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

MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation

PubMed Central

Wang, Luman; Mo, Qiaochu; Wang, Jianxin

2015-01-01

Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches. PMID:26881263

MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation.

PubMed

Wang, Luman; Mo, Qiaochu; Wang, Jianxin

2015-01-01

Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches.

Drug-Path: a database for drug-induced pathways

PubMed Central

Zeng, Hui; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. Database URL: http://www.cuilab.cn/drugpath PMID:26130661

Update of the Diatom EST Database: a new tool for digital transcriptomics

PubMed Central

Maheswari, Uma; Mock, Thomas; Armbrust, E. Virginia; Bowler, Chris

2009-01-01

The Diatom Expressed Sequence Tag (EST) Database was constructed to provide integral access to ESTs from these ecologically and evolutionarily interesting microalgae. It has now been updated with 130 000 Phaeodactylum tricornutum ESTs from 16 cDNA libraries and 77 000 Thalassiosira pseudonana ESTs from seven libraries, derived from cells grown in different nutrient and stress regimes. The updated relational database incorporates results from statistical analyses such as log-likelihood ratios and hierarchical clustering, which help to identify differentially expressed genes under different conditions, and allow similarities in gene expression in different libraries to be investigated in a functional context. The database also incorporates links to the recently sequenced genomes of P. tricornutum and T. pseudonana, enabling an easy cross-talk between the expression pattern of diatom orthologs and the genome browsers. These improvements will facilitate exploration of diatom responses to conditions of ecological relevance and will aid gene function identification of diatom-specific genes and in silico gene prediction in this largely unexplored class of eukaryotes. The updated Diatom EST Database is available at http://www.biologie.ens.fr/diatomics/EST3. PMID:19029140

Liverome: a curated database of liver cancer-related gene signatures with self-contained context information.

PubMed

Lee, Langho; Wang, Kai; Li, Gang; Xie, Zhi; Wang, Yuli; Xu, Jiangchun; Sun, Shaoxian; Pocalyko, David; Bhak, Jong; Kim, Chulhong; Lee, Kee-Ho; Jang, Ye Jin; Yeom, Young Il; Yoo, Hyang-Sook; Hwang, Seungwoo

2011-11-30

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide. A number of molecular profiling studies have investigated the changes in gene and protein expression that are associated with various clinicopathological characteristics of HCC and generated a wealth of scattered information, usually in the form of gene signature tables. A database of the published HCC gene signatures would be useful to liver cancer researchers seeking to retrieve existing differential expression information on a candidate gene and to make comparisons between signatures for prioritization of common genes. A challenge in constructing such database is that a direct import of the signatures as appeared in articles would lead to a loss or ambiguity of their context information that is essential for a correct biological interpretation of a gene's expression change. This challenge arises because designation of compared sample groups is most often abbreviated, ad hoc, or even missing from published signature tables. Without manual curation, the context information becomes lost, leading to uninformative database contents. Although several databases of gene signatures are available, none of them contains informative form of signatures nor shows comprehensive coverage on liver cancer. Thus we constructed Liverome, a curated database of liver cancer-related gene signatures with self-contained context information. Liverome's data coverage is more than three times larger than any other signature database, consisting of 143 signatures taken from 98 HCC studies, mostly microarray and proteome, and involving 6,927 genes. The signatures were post-processed into an informative and uniform representation and annotated with an itemized summary so that all context information is unambiguously self-contained within the database. The signatures were further informatively named and meaningfully organized according to ten functional categories for guided browsing. Its web interface enables a straightforward retrieval of known differential expression information on a query gene and a comparison of signatures to prioritize common genes. The utility of Liverome-collected data is shown by case studies in which useful biological insights on HCC are produced. Liverome database provides a comprehensive collection of well-curated HCC gene signatures and straightforward interfaces for gene search and signature comparison as well. Liverome is available at http://liverome.kobic.re.kr.

Bayesian approach to transforming public gene expression repositories into disease diagnosis databases.

PubMed

Huang, Haiyan; Liu, Chun-Chi; Zhou, Xianghong Jasmine

2010-04-13

The rapid accumulation of gene expression data has offered unprecedented opportunities to study human diseases. The National Center for Biotechnology Information Gene Expression Omnibus is currently the largest database that systematically documents the genome-wide molecular basis of diseases. However, thus far, this resource has been far from fully utilized. This paper describes the first study to transform public gene expression repositories into an automated disease diagnosis database. Particularly, we have developed a systematic framework, including a two-stage Bayesian learning approach, to achieve the diagnosis of one or multiple diseases for a query expression profile along a hierarchical disease taxonomy. Our approach, including standardizing cross-platform gene expression data and heterogeneous disease annotations, allows analyzing both sources of information in a unified probabilistic system. A high level of overall diagnostic accuracy was shown by cross validation. It was also demonstrated that the power of our method can increase significantly with the continued growth of public gene expression repositories. Finally, we showed how our disease diagnosis system can be used to characterize complex phenotypes and to construct a disease-drug connectivity map.

LCGbase: A Comprehensive Database for Lineage-Based Co-regulated Genes.

PubMed

Wang, Dapeng; Zhang, Yubin; Fan, Zhonghua; Liu, Guiming; Yu, Jun

2012-01-01

Animal genes of different lineages, such as vertebrates and arthropods, are well-organized and blended into dynamic chromosomal structures that represent a primary regulatory mechanism for body development and cellular differentiation. The majority of genes in a genome are actually clustered, which are evolutionarily stable to different extents and biologically meaningful when evaluated among genomes within and across lineages. Until now, many questions concerning gene organization, such as what is the minimal number of genes in a cluster and what is the driving force leading to gene co-regulation, remain to be addressed. Here, we provide a user-friendly database-LCGbase (a comprehensive database for lineage-based co-regulated genes)-hosting information on evolutionary dynamics of gene clustering and ordering within animal kingdoms in two different lineages: vertebrates and arthropods. The database is constructed on a web-based Linux-Apache-MySQL-PHP framework and effective interactive user-inquiry service. Compared to other gene annotation databases with similar purposes, our database has three comprehensible advantages. First, our database is inclusive, including all high-quality genome assemblies of vertebrates and representative arthropod species. Second, it is human-centric since we map all gene clusters from other genomes in an order of lineage-ranks (such as primates, mammals, warm-blooded, and reptiles) onto human genome and start the database from well-defined gene pairs (a minimal cluster where the two adjacent genes are oriented as co-directional, convergent, and divergent pairs) to large gene clusters. Furthermore, users can search for any adjacent genes and their detailed annotations. Third, the database provides flexible parameter definitions, such as the distance of transcription start sites between two adjacent genes, which is extendable to genes that flanking the cluster across species. We also provide useful tools for sequence alignment, gene ontology (GO) annotation, promoter identification, gene expression (co-expression), and evolutionary analysis. This database not only provides a way to define lineage-specific and species-specific gene clusters but also facilitates future studies on gene co-regulation, epigenetic control of gene expression (DNA methylation and histone marks), and chromosomal structures in a context of gene clusters and species evolution. LCGbase is freely available at http://lcgbase.big.ac.cn/LCGbase.

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

PubMed

Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis) whereby the recovered sub-networks reconfirm established plant gene functions and also identify novel associations. Together, we present valuable insights into grapevine transcriptional regulation by developing network models applicable to researchers in their prioritisation of gene candidates, for on-going study of biological processes related to grapevine development, metabolism and stress responses.

SurvExpress: an online biomarker validation tool and database for cancer gene expression data using survival analysis.

PubMed

Aguirre-Gamboa, Raul; Gomez-Rueda, Hugo; Martínez-Ledesma, Emmanuel; Martínez-Torteya, Antonio; Chacolla-Huaringa, Rafael; Rodriguez-Barrientos, Alberto; Tamez-Peña, José G; Treviño, Victor

2013-01-01

Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R.

SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis

PubMed Central

Aguirre-Gamboa, Raul; Gomez-Rueda, Hugo; Martínez-Ledesma, Emmanuel; Martínez-Torteya, Antonio; Chacolla-Huaringa, Rafael; Rodriguez-Barrientos, Alberto; Tamez-Peña, José G.; Treviño, Victor

2013-01-01

Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R. PMID:24066126

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.

Arabidopsis Gene Family Profiler (aGFP)--user-oriented transcriptomic database with easy-to-use graphic interface.

PubMed

Dupl'áková, Nikoleta; Renák, David; Hovanec, Patrik; Honysová, Barbora; Twell, David; Honys, David

2007-07-23

Microarray technologies now belong to the standard functional genomics toolbox and have undergone massive development leading to increased genome coverage, accuracy and reliability. The number of experiments exploiting microarray technology has markedly increased in recent years. In parallel with the rapid accumulation of transcriptomic data, on-line analysis tools are being introduced to simplify their use. Global statistical data analysis methods contribute to the development of overall concepts about gene expression patterns and to query and compose working hypotheses. More recently, these applications are being supplemented with more specialized products offering visualization and specific data mining tools. We present a curated gene family-oriented gene expression database, Arabidopsis Gene Family Profiler (aGFP; http://agfp.ueb.cas.cz), which gives the user access to a large collection of normalised Affymetrix ATH1 microarray datasets. The database currently contains NASC Array and AtGenExpress transcriptomic datasets for various tissues at different developmental stages of wild type plants gathered from nearly 350 gene chips. The Arabidopsis GFP database has been designed as an easy-to-use tool for users needing an easily accessible resource for expression data of single genes, pre-defined gene families or custom gene sets, with the further possibility of keyword search. Arabidopsis Gene Family Profiler presents a user-friendly web interface using both graphic and text output. Data are stored at the MySQL server and individual queries are created in PHP script. The most distinguishable features of Arabidopsis Gene Family Profiler database are: 1) the presentation of normalized datasets (Affymetrix MAS algorithm and calculation of model-based gene-expression values based on the Perfect Match-only model); 2) the choice between two different normalization algorithms (Affymetrix MAS4 or MAS5 algorithms); 3) an intuitive interface; 4) an interactive "virtual plant" visualizing the spatial and developmental expression profiles of both gene families and individual genes. Arabidopsis GFP gives users the possibility to analyze current Arabidopsis developmental transcriptomic data starting with simple global queries that can be expanded and further refined to visualize comparative and highly selective gene expression profiles.

Drug-Path: a database for drug-induced pathways.

PubMed

Zeng, Hui; Qiu, Chengxiang; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. © The Author(s) 2015. Published by Oxford University Press.

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface.

PubMed

Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

2009-08-25

Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms.

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

PubMed Central

Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

2009-01-01

Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

MiRNA-TF-gene network analysis through ranking of biomolecules for multi-informative uterine leiomyoma dataset.

PubMed

Mallik, Saurav; Maulik, Ujjwal

2015-10-01

Gene ranking is an important problem in bioinformatics. Here, we propose a new framework for ranking biomolecules (viz., miRNAs, transcription-factors/TFs and genes) in a multi-informative uterine leiomyoma dataset having both gene expression and methylation data using (statistical) eigenvector centrality based approach. At first, genes that are both differentially expressed and methylated, are identified using Limma statistical test. A network, comprising these genes, corresponding TFs from TRANSFAC and ITFP databases, and targeter miRNAs from miRWalk database, is then built. The biomolecules are then ranked based on eigenvector centrality. Our proposed method provides better average accuracy in hub gene and non-hub gene classifications than other methods. Furthermore, pre-ranked Gene set enrichment analysis is applied on the pathway database as well as GO-term databases of Molecular Signatures Database with providing a pre-ranked gene-list based on different centrality values for comparing among the ranking methods. Finally, top novel potential gene-markers for the uterine leiomyoma are provided. Copyright © 2015 Elsevier Inc. All rights reserved.

yStreX: yeast stress expression database

PubMed Central

Wanichthanarak, Kwanjeera; Nookaew, Intawat; Petranovic, Dina

2014-01-01

Over the past decade genome-wide expression analyses have been often used to study how expression of genes changes in response to various environmental stresses. Many of these studies (such as effects of oxygen concentration, temperature stress, low pH stress, osmotic stress, depletion or limitation of nutrients, addition of different chemical compounds, etc.) have been conducted in the unicellular Eukaryal model, yeast Saccharomyces cerevisiae. However, the lack of a unifying or integrated, bioinformatics platform that would permit efficient and rapid use of all these existing data remain an important issue. To facilitate research by exploiting existing transcription data in the field of yeast physiology, we have developed the yStreX database. It is an online repository of analyzed gene expression data from curated data sets from different studies that capture genome-wide transcriptional changes in response to diverse environmental transitions. The first aim of this online database is to facilitate comparison of cross-platform and cross-laboratory gene expression data. Additionally, we performed different expression analyses, meta-analyses and gene set enrichment analyses; and the results are also deposited in this database. Lastly, we constructed a user-friendly Web interface with interactive visualization to provide intuitive access and to display the queried data for users with no background in bioinformatics. Database URL: http://www.ystrexdb.com PMID:25024351

NCBI GEO: mining millions of expression profiles--database and tools.

PubMed

Barrett, Tanya; Suzek, Tugba O; Troup, Dennis B; Wilhite, Stephen E; Ngau, Wing-Chi; Ledoux, Pierre; Rudnev, Dmitry; Lash, Alex E; Fujibuchi, Wataru; Edgar, Ron

2005-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30,000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

PubMed

Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

2017-11-13

The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly correlated with BMI (r = 0.56, P = 0.04), and hub genes of KCNN1 and AQP10 were differentially expressed. We identified significant genes and specific modules potentially related to BMI based on the gene expression profile data of monozygotic twins. The findings may help further elucidate the underlying mechanisms of obesity development and provide novel insights to research potential gene biomarkers and signaling pathways for obesity treatment. Further analysis and validation of the findings reported here are important and necessary when more sample size is acquired.

VitisExpDB: a database resource for grape functional genomics.

PubMed

Doddapaneni, Harshavardhan; Lin, Hong; Walker, M Andrew; Yao, Jiqiang; Civerolo, Edwin L

2008-02-28

The family Vitaceae consists of many different grape species that grow in a range of climatic conditions. In the past few years, several studies have generated functional genomic information on different Vitis species and cultivars, including the European grape vine, Vitis vinifera. Our goal is to develop a comprehensive web data source for Vitaceae. VitisExpDB is an online MySQL-PHP driven relational database that houses annotated EST and gene expression data for V. vinifera and non-vinifera grape species and varieties. Currently, the database stores approximately 320,000 EST sequences derived from 8 species/hybrids, their annotation (BLAST top match) details and Gene Ontology based structured vocabulary. Putative homologs for each EST in other species and varieties along with information on their percent nucleotide identities, phylogenetic relationship and common primers can be retrieved. The database also includes information on probe sequence and annotation features of the high density 60-mer gene expression chip consisting of approximately 20,000 non-redundant set of ESTs. Finally, the database includes 14 processed global microarray expression profile sets. Data from 12 of these expression profile sets have been mapped onto metabolic pathways. A user-friendly web interface with multiple search indices and extensively hyperlinked result features that permit efficient data retrieval has been developed. Several online bioinformatics tools that interact with the database along with other sequence analysis tools have been added. In addition, users can submit their ESTs to the database. The developed database provides genomic resource to grape community for functional analysis of genes in the collection and for the grape genome annotation and gene function identification. The VitisExpDB database is available through our website http://cropdisease.ars.usda.gov/vitis_at/main-page.htm.

VitisExpDB: A database resource for grape functional genomics

PubMed Central

Doddapaneni, Harshavardhan; Lin, Hong; Walker, M Andrew; Yao, Jiqiang; Civerolo, Edwin L

2008-01-01

Background The family Vitaceae consists of many different grape species that grow in a range of climatic conditions. In the past few years, several studies have generated functional genomic information on different Vitis species and cultivars, including the European grape vine, Vitis vinifera. Our goal is to develop a comprehensive web data source for Vitaceae. Description VitisExpDB is an online MySQL-PHP driven relational database that houses annotated EST and gene expression data for V. vinifera and non-vinifera grape species and varieties. Currently, the database stores ~320,000 EST sequences derived from 8 species/hybrids, their annotation (BLAST top match) details and Gene Ontology based structured vocabulary. Putative homologs for each EST in other species and varieties along with information on their percent nucleotide identities, phylogenetic relationship and common primers can be retrieved. The database also includes information on probe sequence and annotation features of the high density 60-mer gene expression chip consisting of ~20,000 non-redundant set of ESTs. Finally, the database includes 14 processed global microarray expression profile sets. Data from 12 of these expression profile sets have been mapped onto metabolic pathways. A user-friendly web interface with multiple search indices and extensively hyperlinked result features that permit efficient data retrieval has been developed. Several online bioinformatics tools that interact with the database along with other sequence analysis tools have been added. In addition, users can submit their ESTs to the database. Conclusion The developed database provides genomic resource to grape community for functional analysis of genes in the collection and for the grape genome annotation and gene function identification. The VitisExpDB database is available through our website . PMID:18307813

The GermOnline cross-species systems browser provides comprehensive information on genes and gene products relevant for sexual reproduction.

PubMed

Gattiker, Alexandre; Niederhauser-Wiederkehr, Christa; Moore, James; Hermida, Leandro; Primig, Michael

2007-01-01

We report a novel release of the GermOnline knowledgebase covering genes relevant for the cell cycle, gametogenesis and fertility. GermOnline was extended into a cross-species systems browser including information on DNA sequence annotation, gene expression and the function of gene products. The database covers eight model organisms and Homo sapiens, for which complete genome annotation data are available. The database is now built around a sophisticated genome browser (Ensembl), our own microarray information management and annotation system (MIMAS) used to extensively describe experimental data obtained with high-density oligonucleotide microarrays (GeneChips) and a comprehensive system for online editing of database entries (MediaWiki). The RNA data include results from classical microarrays as well as tiling arrays that yield information on RNA expression levels, transcript start sites and lengths as well as exon composition. Members of the research community are solicited to help GermOnline curators keep database entries on genes and gene products complete and accurate. The database is accessible at http://www.germonline.org/.

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.

GeneSigDB—a curated database of gene expression signatures

PubMed Central

Culhane, Aedín C.; Schwarzl, Thomas; Sultana, Razvan; Picard, Kermshlise C.; Picard, Shaita C.; Lu, Tim H.; Franklin, Katherine R.; French, Simon J.; Papenhausen, Gerald; Correll, Mick; Quackenbush, John

2010-01-01

The primary objective of most gene expression studies is the identification of one or more gene signatures; lists of genes whose transcriptional levels are uniquely associated with a specific biological phenotype. Whilst thousands of experimentally derived gene signatures are published, their potential value to the community is limited by their computational inaccessibility. Gene signatures are embedded in published article figures, tables or in supplementary materials, and are frequently presented using non-standard gene or probeset nomenclature. We present GeneSigDB (http://compbio.dfci.harvard.edu/genesigdb) a manually curated database of gene expression signatures. GeneSigDB release 1.0 focuses on cancer and stem cells gene signatures and was constructed from more than 850 publications from which we manually transcribed 575 gene signatures. Most gene signatures (n = 560) were successfully mapped to the genome to extract standardized lists of EnsEMBL gene identifiers. GeneSigDB provides the original gene signature, the standardized gene list and a fully traceable gene mapping history for each gene from the original transcribed data table through to the standardized list of genes. The GeneSigDB web portal is easy to search, allows users to compare their own gene list to those in the database, and download gene signatures in most common gene identifier formats. PMID:19934259

GExplore: a web server for integrated queries of protein domains, gene expression and mutant phenotypes

PubMed Central

2009-01-01

Background The majority of the genes even in well-studied multi-cellular model organisms have not been functionally characterized yet. Mining the numerous genome wide data sets related to protein function to retrieve potential candidate genes for a particular biological process remains a challenge. Description GExplore has been developed to provide a user-friendly database interface for data mining at the gene expression/protein function level to help in hypothesis development and experiment design. It supports combinatorial searches for proteins with certain domains, tissue- or developmental stage-specific expression patterns, and mutant phenotypes. GExplore operates on a stand-alone database and has fast response times, which is essential for exploratory searches. The interface is not only user-friendly, but also modular so that it accommodates additional data sets in the future. Conclusion GExplore is an online database for quick mining of data related to gene and protein function, providing a multi-gene display of data sets related to the domain composition of proteins as well as expression and phenotype data. GExplore is publicly available at: http://genome.sfu.ca/gexplore/ PMID:19917126

dbWFA: a web-based database for functional annotation of Triticum aestivum transcripts

PubMed Central

Vincent, Jonathan; Dai, Zhanwu; Ravel, Catherine; Choulet, Frédéric; Mouzeyar, Said; Bouzidi, M. Fouad; Agier, Marie; Martre, Pierre

2013-01-01

The functional annotation of genes based on sequence homology with genes from model species genomes is time-consuming because it is necessary to mine several unrelated databases. The aim of the present work was to develop a functional annotation database for common wheat Triticum aestivum (L.). The database, named dbWFA, is based on the reference NCBI UniGene set, an expressed gene catalogue built by expressed sequence tag clustering, and on full-length coding sequences retrieved from the TriFLDB database. Information from good-quality heterogeneous sources, including annotations for model plant species Arabidopsis thaliana (L.) Heynh. and Oryza sativa L., was gathered and linked to T. aestivum sequences through BLAST-based homology searches. Even though the complexity of the transcriptome cannot yet be fully appreciated, we developed a tool to easily and promptly obtain information from multiple functional annotation systems (Gene Ontology, MapMan bin codes, MIPS Functional Categories, PlantCyc pathway reactions and TAIR gene families). The use of dbWFA is illustrated here with several query examples. We were able to assign a putative function to 45% of the UniGenes and 81% of the full-length coding sequences from TriFLDB. Moreover, comparison of the annotation of the whole T. aestivum UniGene set along with curated annotations of the two model species assessed the accuracy of the annotation provided by dbWFA. To further illustrate the use of dbWFA, genes specifically expressed during the early cell division or late storage polymer accumulation phases of T. aestivum grain development were identified using a clustering analysis and then annotated using dbWFA. The annotation of these two sets of genes was consistent with previous analyses of T. aestivum grain transcriptomes and proteomes. Database URL: urgi.versailles.inra.fr/dbWFA/ PMID:23660284

Construction of a rice glycoside hydrolase phylogenomic database and identification of targets for biofuel research

PubMed Central

Sharma, Rita; Cao, Peijian; Jung, Ki-Hong; Sharma, Manoj K.; Ronald, Pamela C.

2013-01-01

Glycoside hydrolases (GH) catalyze the hydrolysis of glycosidic bonds in cell wall polymers and can have major effects on cell wall architecture. Taking advantage of the massive datasets available in public databases, we have constructed a rice phylogenomic database of GHs (http://ricephylogenomics.ucdavis.edu/cellwalls/gh/). This database integrates multiple data types including the structural features, orthologous relationships, mutant availability, and gene expression patterns for each GH family in a phylogenomic context. The rice genome encodes 437 GH genes classified into 34 families. Based on pairwise comparison with eight dicot and four monocot genomes, we identified 138 GH genes that are highly diverged between monocots and dicots, 57 of which have diverged further in rice as compared with four monocot genomes scanned in this study. Chromosomal localization and expression analysis suggest a role for both whole-genome and localized gene duplications in expansion and diversification of GH families in rice. We examined the meta-profiles of expression patterns of GH genes in twenty different anatomical tissues of rice. Transcripts of 51 genes exhibit tissue or developmental stage-preferential expression, whereas, seventeen other genes preferentially accumulate in actively growing tissues. When queried in RiceNet, a probabilistic functional gene network that facilitates functional gene predictions, nine out of seventeen genes form a regulatory network with the well-characterized genes involved in biosynthesis of cell wall polymers including cellulose synthase and cellulose synthase-like genes of rice. Two-thirds of the GH genes in rice are up regulated in response to biotic and abiotic stress treatments indicating a role in stress adaptation. Our analyses identify potential GH targets for cell wall modification. PMID:23986771

MicroRNA expression, target genes, and signaling pathways in infants with a ventricular septal defect.

PubMed

Chai, Hui; Yan, Zhaoyuan; Huang, Ke; Jiang, Yuanqing; Zhang, Lin

2018-02-01

This study aimed to systematically investigate the relationship between miRNA expression and the occurrence of ventricular septal defect (VSD), and characterize the miRNA target genes and pathways that can lead to VSD. The miRNAs that were differentially expressed in blood samples from VSD and normal infants were screened and validated by implementing miRNA microarrays and qRT-PCR. The target genes regulated by differentially expressed miRNAs were predicted using three target gene databases. The functions and signaling pathways of the target genes were enriched using the GO database and KEGG database, respectively. The transcription and protein expression of specific target genes in critical pathways were compared in the VSD and normal control groups using qRT-PCR and western blotting, respectively. Compared with the normal control group, the VSD group had 22 differentially expressed miRNAs; 19 were downregulated and three were upregulated. The 10,677 predicted target genes participated in many biological functions related to cardiac development and morphogenesis. Four target genes (mGLUR, Gq, PLC, and PKC) were involved in the PKC pathway and four (ECM, FAK, PI3 K, and PDK1) were involved in the PI3 K-Akt pathway. The transcription and protein expression of these eight target genes were significantly upregulated in the VSD group. The 22 miRNAs that were dysregulated in the VSD group were mainly downregulated, which may result in the dysregulation of several key genes and biological functions related to cardiac development. These effects could also be exerted via the upregulation of eight specific target genes, the subsequent over-activation of the PKC and PI3 K-Akt pathways, and the eventual abnormal cardiac development and VSD.

Exploring of the molecular mechanism of rhinitis via bioinformatics methods

PubMed Central

Song, Yufen; Yan, Zhaohui

2018-01-01

The aim of this study was to analyze gene expression profiles for exploring the function and regulatory network of differentially expressed genes (DEGs) in pathogenesis of rhinitis by a bioinformatics method. The gene expression profile of GSE43523 was downloaded from the Gene Expression Omnibus database. The dataset contained 7 seasonal allergic rhinitis samples and 5 non-allergic normal samples. DEGs between rhinitis samples and normal samples were identified via the limma package of R. The webGestal database was used to identify enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the DEGs. The differentially co-expressed pairs of the DEGs were identified via the DCGL package in R, and the differential co-expression network was constructed based on these pairs. A protein-protein interaction (PPI) network of the DEGs was constructed based on the Search Tool for the Retrieval of Interacting Genes database. A total of 263 DEGs were identified in rhinitis samples compared with normal samples, including 125 downregulated ones and 138 upregulated ones. The DEGs were enriched in 7 KEGG pathways. 308 differential co-expression gene pairs were obtained. A differential co-expression network was constructed, containing 212 nodes. In total, 148 PPI pairs of the DEGs were identified, and a PPI network was constructed based on these pairs. Bioinformatics methods could help us identify significant genes and pathways related to the pathogenesis of rhinitis. Steroid biosynthesis pathway and metabolic pathways might play important roles in the development of allergic rhinitis (AR). Genes such as CDC42 effector protein 5, solute carrier family 39 member A11 and PR/SET domain 10 might be also associated with the pathogenesis of AR, which provided references for the molecular mechanisms of AR. PMID:29257233

The Gene Expression Omnibus Database.

PubMed

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

The Gene Expression Omnibus database

PubMed Central

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

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

A-WINGS: an integrated genome database for Pleurocybella porrigens (Angel's wing oyster mushroom, Sugihiratake).

PubMed

Yamamoto, Naoki; Suzuki, Tomohiro; Kobayashi, Masaaki; Dohra, Hideo; Sasaki, Yohei; Hirai, Hirofumi; Yokoyama, Koji; Kawagishi, Hirokazu; Yano, Kentaro

2014-12-03

The angel's wing oyster mushroom (Pleurocybella porrigens, Sugihiratake) is a well-known delicacy. However, its potential risk in acute encephalopathy was recently revealed by a food poisoning incident. To disclose the genes underlying the accident and provide mechanistic insight, we seek to develop an information infrastructure containing omics data. In our previous work, we sequenced the genome and transcriptome using next-generation sequencing techniques. The next step in achieving our goal is to develop a web database to facilitate the efficient mining of large-scale omics data and identification of genes specifically expressed in the mushroom. This paper introduces a web database A-WINGS (http://bioinf.mind.meiji.ac.jp/a-wings/) that provides integrated genomic and transcriptomic information for the angel's wing oyster mushroom. The database contains structure and functional annotations of transcripts and gene expressions. Functional annotations contain information on homologous sequences from NCBI nr and UniProt, Gene Ontology, and KEGG Orthology. Digital gene expression profiles were derived from RNA sequencing (RNA-seq) analysis in the fruiting bodies and mycelia. The omics information stored in the database is freely accessible through interactive and graphical interfaces by search functions that include 'GO TREE VIEW' browsing, keyword searches, and BLAST searches. The A-WINGS database will accelerate omics studies on specific aspects of the angel's wing oyster mushroom and the family Tricholomataceae.

MAGIC database and interfaces: an integrated package for gene discovery and expression.

PubMed

Cordonnier-Pratt, Marie-Michèle; Liang, Chun; Wang, Haiming; Kolychev, Dmitri S; Sun, Feng; Freeman, Robert; Sullivan, Robert; Pratt, Lee H

2004-01-01

The rapidly increasing rate at which biological data is being produced requires a corresponding growth in relational databases and associated tools that can help laboratories contend with that data. With this need in mind, we describe here a Modular Approach to a Genomic, Integrated and Comprehensive (MAGIC) Database. This Oracle 9i database derives from an initial focus in our laboratory on gene discovery via production and analysis of expressed sequence tags (ESTs), and subsequently on gene expression as assessed by both EST clustering and microarrays. The MAGIC Gene Discovery portion of the database focuses on information derived from DNA sequences and on its biological relevance. In addition to MAGIC SEQ-LIMS, which is designed to support activities in the laboratory, it contains several additional subschemas. The latter include MAGIC Admin for database administration, MAGIC Sequence for sequence processing as well as sequence and clone attributes, MAGIC Cluster for the results of EST clustering, MAGIC Polymorphism in support of microsatellite and single-nucleotide-polymorphism discovery, and MAGIC Annotation for electronic annotation by BLAST and BLAT. The MAGIC Microarray portion is a MIAME-compliant database with two components at present. These are MAGIC Array-LIMS, which makes possible remote entry of all information into the database, and MAGIC Array Analysis, which provides data mining and visualization. Because all aspects of interaction with the MAGIC Database are via a web browser, it is ideally suited not only for individual research laboratories but also for core facilities that serve clients at any distance.

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

Transcriptomic Analysis and the Expression of Disease-Resistant Genes in Oryza meyeriana under Native Condition

PubMed Central

He, Bin; Tao, Xiang; Gu, Yinghong; Wei, Changhe; Cheng, Xiaojie; Xiao, Suqin; Cheng, Zaiquan; Zhang, Yizheng

2015-01-01

Oryza meyeriana (O. meyeriana), with a GG genome type (2n = 24), accumulated plentiful excellent characteristics with respect to resistance to many diseases such as rice shade and blast, even immunity to bacterial blight. It is very important to know if the diseases-resistant genes exist and express in this wild rice under native conditions. However, limited genomic or transcriptomic data of O. meyeriana are currently available. In this study, we present the first comprehensive characterization of the O. meyeriana transcriptome using RNA-seq and obtained 185,323 contigs with an average length of 1,692 bp and an N50 of 2,391 bp. Through differential expression analysis, it was found that there were most tissue-specifically expressed genes in roots, and next to stems and leaves. By similarity search against protein databases, 146,450 had at least a significant alignment to existed gene models. Comparison with the Oryza sativa (japonica-type Nipponbare and indica-type 93–11) genomes revealed that 13% of the O. meyeriana contigs had not been detected in O. sativa. Many diseases-resistant genes, such as bacterial blight resistant, blast resistant, rust resistant, fusarium resistant, cyst nematode resistant and downy mildew gene, were mined from the transcriptomic database. There are two kinds of rice bacterial blight-resistant genes (Xa1 and Xa26) differentially or specifically expressed in O. meyeriana. The 4 Xa1 contigs were all only expressed in root, while three of Xa26 contigs have the highest expression level in leaves, two of Xa26 contigs have the highest expression profile in stems and one of Xa26 contigs was expressed dominantly in roots. The transcriptomic database of O. meyeriana has been constructed and many diseases-resistant genes were found to express under native condition, which provides a foundation for future discovery of a number of novel genes and provides a basis for studying the molecular mechanisms associated with disease resistance in O. meyeriana. PMID:26640944

CellLineNavigator: a workbench for cancer cell line analysis

PubMed Central

Krupp, Markus; Itzel, Timo; Maass, Thorsten; Hildebrandt, Andreas; Galle, Peter R.; Teufel, Andreas

2013-01-01

The CellLineNavigator database, freely available at http://www.medicalgenomics.org/celllinenavigator, is a web-based workbench for large scale comparisons of a large collection of diverse cell lines. It aims to support experimental design in the fields of genomics, systems biology and translational biomedical research. Currently, this compendium holds genome wide expression profiles of 317 different cancer cell lines, categorized into 57 different pathological states and 28 individual tissues. To enlarge the scope of CellLineNavigator, the database was furthermore closely linked to commonly used bioinformatics databases and knowledge repositories. To ensure easy data access and search ability, a simple data and an intuitive querying interface were implemented. It allows the user to explore and filter gene expression, focusing on pathological or physiological conditions. For a more complex search, the advanced query interface may be used to query for (i) differentially expressed genes; (ii) pathological or physiological conditions; or (iii) gene names or functional attributes, such as Kyoto Encyclopaedia of Genes and Genomes pathway maps. These queries may also be combined. Finally, CellLineNavigator allows additional advanced analysis of differentially regulated genes by a direct link to the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources. PMID:23118487

Identification of Novel Tissue-Specific Genes by Analysis of Microarray Databases: A Human and Mouse Model

PubMed Central

Suh, Yeunsu; Davis, Michael E.; Lee, Kichoon

2013-01-01

Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI′s Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved. PMID:23741331

Identification of differentially expressed genes in cucumber (Cucumis sativus L.) root under waterlogging stress by digital gene expression profile.

PubMed

Qi, Xiao-Hua; Xu, Xue-Wen; Lin, Xiao-Jian; Zhang, Wen-Jie; Chen, Xue-Hao

2012-03-01

High-throughput tag-sequencing (Tag-seq) analysis based on the Solexa Genome Analyzer platform was applied to analyze the gene expression profiling of cucumber plant at 5 time points over a 24h period of waterlogging treatment. Approximately 5.8 million total clean sequence tags per library were obtained with 143013 distinct clean tag sequences. Approximately 23.69%-29.61% of the distinct clean tags were mapped unambiguously to the unigene database, and 53.78%-60.66% of the distinct clean tags were mapped to the cucumber genome database. Analysis of the differentially expressed genes revealed that most of the genes were down-regulated in the waterlogging stages, and the differentially expressed genes mainly linked to carbon metabolism, photosynthesis, reactive oxygen species generation/scavenging, and hormone synthesis/signaling. Finally, quantitative real-time polymerase chain reaction using nine genes independently verified the tag-mapped results. This present study reveals the comprehensive mechanisms of waterlogging-responsive transcription in cucumber. Copyright © 2011 Elsevier Inc. All rights reserved.

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.

PubMed

Wang, Anping; Zhang, Guibin

2017-11-01

The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.

GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data.

PubMed

Ben-Ari Fuchs, Shani; Lieder, Iris; Stelzer, Gil; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

2016-03-01

Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ ( geneanalytics.genecards.org ), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®--the human gene database; the MalaCards-the human diseases database; and the PathCards--the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®--the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene-tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics, and others yet to emerge on the postgenomics horizon.

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

The complex genetics of human insulin-like growth factor 2 are not reflected in public databases.

PubMed

Rotwein, Peter

2018-03-23

Recent advances in genetics present unique opportunities for enhancing knowledge about human physiology and disease susceptibility. Understanding this information at the individual gene level is challenging and requires extracting, collating, and interpreting data from a variety of public gene repositories. Here, I illustrate this challenge by analyzing the gene for human insulin-like growth factor 2 ( IGF2 ) through the lens of several databases. IGF2, a 67-amino acid secreted peptide, is essential for normal prenatal growth and is involved in other physiological and pathophysiological processes in humans. Surprisingly, none of the genetic databases accurately described or completely delineated human IGF2 gene structure or transcript expression, even though all relevant information could be found in the published literature. Although IGF2 shares multiple features with the mouse Igf2 gene, it has several unique properties, including transcription from five promoters. Both genes undergo parental imprinting, with IGF2 / Igf2 being expressed primarily from the paternal chromosome and the adjacent H19 gene from the maternal chromosome. Unlike mouse Igf2 , whose expression declines after birth, human IGF2 remains active throughout life. This characteristic has been attributed to a unique human gene promoter that escapes imprinting, but as shown here, it involves several different promoters with distinct tissue-specific expression patterns. Because new testable hypotheses could lead to critical insights into IGF2 actions in human physiology and disease, it is incumbent that our fundamental understanding is accurate. Similar challenges affecting knowledge of other human genes should promote attempts to critically evaluate, interpret, and correct human genetic data in publicly available databases. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Tcof1-Related Molecular Networks in Treacher Collins Syndrome.

PubMed

Dai, Jiewen; Si, Jiawen; Wang, Minjiao; Huang, Li; Fang, Bing; Shi, Jun; Wang, Xudong; Shen, Guofang

2016-09-01

Treacher Collins syndrome (TCS) is a rare, autosomal-dominant disorder characterized by craniofacial deformities, and is primarily caused by mutations in the Tcof1 gene. This article was aimed to perform a comprehensive literature review and systematic bioinformatic analysis of Tcof1-related molecular networks in TCS. First, the up- and down-regulated genes in Tcof1 heterozygous haploinsufficient mutant mice embryos and Tcof1 knockdown and Tcof1 over-expressed neuroblastoma N1E-115 cells were obtained from the Gene Expression Omnibus database. The GeneDecks database was used to calculate the 500 genes most closely related to Tcof1. Then, the relationships between 4 gene sets (a predicted set and sets comparing the wildtype with the 3 Gene Expression Omnibus datasets) were analyzed using the DAVID, GeneMANIA and STRING databases. The analysis results showed that the Tcof1-related genes were enriched in various biological processes, including cell proliferation, apoptosis, cell cycle, differentiation, and migration. They were also enriched in several signaling pathways, such as the ribosome, p53, cell cycle, and WNT signaling pathways. Additionally, these genes clearly had direct or indirect interactions with Tcof1 and between each other. Literature review and bioinformatic analysis finds imply that special attention should be given to these pathways, as they may offer target points for TCS therapies.

GRBase, a new gene regulation data base available by anonymous ftp.

PubMed Central

Collier, B; Danielsen, M

1994-01-01

The Gene Regulation Database (GRBase) is a compendium of information on the structure and function of proteins involved in the control of gene expression in eukaryotes. These proteins include transcription factors, proteins involved in signal transduction, and receptors. The database can be obtained by FTP in Filemaker Pro, text, and postscript formats. The database will be expanded in the coming year to include reviews on families of proteins involved in gene regulation and to allow online searching. PMID:7937071

DNA methylation biomarkers for head and neck squamous cell carcinoma.

PubMed

Zhou, Chongchang; Ye, Meng; Ni, Shumin; Li, Qun; Ye, Dong; Li, Jinyun; Shen, Zhishen; Deng, Hongxia

2018-06-21

DNA methylation plays an important role in the etiology and pathogenesis of head and neck squamous cell carcinoma (HNSCC). The current study aimed to identify aberrantly methylated-differentially expressed genes (DEGs) by a comprehensive bioinformatics analysis. In addition, we screened for DEGs affected by DNA methylation modification and further investigated their prognostic values for HNSCC. We included microarray data of DNA methylation (GSE25093 and GSE33202) and gene expression (GSE23036 and GSE58911) from Gene Expression Omnibus. Aberrantly methylated-DEGs were analyzed with R software. The Cancer Genome Atlas (TCGA) RNA sequencing and DNA methylation (Illumina HumanMethylation450) databases were utilized for validation. In total, 27 aberrantly methylated genes accompanied by altered expression were identified. After confirmation by The Cancer Genome Atlas (TCGA) database, 2 hypermethylated-low-expression genes (FAM135B and ZNF610) and 2 hypomethylated-high-expression genes (HOXA9 and DCC) were identified. A receiver operating characteristic (ROC) curve confirmed the diagnostic value of these four methylated genes for HNSCC. Multivariate Cox proportional hazards analysis showed that FAM135B methylation was a favorable independent prognostic biomarker for overall survival of HNSCC patients.

EMAP and EMAGE: a framework for understanding spatially organized data.

PubMed

Baldock, Richard A; Bard, Jonathan B L; Burger, Albert; Burton, Nicolas; Christiansen, Jeff; Feng, Guanjie; Hill, Bill; Houghton, Derek; Kaufman, Matthew; Rao, Jianguo; Sharpe, James; Ross, Allyson; Stevenson, Peter; Venkataraman, Shanmugasundaram; Waterhouse, Andrew; Yang, Yiya; Davidson, Duncan R

2003-01-01

The Edinburgh MouseAtlas Project (EMAP) is a time-series of mouse-embryo volumetric models. The models provide a context-free spatial framework onto which structural interpretations and experimental data can be mapped. This enables collation, comparison, and query of complex spatial patterns with respect to each other and with respect to known or hypothesized structure. The atlas also includes a time-dependent anatomical ontology and mapping between the ontology and the spatial models in the form of delineated anatomical regions or tissues. The models provide a natural, graphical context for browsing and visualizing complex data. The Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) is one of the first applications of the EMAP framework and provides a spatially mapped gene-expression database with associated tools for data mapping, submission, and query. In this article, we describe the underlying principles of the Atlas and the gene-expression database, and provide a practical introduction to the use of the EMAP and EMAGE tools, including use of new techniques for whole body gene-expression data capture and mapping.

PAGE-1, an X chromosome-linked GAGE-like gene that is expressed in normal and neoplastic prostate, testis, and uterus

PubMed Central

Brinkmann, Ulrich; Vasmatzis, George; Lee, Byungkook; Yerushalmi, Noga; Essand, Magnus; Pastan, Ira

1998-01-01

We have used a combination of computerized database mining and experimental expression analyses to identify a gene that is preferentially expressed in normal male and female reproductive tissues, prostate, testis, fallopian tube, uterus, and placenta, as well as in prostate cancer, testicular cancer, and uterine cancer. This gene is located on the human X chromosome, and it is homologous to a family of genes encoding GAGE-like proteins. GAGE proteins are expressed in a variety of tumors and in testis. We designate the novel gene PAGE-1 because the expression pattern in the Cancer Genome Anatomy Project libraries indicates that it is predominantly expressed in normal and neoplastic prostate. Further database analysis indicates the presence of other genes with high homology to PAGE-1, which were found in cDNA libraries derived from testis, pooled libraries (with testis), and in a germ cell tumor library. The expression of PAGE-1 in normal and malignant prostate, testicular, and uterine tissues makes it a possible target for the diagnosis and possibly for the vaccine-based therapy of neoplasms of prostate, testis, and uterus. PMID:9724777

PAGE-1, an X chromosome-linked GAGE-like gene that is expressed in normal and neoplastic prostate, testis, and uterus.

PubMed

Brinkmann, U; Vasmatzis, G; Lee, B; Yerushalmi, N; Essand, M; Pastan, I

1998-09-01

We have used a combination of computerized database mining and experimental expression analyses to identify a gene that is preferentially expressed in normal male and female reproductive tissues, prostate, testis, fallopian tube, uterus, and placenta, as well as in prostate cancer, testicular cancer, and uterine cancer. This gene is located on the human X chromosome, and it is homologous to a family of genes encoding GAGE-like proteins. GAGE proteins are expressed in a variety of tumors and in testis. We designate the novel gene PAGE-1 because the expression pattern in the Cancer Genome Anatomy Project libraries indicates that it is predominantly expressed in normal and neoplastic prostate. Further database analysis indicates the presence of other genes with high homology to PAGE-1, which were found in cDNA libraries derived from testis, pooled libraries (with testis), and in a germ cell tumor library. The expression of PAGE-1 in normal and malignant prostate, testicular, and uterine tissues makes it a possible target for the diagnosis and possibly for the vaccine-based therapy of neoplasms of prostate, testis, and uterus.

[Genome-wide identification and expression analysis of auxin-related gene families in grape].

PubMed

Yuan, Hua-zhao; Zhao, Mi-zhen; Wu, Wei-min; Yu, Hong-Mei; Qian, Ya-ming; Wang, Zhuang-wei; Wang, Xi-cheng

2015-07-01

The auxin response gene family adjusts the auxin balance and the growth hormone signaling pathways in plants. Using bioinformatics methods, the auxin-response genes from the grape genome database are identified and their chromosomal location, gene collinearity and phylogenetic analysis are performed. Probable genes include 25 AUX_IAA, 19 ARF, 9 GH3 and 42 LBD genes, which are unevenly distributed on all 19 chromosomes and some of them formed distinct tandem duplicate gene clusters. The available grape microarray databases show that all of the auxin-response genes are expressed in fruit and leaf buds, and significant overexpressed during fruit color-changing, bud break and bud dormancy periods. This paper provides a resource for functional studies of auxin-response genes in grape leaf and fruit development.

Analysis of gene expression profile microarray data in complex regional pain syndrome.

PubMed

Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing

2017-09-01

The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

Database construction for PromoterCAD: synthetic promoter design for mammals and plants.

PubMed

Nishikata, Koro; Cox, Robert Sidney; Shimoyama, Sayoko; Yoshida, Yuko; Matsui, Minami; Makita, Yuko; Toyoda, Tetsuro

2014-03-21

Synthetic promoters can control a gene's timing, location, and expression level. The PromoterCAD web server ( http://promotercad.org ) allows the design of synthetic promoters to control plant gene expression, by novel arrangement of cis-regulatory elements. Recently, we have expanded PromoterCAD's scope with additional plant and animal data: (1) PLACE (Plant Cis-acting Regulatory DNA Elements), including various sized sequence motifs; (2) PEDB (Mammalian Promoter/Enhancer Database), including gene expression data for mammalian tissues. The plant PromoterCAD data now contains 22 000 Arabidopsis thaliana genes, 2 200 000 microarray measurements in 20 growth conditions and 79 tissue organs and developmental stages, while the new mammalian PromoterCAD data contains 679 Mus musculus genes and 65 000 microarray measurements in 96 tissue organs and cell types ( http://promotercad.org/mammal/ ). This work presents step-by-step instructions for adding both regulatory motif and gene expression data to PromoterCAD, to illustrate how users can expand PromoterCAD functionality for their own applications and organisms.

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

PubMed

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

2007-01-01

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

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.

Database of cattle candidate genes and genetic markers for milk production and mastitis

PubMed Central

Ogorevc, J; Kunej, T; Razpet, A; Dovc, P

2009-01-01

A cattle database of candidate genes and genetic markers for milk production and mastitis has been developed to provide an integrated research tool incorporating different types of information supporting a genomic approach to study lactation, udder development and health. The database contains 943 genes and genetic markers involved in mammary gland development and function, representing candidates for further functional studies. The candidate loci were drawn on a genetic map to reveal positional overlaps. For identification of candidate loci, data from seven different research approaches were exploited: (i) gene knockouts or transgenes in mice that result in specific phenotypes associated with mammary gland (143 loci); (ii) cattle QTL for milk production (344) and mastitis related traits (71); (iii) loci with sequence variations that show specific allele-phenotype interactions associated with milk production (24) or mastitis (10) in cattle; (iv) genes with expression profiles associated with milk production (207) or mastitis (107) in cattle or mouse; (v) cattle milk protein genes that exist in different genetic variants (9); (vi) miRNAs expressed in bovine mammary gland (32) and (vii) epigenetically regulated cattle genes associated with mammary gland function (1). Fourty-four genes found by multiple independent analyses were suggested as the most promising candidates and were further in silico analysed for expression levels in lactating mammary gland, genetic variability and top biological functions in functional networks. A miRNA target search for mammary gland expressed miRNAs identified 359 putative binding sites in 3′UTRs of candidate genes. PMID:19508288

Identification of genes differentially expressed in ectomycorrhizal roots during the Pinus pinaster-Laccaria bicolor interaction.

