the cDNA sequence of Medicago truncatula (accession no. AY690425), the LFY gene of alfalfa was cloned. Sequence similarity analysis revealed high homology with FLO/LFY family genes of other plants. When fused to the green fluorescent protein, MsLFY protein was localized in the nucleus of onion (Allium cepa L.) epidermal cells. The RT-qPCR analysis of MsLFY expression patterns showed that the expression of MsLFY gene was at a low level in roots, stems, leaves and pods, and the expression level in floral buds was the highest. The expression of MsLFY was induced by GA3 and long photoperiod. Plant expression vector was constructed and transformed into Arabidopsis by the agrobacterium-mediated methods. PCR amplification with the transgenic Arabidopsis genome DNA indicated that MsLFY gene had integrated in Arabidopsis genome. Overexpression of MsLFY specifically caused early flowering under long day conditions compared with non-transgenic plants. These results indicated MsLFY played roles in promoting flowering time.

BFDCA: A Comprehensive Tool of Using Bayes Factor for Differential Co-Expression Analysis.

PubMed

Wang, Duolin; Wang, Juexin; Jiang, Yuexu; Liang, Yanchun; Xu, Dong

2017-02-03

Comparing the gene-expression profiles between biological conditions is useful for understanding gene regulation underlying complex phenotypes. Along this line, analysis of differential co-expression (DC) has gained attention in the recent years, where genes under one condition have different co-expression patterns compared with another. We developed an R package Bayes Factor approach for Differential Co-expression Analysis (BFDCA) for DC analysis. BFDCA is unique in integrating various aspects of DC patterns (including Shift, Cross, and Re-wiring) into one uniform Bayes factor. We tested BFDCA using simulation data and experimental data. Simulation results indicate that BFDCA outperforms existing methods in accuracy and robustness of detecting DC pairs and DC modules. Results of using experimental data suggest that BFDCA can cluster disease-related genes into functional DC subunits and estimate the regulatory impact of disease-related genes well. BFDCA also achieves high accuracy in predicting case-control phenotypes by using significant DC gene pairs as markers. BFDCA is publicly available at http://dx.doi.org/10.17632/jdz4vtvnm3.1. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data.

PubMed

Racle, Julien; de Jonge, Kaat; Baumgaertner, Petra; Speiser, Daniel E; Gfeller, David

2017-11-13

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org).

Integrative radiogenomic analysis for multicentric radiophenotype in glioblastoma

PubMed Central

Kong, Doo-Sik; Kim, Jinkuk; Lee, In-Hee; Kim, Sung Tae; Seol, Ho Jun; Lee, Jung-Il; Park, Woong-Yang; Ryu, Gyuha; Wang, Zichen; Ma'ayan, Avi; Nam, Do-Hyun

2016-01-01

We postulated that multicentric glioblastoma (GBM) represents more invasiveness form than solitary GBM and has their own genomic characteristics. From May 2004 to June 2010 we retrospectively identified 51 treatment-naïve GBM patients with available clinical information from the Samsung Medical Center data registry. Multicentricity of the tumor was defined as the presence of multiple foci on the T1 contrast enhancement of MR images or having high signal for multiple lesions without contiguity of each other on the FLAIR image. Kaplan-Meier survival analysis demonstrated that multicentric GBM had worse prognosis than solitary GBM (median, 16.03 vs. 20.57 months, p < 0.05). Copy number variation (CNV) analysis revealed there was an increase in 11 regions, and a decrease in 17 regions, in the multicentric GBM. Gene expression profiling identified 738 genes to be increased and 623 genes to be decreased in the multicentric radiophenotype (p < 0.001). Integration of the CNV and expression datasets identified twelve representative genes: CPM, LANCL2, LAMP1, GAS6, DCUN1D2, CDK4, AGAP2, TSPAN33, PDLIM1, CLDN12, and GTPBP10 having high correlation across CNV, gene expression and patient outcome. Network and enrichment analyses showed that the multicentric tumor had elevated fibrotic signaling pathways compared with a more proliferative and mitogenic signal in the solitary tumors. Noninvasive radiological imaging together with integrative radiogenomic analysis can provide an important tool in helping to advance personalized therapy for the more clinically aggressive subset of GBM. PMID:26863628

Integrating machine learning techniques into robust data enrichment approach and its application to gene expression data.

PubMed

Erdoğdu, Utku; Tan, Mehmet; Alhajj, Reda; Polat, Faruk; Rokne, Jon; Demetrick, Douglas

2013-01-01

The availability of enough samples for effective analysis and knowledge discovery has been a challenge in the research community, especially in the area of gene expression data analysis. Thus, the approaches being developed for data analysis have mostly suffered from the lack of enough data to train and test the constructed models. We argue that the process of sample generation could be successfully automated by employing some sophisticated machine learning techniques. An automated sample generation framework could successfully complement the actual sample generation from real cases. This argument is validated in this paper by describing a framework that integrates multiple models (perspectives) for sample generation. We illustrate its applicability for producing new gene expression data samples, a highly demanding area that has not received attention. The three perspectives employed in the process are based on models that are not closely related. The independence eliminates the bias of having the produced approach covering only certain characteristics of the domain and leading to samples skewed towards one direction. The first model is based on the Probabilistic Boolean Network (PBN) representation of the gene regulatory network underlying the given gene expression data. The second model integrates Hierarchical Markov Model (HIMM) and the third model employs a genetic algorithm in the process. Each model learns as much as possible characteristics of the domain being analysed and tries to incorporate the learned characteristics in generating new samples. In other words, the models base their analysis on domain knowledge implicitly present in the data itself. The developed framework has been extensively tested by checking how the new samples complement the original samples. The produced results are very promising in showing the effectiveness, usefulness and applicability of the proposed multi-model framework.

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes.

PubMed

Santiago, Jose A; Potashkin, Judith A

2013-01-01

Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP), previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Prognostic Biomarker Study (PROBE), revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients. These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first time that increased expression of APP in blood may modulate the neurodegenerative phenotype in type 2 diabetes patients.

[Suppression of replication of swine parvoviral antisense RNA against the NS PPV gene in swine thyroid gland cells].

PubMed

Voskresenskaia, E P; Miroshnichenko, O I; Ponamareva, T I; Savich, O M; Tikhonenko, T I

1993-01-01

The possibility of suppression of porcine parvovirus (PPV) reproduction in the culture of thyroid gland cells of a swine that contain the integrated genes for asRNA against the nonstructural proteins of the virus has been studied. 10 cell lines with the asRNA genes have been obtained. The line with the maximal number of integrated gene copies was used to inflict with the parvovirus. The expression of asRNA in this cell line was shown to lead to 95% suppression of PPV replication as compared with the control cell line.

Enhancer Linking by Methylation/Expression Relationships (ELMER) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

R tool for analysis of DNA methylation and expression datasets. Integrative analysis allows reconstruction of in vivo transcription factor networks altered in cancer along with identification of the underlying gene regulatory sequences.

Expression of Hygromycin Phosphotransferase Alters Virulence of Histoplasma capsulatum▿

PubMed Central

Smulian, A. George; Gibbons, Reta S.; Demland, Jeffery A.; Spaulding, Deborah T.; Deepe, George S.

2007-01-01

The Escherichia coli hygromycin phosphotransferase (hph) gene, which confers hygromycin resistance, is commonly used as a dominant selectable marker in genetically modified bacteria, fungi, plants, insects, and mammalian cells. Expression of the hph gene has rarely been reported to induce effects other than those expected. Hygromycin B is the most common dominant selectable marker used in the molecular manipulation of Histoplasma capsulatum in the generation of knockout strains of H. capsulatum or as a marker in mutant strains. hph-expressing organisms appear to have no defect in long-term in vitro growth and survival and have been successfully used to exploit host-parasite interaction in short-term cell culture systems and animal experiments. We introduced the hph gene as a selectable marker together with the gene encoding green fluorescent protein into wild-type strains of H. capsulatum. Infection of mice with hph-expressing H. capsulatum yeast cells at sublethal doses resulted in lethality. The lethality was not attributable to the site of integration of the hph construct into the genomes or to the method of integration and was not H. capsulatum strain related. Death of mice was not caused by altered cytokine profiles or an overwhelming fungal burden. The lethality was dependent on the kinase activity of hygromycin phosphotransferase. These results should raise awareness of the potential detrimental effects of the hph gene. PMID:17873086

Expression of hygromycin phosphotransferase alters virulence of Histoplasma capsulatum.

PubMed

Smulian, A George; Gibbons, Reta S; Demland, Jeffery A; Spaulding, Deborah T; Deepe, George S

2007-11-01

The Escherichia coli hygromycin phosphotransferase (hph) gene, which confers hygromycin resistance, is commonly used as a dominant selectable marker in genetically modified bacteria, fungi, plants, insects, and mammalian cells. Expression of the hph gene has rarely been reported to induce effects other than those expected. Hygromycin B is the most common dominant selectable marker used in the molecular manipulation of Histoplasma capsulatum in the generation of knockout strains of H. capsulatum or as a marker in mutant strains. hph-expressing organisms appear to have no defect in long-term in vitro growth and survival and have been successfully used to exploit host-parasite interaction in short-term cell culture systems and animal experiments. We introduced the hph gene as a selectable marker together with the gene encoding green fluorescent protein into wild-type strains of H. capsulatum. Infection of mice with hph-expressing H. capsulatum yeast cells at sublethal doses resulted in lethality. The lethality was not attributable to the site of integration of the hph construct into the genomes or to the method of integration and was not H. capsulatum strain related. Death of mice was not caused by altered cytokine profiles or an overwhelming fungal burden. The lethality was dependent on the kinase activity of hygromycin phosphotransferase. These results should raise awareness of the potential detrimental effects of the hph gene.

Proteogenomic characterization of human colon and rectal cancer

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

Zhang, Bing; Wang, Jing; Wang, Xiaojing

2014-09-18

We analyzed proteomes of colon and rectal tumors previously characterized by the Cancer Genome Atlas (TCGA) and performed integrated proteogenomic analyses. Protein sequence variants encoded by somatic genomic variations displayed reduced expression compared to protein variants encoded by germline variations. mRNA transcript abundance did not reliably predict protein expression differences between tumors. Proteomics identified five protein expression subtypes, two of which were associated with the TCGA "MSI/CIMP" transcriptional subtype, but had distinct mutation and methylation patterns and associated with different clinical outcomes. Although CNAs showed strong cis- and trans-effects on mRNA expression, relatively few of these extend to the proteinmore » level. Thus, proteomics data enabled prioritization of candidate driver genes. Our analyses identified HNF4A, a novel candidate driver gene in tumors with chromosome 20q amplifications. Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords novel insights into cancer biology.« less

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

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

Weighill, Deborah; Jones, Piet; Shah, Manesh

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.« less

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

DOE PAGES

Weighill, Deborah; Jones, Piet; Shah, Manesh; ...

2018-05-11

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.« less

Integrated proteomic and genomic analysis of colorectal cancer

Cancer.gov

Investigators who analyzed 95 human colorectal tumor samples have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, pro

Hybrid lentivirus-phiC31-int-NLS vector allows site-specific recombination in murine and human cells but induces DNA damage.