PubMed

Flores-Monterroso, Aranzazu; Canales, Javier; de la Torre, Fernando; Ávila, Concepción; Cánovas, Francisco M

2013-06-01

Ectomycorrhizal associations are of major ecological importance in temperate and boreal forests. The development of a functional ectomycorrhiza requires many genetic and biochemical changes. In this study, suppressive subtraction hybridization was used to identify differentially expressed genes in the roots of maritime pine (Pinus pinaster Aiton) inoculated with Laccaria bicolor, a mycorrhizal fungus. A total number of 200 unigenes were identified as being differentially regulated in maritime pine roots during the development of mycorrhiza. These unigenes were classified into 10 categories according to the function of their homologues in the GenBank database. Approximately, 40 % of the differentially expressed transcripts were genes that coded for unknown proteins in the databases or that had no homology to known genes. A group of these differentially expressed genes was selected to validate the results using quantitative real-time PCR. The transcript levels of the representative genes were compared between the non-inoculated and inoculated plants at 1, 5, 15 and 30 days after inoculation. The observed expression patterns indicate (1) changes in the composition of the wall cell, (2) tight regulation of defence genes during the development of mycorrhiza and (3) changes in carbon and nitrogen metabolism. Ammonium excess or deficiency dramatically affected the stability of ectomycorrhiza and altered gene expression in maritime pine roots.

Release of (and lessons learned from mining) a pioneering large toxicogenomics database.

PubMed

Sandhu, Komal S; Veeramachaneni, Vamsi; Yao, Xiang; Nie, Alex; Lord, Peter; Amaratunga, Dhammika; McMillian, Michael K; Verheyen, Geert R

2015-07-01

We release the Janssen Toxicogenomics database. This rat liver gene-expression database was generated using Codelink microarrays, and has been used over the past years within Janssen to derive signatures for multiple end points and to classify proprietary compounds. The release consists of gene-expression responses to 124 compounds, selected to give a broad coverage of liver-active compounds. A selection of the compounds were also analyzed on Affymetrix microarrays. The release includes results of an in-house reannotation pipeline to Entrez gene annotations, to classify probes into different confidence classes. High confidence unambiguously annotated probes were used to create gene-level data which served as starting point for cross-platform comparisons. Connectivity map-based similarity methods show excellent agreement between Codelink and Affymetrix runs of the same samples. We also compared our dataset with the Japanese Toxicogenomics Project and observed reasonable agreement, especially for compounds with stronger gene signatures. We describe an R-package containing the gene-level data and show how it can be used for expression-based similarity searches. Comparing the same biological samples run on the Affymetrix and the Codelink platform, good correspondence is observed using connectivity mapping approaches. As expected, this correspondence is smaller when the data are compared with an independent dataset such as TG-GATE. We hope that this collection of gene-expression profiles will be incorporated in toxicogenomics pipelines of users.

Combining Evidence of Preferential Gene-Tissue Relationships from Multiple Sources

PubMed Central

Guo, Jing; Hammar, Mårten; Öberg, Lisa; Padmanabhuni, Shanmukha S.; Bjäreland, Marcus; Dalevi, Daniel

2013-01-01

An important challenge in drug discovery and disease prognosis is to predict genes that are preferentially expressed in one or a few tissues, i.e. showing a considerably higher expression in one tissue(s) compared to the others. Although several data sources and methods have been published explicitly for this purpose, they often disagree and it is not evident how to retrieve these genes and how to distinguish true biological findings from those that are due to choice-of-method and/or experimental settings. In this work we have developed a computational approach that combines results from multiple methods and datasets with the aim to eliminate method/study-specific biases and to improve the predictability of preferentially expressed human genes. A rule-based score is used to merge and assign support to the results. Five sets of genes with known tissue specificity were used for parameter pruning and cross-validation. In total we identify 3434 tissue-specific genes. We compare the genes of highest scores with the public databases: PaGenBase (microarray), TiGER (EST) and HPA (protein expression data). The results have 85% overlap to PaGenBase, 71% to TiGER and only 28% to HPA. 99% of our predictions have support from at least one of these databases. Our approach also performs better than any of the databases on identifying drug targets and biomarkers with known tissue-specificity. PMID:23950964

Analysis of the Nicotiana tabacum Stigma/Style Transcriptome Reveals Gene Expression Differences between Wet and Dry Stigma Species1[W][OA

PubMed Central

Quiapim, Andréa C.; Brito, Michael S.; Bernardes, Luciano A.S.; daSilva, Idalete; Malavazi, Iran; DePaoli, Henrique C.; Molfetta-Machado, Jeanne B.; Giuliatti, Silvana; Goldman, Gustavo H.; Goldman, Maria Helena S.

2009-01-01

The success of plant reproduction depends on pollen-pistil interactions occurring at the stigma/style. These interactions vary depending on the stigma type: wet or dry. Tobacco (Nicotiana tabacum) represents a model of wet stigma, and its stigmas/styles express genes to accomplish the appropriate functions. For a large-scale study of gene expression during tobacco pistil development and preparation for pollination, we generated 11,216 high-quality expressed sequence tags (ESTs) from stigmas/styles and created the TOBEST database. These ESTs were assembled in 6,177 clusters, from which 52.1% are pistil transcripts/genes of unknown function. The 21 clusters with the highest number of ESTs (putative higher expression levels) correspond to genes associated with defense mechanisms or pollen-pistil interactions. The database analysis unraveled tobacco sequences homologous to the Arabidopsis (Arabidopsis thaliana) genes involved in specifying pistil identity or determining normal pistil morphology and function. Additionally, 782 independent clusters were examined by macroarray, revealing 46 stigma/style preferentially expressed genes. Real-time reverse transcription-polymerase chain reaction experiments validated the pistil-preferential expression for nine out of 10 genes tested. A search for these 46 genes in the Arabidopsis pistil data sets demonstrated that only 11 sequences, with putative equivalent molecular functions, are expressed in this dry stigma species. The reverse search for the Arabidopsis pistil genes in the TOBEST exposed a partial overlap between these dry and wet stigma transcriptomes. The TOBEST represents the most extensive survey of gene expression in the stigmas/styles of wet stigma plants, and our results indicate that wet and dry stigmas/styles express common as well as distinct genes in preparation for the pollination process. PMID:19052150

Identification of candidate genes in Populus cell wall biosynthesis using text-mining, co-expression network and comparative genomics

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

Yang, Xiaohan; Ye, Chuyu; Bisaria, Anjali

2011-01-01

Populus is an important bioenergy crop for bioethanol production. A greater understanding of cell wall biosynthesis processes is critical in reducing biomass recalcitrance, a major hindrance in efficient generation of ethanol from lignocellulosic biomass. Here, we report the identification of candidate cell wall biosynthesis genes through the development and application of a novel bioinformatics pipeline. As a first step, via text-mining of PubMed publications, we obtained 121 Arabidopsis genes that had the experimental evidences supporting their involvement in cell wall biosynthesis or remodeling. The 121 genes were then used as bait genes to query an Arabidopsis co-expression database and additionalmore » genes were identified as neighbors of the bait genes in the network, increasing the number of genes to 548. The 548 Arabidopsis genes were then used to re-query the Arabidopsis co-expression database and re-construct a network that captured additional network neighbors, expanding to a total of 694 genes. The 694 Arabidopsis genes were computationally divided into 22 clusters. Queries of the Populus genome using the Arabidopsis genes revealed 817 Populus orthologs. Functional analysis of gene ontology and tissue-specific gene expression indicated that these Arabidopsis and Populus genes are high likelihood candidates for functional genomics in relation to cell wall biosynthesis.« less

[Establishment of a comprehensive database for laryngeal cancer related genes and the miRNAs].

PubMed

Li, Mengjiao; E, Qimin; Liu, Jialin; Huang, Tingting; Liang, Chuanyu

2015-09-01

By collecting and analyzing the laryngeal cancer related genes and the miRNAs, to build a comprehensive laryngeal cancer-related gene database, which differs from the current biological information database with complex and clumsy structure and focuses on the theme of gene and miRNA, and it could make the research and teaching more convenient and efficient. Based on the B/S architecture, using Apache as a Web server, MySQL as coding language of database design and PHP as coding language of web design, a comprehensive database for laryngeal cancer-related genes was established, providing with the gene tables, protein tables, miRNA tables and clinical information tables of the patients with laryngeal cancer. The established database containsed 207 laryngeal cancer related genes, 243 proteins, 26 miRNAs, and their particular information such as mutations, methylations, diversified expressions, and the empirical references of laryngeal cancer relevant molecules. The database could be accessed and operated via the Internet, by which browsing and retrieval of the information were performed. The database were maintained and updated regularly. The database for laryngeal cancer related genes is resource-integrated and user-friendly, providing a genetic information query tool for the study of laryngeal cancer.

DNetDB: The human disease network database based on dysfunctional regulation mechanism.

PubMed

Yang, Jing; Wu, Su-Juan; Yang, Shao-You; Peng, Jia-Wei; Wang, Shi-Nuo; Wang, Fu-Yan; Song, Yu-Xing; Qi, Ting; Li, Yi-Xue; Li, Yuan-Yuan

2016-05-21

Disease similarity study provides new insights into disease taxonomy, pathogenesis, which plays a guiding role in diagnosis and treatment. The early studies were limited to estimate disease similarities based on clinical manifestations, disease-related genes, medical vocabulary concepts or registry data, which were inevitably biased to well-studied diseases and offered small chance of discovering novel findings in disease relationships. In other words, genome-scale expression data give us another angle to address this problem since simultaneous measurement of the expression of thousands of genes allows for the exploration of gene transcriptional regulation, which is believed to be crucial to biological functions. Although differential expression analysis based methods have the potential to explore new disease relationships, it is difficult to unravel the upstream dysregulation mechanisms of diseases. We therefore estimated disease similarities based on gene expression data by using differential coexpression analysis, a recently emerging method, which has been proved to be more potential to capture dysfunctional regulation mechanisms than differential expression analysis. A total of 1,326 disease relationships among 108 diseases were identified, and the relevant information constituted the human disease network database (DNetDB). Benefiting from the use of differential coexpression analysis, the potential common dysfunctional regulation mechanisms shared by disease pairs (i.e. disease relationships) were extracted and presented. Statistical indicators, common disease-related genes and drugs shared by disease pairs were also included in DNetDB. In total, 1,326 disease relationships among 108 diseases, 5,598 pathways, 7,357 disease-related genes and 342 disease drugs are recorded in DNetDB, among which 3,762 genes and 148 drugs are shared by at least two diseases. DNetDB is the first database focusing on disease similarity from the viewpoint of gene regulation mechanism. It provides an easy-to-use web interface to search and browse the disease relationships and thus helps to systematically investigate etiology and pathogenesis, perform drug repositioning, and design novel therapeutic interventions.Database URL: http://app.scbit.org/DNetDB/ #.

Tomato Expression Database (TED): a suite of data presentation and analysis tools

PubMed Central

Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James

2006-01-01

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150 000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at . PMID:16381976

Tomato Expression Database (TED): a suite of data presentation and analysis tools.

PubMed

Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James

2006-01-01

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150,000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at http://ted.bti.cornell.edu.

Identification of functional enolase genes of the silkworm Bombyx mori from public databases with a combination of dry and wet bench processes.

PubMed

Kikuchi, Akira; Nakazato, Takeru; Ito, Katsuhiko; Nojima, Yosui; Yokoyama, Takeshi; Iwabuchi, Kikuo; Bono, Hidemasa; Toyoda, Atsushi; Fujiyama, Asao; Sato, Ryoichi; Tabunoki, Hiroko

2017-01-13

Various insect species have been added to genomic databases over the years. Thus, researchers can easily obtain online genomic information on invertebrates and insects. However, many incorrectly annotated genes are included in these databases, which can prevent the correct interpretation of subsequent functional analyses. To address this problem, we used a combination of dry and wet bench processes to select functional genes from public databases. Enolase is an important glycolytic enzyme in all organisms. We used a combination of dry and wet bench processes to identify functional enolases in the silkworm Bombyx mori (BmEno). First, we detected five annotated enolases from public databases using a Hidden Markov Model (HMM) search, and then through cDNA cloning, Northern blotting, and RNA-seq analysis, we revealed three functional enolases in B. mori: BmEno1, BmEno2, and BmEnoC. BmEno1 contained a conserved key amino acid residue for metal binding and substrate binding in other species. However, BmEno2 and BmEnoC showed a change in this key amino acid. Phylogenetic analysis showed that BmEno2 and BmEnoC were distinct from BmEno1 and other enolases, and were distributed only in lepidopteran clusters. BmEno1 was expressed in all of the tissues used in our study. In contrast, BmEno2 was mainly expressed in the testis with some expression in the ovary and suboesophageal ganglion. BmEnoC was weakly expressed in the testis. Quantitative RT-PCR showed that the mRNA expression of BmEno2 and BmEnoC correlated with testis development; thus, BmEno2 and BmEnoC may be related to lepidopteran-specific spermiogenesis. We identified and characterized three functional enolases from public databases with a combination of dry and wet bench processes in the silkworm B. mori. In addition, we determined that BmEno2 and BmEnoC had species-specific functions. Our strategy could be helpful for the detection of minor genes and functional genes in non-model organisms from public databases.

Global differential expression of genes located in the Down Syndrome Critical Region in normal human brain

PubMed Central

Montoya, Julio Cesar; Fajardo, Dianora; Peña, Angela; Sánchez, Adalberto; Domínguez, Martha C; Satizábal, José María

2014-01-01

Background: The information of gene expression obtained from databases, have made possible the extraction and analysis of data related with several molecular processes involving not only in brain homeostasis but its disruption in some neuropathologies; principally in Down syndrome and the Alzheimer disease. Objective: To correlate the levels of transcription of 19 genes located in the Down Syndrome Critical Region (DSCR) with their expression in several substructures of normal human brain. Methods: There were obtained expression profiles of 19 DSCR genes in 42 brain substructures, from gene expression values available at the database of the human brain of the Brain Atlas of the Allen Institute for Brain Sciences", (http://human.brain-map.org/). The co-expression patterns of DSCR genes in brain were calculated by using multivariate statistical methods. Results: Highest levels of gene expression were registered at caudate nucleus, nucleus accumbens and putamen among central areas of cerebral cortex. Increased expression levels of RCAN1 that encode by a protein involved in signal transduction process of the CNS were recorded for PCP4 that participates in the binding to calmodulin and TTC3; a protein that is associated with differentiation of neurons. That previously identified brain structures play a crucial role in the learning process, in different class of memory and in motor skills. Conclusion: The precise regulation of DSCR gene expression is crucial to maintain the brain homeostasis, especially in those areas with high levels of gene expression associated with a remarkable process of learning and cognition. PMID:25767303

Systematic identification of human housekeeping genes possibly useful as references in gene expression studies.

PubMed

Caracausi, Maria; Piovesan, Allison; Antonaros, Francesca; Strippoli, Pierluigi; Vitale, Lorenza; Pelleri, Maria Chiara

2017-09-01

The ideal reference, or control, gene for the study of gene expression in a given organism should be expressed at a medium‑high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human gene expression studies in biology and medicine, both cross‑ and within‑tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra‑ and inter‑sample normalization, elaboration and representation of gene expression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross‑tissue width of expression for more than 31,000 transcripts. The present study conducted a meta‑analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue‑ and organ‑specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative, quantitative portrait of the relative, typical gene‑expression profile in the form of searchable database tables.

HRGFish: A database of hypoxia responsive genes in fishes

NASA Astrophysics Data System (ADS)

Rashid, Iliyas; Nagpure, Naresh Sahebrao; Srivastava, Prachi; Kumar, Ravindra; Pathak, Ajey Kumar; Singh, Mahender; Kushwaha, Basdeo

2017-02-01

Several studies have highlighted the changes in the gene expression due to the hypoxia response in fishes, but the systematic organization of the information and the analytical platform for such genes are lacking. In the present study, an attempt was made to develop a database of hypoxia responsive genes in fishes (HRGFish), integrated with analytical tools, using LAMPP technology. Genes reported in hypoxia response for fishes were compiled through literature survey and the database presently covers 818 gene sequences and 35 gene types from 38 fishes. The upstream fragments (3,000 bp), covered in this database, enables to compute CG dinucleotides frequencies, motif finding of the hypoxia response element, identification of CpG island and mapping with the reference promoter of zebrafish. The database also includes functional annotation of genes and provides tools for analyzing sequences and designing primers for selected gene fragments. This may be the first database on the hypoxia response genes in fishes that provides a workbench to the scientific community involved in studying the evolution and ecological adaptation of the fish species in relation to hypoxia.

TRAM (Transcriptome Mapper): database-driven creation and analysis of transcriptome maps from multiple sources

PubMed Central

2011-01-01

Background Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input. Results TRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified. Conclusions TRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at http://apollo11.isto.unibo.it/software/, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes. PMID:21333005

MicroRNA profiling in the dentate gyrus in epileptic rats: The role of miR-187-3p.

PubMed

Zhang, Suya; Kou, Yubin; Hu, Chunmei; Han, Yan

2017-06-01

This study aimed to explore the role of aberrant miRNA expression in epilepsy and to identify more potential genes associated with epileptogenesis.The miRNA expression profile of GSE49850, which included 20 samples from the rat epileptic dentate gyrus at 7, 14, 30, and 90 days after electrical stimulation and 20 additional samples from sham time-matched controls, was downloaded from the Gene Expression Omnibus database. The significantly differentially expressed miRNAs were identified in stimulated samples at each time point compared to time-matched controls, respectively. The target genes of consistently differentially expressed miRNAs were screened from miRDB and microRNA.org databases, followed by Gene Ontology (GO) and pathway enrichment analysis and regulatory network construction. The overlapping target genes for consistently differentially expressed miRNAs were also identified from these 2 databases. Furthermore, the potential binding sites of miRNAs and their target genes were analyzed.Rno-miR-187-3p was consistently downregulated in stimulated groups compared with time-matched controls. The predicted target genes of rno-miR-187-3p were enriched in different GO terms and pathways. In addition, 7 overlapping target genes of rno-miR-187-3p were identified, including NFS1, PAQR4, CAND1, DCLK1, PRKAR2A, AKAP3, and KCNK10. These 7 overlapping target genes were determined to have a different number of matched binding sites with rno-miR-187-3p.Our study suggests that miR-187-3p may play an important role in epilepsy development and progression via regulating numerous target genes, such as NFS1, CAND1, DCLK1, AKAP3, and KCNK10. Determining the underlying mechanism of the role of miR-187-3p in epilepsy may make it a potential therapeutic option.

NCBI GEO: mining tens of millions of expression profiles--database and tools update.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Edgar, Ron

2007-01-01

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely disseminates microarray and other forms of high-throughput data generated by the scientific community. The database has a minimum information about a microarray experiment (MIAME)-compliant infrastructure that captures fully annotated raw and processed data. Several data deposit options and formats are supported, including web forms, spreadsheets, XML and Simple Omnibus Format in Text (SOFT). In addition to data storage, a collection of user-friendly web-based interfaces and applications are available to help users effectively explore, visualize and download the thousands of experiments and tens of millions of gene expression patterns stored in GEO. This paper provides a summary of the GEO database structure and user facilities, and describes recent enhancements to database design, performance, submission format options, data query and retrieval utilities. GEO is accessible at http://www.ncbi.nlm.nih.gov/geo/

The Innate Immune Database (IIDB)

PubMed Central

Korb, Martin; Rust, Aistair G; Thorsson, Vesteinn; Battail, Christophe; Li, Bin; Hwang, Daehee; Kennedy, Kathleen A; Roach, Jared C; Rosenberger, Carrie M; Gilchrist, Mark; Zak, Daniel; Johnson, Carrie; Marzolf, Bruz; Aderem, Alan; Shmulevich, Ilya; Bolouri, Hamid

2008-01-01

Background As part of a National Institute of Allergy and Infectious Diseases funded collaborative project, we have performed over 150 microarray experiments measuring the response of C57/BL6 mouse bone marrow macrophages to toll-like receptor stimuli. These microarray expression profiles are available freely from our project web site . Here, we report the development of a database of computationally predicted transcription factor binding sites and related genomic features for a set of over 2000 murine immune genes of interest. Our database, which includes microarray co-expression clusters and a host of web-based query, analysis and visualization facilities, is available freely via the internet. It provides a broad resource to the research community, and a stepping stone towards the delineation of the network of transcriptional regulatory interactions underlying the integrated response of macrophages to pathogens. Description We constructed a database indexed on genes and annotations of the immediate surrounding genomic regions. To facilitate both gene-specific and systems biology oriented research, our database provides the means to analyze individual genes or an entire genomic locus. Although our focus to-date has been on mammalian toll-like receptor signaling pathways, our database structure is not limited to this subject, and is intended to be broadly applicable to immunology. By focusing on selected immune-active genes, we were able to perform computationally intensive expression and sequence analyses that would currently be prohibitive if applied to the entire genome. Using six complementary computational algorithms and methodologies, we identified transcription factor binding sites based on the Position Weight Matrices available in TRANSFAC. For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results. Our database can be interrogated via a web interface. Genomic annotations and binding site predictions can be automatically viewed with a customized version of the Argo genome browser. Conclusion We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens. The database website can be freely accessed at . PMID:18321385

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.

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

Mango (Mangifera indica L.) cv. Kent fruit mesocarp de novo transcriptome assembly identifies gene families important for ripening

PubMed Central

Dautt-Castro, Mitzuko; Ochoa-Leyva, Adrian; Contreras-Vergara, Carmen A.; Pacheco-Sanchez, Magda A.; Casas-Flores, Sergio; Sanchez-Flores, Alejandro; Kuhn, David N.; Islas-Osuna, Maria A.

2015-01-01

Fruit ripening is a physiological and biochemical process genetically programmed to regulate fruit quality parameters like firmness, flavor, odor and color, as well as production of ethylene in climacteric fruit. In this study, a transcriptomic analysis of mango (Mangifera indica L.) mesocarp cv. “Kent” was done to identify key genes associated with fruit ripening. Using the Illumina sequencing platform, 67,682,269 clean reads were obtained and a transcriptome of 4.8 Gb. A total of 33,142 coding sequences were predicted and after functional annotation, 25,154 protein sequences were assigned with a product according to Swiss-Prot database and 32,560 according to non-redundant database. Differential expression analysis identified 2,306 genes with significant differences in expression between mature-green and ripe mango [1,178 up-regulated and 1,128 down-regulated (FDR ≤ 0.05)]. The expression of 10 genes evaluated by both qRT-PCR and RNA-seq data was highly correlated (R = 0.97), validating the differential expression data from RNA-seq alone. Gene Ontology enrichment analysis, showed significantly represented terms associated to fruit ripening like “cell wall,” “carbohydrate catabolic process” and “starch and sucrose metabolic process” among others. Mango genes were assigned to 327 metabolic pathways according to Kyoto Encyclopedia of Genes and Genomes database, among them those involved in fruit ripening such as plant hormone signal transduction, starch and sucrose metabolism, galactose metabolism, terpenoid backbone, and carotenoid biosynthesis. This study provides a mango transcriptome that will be very helpful to identify genes for expression studies in early and late flowering mangos during fruit ripening. PMID:25741352

Effect of the difference in vehicles on gene expression in the rat liver--analysis of the control data in the Toxicogenomics Project Database.

PubMed

Takashima, Kayoko; Mizukawa, Yumiko; Morishita, Katsumi; Okuyama, Manabu; Kasahara, Toshihiko; Toritsuka, Naoki; Miyagishima, Toshikazu; Nagao, Taku; Urushidani, Tetsuro

2006-05-08

The Toxicogenomics Project is a 5-year collaborative project by the Japanese government and pharmaceutical companies in 2002. Its aim is to construct a large-scale toxicology database of 150 compounds orally administered to rats. The test consists of a single administration test (3, 6, 9 and 24 h) and a repeated administration test (3, 7, 14 and 28 days), and the conventional toxicology data together with the gene expression data in liver as analyzed by using Affymetrix GeneChip are being accumulated. In the project, either methylcellulose or corn oil is employed as vehicle. We examined whether the vehicle itself affects the analysis of gene expression and found that corn oil alone affected the food consumption and biochemical parameters mainly related to lipid metabolism, and this accompanied typical changes in the gene expression. Most of the genes modulated by corn oil were related to cholesterol or fatty acid metabolism (e.g., CYP7A1, CYP8B1, 3-hydroxy-3-methylglutaryl-Coenzyme A reductase, squalene epoxidase, angiopoietin-like protein 4, fatty acid synthase, fatty acid binding proteins), suggesting that the response was physiologic to the oil intake. Many of the lipid-related genes showed circadian rhythm within a day, but the expression pattern of general clock genes (e.g., period 2, arylhydrocarbon nuclear receptor translocator-like, D site albumin promoter binding protein) were unaffected by corn oil, suggesting that the effects are specific for lipid metabolism. These results would be useful for usage of the database especially when drugs with different vehicle control are compared.

Transcriptome Analysis of the Differentially Expressed Genes in the Male and Female Shrub Willows (Salix suchowensis)

PubMed Central

Liu, Jingjing; Yin, Tongming; Ye, Ning; Chen, Yingnan; Yin, Tingting; Liu, Min; Hassani, Danial

2013-01-01

Background The dioecious system is relatively rare in plants. Shrub willow is an annual flowering dioecious woody plant, and possesses many characteristics that lend it as a great model for tracking the missing pieces of sex determination evolution. To gain a global view of the genes differentially expressed in the male and female shrub willows and to develop a database for further studies, we performed a large-scale transcriptome sequencing of flower buds which were separately collected from two types of sexes. Results Totally, 1,201,931 high quality reads were obtained, with an average length of 389 bp and a total length of 467.96 Mb. The ESTs were assembled into 29,048 contigs, and 132,709 singletons. These unigenes were further functionally annotated by comparing their sequences to different proteins and functional domain databases and assigned with Gene Ontology (GO) terms. A biochemical pathway database containing 291 predicted pathways was also created based on the annotations of the unigenes. Digital expression analysis identified 806 differentially expressed genes between the male and female flower buds. And 33 of them located on the incipient sex chromosome of Salicaceae, among which, 12 genes might involve in plant sex determination empirically. These genes were worthy of special notification in future studies. Conclusions In this study, a large number of EST sequences were generated from the flower buds of a male and a female shrub willow. We also reported the differentially expressed genes between the two sex-type flowers. This work provides valuable information and sequence resources for uncovering the sex determining genes and for future functional genomics analysis of Salicaceae spp. PMID:23560075

Mango (Mangifera indica L.) cv. Kent fruit mesocarp de novo transcriptome assembly identifies gene families important for ripening.

PubMed

Dautt-Castro, Mitzuko; Ochoa-Leyva, Adrian; Contreras-Vergara, Carmen A; Pacheco-Sanchez, Magda A; Casas-Flores, Sergio; Sanchez-Flores, Alejandro; Kuhn, David N; Islas-Osuna, Maria A

2015-01-01

Fruit ripening is a physiological and biochemical process genetically programmed to regulate fruit quality parameters like firmness, flavor, odor and color, as well as production of ethylene in climacteric fruit. In this study, a transcriptomic analysis of mango (Mangifera indica L.) mesocarp cv. "Kent" was done to identify key genes associated with fruit ripening. Using the Illumina sequencing platform, 67,682,269 clean reads were obtained and a transcriptome of 4.8 Gb. A total of 33,142 coding sequences were predicted and after functional annotation, 25,154 protein sequences were assigned with a product according to Swiss-Prot database and 32,560 according to non-redundant database. Differential expression analysis identified 2,306 genes with significant differences in expression between mature-green and ripe mango [1,178 up-regulated and 1,128 down-regulated (FDR ≤ 0.05)]. The expression of 10 genes evaluated by both qRT-PCR and RNA-seq data was highly correlated (R = 0.97), validating the differential expression data from RNA-seq alone. Gene Ontology enrichment analysis, showed significantly represented terms associated to fruit ripening like "cell wall," "carbohydrate catabolic process" and "starch and sucrose metabolic process" among others. Mango genes were assigned to 327 metabolic pathways according to Kyoto Encyclopedia of Genes and Genomes database, among them those involved in fruit ripening such as plant hormone signal transduction, starch and sucrose metabolism, galactose metabolism, terpenoid backbone, and carotenoid biosynthesis. This study provides a mango transcriptome that will be very helpful to identify genes for expression studies in early and late flowering mangos during fruit ripening.

Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms.

PubMed

Milnthorpe, Andrew T; Soloviev, Mikhail

2011-04-15

The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries. We discovered that the CGAP approach often includes libraries from dependent or irrelevant tissues (one third of libraries were incorrect on average, with some tissue searches no correct libraries being selected at all). We also discovered that the CGAP approach reported genes from outside the selected libraries and may omit genes found within the libraries. Other errors include the incorrect estimation of the significance values and inaccurate settings for the library size cut-off values. We advocated a revised approach to finding libraries associated with tissues. In doing so, libraries from dependent or irrelevant tissues do not get included in the final library pool. We also revised the method for determining the presence or absence of a gene by searching the UniGene relational database, revised calculation of statistical significance and sorted the library cut-off filter. Our results justify re-evaluation of all previously reported results where NCBI CGAP expression data and tools were used.

Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms

PubMed Central

2011-01-01

Background The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries. Results We discovered that the CGAP approach often includes libraries from dependent or irrelevant tissues (one third of libraries were incorrect on average, with some tissue searches no correct libraries being selected at all). We also discovered that the CGAP approach reported genes from outside the selected libraries and may omit genes found within the libraries. Other errors include the incorrect estimation of the significance values and inaccurate settings for the library size cut-off values. We advocated a revised approach to finding libraries associated with tissues. In doing so, libraries from dependent or irrelevant tissues do not get included in the final library pool. We also revised the method for determining the presence or absence of a gene by searching the UniGene relational database, revised calculation of statistical significance and sorted the library cut-off filter. Conclusion Our results justify re-evaluation of all previously reported results where NCBI CGAP expression data and tools were used. PMID:21496233

Identification of Immunity-Related Genes in Dialeurodes citri against Entomopathogenic Fungus Lecanicillium attenuatum by RNA-Seq Analysis.

PubMed

Yu, Shijiang; Ding, Lili; Luo, Ren; Li, Xiaojiao; Yang, Juan; Liu, Haoqiang; Cong, Lin; Ran, Chun

2016-01-01

Dialeurodes citri is a major pest in citrus producing areas, and large-scale outbreaks have occurred increasingly often in recent years. Lecanicillium attenuatum is an important entomopathogenic fungus that can parasitize and kill D. citri. We separated the fungus from corpses of D. citri larvae. However, the sound immune defense system of pests makes infection by an entomopathogenic fungus difficult. Here we used RNA sequencing technology (RNA-Seq) to build a transcriptome database for D. citri and performed digital gene expression profiling to screen genes that act in the immune defense of D. citri larvae infected with a pathogenic fungus. De novo assembly generated 84,733 unigenes with mean length of 772 nt. All unigenes were searched against GO, Nr, Swiss-Prot, COG, and KEGG databases and a total of 28,190 (33.3%) unigenes were annotated. We identified 129 immunity-related unigenes in transcriptome database that were related to pattern recognition receptors, information transduction factors and response factors. From the digital gene expression profile, we identified 441 unigenes that were differentially expressed in D. citri infected with L. attenuatum. Through calculated Log2Ratio values, we identified genes for which fold changes in expression were obvious, including cuticle protein, vitellogenin, cathepsin, prophenoloxidase, clip-domain serine protease, lysozyme, and others. Subsequent quantitative real-time polymerase chain reaction analysis verified the results. The identified genes may serve as target genes for microbial control of D. citri.

Identification of Immunity-Related Genes in Dialeurodes citri against Entomopathogenic Fungus Lecanicillium attenuatum by RNA-Seq Analysis

PubMed Central

Yu, Shijiang; Ding, Lili; Luo, Ren; Li, Xiaojiao; Yang, Juan; Liu, Haoqiang; Cong, Lin; Ran, Chun

2016-01-01

Dialeurodes citri is a major pest in citrus producing areas, and large-scale outbreaks have occurred increasingly often in recent years. Lecanicillium attenuatum is an important entomopathogenic fungus that can parasitize and kill D. citri. We separated the fungus from corpses of D. citri larvae. However, the sound immune defense system of pests makes infection by an entomopathogenic fungus difficult. Here we used RNA sequencing technology (RNA-Seq) to build a transcriptome database for D. citri and performed digital gene expression profiling to screen genes that act in the immune defense of D. citri larvae infected with a pathogenic fungus. De novo assembly generated 84,733 unigenes with mean length of 772 nt. All unigenes were searched against GO, Nr, Swiss-Prot, COG, and KEGG databases and a total of 28,190 (33.3%) unigenes were annotated. We identified 129 immunity-related unigenes in transcriptome database that were related to pattern recognition receptors, information transduction factors and response factors. From the digital gene expression profile, we identified 441 unigenes that were differentially expressed in D. citri infected with L. attenuatum. Through calculated Log2Ratio values, we identified genes for which fold changes in expression were obvious, including cuticle protein, vitellogenin, cathepsin, prophenoloxidase, clip-domain serine protease, lysozyme, and others. Subsequent quantitative real-time polymerase chain reaction analysis verified the results. The identified genes may serve as target genes for microbial control of D. citri. PMID:27644092

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface.

PubMed

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B; Almon, Richard R; DuBois, Debra C; Jusko, William J; Hoffman, Eric P

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp).

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface

PubMed Central

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B.; Almon, Richard R.; DuBois, Debra C.; Jusko, William J.; Hoffman, Eric P.

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp). PMID:14681485

TransAtlasDB: an integrated database connecting expression data, metadata and variants

PubMed Central

Adetunji, Modupeore O; Lamont, Susan J; Schmidt, Carl J

2018-01-01

Abstract High-throughput transcriptome sequencing (RNAseq) is the universally applied method for target-free transcript identification and gene expression quantification, generating huge amounts of data. The constraint of accessing such data and interpreting results can be a major impediment in postulating suitable hypothesis, thus an innovative storage solution that addresses these limitations, such as hard disk storage requirements, efficiency and reproducibility are paramount. By offering a uniform data storage and retrieval mechanism, various data can be compared and easily investigated. We present a sophisticated system, TransAtlasDB, which incorporates a hybrid architecture of both relational and NoSQL databases for fast and efficient data storage, processing and querying of large datasets from transcript expression analysis with corresponding metadata, as well as gene-associated variants (such as SNPs) and their predicted gene effects. TransAtlasDB provides the data model of accurate storage of the large amount of data derived from RNAseq analysis and also methods of interacting with the database, either via the command-line data management workflows, written in Perl, with useful functionalities that simplifies the complexity of data storage and possibly manipulation of the massive amounts of data generated from RNAseq analysis or through the web interface. The database application is currently modeled to handle analyses data from agricultural species, and will be expanded to include more species groups. Overall TransAtlasDB aims to serve as an accessible repository for the large complex results data files derived from RNAseq gene expression profiling and variant analysis. Database URL: https://modupeore.github.io/TransAtlasDB/ PMID:29688361

Application of connectivity mapping in predictive toxicology based on gene-expression similarity.

PubMed

Smalley, Joshua L; Gant, Timothy W; Zhang, Shu-Dong

2010-02-09

Connectivity mapping is the process of establishing connections between different biological states using gene-expression profiles or signatures. There are a number of applications but in toxicology the most pertinent is for understanding mechanisms of toxicity. In its essence the process involves comparing a query gene signature generated as a result of exposure of a biological system to a chemical to those in a database that have been previously derived. In the ideal situation the query gene-expression signature is characteristic of the event and will be matched to similar events in the database. Key criteria are therefore the means of choosing the signature to be matched and the means by which the match is made. In this article we explore these concepts with examples applicable to toxicology. (c) 2009 Elsevier Ireland Ltd. All rights reserved.

MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

PubMed

Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan

2014-06-15

The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.

A large scale analysis of cDNA in Arabidopsis thaliana: generation of 12,028 non-redundant expressed sequence tags from normalized and size-selected cDNA libraries.

PubMed

Asamizu, E; Nakamura, Y; Sato, S; Tabata, S

2000-06-30

For comprehensive analysis of genes expressed in the model dicotyledonous plant, Arabidopsis thaliana, expressed sequence tags (ESTs) were accumulated. Normalized and size-selected cDNA libraries were constructed from aboveground organs, flower buds, roots, green siliques and liquid-cultured seedlings, respectively, and a total of 14,026 5'-end ESTs and 39,207 3'-end ESTs were obtained. The 3'-end ESTs could be clustered into 12,028 non-redundant groups. Similarity search of the non-redundant ESTs against the public non-redundant protein database indicated that 4816 groups show similarity to genes of known function, 1864 to hypothetical genes, and the remaining 5348 are novel sequences. Gene coverage by the non-redundant ESTs was analyzed using the annotated genomic sequences of approximately 10 Mb on chromosomes 3 and 5. A total of 923 regions were hit by at least one EST, among which only 499 regions were hit by the ESTs deposited in the public database. The result indicates that the EST source generated in this project complements the EST data in the public database and facilitates new gene discovery.

STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data

PubMed Central

Jupiter, Daniel; Chen, Hailin; VanBuren, Vincent

2009-01-01

Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a STARNET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at , and does not require user registration. PMID:19828039

Gene Expression Profiling of Benign and Malignant Pheochromocytoma

PubMed Central

BROUWERS, FREDERIEKE M.; ELKAHLOUN, ABDEL G.; MUNSON, PETER J.; EISENHOFER, GRAEME; BARB, JENNIFER; LINEHAN, W. MARSTON; LENDERS, JACQUES W.M.; DE KRIJGER, RONALD; MANNELLI, MASSIMO; UDELSMAN, ROBERT; OCAL, IDRIS T.; SHULKIN, BARRY L.; BORNSTEIN, STEFAN R.; BREZA, JAN; KSINANTOVA, LUCIA; PACAK, KAREL

2016-01-01

There are currently no reliable diagnostic and prognostic markers or effective treatments for malignant pheochromocytoma. This study used oligonucleotide microarrays to examine gene expression profiles in pheochromocytomas from 90 patients, including 20 with malignant tumors, the latter including metastases and primary tumors from which metastases developed. Other subgroups of tumors included those defined by tissue norepinephrine compared to epinephrine contents (i.e., noradrenergic versus adrenergic phenotypes), adrenal versus extra-adrenal locations, and presence of germline mutations of genes pre-disposing to the tumor. Correcting for the confounding influence of nora-drenergic versus adrenergic catecholamine phenotype by the analysis of variance revealed a larger and more accurate number of genes that discriminated benign from malignant pheochromocytomas than when the confounding influence of catecholamine phenotype was not considered. Seventy percent of these genes were underexpressed in malignant compared to benign tumors. Similarly, 89% of genes were underexpressed in malignant primary tumors compared to benign tumors, suggesting that malignant potential is largely characterized by a less-differentiated pattern of gene expression. The present database of differentially expressed genes provides a unique resource for mapping the pathways leading to malignancy and for establishing new targets for treatment and diagnostic and prognostic markers of malignant disease. The database may also be useful for examining mechanisms of tumorigenesis and genotype–phenotype relationships. Further progress on the basis of this database can be made from follow-up confirmatory studies, application of bioinformatics approaches for data mining and pathway analyses, testing in pheochromocytoma cell culture and animal model systems, and retrospective and prospective studies of diagnostic markers. PMID:17102123

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.

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.

Identification of Anhydrobiosis-related Genes from an Expressed Sequence Tag Database in the Cryptobiotic Midge Polypedilum vanderplanki (Diptera; Chironomidae)*

PubMed Central

Cornette, Richard; Kanamori, Yasushi; Watanabe, Masahiko; Nakahara, Yuichi; Gusev, Oleg; Mitsumasu, Kanako; Kadono-Okuda, Keiko; Shimomura, Michihiko; Mita, Kazuei; Kikawada, Takahiro; Okuda, Takashi

2010-01-01

Some organisms are able to survive the loss of almost all their body water content, entering a latent state known as anhydrobiosis. The sleeping chironomid (Polypedilum vanderplanki) lives in the semi-arid regions of Africa, and its larvae can survive desiccation in an anhydrobiotic form during the dry season. To unveil the molecular mechanisms of this resistance to desiccation, an anhydrobiosis-related Expressed Sequence Tag (EST) database was obtained from the sequences of three cDNA libraries constructed from P. vanderplanki larvae after 0, 12, and 36 h of desiccation. The database contained 15,056 ESTs distributed into 4,807 UniGene clusters. ESTs were classified according to gene ontology categories, and putative expression patterns were deduced for all clusters on the basis of the number of clones in each library; expression patterns were confirmed by real-time PCR for selected genes. Among up-regulated genes, antioxidants, late embryogenesis abundant (LEA) proteins, and heat shock proteins (Hsps) were identified as important groups for anhydrobiosis. Genes related to trehalose metabolism and various transporters were also strongly induced by desiccation. Those results suggest that the oxidative stress response plays a central role in successful anhydrobiosis. Similarly, protein denaturation and aggregation may be prevented by marked up-regulation of Hsps and the anhydrobiosis-specific LEA proteins. A third major feature is the predicted increase in trehalose synthesis and in the expression of various transporter proteins allowing the distribution of trehalose and other solutes to all tissues. PMID:20833722

Expression of drought tolerance genes in tropical upland rice cultivars (Oryza sativa).

PubMed

Silveira, R D D; Abreu, F R M; Mamidi, S; McClean, P E; Vianello, R P; Lanna, A C; Carneiro, N P; Brondani, C

2015-07-27

Gene expression related to drought response in the leaf tissues of two Brazilian upland cultivars, the drought-tolerant Douradão and the drought-sensitive Primavera, was analyzed. RNA-seq identified 27,618 transcripts in the Douradão cultivar, with 24,090 (87.2%) homologous to the rice database, and 27,221 transcripts in the Primavera cultivar, with 23,663 (86.9%) homologous to the rice database. Gene-expression analysis between control and water-deficient treatments revealed 493 and 1154 differentially expressed genes in Douradão and Primavera cultivars, respectively. Genes exclusively expressed under drought were identified for Douradão, including two genes of particular interest coding for the protein peroxidase precursor, which is involved in three distinct metabolic pathways. Comparisons between the two drought-exposed cultivars revealed 2314 genes were differentially expressed (978 upregulated, 1336 downregulated in Douradão). Six genes distributed across 4 different transcription factor families (bHLH, MYB, NAC, and WRKY) were identified, all of which were upregulated in Douradão compared to Primavera during drought. Most of the genes identified in Douradão activate metabolic pathways responsible for production of secondary metabolites and genes coding for enzymatically active signaling receptors. Quantitative PCR validation showed that most gene expression was in agreement with computational prediction of these transcripts. The transcripts identified here will define molecular markers for identification of Cis-acting elements to search for allelic variants of these genes through analysis of polymorphic SNPs in GenBank accessions of upland rice, aiming to develop cultivars with the best combination of these alleles, resulting in materials with high yield potential in the event of drought during the reproductive phase.

GEneSTATION 1.0: a synthetic resource of diverse evolutionary and functional genomic data for studying the evolution of pregnancy-associated tissues and phenotypes

PubMed Central

Kim, Mara; Cooper, Brian A.; Venkat, Rohit; Phillips, Julie B.; Eidem, Haley R.; Hirbo, Jibril; Nutakki, Sashank; Williams, Scott M.; Muglia, Louis J.; Capra, J. Anthony; Petren, Kenneth; Abbot, Patrick; Rokas, Antonis; McGary, Kriston L.

2016-01-01

Mammalian gestation and pregnancy are fast evolving processes that involve the interaction of the fetal, maternal and paternal genomes. Version 1.0 of the GEneSTATION database (http://genestation.org) integrates diverse types of omics data across mammals to advance understanding of the genetic basis of gestation and pregnancy-associated phenotypes and to accelerate the translation of discoveries from model organisms to humans. GEneSTATION is built using tools from the Generic Model Organism Database project, including the biology-aware database CHADO, new tools for rapid data integration, and algorithms that streamline synthesis and user access. GEneSTATION contains curated life history information on pregnancy and reproduction from 23 high-quality mammalian genomes. For every human gene, GEneSTATION contains diverse evolutionary (e.g. gene age, population genetic and molecular evolutionary statistics), organismal (e.g. tissue-specific gene and protein expression, differential gene expression, disease phenotype), and molecular data types (e.g. Gene Ontology Annotation, protein interactions), as well as links to many general (e.g. Entrez, PubMed) and pregnancy disease-specific (e.g. PTBgene, dbPTB) databases. By facilitating the synthesis of diverse functional and evolutionary data in pregnancy-associated tissues and phenotypes and enabling their quick, intuitive, accurate and customized meta-analysis, GEneSTATION provides a novel platform for comprehensive investigation of the function and evolution of mammalian pregnancy. PMID:26567549

Computational genomic analysis of PARK7 interactome reveals high BBS1 gene expression as a prognostic factor favoring survival in malignant pleural mesothelioma.

PubMed

Vavougios, Georgios D; Solenov, Evgeniy I; Hatzoglou, Chrissi; Baturina, Galina S; Katkova, Liubov E; Molyvdas, Paschalis Adam; Gourgoulianis, Konstantinos I; Zarogiannis, Sotirios G

2015-10-01

The aim of our study was to assess the differential gene expression of Parkinson protein 7 (PARK7) interactome in malignant pleural mesothelioma (MPM) using data mining techniques to identify novel candidate genes that may play a role in the pathogenicity of MPM. We constructed the PARK7 interactome using the ConsensusPathDB database. We then interrogated the Oncomine Cancer Microarray database using the Gordon Mesothelioma Study, for differential gene expression of the PARK7 interactome. In ConsensusPathDB, 38 protein interactors of PARK7 were identified. In the Gordon Mesothelioma Study, 34 of them were assessed out of which SUMO1, UBC3, KIAA0101, HDAC2, DAXX, RBBP4, BBS1, NONO, RBBP7, HTRA2, and STUB1 were significantly overexpressed whereas TRAF6 and MTA2 were significantly underexpressed in MPM patients (network 2). Furthermore, Kaplan-Meier analysis revealed that MPM patients with high BBS1 expression had a median overall survival of 16.5 vs. 8.7 mo of those that had low expression. For validation purposes, we performed a meta-analysis in Oncomine database in five sarcoma datasets. Eight network 2 genes (KIAA0101, HDAC2, SUMO1, RBBP4, NONO, RBBP7, HTRA2, and MTA2) were significantly differentially expressed in an array of 18 different sarcoma types. Finally, Gene Ontology annotation enrichment analysis revealed significant roles of the PARK7 interactome in NuRD, CHD, and SWI/SNF protein complexes. In conclusion, we identified 13 novel genes differentially expressed in MPM, never reported before. Among them, BBS1 emerged as a novel predictor of overall survival in MPM. Finally, we identified that PARK7 interactome is involved in novel pathways pertinent in MPM disease. Copyright © 2015 the American Physiological Society.