PubMed

Grandchamp, Nicolas; Altémir, Dorothée; Philippe, Stéphanie; Ursulet, Suzanna; Pilet, Héloïse; Serre, Marie-Claude; Lenain, Aude; Serguera, Che; Mallet, Jacques; Sarkis, Chamsy

2014-01-01

Gene transfer allows transient or permanent genetic modifications of cells for experimental or therapeutic purposes. Gene delivery by HIV-derived lentiviral vector (LV) is highly effective but the risk of insertional mutagenesis is important and the random/uncontrollable integration of the DNA vector can deregulate the cell transcriptional activity. Non Integrative Lentiviral Vectors (NILVs) solve this issue in non-dividing cells, but they do not allow long term expression in dividing cells. In this context, obtaining stable expression while avoiding the problems inherent to unpredictable DNA vector integration requires the ability to control the integration site. One possibility is to use the integrase of phage phiC31 (phiC31-int) which catalyzes efficient site-specific recombination between the attP site in the phage genome and the chromosomal attB site of its Streptomyces host. Previous studies showed that phiC31-int is active in many eukaryotic cells, such as murine or human cells, and directs the integration of a DNA substrate into pseudo attP sites (pattP) which are homologous to the native attP site. In this study, we combined the efficiency of NILV for gene delivery and the specificity of phiC31-int for DNA substrate integration to engineer a hybrid tool for gene transfer with the aim of allowing long term expression in dividing and non-dividing cells preventing genotoxicity. We demonstrated the feasibility to target NILV integration in human and murine pattP sites with a dual NILV vectors system: one which delivers phiC31-int, the other which constitute the substrate containing an attB site in its DNA sequence. These promising results are however alleviated by the occurrence of significant DNA damages. Further improvements are thus required to prevent chromosomal rearrangements for a therapeutic use of the system. However, its use as a tool for experimental applications such as transgenesis is already applicable.

Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS.

PubMed

Dobbyn, Amanda; Huckins, Laura M; Boocock, James; Sloofman, Laura G; Glicksberg, Benjamin S; Giambartolomei, Claudia; Hoffman, Gabriel E; Perumal, Thanneer M; Girdhar, Kiran; Jiang, Yan; Raj, Towfique; Ruderfer, Douglas M; Kramer, Robin S; Pinto, Dalila; Akbarian, Schahram; Roussos, Panos; Domenici, Enrico; Devlin, Bernie; Sklar, Pamela; Stahl, Eli A; Sieberts, Solveig K

2018-06-07

Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

An EDMD mutation in C. elegans lamin blocks muscle-specific gene relocation and compromises muscle integrity.

PubMed

Mattout, Anna; Pike, Brietta L; Towbin, Benjamin D; Bank, Erin M; Gonzalez-Sandoval, Adriana; Stadler, Michael B; Meister, Peter; Gruenbaum, Yosef; Gasser, Susan M

2011-10-11

In worms, as in other organisms, many tissue-specific promoters are sequestered at the nuclear periphery when repressed and shift inward when activated. It has remained unresolved, however, whether the association of facultative heterochromatin with the nuclear periphery, or its release, has functional relevance for cell or tissue integrity. Using ablation of the unique lamin gene in C. elegans, we show that lamin is necessary for the perinuclear positioning of heterochromatin. We then express at low levels in otherwise wild-type worms a lamin carrying a point mutation, Y59C, which in humans is linked to an autosomal-dominant form of Emery-Dreifuss muscular dystrophy. Using embryos and differentiated tissues, we track the subnuclear position of integrated heterochromatic arrays and their expression. In LMN-1 Y59C-expressing worms, we see abnormal retention at the nuclear envelope of a gene array bearing a muscle-specific promoter. This correlates with impaired activation of the array-borne myo-3 promoter and altered expression of a number of muscle-specific genes. However, an equivalent array carrying the intestine-specific pha-4 promoter is expressed normally and shifts inward when activated in gut cells of LMN-1 Y59C worms. Remarkably, adult LMN-1 Y59C animals have selectively perturbed body muscle ultrastructure and reduced muscle function. Lamin helps sequester heterochromatin at the nuclear envelope, and wild-type lamin permits promoter release following tissue-specific activation. A disease-linked point mutation in lamin impairs muscle-specific reorganization of a heterochromatic array during tissue-specific promoter activation in a dominant manner. This dominance and the correlated muscle dysfunction in LMN-1 Y59C worms phenocopies Emery-Dreifuss muscular dystrophy. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reference genes for reverse transcription quantitative PCR in canine brain tissue.

PubMed

Stassen, Quirine E M; Riemers, Frank M; Reijmerink, Hannah; Leegwater, Peter A J; Penning, Louis C

2015-12-09

In the last decade canine models have been used extensively to study genetic causes of neurological disorders such as epilepsy and Alzheimer's disease and unravel their pathophysiological pathways. Reverse transcription quantitative polymerase chain reaction is a sensitive and inexpensive method to study expression levels of genes involved in disease processes. Accurate normalisation with stably expressed so-called reference genes is crucial for reliable expression analysis. Following the minimum information for publication of quantitative real-time PCR experiments precise guidelines, the expression of ten frequently used reference genes, namely YWHAZ, HMBS, B2M, SDHA, GAPDH, HPRT, RPL13A, RPS5, RPS19 and GUSB was evaluated in seven brain regions (frontal lobe, parietal lobe, occipital lobe, temporal lobe, thalamus, hippocampus and cerebellum) and whole brain of healthy dogs. The stability of expression varied between different brain areas. Using the GeNorm and Normfinder software HMBS, GAPDH and HPRT were the most reliable reference genes for whole brain. Furthermore based on GeNorm calculations it was concluded that as little as two to three reference genes are sufficient to obtain reliable normalisation, irrespective the brain area. Our results amend/extend the limited previously published data on canine brain reference genes. Despite the excellent expression stability of HMBS, GAPDH and HRPT, the evaluation of expression stability of reference genes must be a standard and integral part of experimental design and subsequent data analysis.

Gene expression profile analysis of rat cerebellum under acute alcohol intoxication.

PubMed

Zhang, Yu; Wei, Guangkuan; Wang, Yuehong; Jing, Ling; Zhao, Qingjie

2015-02-25

Acute alcohol intoxication, a common disease causing damage to the central nervous system (CNS) has been primarily studied on the aspects of alcohol addiction and chronic alcohol exposure. The understanding of gene expression change in the CNS during acute alcohol intoxication is still lacking. We established a model for acute alcohol intoxication in SD rats by oral gavage. A rat cDNA microarray was used to profile mRNA expression in the cerebella of alcohol-intoxicated rats (experimental group) and saline-treated rats (control group). A total of 251 differentially expressed genes were identified in response to acute alcohol intoxication, in which 208 of them were up-regulated and 43 were down-regulated. Gene ontology (GO) term enrichment analysis and pathway analysis revealed that the genes involved in the biological processes of immune response and endothelial integrity are among the most severely affected in response to acute alcohol intoxication. We discovered five transcription factors whose consensus binding motifs are overrepresented in the promoter region of differentially expressed genes. Additionally, we identified 20 highly connected hub genes by co-expression analysis, and validated the differential expression of these genes by real-time quantitative PCR. By determining novel biological pathways and transcription factors that have functional implication to acute alcohol intoxication, our study substantially contributes to the understanding of the molecular mechanism underlying the pathology of acute alcoholism. Copyright © 2014 Elsevier B.V. All rights reserved.

Integrated analysis of microRNA and gene expression profiles reveals a functional regulatory module associated with liver fibrosis.

PubMed

Chen, Wei; Zhao, Wenshan; Yang, Aiting; Xu, Anjian; Wang, Huan; Cong, Min; Liu, Tianhui; Wang, Ping; You, Hong

2017-12-15

Liver fibrosis, characterized with the excessive accumulation of extracellular matrix (ECM) proteins, represents the final common pathway of chronic liver inflammation. Ever-increasing evidence indicates microRNAs (miRNAs) dysregulation has important implications in the different stages of liver fibrosis. However, our knowledge of miRNA-gene regulation details pertaining to such disease remains unclear. The publicly available Gene Expression Omnibus (GEO) datasets of patients suffered from cirrhosis were extracted for integrated analysis. Differentially expressed miRNAs (DEMs) and genes (DEGs) were identified using GEO2R web tool. Putative target gene prediction of DEMs was carried out using the intersection of five major algorithms: DIANA-microT, TargetScan, miRanda, PICTAR5 and miRWalk. Functional miRNA-gene regulatory network (FMGRN) was constructed based on the computational target predictions at the sequence level and the inverse expression relationships between DEMs and DEGs. DAVID web server was selected to perform KEGG pathway enrichment analysis. Functional miRNA-gene regulatory module was generated based on the biological interpretation. Internal connections among genes in liver fibrosis-related module were determined using String database. MiRNA-gene regulatory modules related to liver fibrosis were experimentally verified in recombinant human TGFβ1 stimulated and specific miRNA inhibitor treated LX-2 cells. We totally identified 85 and 923 dysregulated miRNAs and genes in liver cirrhosis biopsy samples compared to their normal controls. All evident miRNA-gene pairs were identified and assembled into FMGRN which consisted of 990 regulations between 51 miRNAs and 275 genes, forming two big sub-networks that were defined as down-network and up-network, respectively. KEGG pathway enrichment analysis revealed that up-network was prominently involved in several KEGG pathways, in which "Focal adhesion", "PI3K-Akt signaling pathway" and "ECM-receptor interaction" were remarked significant (adjusted p<0.001). Genes enriched in these pathways coupled with their regulatory miRNAs formed a functional miRNA-gene regulatory module that contains 7 miRNAs, 22 genes and 42 miRNA-gene connections. Gene interaction analysis based on String database revealed that 8 out of 22 genes were highly clustered. Finally, we experimentally confirmed a functional regulatory module containing 5 miRNAs (miR-130b-3p, miR-148a-3p, miR-345-5p, miR-378a-3p, and miR-422a) and 6 genes (COL6A1, COL6A2, COL6A3, PIK3R3, COL1A1, CCND2) associated with liver fibrosis. Our integrated analysis of miRNA and gene expression profiles highlighted a functional miRNA-gene regulatory module associated with liver fibrosis, which, to some extent, may provide important clues to better understand the underlying pathogenesis of liver fibrosis. Copyright © 2017. Published by Elsevier B.V.

Safe Genetic Modification of Cardiac Stem Cells Using a Site-Specific Integration Technique

PubMed Central

Lan, Feng; Liu, Junwei; Narsinh, Kazim H.; Hu, Shijun; Han, Leng; Lee, Andrew S.; Karow, Marisa; Nguyen, Patricia K.; Nag, Divya; Calos, Michele P.; Robbins, Robert C.; Wu, Joseph C.