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

Mouse IDGenes: a reference database for genetic interactions in the developing mouse brain

PubMed Central

Matthes, Michaela; Preusse, Martin; Zhang, Jingzhong; Schechter, Julia; Mayer, Daniela; Lentes, Bernd; Theis, Fabian; Prakash, Nilima; Wurst, Wolfgang; Trümbach, Dietrich

2014-01-01

The study of developmental processes in the mouse and other vertebrates includes the understanding of patterning along the anterior–posterior, dorsal–ventral and medial– lateral axis. Specifically, neural development is also of great clinical relevance because several human neuropsychiatric disorders such as schizophrenia, autism disorders or drug addiction and also brain malformations are thought to have neurodevelopmental origins, i.e. pathogenesis initiates during childhood and adolescence. Impacts during early neurodevelopment might also predispose to late-onset neurodegenerative disorders, such as Parkinson’s disease. The neural tube develops from its precursor tissue, the neural plate, in a patterning process that is determined by compartmentalization into morphogenetic units, the action of local signaling centers and a well-defined and locally restricted expression of genes and their interactions. While public databases provide gene expression data with spatio-temporal resolution, they usually neglect the genetic interactions that govern neural development. Here, we introduce Mouse IDGenes, a reference database for genetic interactions in the developing mouse brain. The database is highly curated and offers detailed information about gene expressions and the genetic interactions at the developing mid-/hindbrain boundary. To showcase the predictive power of interaction data, we infer new Wnt/β-catenin target genes by machine learning and validate one of them experimentally. The database is updated regularly. Moreover, it can easily be extended by the research community. Mouse IDGenes will contribute as an important resource to the research on mouse brain development, not exclusively by offering data retrieval, but also by allowing data input. Database URL: http://mouseidgenes.helmholtz-muenchen.de. PMID:25145340

MeSH key terms for validation and annotation of gene expression clusters

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

Rechtsteiner, A.; Rocha, L. M.

2004-01-01

Integration of different sources of information is a great challenge for the analysis of gene expression data, and for the field of Functional Genomics in general. As the availability of numerical data from high-throughput methods increases, so does the need for technologies that assist in the validation and evaluation of the biological significance of results extracted from these data. In mRNA assaying with microarrays, for example, numerical analysis often attempts to identify clusters of co-expressed genes. The important task to find the biological significance of the results and validate them has so far mostly fallen to the biological expert whomore » had to perform this task manually. One of the most promising avenues to develop automated and integrative technology for such tasks lies in the application of modern Information Retrieval (IR) and Knowledge Management (KM) algorithms to databases with biomedical publications and data. Examples of databases available for the field are bibliographic databases c ntaining scientific publications (e.g. MEDLINE/PUBMED), databases containing sequence data (e.g. GenBank) and databases of semantic annotations (e.g. the Gene Ontology Consortium and Medical Subject Headings (MeSH)). We present here an approach that uses the MeSH terms and their concept hierarchies to validate and obtain functional information for gene expression clusters. The controlled and hierarchical MeSH vocabulary is used by the National Library of Medicine (NLM) to index all the articles cited in MEDLINE. Such indexing with a controlled vocabulary eliminates some of the ambiguity due to polysemy (terms that have multiple meanings) and synonymy (multiple terms have similar meaning) that would be encountered if terms would be extracted directly from the articles due to differing article contexts or author preferences and background. Further, the hierarchical organization of the MeSH terms can illustrate the conceptuallfunctional relationships of genes associated with MeSH terms. MeSH terms can be associated with genes through co-occurrence of these in MEDLINE citations, i.e. the genes occur in titles or abstracts and the MeSH terms are assigned by experts. To identify MeSH terms associated with a group of genes we used the tool MESHGENE developed at the Information Dynamics Lab at HP Labs (http://www-idl.hpl.hp.com/meshgene/). When presented with a list of human genes, MESHGENE uses some sophisticated techniques to search for these gene symbols in the titles and abstracts of all MEDLINE citations. MeSH terms and the number of co-occurrences can be retrieved. Gene symbols that are aliases of each other are pooled from several databases. This addresses the problem of synonymy, the fact that several symbols can refer to the same gene. MESHGENE employs some sophisticated algorithms that disregards symbols that are likely to be acronyms for other concepts than a gene. This addresses the problem of polysemy, i.e. possible multiple meanings of a gene symbol. We applied our approach to gene expression data from herpes virus infected human fibroblast cells. The data contains 12 time-points, between 1/2 hrs and 48 hrs after infection. Singular Value Decomposition was used to identify the dominant modes of expression. 75% of the variance in the expression data was captured by the first two modes, the first exhibiting a monotonly increasing expression pattern and the second a more transient pattern. Projection of the gene expression vectors onto this first two modes identified 3 statistically significant clusters of co-expressed genes. 500 genes from cluster 1 and 300 genes from clusters 2 and 3 each were uploaded to MESHGENE and the MeSH terms and co-occurrence values were retrieved. MeSH terms were also obtained for 5 groups of randomly selected genes with similar numbers of genes. The log was taken of the co-occurrence values and for each MeSH term these log co-occurrence values were summed for each group over the genes in that group. A matrix with 8 columns for the 8 groups of genes and with 14,000 rows with the MeSH terms was obtained. To analyze this association matrix we used a Latent Semantic Analysis (LSA) approach. We applied SVD to this gene-group vs. MeSH term association matrix. The first 2 modes that capture most of the variation (and therefore most times also information) in the association matrix were highly associated with MeSH terms that occurred uniquely or disproportionally in the 3 gene clusters. MeSH terms highly associated with the 5 groups of randomly selected genes were associated with the lower modes. These modes seem to just capture 'noise' in the association matrix. This result by itself is of great interest for gene expression analysis. We were able to show that the 3 clusters of genes not only separated in 'expression space' but also in the MeSH term space with which they are associated through the literature.« less

Clinical value of miR-182-5p in lung squamous cell carcinoma: a study combining data from TCGA, GEO, and RT-qPCR validation.

PubMed

Luo, Jie; Shi, Ke; Yin, Shu-Ya; Tang, Rui-Xue; Chen, Wen-Jie; Huang, Lin-Zhen; Gan, Ting-Qing; Cai, Zheng-Wen; Chen, Gang

2018-04-10

MiR-182-5p, as a member of miRNA family, can be detected in lung cancer and plays an important role in lung cancer. To explore the clinical value of miR-182-5p in lung squamous cell carcinoma (LUSC) and to unveil the molecular mechanism of LUSC. The clinical value of miR-182-5p in LUSC was investigated by collecting and calculating data from The Cancer Genome Atlas (TCGA) database, the Gene Expression Omnibus (GEO) database, and real-time quantitative polymerase chain reaction (RT-qPCR). Twelve prediction platforms were used to predict the target genes of miR-182-5p. Protein-protein interaction (PPI) networks and gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to explore the molecular mechanism of LUSC. The expression of miR-182-5p was significantly over-expressed in LUSC than in non-cancerous tissues, as evidenced by various approaches, including the TCGA database, GEO microarrays, RT-qPCR, and a comprehensive meta-analysis of 501 LUSC cases and 148 non-cancerous cases. Furthermore, a total of 81 potential target genes were chosen from the union of predicted genes and the TCGA database. GO and KEGG analyses demonstrated that the target genes are involved in pathways related to biological processes. PPIs revealed the relationships between these genes, with EPAS1, PRKCE, NR3C1, and RHOB being located in the center of the PPI network. MiR-182-5p upregulation greatly contributes to LUSC and may serve as a biomarker in LUSC.

HEROD: a human ethnic and regional specific omics database.

PubMed

Zeng, Xian; Tao, Lin; Zhang, Peng; Qin, Chu; Chen, Shangying; He, Weidong; Tan, Ying; Xia Liu, Hong; Yang, Sheng Yong; Chen, Zhe; Jiang, Yu Yang; Chen, Yu Zong

2017-10-15

Genetic and gene expression variations within and between populations and across geographical regions have substantial effects on the biological phenotypes, diseases, and therapeutic response. The development of precision medicines can be facilitated by the OMICS studies of the patients of specific ethnicity and geographic region. However, there is an inadequate facility for broadly and conveniently accessing the ethnic and regional specific OMICS data. Here, we introduced a new free database, HEROD, a human ethnic and regional specific OMICS database. Its first version contains the gene expression data of 53 070 patients of 169 diseases in seven ethnic populations from 193 cities/regions in 49 nations curated from the Gene Expression Omnibus (GEO), the ArrayExpress Archive of Functional Genomics Data (ArrayExpress), the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Geographic region information of curated patients was mainly manually extracted from referenced publications of each original study. These data can be accessed and downloaded via keyword search, World map search, and menu-bar search of disease name, the international classification of disease code, geographical region, location of sample collection, ethnic population, gender, age, sample source organ, patient type (patient or healthy), sample type (disease or normal tissue) and assay type on the web interface. The HEROD database is freely accessible at http://bidd2.nus.edu.sg/herod/index.php. The database and web interface are implemented in MySQL, PHP and HTML with all major browsers supported. phacyz@nus.edu.sg. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Comparative methods for the analysis of gene-expression evolution: an example using yeast functional genomic data.

PubMed

Oakley, Todd H; Gu, Zhenglong; Abouheif, Ehab; Patel, Nipam H; Li, Wen-Hsiung

2005-01-01

Understanding the evolution of gene function is a primary challenge of modern evolutionary biology. Despite an expanding database from genomic and developmental studies, we are lacking quantitative methods for analyzing the evolution of some important measures of gene function, such as gene-expression patterns. Here, we introduce phylogenetic comparative methods to compare different models of gene-expression evolution in a maximum-likelihood framework. We find that expression of duplicated genes has evolved according to a nonphylogenetic model, where closely related genes are no more likely than more distantly related genes to share common expression patterns. These results are consistent with previous studies that found rapid evolution of gene expression during the history of yeast. The comparative methods presented here are general enough to test a wide range of evolutionary hypotheses using genomic-scale data from any organism.

Defining the Human Macula Transcriptome and Candidate Retinal Disease Genes UsingEyeSAGE

PubMed Central

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

2009-01-01

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

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

PubMed

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

2006-06-01

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

Mining microarray data at NCBI's Gene Expression Omnibus (GEO)*.

PubMed

Barrett, Tanya; Edgar, Ron

2006-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

TrSDB: a proteome database of transcription factors

PubMed Central

Hermoso, Antoni; Aguilar, Daniel; Aviles, Francesc X.; Querol, Enrique

2004-01-01

TrSDB—TranScout Database—(http://ibb.uab.es/trsdb) is a proteome database of eukaryotic transcription factors based upon predicted motifs by TranScout and data sources such as InterPro and Gene Ontology Annotation. Nine eukaryotic proteomes are included in the current version. Extensive and diverse information for each database entry, different analyses considering TranScout classification and similarity relationships are offered for research on transcription factors or gene expression. PMID:14681387

CyanoEXpress: A web database for exploration and visualisation of the integrated transcriptome of cyanobacterium Synechocystis sp. PCC6803.

PubMed

Hernandez-Prieto, Miguel A; Futschik, Matthias E

2012-01-01

Synechocystis sp. PCC6803 is one of the best studied cyanobacteria and an important model organism for our understanding of photosynthesis. The early availability of its complete genome sequence initiated numerous transcriptome studies, which have generated a wealth of expression data. Analysis of the accumulated data can be a powerful tool to study transcription in a comprehensive manner and to reveal underlying regulatory mechanisms, as well as to annotate genes whose functions are yet unknown. However, use of divergent microarray platforms, as well as distributed data storage make meta-analyses of Synechocystis expression data highly challenging, especially for researchers with limited bioinformatic expertise and resources. To facilitate utilisation of the accumulated expression data for a wider research community, we have developed CyanoEXpress, a web database for interactive exploration and visualisation of transcriptional response patterns in Synechocystis. CyanoEXpress currently comprises expression data for 3073 genes and 178 environmental and genetic perturbations obtained in 31 independent studies. At present, CyanoEXpress constitutes the most comprehensive collection of expression data available for Synechocystis and can be freely accessed. The database is available for free at http://cyanoexpress.sysbiolab.eu.

NABIC marker database: A molecular markers information network of agricultural crops.

PubMed

Kim, Chang-Kug; Seol, Young-Joo; Lee, Dong-Jun; Jeong, In-Seon; Yoon, Ung-Han; Lee, Gang-Seob; Hahn, Jang-Ho; Park, Dong-Suk

2013-01-01

In 2013, National Agricultural Biotechnology Information Center (NABIC) reconstructs a molecular marker database for useful genetic resources. The web-based marker database consists of three major functional categories: map viewer, RSN marker and gene annotation. It provides 7250 marker locations, 3301 RSN marker property, 3280 molecular marker annotation information in agricultural plants. The individual molecular marker provides information such as marker name, expressed sequence tag number, gene definition and general marker information. This updated marker-based database provides useful information through a user-friendly web interface that assisted in tracing any new structures of the chromosomes and gene positional functions using specific molecular markers. The database is available for free at http://nabic.rda.go.kr/gere/rice/molecularMarkers/

Molecular differences between mature and immature dental pulp cells: Bioinformatics and preliminary results.

PubMed

Chen, Long; Jiang, Yifeng; Du, Zhen

2018-04-01

Although previous studies have demonstrated that dental pulp stem cells (DPSCs) from mature and immature teeth exhibit potential for multi-directional differentiation, the molecular and biological difference between the DPSCs from mature and immature permanent teeth has not been fully investigated. In the present study, 500 differentially expressed genes from dental pulp cells (DPCs) in mature and immature permanent teeth were obtained from the Gene Expression Omnibus online database. Based on bioinformatics analysis using the Database for Annotation, Visualization and Integrated Discovery, these genes were divided into a number of subgroups associated with immunity, inflammation and cell signaling. The results of the present study suggest that immune features, response to infection and cell signaling may be different in DPCs from mature and immature permanent teeth; furthermore, DPCs from immature permanent teeth may be more suitable for use in tissue engineering or stem cell therapy. The Online Mendelian Inheritance in Man database stated that Sonic Hedgehog (SHH), a differentially expressed gene in DPCs from mature and immature permanent teeth, serves a crucial role in the development of craniofacial tissues, including teeth, which further confirmed that SHH may cause DPCs from mature and immature permanent teeth to exhibit different biological characteristics. The Search Tool for the Retrieval of Interacting Genes/Proteins database revealed that SHH has functional protein associations with a number of other proteins, including Glioma-associated oncogene (GLI)1, GLI2, growth arrest-specific protein 1, bone morphogenetic protein (BMP)2 and BMP4, in mice and humans. It was also demonstrated that SHH may interact with other genes to regulate the biological characteristics of DPCs. The results of the present study may provide a useful reference basis for selecting suitable DPSCs and molecules for the treatment of these cells to optimize features for tissue engineering or stem cell therapy. Quantitative polymerase chain reaction should be performed to confirm the differential expression of these genes prior to the beginning of a functional study.

EPConDB: a web resource for gene expression related to pancreatic development, beta-cell function and diabetes.

PubMed

Mazzarelli, Joan M; Brestelli, John; Gorski, Regina K; Liu, Junmin; Manduchi, Elisabetta; Pinney, Deborah F; Schug, Jonathan; White, Peter; Kaestner, Klaus H; Stoeckert, Christian J

2007-01-01

EPConDB (http://www.cbil.upenn.edu/EPConDB) is a public web site that supports research in diabetes, pancreatic development and beta-cell function by providing information about genes expressed in cells of the pancreas. EPConDB displays expression profiles for individual genes and information about transcripts, promoter elements and transcription factor binding sites. Gene expression results are obtained from studies examining tissue expression, pancreatic development and growth, differentiation of insulin-producing cells, islet or beta-cell injury, and genetic models of impaired beta-cell function. The expression datasets are derived using different microarray platforms, including the BCBC PancChips and Affymetrix gene expression arrays. Other datasets include semi-quantitative RT-PCR and MPSS expression studies. For selected microarray studies, lists of differentially expressed genes, derived from PaGE analysis, are displayed on the site. EPConDB provides database queries and tools to examine the relationship between a gene, its transcriptional regulation, protein function and expression in pancreatic tissues.

Gene expression profiling of intestinal regeneration in the sea cucumber

PubMed Central

Ortiz-Pineda, Pablo A; Ramírez-Gómez, Francisco; Pérez-Ortiz, Judit; González-Díaz, Sebastián; Santiago-De Jesús, Francisco; Hernández-Pasos, Josue; Del Valle-Avila, Cristina; Rojas-Cartagena, Carmencita; Suárez-Castillo, Edna C; Tossas, Karen; Méndez-Merced, Ana T; Roig-López, José L; Ortiz-Zuazaga, Humberto; García-Arrarás, José E

2009-01-01

Background Among deuterostomes, the regenerative potential is maximally expressed in echinoderms, animals that can quickly replace most injured organs. In particular, sea cucumbers are excellent models for studying organ regeneration since they regenerate their digestive tract after evisceration. However, echinoderms have been sidelined in modern regeneration studies partially because of the lack of genome-wide profiling approaches afforded by modern genomic tools. For the last decade, our laboratory has been using the sea cucumber Holothuria glaberrima to dissect the cellular and molecular events that allow for such amazing regenerative processes. We have already established an EST database obtained from cDNA libraries of normal and regenerating intestine at two different regeneration stages. This database now has over 7000 sequences. Results In the present work we used a custom-made microchip from Agilent with 60-mer probes for these ESTs, to determine the gene expression profile during intestinal regeneration. Here we compared the expression profile of animals at three different intestinal regeneration stages (3-, 7- and 14-days post evisceration) against the profile from normal (uneviscerated) intestines. The number of differentially expressed probes ranged from 70% at p < 0.05 to 39% at p < 0.001. Clustering analyses show specific profiles of expression for early (first week) and late (second week) regeneration stages. We used semiquantitative reverse transcriptase polymerase chain reaction (RT-PCR) to validate the expression profile of fifteen microarray detected differentially expressed genes which resulted in over 86% concordance between both techniques. Most of the differentially expressed ESTs showed no clear similarity to sequences in the databases and might represent novel genes associated with regeneration. However, other ESTs were similar to genes known to be involved in regeneration-related processes, wound healing, cell proliferation, differentiation, morphological plasticity, cell survival, stress response, immune challenge, and neoplastic transformation. Among those that have been validated, cytoskeletal genes, such as actins, and developmental genes, such as Wnt and Hox genes, show interesting expression profiles during regeneration. Conclusion Our findings set the base for future studies into the molecular basis of intestinal regeneration. Moreover, it advances the use of echinoderms in regenerative biology, animals that because of their amazing properties and their key evolutionary position, might provide important clues to the genetic basis of regenerative processes. PMID:19505337

Gene evolution and gene expression after whole genome duplication in fish: the PhyloFish database.

PubMed

Pasquier, Jeremy; Cabau, Cédric; Nguyen, Thaovi; Jouanno, Elodie; Severac, Dany; Braasch, Ingo; Journot, Laurent; Pontarotti, Pierre; Klopp, Christophe; Postlethwait, John H; Guiguen, Yann; Bobe, Julien

2016-05-18

With more than 30,000 species, ray-finned fish represent approximately half of vertebrates. The evolution of ray-finned fish was impacted by several whole genome duplication (WGD) events including a teleost-specific WGD event (TGD) that occurred at the root of the teleost lineage about 350 million years ago (Mya) and more recent WGD events in salmonids, carps, suckers and others. In plants and animals, WGD events are associated with adaptive radiations and evolutionary innovations. WGD-spurred innovation may be especially relevant in the case of teleost fish, which colonized a wide diversity of habitats on earth, including many extreme environments. Fish biodiversity, the use of fish models for human medicine and ecological studies, and the importance of fish in human nutrition, fuel an important need for the characterization of gene expression repertoires and corresponding evolutionary histories of ray-finned fish genes. To this aim, we performed transcriptome analyses and developed the PhyloFish database to provide (i) de novo assembled gene repertoires in 23 different ray-finned fish species including two holosteans (i.e. a group that diverged from teleosts before TGD) and 21 teleosts (including six salmonids), and (ii) gene expression levels in ten different tissues and organs (and embryos for many) in the same species. This resource was generated using a common deep RNA sequencing protocol to obtain the most exhaustive gene repertoire possible in each species that allows between-species comparisons to study the evolution of gene expression in different lineages. The PhyloFish database described here can be accessed and searched using RNAbrowse, a simple and efficient solution to give access to RNA-seq de novo assembled transcripts.

ANISEED 2017: extending the integrated ascidian database to the exploration and evolutionary comparison of genome-scale datasets

PubMed Central

Brozovic, Matija; Dantec, Christelle; Dardaillon, Justine; Dauga, Delphine; Faure, Emmanuel; Gineste, Mathieu; Louis, Alexandra; Naville, Magali; Nitta, Kazuhiro R; Piette, Jacques; Reeves, Wendy; Scornavacca, Céline; Simion, Paul; Vincentelli, Renaud; Bellec, Maelle; Aicha, Sameh Ben; Fagotto, Marie; Guéroult-Bellone, Marion; Haeussler, Maximilian; Jacox, Edwin; Lowe, Elijah K; Mendez, Mickael; Roberge, Alexis; Stolfi, Alberto; Yokomori, Rui; Cambillau, Christian; Christiaen, Lionel; Delsuc, Frédéric; Douzery, Emmanuel; Dumollard, Rémi; Kusakabe, Takehiro; Nakai, Kenta; Nishida, Hiroki; Satou, Yutaka; Swalla, Billie; Veeman, Michael; Volff, Jean-Nicolas

2018-01-01

Abstract ANISEED (www.aniseed.cnrs.fr) is the main model organism database for tunicates, the sister-group of vertebrates. This release gives access to annotated genomes, gene expression patterns, and anatomical descriptions for nine ascidian species. It provides increased integration with external molecular and taxonomy databases, better support for epigenomics datasets, in particular RNA-seq, ChIP-seq and SELEX-seq, and features novel interactive interfaces for existing and novel datatypes. In particular, the cross-species navigation and comparison is enhanced through a novel taxonomy section describing each represented species and through the implementation of interactive phylogenetic gene trees for 60% of tunicate genes. The gene expression section displays the results of RNA-seq experiments for the three major model species of solitary ascidians. Gene expression is controlled by the binding of transcription factors to cis-regulatory sequences. A high-resolution description of the DNA-binding specificity for 131 Ciona robusta (formerly C. intestinalis type A) transcription factors by SELEX-seq is provided and used to map candidate binding sites across the Ciona robusta and Phallusia mammillata genomes. Finally, use of a WashU Epigenome browser enhances genome navigation, while a Genomicus server was set up to explore microsynteny relationships within tunicates and with vertebrates, Amphioxus, echinoderms and hemichordates. PMID:29149270

Role of miR-1 expression in clear cell renal cell carcinoma (ccRCC): A bioinformatics study based on GEO, ArrayExpress microarrays and TCGA database.

PubMed

Yan, Hai-Biao; Huang, Jia-Cheng; Chen, You-Rong; Yao, Jian-Ni; Cen, Wei-Ning; Li, Jia-Yi; Jiang, Yi-Fan; Chen, Gang; Li, Sheng-Hua

2018-02-01

To investigate the clinical value and potential molecular mechanisms of miR-1 in clear cell renal cell carcinoma (ccRCC). We searched the Gene Expression Omnibus (GEO), ArrayExpress, several online publication databases and the Cancer Genome Atlas (TCGA). Continuous variable meta-analysis and diagnostic meta-analysis were conducted, both in Stata 14, to show the expression of miR-1 in ccRCC. Furthermore, we acquired the potential targets of miR-1 from datasets that transfected miR-1 into ccRCC cells, online prediction databases, differentially expressed genes from TCGA and literature. Subsequently bioinformatics analysis based on aforementioned selected target genes was conducted. The combined effect was -0.92 with the 95% confidence interval (CI) of -1.08 to -0.77 based on fixed effect model (I 2  = 81.3%, P < 0.001). No publication bias was found in our investigation. Sensitivity analysis showed that GSE47582 and 2 TCGA studies might cause heterogeneity. After eliminating them, the combined effect was -0.47 (95%CI: -0.78, -0.16) with I 2  = 18.3%. As for the diagnostic meta-analysis, the combined sensitivity and specificity were 0.90 (95%CI: 0.61, 0.98) and 0.63 (95%CI: 0.39, 0.82). The area under the curve (AUC) in the summarized receiver operating characteristic (SROC) curve was 0.83 (95%CI: 0.80, 0.86). No publication bias was found (P = 0.15). We finally got 67 genes which were defined the promising target genes of miR-1 in ccRCC. The most three significant KEGG pathways based on the aforementioned genes were Complement and coagulation cascades, ECM-receptor interaction and Focal adhesion. The downregulation of miR-1 might play an important role in ccRCC by targeting its target genes. Copyright © 2017 Elsevier GmbH. All rights reserved.

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

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

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

2009-01-01

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

NCBI GEO: archive for functional genomics data sets--10 years on.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20,000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity

NASA Astrophysics Data System (ADS)

Corcoran, Martin M.; Phad, Ganesh E.; Bernat, Néstor Vázquez; Stahl-Hennig, Christiane; Sumida, Noriyuki; Persson, Mats A. A.; Martin, Marcel; Hedestam, Gunilla B. Karlsson

2016-12-01

Comprehensive knowledge of immunoglobulin genetics is required to advance our understanding of B cell biology. Validated immunoglobulin variable (V) gene databases are close to completion only for human and mouse. We present a novel computational approach, IgDiscover, that identifies germline V genes from expressed repertoires to a specificity of 100%. IgDiscover uses a cluster identification process to produce candidate sequences that, once filtered, results in individualized germline V gene databases. IgDiscover was tested in multiple species, validated by genomic cloning and cross library comparisons and produces comprehensive gene databases even where limited genomic sequence is available. IgDiscover analysis of the allelic content of the Indian and Chinese-origin rhesus macaques reveals high levels of immunoglobulin gene diversity in this species. Further, we describe a novel human IGHV3-21 allele and confirm significant gene differences between Balb/c and C57BL6 mouse strains, demonstrating the power of IgDiscover as a germline V gene discovery tool.

Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity

PubMed Central

Corcoran, Martin M.; Phad, Ganesh E.; Bernat, Néstor Vázquez; Stahl-Hennig, Christiane; Sumida, Noriyuki; Persson, Mats A.A.; Martin, Marcel; Hedestam, Gunilla B. Karlsson

2016-01-01

Comprehensive knowledge of immunoglobulin genetics is required to advance our understanding of B cell biology. Validated immunoglobulin variable (V) gene databases are close to completion only for human and mouse. We present a novel computational approach, IgDiscover, that identifies germline V genes from expressed repertoires to a specificity of 100%. IgDiscover uses a cluster identification process to produce candidate sequences that, once filtered, results in individualized germline V gene databases. IgDiscover was tested in multiple species, validated by genomic cloning and cross library comparisons and produces comprehensive gene databases even where limited genomic sequence is available. IgDiscover analysis of the allelic content of the Indian and Chinese-origin rhesus macaques reveals high levels of immunoglobulin gene diversity in this species. Further, we describe a novel human IGHV3-21 allele and confirm significant gene differences between Balb/c and C57BL6 mouse strains, demonstrating the power of IgDiscover as a germline V gene discovery tool. PMID:27995928

The Molecular Signatures Database (MSigDB) hallmark gene set collection.

PubMed

Liberzon, Arthur; Birger, Chet; Thorvaldsdóttir, Helga; Ghandi, Mahmoud; Mesirov, Jill P; Tamayo, Pablo

2015-12-23

The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

Characterization of circulating microRNA expression in patients with a ventricular septal defect.

PubMed

Li, Dong; Ji, Long; Liu, Lianbo; Liu, Yizhi; Hou, Haifeng; Yu, Kunkun; Sun, Qiang; Zhao, Zhongtang

2014-01-01

Ventricular septal defect (VSD), one of the most common types of congenital heart disease (CHD), results from a combination of environmental and genetic factors. Recent studies demonstrated that microRNAs (miRNAs) are involved in development of CHD. This study was to characterize the expression of miRNAs that might be involved in the development or reflect the consequences of VSD. MiRNA microarray analysis and reverse transcription-polymerase chain reaction (RT-PCR) were employed to determine the miRNA expression profile from 3 patients with VSD and 3 VSD-free controls. 3 target gene databases were employed to predict the target genes of differentially expressed miRNAs. miRNAs that were generally consensus across the three databases were selected and then independently validated using real time PCR in plasma samples from 20 VSD patients and 15 VSD-free controls. Target genes of validated 8 miRNAs were predicted using bioinformatic methods. 36 differentially expressed miRNAs were found in the patients with VSD and the VSD-free controls. Compared with VSD-free controls, expression of 15 miRNAs were up-regulated and 21 miRNAs were downregulated in the VSD group. 15 miRNAs were selected based on database analysis results and expression levels of 8 miRNAs were validated. The results of the real time PCR were consistent with those of the microarray analysis. Gene ontology analysis indicated that the top target genes were mainly related to cardiac right ventricle morphogenesis. NOTCH1, HAND1, ZFPM2, and GATA3 were predicted as targets of hsa-let-7e-5p, hsa-miR-222-3p and hsa-miR-433. We report for the first time the circulating miRNA profile for patients with VSD and showed that 7 miRNAs were downregulated and 1 upregulated when matched to VSD-free controls. Analysis revealed target genes involved in cardiac development were probably regulated by these miRNAs.

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.

Estrogen alters the profile of the transcriptome in river snail Bellamya aeruginosa.

PubMed

Lei, Kun; Liu, Ruizhi; An, Li-Hui; Luo, Ying-Feng; LeBlanc, Gerald A

2015-03-01

We evaluated the transcriptome dynamics of the freshwater river snail Bellamya aeruginosa exposed to 17β-estradiol (E2) using the Roche/454 GS-FLX platform. In total, 41,869 unigenes, with an average length of 586 bp, representing 36,181 contigs and 5,688 singlets were obtained. Among them, 18.08, 36.85, and 25.47 % matched sequences in the GenBank non-redundant nucleic acid database, non-redundant protein database, and Swiss protein database, respectively. Annotation of the unigenes with gene ontology, and then mapping them to biological pathways, revealed large groups of genes related to growth, development, reproduction, signal transduction, and defense mechanisms. Significant differences were found in gene expression in both liver and testicular tissues between control and E2-exposed organisms. These changes in gene expression will help in understanding the molecular mechanisms of the response to physiological stress in the river snail exposed to estrogen, and will facilitate research into biological processes and underlying physiological adaptations to xenoestrogen exposure in gastropods.

Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods.

PubMed

Wang, Liming; Zhu, L; Luan, R; Wang, L; Fu, J; Wang, X; Sui, L

2016-10-10

Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM.

Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods

PubMed Central

Wang, Liming; Zhu, L.; Luan, R.; Wang, L.; Fu, J.; Wang, X.; Sui, L.

2016-01-01

Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM. PMID:27737314

An expression database for roots of the model legume Medicago truncatula under salt stress

PubMed Central

2009-01-01

Background Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. Description The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. Conclusion MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/. PMID:19906315

An expression database for roots of the model legume Medicago truncatula under salt stress.

PubMed

Li, Daofeng; Su, Zhen; Dong, Jiangli; Wang, Tao

2009-11-11

Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/.

VisANT 3.0: new modules for pathway visualization, editing, prediction and construction.

PubMed

Hu, Zhenjun; Ng, David M; Yamada, Takuji; Chen, Chunnuan; Kawashima, Shuichi; Mellor, Joe; Linghu, Bolan; Kanehisa, Minoru; Stuart, Joshua M; DeLisi, Charles

2007-07-01

With the integration of the KEGG and Predictome databases as well as two search engines for coexpressed genes/proteins using data sets obtained from the Stanford Microarray Database (SMD) and Gene Expression Omnibus (GEO) database, VisANT 3.0 supports exploratory pathway analysis, which includes multi-scale visualization of multiple pathways, editing and annotating pathways using a KEGG compatible visual notation and visualization of expression data in the context of pathways. Expression levels are represented either by color intensity or by nodes with an embedded expression profile. Multiple experiments can be navigated or animated. Known KEGG pathways can be enriched by querying either coexpressed components of known pathway members or proteins with known physical interactions. Predicted pathways for genes/proteins with unknown functions can be inferred from coexpression or physical interaction data. Pathways produced in VisANT can be saved as computer-readable XML format (VisML), graphic images or high-resolution Scalable Vector Graphics (SVG). Pathways in the format of VisML can be securely shared within an interested group or published online using a simple Web link. VisANT is freely available at http://visant.bu.edu.

Quantitative comparison of microarray experiments with published leukemia related gene expression signatures.

PubMed

Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin

2009-12-15

Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. A database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application. The presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may help to interpret new microarray data.

Transcriptome-wide analysis of WRKY transcription factors in wheat and their leaf rust responsive expression profiling.

PubMed

Satapathy, Lopamudra; Singh, Dharmendra; Ranjan, Prashant; Kumar, Dhananjay; Kumar, Manish; Prabhu, Kumble Vinod; Mukhopadhyay, Kunal

2014-12-01

WRKY, a plant-specific transcription factor family, has important roles in pathogen defense, abiotic cues and phytohormone signaling, yet little is known about their roles and molecular mechanism of function in response to rust diseases in wheat. We identified 100 TaWRKY sequences using wheat Expressed Sequence Tag database of which 22 WRKY sequences were novel. Identified proteins were characterized based on their zinc finger motifs and phylogenetic analysis clustered them into six clades consisting of class IIc and class III WRKY proteins. Functional annotation revealed major functions in metabolic and cellular processes in control plants; whereas response to stimuli, signaling and defense in pathogen inoculated plants, their major molecular function being binding to DNA. Tag-based expression analysis of the identified genes revealed differential expression between mock and Puccinia triticina inoculated wheat near isogenic lines. Gene expression was also performed with six rust-related microarray experiments at Gene Expression Omnibus database. TaWRKY10, 15, 17 and 56 were common in both tag-based and microarray-based differential expression analysis and could be representing rust specific WRKY genes. The obtained results will bestow insight into the functional characterization of WRKY transcription factors responsive to leaf rust pathogenesis that can be used as candidate genes in molecular breeding programs to improve biotic stress tolerance in wheat.

Access and use of the GUDMAP database of genitourinary development.

PubMed

Davies, Jamie A; Little, Melissa H; Aronow, Bruce; Armstrong, Jane; Brennan, Jane; Lloyd-MacGilp, Sue; Armit, Chris; Harding, Simon; Piu, Xinjun; Roochun, Yogmatee; Haggarty, Bernard; Houghton, Derek; Davidson, Duncan; Baldock, Richard

2012-01-01

The Genitourinary Development Molecular Atlas Project (GUDMAP) aims to document gene expression across time and space in the developing urogenital system of the mouse, and to provide access to a variety of relevant practical and educational resources. Data come from microarray gene expression profiling (from laser-dissected and FACS-sorted samples) and in situ hybridization at both low (whole-mount) and high (section) resolutions. Data are annotated to a published, high-resolution anatomical ontology and can be accessed using a variety of search interfaces. Here, we explain how to run typical queries on the database, by gene or anatomical location, how to view data, how to perform complex queries, and how to submit data.

miRWalk--database: prediction of possible miRNA binding sites by "walking" the genes of three genomes.

PubMed

Dweep, Harsh; Sticht, Carsten; Pandey, Priyanka; Gretz, Norbert

2011-10-01

MicroRNAs are small, non-coding RNA molecules that can complementarily bind to the mRNA 3'-UTR region to regulate the gene expression by transcriptional repression or induction of mRNA degradation. Increasing evidence suggests a new mechanism by which miRNAs may regulate target gene expression by binding in promoter and amino acid coding regions. Most of the existing databases on miRNAs are restricted to mRNA 3'-UTR region. To address this issue, we present miRWalk, a comprehensive database on miRNAs, which hosts predicted as well as validated miRNA binding sites, information on all known genes of human, mouse and rat. All mRNAs, mitochondrial genes and 10 kb upstream flanking regions of all known genes of human, mouse and rat were analyzed by using a newly developed algorithm named 'miRWalk' as well as with eight already established programs for putative miRNA binding sites. An automated and extensive text-mining search was performed on PubMed database to extract validated information on miRNAs. Combined information was put into a MySQL database. miRWalk presents predicted and validated information on miRNA-target interaction. Such a resource enables researchers to validate new targets of miRNA not only on 3'-UTR, but also on the other regions of all known genes. The 'Validated Target module' is updated every month and the 'Predicted Target module' is updated every 6 months. miRWalk is freely available at http://mirwalk.uni-hd.de/. Copyright © 2011 Elsevier Inc. All rights reserved.

The Plant Structure Ontology, a Unified Vocabulary of Anatomy and Morphology of a Flowering Plant1[W][OA

PubMed Central

Ilic, Katica; Kellogg, Elizabeth A.; Jaiswal, Pankaj; Zapata, Felipe; Stevens, Peter F.; Vincent, Leszek P.; Avraham, Shulamit; Reiser, Leonore; Pujar, Anuradha; Sachs, Martin M.; Whitman, Noah T.; McCouch, Susan R.; Schaeffer, Mary L.; Ware, Doreen H.; Stein, Lincoln D.; Rhee, Seung Y.

2007-01-01

Formal description of plant phenotypes and standardized annotation of gene expression and protein localization data require uniform terminology that accurately describes plant anatomy and morphology. This facilitates cross species comparative studies and quantitative comparison of phenotypes and expression patterns. A major drawback is variable terminology that is used to describe plant anatomy and morphology in publications and genomic databases for different species. The same terms are sometimes applied to different plant structures in different taxonomic groups. Conversely, similar structures are named by their species-specific terms. To address this problem, we created the Plant Structure Ontology (PSO), the first generic ontological representation of anatomy and morphology of a flowering plant. The PSO is intended for a broad plant research community, including bench scientists, curators in genomic databases, and bioinformaticians. The initial releases of the PSO integrated existing ontologies for Arabidopsis (Arabidopsis thaliana), maize (Zea mays), and rice (Oryza sativa); more recent versions of the ontology encompass terms relevant to Fabaceae, Solanaceae, additional cereal crops, and poplar (Populus spp.). Databases such as The Arabidopsis Information Resource, Nottingham Arabidopsis Stock Centre, Gramene, MaizeGDB, and SOL Genomics Network are using the PSO to describe expression patterns of genes and phenotypes of mutants and natural variants and are regularly contributing new annotations to the Plant Ontology database. The PSO is also used in specialized public databases, such as BRENDA, GENEVESTIGATOR, NASCArrays, and others. Over 10,000 gene annotations and phenotype descriptions from participating databases can be queried and retrieved using the Plant Ontology browser. The PSO, as well as contributed gene associations, can be obtained at www.plantontology.org. PMID:17142475

ImmunemiR - A Database of Prioritized Immune miRNA Disease Associations and its Interactome.

PubMed

Prabahar, Archana; Natarajan, Jeyakumar

2017-01-01

MicroRNAs are the key regulators of gene expression and their abnormal expression in the immune system may be associated with several human diseases such as inflammation, cancer and autoimmune diseases. Elucidation of miRNA disease association through the interactome will deepen the understanding of its disease mechanisms. A specialized database for immune miRNAs is highly desirable to demonstrate the immune miRNA disease associations in the interactome. miRNAs specific to immune related diseases were retrieved from curated databases such as HMDD, miR2disease and PubMed literature based on MeSH classification of immune system diseases. The additional data such as miRNA target genes, genes coding protein-protein interaction information were compiled from related resources. Further, miRNAs were prioritized to specific immune diseases using random walk ranking algorithm. In total 245 immune miRNAs associated with 92 OMIM disease categories were identified from external databases. The resultant data were compiled as ImmunemiR, a database of prioritized immune miRNA disease associations. This database provides both text based annotation information and network visualization of its interactome. To our knowledge, ImmunemiR is the first available database to provide a comprehensive repository of human immune disease associated miRNAs with network visualization options of its target genes, protein-protein interactions (PPI) and its disease associations. It is freely available at http://www.biominingbu.org/immunemir/. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Transcriptome database resource and gene expression atlas for the rose

PubMed Central

2012-01-01

Background For centuries roses have been selected based on a number of traits. Little information exists on the genetic and molecular basis that contributes to these traits, mainly because information on expressed genes for this economically important ornamental plant is scarce. Results Here, we used a combination of Illumina and 454 sequencing technologies to generate information on Rosa sp. transcripts using RNA from various tissues and in response to biotic and abiotic stresses. A total of 80714 transcript clusters were identified and 76611 peptides have been predicted among which 20997 have been clustered into 13900 protein families. BLASTp hits in closely related Rosaceae species revealed that about half of the predicted peptides in the strawberry and peach genomes have orthologs in Rosa dataset. Digital expression was obtained using RNA samples from organs at different development stages and under different stress conditions. qPCR validated the digital expression data for a selection of 23 genes with high or low expression levels. Comparative gene expression analyses between the different tissues and organs allowed the identification of clusters that are highly enriched in given tissues or under particular conditions, demonstrating the usefulness of the digital gene expression analysis. A web interface ROSAseq was created that allows data interrogation by BLAST, subsequent analysis of DNA clusters and access to thorough transcript annotation including best BLAST matches on Fragaria vesca, Prunus persica and Arabidopsis. The rose peptides dataset was used to create the ROSAcyc resource pathway database that allows access to the putative genes and enzymatic pathways. Conclusions The study provides useful information on Rosa expressed genes, with thorough annotation and an overview of expression patterns for transcripts with good accuracy. PMID:23164410

Regulatory interactions between long noncoding RNA LINC00968 and miR-9-3p in non-small cell lung cancer: A bioinformatic analysis based on miRNA microarray, GEO and TCGA.

PubMed

Li, Dong-Yao; Chen, Wen-Jie; Shang, Jun; Chen, Gang; Li, Shi-Kang

2018-06-01

Long non-coding RNAs (lncRNAs) have been demonstrated to mediate carcinogenesis in various types of cancer. However, the regulatory role of lncRNA LINC00968 in lung adenocarcinoma remains unclear. The microRNA (miRNA) expression in LINC00968-overexpressing human lung adenocarcinoma A549 cells was detected using miRNA microarray analysis. miR-9-3p was selected for further analysis, and its expression was verified in the Gene Expression Omnibus (GEO) database. In addition, the regulatory axis of LINC00968 was validated using The Cancer Genome Atlas (TCGA) database. Results of the GEO database indicated miR-9-3p expression in lung adenocarcinoma was significantly higher compared with normal tissues. Functional enrichment analyses of the target genes of miR-9-3p indicated protein binding and the AMP-activated protein kinase pathway were the most enriched Gene Ontology and KEGG terms, respectively. Combining target genes with the correlated genes of LINC00968 and miR-9-3p, 120 objective genes were obtained, which were used to construct a protein-protein interaction (PPI) network. Cyclin A2 (CCNA2) was identified to have a vital role in the PPI network. Significant correlations were detected between LINC00968, miR-9-3p and CCNA2 in lung adenocarcinoma. The LINC00968/miR-9-3p/CCNA2 regulatory axis provides a new foundation for further evaluating the regulatory mechanisms of LINC00968 in lung adenocarcinoma.

Mining Microarray Data at NCBI’s Gene Expression Omnibus (GEO)*

PubMed Central

Barrett, Tanya; Edgar, Ron

2006-01-01

Summary The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo. PMID:16888359

Database resources of the National Center for Biotechnology Information

PubMed Central

2015-01-01

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (Bookshelf, PubMed Central (PMC) and PubReader); medical genetics (ClinVar, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen); genes and genomics (BioProject, BioSample, dbSNP, dbVar, Epigenomics, Gene, Gene Expression Omnibus (GEO), Genome, HomoloGene, the Map Viewer, Nucleotide, PopSet, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser, Trace Archive and UniGene); and proteins and chemicals (Biosystems, COBALT, the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB), Protein Clusters, Protein and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for many of these databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov. PMID:25398906

Database resources of the National Center for Biotechnology Information

PubMed Central

2016-01-01

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (PubMed Central (PMC), Bookshelf and PubReader), health (ClinVar, dbGaP, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen), genomes (BioProject, Assembly, Genome, BioSample, dbSNP, dbVar, Epigenomics, the Map Viewer, Nucleotide, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser and the Trace Archive), genes (Gene, Gene Expression Omnibus (GEO), HomoloGene, PopSet and UniGene), proteins (Protein, the Conserved Domain Database (CDD), COBALT, Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB) and Protein Clusters) and chemicals (Biosystems and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for most of these databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:26615191

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

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.

mirEX: a platform for comparative exploration of plant pri-miRNA expression data.

PubMed

Bielewicz, Dawid; Dolata, Jakub; Zielezinski, Andrzej; Alaba, Sylwia; Szarzynska, Bogna; Szczesniak, Michal W; Jarmolowski, Artur; Szweykowska-Kulinska, Zofia; Karlowski, Wojciech M

2012-01-01

mirEX is a comprehensive platform for comparative analysis of primary microRNA expression data. RT-qPCR-based gene expression profiles are stored in a universal and expandable database scheme and wrapped by an intuitive user-friendly interface. A new way of accessing gene expression data in mirEX includes a simple mouse operated querying system and dynamic graphs for data mining analyses. In contrast to other publicly available databases, the mirEX interface allows a simultaneous comparison of expression levels between various microRNA genes in diverse organs and developmental stages. Currently, mirEX integrates information about the expression profile of 190 Arabidopsis thaliana pri-miRNAs in seven different developmental stages: seeds, seedlings and various organs of mature plants. Additionally, by providing RNA structural models, publicly available deep sequencing results, experimental procedure details and careful selection of auxiliary data in the form of web links, mirEX can function as a one-stop solution for Arabidopsis microRNA information. A web-based mirEX interface can be accessed at http://bioinfo.amu.edu.pl/mirex.

Development of a versatile enrichment analysis tool reveals associations between the maternal brain and mental health disorders, including autism

PubMed Central

2013-01-01

Background A recent study of lateral septum (LS) suggested a large number of autism-related genes with altered expression in the postpartum state. However, formally testing the findings for enrichment of autism-associated genes proved to be problematic with existing software. Many gene-disease association databases have been curated which are not currently incorporated in popular, full-featured enrichment tools, and the use of custom gene lists in these programs can be difficult to perform and interpret. As a simple alternative, we have developed the Modular Single-set Enrichment Test (MSET), a minimal tool that enables one to easily evaluate expression data for enrichment of any conceivable gene list of interest. Results The MSET approach was validated by testing several publicly available expression data sets for expected enrichment in areas of autism, attention deficit hyperactivity disorder (ADHD), and arthritis. Using nine independent, unique autism gene lists extracted from association databases and two recent publications, a striking consensus of enrichment was detected within gene expression changes in LS of postpartum mice. A network of 160 autism-related genes was identified, representing developmental processes such as synaptic plasticity, neuronal morphogenesis, and differentiation. Additionally, maternal LS displayed enrichment for genes associated with bipolar disorder, schizophrenia, ADHD, and depression. Conclusions The transition to motherhood includes the most fundamental social bonding event in mammals and features naturally occurring changes in sociability. Some individuals with autism, schizophrenia, or other mental health disorders exhibit impaired social traits. Genes involved in these deficits may also contribute to elevated sociability in the maternal brain. To date, this is the first study to show a significant, quantitative link between the maternal brain and mental health disorders using large scale gene expression data. Thus, the postpartum brain may provide a novel and promising platform for understanding the complex genetics of improved sociability that may have direct relevance for multiple psychiatric illnesses. This study also provides an important new tool that fills a critical analysis gap and makes evaluation of enrichment using any database of interest possible with an emphasis on ease of use and methodological transparency. PMID:24245670

Development of a versatile enrichment analysis tool reveals associations between the maternal brain and mental health disorders, including autism.