2012-01-01

Background Human cardiac progenitor cells (hCPCs) are a promising cell source for regenerative repair after myocardial infarction. Exploitation of their full therapeutic potential may require stable genetic modification of the cells ex vivo. Safe genetic engineering of stem cells, using facile methods for site-specific integration of transgenes into known genomic contexts, would significantly enhance the overall safety and efficacy of cellular therapy in a variety of clinical contexts. Methods and Results We employed the phiC31 site-specific recombinase to achieve targeted integration of a triple fusion reporter gene into a known chromosomal context in hCPCs and human endothelial cells (hECs). Stable expression of the reporter gene from its unique chromosomal integration site resulted in no discernible genomic instability or adverse changes in cell phenotype. Namely, phiC31-modified hCPCs were unchanged in their differentiation propensity, cellular proliferative rate, and global gene expression profile when compared to unaltered control hCPCs. Expression of the triple fusion reporter gene enabled multimodal assessment of cell fate in vitro and in vivo using fluorescence microscopy, bioluminescence imaging (BLI), and positron emission tomography (PET). Intramyocardial transplantation of genetically modified hCPCs resulted in significant improvement in myocardial function two weeks after cell delivery, as assessed by echocardiography (P = 0.002) and magnetic resonance imaging (P = 0.001). We also demonstrated the feasibility and therapeutic efficacy of genetically modifying differentiated hECs, which enhanced hindlimb perfusion (P<0.05 at day 7 and 14 after transplantation) on laser Doppler imaging. Conclusions The phiC31 integrase genomic modification system is a safe, efficient tool to enable site-specific integration of reporter transgenes in progenitor and differentiated cell types. PMID:22965984

Safe genetic modification of cardiac stem cells using a site-specific integration technique.

PubMed

Lan, Feng; Liu, Junwei; Narsinh, Kazim H; Hu, Shijun; Han, Leng; Lee, Andrew S; Karow, Marisa; Nguyen, Patricia K; Nag, Divya; Calos, Michele P; Robbins, Robert C; Wu, Joseph C

2012-09-11

Human cardiac progenitor cells (hCPCs) are a promising cell source for regenerative repair after myocardial infarction. Exploitation of their full therapeutic potential may require stable genetic modification of the cells ex vivo. Safe genetic engineering of stem cells, using facile methods for site-specific integration of transgenes into known genomic contexts, would significantly enhance the overall safety and efficacy of cellular therapy in a variety of clinical contexts. We used the phiC31 site-specific recombinase to achieve targeted integration of a triple fusion reporter gene into a known chromosomal context in hCPCs and human endothelial cells. Stable expression of the reporter gene from its unique chromosomal integration site resulted in no discernible genomic instability or adverse changes in cell phenotype. Namely, phiC31-modified hCPCs were unchanged in their differentiation propensity, cellular proliferative rate, and global gene expression profile when compared with unaltered control hCPCs. Expression of the triple fusion reporter gene enabled multimodal assessment of cell fate in vitro and in vivo using fluorescence microscopy, bioluminescence imaging, and positron emission tomography. Intramyocardial transplantation of genetically modified hCPCs resulted in significant improvement in myocardial function 2 weeks after cell delivery, as assessed by echocardiography (P=0.002) and MRI (P=0.001). We also demonstrated the feasibility and therapeutic efficacy of genetically modifying differentiated human endothelial cells, which enhanced hind limb perfusion (P<0.05 at day 7 and 14 after transplantation) on laser Doppler imaging. The phiC31 integrase genomic modification system is a safe, efficient tool to enable site-specific integration of reporter transgenes in progenitor and differentiated cell types.

Annotation of gene function in citrus using gene expression information and co-expression networks

PubMed Central

2014-01-01

Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related biological processes may exhibit similar expression patterns across diverse sets of experimental conditions. While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed. Results We have constructed a comprehensive GCN for citrus inferred from 297 publicly available Affymetrix Genechip Citrus Genome microarray datasets, providing gene co-expression relationships at a genome-wide scale (33,000 transcripts). The comprehensive citrus GCN consists of a global GCN (condition-independent) and four condition-dependent GCNs that survey the sweet orange species only, all citrus fruit tissues, all citrus leaf tissues, or stress-exposed plants. All of these GCNs are clustered using genome-wide, gene-centric (guide) and graph clustering algorithms for flexibility of gene function prediction. For each putative cluster, gene ontology (GO) enrichment and gene expression specificity analyses were performed to enhance gene function, expression and regulation pattern prediction. The guide-gene approach was used to infer novel roles of genes involved in disease susceptibility and vitamin C metabolism, and graph-clustering approaches were used to investigate isoprenoid/phenylpropanoid metabolism in citrus peel, and citric acid catabolism via the GABA shunt in citrus fruit. Conclusions Integration of citrus gene co-expression networks, functional enrichment analysis and gene expression information provide opportunities to infer gene function in citrus. We present a publicly accessible tool, Network Inference for Citrus Co-Expression (NICCE, http://citrus.adelaide.edu.au/nicce/home.aspx), for the gene co-expression analysis in citrus. PMID:25023870

SEURAT: visual analytics for the integrated analysis of microarray data.

PubMed

Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

2010-06-03

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

RAS oncogene-mediated deregulation of the transcriptome: from molecular signature to function.