PubMed

Eisinger, Brian E; Saul, Michael C; Driessen, Terri M; Gammie, Stephen C

2013-11-19

A recent study of lateral septum (LS) suggested a large number of autism-related genes with altered expression in the postpartum state. However, formally testing the findings for enrichment of autism-associated genes proved to be problematic with existing software. Many gene-disease association databases have been curated which are not currently incorporated in popular, full-featured enrichment tools, and the use of custom gene lists in these programs can be difficult to perform and interpret. As a simple alternative, we have developed the Modular Single-set Enrichment Test (MSET), a minimal tool that enables one to easily evaluate expression data for enrichment of any conceivable gene list of interest. The MSET approach was validated by testing several publicly available expression data sets for expected enrichment in areas of autism, attention deficit hyperactivity disorder (ADHD), and arthritis. Using nine independent, unique autism gene lists extracted from association databases and two recent publications, a striking consensus of enrichment was detected within gene expression changes in LS of postpartum mice. A network of 160 autism-related genes was identified, representing developmental processes such as synaptic plasticity, neuronal morphogenesis, and differentiation. Additionally, maternal LS displayed enrichment for genes associated with bipolar disorder, schizophrenia, ADHD, and depression. The transition to motherhood includes the most fundamental social bonding event in mammals and features naturally occurring changes in sociability. Some individuals with autism, schizophrenia, or other mental health disorders exhibit impaired social traits. Genes involved in these deficits may also contribute to elevated sociability in the maternal brain. To date, this is the first study to show a significant, quantitative link between the maternal brain and mental health disorders using large scale gene expression data. Thus, the postpartum brain may provide a novel and promising platform for understanding the complex genetics of improved sociability that may have direct relevance for multiple psychiatric illnesses. This study also provides an important new tool that fills a critical analysis gap and makes evaluation of enrichment using any database of interest possible with an emphasis on ease of use and methodological transparency.

Mouse IDGenes: a reference database for genetic interactions in the developing mouse brain.

PubMed

Matthes, Michaela; Preusse, Martin; Zhang, Jingzhong; Schechter, Julia; Mayer, Daniela; Lentes, Bernd; Theis, Fabian; Prakash, Nilima; Wurst, Wolfgang; Trümbach, Dietrich

2014-01-01

The study of developmental processes in the mouse and other vertebrates includes the understanding of patterning along the anterior-posterior, dorsal-ventral and medial- lateral axis. Specifically, neural development is also of great clinical relevance because several human neuropsychiatric disorders such as schizophrenia, autism disorders or drug addiction and also brain malformations are thought to have neurodevelopmental origins, i.e. pathogenesis initiates during childhood and adolescence. Impacts during early neurodevelopment might also predispose to late-onset neurodegenerative disorders, such as Parkinson's disease. The neural tube develops from its precursor tissue, the neural plate, in a patterning process that is determined by compartmentalization into morphogenetic units, the action of local signaling centers and a well-defined and locally restricted expression of genes and their interactions. While public databases provide gene expression data with spatio-temporal resolution, they usually neglect the genetic interactions that govern neural development. Here, we introduce Mouse IDGenes, a reference database for genetic interactions in the developing mouse brain. The database is highly curated and offers detailed information about gene expressions and the genetic interactions at the developing mid-/hindbrain boundary. To showcase the predictive power of interaction data, we infer new Wnt/β-catenin target genes by machine learning and validate one of them experimentally. The database is updated regularly. Moreover, it can easily be extended by the research community. Mouse IDGenes will contribute as an important resource to the research on mouse brain development, not exclusively by offering data retrieval, but also by allowing data input. http://mouseidgenes.helmholtz-muenchen.de. © The Author(s) 2014. Published by Oxford University Press.

Whole Transcriptome Analysis Provides Insights into Molecular Mechanisms for Molting in Litopenaeus vannamei

PubMed Central

Gao, Yi; Zhang, Xiaojun; Wei, Jiankai; Sun, Xiaoqing; Yuan, Jianbo; Li, Fuhua; Xiang, Jianhai

2015-01-01

Molting is one of the most important biological processes in shrimp growth and development. All shrimp undergo cyclic molting periodically to shed and replace their exoskeletons. This process is essential for growth, metamorphosis, and reproduction in shrimp. However, the molecular mechanisms underlying shrimp molting remain poorly understood. In this study, we investigated global expression changes in the transcriptomes of the Pacific white shrimp, Litopenaeus vannamei, the most commonly cultured shrimp species worldwide. The transcriptome of whole L. vannamei was investigated by RNA-sequencing (RNA-seq) throughout the molting cycle, including the inter-molt (C), pre-molt (D0, D1, D2, D3, D4), and post-molt (P1 and P2) stages, and 93,756 unigenes were identified. Among these genes, we identified 5,117 genes differentially expressed (log2ratio ≥1 and FDR ≤0.001) in adjacent molt stages. The results were compared against the National Center for Biotechnology Information (NCBI) non-redundant protein/nucleotide sequence database, Swiss-Prot, PFAM database, the Gene Ontology database, and the Kyoto Encyclopedia of Genes and Genomes database in order to annotate gene descriptions, associate them with gene ontology terms, and assign them to pathways. The expression patterns for genes involved in several molecular events critical for molting, such as hormone regulation, triggering events, implementation phases, skelemin, immune responses were characterized and considered as mechanisms underlying molting in L. vannamei. Comparisons with transcriptomic analyses in other arthropods were also performed. The characterization of major transcriptional changes in genes involved in the molting cycle provides candidates for future investigation of the molecular mechanisms. The data generated in this study will serve as an important transcriptomic resource for the shrimp research community to facilitate gene and genome annotation and to characterize key molecular processes underlying shrimp development. PMID:26650402

NeuroTransDB: highly curated and structured transcriptomic metadata for neurodegenerative diseases.

PubMed

Bagewadi, Shweta; Adhikari, Subash; Dhrangadhariya, Anjani; Irin, Afroza Khanam; Ebeling, Christian; Namasivayam, Aishwarya Alex; Page, Matthew; Hofmann-Apitius, Martin; Senger, Philipp

2015-01-01

Neurodegenerative diseases are chronic debilitating conditions, characterized by progressive loss of neurons that represent a significant health care burden as the global elderly population continues to grow. Over the past decade, high-throughput technologies such as the Affymetrix GeneChip microarrays have provided new perspectives into the pathomechanisms underlying neurodegeneration. Public transcriptomic data repositories, namely Gene Expression Omnibus and curated ArrayExpress, enable researchers to conduct integrative meta-analysis; increasing the power to detect differentially regulated genes in disease and explore patterns of gene dysregulation across biologically related studies. The reliability of retrospective, large-scale integrative analyses depends on an appropriate combination of related datasets, in turn requiring detailed meta-annotations capturing the experimental setup. In most cases, we observe huge variation in compliance to defined standards for submitted metadata in public databases. Much of the information to complete, or refine meta-annotations are distributed in the associated publications. For example, tissue preparation or comorbidity information is frequently described in an article's supplementary tables. Several value-added databases have employed additional manual efforts to overcome this limitation. However, none of these databases explicate annotations that distinguish human and animal models in neurodegeneration context. Therefore, adopting a more specific disease focus, in combination with dedicated disease ontologies, will better empower the selection of comparable studies with refined annotations to address the research question at hand. In this article, we describe the detailed development of NeuroTransDB, a manually curated database containing metadata annotations for neurodegenerative studies. The database contains more than 20 dimensions of metadata annotations within 31 mouse, 5 rat and 45 human studies, defined in collaboration with domain disease experts. We elucidate the step-by-step guidelines used to critically prioritize studies from public archives and their metadata curation and discuss the key challenges encountered. Curated metadata for Alzheimer's disease gene expression studies are available for download. Database URL: www.scai.fraunhofer.de/NeuroTransDB.html. © The Author(s) 2015. Published by Oxford University Press.

NeuroTransDB: highly curated and structured transcriptomic metadata for neurodegenerative diseases

PubMed Central

Bagewadi, Shweta; Adhikari, Subash; Dhrangadhariya, Anjani; Irin, Afroza Khanam; Ebeling, Christian; Namasivayam, Aishwarya Alex; Page, Matthew; Hofmann-Apitius, Martin

2015-01-01

Neurodegenerative diseases are chronic debilitating conditions, characterized by progressive loss of neurons that represent a significant health care burden as the global elderly population continues to grow. Over the past decade, high-throughput technologies such as the Affymetrix GeneChip microarrays have provided new perspectives into the pathomechanisms underlying neurodegeneration. Public transcriptomic data repositories, namely Gene Expression Omnibus and curated ArrayExpress, enable researchers to conduct integrative meta-analysis; increasing the power to detect differentially regulated genes in disease and explore patterns of gene dysregulation across biologically related studies. The reliability of retrospective, large-scale integrative analyses depends on an appropriate combination of related datasets, in turn requiring detailed meta-annotations capturing the experimental setup. In most cases, we observe huge variation in compliance to defined standards for submitted metadata in public databases. Much of the information to complete, or refine meta-annotations are distributed in the associated publications. For example, tissue preparation or comorbidity information is frequently described in an article’s supplementary tables. Several value-added databases have employed additional manual efforts to overcome this limitation. However, none of these databases explicate annotations that distinguish human and animal models in neurodegeneration context. Therefore, adopting a more specific disease focus, in combination with dedicated disease ontologies, will better empower the selection of comparable studies with refined annotations to address the research question at hand. In this article, we describe the detailed development of NeuroTransDB, a manually curated database containing metadata annotations for neurodegenerative studies. The database contains more than 20 dimensions of metadata annotations within 31 mouse, 5 rat and 45 human studies, defined in collaboration with domain disease experts. We elucidate the step-by-step guidelines used to critically prioritize studies from public archives and their metadata curation and discuss the key challenges encountered. Curated metadata for Alzheimer’s disease gene expression studies are available for download. Database URL: www.scai.fraunhofer.de/NeuroTransDB.html PMID:26475471

Members of the Dof transcription factor family in Triticum aestivum are associated with light-mediated gene regulation.

PubMed

Shaw, Lindsay M; McIntyre, C Lynne; Gresshoff, Peter M; Xue, Gang-Ping

2009-11-01

DNA binding with One Finger (Dof) protein is a plant-specific transcription factor implicated in the regulation of many important plant-specific processes, including photosynthesis and carbohydrate metabolism. This study has identified 31 Dof genes (TaDof) in bread wheat through extensive analysis of current nucleotide databases. Phylogenetic analysis suggests that the TaDof family can be divided into four clades. Expression analysis of the TaDof family across all major organs using quantitative RT-PCR and searches of the wheat genome array database revealed that the majority of TaDof members were predominately expressed in vegetative organs. A large number of TaDof members were down-regulated by drought and/or were responsive to the light and dark cycle. Further expression analysis revealed that light up-regulated TaDof members were highly correlated in expression with a number of genes that are involved in photosynthesis or sucrose transport. These data suggest that the TaDof family may have an important role in light-mediated gene regulation, including involvement in the photosynthetic process.

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR.

PubMed

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch.

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR

PubMed Central

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch. PMID:21917859

Transcriptome Sequencing and Positive Selected Genes Analysis of Bombyx mandarina

PubMed Central

Wu, Yuqian; Long, Renwen; Liu, Chun; Xia, Qingyou

2015-01-01

The wild silkworm Bombyx mandarina is widely believed to be an ancestor of the domesticated silkworm, Bombyx mori. Silkworms are often used as a model for studying the mechanism of species domestication. Here, we performed transcriptome sequencing of the wild silkworm using an Illumina HiSeq2000 platform. We produced 100,004,078 high-quality reads and assembled them into 50,773 contigs with an N50 length of 1764 bp and a mean length of 941.62 bp. A total of 33,759 unigenes were identified, with 12,805 annotated in the Nr database, 8273 in the Pfam database, and 9093 in the Swiss-Prot database. Expression profile analysis found significant differential expression of 1308 unigenes between the middle silk gland (MSG) and posterior silk gland (PSG). Three sericin genes (sericin 1, sericin 2, and sericin 3) were expressed specifically in the MSG and three fibroin genes (fibroin-H, fibroin-L, and fibroin/P25) were expressed specifically in the PSG. In addition, 32,297 Single-nucleotide polymorphisms (SNPs) and 361 insertion-deletions (INDELs) were detected. Comparison with the domesticated silkworm p50/Dazao identified 5,295 orthologous genes, among which 400 might have experienced or to be experiencing positive selection by Ka/Ks analysis. These data and analyses presented here provide insights into silkworm domestication and an invaluable resource for wild silkworm genomics research. PMID:25806526

iMETHYL: an integrative database of human DNA methylation, gene expression, and genomic variation.

PubMed

Komaki, Shohei; Shiwa, Yuh; Furukawa, Ryohei; Hachiya, Tsuyoshi; Ohmomo, Hideki; Otomo, Ryo; Satoh, Mamoru; Hitomi, Jiro; Sobue, Kenji; Sasaki, Makoto; Shimizu, Atsushi

2018-01-01

We launched an integrative multi-omics database, iMETHYL (http://imethyl.iwate-megabank.org). iMETHYL provides whole-DNA methylation (~24 million autosomal CpG sites), whole-genome (~9 million single-nucleotide variants), and whole-transcriptome (>14 000 genes) data for CD4 + T-lymphocytes, monocytes, and neutrophils collected from approximately 100 subjects. These data were obtained from whole-genome bisulfite sequencing, whole-genome sequencing, and whole-transcriptome sequencing, making iMETHYL a comprehensive database.

Investigation of candidate genes for osteoarthritis based on gene expression profiles.

PubMed

Dong, Shuanghai; Xia, Tian; Wang, Lei; Zhao, Qinghua; Tian, Jiwei

2016-12-01

To explore the mechanism of osteoarthritis (OA) and provide valid biological information for further investigation. Gene expression profile of GSE46750 was downloaded from Gene Expression Omnibus database. The Linear Models for Microarray Data (limma) package (Bioconductor project, http://www.bioconductor.org/packages/release/bioc/html/limma.html) was used to identify differentially expressed genes (DEGs) in inflamed OA samples. Gene Ontology function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were performed based on Database for Annotation, Visualization and Integrated Discovery data, and protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins database. Regulatory network was screened based on Encyclopedia of DNA Elements. Molecular Complex Detection was used for sub-network screening. Two sub-networks with highest node degree were integrated with transcriptional regulatory network and KEGG functional enrichment analysis was processed for 2 modules. In total, 401 up- and 196 down-regulated DEGs were obtained. Up-regulated DEGs were involved in inflammatory response, while down-regulated DEGs were involved in cell cycle. PPI network with 2392 protein interactions was constructed. Moreover, 10 genes including Interleukin 6 (IL6) and Aurora B kinase (AURKB) were found to be outstanding in PPI network. There are 214 up- and 8 down-regulated transcription factor (TF)-target pairs in the TF regulatory network. Module 1 had TFs including SPI1, PRDM1, and FOS, while module 2 contained FOSL1. The nodes in module 1 were enriched in chemokine signaling pathway, while the nodes in module 2 were mainly enriched in cell cycle. The screened DEGs including IL6, AGT, and AURKB might be potential biomarkers for gene therapy for OA by being regulated by TFs such as FOS and SPI1, and participating in the cell cycle and cytokine-cytokine receptor interaction pathway. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.

Discovery of Possible Gene Relationships through the Application of Self-Organizing Maps to DNA Microarray Databases

PubMed Central

Chavez-Alvarez, Rocio; Chavoya, Arturo; Mendez-Vazquez, Andres

2014-01-01

DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. On the other hand, pattern recognition techniques can contribute to the analysis of such massive measurements, providing a model of gene expression level evolution through the cell cycle process. In this paper, we propose the use of one of such techniques –an unsupervised artificial neural network called a Self-Organizing Map (SOM)–which has been successfully applied to processes involving very noisy signals, classifying and organizing them, and assisting in the discovery of behavior patterns without requiring prior knowledge about the process under analysis. As a test bed for the use of SOMs in finding possible relationships among genes and their possible contribution in some biological processes, we selected 282 S. cerevisiae genes that have been shown through biological experiments to have an activity during the cell cycle. The expression level of these genes was analyzed in five of the most cited time series DNA microarray databases used in the study of the cell cycle of this organism. With the use of SOM, it was possible to find clusters of genes with similar behavior in the five databases along two cell cycles. This result suggested that some of these genes might be biologically related or might have a regulatory relationship, as was corroborated by comparing some of the clusters obtained with SOMs against a previously reported regulatory network that was generated using biological knowledge, such as protein-protein interactions, gene expression levels, metabolism dynamics, promoter binding, and modification, regulation and transport of proteins. The methodology described in this paper could be applied to the study of gene relationships of other biological processes in different organisms. PMID:24699245

Profiling and Quantifying Differential Gene Transcription Provide Insights into Ganoderic Acid Biosynthesis in Ganoderma lucidum in Response to Methyl Jasmonate

PubMed Central

Shi, Liang; Mu, Da-Shuai; Jiang, Ai-Liang; Han, Qin; Zhao, Ming-Wen

2013-01-01

Ganoderma lucidum is a mushroom with traditional medicinal properties that has been widely used in China and other countries in Eastern Asia. Ganoderic acids (GA) produced by G. lucidum exhibit important pharmacological activities. Previous studies have demonstrated that methyl jasmonate (MeJA) is a potent inducer of GA biosynthesis and the expression of genes involved in the GA biosynthesis pathway in G. lucidum. To further explore the mechanism of GA biosynthesis, cDNA-Amplified Fragment Length Polymorphism (cDNA-AFLP) was used to identify genes that are differentially expressed in response to MeJA. Using 64 primer combinations, over 3910 transcriptionally derived fragments (TDFs) were obtained. Reliable sequence data were obtained for 390 of 458 selected TDFs. Ninety of these TDFs were annotated with known functions through BLASTX searching the GenBank database, and 12 annotated TDFs were assigned into secondary metabolic pathways by searching the KEGGPATHWAY database. Twenty-five TDFs were selected for qRT-PCR analysis to confirm the expression patterns observed with cDNA-AFLP. The qRT-PCR results were consistent with the altered patterns of gene expression revealed by the cDNA-AFLP technique. Additionally, the transcript levels of 10 genes were measured at the mycelium, primordia, and fruiting body developmental stages of G. lucidum. The greatest expression levels were reached during primordia for all of the genes except cytochrome b2 reached its highest expression level in the mycelium stage. This study not only identifies new candidate genes involved in the regulation of GA biosynthesis but also provides further insight into MeJA-induced gene expression and secondary metabolic response in G. lucidum. PMID:23762280

A Novel Paramyxovirus?

PubMed Central

García-Sastre, Adolfo; Palese, Peter

2005-01-01

In public databases, we identified sequences reported as human genes expressed in kidney mesangial cells. The similarity of these genes to paramyxovirus matrix, fusion, and phosphoprotein genes suggests that they are derived from a novel paramyxovirus. These genes are sufficiently unique to suggest the existence of a novel paramyxovirus genus. PMID:15705331

Comparative transcriptome analysis of papilla and skin in the sea cucumber, Apostichopus japonicus.

PubMed

Zhou, Xiaoxu; Cui, Jun; Liu, Shikai; Kong, Derong; Sun, He; Gu, Chenlei; Wang, Hongdi; Qiu, Xuemei; Chang, Yaqing; Liu, Zhanjiang; Wang, Xiuli

2016-01-01

Papilla and skin are two important organs of the sea cucumber. Both tissues have ectodermic origin, but they are morphologically and functionally very different. In the present study, we performed comparative transcriptome analysis of the papilla and skin from the sea cucumber (Apostichopus japonicus) in order to identify and characterize gene expression profiles by using RNA-Seq technology. We generated 30.6 and 36.4 million clean reads from the papilla and skin and de novo assembled in 156,501 transcripts. The Gene Ontology (GO) analysis indicated that cell part, metabolic process and catalytic activity were the most abundant GO category in cell component, biological process and molecular funcation, respectively. Comparative transcriptome analysis between the papilla and skin allowed the identification of 1,059 differentially expressed genes, of which 739 genes were expressed at higher levels in papilla, while 320 were expressed at higher levels in skin. In addition, 236 differentially expressed unigenes were not annotated with any database, 160 of which were apparently expressed at higher levels in papilla, 76 were expressed at higher levels in skin. We identified a total of 288 papilla-specific genes, 171 skin-specific genes and 600 co-expressed genes. Also, 40 genes in papilla-specific were not annotated with any database, 2 in skin-specific. Development-related genes were also enriched, such as fibroblast growth factor, transforming growth factor-β, collagen-α2 and Integrin-α2, which may be related to the formation of the papilla and skin in sea cucumber. Further pathway analysis identified ten KEGG pathways that were differently enriched between the papilla and skin. The findings on expression profiles between two key organs of the sea cucumber should be valuable to reveal molecular mechanisms involved in the development of organs that are related but with morphological differences in the sea cucumber.

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

Generation of a foveomacular transcriptome

PubMed Central

Bernstein, Steven; Wong, Paul W.

2014-01-01

Purpose Organizing molecular biologic data is a growing challenge since the rate of data accumulation is steadily increasing. Information relevant to a particular biologic query can be difficult to extract from the comprehensive databases currently available. We present a data collection and organization model designed to ameliorate these problems and applied it to generate an expressed sequence tag (EST)–based foveomacular transcriptome. Methods Using Perl, MySQL, EST libraries, screening, and human foveomacular gene expression as a model system, we generated a foveomacular transcriptome database enriched for molecularly relevant data. Results Using foveomacula as a gene expression model tissue, we identified and organized 6,056 genes expressed in that tissue. Of those identified genes, 3,480 had not been previously described as expressed in the foveomacula. Internal experimental controls as well as comparison of our data set to published data sets suggest we do not yet have a complete description of the foveomacula transcriptome. Conclusions We present an organizational method designed to amplify the utility of data pertinent to a specific research interest. Our method is generic enough to be applicable to a variety of conditions yet focused enough to allow for specialized study. PMID:24991187

BioImaging Database

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

David Nix, Lisa Simirenko

2006-10-25

The Biolmaging Database (BID) is a relational database developed to store the data and meta-data for the 3D gene expression in early Drosophila embryo development on a cellular level. The schema was written to be used with the MySQL DBMS but with minor modifications can be used on any SQL compliant relational DBMS.

MGDB: a comprehensive database of genes involved in melanoma.

PubMed

Zhang, Di; Zhu, Rongrong; Zhang, Hanqian; Zheng, Chun-Hou; Xia, Junfeng

2015-01-01

The Melanoma Gene Database (MGDB) is a manually curated catalog of molecular genetic data relating to genes involved in melanoma. The main purpose of this database is to establish a network of melanoma related genes and to facilitate the mechanistic study of melanoma tumorigenesis. The entries describing the relationships between melanoma and genes in the current release were manually extracted from PubMed abstracts, which contains cumulative to date 527 human melanoma genes (422 protein-coding and 105 non-coding genes). Each melanoma gene was annotated in seven different aspects (General Information, Expression, Methylation, Mutation, Interaction, Pathway and Drug). In addition, manually curated literature references have also been provided to support the inclusion of the gene in MGDB and establish its association with melanoma. MGDB has a user-friendly web interface with multiple browse and search functions. We hoped MGDB will enrich our knowledge about melanoma genetics and serve as a useful complement to the existing public resources. Database URL: http://bioinfo.ahu.edu.cn:8080/Melanoma/index.jsp. © The Author(s) 2015. Published by Oxford University Press.

Mining functionally relevant gene sets for analyzing physiologically novel clinical expression data.

PubMed

Turcan, Sevin; Vetter, Douglas E; Maron, Jill L; Wei, Xintao; Slonim, Donna K

2011-01-01

Gene set analyses have become a standard approach for increasing the sensitivity of transcriptomic studies. However, analytical methods incorporating gene sets require the availability of pre-defined gene sets relevant to the underlying physiology being studied. For novel physiological problems, relevant gene sets may be unavailable or existing gene set databases may bias the results towards only the best-studied of the relevant biological processes. We describe a successful attempt to mine novel functional gene sets for translational projects where the underlying physiology is not necessarily well characterized in existing annotation databases. We choose targeted training data from public expression data repositories and define new criteria for selecting biclusters to serve as candidate gene sets. Many of the discovered gene sets show little or no enrichment for informative Gene Ontology terms or other functional annotation. However, we observe that such gene sets show coherent differential expression in new clinical test data sets, even if derived from different species, tissues, and disease states. We demonstrate the efficacy of this method on a human metabolic data set, where we discover novel, uncharacterized gene sets that are diagnostic of diabetes, and on additional data sets related to neuronal processes and human development. Our results suggest that our approach may be an efficient way to generate a collection of gene sets relevant to the analysis of data for novel clinical applications where existing functional annotation is relatively incomplete.

Identification of Biological Targets of Therapeutic Intervention for Hepatocellular Carcinoma by Integrated Bioinformatical Analysis.

PubMed

Hu, Wei Qi; Wang, Wei; Fang, Di Long; Yin, Xue Feng

2018-05-24

BACKGROUND We screened the potential molecular targets and investigated the molecular mechanisms of hepatocellular carcinoma (HCC). MATERIAL AND METHODS Microarray data of GSE47786, including the 40 μM berberine-treated HepG2 human hepatoma cell line and 0.08% DMSO-treated as control cells samples, was downloaded from the GEO database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed; the protein-protein interaction (PPI) networks were constructed using STRING database and Cytoscape; the genetic alteration, neighboring genes networks, and survival analysis of hub genes were explored by cBio portal; and the expression of mRNA level of hub genes was obtained from the Oncomine databases. RESULTS A total of 56 upregulated and 8 downregulated DEGs were identified. The GO analysis results were significantly enriched in cell-cycle arrest, regulation of transcription, DNA-dependent, protein amino acid phosphorylation, cell cycle, and apoptosis. The KEGG pathway analysis showed that DEGs were enriched in MAPK signaling pathway, ErbB signaling pathway, and p53 signaling pathway. JUN, EGR1, MYC, and CDKN1A were identified as hub genes in PPI networks. The genetic alteration of hub genes was mainly concentrated in amplification. TP53, NDRG1, and MAPK15 were found in neighboring genes networks. Altered genes had worse overall survival and disease-free survival than unaltered genes. The expressions of EGR1, MYC, and CDKN1A were significantly increased, but expression of JUN was not, in the Roessler Liver datasets. CONCLUSIONS We found that JUN, EGR1, MYC, and CDKN1A might be used as diagnostic and therapeutic molecular biomarkers and broaden our understanding of the molecular mechanisms of HCC.

Plant Reactome: a resource for plant pathways and comparative analysis

PubMed Central

Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D.; Wu, Guanming; Fabregat, Antonio; Elser, Justin L.; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D.; Ware, Doreen; Jaiswal, Pankaj

2017-01-01

Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. PMID:27799469

Sequence analysis of 497 mouse brain ESTs expressed in the substantia nigra

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

Stewart, G.J.; Savioz, A.; Davies, R.W.

1997-01-15

The use of subtracted, region-specific cDNA libraries combined with single-pass cDNA sequencing allows the discovery of novel genes and facilitates molecular description of the tissue or region involved. We report the sequence of 497 mouse expressed sequence tags (ESTs) from two subtracted libraries enriched for cDNAs expressed in the substantia nigra, a brain region with important roles in movement control and Parkinson disease. Of these, 238 ESTs give no database matches and therefore derive from novel genes. A further 115 ESTs show sequence similarity to ESTs from other organisms, which themselves do not yield any significant database matches to genesmore » of known function. Fifty-six ESTs show sequence similarity to previously identified genes whose mouse homologues have not been reported. The total number of ESTs reported that are new for the mouse is 407, which, together with the 90 ESTs corresponding to known mouse genes or cDNAs, contributes to the molecular description of the substantia nigra. 21 refs., 4 tabs.« less

On-the-fly selection of cell-specific enhancers, genes, miRNAs and proteins across the human body using SlideBase

PubMed Central

Ienasescu, Hans; Li, Kang; Andersson, Robin; Vitezic, Morana; Rennie, Sarah; Chen, Yun; Vitting-Seerup, Kristoffer; Lagoni, Emil; Boyd, Mette; Bornholdt, Jette; de Hoon, Michiel J. L.; Kawaji, Hideya; Lassmann, Timo; Hayashizaki, Yoshihide; Forrest, Alistair R. R.; Carninci, Piero; Sandelin, Albin

2016-01-01

Genomics consortia have produced large datasets profiling the expression of genes, micro-RNAs, enhancers and more across human tissues or cells. There is a need for intuitive tools to select subsets of such data that is the most relevant for specific studies. To this end, we present SlideBase, a web tool which offers a new way of selecting genes, promoters, enhancers and microRNAs that are preferentially expressed/used in a specified set of cells/tissues, based on the use of interactive sliders. With the help of sliders, SlideBase enables users to define custom expression thresholds for individual cell types/tissues, producing sets of genes, enhancers etc. which satisfy these constraints. Changes in slider settings result in simultaneous changes in the selected sets, updated in real time. SlideBase is linked to major databases from genomics consortia, including FANTOM, GTEx, The Human Protein Atlas and BioGPS. Database URL: http://slidebase.binf.ku.dk PMID:28025337

Gene expression pattern recognition algorithm inferences to classify samples exposed to chemical agents

NASA Astrophysics Data System (ADS)

Bushel, Pierre R.; Bennett, Lee; Hamadeh, Hisham; Green, James; Ableson, Alan; Misener, Steve; Paules, Richard; Afshari, Cynthia

2002-06-01

We present an analysis of pattern recognition procedures used to predict the classes of samples exposed to pharmacologic agents by comparing gene expression patterns from samples treated with two classes of compounds. Rat liver mRNA samples following exposure for 24 hours with phenobarbital or peroxisome proliferators were analyzed using a 1700 rat cDNA microarray platform. Sets of genes that were consistently differentially expressed in the rat liver samples following treatment were stored in the MicroArray Project System (MAPS) database. MAPS identified 238 genes in common that possessed a low probability (P < 0.01) of being randomly detected as differentially expressed at the 95% confidence level. Hierarchical cluster analysis on the 238 genes clustered specific gene expression profiles that separated samples based on exposure to a particular class of compound.

Conserved and divergent rhythms of crassulacean acid metabolism-related and core clock gene expression in the cactus Opuntia ficus-indica.

PubMed

Mallona, Izaskun; Egea-Cortines, Marcos; Weiss, Julia

2011-08-01

The cactus Opuntia ficus-indica is a constitutive Crassulacean acid metabolism (CAM) species. Current knowledge of CAM metabolism suggests that the enzyme phosphoenolpyruvate carboxylase kinase (PPCK) is circadian regulated at the transcriptional level, whereas phosphoenolpyruvate carboxylase (PEPC), malate dehydrogenase (MDH), NADP-malic enzyme (NADP-ME), and pyruvate phosphate dikinase (PPDK) are posttranslationally controlled. As little transcriptomic data are available from obligate CAM plants, we created an expressed sequence tag database derived from different organs and developmental stages. Sequences were assembled, compared with sequences in the National Center for Biotechnology Information nonredundant database for identification of putative orthologs, and mapped using Kyoto Encyclopedia of Genes and Genomes Orthology and Gene Ontology. We identified genes involved in circadian regulation and CAM metabolism for transcriptomic analysis in plants grown in long days. We identified stable reference genes for quantitative polymerase chain reaction and found that OfiSAND, like its counterpart in Arabidopsis (Arabidopsis thaliana), and OfiTUB are generally appropriate standards for use in the quantification of gene expression in O. ficus-indica. Three kinds of expression profiles were found: transcripts of OfiPPCK oscillated with a 24-h periodicity; transcripts of the light-active OfiNADP-ME and OfiPPDK genes adapted to 12-h cycles, while transcript accumulation patterns of OfiPEPC and OfiMDH were arrhythmic. Expression of the circadian clock gene OfiTOC1, similar to Arabidopsis, oscillated with a 24-h periodicity, peaking at night. Expression of OfiCCA1 and OfiPRR9, unlike in Arabidopsis, adapted best to a 12-h rhythm, suggesting that circadian clock gene interactions differ from those of Arabidopsis. Our results indicate that the evolution of CAM metabolism could be the result of modified circadian regulation at both the transcriptional and posttranscriptional levels.

Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database

PubMed Central

Drabkin, Harold J.; Blake, Judith A.

2012-01-01

The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as ‘GO’ or ‘homology’ or ‘phenotype’. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as ‘papers selected for GO that refer to genes with NO GO annotation’. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported with statements of evidence as well as access to source publications. PMID:23110975

Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database.

PubMed

Drabkin, Harold J; Blake, Judith A

2012-01-01

The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as 'GO' or 'homology' or 'phenotype'. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as 'papers selected for GO that refer to genes with NO GO annotation'. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported with statements of evidence as well as access to source publications.

Juvenile hormone and colony conditions differentially influence cytochrome P450 gene expression in the termite Reticulitermes flavipes.

PubMed

Zhou, X; Song, C; Grzymala, T L; Oi, F M; Scharf, M E

2006-12-01

In lower termites, the worker caste is a totipotent immature stage that is capable of differentiating into other adult caste phenotypes. We investigated the diversity of family 4 cytochrome P450 (CYP4) genes in Reticulitermes flavipes workers, with the specific goal of identifying P450s potentially involved in regulating caste differentiation. Seven novel CYP4 genes were identified. Quantitative real-time PCR revealed the tissue distribution of expression for the seven CYP4s, as well as temporal expression changes in workers in association with a release from colony influences and during juvenile hormone (JH)-induced soldier caste differentiation. Several fat-body-related CYP4 genes were differentially expressed after JH treatment. Still other genes changed expression in association with removal from colony influences, suggesting that primer pheromones and/or other colony influences impact their expression. These findings add to a growing database of candidate termite caste-regulatory genes, and provide explicit evidence that colony factors influence termite gene expression.

Epididymal genomics and the search for a male contraceptive.

PubMed

Turner, T T; Johnston, D S; Jelinsky, S A

2006-05-16

This report represents the joint efforts of three laboratories, one with a primary interest in understanding regulatory processes in the epididymal epithelium (TTT) and two with a primary interest in identifying and characterizing new contraceptive targets (DSJ and SAJ). We have developed a highly refined mouse epididymal transcriptome and have used it as a starting point for determining genes in the human epididymis, which may serve as targets for male contraceptives. Our database represents gene expression information for approximately 39,000 transcripts, of which over 17,000 are significantly expressed in at least one segment of the mouse epididymis. Over 2000 of these transcripts are up- or down-regulated by at least four-fold between at least two segments. In addition, human databases have been queried to determine expression of orthologs in the human epididymis and the specificity of their expression in the epididymis. Genes highly regulated in the human epididymis and showing high tissue specificity are potential targets for male contraceptives.

METscout: a pathfinder exploring the landscape of metabolites, enzymes and transporters.

PubMed

Geffers, Lars; Tetzlaff, Benjamin; Cui, Xiao; Yan, Jun; Eichele, Gregor

2013-01-01

METscout (http://metscout.mpg.de) brings together metabolism and gene expression landscapes. It is a MySQL relational database linking biochemical pathway information with 3D patterns of gene expression determined by robotic in situ hybridization in the E14.5 mouse embryo. The sites of expression of ∼1500 metabolic enzymes and of ∼350 solute carriers (SLCs) were included and are accessible as single cell resolution images and in the form of semi-quantitative image abstractions. METscout provides several graphical web-interfaces allowing navigation through complex anatomical and metabolic information. Specifically, the database shows where in the organism each of the many metabolic reactions take place and where SLCs transport metabolites. To link enzymatic reactions and transport, the KEGG metabolic reaction network was extended to include metabolite transport. This network in conjunction with spatial expression pattern of the network genes allows for a tracing of metabolic reactions and transport processes across the entire body of the embryo.

RNA-Seq Reveals Dynamic Changes of Gene Expression in Key Stages of Intestine Regeneration in the Sea Cucumber Apostichopus japonicas

PubMed Central

Sun, Lina; Yang, Hongsheng; Chen, Muyan; Ma, Deyou; Lin, Chenggang

2013-01-01

Background Sea cucumbers (Holothuroidea; Echinodermata) have the capacity to regenerate lost tissues and organs. Although the histological and cytological aspects of intestine regeneration have been extensively studied, little is known of the genetic mechanisms involved. There has, however, been a renewed effort to develop a database of Expressed Sequence Tags (ESTs) in Apostichopus japonicus, an economically-important species that occurs in China. This is important for studies on genetic breeding, molecular markers and special physiological phenomena. We have also constructed a library of ESTs obtained from the regenerative body wall and intestine of A. japonicus. The database has increased to ∼30000 ESTs. Results We used RNA-Seq to determine gene expression profiles associated with intestinal regeneration in A. japonicus at 3, 7, 14 and 21 days post evisceration (dpe). This was compared to profiles obtained from a normally-functioning intestine. Approximately 5 million (M) reads were sequenced in every library. Over 2400 up-regulated genes (>10%) and over 1000 down-regulated genes (∼5%) were observed at 3 and 7dpe (log2Ratio≥1, FDR≤0.001). Specific “Go terms” revealed that the DEGs (Differentially Expressed Genes) performed an important function at every regeneration stage. Besides some expected pathways (for example, Ribosome and Spliceosome pathway term), the “Notch signaling pathway,” the “ECM-receptor interaction” and the “Cytokine-cytokine receptor interaction” were significantly enriched. We also investigated the expression profiles of developmental genes, ECM-associated genes and Cytoskeletal genes. Twenty of the most important differentially expressed genes (DEGs) were verified by Real-time PCR, which resulted in a trend concordance of almost 100% between the two techniques. Conclusion Our studies demonstrated dynamic changes in global gene expression during intestine regeneration and presented a series of candidate genes and enriched pathways that contribute to intestine regeneration in sea cucumbers. This provides a foundation for future studies on the genetics/molecular mechanisms associated with intestine regeneration. PMID:23936330

GEOmetadb: powerful alternative search engine for the Gene Expression Omnibus

PubMed Central

Zhu, Yuelin; Davis, Sean; Stephens, Robert; Meltzer, Paul S.; Chen, Yidong

2008-01-01

The NCBI Gene Expression Omnibus (GEO) represents the largest public repository of microarray data. However, finding data in GEO can be challenging. We have developed GEOmetadb in an attempt to make querying the GEO metadata both easier and more powerful. All GEO metadata records as well as the relationships between them are parsed and stored in a local MySQL database. A powerful, flexible web search interface with several convenient utilities provides query capabilities not available via NCBI tools. In addition, a Bioconductor package, GEOmetadb that utilizes a SQLite export of the entire GEOmetadb database is also available, rendering the entire GEO database accessible with full power of SQL-based queries from within R. Availability: The web interface and SQLite databases available at http://gbnci.abcc.ncifcrf.gov/geo/. The Bioconductor package is available via the Bioconductor project. The corresponding MATLAB implementation is also available at the same website. Contact: yidong@mail.nih.gov PMID:18842599

Distinct profiles of expressed sequence tags during intestinal regeneration in the sea cucumber Holothuria glaberrima

PubMed Central

Rojas-Cartagena, Carmencita; Ortíz-Pineda, Pablo; Ramírez-Gómez, Francisco; Suárez-Castillo, Edna C.; Matos-Cruz, Vanessa; Rodríguez, Carlos; Ortíz-Zuazaga, Humberto; García-Arrarás, José E.

2010-01-01

Repair and regeneration are key processes for tissue maintenance, and their disruption may lead to disease states. Little is known about the molecular mechanisms that underline the repair and regeneration of the digestive tract. The sea cucumber Holothuria glaberrima represents an excellent model to dissect and characterize the molecular events during intestinal regeneration. To study the gene expression profile, cDNA libraries were constructed from normal, 3-day, and 7-day regenerating intestines of H. glaberrima. Clones were randomly sequenced and queried against the nonredundant protein database at the National Center for Biotechnology Information. RT-PCR analyses were made of several genes to determine their expression profile during intestinal regeneration. A total of 5,173 sequences from three cDNA libraries were obtained. About 46.2, 35.6, and 26.2% of the sequences for the normal, 3-days, and 7-days cDNA libraries, respectively, shared significant similarity with known sequences in the protein database of GenBank but only present 10% of similarity among them. Analysis of the libraries in terms of functional processes, protein domains, and most common sequences suggests that a differential expression profile is taking place during the regeneration process. Further examination of the expressed sequence tag dataset revealed that 12 putative genes are differentially expressed at significant level (R > 6). Experimental validation by RT-PCR analysis reveals that at least three genes (unknown C-4677-1, melanotransferrin, and centaurin) present a differential expression during regeneration. These findings strongly suggest that the gene expression profile varies among regeneration stages and provide evidence for the existence of differential gene expression. PMID:17579180

ANISEED 2017: extending the integrated ascidian database to the exploration and evolutionary comparison of genome-scale datasets.

PubMed

Brozovic, Matija; Dantec, Christelle; Dardaillon, Justine; Dauga, Delphine; Faure, Emmanuel; Gineste, Mathieu; Louis, Alexandra; Naville, Magali; Nitta, Kazuhiro R; Piette, Jacques; Reeves, Wendy; Scornavacca, Céline; Simion, Paul; Vincentelli, Renaud; Bellec, Maelle; Aicha, Sameh Ben; Fagotto, Marie; Guéroult-Bellone, Marion; Haeussler, Maximilian; Jacox, Edwin; Lowe, Elijah K; Mendez, Mickael; Roberge, Alexis; Stolfi, Alberto; Yokomori, Rui; Brown, C Titus; Cambillau, Christian; Christiaen, Lionel; Delsuc, Frédéric; Douzery, Emmanuel; Dumollard, Rémi; Kusakabe, Takehiro; Nakai, Kenta; Nishida, Hiroki; Satou, Yutaka; Swalla, Billie; Veeman, Michael; Volff, Jean-Nicolas; Lemaire, Patrick

2018-01-04

ANISEED (www.aniseed.cnrs.fr) is the main model organism database for tunicates, the sister-group of vertebrates. This release gives access to annotated genomes, gene expression patterns, and anatomical descriptions for nine ascidian species. It provides increased integration with external molecular and taxonomy databases, better support for epigenomics datasets, in particular RNA-seq, ChIP-seq and SELEX-seq, and features novel interactive interfaces for existing and novel datatypes. In particular, the cross-species navigation and comparison is enhanced through a novel taxonomy section describing each represented species and through the implementation of interactive phylogenetic gene trees for 60% of tunicate genes. The gene expression section displays the results of RNA-seq experiments for the three major model species of solitary ascidians. Gene expression is controlled by the binding of transcription factors to cis-regulatory sequences. A high-resolution description of the DNA-binding specificity for 131 Ciona robusta (formerly C. intestinalis type A) transcription factors by SELEX-seq is provided and used to map candidate binding sites across the Ciona robusta and Phallusia mammillata genomes. Finally, use of a WashU Epigenome browser enhances genome navigation, while a Genomicus server was set up to explore microsynteny relationships within tunicates and with vertebrates, Amphioxus, echinoderms and hemichordates. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

ARMOUR - A Rice miRNA: mRNA Interaction Resource.

PubMed

Sanan-Mishra, Neeti; Tripathi, Anita; Goswami, Kavita; Shukla, Rohit N; Vasudevan, Madavan; Goswami, Hitesh

2018-01-01

ARMOUR was developed as A Rice miRNA:mRNA interaction resource. This informative and interactive database includes the experimentally validated expression profiles of miRNAs under different developmental and abiotic stress conditions across seven Indian rice cultivars. This comprehensive database covers 689 known and 1664 predicted novel miRNAs and their expression profiles in more than 38 different tissues or conditions along with their predicted/known target transcripts. The understanding of miRNA:mRNA interactome in regulation of functional cellular machinery is supported by the sequence information of the mature and hairpin structures. ARMOUR provides flexibility to users in querying the database using multiple ways like known gene identifiers, gene ontology identifiers, KEGG identifiers and also allows on the fly fold change analysis and sequence search query with inbuilt BLAST algorithm. ARMOUR database provides a cohesive platform for novel and mature miRNAs and their expression in different experimental conditions and allows searching for their interacting mRNA targets, GO annotation and their involvement in various biological pathways. The ARMOUR database includes a provision for adding more experimental data from users, with an aim to develop it as a platform for sharing and comparing experimental data contributed by research groups working on rice.

Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping.

PubMed

Chang, Meiping; Smith, Sarah; Thorpe, Andrew; Barratt, Michael J; Karim, Farzana

2010-09-16

We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.

Adaptation of video game UVW mapping to 3D visualization of gene expression patterns

NASA Astrophysics Data System (ADS)

Vize, Peter D.; Gerth, Victor E.

2007-01-01

Analysis of gene expression patterns within an organism plays a critical role in associating genes with biological processes in both health and disease. During embryonic development the analysis and comparison of different gene expression patterns allows biologists to identify candidate genes that may regulate the formation of normal tissues and organs and to search for genes associated with congenital diseases. No two individual embryos, or organs, are exactly the same shape or size so comparing spatial gene expression in one embryo to that in another is difficult. We will present our efforts in comparing gene expression data collected using both volumetric and projection approaches. Volumetric data is highly accurate but difficult to process and compare. Projection methods use UV mapping to align texture maps to standardized spatial frameworks. This approach is less accurate but is very rapid and requires very little processing. We have built a database of over 180 3D models depicting gene expression patterns mapped onto the surface of spline based embryo models. Gene expression data in different models can easily be compared to determine common regions of activity. Visualization software, both Java and OpenGL optimized for viewing 3D gene expression data will also be demonstrated.

Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer

PubMed Central

Makondi, Precious Takondwa; Lee, Chia-Hwa; Huang, Chien-Yu; Chu, Chi-Ming; Chang, Yu-Jia

2018-01-01

Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC) therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). Protein–protein interaction (PPI) networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING) and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs); the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A), toll-like receptor 4 (TLR4), CD19 molecule (CD19), breast cancer 1, early onset (BRCA1), platelet-derived growth factor subunit A (PDGFA), and matrix metallopeptidase 1 (MMP1) were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4) revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS). The identified genes and pathways can be potential targets and predictors of therapeutic resistance and prognosis in bevacizumab-treated patients with mCRC. PMID:29342159

Eukaryotic and prokaryotic promoter databases as valuable tools in exploring the regulation of gene transcription: a comprehensive overview.

PubMed

Majewska, Małgorzata; Wysokińska, Halina; Kuźma, Łukasz; Szymczyk, Piotr

2018-02-20

The complete exploration of the regulation of gene expression remains one of the top-priority goals for researchers. As the regulation is mainly controlled at the level of transcription by promoters, study on promoters and findings are of great importance. This review summarizes forty selected databases that centralize experimental and theoretical knowledge regarding the organization of promoters, interacting transcription factors (TFs) and microRNAs (miRNAs) in many eukaryotic and prokaryotic species. The presented databases offer researchers valuable support in elucidating the regulation of gene transcription. Copyright © 2017 Elsevier B.V. All rights reserved.

Transcriptome-wide selection of a reliable set of reference genes for gene expression studies in potato cyst nematodes (Globodera spp.).

PubMed

Sabeh, Michael; Duceppe, Marc-Olivier; St-Arnaud, Marc; Mimee, Benjamin

2018-01-01

Relative gene expression analyses by qRT-PCR (quantitative reverse transcription PCR) require an internal control to normalize the expression data of genes of interest and eliminate the unwanted variation introduced by sample preparation. A perfect reference gene should have a constant expression level under all the experimental conditions. However, the same few housekeeping genes selected from the literature or successfully used in previous unrelated experiments are often routinely used in new conditions without proper validation of their stability across treatments. The advent of RNA-Seq and the availability of public datasets for numerous organisms are opening the way to finding better reference genes for expression studies. Globodera rostochiensis is a plant-parasitic nematode that is particularly yield-limiting for potato. The aim of our study was to identify a reliable set of reference genes to study G. rostochiensis gene expression. Gene expression levels from an RNA-Seq database were used to identify putative reference genes and were validated with qRT-PCR analysis. Three genes, GR, PMP-3, and aaRS, were found to be very stable within the experimental conditions of this study and are proposed as reference genes for future work.