PubMed

Schäfer, Reinhold; Sers, Christine

2011-01-01

Transcriptome analysis of cancer cells has developed into a standard procedure to elucidate multiple features of the malignant process and to link gene expression to clinical properties. Gene expression profiling based on microarrays provides essentially correlative information and needs to be transferred to the functional level in order to understand the activity and contribution of individual genes or sets of genes as elements of the gene signature. To date, there exist significant gaps in the functional understanding of gene expression profiles. Moreover, the processes that drive the profound transcriptional alterations that characterize cancer cells remain mainly elusive. We have used pathway-restricted gene expression profiles derived from RAS oncogene-transformed cells and from RAS-expressing cancer cells to identify regulators downstream of the MAPK pathway.We describe the role of epigenetic regulation exemplified by the control of several immune genes in generic cell lines and colorectal cancer cells, particularly the functional interaction between signaling and DNA methylation. Moreover, we assess the role of the architectural transcription factor high mobility AT-hook 2 (HMGA2) as a regulator of the RAS-responsive transcriptome in ovarian epithelial cells. Finally, we describe an integrated approach combining pathway interference in colorectal cancer cells, gene expression profiling and computational analysis of regulatory elements of deregulated target genes. This strategy resulted in the identification of Y-box binding protein 1 (YBX1) as a regulator of MAPK-dependent proliferation and gene expression. The implications for a therapeutic application of HMGA2 gene silencing and the role of YBX1 as a prognostic factor are discussed.

Network-based integration of GWAS and gene expression identifies a HOX-centric network associated with serous ovarian cancer risk

PubMed Central

Kar, Siddhartha P.; Tyrer, Jonathan P.; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie T.; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F.; Edwards, Robert P.; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K.; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K.; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain A.; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston-Campbell, Lara E.; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Monteiro, Alvaro N. A.; Freedman, Matthew L.; Gayther, Simon A.; Pharoah, Paul D. P.

2015-01-01

Background Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by co-expression may also be enriched for additional EOC risk associations. Methods We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly co-expressed with each selected TF gene in the unified microarray data set of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this data set were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P<0.05 and FDR<0.05). These results were replicated (P<0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact Network analysis integrating large, context-specific data sets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. PMID:26209509

Novel prediction of anticancer drug chemosensitivity in cancer cell lines: evidence of moderation by microRNA expressions.

PubMed

Yang, Daniel S

2014-01-01

The objectives of this study are (1) to develop a novel "moderation" model of drug chemosensitivity and (2) to investigate if miRNA expression moderates the relationship between gene expression and drug chemosensitivity, specifically for HSP90 inhibitors applied to human cancer cell lines. A moderation model integrating the interaction between miRNA and gene expressions was developed to examine if miRNA expression affects the strength of the relationship between gene expression and chemosensitivity. Comprehensive datasets on miRNA expressions, gene expressions, and drug chemosensitivities were obtained from National Cancer Institute's NCI-60 cell lines including nine different cancer types. A workflow including steps of selecting genes, miRNAs, and compounds, correlating gene expression with chemosensitivity, and performing multivariate analysis was utilized to test the proposed model. The proposed moderation model identified 12 significantly-moderating miRNAs: miR-15b*, miR-16-2*, miR-9, miR-126*, miR-129*, miR-138, miR-519e*, miR-624*, miR-26b, miR-30e*, miR-32, and miR-196a, as well as two genes ERCC2 and SF3B1 which affect chemosensitivities of Tanespimycin and Alvespimycin - both HSP90 inhibitors. A bootstrap resampling of 2,500 times validates the significance of all 12 identified miRNAs. The results confirm that certain miRNA and gene expressions interact to produce an effect on drug response. The lack of correlation between miRNA and gene expression themselves suggests that miRNA transmits its effect through translation inhibition/control rather than mRNA degradation. The results suggest that miRNAs could serve not only as prognostic biomarkers for cancer treatment outcome but also as interventional agents to modulate desired chemosensitivity.

Elevated transcription factor specificity protein 1 in autistic brains alters the expression of autism candidate genes.

PubMed

Thanseem, Ismail; Anitha, Ayyappan; Nakamura, Kazuhiko; Suda, Shiro; Iwata, Keiko; Matsuzaki, Hideo; Ohtsubo, Masafumi; Ueki, Takatoshi; Katayama, Taiichi; Iwata, Yasuhide; Suzuki, Katsuaki; Minoshima, Shinsei; Mori, Norio

2012-03-01

Profound changes in gene expression can result from abnormalities in the concentrations of sequence-specific transcription factors like specificity protein 1 (Sp1). Specificity protein 1 binding sites have been reported in the promoter regions of several genes implicated in autism. We hypothesize that dysfunction of Sp1 could affect the expression of multiple autism candidate genes, contributing to the heterogeneity of autism. We assessed any alterations in the expression of Sp1 and that of autism candidate genes in the postmortem brain (anterior cingulate gyrus [ACG], motor cortex, and thalamus) of autism patients (n = 8) compared with healthy control subjects (n = 13). Alterations in the expression of candidate genes upon Sp1/DNA binding inhibition with mithramycin and Sp1 silencing by RNAi were studied in SK-N-SH neuronal cells. We observed elevated expression of Sp1 in ACG of autism patients (p = .010). We also observed altered expression of several autism candidate genes. GABRB3, RELN, and HTR2A showed reduced expression, whereas CD38, ITGB3, MAOA, MECP2, OXTR, and PTEN showed elevated expression in autism. In SK-N-SH cells, OXTR, PTEN, and RELN showed reduced expression upon Sp1/DNA binding inhibition and Sp1 silencing. The RNA integrity number was not available for any of the samples. Transcription factor Sp1 is dysfunctional in the ACG of autistic brain. Consequently, the expression of potential autism candidate genes regulated by Sp1, especially OXTR and PTEN, could be affected. The diverse downstream pathways mediated by the Sp1-regulated genes, along with the environmental and intracellular signal-related regulation of Sp1, could explain the complex phenotypes associated with autism.

Ossification of the posterior longitudinal ligament related genes identification using microarray gene expression profiling and bioinformatics analysis.