Entamoeba histolytica: construction and applications of subgenomic databases.

PubMed

Hofer, Margit; Duchêne, Michael

2005-07-01

Knowledge about the influence of environmental stress such as the action of chemotherapeutic agents on gene expression in Entamoeba histolytica is limited. We plan to use oligonucleotide microarray hybridization to approach these questions. As the basis for our array, sequence data from the genome project carried out by the Institute for Genomic Research (TIGR) and the Sanger Institute were used to annotate parts of the parasite genome. Three subgenomic databases containing enzymes, cytoskeleton genes, and stress genes were compiled with the help of the ExPASy proteomics website and the BLAST servers at the two genome project sites. The known sequences from reference species, mostly human and Escherichia coli, were searched against TIGR and Sanger E. histolytica sequence contigs and the homologs were copied into a Microsoft Access database. In a similar way, two additional databases of cytoskeletal genes and stress genes were generated. Metabolic pathways could be assembled from our enzyme database, but sometimes they were incomplete as is the case for the sterol biosynthesis pathway. The raw databases contained a significant number of duplicate entries which were merged to obtain curated non-redundant databases. This procedure revealed that some E. histolytica genes may have several putative functions. Representative examples such as the case of the delta-aminolevulinate synthase/serine palmitoyltransferase are discussed.

Identification of differentially expressed genes in the zebrafish hypothalamus - pituitary axis

PubMed Central

Toro, Sabrina; Wegner, Jeremy; Muller, Marc; Westerfield, Monte; Varga, Zoltan M.

2009-01-01

The vertebrate hypothalamic-pituitary axis (HP) is the main link between the central nervous system and endocrine system. Although several signal pathways and regulatory genes have been implicated in adenohypophysis ontogenesis, little is known about hypothalamic and neurohypophysial development or when the HP matures and becomes functional. To identify markers of the HP, we constructed subtractive cDNA libraries between adult zebrafish hypothalamus and pituitary. We identified previously published genes and ESTs and novel zebrafish genes, some of which were predicted by genomic database analysis. We also analyzed expression patterns of these genes and found that several are expressed in the embryonic and larval hypothalamus, neurohypophysis, and/or adenohypophysis. Expression at these stages makes these genes useful markers to study HP maturation and function. PMID:19166982

NCBI GEO: archive for functional genomics data sets—10 years on

PubMed Central

Barrett, Tanya; Troup, Dennis B.; Wilhite, Stephen E.; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F.; Tomashevsky, Maxim; Marshall, Kimberly A.; Phillippy, Katherine H.; Sherman, Patti M.; Muertter, Rolf N.; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20 000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/. PMID:21097893

Construction of Pará rubber tree genome and multi-transcriptome database accelerates rubber researches.

PubMed

Makita, Yuko; Kawashima, Mika; Lau, Nyok Sean; Othman, Ahmad Sofiman; Matsui, Minami

2018-01-19

Natural rubber is an economically important material. Currently the Pará rubber tree, Hevea brasiliensis is the main commercial source. Little is known about rubber biosynthesis at the molecular level. Next-generation sequencing (NGS) technologies brought draft genomes of three rubber cultivars and a variety of RNA sequencing (RNA-seq) data. However, no current genome or transcriptome databases (DB) are organized by gene. A gene-oriented database is a valuable support for rubber research. Based on our original draft genome sequence of H. brasiliensis RRIM600, we constructed a rubber tree genome and transcriptome DB. Our DB provides genome information including gene functional annotations and multi-transcriptome data of RNA-seq, full-length cDNAs including PacBio Isoform sequencing (Iso-Seq), ESTs and genome wide transcription start sites (TSSs) derived from CAGE technology. Using our original and publically available RNA-seq data, we calculated co-expressed genes for identifying functionally related gene sets and/or genes regulated by the same transcription factor (TF). Users can access multi-transcriptome data through both a gene-oriented web page and a genome browser. For the gene searching system, we provide keyword search, sequence homology search and gene expression search; users can also select their expression threshold easily. The rubber genome and transcriptome DB provides rubber tree genome sequence and multi-transcriptomics data. This DB is useful for comprehensive understanding of the rubber transcriptome. This will assist both industrial and academic researchers for rubber and economically important close relatives such as R. communis, M. esculenta and J. curcas. The Rubber Transcriptome DB release 2017.03 is accessible at http://matsui-lab.riken.jp/rubber/ .

Revealing the potential pathogenesis of glioma by utilizing a glioma associated protein-protein interaction network.

PubMed

Pan, Weiran; Li, Gang; Yang, Xiaoxiao; Miao, Jinming

2015-04-01

This study aims to explore the potential mechanism of glioma through bioinformatic approaches. The gene expression profile (GSE4290) of glioma tumor and non-tumor samples was downloaded from Gene Expression Omnibus database. A total of 180 samples were available, including 23 non-tumor and 157 tumor samples. Then the raw data were preprocessed using robust multiarray analysis, and 8,890 differentially expressed genes (DEGs) were identified by using t-test (false discovery rate < 0.0005). Furthermore, 16 known glioma related genes were abstracted from Genetic Association Database. After mapping 8,890 DEGs and 16 known glioma related genes to Human Protein Reference Database, a glioma associated protein-protein interaction network (GAPN) was constructed. In addition, 51 sub-networks in GAPN were screened out through Molecular Complex Detection (score ≥ 1), and sub-network 1 was found to have the closest interaction (score = 3). What' more, for the top 10 sub-networks, Gene Ontology (GO) enrichment analysis (p value < 0.05) was performed, and DEGs involved in sub-network 1 and 2, such as BRMS1L and CCNA1, were predicted to regulate cell growth, cell cycle, and DNA replication via interacting with known glioma related genes. Finally, the overlaps of DEGs and human essential, housekeeping, tissue-specific genes were calculated (p value = 1.0, 1.0, and 0.00014, respectively) and visualized by Venn Diagram package in R. About 61% of human tissue-specific genes were DEGs as well. This research shed new light on the pathogenesis of glioma based on DEGs and GAPN, and our findings might provide potential targets for clinical glioma treatment.

Key genes and pathways in measles and their interaction with environmental chemicals.

PubMed

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-06-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles.

Gene: a gene-centered information resource at NCBI.

PubMed

Brown, Garth R; Hem, Vichet; Katz, Kenneth S; Ovetsky, Michael; Wallin, Craig; Ermolaeva, Olga; Tolstoy, Igor; Tatusova, Tatiana; Pruitt, Kim D; Maglott, Donna R; Murphy, Terence D

2015-01-01

The National Center for Biotechnology Information's (NCBI) Gene database (www.ncbi.nlm.nih.gov/gene) integrates gene-specific information from multiple data sources. NCBI Reference Sequence (RefSeq) genomes for viruses, prokaryotes and eukaryotes are the primary foundation for Gene records in that they form the critical association between sequence and a tracked gene upon which additional functional and descriptive content is anchored. Additional content is integrated based on the genomic location and RefSeq transcript and protein sequence data. The content of a Gene record represents the integration of curation and automated processing from RefSeq, collaborating model organism databases, consortia such as Gene Ontology, and other databases within NCBI. Records in Gene are assigned unique, tracked integers as identifiers. The content (citations, nomenclature, genomic location, gene products and their attributes, phenotypes, sequences, interactions, variation details, maps, expression, homologs, protein domains and external databases) is available via interactive browsing through NCBI's Entrez system, via NCBI's Entrez programming utilities (E-Utilities and Entrez Direct) and for bulk transfer by FTP. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

PubMed

Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

Candidate gene database and transcript map for peach, a model species for fruit trees.

PubMed

Horn, Renate; Lecouls, Anne-Claire; Callahan, Ann; Dandekar, Abhaya; Garay, Lilibeth; McCord, Per; Howad, Werner; Chan, Helen; Verde, Ignazio; Main, Doreen; Jung, Sook; Georgi, Laura; Forrest, Sam; Mook, Jennifer; Zhebentyayeva, Tatyana; Yu, Yeisoo; Kim, Hye Ran; Jesudurai, Christopher; Sosinski, Bryon; Arús, Pere; Baird, Vance; Parfitt, Dan; Reighard, Gregory; Scorza, Ralph; Tomkins, Jeffrey; Wing, Rod; Abbott, Albert Glenn

2005-05-01

Peach (Prunus persica) is a model species for the Rosaceae, which includes a number of economically important fruit tree species. To develop an extensive Prunus expressed sequence tag (EST) database for identifying and cloning the genes important to fruit and tree development, we generated 9,984 high-quality ESTs from a peach cDNA library of developing fruit mesocarp. After assembly and annotation, a putative peach unigene set consisting of 3,842 ESTs was defined. Gene ontology (GO) classification was assigned based on the annotation of the single "best hit" match against the Swiss-Prot database. No significant homology could be found in the GenBank nr databases for 24.3% of the sequences. Using core markers from the general Prunus genetic map, we anchored bacterial artificial chromosome (BAC) clones on the genetic map, thereby providing a framework for the construction of a physical and transcript map. A transcript map was developed by hybridizing 1,236 ESTs from the putative peach unigene set and an additional 68 peach cDNA clones against the peach BAC library. Hybridizing ESTs to genetically anchored BACs immediately localized 11.2% of the ESTs on the genetic map. ESTs showed a clustering of expressed genes in defined regions of the linkage groups. [The data were built into a regularly updated Genome Database for Rosaceae (GDR), available at (http://www.genome.clemson.edu/gdr/).].

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

PubMed Central

Baumbach, Jan

2007-01-01

Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression) and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user) can be analyzed in the context of known transcriptional regulatory networks to predict putative contradictions or further gene regulatory interactions. Furthermore, it integrates protein clusters by means of heuristically solving the weighted graph cluster editing problem. In addition, it provides Web Service based access to up to date gene annotation data from GenDB. Conclusion The release 4.0 of CoryneRegNet is a comprehensive system for the integrated analysis of procaryotic gene regulatory networks. It is a versatile systems biology platform to support the efficient and large-scale analysis of transcriptional regulation of gene expression in microorganisms. It is publicly available at . PMID:17986320

CCDB: a curated database of genes involved in cervix cancer.

PubMed

Agarwal, Subhash M; Raghav, Dhwani; Singh, Harinder; Raghava, G P S

2011-01-01

The Cervical Cancer gene DataBase (CCDB, http://crdd.osdd.net/raghava/ccdb) is a manually curated catalog of experimentally validated genes that are thought, or are known to be involved in the different stages of cervical carcinogenesis. In spite of the large women population that is presently affected from this malignancy still at present, no database exists that catalogs information on genes associated with cervical cancer. Therefore, we have compiled 537 genes in CCDB that are linked with cervical cancer causation processes such as methylation, gene amplification, mutation, polymorphism and change in expression level, as evident from published literature. Each record contains details related to gene like architecture (exon-intron structure), location, function, sequences (mRNA/CDS/protein), ontology, interacting partners, homology to other eukaryotic genomes, structure and links to other public databases, thus augmenting CCDB with external data. Also, manually curated literature references have been provided to support the inclusion of the gene in the database and establish its association with cervix cancer. In addition, CCDB provides information on microRNA altered in cervical cancer as well as search facility for querying, several browse options and an online tool for sequence similarity search, thereby providing researchers with easy access to the latest information on genes involved in cervix cancer.

SAMMD: Staphylococcus aureus microarray meta-database.

PubMed

Nagarajan, Vijayaraj; Elasri, Mohamed O

2007-10-02

Staphylococcus aureus is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. S. aureus is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of S. aureus, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of S. aureus and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation system to comprehensively examine them. We report the development of the Staphylococcus aureus Microarray meta-database (SAMMD) which includes data from all the published transcriptional profiles. SAMMD is a web-accessible database that helps users to perform a variety of analysis against and within the existing transcriptional profiles. SAMMD is a relational database that uses MySQL as the back end and PHP/JavaScript/DHTML as the front end. The database is normalized and consists of five tables, which holds information about gene annotations, regulated gene lists, experimental details, references, and other details. SAMMD data is collected from the peer-reviewed published articles. Data extraction and conversion was done using perl scripts while data entry was done through phpMyAdmin tool. The database is accessible via a web interface that contains several features such as a simple search by ORF ID, gene name, gene product name, advanced search using gene lists, comparing among datasets, browsing, downloading, statistics, and help. The database is licensed under General Public License (GPL). SAMMD is hosted and available at http://www.bioinformatics.org/sammd/. Currently there are over 9500 entries for regulated genes, from 67 microarray experiments. SAMMD will help staphylococcal scientists to analyze their expression data and understand it at global level. It will also allow scientists to compare and contrast their transcriptome to that of the other published transcriptomes.

SAMMD: Staphylococcus aureus Microarray Meta-Database

PubMed Central

Nagarajan, Vijayaraj; Elasri, Mohamed O

2007-01-01

Background Staphylococcus aureus is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. S. aureus is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of S. aureus, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of S. aureus and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation system to comprehensively examine them. We report the development of the Staphylococcus aureus Microarray meta-database (SAMMD) which includes data from all the published transcriptional profiles. SAMMD is a web-accessible database that helps users to perform a variety of analysis against and within the existing transcriptional profiles. Description SAMMD is a relational database that uses MySQL as the back end and PHP/JavaScript/DHTML as the front end. The database is normalized and consists of five tables, which holds information about gene annotations, regulated gene lists, experimental details, references, and other details. SAMMD data is collected from the peer-reviewed published articles. Data extraction and conversion was done using perl scripts while data entry was done through phpMyAdmin tool. The database is accessible via a web interface that contains several features such as a simple search by ORF ID, gene name, gene product name, advanced search using gene lists, comparing among datasets, browsing, downloading, statistics, and help. The database is licensed under General Public License (GPL). Conclusion SAMMD is hosted and available at . Currently there are over 9500 entries for regulated genes, from 67 microarray experiments. SAMMD will help staphylococcal scientists to analyze their expression data and understand it at global level. It will also allow scientists to compare and contrast their transcriptome to that of the other published transcriptomes. PMID:17910768

Transcriptome analysis in Coffea eugenioides, an Arabica coffee ancestor, reveals differentially expressed genes in leaves and fruits.

PubMed

Yuyama, Priscila Mary; Reis Júnior, Osvaldo; Ivamoto, Suzana Tiemi; Domingues, Douglas Silva; Carazzolle, Marcelo Falsarella; Pereira, Gonçalo Amarante Guimarães; Charmetant, Pierre; Leroy, Thierry; Pereira, Luiz Filipe Protasio

2016-02-01

Studies in diploid parental species of polyploid plants are important to understand their contributions to the formation of plant and species evolution. Coffea eugenioides is a diploid species that is considered to be an ancestor of allopolyploid Coffea arabica together with Coffea canephora. Despite its importance in the evolutionary history of the main economic species of coffee, no study has focused on C. eugenioides molecular genetics. RNA-seq creates the possibility to generate reference transcriptomes and identify coding genes and potential candidates related to important agronomic traits. Therefore, the main objectives were to obtain a global overview of transcriptionally active genes in this species using next-generation sequencing and to analyze specific genes that were highly expressed in leaves and fruits with potential exploratory characteristics for breeding and understanding the evolutionary biology of coffee. A de novo assembly generated 36,935 contigs that were annotated using eight databases. We observed a total of ~5000 differentially expressed genes between leaves and fruits. Several genes exclusively expressed in fruits did not exhibit similarities with sequences in any database. We selected ten differentially expressed unigenes in leaves and fruits to evaluate transcriptional profiles using qPCR. Our study provides the first gene catalog for C. eugenioides and enhances the knowledge concerning the mechanisms involved in the C. arabica homeologous. Furthermore, this work will open new avenues for studies into specific genes and pathways in this species, especially related to fruit, and our data have potential value in assisted breeding applications.

Differential expression of the Nrf2-linked genes in pediatric septic shock.

PubMed

Grunwell, Jocelyn R; Weiss, Scott L; Cvijanovich, Natalie Z; Allen, Geoffrey L; Thomas, Neal J; Freishtat, Robert J; Anas, Nick; Meyer, Keith; Checchia, Paul A; Shanley, Thomas P; Bigham, Michael T; Fitzgerald, Julie; Howard, Kelli; Frank, Erin; Harmon, Kelli; Wong, Hector R

2015-09-17

Experimental data from animal models of sepsis support a role for a transcription factor, nuclear erythroid-related factor 2 p45-related factor 2 (Nrf2), as a master regulator of antioxidant and detoxifying genes and intermediary metabolism during stress. Prior analysis of a pediatric septic shock transcriptomic database showed that the Nrf2 response is a top 5 upregulated signaling pathway in early pediatric septic shock. We conducted a focused analysis of 267 Nrf2-linked genes using a multicenter, genome-wide expression database of 180 children with septic shock 10 years of age or younger and 53 healthy controls. The analysis involved RNA isolated from whole blood within 24 h of pediatric intensive care unit admission for septic shock and a false discovery rate of 5 %. We compared differentially expressed genes from (1) patients with septic shock and healthy controls and (2) across validated gene expression-based subclasses of pediatric septic shock (endotypes A and B) using several bioinformatic methods. We found upregulation of 123 Nrf2-linked genes in children with septic shock. The top gene network represented by these genes contained primarily enzymes with oxidoreductase activity involved in cellular lipid metabolism that were highly connected to the peroxisome proliferator activated receptor and the retinoic acid receptor families. Endotype A, which had higher organ failure burden and mortality, exhibited a greater downregulation of Nrf2-linked genes than endotype B, with 92 genes differentially regulated between endotypes. Our findings indicate that Nrf2-linked genes may contribute to alterations in oxidative signaling and intermediary metabolism in pediatric septic shock.

A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells.

PubMed

Ly, Tony; Ahmad, Yasmeen; Shlien, Adam; Soroka, Dominique; Mills, Allie; Emanuele, Michael J; Stratton, Michael R; Lamond, Angus I

2014-01-01

Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re-evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry-based proteomics and RNA-Seq, avoiding artificial synchronization procedures. We identify myeloid-specific gene expression and variations in protein abundance, isoform expression and phosphorylation at different cell cycle stages. We dissect the relationship between protein and mRNA levels for both bulk gene expression and for over ∼6000 genes individually across the cell cycle, revealing complex, gene-specific patterns. This data set, one of the deepest surveys to date of gene expression in human cells, is presented in an online, searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/). DOI: http://dx.doi.org/10.7554/eLife.01630.001.

A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells

PubMed Central

Ly, Tony; Ahmad, Yasmeen; Shlien, Adam; Soroka, Dominique; Mills, Allie; Emanuele, Michael J; Stratton, Michael R; Lamond, Angus I

2014-01-01

Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re-evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry-based proteomics and RNA-Seq, avoiding artificial synchronization procedures. We identify myeloid-specific gene expression and variations in protein abundance, isoform expression and phosphorylation at different cell cycle stages. We dissect the relationship between protein and mRNA levels for both bulk gene expression and for over ∼6000 genes individually across the cell cycle, revealing complex, gene-specific patterns. This data set, one of the deepest surveys to date of gene expression in human cells, is presented in an online, searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/). DOI: http://dx.doi.org/10.7554/eLife.01630.001 PMID:24596151

Integrated genome-wide Alu methylation and transcriptome profiling analyses reveal novel epigenetic regulatory networks associated with autism spectrum disorder.

PubMed

Saeliw, Thanit; Tangsuwansri, Chayanin; Thongkorn, Surangrat; Chonchaiya, Weerasak; Suphapeetiporn, Kanya; Mutirangura, Apiwat; Tencomnao, Tewin; Hu, Valerie W; Sarachana, Tewarit

2018-01-01

Alu elements are a group of repetitive elements that can influence gene expression through CpG residues and transcription factor binding. Altered gene expression and methylation profiles have been reported in various tissues and cell lines from individuals with autism spectrum disorder (ASD). However, the role of Alu elements in ASD remains unclear. We thus investigated whether Alu elements are associated with altered gene expression profiles in ASD. We obtained five blood-based gene expression profiles from the Gene Expression Omnibus database and human Alu-inserted gene lists from the TranspoGene database. Differentially expressed genes (DEGs) in ASD were identified from each study and overlapped with the human Alu-inserted genes. The biological functions and networks of Alu-inserted DEGs were then predicted by Ingenuity Pathway Analysis (IPA). A combined bisulfite restriction analysis of lymphoblastoid cell lines (LCLs) derived from 36 ASD and 20 sex- and age-matched unaffected individuals was performed to assess the global DNA methylation levels within Alu elements, and the Alu expression levels were determined by quantitative RT-PCR. In ASD blood or blood-derived cells, 320 Alu-inserted genes were reproducibly differentially expressed. Biological function and pathway analysis showed that these genes were significantly associated with neurodevelopmental disorders and neurological functions involved in ASD etiology. Interestingly, estrogen receptor and androgen signaling pathways implicated in the sex bias of ASD, as well as IL-6 signaling and neuroinflammation signaling pathways, were also highlighted. Alu methylation was not significantly different between the ASD and sex- and age-matched control groups. However, significantly altered Alu methylation patterns were observed in ASD cases sub-grouped based on Autism Diagnostic Interview-Revised scores compared with matched controls. Quantitative RT-PCR analysis of Alu expression also showed significant differences between ASD subgroups. Interestingly, Alu expression was correlated with methylation status in one phenotypic ASD subgroup. Alu methylation and expression were altered in LCLs from ASD subgroups. Our findings highlight the association of Alu elements with gene dysregulation in ASD blood samples and warrant further investigation. Moreover, the classification of ASD individuals into subgroups based on phenotypes may be beneficial and could provide insights into the still unknown etiology and the underlying mechanisms of ASD.

Identification of repaglinide as a therapeutic drug for glioblastoma multiforme

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

Xiao, Zui Xuan; Chen, Ruo Qiao; Hu, Dian Xing

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with a median survival time of only 14 months after treatment. It is urgent to find new therapeutic drugs that increase survival time of GBM patients. To achieve this goal, we screened differentially expressed genes between long-term and short-term survived GBM patients from Gene Expression Omnibus database and found gene expression signature for the long-term survived GBM patients. The signaling networks of all those differentially expressed genes converged to protein binding, extracellular matrix and tissue development as revealed in BiNGO and Cytoscape. Drug repositioning in Connectivity Map by using the genemore » expression signature identified repaglinide, a first-line drug for diabetes mellitus, as the most promising novel drug for GBM. In vitro experiments demonstrated that repaglinide significantly inhibited the proliferation and migration of human GBM cells. In vivo experiments demonstrated that repaglinide prominently prolonged the median survival time of mice bearing orthotopic glioma. Mechanistically, repaglinide significantly reduced Bcl-2, Beclin-1 and PD-L1 expression in glioma tissues, indicating that repaglinide may exert its anti-cancer effects via apoptotic, autophagic and immune checkpoint signaling. Taken together, repaglinide is likely to be an effective drug to prolong life span of GBM patients. - Highlights: • Gene expression signarue in long-term survived GBM patients are identified from Gene Expression Omnibus database. • Repaglinide is identified as a survival-related drug for GBM via drug repositioning in CMap. • Repaglinide effectively kills GBM cells, inhibits GBM cell migration and increases survival of mice bearing orthotopic glioma. • Repaglinide reduces Bcl-2, Beclin-1 and PD-L1 in GBM tissues.« less

Differential co-expression analysis of rheumatoid arthritis with microarray data.

PubMed

Wang, Kunpeng; Zhao, Liqiang; Liu, Xuefeng; Hao, Zhenyong; Zhou, Yong; Yang, Chuandong; Li, Hongqiang

2014-11-01

The aim of the present study was to investigate the underlying molecular mechanisms of rheumatoid arthritis (RA) using microarray expression profiles from osteoarthritis and RA patients, to improve diagnosis and treatment strategies for the condition. The gene expression profile of GSE27390 was downloaded from Gene Expression Omnibus, including 19 samples from patients with RA (n=9) or osteoarthritis (n=10). Firstly, the differentially expressed genes (DEGs) were obtained with the thresholds of |logFC|>1.0 and P<0.05, using the t‑test method in LIMMA package. Then, differentially co-expressed genes (DCGs) and differentially co-expressed links (DCLs) were screened with q<0.25 by the differential coexpression analysis and differential regulation analysis of gene expression microarray data package. Secondly, pathway enrichment analysis for DCGs was performed by the Database for Annotation, Visualization and Integrated Discovery and the DCLs associated with RA were selected by comparing the obtained DCLs with known transcription factor (TF)-targets in the TRANSFAC database. Finally, the obtained TFs were mapped to the known TF-targets to construct the network using cytoscape software. A total of 1755 DEGs, 457 DCGs and 101988 DCLs were achieved and there were 20 TFs in the obtained six TF-target relations (STAT3-TNF, PBX1‑PLAU, SOCS3-STAT3, GATA1-ETS2, ETS1-ICAM4 and CEBPE‑GATA1) and 457 DCGs. A number of TF-target relations in the constructed network were not within DCLs when the TF and target gene were DCGs. The identified TFs may have an important role in the pathogenesis of RA and have the potential to be used as biomarkers for the development of novel diagnostic and therapeutic strategies for RA.

RefEx, a reference gene expression dataset as a web tool for the functional analysis of genes.

PubMed

Ono, Hiromasa; Ogasawara, Osamu; Okubo, Kosaku; Bono, Hidemasa

2017-08-29

Gene expression data are exponentially accumulating; thus, the functional annotation of such sequence data from metadata is urgently required. However, life scientists have difficulty utilizing the available data due to its sheer magnitude and complicated access. We have developed a web tool for browsing reference gene expression pattern of mammalian tissues and cell lines measured using different methods, which should facilitate the reuse of the precious data archived in several public databases. The web tool is called Reference Expression dataset (RefEx), and RefEx allows users to search by the gene name, various types of IDs, chromosomal regions in genetic maps, gene family based on InterPro, gene expression patterns, or biological categories based on Gene Ontology. RefEx also provides information about genes with tissue-specific expression, and the relative gene expression values are shown as choropleth maps on 3D human body images from BodyParts3D. Combined with the newly incorporated Functional Annotation of Mammals (FANTOM) dataset, RefEx provides insight regarding the functional interpretation of unfamiliar genes. RefEx is publicly available at http://refex.dbcls.jp/.

RefEx, a reference gene expression dataset as a web tool for the functional analysis of genes

PubMed Central

Ono, Hiromasa; Ogasawara, Osamu; Okubo, Kosaku; Bono, Hidemasa

2017-01-01

Gene expression data are exponentially accumulating; thus, the functional annotation of such sequence data from metadata is urgently required. However, life scientists have difficulty utilizing the available data due to its sheer magnitude and complicated access. We have developed a web tool for browsing reference gene expression pattern of mammalian tissues and cell lines measured using different methods, which should facilitate the reuse of the precious data archived in several public databases. The web tool is called Reference Expression dataset (RefEx), and RefEx allows users to search by the gene name, various types of IDs, chromosomal regions in genetic maps, gene family based on InterPro, gene expression patterns, or biological categories based on Gene Ontology. RefEx also provides information about genes with tissue-specific expression, and the relative gene expression values are shown as choropleth maps on 3D human body images from BodyParts3D. Combined with the newly incorporated Functional Annotation of Mammals (FANTOM) dataset, RefEx provides insight regarding the functional interpretation of unfamiliar genes. RefEx is publicly available at http://refex.dbcls.jp/. PMID:28850115

BIOSPIDA: A Relational Database Translator for NCBI.

PubMed

Hagen, Matthew S; Lee, Eva K

2010-11-13

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time.

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis

PubMed Central

Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet. PMID:28695067

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis.

PubMed

Costa, Raquel L; Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet.

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.

Deep insight into the Ganoderma lucidum by comprehensive analysis of its transcriptome.

PubMed

Yu, Guo-Jun; Wang, Man; Huang, Jie; Yin, Ya-Lin; Chen, Yi-Jie; Jiang, Shuai; Jin, Yan-Xia; Lan, Xian-Qing; Wong, Barry Hon Cheung; Liang, Yi; Sun, Hui

2012-01-01

Ganoderma lucidum is a basidiomycete white rot fungus and is of medicinal importance in China, Japan and other countries in the Asiatic region. To date, much research has been performed in identifying the medicinal ingredients in Ganoderma lucidum. Despite its important therapeutic effects in disease, little is known about Ganoderma lucidum at the genomic level. In order to gain a molecular understanding of this fungus, we utilized Illumina high-throughput technology to sequence and analyze the transcriptome of Ganoderma lucidum. We obtained 6,439,690 and 6,416,670 high-quality reads from the mycelium and fruiting body of Ganoderma lucidum, and these were assembled to form 18,892 and 27,408 unigenes, respectively. A similarity search was performed against the NCBI non-redundant nucleotide database and a customized database composed of five fungal genomes. 11,098 and 8, 775 unigenes were matched to the NCBI non-redundant nucleotide database and our customized database, respectively. All unigenes were subjected to annotation by Gene Ontology, Eukaryotic Orthologous Group terms and Kyoto Encyclopedia of Genes and Genomes. Differentially expressed genes from the Ganoderma lucidum mycelium and fruiting body stage were analyzed, resulting in the identification of 13 unigenes which are involved in the terpenoid backbone biosynthesis pathway. Quantitative real-time PCR was used to confirm the expression levels of these unigenes. Ganoderma lucidum was also studied for wood degrading activity and a total of 22 putative FOLymes (fungal oxidative lignin enzymes) and 120 CAZymes (carbohydrate-active enzymes) were predicted from our Ganoderma lucidum transcriptome. Our study provides comprehensive gene expression information on Ganoderma lucidum at the transcriptional level, which will form the foundation for functional genomics studies in this fungus. The use of Illumina sequencing technology has made de novo transcriptome assembly and gene expression analysis possible in species that lack full genome information.

Deep Insight into the Ganoderma lucidum by Comprehensive Analysis of Its Transcriptome

PubMed Central

Yu, Guo-Jun; Wang, Man; Huang, Jie; Yin, Ya-Lin; Chen, Yi-Jie; Jiang, Shuai; Jin, Yan-Xia; Lan, Xian-Qing; Wong, Barry Hon Cheung; Liang, Yi; Sun, Hui

2012-01-01

Background Ganoderma lucidum is a basidiomycete white rot fungus and is of medicinal importance in China, Japan and other countries in the Asiatic region. To date, much research has been performed in identifying the medicinal ingredients in Ganoderma lucidum. Despite its important therapeutic effects in disease, little is known about Ganoderma lucidum at the genomic level. In order to gain a molecular understanding of this fungus, we utilized Illumina high-throughput technology to sequence and analyze the transcriptome of Ganoderma lucidum. Methodology/Principal Findings We obtained 6,439,690 and 6,416,670 high-quality reads from the mycelium and fruiting body of Ganoderma lucidum, and these were assembled to form 18,892 and 27,408 unigenes, respectively. A similarity search was performed against the NCBI non-redundant nucleotide database and a customized database composed of five fungal genomes. 11,098 and 8, 775 unigenes were matched to the NCBI non-redundant nucleotide database and our customized database, respectively. All unigenes were subjected to annotation by Gene Ontology, Eukaryotic Orthologous Group terms and Kyoto Encyclopedia of Genes and Genomes. Differentially expressed genes from the Ganoderma lucidum mycelium and fruiting body stage were analyzed, resulting in the identification of 13 unigenes which are involved in the terpenoid backbone biosynthesis pathway. Quantitative real-time PCR was used to confirm the expression levels of these unigenes. Ganoderma lucidum was also studied for wood degrading activity and a total of 22 putative FOLymes (fungal oxidative lignin enzymes) and 120 CAZymes (carbohydrate-active enzymes) were predicted from our Ganoderma lucidum transcriptome. Conclusions Our study provides comprehensive gene expression information on Ganoderma lucidum at the transcriptional level, which will form the foundation for functional genomics studies in this fungus. The use of Illumina sequencing technology has made de novo transcriptome assembly and gene expression analysis possible in species that lack full genome information. PMID:22952861

Identifying osteosarcoma metastasis associated genes by weighted gene co-expression network analysis (WGCNA).

PubMed

Tian, Honglai; Guan, Donghui; Li, Jianmin

2018-06-01

Osteosarcoma (OS), the most common malignant bone tumor, accounts for the heavy healthy threat in the period of children and adolescents. OS occurrence usually correlates with early metastasis and high death rate. This study aimed to better understand the mechanism of OS metastasis.Based on Gene Expression Omnibus (GEO) database, we downloaded 4 expression profile data sets associated with OS metastasis, and selected differential expressed genes. Weighted gene co-expression network analysis (WGCNA) approach allowed us to investigate the most OS metastasis-correlated module. Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to give annotation of selected OS metastasis-associated genes.We select 897 differential expressed genes from OS metastasis and OS non-metastasis groups. Based on these selected genes, WGCNA further explored 142 genes included in the most OS metastasis-correlated module. Gene Ontology functional and KEGG pathway enrichment analyses showed that significantly OS metastasis-associated genes were involved in pathway correlated with insulin-like growth factor binding.Our research figured out several potential molecules participating in metastasis process and factors acting as biomarker. With this study, we could better explore the mechanism of OS metastasis and further discover more therapy targets.

Epigenetic hereditary transcription profiles III, evidence for an epigenetic network resulting in gender, tissue and age-specific variation in overall transcription

PubMed Central

Simons, Johannes WIM

2009-01-01

Background We have previously shown that deviations from the average transcription profile of a group of functionally related genes are not only heritable, but also demonstrate specific patterns associated with age, gender and differentiation, thereby implicating genome-wide nuclear programming as the cause. To determine whether these results could be reproduced, a different micro-array database (obtained from two types of muscle tissue, derived from 81 human donors aged between 16 to 89 years) was studied. Results This new database also revealed the existence of age, gender and tissue-specific features in a small group of functionally related genes. In order to further analyze this phenomenon, a method was developed for quantifying the contribution of different factors to the variability in gene expression, and for generating a database limited to residual values reflecting constitutional differences between individuals. These constitutional differences, presumably epigenetic in origin, contribute to about 50% of the observed residual variance which is connected with a network of interrelated changes in gene expression with some genes displaying a decrease or increase in residual variation with age. Conclusion Epigenetic variation in gene expression without a clear concomitant relation to gene function appears to be a widespread phenomenon. This variation is connected with interactions between genes, is gender and tissue specific and is related to cellular aging. This finding, together with the method developed for analysis, might contribute to the elucidation of the role of nuclear programming in differentiation, aging and carcinogenesis Reviewers This article was reviewed by Thiago M. Venancio (nominated by Aravind Iyer), Hua Li (nominated by Arcady Mushegian) and Arcady Mushegian and J.P.de Magelhaes (nominated by G. Church). PMID:19796384

Comparative Transcriptional Analysis of Loquat Fruit Identifies Major Signal Networks Involved in Fruit Development and Ripening Process.

PubMed

Song, Huwei; Zhao, Xiangxiang; Hu, Weicheng; Wang, Xinfeng; Shen, Ting; Yang, Liming

2016-11-04

Loquat ( Eriobotrya japonica Lindl.) is an important non-climacteric fruit and rich in essential nutrients such as minerals and carotenoids. During fruit development and ripening, thousands of the differentially expressed genes (DEGs) from various metabolic pathways cause a series of physiological and biochemical changes. To better understand the underlying mechanism of fruit development, the Solexa/Illumina RNA-seq high-throughput sequencing was used to evaluate the global changes of gene transcription levels. More than 51,610,234 high quality reads from ten runs of fruit development were sequenced and assembled into 48,838 unigenes. Among 3256 DEGs, 2304 unigenes could be annotated to the Gene Ontology database. These DEGs were distributed into 119 pathways described in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A large number of DEGs were involved in carbohydrate metabolism, hormone signaling, and cell-wall degradation. The real-time reverse transcription (qRT)-PCR analyses revealed that several genes related to cell expansion, auxin signaling and ethylene response were differentially expressed during fruit development. Other members of transcription factor families were also identified. There were 952 DEGs considered as novel genes with no annotation in any databases. These unigenes will serve as an invaluable genetic resource for loquat molecular breeding and postharvest storage.

Gene expression analysis of flax seed development

PubMed Central

2011-01-01

Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages) seed coats (globular and torpedo stages) and endosperm (pooled globular to torpedo stages) and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST) (GenBank accessions LIBEST_026995 to LIBEST_027011) were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152) had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid clones that comprise even low-expressed genes such as those encoding transcription factors. This has allowed us to delineate the spatio-temporal aspects of gene expression underlying the biosynthesis of a number of important seed constituents in flax. Flax belongs to a taxonomic group of diverse plants and the large sequence database will allow for evolutionary studies as well. PMID:21529361

Identification of transcriptional factors and key genes in primary osteoporosis by DNA microarray.

PubMed

Xie, Wengui; Ji, Lixin; Zhao, Teng; Gao, Pengfei

2015-05-09

A number of genes have been identified to be related with primary osteoporosis while less is known about the comprehensive interactions between regulating genes and proteins. We aimed to identify the differentially expressed genes (DEGs) and regulatory effects of transcription factors (TFs) involved in primary osteoporosis. The gene expression profile GSE35958 was obtained from Gene Expression Omnibus database, including 5 primary osteoporosis and 4 normal bone tissues. The differentially expressed genes between primary osteoporosis and normal bone tissues were identified by the same package in R language. The TFs of these DEGs were predicted with the Essaghir A method. DAVID (The Database for Annotation, Visualization and Integrated Discovery) was applied to perform the GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis of DEGs. After analyzing regulatory effects, a regulatory network was built between TFs and the related DEGs. A total of 579 DEGs was screened, including 310 up-regulated genes and 269 down-regulated genes in primary osteoporosis samples. In GO terms, more up-regulated genes were enriched in transcription regulator activity, and secondly in transcription factor activity. A total 10 significant pathways were enriched in KEGG analysis, including colorectal cancer, Wnt signaling pathway, Focal adhesion, and MAPK signaling pathway. Moreover, total 7 TFs were enriched, of which CTNNB1, SP1, and TP53 regulated most up-regulated DEGs. The discovery of the enriched TFs might contribute to the understanding of the mechanism of primary osteoporosis. Further research on genes and TFs related to the WNT signaling pathway and MAPK pathway is urgent for clinical diagnosis and directing treatment of primary osteoporosis.

A database for the analysis of immunity genes in Drosophila: PADMA database.

PubMed

Lee, Mark J; Mondal, Ariful; Small, Chiyedza; Paddibhatla, Indira; Kawaguchi, Akira; Govind, Shubha

2011-01-01

While microarray experiments generate voluminous data, discerning trends that support an existing or alternative paradigm is challenging. To synergize hypothesis building and testing, we designed the Pathogen Associated Drosophila MicroArray (PADMA) database for easy retrieval and comparison of microarray results from immunity-related experiments (www.padmadatabase.org). PADMA also allows biologists to upload their microarray-results and compare it with datasets housed within PADMA. We tested PADMA using a preliminary dataset from Ganaspis xanthopoda-infected fly larvae, and uncovered unexpected trends in gene expression, reshaping our hypothesis. Thus, the PADMA database will be a useful resource to fly researchers to evaluate, revise, and refine hypotheses.

The construction of an EST database for Bombyx mori and its application

PubMed Central

Mita, Kazuei; Morimyo, Mitsuoki; Okano, Kazuhiro; Koike, Yoshiko; Nohata, Junko; Kawasaki, Hideki; Kadono-Okuda, Keiko; Yamamoto, Kimiko; Suzuki, Masataka G.; Shimada, Toru; Goldsmith, Marian R.; Maeda, Susumu

2003-01-01

To build a foundation for the complete genome analysis of Bombyx mori, we have constructed an EST database. Because gene expression patterns deeply depend on tissues as well as developmental stages, we analyzed many cDNA libraries prepared from various tissues and different developmental stages to cover the entire set of Bombyx genes. So far, the Bombyx EST database contains 35,000 ESTs from 36 cDNA libraries, which are grouped into ≈11,000 nonredundant ESTs with the average length of 1.25 kb. The comparison with FlyBase suggests that the present EST database, SilkBase, covers >55% of all genes of Bombyx. The fraction of library-specific ESTs in each cDNA library indicates that we have not yet reached saturation, showing the validity of our strategy for constructing an EST database to cover all genes. To tackle the coming saturation problem, we have checked two methods, subtraction and normalization, to increase coverage and decrease the number of housekeeping genes, resulting in a 5–11% increase of library-specific ESTs. The identification of a number of genes and comprehensive cloning of gene families have already emerged from the SilkBase search. Direct links of SilkBase with FlyBase and WormBase provide ready identification of candidate Lepidoptera-specific genes. PMID:14614147

Construction of a cDNA library from female adult of Toxocara canis, and analysis of EST and immune-related genes expressions.

PubMed

Zhou, Rongqiong; Xia, Qingyou; Huang, Hancheng; Lai, Min; Wang, Zhenxin

2011-10-01

Toxocara canis is a widespread intestinal nematode parasite of dogs, which can also cause disease in humans. We employed an expressed sequence tag (EST) strategy in order to study gene-expression including development, digestion and reproduction of T. canis. ESTs provided a rapid way to identify genes, particularly in organisms for which we have very little molecular information. In this study, a cDNA library was constructed from a female adult of T. canis and 215 high-quality ESTs from 5'-ends of the cDNA clones representing 79 unigenes were obtained. The titer of the primary cDNA library was 1.83×10(6)pfu/mL with a recombination rate of 99.33%. Most of the sequences ranged from 300 to 900bp with an average length of 656bp. Cluster analysis of these ESTs allowed identification of 79 unique sequences containing 28 contigs and 51 singletons. BLASTX searches revealed that 18 unigenes (22.78% of the total) or 70 ESTs (32.56% of the total) were novel genes that had no significant matches to any protein sequences in the public databases. The rest of the 61 unigenes (77.22% of the total) or 145 ESTs (67.44% of the total) were closely matched to the known genes or sequences deposited in the public databases. These genes were classified into seven groups based on their known or putative biological functions. We also confirmed the gene expression patterns of several immune-related genes using RT-PCR examination. This work will provide a valuable resource for the further investigations in the stage-, sex- and tissue-specific gene transcription or expression. Copyright © 2011. Published by Elsevier Inc.

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Barrett, Tanya; Benson, Dennis A.; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Kenton, David L.; Khovayko, Oleg; Lipman, David J.; Madden, Thomas L.; Maglott, Donna R.; Ostell, James; Pruitt, Kim D.; Schuler, Gregory D.; Schriml, Lynn M.; Sequeira, Edwin; Sherry, Stephen T.; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Suzek, Tugba O.; Tatusov, Roman; Tatusova, Tatiana A.; Wagner, Lukas; Yaschenko, Eugene

2006-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups, Retroviral Genotyping Tools, HIV-1, Human Protein Interaction Database, SAGEmap, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of the resources can be accessed through the NCBI home page at: . PMID:16381840

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bolton, Evan; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; Dicuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Krasnov, Sergey; Landsman, David; Lipman, David J; Lu, Zhiyong; Madden, Thomas L; Madej, Tom; Maglott, Donna R; Marchler-Bauer, Aron; Miller, Vadim; Karsch-Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Wang, Yanli; Wilbur, W John; Yaschenko, Eugene; Ye, Jian

2012-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Database resources of the National Center for Biotechnology Information

PubMed Central

Acland, Abigail; Agarwala, Richa; Barrett, Tanya; Beck, Jeff; Benson, Dennis A.; Bollin, Colleen; Bolton, Evan; Bryant, Stephen H.; Canese, Kathi; Church, Deanna M.; Clark, Karen; DiCuccio, Michael; Dondoshansky, Ilya; Federhen, Scott; Feolo, Michael; Geer, Lewis Y.; Gorelenkov, Viatcheslav; Hoeppner, Marilu; Johnson, Mark; Kelly, Christopher; Khotomlianski, Viatcheslav; Kimchi, Avi; Kimelman, Michael; Kitts, Paul; Krasnov, Sergey; Kuznetsov, Anatoliy; Landsman, David; Lipman, David J.; Lu, Zhiyong; Madden, Thomas L.; Madej, Tom; Maglott, Donna R.; Marchler-Bauer, Aron; Karsch-Mizrachi, Ilene; Murphy, Terence; Ostell, James; O'Sullivan, Christopher; Panchenko, Anna; Phan, Lon; Pruitt, Don Preussm Kim D.; Rubinstein, Wendy; Sayers, Eric W.; Schneider, Valerie; Schuler, Gregory D.; Sequeira, Edwin; Sherry, Stephen T.; Shumway, Martin; Sirotkin, Karl; Siyan, Karanjit; Slotta, Douglas; Soboleva, Alexandra; Soussov, Vladimir; Starchenko, Grigory; Tatusova, Tatiana A.; Trawick, Bart W.; Vakatov, Denis; Wang, Yanli; Ward, Minghong; John Wilbur, W.; Yaschenko, Eugene; Zbicz, Kerry

2014-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, PubReader, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link, Primer-BLAST, COBALT, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, ClinVar, MedGen, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page. PMID:24259429

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Church, Deanna M.; Lash, Alex E.; Leipe, Detlef D.; Madden, Thomas L.; Pontius, Joan U.; Schuler, Gregory D.; Schriml, Lynn M.; Tatusova, Tatiana A.; Wagner, Lukas; Rapp, Barbara A.

2001-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources that operate on the data in GenBank and a variety of other biological data made available through NCBI’s Web site. NCBI data retrieval resources include Entrez, PubMed, LocusLink and the Taxonomy Browser. Data analysis resources include BLAST, Electronic PCR, OrfFinder, RefSeq, UniGene, HomoloGene, Database of Single Nucleotide Polymorphisms (dbSNP), Human Genome Sequencing, Human MapViewer, GeneMap’99, Human–Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, Cancer Genome Anatomy Project (CGAP), SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheri­tance in Man (OMIM), the Molecular Modeling Database (MMDB) and the Conserved Domain Database (CDD). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov. PMID:11125038

CnidBase: The Cnidarian Evolutionary Genomics Database

PubMed Central

Ryan, Joseph F.; Finnerty, John R.

2003-01-01

CnidBase, the Cnidarian Evolutionary Genomics Database, is a tool for investigating the evolutionary, developmental and ecological factors that affect gene expression and gene function in cnidarians. In turn, CnidBase will help to illuminate the role of specific genes in shaping cnidarian biodiversity in the present day and in the distant past. CnidBase highlights evolutionary changes between species within the phylum Cnidaria and structures genomic and expression data to facilitate comparisons to non-cnidarian metazoans. CnidBase aims to further the progress that has already been made in the realm of cnidarian evolutionary genomics by creating a central community resource which will help drive future research and facilitate more accurate classification and comparison of new experimental data with existing data. CnidBase is available at http://cnidbase.bu.edu/. PMID:12519972

The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

PubMed Central

2012-01-01

Background Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis. Methods Array-comparative genomic hybridization (array-CGH) was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array-CGH database and the expression array database, and literature search for copy number variation genes were performed to select novel lung cancer candidate genes. Four candidate oncogenes were validated for DNA copy number and mRNA and protein expression by quantitative polymerase chain reaction (qPCR), chromogenic in situ hybridization (CISH), reverse transcriptase-qPCR (RT-qPCR), and immunohistochemistry (IHC) in more patients. Results We identified 20 chromosomal imbalance regions harboring 459 genes for Caucasian and 17 regions containing 476 genes for Asian lung cancer patients. Seven common chromosomal imbalance regions harboring 117 genes, included gain on 3p13-14, 6p22.1, 9q21.13, 13q14.1, and 17p13.3; and loss on 3p22.2-22.3 and 13q13.3 were found both in Asian and Caucasian patients. Gene validation for four genes including ARHGAP19 (10q24.1) functioning in Rho activity control, FRAT2 (10q24.1) involved in Wnt signaling, PAFAH1B1 (17p13.3) functioning in motility control, and ZNF322A (6p22.1) involved in MAPK signaling was performed using qPCR and RT-qPCR. Mean gene dosage and mRNA expression level of the four candidate genes in tumor tissues were significantly higher than the corresponding normal tissues (P<0.001~P=0.06). In addition, CISH analysis of patients indicated that copy number amplification indeed occurred for ARHGAP19 and ZNF322A genes in lung cancer patients. IHC analysis of paraffin blocks from Asian Caucasian patients demonstrated that the frequency of PAFAH1B1 protein overexpression was 68% in Asian and 70% in Caucasian. Conclusions Our study provides an invaluable database revealing common and differential imbalance regions at specific chromosomes among Asian and Caucasian lung cancer patients. Four validation methods confirmed our database, which would help in further studies on the mechanism of lung tumorigenesis. PMID:22691236

Complementary DNA sequencing and identification of mRNAs from the venomous gland of Agkistrodon piscivorus leucostoma.

PubMed

Jia, Ying; Cantu, Bruno A; Sánchez, Elda E; Pérez, John C

2008-06-15

To advance our knowledge on the snake venom composition and transcripts expressed in venom gland at the molecular level, we constructed a cDNA library from the venom gland of Agkistrodon piscivorus leucostoma for the generation of expressed sequence tags (ESTs) database. From the randomly sequenced 2112 independent clones, we have obtained ESTs for 1309 (62%) cDNAs, which showed significant deduced amino acid sequence similarity (scores >80) to previously characterized proteins in National Center for Biotechnology Information (NCBI) database. Ribosomal proteins make up 47 clones (2%) and the remaining 756 (36%) cDNAs represent either unknown identity or show BLASTX sequence identity scores of <80 with known GenBank accessions. The most highly expressed gene encoding phospholipase A(2) (PLA(2)) accounting for 35% of A. p. leucostoma venom gland cDNAs was identified and further confirmed by crude venom applied to sodium dodecyl sulfate/polyacrylamide gel electrophoresis (SDS-PAGE) electrophoresis and protein sequencing. A total of 180 representative genes were obtained from the sequence assemblies and deposited to EST database. Clones showing sequence identity to disintegrins, thrombin-like enzymes, hemorrhagic toxins, fibrinogen clotting inhibitors and plasminogen activators were also identified in our EST database. These data can be used to develop a research program that will help us identify genes encoding proteins that are of medical importance or proteins involved in the mechanisms of the toxin venom.

SEA: a super-enhancer archive.

PubMed

Wei, Yanjun; Zhang, Shumei; Shang, Shipeng; Zhang, Bin; Li, Song; Wang, Xinyu; Wang, Fang; Su, Jianzhong; Wu, Qiong; Liu, Hongbo; Zhang, Yan

2016-01-04

Super-enhancers are large clusters of transcriptional enhancers regarded as having essential roles in driving the expression of genes that control cell identity during development and tumorigenesis. The construction of a genome-wide super-enhancer database is urgently needed to better understand super-enhancer-directed gene expression regulation for a given biology process. Here, we present a specifically designed web-accessible database, Super-Enhancer Archive (SEA, http://sea.edbc.org). SEA focuses on integrating super-enhancers in multiple species and annotating their potential roles in the regulation of cell identity gene expression. The current release of SEA incorporates 83 996 super-enhancers computationally or experimentally identified in 134 cell types/tissues/diseases, including human (75 439, three of which were experimentally identified), mouse (5879, five of which were experimentally identified), Drosophila melanogaster (1774) and Caenorhabditis elegans (904). To facilitate data extraction, SEA supports multiple search options, including species, genome location, gene name, cell type/tissue and super-enhancer name. The response provides detailed (epi)genetic information, incorporating cell type specificity, nearby genes, transcriptional factor binding sites, CRISPR/Cas9 target sites, evolutionary conservation, SNPs, H3K27ac, DNA methylation, gene expression and TF ChIP-seq data. Moreover, analytical tools and a genome browser were developed for users to explore super-enhancers and their roles in defining cell identity and disease processes in depth. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

PubMed

Strakova, Eva; Zikova, Alice; Vohradsky, Jiri

2014-01-01

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

Role of miR-452-5p in the tumorigenesis of prostate cancer: A study based on the Cancer Genome Atl(TCGA), Gene Expression Omnibus (GEO), and bioinformatics analysis.

PubMed

Gao, Li; Zhang, Li-Jie; Li, Sheng-Hua; Wei, Li-Li; Luo, Bin; He, Rong-Quan; Xia, Shuang

2018-03-06

MiR-452-5p has been reported to be down-regulated in prostate cancer, affecting the development of this type of cancer. However, the molecular mechanism of miR-452-5p in prostate cancer remains unclear. Therefore, we investigated the network of target genes of miR-452-5p in prostate cancer using bioinformatics analyses. We first analyzed the expression profiles and prognostic value of miR-452-5p in prostate cancer tissues from a public database. Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), PANTHER pathway analyses, and a disease ontology (DG) analysis were performed to find the molecular functions of the target genes from GSE datasets and miRWalk. Finally, we validated hub genes from the protein-protein interaction (PPI) networks of the target genes in the Human Protein Atlas (HPA) database and Gene Expression Profiling Interactive Analysis (GEPIA). Narrowing down the optimal target genes was conducted by seeking the common parts of up-regulated genes from GEPIA, down-regulated genes from GSE datasets, and predicted genes in miRWalk. Based on mining of GEO and ArrayExpress microarray chips and miRNA-Seq data in the TCGA database, which includes 1007 prostate cancer samples and 387 non-cancer samples, miR-452-5p is shown to be down-regulated in prostate cancer. GO, KEGG, and PANTHER pathway analyses suggested that the target genes might participate in important biological processes, such as transforming growth factor beta signaling and the positive regulation of brown fat cell differentiation and mesenchymal cell differentiation, as well as the Ras signaling pathway and pathways regulating the pluripotency of stem cells and arrhythmogenic right ventricular cardiomyopathy (ARVC). Nine genes-GABBR, PNISR, NTSR1, DOCK1, EREG, SFRP1, PTGS2, LEF1, and BMP2-were defined as hub genes in the PPI network. Three genes-FAM174B, SLC30A4, and SLIT1-were jointly shared by GEPIA, the GSE datasets, and miRWalk. Down-regulated miR-452-5p might play an essential role in the tumorigenesis of prostate cancer. Copyright © 2018. Published by Elsevier GmbH.

Plant Reactome: a resource for plant pathways and comparative analysis.

PubMed

Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D; Wu, Guanming; Fabregat, Antonio; Elser, Justin L; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D; Ware, Doreen; Jaiswal, Pankaj

2017-01-04

Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comprehensive Analysis of Gene Expression Profiles of Sepsis-Induced Multiorgan Failure Identified Its Valuable Biomarkers.

PubMed

Wang, Yumei; Yin, Xiaoling; Yang, Fang

2018-02-01

Sepsis is an inflammatory-related disease, and severe sepsis would induce multiorgan dysfunction, which is the most common cause of death of patients in noncoronary intensive care units. Progression of novel therapeutic strategies has proven to be of little impact on the mortality of severe sepsis, and unfortunately, its mechanisms still remain poorly understood. In this study, we analyzed gene expression profiles of severe sepsis with failure of lung, kidney, and liver for the identification of potential biomarkers. We first downloaded the gene expression profiles from the Gene Expression Omnibus and performed preprocessing of raw microarray data sets and identification of differential expression genes (DEGs) through the R programming software; then, significantly enriched functions of DEGs in lung, kidney, and liver failure sepsis samples were obtained from the Database for Annotation, Visualization, and Integrated Discovery; finally, protein-protein interaction network was constructed for DEGs based on the STRING database, and network modules were also obtained through the MCODE cluster method. As a result, lung failure sepsis has the highest number of DEGs of 859, whereas the number of DEGs in kidney and liver failure sepsis samples is 178 and 175, respectively. In addition, 17 overlaps were obtained among the three lists of DEGs. Biological processes related to immune and inflammatory response were found to be significantly enriched in DEGs. Network and module analysis identified four gene clusters in which all or most of genes were upregulated. The expression changes of Icam1 and Socs3 were further validated through quantitative PCR analysis. This study should shed light on the development of sepsis and provide potential therapeutic targets for sepsis-induced multiorgan failure.

Biological and Clinical Significance of MAD2L1 and BUB1, Genes Frequently Appearing in Expression Signatures for Breast Cancer Prognosis

PubMed Central

Wang, Zhanwei; Katsaros, Dionyssios; Shen, Yi; Fu, Yuanyuan; Canuto, Emilie Marion; Benedetto, Chiara; Lu, Lingeng; Chu, Wen-Ming; Risch, Harvey A.; Yu, Herbert

2015-01-01

To investigate the biologic relevance and clinical implication of genes involved in multiple gene expression signatures for breast cancer prognosis, we identified 16 published gene expression signatures, and selected two genes, MAD2L1 and BUB1. These genes appeared in 5 signatures and were involved in cell-cycle regulation. We analyzed the expression of these genes in relation to tumor features and disease outcomes. In vitro experiments were also performed in two breast cancer cell lines, MDA-MB-231 and MDA-MB-468, to assess cell proliferation, migration and invasion after knocking down the expression of these genes. High expression of these genes was found to be associated with aggressive tumors and poor disease-free survival of 203 breast cancer patients in our study, and the association with survival was confirmed in an online database consisting of 914 patients. In vitro experiments demonstrated that lowering the expression of these genes by siRNAs reduced tumor cell growth and inhibited cell migration and invasion. Our investigation suggests that MAD2L1 and BUB1 may play important roles in breast cancer progression, and measuring the expression of these genes may assist the prediction of breast cancer prognosis. PMID:26287798

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

Macronutrients and the FTO gene expression in hypothalamus; a systematic review of experimental studies.

PubMed

Doaei, Saeid; Kalantari, Naser; Mohammadi, Nastaran Keshavarz; Tabesh, Ghasem Azizi; Gholamalizadeh, Maryam

The various studies have examined the relationship between FTO gene expression and macronutrients levels. In order to obtain better viewpoint from this interactions, all of existing studies were reviewed systematically. All published papers have been obtained and reviewed using standard and sensitive keywords from databases such as CINAHL, Embase, PubMed, PsycInfo, and the Cochrane, from 1990 to 2016. The results indicated that all of 6 studies that met the inclusion criteria (from a total of 428 published article) found FTO gene expression changes at short-term follow-ups. Four of six studies found an increased FTO gene expression after calorie restriction, while two of them indicated decreased FTO gene expression. The effect of protein, carbohydrate and fat were separately assessed and suggested by all of six studies. In Conclusion, The level of FTO gene expression in hypothalamus is related to macronutrients levels. Future research should evaluate the long-term impact of dietary interventions. Copyright © 2017. Published by Elsevier B.V.

Rapid in silico cloning of genes using expressed sequence tags (ESTs).

PubMed

Gill, R W; Sanseau, P

2000-01-01

Expressed sequence tags (ESTs) are short single-pass DNA sequences obtained from either end of cDNA clones. These ESTs are derived from a vast number of cDNA libraries obtained from different species. Human ESTs are the bulk of the data and have been widely used to identify new members of gene families, as markers on the human chromosomes, to discover polymorphism sites and to compare expression patterns in different tissues or pathologies states. Information strategies have been devised to query EST databases. Since most of the analysis is performed with a computer, the term "in silico" strategy has been coined. In this chapter we will review the current status of EST databases, the pros and cons of EST-type data and describe possible strategies to retrieve meaningful information.

Expression of the Long Intergenic Non-Protein Coding RNA 665 (LINC00665) Gene and the Cell Cycle in Hepatocellular Carcinoma Using The Cancer Genome Atlas, the Gene Expression Omnibus, and Quantitative Real-Time Polymerase Chain Reaction.

PubMed

Wen, Dong-Yue; Lin, Peng; Pang, Yu-Yan; Chen, Gang; He, Yun; Dang, Yi-Wu; Yang, Hong

2018-05-05

BACKGROUND Long non-coding RNAs (lncRNAs) have a role in physiological and pathological processes, including cancer. The aim of this study was to investigate the expression of the long intergenic non-protein coding RNA 665 (LINC00665) gene and the cell cycle in hepatocellular carcinoma (HCC) using database analysis including The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and quantitative real-time polymerase chain reaction (qPCR). MATERIAL AND METHODS Expression levels of LINC00665 were compared between human tissue samples of HCC and adjacent normal liver, clinicopathological correlations were made using TCGA and the GEO, and qPCR was performed to validate the findings. Other public databases were searched for other genes associated with LINC00665 expression, including The Atlas of Noncoding RNAs in Cancer (TANRIC), the Multi Experiment Matrix (MEM), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) networks. RESULTS Overexpression of LINC00665 in patients with HCC was significantly associated with gender, tumor grade, stage, and tumor cell type. Overexpression of LINC00665 in patients with HCC was significantly associated with overall survival (OS) (HR=1.47795%; CI: 1.046-2.086). Bioinformatics analysis identified 469 related genes and further analysis supported a hypothesis that LINC00665 regulates pathways in the cell cycle to facilitate the development and progression of HCC through ten identified core genes: CDK1, BUB1B, BUB1, PLK1, CCNB2, CCNB1, CDC20, ESPL1, MAD2L1, and CCNA2. CONCLUSIONS Overexpression of the lncRNA, LINC00665 may be involved in the regulation of cell cycle pathways in HCC through ten identified hub genes.

EUCANEXT: an integrated database for the exploration of genomic and transcriptomic data from Eucalyptus species

PubMed Central

Nascimento, Leandro Costa; Salazar, Marcela Mendes; Lepikson-Neto, Jorge; Camargo, Eduardo Leal Oliveira; Parreiras, Lucas Salera; Carazzolle, Marcelo Falsarella

2017-01-01

Abstract Tree species of the genus Eucalyptus are the most valuable and widely planted hardwoods in the world. Given the economic importance of Eucalyptus trees, much effort has been made towards the generation of specimens with superior forestry properties that can deliver high-quality feedstocks, customized to the industrýs needs for both cellulosic (paper) and lignocellulosic biomass production. In line with these efforts, large sets of molecular data have been generated by several scientific groups, providing invaluable information that can be applied in the development of improved specimens. In order to fully explore the potential of available datasets, the development of a public database that provides integrated access to genomic and transcriptomic data from Eucalyptus is needed. EUCANEXT is a database that analyses and integrates publicly available Eucalyptus molecular data, such as the E. grandis genome assembly and predicted genes, ESTs from several species and digital gene expression from 26 RNA-Seq libraries. The database has been implemented in a Fedora Linux machine running MySQL and Apache, while Perl CGI was used for the web interfaces. EUCANEXT provides a user-friendly web interface for easy access and analysis of publicly available molecular data from Eucalyptus species. This integrated database allows for complex searches by gene name, keyword or sequence similarity and is publicly accessible at http://www.lge.ibi.unicamp.br/eucalyptusdb. Through EUCANEXT, users can perform complex analysis to identify genes related traits of interest using RNA-Seq libraries and tools for differential expression analysis. Moreover, all the bioinformatics pipeline here described, including the database schema and PERL scripts, are readily available and can be applied to any genomic and transcriptomic project, regardless of the organism. Database URL: http://www.lge.ibi.unicamp.br/eucalyptusdb PMID:29220468

Partial Least Squares Based Gene Expression Analysis in EBV- Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders.

PubMed

Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi

2013-01-01

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

Identification of potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma.

PubMed

Pan, Yue; Lu, Lingyun; Chen, Junquan; Zhong, Yong; Dai, Zhehao

2018-01-01

This study aimed to identify potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma by comprehensive bioinformatics analysis. Data of gene expression profiles (GSE28424) and miRNA expression profiles (GSE28423) were downloaded from GEO database. The differentially expressed genes (DEGs) and miRNAs (DEMIs) were obtained by R Bioconductor packages. Functional and enrichment analyses of selected genes were performed using DAVID database. Protein-protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape. The relationships among the DEGs and module in PPI network were analyzed by plug-in NetworkAnalyzer and MCODE seperately. Through the TargetScan and comparing target genes with DEGs, the miRNA-mRNA regulation network was established. Totally 346 DEGs and 90 DEMIs were found to be differentially expressed. These DEGs were enriched in biological processes and KEGG pathway of inflammatory immune response. 25 genes in the PPI network were selected as hub genes. Top 10 hub genes were TYROBP, HLA-DRA, VWF, PPBP, SERPING1, HLA-DPA1, SERPINA1, KIF20A, FERMT3, HLA-E. PPI network of DEGs followed a pattern of power law network and met the characteristics of small-world network. MCODE analysis identified 4 clusters and the most significant cluster consisted of 11 nodes and 55 edges. SEPP1, CKS2, TCAP, BPI were identified as the seed genes in their own clusters, respectively. The miRNA-mRNA regulation network which was composed of 89 pairs was established. MiR-210 had the highest connectivity with 12 target genes. Among the predicted target of MiR-96, HLA-DPA1 and TYROBP were the hub genes. Our study indicated possible differentially expressed genes and miRNA, and microRNA-mRNA negative regulatory networks in osteosarcoma by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of osteosarcoma.

An Ambystoma mexicanum EST sequencing project: analysis of 17,352 expressed sequence tags from embryonic and regenerating blastema cDNA libraries

PubMed Central

Habermann, Bianca; Bebin, Anne-Gaelle; Herklotz, Stephan; Volkmer, Michael; Eckelt, Kay; Pehlke, Kerstin; Epperlein, Hans Henning; Schackert, Hans Konrad; Wiebe, Glenis; Tanaka, Elly M

2004-01-01

Background The ambystomatid salamander, Ambystoma mexicanum (axolotl), is an important model organism in evolutionary and regeneration research but relatively little sequence information has so far been available. This is a major limitation for molecular studies on caudate development, regeneration and evolution. To address this lack of sequence information we have generated an expressed sequence tag (EST) database for A. mexicanum. Results Two cDNA libraries, one made from stage 18-22 embryos and the other from day-6 regenerating tail blastemas, generated 17,352 sequences. From the sequenced ESTs, 6,377 contigs were assembled that probably represent 25% of the expressed genes in this organism. Sequence comparison revealed significant homology to entries in the NCBI non-redundant database. Further examination of this gene set revealed the presence of genes involved in important cell and developmental processes, including cell proliferation, cell differentiation and cell-cell communication. On the basis of these data, we have performed phylogenetic analysis of key cell-cycle regulators. Interestingly, while cell-cycle proteins such as the cyclin B family display expected evolutionary relationships, the cyclin-dependent kinase inhibitor 1 gene family shows an unusual evolutionary behavior among the amphibians. Conclusions Our analysis reveals the importance of a comprehensive sequence set from a representative of the Caudata and illustrates that the EST sequence database is a rich source of molecular, developmental and regeneration studies. To aid in data mining, the ESTs have been organized into an easily searchable database that is freely available online. PMID:15345051

Global gene expression analyses of hematopoietic stem cell-like cell lines with inducible Lhx2 expression

PubMed Central

Richter, Karin; Wirta, Valtteri; Dahl, Lina; Bruce, Sara; Lundeberg, Joakim; Carlsson, Leif; Williams, Cecilia

2006-01-01

Background Expression of the LIM-homeobox gene Lhx2 in murine hematopoietic cells allows for the generation of hematopoietic stem cell (HSC)-like cell lines. To address the molecular basis of Lhx2 function, we generated HSC-like cell lines where Lhx2 expression is regulated by a tet-on system and hence dependent on the presence of doxycyclin (dox). These cell lines efficiently down-regulate Lhx2 expression upon dox withdrawal leading to a rapid differentiation into various myeloid cell types. Results Global gene expression of these cell lines cultured in dox was compared to different time points after dox withdrawal using microarray technology. We identified 267 differentially expressed genes. The majority of the genes overlapping with HSC-specific databases were those down-regulated after turning off Lhx2 expression and a majority of the genes overlapping with those defined as late progenitor-specific genes were the up-regulated genes, suggesting that these cell lines represent a relevant model system for normal HSCs also at the level of global gene expression. Moreover, in situ hybridisations of several genes down-regulated after dox withdrawal showed overlapping expression patterns with Lhx2 in various tissues during embryonic development. Conclusion Global gene expression analysis of HSC-like cell lines with inducible Lhx2 expression has identified genes putatively linked to self-renewal / differentiation of HSCs, and function of Lhx2 in organ development and stem / progenitor cells of non-hematopoietic origin. PMID:16600034

Ewing's Sarcoma: An Analysis of miRNA Expression Profiles and Target Genes in Paraffin-Embedded Primary Tumor Tissue.

PubMed

Parafioriti, Antonina; Bason, Caterina; Armiraglio, Elisabetta; Calciano, Lucia; Daolio, Primo Andrea; Berardocco, Martina; Di Bernardo, Andrea; Colosimo, Alessia; Luksch, Roberto; Berardi, Anna C

2016-04-30

The molecular mechanism responsible for Ewing's Sarcoma (ES) remains largely unknown. MicroRNAs (miRNAs), a class of small non-coding RNAs able to regulate gene expression, are deregulated in tumors and may serve as a tool for diagnosis and prediction. However, the status of miRNAs in ES has not yet been thoroughly investigated. This study compared global miRNAs expression in paraffin-embedded tumor tissue samples from 20 ES patients, affected by primary untreated tumors, with miRNAs expressed in normal human mesenchymal stromal cells (MSCs) by microarray analysis. A miRTarBase database was used to identify the predicted target genes for differentially expressed miRNAs. The miRNAs microarray analysis revealed distinct patterns of miRNAs expression between ES samples and normal MSCs. 58 of the 954 analyzed miRNAs were significantly differentially expressed in ES samples compared to MSCs. Moreover, the qRT-PCR analysis carried out on three selected miRNAs showed that miR-181b, miR-1915 and miR-1275 were significantly aberrantly regulated, confirming the microarray results. Bio-database analysis identified BCL-2 as a bona fide target gene of the miR-21, miR-181a, miR-181b, miR-29a, miR-29b, miR-497, miR-195, miR-let-7a, miR-34a and miR-1915. Using paraffin-embedded tissues from ES patients, this study has identified several potential target miRNAs and one gene that might be considered a novel critical biomarker for ES pathogenesis.

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks

PubMed Central

Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways. PMID:29049295

Key genes and pathways in measles and their interaction with environmental chemicals

PubMed Central

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-01-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles. PMID:29805511

ExAtlas: An interactive online tool for meta-analysis of gene expression data.

PubMed

Sharov, Alexei A; Schlessinger, David; Ko, Minoru S H

2015-12-01

We have developed ExAtlas, an on-line software tool for meta-analysis and visualization of gene expression data. In contrast to existing software tools, ExAtlas compares multi-component data sets and generates results for all combinations (e.g. all gene expression profiles versus all Gene Ontology annotations). ExAtlas handles both users' own data and data extracted semi-automatically from the public repository (GEO/NCBI database). ExAtlas provides a variety of tools for meta-analyses: (1) standard meta-analysis (fixed effects, random effects, z-score, and Fisher's methods); (2) analyses of global correlations between gene expression data sets; (3) gene set enrichment; (4) gene set overlap; (5) gene association by expression profile; (6) gene specificity; and (7) statistical analysis (ANOVA, pairwise comparison, and PCA). ExAtlas produces graphical outputs, including heatmaps, scatter-plots, bar-charts, and three-dimensional images. Some of the most widely used public data sets (e.g. GNF/BioGPS, Gene Ontology, KEGG, GAD phenotypes, BrainScan, ENCODE ChIP-seq, and protein-protein interaction) are pre-loaded and can be used for functional annotations.

Genome-Wide Identification, Evolution and Expression Analysis of mTERF Gene Family in Maize

PubMed Central

Zhao, Yanxin; Cai, Manjun; Zhang, Xiaobo; Li, Yurong; Zhang, Jianhua; Zhao, Hailiang; Kong, Fei; Zheng, Yonglian; Qiu, Fazhan

2014-01-01

Plant mitochondrial transcription termination factor (mTERF) genes comprise a large family with important roles in regulating organelle gene expression. In this study, a comprehensive database search yielded 31 potential mTERF genes in maize (Zea mays L.) and most of them were targeted to mitochondria or chloroplasts. Maize mTERF were divided into nine main groups based on phylogenetic analysis, and group IX represented the mitochondria and species-specific clade that diverged from other groups. Tandem and segmental duplication both contributed to the expansion of the mTERF gene family in the maize genome. Comprehensive expression analysis of these genes, using microarray data and RNA-seq data, revealed that these genes exhibit a variety of expression patterns. Environmental stimulus experiments revealed differential up or down-regulation expression of maize mTERF genes in seedlings exposed to light/dark, salts and plant hormones, respectively, suggesting various important roles of maize mTERF genes in light acclimation and stress-related responses. These results will be useful for elucidating the roles of mTERF genes in the growth, development and stress response of maize. PMID:24718683

Database resources of the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Barrett, Tanya; Benson, Dennis A.; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Feolo, Michael; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Khovayko, Oleg; Landsman, David; Lipman, David J.; Madden, Thomas L.; Maglott, Donna R.; Miller, Vadim; Ostell, James; Pruitt, Kim D.; Schuler, Gregory D.; Shumway, Martin; Sequeira, Edwin; Sherry, Steven T.; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusov, Roman L.; Tatusova, Tatiana A.; Wagner, Lukas; Yaschenko, Eugene

2008-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data available through NCBI's web site. NCBI resources include Entrez, the Entrez Programming Utilities, My NCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link, Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genome, Genome Project and related tools, the Trace, Assembly, and Short Read Archives, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups, Influenza Viral Resources, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Entrez Probe, GENSAT, Database of Genotype and Phenotype, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool and the PubChem suite of small molecule databases. Augmenting the web applications are custom implementations of the BLAST program optimized to search specialized data sets. These resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:18045790

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.

Oral cancer databases: A comprehensive review.

PubMed

Sarode, Gargi S; Sarode, Sachin C; Maniyar, Nikunj; Anand, Rahul; Patil, Shankargouda

2017-11-29

Cancer database is a systematic collection and analysis of information on various human cancers at genomic and molecular level that can be utilized to understand various steps in carcinogenesis and for therapeutic advancement in cancer field. Oral cancer is one of the leading causes of morbidity and mortality all over the world. The current research efforts in this field are aimed at cancer etiology and therapy. Advanced genomic technologies including microarrays, proteomics, transcrpitomics, and gene sequencing development have culminated in generation of extensive data and subjection of several genes and microRNAs that are distinctively expressed and this information is stored in the form of various databases. Extensive data from various resources have brought the need for collaboration and data sharing to make effective use of this new knowledge. The current review provides comprehensive information of various publicly accessible databases that contain information pertinent to oral squamous cell carcinoma (OSCC) and databases designed exclusively for OSCC. The databases discussed in this paper are Protein-Coding Gene Databases and microRNA Databases. This paper also describes gene overlap in various databases, which will help researchers to reduce redundancy and focus on only those genes, which are common to more than one databases. We hope such introduction will promote awareness and facilitate the usage of these resources in the cancer research community, and researchers can explore the molecular mechanisms involved in the development of cancer, which can help in subsequent crafting of therapeutic strategies. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

iSyTE 2.0: a database for expression-based gene discovery in the eye

PubMed Central

Kakrana, Atul; Yang, Andrian; Anand, Deepti; Djordjevic, Djordje; Ramachandruni, Deepti; Singh, Abhyudai; Huang, Hongzhan

2018-01-01

Abstract Although successful in identifying new cataract-linked genes, the previous version of the database iSyTE (integrated Systems Tool for Eye gene discovery) was based on expression information on just three mouse lens stages and was functionally limited to visualization by only UCSC-Genome Browser tracks. To increase its efficacy, here we provide an enhanced iSyTE version 2.0 (URL: http://research.bioinformatics.udel.edu/iSyTE) based on well-curated, comprehensive genome-level lens expression data as a one-stop portal for the effective visualization and analysis of candidate genes in lens development and disease. iSyTE 2.0 includes all publicly available lens Affymetrix and Illumina microarray datasets representing a broad range of embryonic and postnatal stages from wild-type and specific gene-perturbation mouse mutants with eye defects. Further, we developed a new user-friendly web interface for direct access and cogent visualization of the curated expression data, which supports convenient searches and a range of downstream analyses. The utility of these new iSyTE 2.0 features is illustrated through examples of established genes associated with lens development and pathobiology, which serve as tutorials for its application by the end-user. iSyTE 2.0 will facilitate the prioritization of eye development and disease-linked candidate genes in studies involving transcriptomics or next-generation sequencing data, linkage analysis and GWAS approaches. PMID:29036527

Clinical value of miR-452-5p expression in lung adenocarcinoma: A retrospective quantitative real-time polymerase chain reaction study and verification based on The Cancer Genome Atlas and Gene Expression Omnibus databases.

PubMed

Gan, Xiao-Ning; Luo, Jie; Tang, Rui-Xue; Wang, Han-Lin; Zhou, Hong; Qin, Hui; Gan, Ting-Qing; Chen, Gang

2017-05-01

The role and mechanism of miR-452-5p in lung adenocarcinoma remain unclear. In this study, we performed a systematic study to investigate the clinical value of miR-452-5p expression in lung adenocarcinoma. The expression of miR-452-5p in 101 lung adenocarcinoma patients was detected by quantitative real-time polymerase chain reaction. The Cancer Genome Atlas and Gene Expression Omnibus databases were joined to verify the expression level of miR-452-5p in lung adenocarcinoma. Via several online prediction databases and bioinformatics software, pathway and network analyses of miR-452-5p target genes were performed to explore its prospective molecular mechanism. The expression of miR-452-5p in lung adenocarcinoma in house was significantly lower than that in adjacent tissues (p < 0.001). Additionally, the expression level of miR-452-5p was negatively correlated with several clinicopathological parameters including the tumor size (p = 0.014), lymph node metastasis (p = 0.032), and tumor-node-metastasis stage (p = 0.036). Data from The Cancer Genome Atlas also confirmed the low expression of miR-452 in lung adenocarcinoma (p < 0.001). Furthermore, reduced expression of miR-452-5p in lung adenocarcinoma (standard mean deviations = -0.393, 95% confidence interval: -0.774 to -0.011, p = 0.044) was validated by a meta-analysis. Five hub genes targeted by miR-452-5p, including SMAD family member 4, SMAD family member 2, cyclin-dependent kinase inhibitor 1B, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein epsilon, and tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein beta, were significantly enriched in the cell-cycle pathway. In conclusion, low expression of miR-452-5p tends to play an essential role in lung adenocarcinoma. Bioinformatics analysis might be beneficial to reveal the potential mechanism of miR-452-5p in lung adenocarcinoma.

Transcriptome analysis of duck liver and identification of differentially expressed transcripts in response to duck hepatitis A virus genotype C infection.

PubMed

Tang, Cheng; Lan, Daoliang; Zhang, Huanrong; Ma, Jing; Yue, Hua

2013-01-01

Duck is an economically important poultry and animal model for human viral hepatitis B. However, the molecular mechanisms underlying host-virus interaction remain unclear because of limited information on the duck genome. This study aims to characterize the duck normal liver transcriptome and to identify the differentially expressed transcripts at 24 h after duck hepatitis A virus genotype C (DHAV-C) infection using Illumina-Solexa sequencing. After removal of low-quality sequences and assembly, a total of 52,757 unigenes was obtained from the normal liver group. Further blast analysis showed that 18,918 unigenes successfully matched the known genes in the database. GO analysis revealed that 25,116 unigenes took part in 61 categories of biological processes, cellular components, and molecular functions. Among the 25 clusters of orthologous group categories (COG), the cluster for "General function prediction only" represented the largest group, followed by "Transcription" and "Replication, recombination, and repair." KEGG analysis showed that 17,628 unigenes were involved in 301 pathways. Through comparison of normal and infected transcriptome data, we identified 20 significantly differentially expressed unigenes, which were further confirmed by real-time polymerase chain reaction. Of the 20 unigenes, nine matched the known genes in the database, including three up-regulated genes (virus replicase polyprotein, LRRC3B, and PCK1) and six down-regulated genes (CRP, AICL-like 2, L1CAM, CYB26A1, CHAC1, and ADAM32). The remaining 11 novel unigenes that did not match any known genes in the database may provide a basis for the discovery of new transcripts associated with infection. This study provided a gene expression pattern for normal duck liver and for the previously unrecognized changes in gene transcription that are altered during DHAV-C infection. Our data revealed useful information for future studies on the duck genome and provided new insights into the molecular mechanism of host-DHAV-C interaction.

Generation and Analysis of a Large-Scale Expressed Sequence Tag Database from a Full-Length Enriched cDNA Library of Developing Leaves of Gossypium hirsutum L

PubMed Central

Pang, Chaoyou; Fan, Shuli; Song, Meizhen; Yu, Shuxun

2013-01-01

Background Cotton (Gossypium hirsutum L.) is one of the world’s most economically-important crops. However, its entire genome has not been sequenced, and limited resources are available in GenBank for understanding the molecular mechanisms underlying leaf development and senescence. Methodology/Principal Findings In this study, 9,874 high-quality ESTs were generated from a normalized, full-length cDNA library derived from pooled RNA isolated from throughout leaf development during the plant blooming stage. After clustering and assembly of these ESTs, 5,191 unique sequences, representative 1,652 contigs and 3,539 singletons, were obtained. The average unique sequence length was 682 bp. Annotation of these unique sequences revealed that 84.4% showed significant homology to sequences in the NCBI non-redundant protein database, and 57.3% had significant hits to known proteins in the Swiss-Prot database. Comparative analysis indicated that our library added 2,400 ESTs and 991 unique sequences to those known for cotton. The unigenes were functionally characterized by gene ontology annotation. We identified 1,339 and 200 unigenes as potential leaf senescence-related genes and transcription factors, respectively. Moreover, nine genes related to leaf senescence and eleven MYB transcription factors were randomly selected for quantitative real-time PCR (qRT-PCR), which revealed that these genes were regulated differentially during senescence. The qRT-PCR for three GhYLSs revealed that these genes express express preferentially in senescent leaves. Conclusions/Significance These EST resources will provide valuable sequence information for gene expression profiling analyses and functional genomics studies to elucidate their roles, as well as for studying the mechanisms of leaf development and senescence in cotton and discovering candidate genes related to important agronomic traits of cotton. These data will also facilitate future whole-genome sequence assembly and annotation in G. hirsutum and comparative genomics among Gossypium species. PMID:24146870

BIOSPIDA: A Relational Database Translator for NCBI

PubMed Central

Hagen, Matthew S.; Lee, Eva K.

2010-01-01

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time. PMID:21347013

A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages

PubMed Central

Yu, Ying; Fuscoe, James C.; Zhao, Chen; Guo, Chao; Jia, Meiwen; Qing, Tao; Bannon, Desmond I.; Lancashire, Lee; Bao, Wenjun; Du, Tingting; Luo, Heng; Su, Zhenqiang; Jones, Wendell D.; Moland, Carrie L.; Branham, William S.; Qian, Feng; Ning, Baitang; Li, Yan; Hong, Huixiao; Guo, Lei; Mei, Nan; Shi, Tieliu; Wang, Kevin Y.; Wolfinger, Russell D.; Nikolsky, Yuri; Walker, Stephen J.; Duerksen-Hughes, Penelope; Mason, Christopher E.; Tong, Weida; Thierry-Mieg, Jean; Thierry-Mieg, Danielle; Shi, Leming; Wang, Charles

2014-01-01

The rat has been used extensively as a model for evaluating chemical toxicities and for understanding drug mechanisms. However, its transcriptome across multiple organs, or developmental stages, has not yet been reported. Here we show, as part of the SEQC consortium efforts, a comprehensive rat transcriptomic BodyMap created by performing RNA-Seq on 320 samples from 11 organs of both sexes of juvenile, adolescent, adult and aged Fischer 344 rats. We catalogue the expression profiles of 40,064 genes, 65,167 transcripts, 31,909 alternatively spliced transcript variants and 2,367 non-coding genes/non-coding RNAs (ncRNAs) annotated in AceView. We find that organ-enriched, differentially expressed genes reflect the known organ-specific biological activities. A large number of transcripts show organ-specific, age-dependent or sex-specific differential expression patterns. We create a web-based, open-access rat BodyMap database of expression profiles with crosslinks to other widely used databases, anticipating that it will serve as a primary resource for biomedical research using the rat model. PMID:24510058

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

PubMed

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

2017-01-21

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

Zipf's Law in Gene Expression

NASA Astrophysics Data System (ADS)

Furusawa, Chikara; Kaneko, Kunihiko

2003-02-01

Using data from gene expression databases on various organisms and tissues, including yeast, nematodes, human normal and cancer tissues, and embryonic stem cells, we found that the abundances of expressed genes exhibit a power-law distribution with an exponent close to -1; i.e., they obey Zipf’s law. Furthermore, by simulations of a simple model with an intracellular reaction network, we found that Zipf’s law of chemical abundance is a universal feature of cells where such a network optimizes the efficiency and faithfulness of self-reproduction. These findings provide novel insights into the nature of the organization of reaction dynamics in living cells.

Characterization of transcriptome in the Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) and gene expression analysis during developmental stages.

PubMed

Tang, Pei-An; Wu, Hai-Jing; Xue, Hao; Ju, Xing-Rong; Song, Wei; Zhang, Qi-Lin; Yuan, Ming-Long

2017-07-30

The Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) is a worldwide pest that causes serious damage to stored foods. Although many efforts have been conducted on this species due to its economic importance, the study of genetic basis of development, behavior and insecticide resistance has been greatly hampered due to lack of genomic information. In this study, we used high throughput sequencing platform to perform a de novo transcriptome assembly and tag-based digital gene expression profiling (DGE) analyses across four different developmental stages of P. interpunctella (egg, third-instar larvae, pupae and adult). We obtained approximate 9gigabyte (GB) of clean data and recovered 84,938 unigenes, including 37,602 clusters and 47,336 singletons. These unigenes were annotated using BLAST against the non-redundant protein databases and then functionally classified based on Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes databases (KEGG). A large number of differentially expressed genes were identified by pairwise comparisons among different developmental stages. Gene expression profiles dramatically changed between developmental stage transitions. Some of these differentially expressed genes were related to digestion and cuticularization. Quantitative real-time PCR results of six randomly selected genes conformed the findings in the DGEs. Furthermore, we identified over 8000 microsatellite markers and 97,648 single nucleotide polymorphisms which will be useful for population genetics studies of P. interpunctella. This transcriptomic information provided insight into the developmental basis of P. interpunctella and will be helpful for establishing integrated management strategies and developing new targets of insecticides for this serious pest. Copyright © 2017 Elsevier B.V. All rights reserved.

Database resources of the National Center for Biotechnology Information: 2002 update

PubMed Central

Wheeler, David L.; Church, Deanna M.; Lash, Alex E.; Leipe, Detlef D.; Madden, Thomas L.; Pontius, Joan U.; Schuler, Gregory D.; Schriml, Lynn M.; Tatusova, Tatiana A.; Wagner, Lukas; Rapp, Barbara A.

2002-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources that operate on the data in GenBank and a variety of other biological data made available through NCBI’s web site. NCBI data retrieval resources include Entrez, PubMed, LocusLink and the Taxonomy Browser. Data analysis resources include BLAST, Electronic PCR, OrfFinder, RefSeq, UniGene, HomoloGene, Database of Single Nucleotide Polymorphisms (dbSNP), Human Genome Sequencing, Human MapViewer, Human¡VMouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB) and the Conserved Domain Database (CDD). Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov. PMID:11752242

Database resources of the National Center for Biotechnology Information.

PubMed

2016-01-04

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank(®) nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (PubMed Central (PMC), Bookshelf and PubReader), health (ClinVar, dbGaP, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen), genomes (BioProject, Assembly, Genome, BioSample, dbSNP, dbVar, Epigenomics, the Map Viewer, Nucleotide, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser and the Trace Archive), genes (Gene, Gene Expression Omnibus (GEO), HomoloGene, PopSet and UniGene), proteins (Protein, the Conserved Domain Database (CDD), COBALT, Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB) and Protein Clusters) and chemicals (Biosystems and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for most of these databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. Published by Oxford University Press on behalf of Nucleic Acids Research 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Database resources of the National Center for Biotechnology Information.

PubMed

2015-01-01

The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank(®) nucleic acid sequence database and the PubMed database of citations and abstracts for published life science journals. Additional NCBI resources focus on literature (Bookshelf, PubMed Central (PMC) and PubReader); medical genetics (ClinVar, dbMHC, the Genetic Testing Registry, HIV-1/Human Protein Interaction Database and MedGen); genes and genomics (BioProject, BioSample, dbSNP, dbVar, Epigenomics, Gene, Gene Expression Omnibus (GEO), Genome, HomoloGene, the Map Viewer, Nucleotide, PopSet, Probe, RefSeq, Sequence Read Archive, the Taxonomy Browser, Trace Archive and UniGene); and proteins and chemicals (Biosystems, COBALT, the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), the Molecular Modeling Database (MMDB), Protein Clusters, Protein and the PubChem suite of small molecule databases). The Entrez system provides search and retrieval operations for many of these databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Comprehensive Expression Map of Transcription Regulators in the Adult Zebrafish Telencephalon Reveals Distinct Neurogenic Niches

PubMed Central

Diotel, Nicolas; Rodriguez Viales, Rebecca; Armant, Olivier; März, Martin; Ferg, Marco; Rastegar, Sepand; Strähle, Uwe

2015-01-01

The zebrafish has become a model to study adult vertebrate neurogenesis. In particular, the adult telencephalon has been an intensely studied structure in the zebrafish brain. Differential expression of transcriptional regulators (TRs) is a key feature of development and tissue homeostasis. Here we report an expression map of 1,202 TR genes in the telencephalon of adult zebrafish. Our results are summarized in a database with search and clustering functions to identify genes expressed in particular regions of the telencephalon. We classified 562 genes into 13 distinct patterns, including genes expressed in the proliferative zone. The remaining 640 genes displayed unique and complex patterns of expression and could thus not be grouped into distinct classes. The neurogenic ventricular regions express overlapping but distinct sets of TR genes, suggesting regional differences in the neurogenic niches in the telencephalon. In summary, the small telencephalon of the zebrafish shows a remarkable complexity in TR gene expression. The adult zebrafish telencephalon has become a model to study neurogenesis. We established the expression pattern of more than 1200 transcription regulators (TR) in the adult telencephalon. The neurogenic regions express overlapping but distinct sets of TR genes suggesting regional differences in the neurogenic potential. J. Comp. Neurol. 523:1202–1221, 2015. © 2015 Wiley Periodicals, Inc. PMID:25556858

Comprehensive expression map of transcription regulators in the adult zebrafish telencephalon reveals distinct neurogenic niches.

PubMed

Diotel, Nicolas; Rodriguez Viales, Rebecca; Armant, Olivier; März, Martin; Ferg, Marco; Rastegar, Sepand; Strähle, Uwe

2015-06-01

The zebrafish has become a model to study adult vertebrate neurogenesis. In particular, the adult telencephalon has been an intensely studied structure in the zebrafish brain. Differential expression of transcriptional regulators (TRs) is a key feature of development and tissue homeostasis. Here we report an expression map of 1,202 TR genes in the telencephalon of adult zebrafish. Our results are summarized in a database with search and clustering functions to identify genes expressed in particular regions of the telencephalon. We classified 562 genes into 13 distinct patterns, including genes expressed in the proliferative zone. The remaining 640 genes displayed unique and complex patterns of expression and could thus not be grouped into distinct classes. The neurogenic ventricular regions express overlapping but distinct sets of TR genes, suggesting regional differences in the neurogenic niches in the telencephalon. In summary, the small telencephalon of the zebrafish shows a remarkable complexity in TR gene expression. The adult zebrafish telencephalon has become a model to study neurogenesis. We established the expression pattern of more than 1200 transcription regulators (TR) in the adult telencephalon. The neurogenic regions express overlapping but distinct sets of TR genes suggesting regional differences in the neurogenic potential. © 2015 Wiley Periodicals, Inc.

Transcriptome profiling analysis reveals biomarkers in colon cancer samples of various differentiation

PubMed Central

Yu, Tonghu; Zhang, Huaping; Qi, Hong

2018-01-01

The aim of the present study was to investigate more colon cancer-related genes in different stages. Gene expression profile E-GEOD-62932 was extracted for differentially expressed gene (DEG) screening. Series test of cluster analysis was used to obtain significant trending models. Based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, functional and pathway enrichment analysis were processed and a pathway relation network was constructed. Gene co-expression network and gene signal network were constructed for common DEGs. The DEGs with the same trend were clustered and in total, 16 clusters with statistical significance were obtained. The screened DEGs were enriched into small molecule metabolic process and metabolic pathways. The pathway relation network was constructed with 57 nodes. A total of 328 common DEGs were obtained. Gene signal network was constructed with 71 nodes. Gene co-expression network was constructed with 161 nodes and 211 edges. ABCD3, CPT2, AGL and JAM2 are potential biomarkers for the diagnosis of colon cancer. PMID:29928385

Differential expression of the nuclear-encoded mitochondrial transcriptome in pediatric septic shock.

PubMed

Weiss, Scott L; Cvijanovich, Natalie Z; Allen, Geoffrey L; Thomas, Neal J; Freishtat, Robert J; Anas, Nick; Meyer, Keith; Checchia, Paul A; Shanley, Thomas P; Bigham, Michael T; Fitzgerald, Julie; Banschbach, Sharon; Beckman, Eileen; Howard, Kelli; Frank, Erin; Harmon, Kelli; Wong, Hector R

2014-11-19

Increasing evidence supports a role for mitochondrial dysfunction in organ injury and immune dysregulation in sepsis. Although differential expression of mitochondrial genes in blood cells has been reported for several diseases in which bioenergetic failure is a postulated mechanism, there are no data about the blood cell mitochondrial transcriptome in pediatric sepsis. We conducted a focused analysis using a multicenter genome-wide expression database of 180 children ≤ 10 years of age with septic shock and 53 healthy controls. Using total RNA isolated from whole blood within 24 hours of PICU admission for septic shock, we evaluated 296 nuclear-encoded mitochondrial genes using a false discovery rate of 1%. A series of bioinformatic approaches were applied to compare differentially expressed genes across previously validated gene expression-based subclasses (groups A, B, and C) of pediatric septic shock. In total, 118 genes were differentially regulated in subjects with septic shock compared to healthy controls, including 48 genes that were upregulated and 70 that were downregulated. The top scoring canonical pathway was oxidative phosphorylation, with general downregulation of the 51 genes corresponding to the electron transport system (ETS). The top two gene networks were composed primarily of mitochondrial ribosomal proteins highly connected to ETS complex I, and genes encoding for ETS complexes I, II, and IV that were highly connected to the peroxisome proliferator activated receptor (PPAR) family. There were 162 mitochondrial genes differentially regulated between groups A, B, and C. Group A, which had the highest maximum number of organ failures and mortality, exhibited a greater downregulation of mitochondrial genes compared to groups B and C. Based on a focused analysis of a pediatric septic shock transcriptomic database, nuclear-encoded mitochondrial genes were differentially regulated early in pediatric septic shock compared to healthy controls, as well as across genotypic and phenotypic distinct pediatric septic shock subclasses. The nuclear genome may be an important mechanism contributing to alterations in mitochondrial bioenergetic function and outcomes in pediatric sepsis.

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

PubMed Central

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

2012-01-01

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

Current projects in Pre-analytics: where to go?