PubMed

He, Hailong; Mao, Lingzhou; Xu, Peng; Xi, Yanhai; Xu, Ning; Xue, Mingtao; Yu, Jiangming; Ye, Xiaojian

2014-01-10

Ossification of the posterior longitudinal ligament (OPLL) is a kind of disease with physical barriers and neurological disorders. The objective of this study was to explore the differentially expressed genes (DEGs) in OPLL patient ligament cells and identify the target sites for the prevention and treatment of OPLL in clinic. Gene expression data GSE5464 was downloaded from Gene Expression Omnibus; then DEGs were screened by limma package in R language, and changed functions and pathways of OPLL cells compared to normal cells were identified by DAVID (The Database for Annotation, Visualization and Integrated Discovery); finally, an interaction network of DEGs was constructed by string. A total of 1536 DEGs were screened, with 31 down-regulated and 1505 up-regulated genes. Response to wounding function and Toll-like receptor signaling pathway may involve in the development of OPLL. Genes, such as PDGFB, PRDX2 may involve in OPLL through response to wounding function. Toll-like receptor signaling pathway enriched genes such as TLR1, TLR5, and TLR7 may involve in spine cord injury in OPLL. PIK3R1 was the hub gene in the network of DEGs with the highest degree; INSR was one of the most closely related genes of it. OPLL related genes screened by microarray gene expression profiling and bioinformatics analysis may be helpful for elucidating the mechanism of OPLL. © 2013.

IDP-ASE: haplotyping and quantifying allele-specific expression at the gene and gene isoform level by hybrid sequencing

PubMed Central

Deonovic, Benjamin; Wang, Yunhao; Weirather, Jason; Wang, Xiu-Jie; Au, Kin Fai

2017-01-01

Abstract Allele-specific expression (ASE) is a fundamental problem in studying gene regulation and diploid transcriptome profiles, with two key challenges: (i) haplotyping and (ii) estimation of ASE at the gene isoform level. Existing ASE analysis methods are limited by a dependence on haplotyping from laborious experiments or extra genome/family trio data. In addition, there is a lack of methods for gene isoform level ASE analysis. We developed a tool, IDP-ASE, for full ASE analysis. By innovative integration of Third Generation Sequencing (TGS) long reads with Second Generation Sequencing (SGS) short reads, the accuracy of haplotyping and ASE quantification at the gene and gene isoform level was greatly improved as demonstrated by the gold standard data GM12878 data and semi-simulation data. In addition to methodology development, applications of IDP-ASE to human embryonic stem cells and breast cancer cells indicate that the imbalance of ASE and non-uniformity of gene isoform ASE is widespread, including tumorigenesis relevant genes and pluripotency markers. These results show that gene isoform expression and allele-specific expression cooperate to provide high diversity and complexity of gene regulation and expression, highlighting the importance of studying ASE at the gene isoform level. Our study provides a robust bioinformatics solution to understand ASE using RNA sequencing data only. PMID:27899656

Efficient production by sperm-mediated gene transfer of human decay accelerating factor (hDAF) transgenic pigs for xenotransplantation

PubMed Central

Lavitrano, Marialuisa; Bacci, Maria Laura; Forni, Monica; Lazzereschi, Davide; Di Stefano, Carla; Fioretti, Daniela; Giancotti, Paola; Marfé, Gabriella; Pucci, Loredana; Renzi, Luigina; Wang, Hongjun; Stoppacciaro, Antonella; Stassi, Giorgio; Sargiacomo, Massimo; Sinibaldi, Paola; Turchi, Valeria; Giovannoni, Roberto; Della Casa, Giacinto; Seren, Eraldo; Rossi, Giancarlo

2002-01-01

A large number of hDAF transgenic pigs to be used for xenotransplantation research were generated by using sperm-mediated gene transfer (SMGT). The efficiency of transgenesis obtained with SMGT was much greater than with any other method. In the experiments reported, up to 80% of pigs had the transgene integrated into the genome. Most of the pigs carrying the hDAF gene transcribed it in a stable manner (64%). The great majority of pigs that transcribed the gene expressed the protein (83%). The hDAF gene was transmitted to progeny. Expression was stable and found in caveolae as it is in human cells. The expressed gene was functional based on in vitro experiments performed on peripheral blood mononuclear cells. These results show that our SMGT approach to transgenesis provides an efficient procedure for studies involving large animal models. PMID:12393815

Comparative performance of modified full-length and truncated Bacillus thuringiensis-cry1Ac genes in transgenic tomato.

PubMed

Koul, Bhupendra; Yadav, Reena; Sanyal, Indraneel; Amla, Devindra Vijay

2015-01-01

Bt-cry1Ac gene has been reputedly effective against Helicoverpa armigera a notorious lepidopteran pest. Reports on the expression of full-length and truncated cry1Ac genes in plants for effective resistance against Helicoverpa sp. have been documented however, their performance is still ambiguous. Moreover, the question remains to be addressed that truncation of 3' end of the native gene was documented and suggested for active insecticidal toxin production while the most successful transgenic event(s) of commercialized-cotton are based on full-length of the cry gene. Therefore, we performed a comparative study on the efficacy of the two versions of cry1Ac genes (full-length: 3,510 bp and truncated: 1,845 bp) in T0 and T1 transgenic tomato plants and analyzed the extent of protection against H. armigera and also compared the results with our previous findings related to a successful transgenic tomato line Ab25E, expressing cry1Ab gene. The integration of cry1Ac gene(s) in T0 transgenic plants and its inheritance in T1 progeny was observed by PCR, RT-PCR and Southern blot hybridization analysis while, the toxin integrity, expression and toxicity was monitored by Western immunoassay, DAS-ELISA and insect bioassay respectively. An average transformation frequency and Bt-Cry protein content of 16.93 ± 2.10 and 0.0020-0.0128% of total soluble protein (TSP) was obtained with pRD400 vector (Trcry1Ac) while, a much lower value of 9.30 ± 2.041 and 0.0001 - 0.0026% of TSP was observed with pNBRI-1 vector (Flcry1Ac), respectively. The promising Trcry1Ac T0 transgenic plants and their T1 progeny gave full protection from H. armigera. Although Flcry1Ac gene showed lower transformation frequency and lower expression, it showed higher toxicity to H. armigera when compared with truncated Trcry1Ac gene. The full-length cry1Ac gene can be redesigned for higher expression and performance in dicots or a hybrid gene could be designed having a blend of strong receptor binding and stable expression characteristics for enhanced efficacy and toxicity to the susceptible insects.