PubMed

Sapino, Anna; Annaratone, Laura; Marchiò, Caterina

2015-01-01

The current clinical practice of tissue handling and sample preparation is multifaceted and lacks strict standardisation: this scenario leads to significant variability in the quality of clinical samples. Poor tissue preservation has a detrimental effect thus leading to morphological artefacts, hampering the reproducibility of immunocytochemical and molecular diagnostic results (protein expression, DNA gene mutations, RNA gene expression) and affecting the research outcomes with irreproducible gene expression and post-transcriptional data. Altogether, this limits the opportunity to share and pool national databases into European common databases. At the European level, standardization of pre-analytical steps is just at the beginning and issues regarding bio-specimen collection and management are still debated. A joint (public-private) project entitled on standardization of tissue handling in pre-analytical procedures has been recently funded in Italy with the aim of proposing novel approaches to the neglected issue of pre-analytical procedures. In this chapter, we will show how investing in pre-analytics may impact both public health problems and practical innovation in solid tumour processing.

Analysis and functional annotation of expressed sequence tags from the fall armyworm Spodoptera frugiperda

PubMed Central

Deng, Youping; Dong, Yinghua; Thodima, Venkata; Clem, Rollie J; Passarelli, A Lorena

2006-01-01

Background Little is known about the genome sequences of lepidopteran insects, although this group of insects has been studied extensively in the fields of endocrinology, development, immunity, and pathogen-host interactions. In addition, cell lines derived from Spodoptera frugiperda and other lepidopteran insects are routinely used for baculovirus foreign gene expression. This study reports the results of an expressed sequence tag (EST) sequencing project in cells from the lepidopteran insect S. frugiperda, the fall armyworm. Results We have constructed an EST database using two cDNA libraries from the S. frugiperda-derived cell line, SF-21. The database consists of 2,367 ESTs which were assembled into 244 contigs and 951 singlets for a total of 1,195 unique sequences. Conclusion S. frugiperda is an agriculturally important pest insect and genomic information will be instrumental for establishing initial transcriptional profiling and gene function studies, and for obtaining information about genes manipulated during infections by insect pathogens such as baculoviruses. PMID:17052344

Scanning of Transposable Elements and Analyzing Expression of Transposase Genes of Sweet Potato [Ipomoea batatas

PubMed Central

Tao, Xiang; Lai, Xian-Jun; Zhang, Yi-Zheng; Tan, Xue-Mei; Wang, Haiyan

2014-01-01

Background Transposable elements (TEs) are the most abundant genomic components in eukaryotes and affect the genome by their replications and movements to generate genetic plasticity. Sweet potato performs asexual reproduction generally and the TEs may be an important genetic factor for genome reorganization. Complete identification of TEs is essential for the study of genome evolution. However, the TEs of sweet potato are still poorly understood because of its complex hexaploid genome and difficulty in genome sequencing. The recent availability of the sweet potato transcriptome databases provides an opportunity for discovering and characterizing the expressed TEs. Methodology/Principal Findings We first established the integrated-transcriptome database by de novo assembling four published sweet potato transcriptome databases from three cultivars in China. Using sequence-similarity search and analysis, a total of 1,405 TEs including 883 retrotransposons and 522 DNA transposons were predicted and categorized. Depending on mapping sets of RNA-Seq raw short reads to the predicted TEs, we compared the quantities, classifications and expression activities of TEs inter- and intra-cultivars. Moreover, the differential expressions of TEs in seven tissues of Xushu 18 cultivar were analyzed by using Illumina digital gene expression (DGE) tag profiling. It was found that 417 TEs were expressed in one or more tissues and 107 in all seven tissues. Furthermore, the copy number of 11 transposase genes was determined to be 1–3 copies in the genome of sweet potato by Real-time PCR-based absolute quantification. Conclusions/Significance Our result provides a new method for TE searching on species with transcriptome sequences while lacking genome information. The searching, identification and expression analysis of TEs will provide useful TE information in sweet potato, which are valuable for the further studies of TE-mediated gene mutation and optimization in asexual reproduction. It contributes to elucidating the roles of TEs in genome evolution. PMID:24608103

Conserved and Divergent Rhythms of Crassulacean Acid Metabolism-Related and Core Clock Gene Expression in the Cactus Opuntia ficus-indica1[C][W

PubMed Central

Mallona, Izaskun; Egea-Cortines, Marcos; Weiss, Julia

2011-01-01

The cactus Opuntia ficus-indica is a constitutive Crassulacean acid metabolism (CAM) species. Current knowledge of CAM metabolism suggests that the enzyme phosphoenolpyruvate carboxylase kinase (PPCK) is circadian regulated at the transcriptional level, whereas phosphoenolpyruvate carboxylase (PEPC), malate dehydrogenase (MDH), NADP-malic enzyme (NADP-ME), and pyruvate phosphate dikinase (PPDK) are posttranslationally controlled. As little transcriptomic data are available from obligate CAM plants, we created an expressed sequence tag database derived from different organs and developmental stages. Sequences were assembled, compared with sequences in the National Center for Biotechnology Information nonredundant database for identification of putative orthologs, and mapped using Kyoto Encyclopedia of Genes and Genomes Orthology and Gene Ontology. We identified genes involved in circadian regulation and CAM metabolism for transcriptomic analysis in plants grown in long days. We identified stable reference genes for quantitative polymerase chain reaction and found that OfiSAND, like its counterpart in Arabidopsis (Arabidopsis thaliana), and OfiTUB are generally appropriate standards for use in the quantification of gene expression in O. ficus-indica. Three kinds of expression profiles were found: transcripts of OfiPPCK oscillated with a 24-h periodicity; transcripts of the light-active OfiNADP-ME and OfiPPDK genes adapted to 12-h cycles, while transcript accumulation patterns of OfiPEPC and OfiMDH were arrhythmic. Expression of the circadian clock gene OfiTOC1, similar to Arabidopsis, oscillated with a 24-h periodicity, peaking at night. Expression of OfiCCA1 and OfiPRR9, unlike in Arabidopsis, adapted best to a 12-h rhythm, suggesting that circadian clock gene interactions differ from those of Arabidopsis. Our results indicate that the evolution of CAM metabolism could be the result of modified circadian regulation at both the transcriptional and posttranscriptional levels. PMID:21677095

Is chloroplastic class IIA aldolase a marine enzyme?

PubMed

Miyasaka, Hitoshi; Ogata, Takeru; Tanaka, Satoshi; Ohama, Takeshi; Kano, Sanae; Kazuhiro, Fujiwara; Hayashi, Shuhei; Yamamoto, Shinjiro; Takahashi, Hiro; Matsuura, Hideyuki; Hirata, Kazumasa

2016-11-01

Expressed sequence tag analyses revealed that two marine Chlorophyceae green algae, Chlamydomonas sp. W80 and Chlamydomonas sp. HS5, contain genes coding for chloroplastic class IIA aldolase (fructose-1, 6-bisphosphate aldolase: FBA). These genes show robust monophyly with those of the marine Prasinophyceae algae genera Micromonas, Ostreococcus and Bathycoccus, indicating that the acquisition of this gene through horizontal gene transfer by an ancestor of the green algal lineage occurred prior to the divergence of the core chlorophytes (Chlorophyceae and Trebouxiophyceae) and the prasinophytes. The absence of this gene in some freshwater chlorophytes, such as Chlamydomonas reinhardtii, Volvox carteri, Chlorella vulgaris, Chlorella variabilis and Coccomyxa subellipsoidea, can therefore be explained by the loss of this gene somewhere in the evolutionary process. Our survey on the distribution of this gene in genomic and transcriptome databases suggests that this gene occurs almost exclusively in marine algae, with a few exceptions, and as such, we propose that chloroplastic class IIA FBA is a marine environment-adapted enzyme. This hypothesis was also experimentally tested using Chlamydomonas W80, for which we found that the transcript levels of this gene to be significantly lower under low-salt (that is, simulated terrestrial) conditions. Expression analyses of transcriptome data for two algae, Prymnesium parvum and Emiliania huxleyi, taken from the Sequence Read Archive database also indicated that the expression of this gene under terrestrial conditions (low NaCl and low sulfate) is significantly downregulated. Thus, these experimental and transcriptome data provide support for our hypothesis.

Is chloroplastic class IIA aldolase a marine enzyme?

PubMed Central

Miyasaka, Hitoshi; Ogata, Takeru; Tanaka, Satoshi; Ohama, Takeshi; Kano, Sanae; Kazuhiro, Fujiwara; Hayashi, Shuhei; Yamamoto, Shinjiro; Takahashi, Hiro; Matsuura, Hideyuki; Hirata, Kazumasa

2016-01-01

Expressed sequence tag analyses revealed that two marine Chlorophyceae green algae, Chlamydomonas sp. W80 and Chlamydomonas sp. HS5, contain genes coding for chloroplastic class IIA aldolase (fructose-1, 6-bisphosphate aldolase: FBA). These genes show robust monophyly with those of the marine Prasinophyceae algae genera Micromonas, Ostreococcus and Bathycoccus, indicating that the acquisition of this gene through horizontal gene transfer by an ancestor of the green algal lineage occurred prior to the divergence of the core chlorophytes (Chlorophyceae and Trebouxiophyceae) and the prasinophytes. The absence of this gene in some freshwater chlorophytes, such as Chlamydomonas reinhardtii, Volvox carteri, Chlorella vulgaris, Chlorella variabilis and Coccomyxa subellipsoidea, can therefore be explained by the loss of this gene somewhere in the evolutionary process. Our survey on the distribution of this gene in genomic and transcriptome databases suggests that this gene occurs almost exclusively in marine algae, with a few exceptions, and as such, we propose that chloroplastic class IIA FBA is a marine environment-adapted enzyme. This hypothesis was also experimentally tested using Chlamydomonas W80, for which we found that the transcript levels of this gene to be significantly lower under low-salt (that is, simulated terrestrial) conditions. Expression analyses of transcriptome data for two algae, Prymnesium parvum and Emiliania huxleyi, taken from the Sequence Read Archive database also indicated that the expression of this gene under terrestrial conditions (low NaCl and low sulfate) is significantly downregulated. Thus, these experimental and transcriptome data provide support for our hypothesis. PMID:27058504

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

Cytokinin oxidase/dehydrogenase genes in barley and wheat: cloning and heterologous expression.

PubMed

Galuszka, Petr; Frébortová, Jitka; Werner, Tomás; Yamada, Mamoru; Strnad, Miroslav; Schmülling, Thomas; Frébort, Ivo

2004-10-01

The cloning of two novel genes that encode cytokinin oxidase/dehydrogenase (CKX) in barley is described in this work. Transformation of both genes into Arabidopsis and tobacco showed that at least one of the genes codes for a functional enzyme, as its expression caused a cytokinin-deficient phenotype in the heterologous host plants. Additional cloning of two gene fragments, and an in silico search in the public expressed sequence tag clone databases, revealed the presence of at least 13 more members of the CKX gene family in barley and wheat. The expression of three selected barley genes was analyzed by RT-PCR and found to be organ-specific with peak expression in mature kernels. One barley CKX (HvCKX2) was characterized in detail after heterologous expression in tobacco. Interestingly, this enzyme shows a pH optimum at 4.5 and a preference for cytokinin ribosides as substrates, which may indicate its vacuolar targeting. Different substrate specificities, and the pH profiles of cytokinin-degrading enzymes extracted from different barley tissues, are also presented.

A statistical approach to identify, monitor, and manage incomplete curated data sets.

PubMed

Howe, Douglas G

2018-04-02

Many biological knowledge bases gather data through expert curation of published literature. High data volume, selective partial curation, delays in access, and publication of data prior to the ability to curate it can result in incomplete curation of published data. Knowing which data sets are incomplete and how incomplete they are remains a challenge. Awareness that a data set may be incomplete is important for proper interpretation, to avoiding flawed hypothesis generation, and can justify further exploration of published literature for additional relevant data. Computational methods to assess data set completeness are needed. One such method is presented here. In this work, a multivariate linear regression model was used to identify genes in the Zebrafish Information Network (ZFIN) Database having incomplete curated gene expression data sets. Starting with 36,655 gene records from ZFIN, data aggregation, cleansing, and filtering reduced the set to 9870 gene records suitable for training and testing the model to predict the number of expression experiments per gene. Feature engineering and selection identified the following predictive variables: the number of journal publications; the number of journal publications already attributed for gene expression annotation; the percent of journal publications already attributed for expression data; the gene symbol; and the number of transgenic constructs associated with each gene. Twenty-five percent of the gene records (2483 genes) were used to train the model. The remaining 7387 genes were used to test the model. One hundred and twenty-two and 165 of the 7387 tested genes were identified as missing expression annotations based on their residuals being outside the model lower or upper 95% confidence interval respectively. The model had precision of 0.97 and recall of 0.71 at the negative 95% confidence interval and precision of 0.76 and recall of 0.73 at the positive 95% confidence interval. This method can be used to identify data sets that are incompletely curated, as demonstrated using the gene expression data set from ZFIN. This information can help both database resources and data consumers gauge when it may be useful to look further for published data to augment the existing expertly curated information.

Metallopeptidases of Toxoplasma gondii: in silico identification and gene expression.

PubMed

Escotte-Binet, Sandie; Huguenin, Antoine; Aubert, Dominique; Martin, Anne-Pascaline; Kaltenbach, Matthieu; Florent, Isabelle; Villena, Isabelle

2018-01-01

Metallopeptidases are a family of proteins with domains that remain highly conserved throughout evolution. These hydrolases require divalent metal cation(s) to activate the water molecule in order to carry out their catalytic action on peptide bonds by nucleophilic attack. Metallopeptidases from parasitic protozoa, including Toxoplasma, are investigated because of their crucial role in parasite biology. In the present study, we screened the T. gondii database using PFAM motifs specific for metallopeptidases in association with the MEROPS peptidase Database (release 10.0). In all, 49 genes encoding proteins with metallopeptidase signatures were identified in the Toxoplasma genome. An Interpro Search enabled us to uncover their domain/motif organization, and orthologs with the highest similarity by BLAST were used for annotation. These 49 Toxoplasma metallopeptidases clustered into 15 families described in the MEROPS database. Experimental expression analysis of their genes in the tachyzoite stage revealed transcription for all genes studied. Further research on the role of these peptidases should increase our knowledge of basic Toxoplasma biology and provide opportunities to identify novel therapeutic targets. This type of study would also open a path towards the comparative biology of apicomplexans. © S. Escotte-Binet et al., published by EDP Sciences, 2018.

Tissue Molecular Anatomy Project (TMAP): an expression database for comparative cancer proteomics.

PubMed

Medjahed, Djamel; Luke, Brian T; Tontesh, Tawady S; Smythers, Gary W; Munroe, David J; Lemkin, Peter F

2003-08-01

By mining publicly accessible databases, we have developed a collection of tissue-specific predictive protein expression maps as a function of cancer histological state. Data analysis is applied to the differential expression of gene products in pooled libraries from the normal to the altered state(s). We wish to report the initial results of our survey across different tissues and explore the extent to which this comparative approach may help uncover panels of potential biomarkers of tumorigenesis which would warrant further examination in the laboratory.

A maize database resource that captures tissue-specific and subcellular-localized gene expression, via fluorescent tags and confocal imaging (Maize Cell Genomics Database).

PubMed

Krishnakumar, Vivek; Choi, Yongwook; Beck, Erin; Wu, Qingyu; Luo, Anding; Sylvester, Anne; Jackson, David; Chan, Agnes P

2015-01-01

Maize is a global crop and a powerful system among grain crops for genetic and genomic studies. However, the development of novel biological tools and resources to aid in the functional identification of gene sequences is greatly needed. Towards this goal, we have developed a collection of maize marker lines for studying native gene expression in specific cell types and subcellular compartments using fluorescent proteins (FPs). To catalog FP expression, we have developed a public repository, the Maize Cell Genomics (MCG) Database, (http://maize.jcvi.org/cellgenomics), to organize a large data set of confocal images generated from the maize marker lines. To date, the collection represents major subcellular structures and also developmentally important progenitor cell populations. The resource is available to the research community, for example to study protein localization or interactions under various experimental conditions or mutant backgrounds. A subset of the marker lines can also be used to induce misexpression of target genes through a transactivation system. For future directions, the image repository can be expanded to accept new image submissions from the research community, and to perform customized large-scale computational image analysis. This community resource will provide a suite of new tools for gaining biological insights by following the dynamics of protein expression at the subcellular, cellular and tissue levels. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Identification of potential crucial genes associated with steroid-induced necrosis of femoral head based on gene expression profile.

PubMed

Lin, Zhe; Lin, Yongsheng

2017-09-05

The aim of this study was to explore potential crucial genes associated with the steroid-induced necrosis of femoral head (SINFH) and to provide valid biological information for further investigation of SINFH. Gene expression profile of GSE26316, generated from 3 SINFH rat samples and 3 normal rat samples were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using LIMMA package. After functional enrichment analyses of DEGs, protein-protein interaction (PPI) network and sub-PPI network analyses were conducted based on the STRING database and cytoscape. In total, 59 up-regulated DEGs and 156 downregulated DEGs were identified. The up-regulated DEGs were mainly involved in functions about immunity (e.g. Fcer1A and Il7R), and the downregulated DEGs were mainly enriched in muscle system process (e.g. Tnni2, Mylpf and Myl1). The PPI network of DEGs consisted of 123 nodes and 300 interactions. Tnni2, Mylpf, and Myl1 were the top 3 outstanding genes based on both subgraph centrality and degree centrality evaluation. These three genes interacted with each other in the network. Furthermore, the significant network module was composed of 22 downregulated genes (e.g. Tnni2, Mylpf and Myl1). These genes were mainly enriched in functions like muscle system process. The DEGs related to the regulation of immune system process (e.g. Fcer1A and Il7R), and DEGs correlated with muscle system process (e.g. Tnni2, Mylpf and Myl1) may be closely associated with the progress of SINFH, which is still needed to be confirmed by experiments. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of pathogenic genes related to rheumatoid arthritis through integrated analysis of DNA methylation and gene expression profiling.

PubMed

Zhang, Lei; Ma, Shiyun; Wang, Huailiang; Su, Hang; Su, Ke; Li, Longjie

2017-11-15

The purpose of our study was to identify new pathogenic genes used for exploring the pathogenesis of rheumatoid arthritis (RA). To screen pathogenic genes of RA, an integrated analysis was performed by using the microarray datasets in RA 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. Afterwards, the integrated analysis of DNA methylation and gene expression profiling was used to screen crucial genes. In addition, we used RT-PCR and MSP to verify the expression levels and methylation status of these crucial genes in 20 synovial biopsy samples obtained from 10 RA model mice and 10 normal mice. BCL11B, CCDC88C, FCRLA and APOL6 were both up-regulated and hypomethylated in RA according to integrated analysis, RT-PCR and MSP verification. Four crucial genes (BCL11B, CCDC88C, FCRLA and APOL6) identified and analyzed in this study might be closely connected with the pathogenesis of RA. Copyright © 2017. Published by Elsevier B.V.

New extension software modules to enhance searching and display of transcriptome data in Tripal databases

PubMed Central

Chen, Ming; Henry, Nathan; Almsaeed, Abdullah; Zhou, Xiao; Wegrzyn, Jill; Ficklin, Stephen

2017-01-01

Abstract Tripal is an open source software package for developing biological databases with a focus on genetic and genomic data. It consists of a set of core modules that deliver essential functions for loading and displaying data records and associated attributes including organisms, sequence features and genetic markers. Beyond the core modules, community members are encouraged to contribute extension modules to build on the Tripal core and to customize Tripal for individual community needs. To expand the utility of the Tripal software system, particularly for RNASeq data, we developed two new extension modules. Tripal Elasticsearch enables fast, scalable searching of the entire content of a Tripal site as well as the construction of customized advanced searches of specific data types. We demonstrate the use of this module for searching assembled transcripts by functional annotation. A second module, Tripal Analysis Expression, houses and displays records from gene expression assays such as RNA sequencing. This includes biological source materials (biomaterials), gene expression values and protocols used to generate the data. In the case of an RNASeq experiment, this would reflect the individual organisms and tissues used to produce sequencing libraries, the normalized gene expression values derived from the RNASeq data analysis and a description of the software or code used to generate the expression values. The module will load data from common flat file formats including standard NCBI Biosample XML. Data loading, display options and other configurations can be controlled by authorized users in the Drupal administrative backend. Both modules are open source, include usage documentation, and can be found in the Tripal organization’s GitHub repository. Database URL: Tripal Elasticsearch module: https://github.com/tripal/tripal_elasticsearch Tripal Analysis Expression module: https://github.com/tripal/tripal_analysis_expression PMID:29220446

SASD: the Synthetic Alternative Splicing Database for identifying novel isoform from proteomics

PubMed Central

2013-01-01

Background Alternative splicing is an important and widespread mechanism for generating protein diversity and regulating protein expression. High-throughput identification and analysis of alternative splicing in the protein level has more advantages than in the mRNA level. The combination of alternative splicing database and tandem mass spectrometry provides a powerful technique for identification, analysis and characterization of potential novel alternative splicing protein isoforms from proteomics. Therefore, based on the peptidomic database of human protein isoforms for proteomics experiments, our objective is to design a new alternative splicing database to 1) provide more coverage of genes, transcripts and alternative splicing, 2) exclusively focus on the alternative splicing, and 3) perform context-specific alternative splicing analysis. Results We used a three-step pipeline to create a synthetic alternative splicing database (SASD) to identify novel alternative splicing isoforms and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. First, we extracted information on gene structures of all genes in the Ensembl Genes 71 database and incorporated the Integrated Pathway Analysis Database. Then, we compiled artificial splicing transcripts. Lastly, we translated the artificial transcripts into alternative splicing peptides. The SASD is a comprehensive database containing 56,630 genes (Ensembl gene IDs), 95,260 transcripts (Ensembl transcript IDs), and 11,919,779 Alternative Splicing peptides, and also covering about 1,956 pathways, 6,704 diseases, 5,615 drugs, and 52 organs. The database has a web-based user interface that allows users to search, display and download a single gene/transcript/protein, custom gene set, pathway, disease, drug, organ related alternative splicing. Moreover, the quality of the database was validated with comparison to other known databases and two case studies: 1) in liver cancer and 2) in breast cancer. Conclusions The SASD provides the scientific community with an efficient means to identify, analyze, and characterize novel Exon Skipping and Intron Retention protein isoforms from mass spectrometry and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. PMID:24267658

Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors.

PubMed

Ma, W; Zhang, T-F; Lu, P; Lu, S H

2014-01-01

Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients. With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis. We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1. Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.

RiceMetaSys for salt and drought stress responsive genes in rice: a web interface for crop improvement.

PubMed

Sandhu, Maninder; Sureshkumar, V; Prakash, Chandra; Dixit, Rekha; Solanke, Amolkumar U; Sharma, Tilak Raj; Mohapatra, Trilochan; S V, Amitha Mithra

2017-09-30

Genome-wide microarray has enabled development of robust databases for functional genomics studies in rice. However, such databases do not directly cater to the needs of breeders. Here, we have attempted to develop a web interface which combines the information from functional genomic studies across different genetic backgrounds with DNA markers so that they can be readily deployed in crop improvement. In the current version of the database, we have included drought and salinity stress studies since these two are the major abiotic stresses in rice. RiceMetaSys, a user-friendly and freely available web interface provides comprehensive information on salt responsive genes (SRGs) and drought responsive genes (DRGs) across genotypes, crop development stages and tissues, identified from multiple microarray datasets. 'Physical position search' is an attractive tool for those using QTL based approach for dissecting tolerance to salt and drought stress since it can provide the list of SRGs and DRGs in any physical interval. To identify robust candidate genes for use in crop improvement, the 'common genes across varieties' search tool is useful. Graphical visualization of expression profiles across genes and rice genotypes has been enabled to facilitate the user and to make the comparisons more impactful. Simple Sequence Repeat (SSR) search in the SRGs and DRGs is a valuable tool for fine mapping and marker assisted selection since it provides primers for survey of polymorphism. An external link to intron specific markers is also provided for this purpose. Bulk retrieval of data without any limit has been enabled in case of locus and SSR search. The aim of this database is to facilitate users with a simple and straight-forward search options for identification of robust candidate genes from among thousands of SRGs and DRGs so as to facilitate linking variation in expression profiles to variation in phenotype. Database URL: http://14.139.229.201.

Analyzing Gene Expression Profiles with Preliminary Validations in Cardiac Hypertrophy Induced by Pressure-overload.

PubMed

Gao, Jing; Li, Yuhong; Wang, Tongmei; Shi, Zhuo; Zhang, Yiqi; Liu, Shuang; Wen, Pushuai; Ma, Chunyan

2018-03-06

The aim of this study was to identify the key genes involved in the cardiac hypertrophy (CH) induced by pressure overload. mRNA microarray dataset GSE5500 and GSE18801 were downloaded from GEO database, and differentially expressed genes (DEGs) were screened using Limma package; then, functional and pathway enrichment analysis were performed for common DEGs using DAVID database. Furthermore, the top DEGs were further validated using qPCR in the hypertrophic heart tissue induced by Isoprenaline (ISO). A total of 113 common DEGs with absolute fold change >0.5, including 60 significantly up-regulated DEGs and 53 down-regulated DEGs were obtained. GO term enrichment analysis suggested that common up-regulated DEG mainly enriched in neutrophil chemotaxis, extracellular fibril organization and cell proliferation, and the common down-regulated genes were significantly enriched in ion transport, endoplasmic reticulum and dendritic spine. KEGG pathway analysis found that the common DEGs were mainly enriched in ECM-receptor interaction, phagosome, and focal adhesion. Additionally, the expression of Mfap4, Ltbp2, Aspn, Serpina3n, and Cnksr1 were up-regulated in the model of cardiac hypertrophy, while the expression of Anp32a was down-regulated. The current study identified the key deregulated genes and pathways involved in the CH, which could shed new light to understand the mechanism of CH.

Expression Atlas: gene and protein expression across multiple studies and organisms

PubMed Central

Tang, Y Amy; Bazant, Wojciech; Burke, Melissa; Fuentes, Alfonso Muñoz-Pomer; George, Nancy; Koskinen, Satu; Mohammed, Suhaib; Geniza, Matthew; Preece, Justin; Jarnuczak, Andrew F; Huber, Wolfgang; Stegle, Oliver; Brazma, Alvis; Petryszak, Robert

2018-01-01

Abstract Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions. PMID:29165655

Analysis of 10,000 ESTs from lymphocytes of the cynomolgus monkey to improve our understanding of its immune system

PubMed Central

Chen, Wei-Hua; Wang, Xue-Xia; Lin, Wei; He, Xiao-Wei; Wu, Zhen-Qiang; Lin, Ying; Hu, Song-Nian; Wang, Xiao-Ning

2006-01-01

Background The cynomolgus monkey (Macaca fascicularis) is one of the most widely used surrogate animal models for an increasing number of human diseases and vaccines, especially immune-system-related ones. Towards a better understanding of the gene expression background upon its immunogenetics, we constructed a cDNA library from Epstein-Barr virus (EBV)-transformed B lymphocytes of a cynomolgus monkey and sequenced 10,000 randomly picked clones. Results After processing, 8,312 high-quality expressed sequence tags (ESTs) were generated and assembled into 3,728 unigenes. Annotations of these uniquely expressed transcripts demonstrated that out of the 2,524 open reading frame (ORF) positive unigenes (mitochondrial and ribosomal sequences were not included), 98.8% shared significant similarities (E-value less than 1e-10) with the NCBI nucleotide (nt) database, while only 67.7% (E-value less than 1e-5) did so with the NCBI non-redundant protein (nr) database. Further analysis revealed that 90.0% of the unigenes that shared no similarities to the nr database could be assigned to human chromosomes, in which 75 did not match significantly to any cynomolgus monkey and human ESTs. The mapping regions to known human genes on the human genome were described in detail. The protein family and domain analysis revealed that the first, second and fourth of the most abundantly expressed protein families were all assigned to immunoglobulin and major histocompatibility complex (MHC)-related proteins. The expression profiles of these genes were compared with that of homologous genes in human blood, lymph nodes and a RAMOS cell line, which demonstrated expression changes after transformation with EBV. The degree of sequence similarity of the MHC class I and II genes to the human reference sequences was evaluated. The results indicated that class I molecules showed weak amino acid identities (<90%), while class II showed slightly higher ones. Conclusion These results indicated that the genes expressed in the cynomolgus monkey could be used to identify novel protein-coding genes and revise those incomplete or incorrect annotations in the human genome by comparative methods, since the old world monkeys and humans share high similarities at the molecular level, especially within coding regions. The identification of multiple genes involved in the immune response, their sequence variations to the human homologues, and their responses to EBV infection could provide useful information to improve our understanding of the cynomolgus monkey immune system. PMID:16618371

Identification and expression of the WRKY transcription factors of Carica papaya in response to abiotic and biotic stresses.

PubMed

Pan, Lin-Jie; Jiang, Ling

2014-03-01

The WRKY transcription factor (TF) plays a very important role in the response of plants to various abiotic and biotic stresses. A local papaya database was built according to the GenBank expressed sequence tag database using the BioEdit software. Fifty-two coding sequences of Carica papaya WRKY TFs were predicted using the tBLASTn tool. The phylogenetic tree of the WRKY proteins was classified. The expression profiles of 13 selected C. papaya WRKY TF genes under stress induction were constructed by quantitative real-time polymerase chain reaction. The expression levels of these WRKY genes in response to 3 abiotic and 2 biotic stresses were evaluated. TF807.3 and TF72.14 are upregulated by low temperature; TF807.3, TF43.76, TF12.199 and TF12.62 are involved in the response to drought stress; TF9.35, TF18.51, TF72.14 and TF12.199 is involved in response to wound; TF12.199, TF807.3, TF21.156 and TF18.51 was induced by PRSV pathogen; TF72.14 and TF43.76 are upregulated by SA. The regulated expression levels of above eight genes normalized against housekeeping gene actin were significant at probability of 0.01 levels. These WRKY TFs could be related to corresponding stress resistance and selected as the candidate genes, especially, the two genes TF807.3 and TF12.199, which were regulated notably by four stresses respectively. This study may provide useful information and candidate genes for the development of transgenic stress tolerant papaya varieties.

Directed random walks and constraint programming reveal active pathways in hepatocyte growth factor signaling.

PubMed

Kittas, Aristotelis; Delobelle, Aurélien; Schmitt, Sabrina; Breuhahn, Kai; Guziolowski, Carito; Grabe, Niels

2016-01-01

An effective means to analyze mRNA expression data is to take advantage of established knowledge from pathway databases, using methods such as pathway-enrichment analyses. However, pathway databases are not case-specific and expression data could be used to infer gene-regulation patterns in the context of specific pathways. In addition, canonical pathways may not always describe the signaling mechanisms properly, because interactions can frequently occur between genes in different pathways. Relatively few methods have been proposed to date for generating and analyzing such networks, preserving the causality between gene interactions and reasoning over the qualitative logic of regulatory effects. We present an algorithm (MCWalk) integrated with a logic programming approach, to discover subgraphs in large-scale signaling networks by random walks in a fully automated pipeline. As an exemplary application, we uncover the signal transduction mechanisms in a gene interaction network describing hepatocyte growth factor-stimulated cell migration and proliferation from gene-expression measured with microarray and RT-qPCR using in-house perturbation experiments in a keratinocyte-fibroblast co-culture. The resulting subgraphs illustrate possible associations of hepatocyte growth factor receptor c-Met nodes, differentially expressed genes and cellular states. Using perturbation experiments and Answer Set programming, we are able to select those which are more consistent with the experimental data. We discover key regulator nodes by measuring the frequency with which they are traversed when connecting signaling between receptors and significantly regulated genes and predict their expression-shift consistently with the measured data. The Java implementation of MCWalk is publicly available under the MIT license at: https://bitbucket.org/akittas/biosubg. © 2015 FEBS.

Target gene screening and evaluation of prognostic values in non-small cell lung cancers by bioinformatics analysis.

PubMed

Piao, Junjie; Sun, Jie; Yang, Yang; Jin, Tiefeng; Chen, Liyan; Lin, Zhenhua

2018-03-20

Non-small cell lung cancer (NSCLC) is the major leading cause of cancer-related deaths worldwide. This study aims to explore molecular mechanism of NSCLC. Microarray dataset was obtained from the Gene Expression Omnibus (GEO) database, and analyzed by using GEO2R. Functional and pathway enrichment analysis were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Then, STRING, Cytoscape and MCODE were applied to construct the Protein-protein interaction (PPI) network and screen hub genes. Following, overall survival (OS) analysis of hub genes was performed by using the Kaplan-Meier plotter online tool. Moreover, miRecords was also applied to predict the targets of the differentially expressed microRNAs (DEMs). A total of 228 DEGs were identified, and they were mainly enriched in the terms of cell adhesion molecules, leukocyte transendothelial migration and ECM-receptor interaction. A PPI network was constructed, and 16 hub genes were identified, including TEK, ANGPT1, MMP9, VWF, CDH5, EDN1, ESAM, CCNE1, CDC45, PRC1, CCNB2, AURKA, MELK, CDC20, TOP2A and PTTG1. Among the genes, expressions of 14 hub genes were associated with prognosis of NSCLC patients. Additionally, a total of 11 DEMs were also identified. Our results provide some potential underlying biomarkers for NSCLC. Further studies are required to elucidate the pathogenesis of NSCLC. Copyright © 2018 Elsevier B.V. All rights reserved.

The database on transgenic luminescent microorganisms as an instrument of studying a microbial component of closed ecosystems

NASA Astrophysics Data System (ADS)

Boyandin, A. N.; Lankin, Y. P.; Kargatova, T. V.; Popova, L. Y.; Pechurkin, N. S.

Luminescent transgenic microorganisms are widely used for study of microbial communities' functioning including closed ones. Bioluminescence is of high sensitive to effects of different environmental factors. Integration of lux-genes into different metabolic ways allows studying many aspects of microorganisms' life permitting to carry out measurements in situ. There is much information about applications of bioluminescent bacteria in different researches. But for effective using these data their summarizing and accumulation in common source is required. Therefore an information system on characteristics of transgenic microorganisms with cloned lux-genes was created. The database and client software related were developed. A database structure includes information on common characteristics of cloned lux-genes, their sources and properties, on regulation of gene expression in bacterial cells, on dependence of bioluminescence manifestation on biotic, abiotic and anthropogenic environmental factors. The database also can store description of changes in bacterial populations depending on environmental changes. The database created allows storing and using bibliographic information and also links to web sites of world collections of microorganisms. Internet publishing software permitting to open access to the database through the Internet is developed.

Database resources of the National Center for Biotechnology Information

PubMed Central

Sayers, Eric W.; Barrett, Tanya; Benson, Dennis A.; Bolton, Evan; Bryant, Stephen H.; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M.; DiCuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M.; Geer, Lewis Y.; Helmberg, Wolfgang; Kapustin, Yuri; Krasnov, Sergey; Landsman, David; Lipman, David J.; Lu, Zhiyong; Madden, Thomas L.; Madej, Tom; Maglott, Donna R.; Marchler-Bauer, Aron; Miller, Vadim; Karsch-Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D.; Schuler, Gregory D.; Sequeira, Edwin; Sherry, Stephen T.; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A.; Wagner, Lukas; Wang, Yanli; Wilbur, W. John; Yaschenko, Eugene; Ye, Jian

2012-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov. PMID:22140104

Database resources of the National Center for Biotechnology Information

PubMed Central

2013-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page. PMID:23193264

Database resources of the National Center for Biotechnology Information.

PubMed

Wheeler, David L; Barrett, Tanya; Benson, Dennis A; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Geer, Lewis Y; Kapustin, Yuri; Khovayko, Oleg; Landsman, David; Lipman, David J; Madden, Thomas L; Maglott, Donna R; Ostell, James; Miller, Vadim; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Steven T; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusov, Roman L; Tatusova, Tatiana A; Wagner, Lukas; Yaschenko, Eugene

2007-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, My NCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link(BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genome, Genome Project and related tools, the Trace and Assembly Archives, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Viral Genotyping Tools, Influenza Viral Resources, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. These resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Edgar, Ron; Federhen, Scott; Feolo, Michael; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Landsman, David; Lipman, David J; Madden, Thomas L; Maglott, Donna R; Miller, Vadim; Mizrachi, Ilene; Ostell, James; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Yaschenko, Eugene; Ye, Jian

2009-01-01

In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the web applications is custom implementation of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

PubMed Central

He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai

2017-01-01

The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF. PMID:28713939

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

PubMed

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

2016-11-01

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

RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse

PubMed Central

Liu, Zhi-Ping; Wu, Canglin; Miao, Hongyu; Wu, Hulin

2015-01-01

Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places. Therefore, in this work, we build a knowledge-based database, named ‘RegNetwork’, of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future. Based on RegNetwork, we characterized the statistical and topological properties of genome-wide regulatory networks for human and mouse, we also extracted and interpreted simple yet important network motifs that involve the interplays between TF-miRNA and their targets. In summary, RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data. Database URL: http://www.regnetworkweb.org PMID:26424082

Cloning, analysis and functional annotation of expressed sequence tags from the Earthworm Eisenia fetida

PubMed Central

Pirooznia, Mehdi; Gong, Ping; Guan, Xin; Inouye, Laura S; Yang, Kuan; Perkins, Edward J; Deng, Youping

2007-01-01

Background Eisenia fetida, commonly known as red wiggler or compost worm, belongs to the Lumbricidae family of the Annelida phylum. Little is known about its genome sequence although it has been extensively used as a test organism in terrestrial ecotoxicology. In order to understand its gene expression response to environmental contaminants, we cloned 4032 cDNAs or expressed sequence tags (ESTs) from two E. fetida libraries enriched with genes responsive to ten ordnance related compounds using suppressive subtractive hybridization-PCR. Results A total of 3144 good quality ESTs (GenBank dbEST accession number EH669363–EH672369 and EL515444–EL515580) were obtained from the raw clone sequences after cleaning. Clustering analysis yielded 2231 unique sequences including 448 contigs (from 1361 ESTs) and 1783 singletons. Comparative genomic analysis showed that 743 or 33% of the unique sequences shared high similarity with existing genes in the GenBank nr database. Provisional function annotation assigned 830 Gene Ontology terms to 517 unique sequences based on their homology with the annotated genomes of four model organisms Drosophila melanogaster, Mus musculus, Saccharomyces cerevisiae, and Caenorhabditis elegans. Seven percent of the unique sequences were further mapped to 99 Kyoto Encyclopedia of Genes and Genomes pathways based on their matching Enzyme Commission numbers. All the information is stored and retrievable at a highly performed, web-based and user-friendly relational database called EST model database or ESTMD version 2. Conclusion The ESTMD containing the sequence and annotation information of 4032 E. fetida ESTs is publicly accessible at . PMID:18047730

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

PubMed Central

2013-01-01

Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200

Microarray‑based bioinformatics analysis of the prospective target gene network of key miRNAs influenced by long non‑coding RNA PVT1 in HCC.

PubMed

Zhang, Yu; Mo, Wei-Jia; Wang, Xiao; Zhang, Tong-Tong; Qin, Yuan; Wang, Han-Lin; Chen, Gang; Wei, Dan-Ming; Dang, Yi-Wu

2018-05-02

The long non‑coding RNA (lncRNA) PVT1 plays vital roles in the tumorigenesis and development of various types of cancer. However, the potential expression profiling, functions and pathways of PVT1 in HCC remain unknown. PVT1 was knocked down in SMMC‑7721 cells, and a miRNA microarray analysis was performed to detect the differentially expressed miRNAs. Twelve target prediction algorithms were used to predict the underlying targets of these differentially expressed miRNAs. Bioinformatics analysis was performed to explore the underlying functions, pathways and networks of the targeted genes. Furthermore, the relationship between PVT1 and the clinical parameters in HCC was confirmed based on the original data in the TCGA database. Among the differentially expressed miRNAs, the top two upregulated and downregulated miRNAs were selected for further analysis based on the false discovery rate (FDR), fold‑change (FC) and P‑values. Based on the TCGA database, PVT1 was obviously highly expressed in HCC, and a statistically higher PVT1 expression was found for sex (male), ethnicity (Asian) and pathological grade (G3+G4) compared to the control groups (P<0.05). Furthermore, Gene Ontology (GO) analysis revealed that the target genes were involved in complex cellular pathways, such as the macromolecule biosynthetic process, compound metabolic process, and transcription. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the MAPK and Wnt signaling pathways may be correlated with the regulation of the four candidate miRNAs. The results therefore provide significant information on the differentially expressed miRNAs associated with PVT1 in HCC, and we hypothesized that PVT1 may play vital roles in HCC by regulating different miRNAs or target gene expression (particularly MAPK8) via the MAPK or Wnt signaling pathways. Thus, further investigation of the molecular mechanism of PVT1 in HCC is needed.

8D.07: GENE EXPRESSION ANALYSIS AND BIOINFORMATICS REVEALED POTENTIAL TRANSCRIPTION FACTORS ASSOCIATED WITH RENIN-ANGIOTENSIN-ALDOSTERONE SYSTEM IN ATHEROMA.

PubMed

Nehme, A; Zibara, K; Cerutti, C; Bricca, G

2015-06-01

The implication of the renin-angiotensin-aldosterone system (RAAS) in atheroma development is well described. However, a complete view of the local RAAS in atheroma is still missing. In this study we aimed to reveal the organization of RAAS in atheroma at the transcriptomic level and identify the transcriptional regulators behind it. Extended RAAS (extRAAS) was defined as the set of 37 genes coding for classical and novel RAAS participants (Figure 1). Five microarray datasets containing overall 590 samples representing carotid and peripheral atheroma were downloaded from the GEO database. Correlation-based hierarchical clustering (R software) of extRAAS genes within each dataset allowed the identification of modules of co-expressed genes. Reproducible co-expression modules across datasets were then extracted. Transcription factors (TFs) having common binding sites (TFBSs) in the promoters of coordinated genes were identified using the Genomatix database tools and analyzed for their correlation with extRAAS genes in the microarray datasets. Expression data revealed the expressed extRAAS components and their relative abundance displaying the favored pathways in atheroma. Three co-expression modules with more than 80% reproducibility across datasets were extracted. Two of them (M1 and M2) contained genes coding for angiotensin metabolizing enzymes involved in different pathways: M1 included ACE, MME, RNPEP, and DPP3, in addition to 7 other genes; and M2 included CMA1, CTSG, and CPA3. The third module (M3) contained genes coding for receptors known to be implicated in atheroma (AGTR1, MR, GR, LNPEP, EGFR and GPER). M1 and M3 were negatively correlated in 3 of 5 datasets. We identified 19 TFs that have enriched TFBSs in the promoters of genes of M1, and two for M3, but none was found for M2. Among the extracted TFs, ELF1, MAX, and IRF5 showed significant positive correlations with peptidase-coding genes from M1 and negative correlations with receptors-coding genes from M3 (p < 0.05). The identified co-expression modules display the transcriptional organization of local extRAAS in human carotid atheroma. The identification of several TFs potentially associated to extRAAS genes may provide a frame for the discovery of atheroma-specific modulators of extRAAS activity.(Figure is included in full-text article.).

Challenges of the information age: the impact of false discovery on pathway identification.

PubMed

Rog, Colin J; Chekuri, Srinivasa C; Edgerton, Mary E

2012-11-21

Pathways with members that have known relevance to a disease are used to support hypotheses generated from analyses of gene expression and proteomic studies. Using cancer as an example, the pitfalls of searching pathways databases as support for genes and proteins that could represent false discoveries are explored. The frequency with which networks could be generated from 100 instances each of randomly selected five and ten genes sets as input to MetaCore, a commercial pathways database, was measured. A PubMed search enumerated cancer-related literature published for any gene in the networks. Using three, two, and one maximum intervening step between input genes to populate the network, networks were generated with frequencies of 97%, 77%, and 7% using ten gene sets and 73%, 27%, and 1% using five gene sets. PubMed reported an average of 4225 cancer-related articles per network gene. This can be attributed to the richly populated pathways databases and the interest in the molecular basis of cancer. As information sources become enriched, they are more likely to generate plausible mechanisms for false discoveries.

A statistical method for measuring activation of gene regulatory networks.

PubMed

Esteves, Gustavo H; Reis, Luiz F L

2018-06-13

Gene expression data analysis is of great importance for modern molecular biology, given our ability to measure the expression profiles of thousands of genes and enabling studies rooted in systems biology. In this work, we propose a simple statistical model for the activation measuring of gene regulatory networks, instead of the traditional gene co-expression networks. We present the mathematical construction of a statistical procedure for testing hypothesis regarding gene regulatory network activation. The real probability distribution for the test statistic is evaluated by a permutation based study. To illustrate the functionality of the proposed methodology, we also present a simple example based on a small hypothetical network and the activation measuring of two KEGG networks, both based on gene expression data collected from gastric and esophageal samples. The two KEGG networks were also analyzed for a public database, available through NCBI-GEO, presented as Supplementary Material. This method was implemented in an R package that is available at the BioConductor project website under the name maigesPack.

Identification of reference genes and validation for gene expression studies in diverse axolotl (Ambystoma mexicanum) tissues.

PubMed

Guelke, Eileen; Bucan, Vesna; Liebsch, Christina; Lazaridis, Andrea; Radtke, Christine; Vogt, Peter M; Reimers, Kerstin

2015-04-10

For the precise quantitative RT-PCR normalization a set of valid reference genes is obligatory. Moreover have to be taken into concern the experimental conditions as they bias the regulation of reference genes. Up till now, no reference targets have been described for the axolotl (Ambystoma mexicanum). In a search in the public database SalSite for genetic information of the axolotl we identified fourteen presumptive reference genes, eleven of which were further tested for their gene expression stability. This study characterizes the expressional patterns of 11 putative endogenous control genes during axolotl limb regeneration and in an axolotl tissue panel. All 11 reference genes showed variable expression. Strikingly, ACTB was to be found most stable expressed in all comparative tissue groups, so we reason it to be suitable for all different kinds of axolotl tissue-type investigations. Moreover do we suggest GAPDH and RPLP0 as suitable for certain axolotl tissue analysis. When it comes to axolotl limb regeneration, a validated pair of reference genes is ODC and RPLP0. With these findings, new insights into axolotl gene expression profiling might be gained. Copyright © 2015 Elsevier B.V. All rights reserved.

Rose Scent

PubMed Central

Guterman, Inna; Shalit, Moshe; Menda, Naama; Piestun, Dan; Dafny-Yelin, Mery; Shalev, Gil; Bar, Einat; Davydov, Olga; Ovadis, Mariana; Emanuel, Michal; Wang, Jihong; Adam, Zach; Pichersky, Eran; Lewinsohn, Efraim; Zamir, Dani; Vainstein, Alexander; Weiss, David

2002-01-01

For centuries, rose has been the most important crop in the floriculture industry; its economic importance also lies in the use of its petals as a source of natural fragrances. Here, we used genomics approaches to identify novel scent-related genes, using rose flowers from tetraploid scented and nonscented cultivars. An annotated petal EST database of ∼2100 unique genes from both cultivars was created, and DNA chips were prepared and used for expression analyses of selected clones. Detailed chemical analysis of volatile composition in the two cultivars, together with the identification of secondary metabolism–related genes whose expression coincides with scent production, led to the discovery of several novel flower scent–related candidate genes. The function of some of these genes, including a germacrene D synthase, was biochemically determined using an Escherichia coli expression system. This work demonstrates the advantages of using the high-throughput approaches of genomics to detail traits of interest expressed in a cultivar-specific manner in nonmodel plants. PMID:12368489

The barley EST DNA Replication and Repair Database (bEST-DRRD) as a tool for the identification of the genes involved in DNA replication and repair.