Insertional Mutagenesis for Genes involved in Otic/Vestibular Development and Function in Xenopus Tropicalis

NASA Technical Reports Server (NTRS)

Torrejon, Marcela; Li, Erica; Nguyen, Minh; Winfree, Seth; Wang, Esther; Reinsch, Sigrid; Dalton, Bonnie (Technical Monitor)

2002-01-01

Sensitivity to gravity is essential for spatial orientation. Consequently, the gravity receptor system is one of the phylogenetically oldest sensory systems, and the special adaptations that enhance sensitivity to gravity are highly conserved. The main goal of this project is to use Xenopus (frog) to identify genes expressed during vestibular and auditory development. These studies will lead a better understanding of the molecular mechanisms involved in vestibular and auditory development and function. We are using a gene-trap approach in Xenopus tropicalis with the green fluorescent protein (GFP) gene as the transgene reporter. GFP expression occurs only when the GFP gene is correctly integrated in actively transcribed genes. Using the GFP as a tag we can easily identify and clone the mutated gene. In addition, we can study the function of the mutated gene by analyzing the defects generated by insertion of the GFP transgene. To date we have tissue specific GFP expression in X. tropicalis including expression in ear, neural tube, kidney, muscle, eyes and nose. Our transgenic animals will soon reach maturity so that we can outcross them and analyze their progeny. Our next goal is to isolate RNA from our transgenics and clone the tagged genes using RACE-PCR. Currently we are optimizing the RACE-PCR method using transgenics with crystallin GFP expression.

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.

Systematic Integration of Brain eQTL and GWAS Identifies ZNF323 as a Novel Schizophrenia Risk Gene and Suggests Recent Positive Selection Based on Compensatory Advantage on Pulmonary Function.

PubMed

Luo, Xiong-Jian; Mattheisen, Manuel; Li, Ming; Huang, Liang; Rietschel, Marcella; Børglum, Anders D; Als, Thomas D; van den Oord, Edwin J; Aberg, Karolina A; Mors, Ole; Mortensen, Preben Bo; Luo, Zhenwu; Degenhardt, Franziska; Cichon, Sven; Schulze, Thomas G; Nöthen, Markus M; Su, Bing; Zhao, Zhongming; Gan, Lin; Yao, Yong-Gang

2015-11-01

Genome-wide association studies have identified multiple risk variants and loci that show robust association with schizophrenia. Nevertheless, it remains unclear how these variants confer risk to schizophrenia. In addition, the driving force that maintains the schizophrenia risk variants in human gene pool is poorly understood. To investigate whether expression-associated genetic variants contribute to schizophrenia susceptibility, we systematically integrated brain expression quantitative trait loci and genome-wide association data of schizophrenia using Sherlock, a Bayesian statistical framework. Our analyses identified ZNF323 as a schizophrenia risk gene (P = 2.22×10(-6)). Subsequent analyses confirmed the association of the ZNF323 and its expression-associated single nucleotide polymorphism rs1150711 in independent samples (gene-expression: P = 1.40×10(-6); single-marker meta-analysis in the combined discovery and replication sample comprising 44123 individuals: P = 6.85×10(-10)). We found that the ZNF323 was significantly downregulated in hippocampus and frontal cortex of schizophrenia patients (P = .0038 and P = .0233, respectively). Evidence for pleiotropic effects was detected (association of rs1150711 with lung function and gene expression of ZNF323 in lung: P = 6.62×10(-5) and P = 9.00×10(-5), respectively) with the risk allele (T allele) for schizophrenia acting as protective allele for lung function. Subsequent population genetics analyses suggest that the risk allele (T) of rs1150711 might have undergone recent positive selection in human population. Our findings suggest that the ZNF323 is a schizophrenia susceptibility gene whose expression may influence schizophrenia risk. Our study also illustrates a possible mechanism for maintaining schizophrenia risk variants in the human gene pool. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Integrative strategies to identify candidate genes in rodent models of human alcoholism.

PubMed

Treadwell, Julie A

2006-01-01

The search for genes underlying alcohol-related behaviours in rodent models of human alcoholism has been ongoing for many years with only limited success. Recently, new strategies that integrate several of the traditional approaches have provided new insights into the molecular mechanisms underlying ethanol's actions in the brain. We have used alcohol-preferring C57BL/6J (B6) and alcohol-avoiding DBA/2J (D2) genetic strains of mice in an integrative strategy combining high-throughput gene expression screening, genetic segregation analysis, and mapping to previously published quantitative trait loci to uncover candidate genes for the ethanol-preference phenotype. In our study, 2 genes, retinaldehyde binding protein 1 (Rlbp1) and syntaxin 12 (Stx12), were found to be strong candidates for ethanol preference. Such experimental approaches have the power and the potential to greatly speed up the laborious process of identifying candidate genes for the animal models of human alcoholism.