PubMed

Gruszka, Damian; Marzec, Marek; Szarejko, Iwona

2012-06-14

The high level of conservation of genes that regulate DNA replication and repair indicates that they may serve as a source of information on the origin and evolution of the species and makes them a reliable system for the identification of cross-species homologs. Studies that had been conducted to date shed light on the processes of DNA replication and repair in bacteria, yeast and mammals. However, there is still much to be learned about the process of DNA damage repair in plants. These studies, which were conducted mainly using bioinformatics tools, enabled the list of genes that participate in various pathways of DNA repair in Arabidopsis thaliana (L.) Heynh to be outlined; however, information regarding these mechanisms in crop plants is still very limited. A similar, functional approach is particularly difficult for a species whose complete genomic sequences are still unavailable. One of the solutions is to apply ESTs (Expressed Sequence Tags) as the basis for gene identification. For the construction of the barley EST DNA Replication and Repair Database (bEST-DRRD), presented here, the Arabidopsis nucleotide and protein sequences involved in DNA replication and repair were used to browse for and retrieve the deposited sequences, derived from four barley (Hordeum vulgare L.) sequence databases, including the "Barley Genome version 0.05" database (encompassing ca. 90% of barley coding sequences) and from two databases covering the complete genomes of two monocot models: Oryza sativa L. and Brachypodium distachyon L. in order to identify homologous genes. Sequences of the categorised Arabidopsis queries are used for browsing the repositories, which are located on the ViroBLAST platform. The bEST-DRRD is currently used in our project during the identification and validation of the barley genes involved in DNA repair. The presented database provides information about the Arabidopsis genes involved in DNA replication and repair, their expression patterns and models of protein interactions. It was designed and established to provide an open-access tool for the identification of monocot homologs of known Arabidopsis genes that are responsible for DNA-related processes. The barley genes identified in the project are currently being analysed to validate their function.

ExpressionDB: An open source platform for distributing genome-scale datasets.

PubMed

Hughes, Laura D; Lewis, Scott A; Hughes, Michael E

2017-01-01

RNA-sequencing (RNA-seq) and microarrays are methods for measuring gene expression across the entire transcriptome. Recent advances have made these techniques practical and affordable for essentially any laboratory with experience in molecular biology. A variety of computational methods have been developed to decrease the amount of bioinformatics expertise necessary to analyze these data. Nevertheless, many barriers persist which discourage new labs from using functional genomics approaches. Since high-quality gene expression studies have enduring value as resources to the entire research community, it is of particular importance that small labs have the capacity to share their analyzed datasets with the research community. Here we introduce ExpressionDB, an open source platform for visualizing RNA-seq and microarray data accommodating virtually any number of different samples. ExpressionDB is based on Shiny, a customizable web application which allows data sharing locally and online with customizable code written in R. ExpressionDB allows intuitive searches based on gene symbols, descriptions, or gene ontology terms, and it includes tools for dynamically filtering results based on expression level, fold change, and false-discovery rates. Built-in visualization tools include heatmaps, volcano plots, and principal component analysis, ensuring streamlined and consistent visualization to all users. All of the scripts for building an ExpressionDB with user-supplied data are freely available on GitHub, and the Creative Commons license allows fully open customization by end-users. We estimate that a demo database can be created in under one hour with minimal programming experience, and that a new database with user-supplied expression data can be completed and online in less than one day.

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

Identification of Modulators of the Nuclear Receptor ...

EPA Pesticide Factsheets

The nuclear receptor family member peroxisome proliferator-activated receptor α (PPARα) is activated by therapeutic hypolipidemic drugs and environmentally-relevant chemicals to regulate genes involved in lipid transport and catabolism. Chronic activation of PPARα in rodents increases in liver cancer incidence, whereas suppression of PPARα activity can lead to hepatocellular steatosis. Analytical approaches were developed to identify biosets (i.e., gene expression differences between two conditions) in a genomic database in which PPARα activity was altered. A gene expression signature of 131 PPARα-dependent genes was built using profiles from the livers of wild-type and PPARα-null mice after exposure to three structurally diverse PPARα activators (WY-14,643, fenofibrate and perfluorohexane sulfonate). A rank-based test (Running Fisher’s test (p-value ≤ 10-4)) was used to evaluate the similarity between the PPARα signature and a test set of 48 and 31 biosets positive or negative, respectively for PPARα activation; the test resulted in a balanced accuracy of 98%. The signature was used to identify factors that activate or suppress PPARα in an annotated mouse liver/primary hepatocyte gene expression database of ~1850 biosets. In addition to the expected activation of PPARα by fibrate drugs, di(2-ethylhexyl) phthalate, and perfluorinated compounds, PPARα was activated by benzofuran, galactosamine and TCDD and suppressed by hepatotoxins acetami

ExpTreeDB: web-based query and visualization of manually annotated gene expression profiling experiments of human and mouse from GEO.

PubMed

Ni, Ming; Ye, Fuqiang; Zhu, Juanjuan; Li, Zongwei; Yang, Shuai; Yang, Bite; Han, Lu; Wu, Yongge; Chen, Ying; Li, Fei; Wang, Shengqi; Bo, Xiaochen

2014-12-01

Numerous public microarray datasets are valuable resources for the scientific communities. Several online tools have made great steps to use these data by querying related datasets with users' own gene signatures or expression profiles. However, dataset annotation and result exhibition still need to be improved. ExpTreeDB is a database that allows for queries on human and mouse microarray experiments from Gene Expression Omnibus with gene signatures or profiles. Compared with similar applications, ExpTreeDB pays more attention to dataset annotations and result visualization. We introduced a multiple-level annotation system to depict and organize original experiments. For example, a tamoxifen-treated cell line experiment is hierarchically annotated as 'agent→drug→estrogen receptor antagonist→tamoxifen'. Consequently, retrieved results are exhibited by an interactive tree-structured graphics, which provide an overview for related experiments and might enlighten users on key items of interest. The database is freely available at http://biotech.bmi.ac.cn/ExpTreeDB. Web site is implemented in Perl, PHP, R, MySQL and Apache. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

An RNA-Seq based gene expression atlas of the common bean.

PubMed

O'Rourke, Jamie A; Iniguez, Luis P; Fu, Fengli; Bucciarelli, Bruna; Miller, Susan S; Jackson, Scott A; McClean, Philip E; Li, Jun; Dai, Xinbin; Zhao, Patrick X; Hernandez, Georgina; Vance, Carroll P

2014-10-06

Common bean (Phaseolus vulgaris) is grown throughout the world and comprises roughly 50% of the grain legumes consumed worldwide. Despite this, genetic resources for common beans have been lacking. Next generation sequencing, has facilitated our investigation of the gene expression profiles associated with biologically important traits in common bean. An increased understanding of gene expression in common bean will improve our understanding of gene expression patterns in other legume species. Combining recently developed genomic resources for Phaseolus vulgaris, including predicted gene calls, with RNA-Seq technology, we measured the gene expression patterns from 24 samples collected from seven tissues at developmentally important stages and from three nitrogen treatments. Gene expression patterns throughout the plant were analyzed to better understand changes due to nodulation, seed development, and nitrogen utilization. We have identified 11,010 genes differentially expressed with a fold change ≥ 2 and a P-value < 0.05 between different tissues at the same time point, 15,752 genes differentially expressed within a tissue due to changes in development, and 2,315 genes expressed only in a single tissue. These analyses identified 2,970 genes with expression patterns that appear to be directly dependent on the source of available nitrogen. Finally, we have assembled this data in a publicly available database, The Phaseolus vulgaris Gene Expression Atlas (Pv GEA), http://plantgrn.noble.org/PvGEA/ . Using the website, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different tissues, or download the dataset in a tabular form. These data provide the basis for a gene expression atlas, which will facilitate functional genomic studies in common bean. Analysis of this dataset has identified genes important in regulating seed composition and has increased our understanding of nodulation and impact of the nitrogen source on assimilation and distribution throughout the plant.

Gene discovery in Eimeria tenella by immunoscreening cDNA expression libraries of sporozoites and schizonts with chicken intestinal antibodies.

PubMed

Réfega, Susana; Girard-Misguich, Fabienne; Bourdieu, Christiane; Péry, Pierre; Labbé, Marie

2003-04-02

Specific antibodies were produced ex vivo from intestinal culture of Eimeria tenella infected chickens. The specificity of these intestinal antibodies was tested against different parasite stages. These antibodies were used to immunoscreen first generation schizont and sporozoite cDNA libraries permitting the identification of new E. tenella antigens. We obtained a total of 119 cDNA clones which were subjected to sequence analysis. The sequences coding for the proteins inducing local immune responses were compared with nucleotide or protein databases and with expressed sequence tags (ESTs) databases. We identified new Eimeria genes coding for heat shock proteins, a ribosomal protein, a pyruvate kinase and a pyridoxine kinase. Specific features of other sequences are discussed.

Strategies to explore functional genomics data sets in NCBI's GEO database.

PubMed

Wilhite, Stephen E; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze, and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries.

Strategies to Explore Functional Genomics Data Sets in NCBI’s GEO Database

PubMed Central

Wilhite, Stephen E.; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries. PMID:22130872

Database resources of the National Center for Biotechnology

PubMed Central

Wheeler, David L.; Church, Deanna M.; Federhen, Scott; Lash, Alex E.; Madden, Thomas L.; Pontius, Joan U.; Schuler, Gregory D.; Schriml, Lynn M.; Sequeira, Edwin; Tatusova, Tatiana A.; Wagner, Lukas

2003-01-01

In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, PubMed, PubMed Central (PMC), LocusLink, the NCBITaxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR (e-PCR), Open Reading Frame (ORF) Finder, References Sequence (RefSeq), UniGene, HomoloGene, ProtEST, Database of Single Nucleotide Polymorphisms (dbSNP), Human/Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker (MM), Evidence Viewer (EV), Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov. PMID:12519941

Identification of Development-Related Genes in the Ovaries of Adult Harmonia axyridis (Pallas) Lady Beetles Using a Time- Series Analysis by RNA-seq.

PubMed

Du, Wenxiao; Zeng, Fanrong

2016-12-14

Adults of the lady beetle species Harmonia axyridis (Pallas) are bred artificially en masse for classic biological control, which requires egg-laying by the H. axyridis ovary. Development-related genes may impact the growth of the H. axyridis adult ovary but have not been reported. Here, we used integrative time-series RNA-seq analysis of the ovary in H. axyridis adults to detect development-related genes. A total of 28,558 unigenes were functionally annotated using seven types of databases to obtain an annotated unigene database for ovaries in H. axyridis adults. We also analysed differentially expressed genes (DEGs) between samples. Based on a combination of the results of this bioinformatics analysis with literature reports and gene expression level changes in four different stages, we focused on the development of oocyte reproductive stem cell and yolk formation process and identified 26 genes with high similarity to development-related genes. 20 DEGs were randomly chosen for quantitative real-time PCR (qRT-PCR) to validate the accuracy of the RNA-seq results. This study establishes a robust pipeline for the discovery of key genes using high-throughput sequencing and the identification of a class of development-related genes for characterization.

Modification of Flight and Locomotion Performances, Respiratory Metabolism, and Transcriptome Expression in the Lady Beetle Harmonia axyridis through Sublethal Pesticide Exposure

PubMed Central

Xiao, Da; Tan, Xiaoling; Wang, Wenjuan; Zhang, Fan; Desneux, Nicolas; Wang, Su

2017-01-01

Biological control is usually used in combination with chemical control for practical agricultural applications. Thus, the influence of insecticides on the natural predators used for biological control should be investigated for integrated pest management. The ladybird Harmonia axyridis is an effective predator on aphids and coccids. Beta-cypermethrin is a broad-spectrum insecticide used worldwide for controlling insect pests. H. axyridis is becoming increasingly threatened by this insecticide. Here, we investigated the effect of a sublethal dose of beta-cypermethrin on flight, locomotion, respiration, and detoxification system of H. axyridis. After exposure to beta-cypermethrin, succinic female adults flew more times, longer distances, and during longer time periods. Exposure to a sublethal dose of beta-cypermethrin also promoted an increase in walking rate, walking distance, walking duration, and also an increase in respiratory quotient and respiratory rate. To investigate the effects of beta-cypermethrin on H. axyridis detoxification system, we analyzed the transcriptome of H. axyridis adults, focusing on genes related to detoxification systems. De novo assembly generated 65,509 unigenes with a mean length of 799 bp. From these genes, 26,020 unigenes (40.91% of all unigenes) exhibited clear homology to known genes in the NCBI non-redundant database. In addition, 10,402 unigenes were annotated in the Cluster of Orthologous Groups database, 12,088 unigenes were assigned to the Gene Ontology database and 12,269 unigenes were in the Kyoto Encyclopedia of Genes and Genome (KEGG) database. Exposure to beta-cypermethrin had significant effects on the transcriptome profile of H. axyridis adult. Based on uniquely mapped reads, 3,296 unigenes were differentially expressed, 868 unigenes were up-regulated and 2,248 unigenes were down-regulated. We identified differentially-expressed unigenes related to general detoxification systems in H. axyridis. This assembled, annotated transcriptome provides a valuable genomic resource for further understanding the molecular basis of detoxification mechanisms in H. axyridis. PMID:28239355

Modification of Flight and Locomotion Performances, Respiratory Metabolism, and Transcriptome Expression in the Lady Beetle Harmonia axyridis through Sublethal Pesticide Exposure.

PubMed

Xiao, Da; Tan, Xiaoling; Wang, Wenjuan; Zhang, Fan; Desneux, Nicolas; Wang, Su

2017-01-01

Biological control is usually used in combination with chemical control for practical agricultural applications. Thus, the influence of insecticides on the natural predators used for biological control should be investigated for integrated pest management. The ladybird Harmonia axyridis is an effective predator on aphids and coccids. Beta-cypermethrin is a broad-spectrum insecticide used worldwide for controlling insect pests. H. axyridis is becoming increasingly threatened by this insecticide. Here, we investigated the effect of a sublethal dose of beta-cypermethrin on flight, locomotion, respiration, and detoxification system of H. axyridis . After exposure to beta-cypermethrin, succinic female adults flew more times, longer distances, and during longer time periods. Exposure to a sublethal dose of beta-cypermethrin also promoted an increase in walking rate, walking distance, walking duration, and also an increase in respiratory quotient and respiratory rate. To investigate the effects of beta-cypermethrin on H. axyridis detoxification system, we analyzed the transcriptome of H. axyridis adults, focusing on genes related to detoxification systems. De novo assembly generated 65,509 unigenes with a mean length of 799 bp. From these genes, 26,020 unigenes (40.91% of all unigenes) exhibited clear homology to known genes in the NCBI non-redundant database. In addition, 10,402 unigenes were annotated in the Cluster of Orthologous Groups database, 12,088 unigenes were assigned to the Gene Ontology database and 12,269 unigenes were in the Kyoto Encyclopedia of Genes and Genome (KEGG) database. Exposure to beta-cypermethrin had significant effects on the transcriptome profile of H. axyridis adult. Based on uniquely mapped reads, 3,296 unigenes were differentially expressed, 868 unigenes were up-regulated and 2,248 unigenes were down-regulated. We identified differentially-expressed unigenes related to general detoxification systems in H. axyridis . This assembled, annotated transcriptome provides a valuable genomic resource for further understanding the molecular basis of detoxification mechanisms in H. axyridis .

RiceFOX: a database of Arabidopsis mutant lines overexpressing rice full-length cDNA that contains a wide range of trait information to facilitate analysis of gene function.

PubMed

Sakurai, Tetsuya; Kondou, Youichi; Akiyama, Kenji; Kurotani, Atsushi; Higuchi, Mieko; Ichikawa, Takanari; Kuroda, Hirofumi; Kusano, Miyako; Mori, Masaki; Saitou, Tsutomu; Sakakibara, Hitoshi; Sugano, Shoji; Suzuki, Makoto; Takahashi, Hideki; Takahashi, Shinya; Takatsuji, Hiroshi; Yokotani, Naoki; Yoshizumi, Takeshi; Saito, Kazuki; Shinozaki, Kazuo; Oda, Kenji; Hirochika, Hirohiko; Matsui, Minami

2011-02-01

Identification of gene function is important not only for basic research but also for applied science, especially with regard to improvements in crop production. For rapid and efficient elucidation of useful traits, we developed a system named FOX hunting (Full-length cDNA Over-eXpressor gene hunting) using full-length cDNAs (fl-cDNAs). A heterologous expression approach provides a solution for the high-throughput characterization of gene functions in agricultural plant species. Since fl-cDNAs contain all the information of functional mRNAs and proteins, we introduced rice fl-cDNAs into Arabidopsis plants for systematic gain-of-function mutation. We generated >30,000 independent Arabidopsis transgenic lines expressing rice fl-cDNAs (rice FOX Arabidopsis mutant lines). These rice FOX Arabidopsis lines were screened systematically for various criteria such as morphology, photosynthesis, UV resistance, element composition, plant hormone profile, metabolite profile/fingerprinting, bacterial resistance, and heat and salt tolerance. The information obtained from these screenings was compiled into a database named 'RiceFOX'. This database contains around 18,000 records of rice FOX Arabidopsis lines and allows users to search against all the observed results, ranging from morphological to invisible traits. The number of searchable items is approximately 100; moreover, the rice FOX Arabidopsis lines can be searched by rice and Arabidopsis gene/protein identifiers, sequence similarity to the introduced rice fl-cDNA and traits. The RiceFOX database is available at http://ricefox.psc.riken.jp/.

RiceFOX: A Database of Arabidopsis Mutant Lines Overexpressing Rice Full-Length cDNA that Contains a Wide Range of Trait Information to Facilitate Analysis of Gene Function

PubMed Central

Sakurai, Tetsuya; Kondou, Youichi; Akiyama, Kenji; Kurotani, Atsushi; Higuchi, Mieko; Ichikawa, Takanari; Kuroda, Hirofumi; Kusano, Miyako; Mori, Masaki; Saitou, Tsutomu; Sakakibara, Hitoshi; Sugano, Shoji; Suzuki, Makoto; Takahashi, Hideki; Takahashi, Shinya; Takatsuji, Hiroshi; Yokotani, Naoki; Yoshizumi, Takeshi; Saito, Kazuki; Shinozaki, Kazuo; Oda, Kenji; Hirochika, Hirohiko; Matsui, Minami

2011-01-01

Identification of gene function is important not only for basic research but also for applied science, especially with regard to improvements in crop production. For rapid and efficient elucidation of useful traits, we developed a system named FOX hunting (Full-length cDNA Over-eXpressor gene hunting) using full-length cDNAs (fl-cDNAs). A heterologous expression approach provides a solution for the high-throughput characterization of gene functions in agricultural plant species. Since fl-cDNAs contain all the information of functional mRNAs and proteins, we introduced rice fl-cDNAs into Arabidopsis plants for systematic gain-of-function mutation. We generated >30,000 independent Arabidopsis transgenic lines expressing rice fl-cDNAs (rice FOX Arabidopsis mutant lines). These rice FOX Arabidopsis lines were screened systematically for various criteria such as morphology, photosynthesis, UV resistance, element composition, plant hormone profile, metabolite profile/fingerprinting, bacterial resistance, and heat and salt tolerance. The information obtained from these screenings was compiled into a database named ‘RiceFOX’. This database contains around 18,000 records of rice FOX Arabidopsis lines and allows users to search against all the observed results, ranging from morphological to invisible traits. The number of searchable items is approximately 100; moreover, the rice FOX Arabidopsis lines can be searched by rice and Arabidopsis gene/protein identifiers, sequence similarity to the introduced rice fl-cDNA and traits. The RiceFOX database is available at http://ricefox.psc.riken.jp/. PMID:21186176

Comparative Bacterial Proteomics: Analysis of the Core Genome Concept

PubMed Central

Callister, Stephen J.; McCue, Lee Ann; Turse, Joshua E.; Monroe, Matthew E.; Auberry, Kenneth J.; Smith, Richard D.; Adkins, Joshua N.; Lipton, Mary S.

2008-01-01

While comparative bacterial genomic studies commonly predict a set of genes indicative of common ancestry, experimental validation of the existence of this core genome requires extensive measurement and is typically not undertaken. Enabled by an extensive proteome database developed over six years, we have experimentally verified the expression of proteins predicted from genomic ortholog comparisons among 17 environmental and pathogenic bacteria. More exclusive relationships were observed among the expressed protein content of phenotypically related bacteria, which is indicative of the specific lifestyles associated with these organisms. Although genomic studies can establish relative orthologous relationships among a set of bacteria and propose a set of ancestral genes, our proteomics study establishes expressed lifestyle differences among conserved genes and proposes a set of expressed ancestral traits. PMID:18253490

Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma

PubMed Central

Kaushik, Abhinav; Bhatia, Yashuma; Ali, Shakir; Gupta, Dinesh

2015-01-01

Metastatic melanoma patients have a poor prognosis, mainly attributable to the underlying heterogeneity in melanoma driver genes and altered gene expression profiles. These characteristics of melanoma also make the development of drugs and identification of novel drug targets for metastatic melanoma a daunting task. Systems biology offers an alternative approach to re-explore the genes or gene sets that display dysregulated behaviour without being differentially expressed. In this study, we have performed systems biology studies to enhance our knowledge about the conserved property of disease genes or gene sets among mutually exclusive datasets representing melanoma progression. We meta-analysed 642 microarray samples to generate melanoma reconstructed networks representing four different stages of melanoma progression to extract genes with altered molecular circuitry wiring as compared to a normal cellular state. Intriguingly, a majority of the melanoma network-rewired genes are not differentially expressed and the disease genes involved in melanoma progression consistently modulate its activity by rewiring network connections. We found that the shortlisted disease genes in the study show strong and abnormal network connectivity, which enhances with the disease progression. Moreover, the deviated network properties of the disease gene sets allow ranking/prioritization of different enriched, dysregulated and conserved pathway terms in metastatic melanoma, in agreement with previous findings. Our analysis also reveals presence of distinct network hubs in different stages of metastasizing tumor for the same set of pathways in the statistically conserved gene sets. The study results are also presented as a freely available database at http://bioinfo.icgeb.res.in/m3db/. The web-based database resource consists of results from the analysis presented here, integrated with cytoscape web and user-friendly tools for visualization, retrieval and further analysis. PMID:26558755

Identification and function analysis of contrary genes in Dupuytren's contracture.

PubMed

Ji, Xianglu; Tian, Feng; Tian, Lijie

2015-07-01

The present study aimed to analyze the expression of genes involved in Dupuytren's contracture (DC), using bioinformatic methods. The profile of GSE21221 was downloaded from the gene expression ominibus, which included six samples, derived from fibroblasts and six healthy control samples, derived from carpal-tunnel fibroblasts. A Distributed Intrusion Detection System was used in order to identify differentially expressed genes. The term contrary genes is proposed. Contrary genes were the genes that exhibited opposite expression patterns in the positive and negative groups, and likely exhibited opposite functions. These were identified using Coexpress software. Gene ontology (GO) function analysis was conducted for the contrary genes. A network of GO terms was constructed using the reduce and visualize gene ontology database. Significantly expressed genes (801) and contrary genes (98) were screened. A significant association was observed between Chitinase-3-like protein 1 and ten genes in the positive gene set. Positive regulation of transcription and the activation of nuclear factor-κB (NF-κB)-inducing kinase activity exhibited the highest degree values in the network of GO terms. In the present study, the expression of genes involved in the development of DC was analyzed, and the concept of contrary genes proposed. The genes identified in the present study are involved in the positive regulation of transcription and activation of NF-κB-inducing kinase activity. The contrary genes and GO terms identified in the present study may potentially be used for DC diagnosis and treatment.

Identification of microRNAs and genes associated with hyperandrogenism in the follicular fluid of women with polycystic ovary syndrome.

PubMed

Xue, Yunping; Lv, Juan; Xu, Pengfei; Gu, Lin; Cao, Jian; Xu, Lingling; Xue, Kai; Li, Qian

2018-05-01

Polycystic ovary syndrome (PCOS) is a common reproductive endocrine disease, which is characterized by hyperandrogenism (HA), chronic anovulation, polycystic ovaries, insulin resistance, and obesity. At present, the mechanism by which PCOS/HA occurs has not been fully elucidated, thus, the mechanisms behind and interventions for HA in PCOS are current hot topics in research. MiRNAs have recently been shown to serve as diagnostic or prognostic biomarkers in patients with cancer. Thus, we are currently focused on studying the altered expression of miRNAs in follicular fluid and their correlation with HA in PCOS. Illumina deep sequencing technology was used to explore different miRNAs in the follicular fluid of women with PCOS/HA and in the follicular fluid of women in a control group. Target prediction databases were then used to analyse the target genes of different expressed miRNAs, and GO analysis and the KEGG pathway database were used to identify the functions and the main biochemical and signalling pathways of differentially expressed target genes. The expression levels of 263 miRNAs were significantly different (>2-fold up-regulated or <0.5-fold down-regulated, P < 0.05) between the two groups of women. For example, the expression levels of miRNA (200a-3p, 10b-3p, 200b-3p, 29c-3p, 99a-3p, and 125a-5p) were significantly increased, while there was a decreased expression of miR-105-3p in PCOS patients with respect to the control. Literature has shown that the above seven miRNAs were associated with HA in PCOS. Furthermore, 31 770 genes were predicted to be targets of the 263 differentially expressed microRNAs. GO analysis and the KEGG pathway database showed involvement of these target genes in HA in PCOS. These results suggest the presence of differentially expressed miRNAs in the follicular fluid of women with PCOS/HA versus women in the control group. The potential role of these microRNAs was elucidated using bioinformatics tools and was found to be involved in the regulation of different pathways, biological functions, and cellular components underlying PCOS. The results of this research may reveal new mechanisms of PCOS/HA and suggest potential treatment targets. © 2017 Wiley Periodicals, Inc.

Coordination of gene expression of arachidonic and docosahexaenoic acid cascade enzymes during human brain development and aging.

PubMed

Ryan, Veronica H; Primiani, Christopher T; Rao, Jagadeesh S; Ahn, Kwangmi; Rapoport, Stanley I; Blanchard, Helene

2014-01-01

The polyunsaturated arachidonic and docosahexaenoic acids (AA and DHA) participate in cell membrane synthesis during neurodevelopment, neuroplasticity, and neurotransmission throughout life. Each is metabolized via coupled enzymatic reactions within separate but interacting metabolic cascades. AA and DHA pathway genes are coordinately expressed and underlie cascade interactions during human brain development and aging. The BrainCloud database for human non-pathological prefrontal cortex gene expression was used to quantify postnatal age changes in mRNA expression of 34 genes involved in AA and DHA metabolism. Expression patterns were split into Development (0 to 20 years) and Aging (21 to 78 years) intervals. Expression of genes for cytosolic phospholipases A2 (cPLA2), cyclooxygenases (COX)-1 and -2, and other AA cascade enzymes, correlated closely with age during Development, less so during Aging. Expression of DHA cascade enzymes was less inter-correlated in each period, but often changed in the opposite direction to expression of AA cascade genes. Except for the PLA2G4A (cPLA2 IVA) and PTGS2 (COX-2) genes at 1q25, highly inter-correlated genes were at distant chromosomal loci. Coordinated age-related gene expression during the brain Development and Aging intervals likely underlies coupled changes in enzymes of the AA and DHA cascades and largely occur through distant transcriptional regulation. Healthy brain aging does not show upregulation of PLA2G4 or PTGS2 expression, which was found in Alzheimer's disease.

GermOnline 4.0 is a genomics gateway for germline development, meiosis and the mitotic cell cycle.

PubMed

Lardenois, Aurélie; Gattiker, Alexandre; Collin, Olivier; Chalmel, Frédéric; Primig, Michael

2010-01-01

GermOnline 4.0 is a cross-species database portal focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. It is thus a source of information for life scientists as well as clinicians who are interested in gene expression and regulatory networks. The GermOnline gateway provides unlimited access to information produced with high-density oligonucleotide microarrays (3'-UTR GeneChips), genome-wide protein-DNA binding assays and protein-protein interaction studies in the context of Ensembl genome annotation. Samples used to produce high-throughput expression data and to carry out genome-wide in vivo DNA binding assays are annotated via the MIAME-compliant Multiomics Information Management and Annotation System (MIMAS 3.0). Furthermore, the Saccharomyces Genomics Viewer (SGV) was developed and integrated into the gateway. SGV is a visualization tool that outputs genome annotation and DNA-strand specific expression data produced with high-density oligonucleotide tiling microarrays (Sc_tlg GeneChips) which cover the complete budding yeast genome on both DNA strands. It facilitates the interpretation of expression levels and transcript structures determined for various cell types cultured under different growth and differentiation conditions. Database URL: www.germonline.org/

GermOnline 4.0 is a genomics gateway for germline development, meiosis and the mitotic cell cycle

PubMed Central

Lardenois, Aurélie; Gattiker, Alexandre; Collin, Olivier; Chalmel, Frédéric; Primig, Michael

2010-01-01

GermOnline 4.0 is a cross-species database portal focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. It is thus a source of information for life scientists as well as clinicians who are interested in gene expression and regulatory networks. The GermOnline gateway provides unlimited access to information produced with high-density oligonucleotide microarrays (3′-UTR GeneChips), genome-wide protein–DNA binding assays and protein–protein interaction studies in the context of Ensembl genome annotation. Samples used to produce high-throughput expression data and to carry out genome-wide in vivo DNA binding assays are annotated via the MIAME-compliant Multiomics Information Management and Annotation System (MIMAS 3.0). Furthermore, the Saccharomyces Genomics Viewer (SGV) was developed and integrated into the gateway. SGV is a visualization tool that outputs genome annotation and DNA-strand specific expression data produced with high-density oligonucleotide tiling microarrays (Sc_tlg GeneChips) which cover the complete budding yeast genome on both DNA strands. It facilitates the interpretation of expression levels and transcript structures determined for various cell types cultured under different growth and differentiation conditions. Database URL: www.germonline.org/ PMID:21149299

Identification of Genes Whose Expression Profile Is Associated with Non-Progression towards AIDS Using eQTLs

PubMed Central

Le Clerc, Sigrid; van Manen, Daniëlle; Coulonges, Cédric; Ulveling, Damien; Laville, Vincent; Labib, Taoufik; Taing, Lieng; Delaneau, Olivier; Montes, Matthieu; Schuitemaker, Hanneke; Zagury, Jean-François

2015-01-01

Background Many genome-wide association studies have been performed on progression towards the acquired immune deficiency syndrome (AIDS) and they mainly identified associations within the HLA loci. In this study, we demonstrate that the integration of biological information, namely gene expression data, can enhance the sensitivity of genetic studies to unravel new genetic associations relevant to AIDS. Methods We collated the biological information compiled from three databases of expression quantitative trait loci (eQTLs) involved in cells of the immune system. We derived a list of single nucleotide polymorphisms (SNPs) that are functional in that they correlate with differential expression of genes in at least two of the databases. We tested the association of those SNPs with AIDS progression in two cohorts, GRIV and ACS. Tests on permuted phenotypes of the GRIV and ACS cohorts or on randomised sets of equivalent SNPs allowed us to assess the statistical robustness of this method and to estimate the true positive rate. Results Eight genes were identified with high confidence (p = 0.001, rate of true positives 75%). Some of those genes had previously been linked with HIV infection. Notably, ENTPD4 belongs to the same family as CD39, whose expression has already been associated with AIDS progression; while DNAJB12 is part of the HSP90 pathway, which is involved in the control of HIV latency. Our study also drew our attention to lesser-known functions such as mitochondrial ribosomal proteins and a zinc finger protein, ZFP57, which could be central to the effectiveness of HIV infection. Interestingly, for six out of those eight genes, down-regulation is associated with non-progression, which makes them appealing targets to develop drugs against HIV. PMID:26367535

Differential display RT PCR of total RNA from human foreskin fibroblasts for investigation of androgen-dependent gene expression

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

Nitsche, E.M.; Moquin, A.; Adams, P.S.

1996-05-03

Male sexual differentiation is a process that involves androgen action via the androgen receptor. Defects in the androgen receptor, many resulting from point mutations in the androgen receptor gene, lead to varying degrees of impaired masculinization in chromosomally male individuals. To date no specific androgen regulated morphogens involved in this process have been identified and no marker genes are known that would help to predict further virilization in infants with partial androgen insensitivity. In the present study we first show data on androgen regulated gene expression investigated by differential display reverse transcription PCR (dd RT PCR) on total RNA frommore » human neonatal genital skin fibroblasts cultured in the presence or absence of 100 nM testosterone. Using three different primer combinations, 54 cDNAs appeared to be regulated by androgens. Most of these sequences show the characteristics of expressed mRNAs but showed no homology to sequences in the database. However 15 clones with significant homology to previously cloned sequences were identified. Seven cDNAs appear to be induced by androgen withdrawal. Of these, five are similar to ETS (expression tagged sequences) from unknown genes; the other two show significant homology to the cDNAs of ubiquitin and human guanylate binding protein 2 (GBP-2). In addition, we have identified 8 cDNA clones which show homologies to other sequences in the database and appear to be upregulated in the presence of testosterone. Three differential expressed sequences show significant homology to the cDNAs of L-plastin and one to the cDNA of testican. This latter gene codes for a proteoglycan involved in cell social behavior and therefore of special interest in this context. The results of this study are of interest in further investigation of normal and disturbed androgen-dependent gene expression. 49 refs., 2 figs., 5 tabs.« less

De novo comparative transcriptome analysis of genes involved in fruit morphology of pumpkin cultivars with extreme size difference and development of EST-SSR markers.

PubMed

Xanthopoulou, Aliki; Ganopoulos, Ioannis; Psomopoulos, Fotis; Manioudaki, Maria; Moysiadis, Theodoros; Kapazoglou, Aliki; Osathanunkul, Maslin; Michailidou, Sofia; Kalivas, Apostolos; Tsaftaris, Athanasios; Nianiou-Obeidat, Irini; Madesis, Panagiotis

2017-07-30

The genetic basis of fruit size and shape was investigated for the first time in Cucurbita species and genetic loci associated with fruit morphology have been identified. Although extensive genomic resources are available at present for tomato (Solanum lycopersicum), cucumber (Cucumis sativus), melon (Cucumis melo) and watermelon (Citrullus lanatus), genomic databases for Cucurbita species are limited. Recently, our group reported the generation of pumpkin (Cucurbita pepo) transcriptome databases from two contrasting cultivars with extreme fruit sizes. In the current study we used these databases to perform comparative transcriptome analysis in order to identify genes with potential roles in fruit morphology and fruit size. Differential Gene Expression (DGE) analysis between cv. 'Munchkin' (small-fruit) and cv. 'Big Moose' (large-fruit) revealed a variety of candidate genes associated with fruit morphology with significant differences in gene expression between the two cultivars. In addition, we have set the framework for generating EST-SSR markers, which discriminate different C. pepo cultivars and show transferability to related Cucurbitaceae species. The results of the present study will contribute to both further understanding the molecular mechanisms regulating fruit morphology and furthermore identifying the factors that determine fruit size. Moreover, they may lead to the development of molecular marker tools for selecting genotypes with desired morphological traits. Copyright © 2017. Published by Elsevier B.V.

Employing conservation of co-expression to improve functional inference

PubMed Central

Daub, Carsten O; Sonnhammer, Erik LL

2008-01-01

Background Observing co-expression between genes suggests that they are functionally coupled. Co-expression of orthologous gene pairs across species may improve function prediction beyond the level achieved in a single species. Results We used orthology between genes of the three different species S. cerevisiae, D. melanogaster, and C. elegans to combine co-expression across two species at a time. This led to increased function prediction accuracy when we incorporated expression data from either of the other two species and even further increased when conservation across both of the two other species was considered at the same time. Employing the conservation across species to incorporate abundant model organism data for the prediction of protein interactions in poorly characterized species constitutes a very powerful annotation method. Conclusion To be able to employ the most suitable co-expression distance measure for our analysis, we evaluated the ability of four popular gene co-expression distance measures to detect biologically relevant interactions between pairs of genes. For the expression datasets employed in our co-expression conservation analysis above, we used the GO and the KEGG PATHWAY databases as gold standards. While the differences between distance measures were small, Spearman correlation showed to give most robust results. PMID:18808668

The National NeuroAIDS Tissue Consortium (NNTC) Database: an integrated database for HIV-related studies

PubMed Central

Cserhati, Matyas F.; Pandey, Sanjit; Beaudoin, James J.; Baccaglini, Lorena; Guda, Chittibabu; Fox, Howard S.

2015-01-01

We herein present the National NeuroAIDS Tissue Consortium-Data Coordinating Center (NNTC-DCC) database, which is the only available database for neuroAIDS studies that contains data in an integrated, standardized form. This database has been created in conjunction with the NNTC, which provides human tissue and biofluid samples to individual researchers to conduct studies focused on neuroAIDS. The database contains experimental datasets from 1206 subjects for the following categories (which are further broken down into subcategories): gene expression, genotype, proteins, endo-exo-chemicals, morphometrics and other (miscellaneous) data. The database also contains a wide variety of downloadable data and metadata for 95 HIV-related studies covering 170 assays from 61 principal investigators. The data represent 76 tissue types, 25 measurement types, and 38 technology types, and reaches a total of 33 017 407 data points. We used the ISA platform to create the database and develop a searchable web interface for querying the data. A gene search tool is also available, which searches for NCBI GEO datasets associated with selected genes. The database is manually curated with many user-friendly features, and is cross-linked to the NCBI, HUGO and PubMed databases. A free registration is required for qualified users to access the database. Database URL: http://nntc-dcc.unmc.edu PMID:26228431

The Effects of Simulated Microgravity on Gene Expression in Human Bone Marrow MSC's Under Osteogenic Differentiation

NASA Astrophysics Data System (ADS)

Buravkova, L. B.; Gershovich, J. G.; Gershovich, P. M.; Grigoriev, A. I.

2013-02-01

In this work it was found that the expression level of 144 genes significantly changed in human mesenchymal stem cells during their osteogenic differentiation after 20 days of exposure to simulated microgravity: the expression of 30 genes significantly increased (from 1.7 to 11.9 fold), and 114 - decreased (from 0.2 to 0.6 fold). Most of the revealed genes were attributed to the 11 major groups corresponding to its biological role in the cells. Additional group was formed from the genes which did not belong to these categories, or did not have a description in the known databases (such as Pubmed). The greatest number of genes with altered expression was found in the group “Matrix and Adhesion", while the lowest - in the "Apoptosis and the response to external stimuli" group. These findings suggest that cultured hMSCs, placed in non-standard conditions, maintain a high level of viability, but have significantly altered functional properties which could affect their efficiency to differentiate towards osteogenic direction.

WormQTLHD--a web database for linking human disease to natural variation data in C. elegans.

PubMed

van der Velde, K Joeri; de Haan, Mark; Zych, Konrad; Arends, Danny; Snoek, L Basten; Kammenga, Jan E; Jansen, Ritsert C; Swertz, Morris A; Li, Yang

2014-01-01

Interactions between proteins are highly conserved across species. As a result, the molecular basis of multiple diseases affecting humans can be studied in model organisms that offer many alternative experimental opportunities. One such organism-Caenorhabditis elegans-has been used to produce much molecular quantitative genetics and systems biology data over the past decade. We present WormQTL(HD) (Human Disease), a database that quantitatively and systematically links expression Quantitative Trait Loci (eQTL) findings in C. elegans to gene-disease associations in man. WormQTL(HD), available online at http://www.wormqtl-hd.org, is a user-friendly set of tools to reveal functionally coherent, evolutionary conserved gene networks. These can be used to predict novel gene-to-gene associations and the functions of genes underlying the disease of interest. We created a new database that links C. elegans eQTL data sets to human diseases (34 337 gene-disease associations from OMIM, DGA, GWAS Central and NHGRI GWAS Catalogue) based on overlapping sets of orthologous genes associated to phenotypes in these two species. We utilized QTL results, high-throughput molecular phenotypes, classical phenotypes and genotype data covering different developmental stages and environments from WormQTL database. All software is available as open source, built on MOLGENIS and xQTL workbench.

An emerging cyberinfrastructure for biodefense pathogen and pathogen-host data.

PubMed

Zhang, C; Crasta, O; Cammer, S; Will, R; Kenyon, R; Sullivan, D; Yu, Q; Sun, W; Jha, R; Liu, D; Xue, T; Zhang, Y; Moore, M; McGarvey, P; Huang, H; Chen, Y; Zhang, J; Mazumder, R; Wu, C; Sobral, B

2008-01-01

The NIAID-funded Biodefense Proteomics Resource Center (RC) provides storage, dissemination, visualization and analysis capabilities for the experimental data deposited by seven Proteomics Research Centers (PRCs). The data and its publication is to support researchers working to discover candidates for the next generation of vaccines, therapeutics and diagnostics against NIAID's Category A, B and C priority pathogens. The data includes transcriptional profiles, protein profiles, protein structural data and host-pathogen protein interactions, in the context of the pathogen life cycle in vivo and in vitro. The database has stored and supported host or pathogen data derived from Bacillus, Brucella, Cryptosporidium, Salmonella, SARS, Toxoplasma, Vibrio and Yersinia, human tissue libraries, and mouse macrophages. These publicly available data cover diverse data types such as mass spectrometry, yeast two-hybrid (Y2H), gene expression profiles, X-ray and NMR determined protein structures and protein expression clones. The growing database covers over 23 000 unique genes/proteins from different experiments and organisms. All of the genes/proteins are annotated and integrated across experiments using UniProt Knowledgebase (UniProtKB) accession numbers. The web-interface for the database enables searching, querying and downloading at the level of experiment, group and individual gene(s)/protein(s) via UniProtKB accession numbers or protein function keywords. The system is accessible at http://www.proteomicsresource.org/.

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.

Databases for Microbiologists

DOE PAGES

Zhulin, Igor B.

2015-05-26

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. Finally, the purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.

Databases for Microbiologists

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

Zhulin, Igor B.

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. Finally, the purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.

Databases for Microbiologists

PubMed Central

2015-01-01

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. The purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists. PMID:26013493

High-Throughput Sequence Analysis of Turbot (Scophthalmus maximus) Transcriptome Using 454-Pyrosequencing for the Discovery of Antiviral Immune Genes

PubMed Central

Pereiro, Patricia; Balseiro, Pablo; Romero, Alejandro; Dios, Sonia; Forn-Cuni, Gabriel; Fuste, Berta; Planas, Josep V.; Beltran, Sergi; Novoa, Beatriz; Figueras, Antonio

2012-01-01

Background Turbot (Scophthalmus maximus L.) is an important aquacultural resource both in Europe and Asia. However, there is little information on gene sequences available in public databases. Currently, one of the main problems affecting the culture of this flatfish is mortality due to several pathogens, especially viral diseases which are not treatable. In order to identify new genes involved in immune defense, we conducted 454-pyrosequencing of the turbot transcriptome after different immune stimulations. Methodology/Principal Findings Turbot were injected with viral stimuli to increase the expression level of immune-related genes. High-throughput deep sequencing using 454-pyrosequencing technology yielded 915,256 high-quality reads. These sequences were assembled into 55,404 contigs that were subjected to annotation steps. Intriguingly, 55.16% of the deduced protein was not significantly similar to any sequences in the databases used for the annotation and only 0.85% of the BLASTx top-hits matched S. maximus protein sequences. This relatively low level of annotation is possibly due to the limited information for this specie and other flatfish in the database. These results suggest the identification of a large number of new genes in turbot and in fish in general. A more detailed analysis showed the presence of putative members of several innate and specific immune pathways. Conclusions/Significance To our knowledge, this study is the first transcriptome analysis using 454-pyrosequencing for turbot. Previously, there were only 12,471 EST and less of 1,500 nucleotide sequences for S. maximus in NCBI database. Our results provide a rich source of data (55,404 contigs and 181,845 singletons) for discovering and identifying new genes, which will serve as a basis for microarray construction, gene expression characterization and for identification of genetic markers to be used in several applications. Immune stimulation in turbot was very effective, obtaining an enormous variety of sequences belonging to genes involved in the defense mechanisms. PMID:22629298

Gene duplication, tissue-specific gene expression and sexual conflict in stalk-eyed flies (Diopsidae).

PubMed

Baker, Richard H; Narechania, Apurva; Johns, Philip M; Wilkinson, Gerald S

2012-08-19

Gene duplication provides an essential source of novel genetic material to facilitate rapid morphological evolution. Traits involved in reproduction and sexual dimorphism represent some of the fastest evolving traits in nature, and gene duplication is intricately involved in the origin and evolution of these traits. Here, we review genomic research on stalk-eyed flies (Diopsidae) that has been used to examine the extent of gene duplication and its role in the genetic architecture of sexual dimorphism. Stalk-eyed flies are remarkable because of the elongation of the head into long stalks, with the eyes and antenna laterally displaced at the ends of these stalks. Many species are strongly sexually dimorphic for eyespan, and these flies have become a model system for studying sexual selection. Using both expressed sequence tag and next-generation sequencing, we have established an extensive database of gene expression in the developing eye-antennal imaginal disc, the adult head and testes. Duplicated genes exhibit narrower expression patterns than non-duplicated genes, and the testes, in particular, provide an abundant source of gene duplication. Within somatic tissue, duplicated genes are more likely to be differentially expressed between the sexes, suggesting gene duplication may provide a mechanism for resolving sexual conflict.

Gene duplication, tissue-specific gene expression and sexual conflict in stalk-eyed flies (Diopsidae)

PubMed Central

Baker, Richard H.; Narechania, Apurva; Johns, Philip M.; Wilkinson, Gerald S.

2012-01-01

Gene duplication provides an essential source of novel genetic material to facilitate rapid morphological evolution. Traits involved in reproduction and sexual dimorphism represent some of the fastest evolving traits in nature, and gene duplication is intricately involved in the origin and evolution of these traits. Here, we review genomic research on stalk-eyed flies (Diopsidae) that has been used to examine the extent of gene duplication and its role in the genetic architecture of sexual dimorphism. Stalk-eyed flies are remarkable because of the elongation of the head into long stalks, with the eyes and antenna laterally displaced at the ends of these stalks. Many species are strongly sexually dimorphic for eyespan, and these flies have become a model system for studying sexual selection. Using both expressed sequence tag and next-generation sequencing, we have established an extensive database of gene expression in the developing eye-antennal imaginal disc, the adult head and testes. Duplicated genes exhibit narrower expression patterns than non-duplicated genes, and the testes, in particular, provide an abundant source of gene duplication. Within somatic tissue, duplicated genes are more likely to be differentially expressed between the sexes, suggesting gene duplication may provide a mechanism for resolving sexual conflict. PMID:22777023

Identification of an expressed gene in Dipylidium caninum.

PubMed

Miranda, Rodrigo R C; Costa-Júnior, Livio M; Campos, Artur K; Santos, Hudson A; Rabelo, Elida M L

2004-10-01

Recombinant DNA studies have been focused on developing vaccines to different cestodes. But few studies involving Dipylidium caninum molecular biology and genes have been done. Only partial sequences of mitochondrial DNA and ribosomal RNA gene are available in databases. Any molecular work with this parasite, including epidemiology, study of drug-resistant strains, and vaccine development, is hampered by the lack of knowledge of its genome. Thus, the knowledge of specific genes of different developmental stages of D. caninum is crucial to locate potential targets to be used as candidates to develop a vaccine and/or new drugs against this parasite. Here we report, for the first time, the sequencing of a fragment of a D. caninum expressed gene.

Inflammatory and mitochondrial gene expression data in GPER-deficient cardiomyocytes from male and female mice.

PubMed

Wang, Hao; Sun, Xuming; Chou, Jeff; Lin, Marina; Ferrario, Carlos M; Zapata-Sudo, Gisele; Groban, Leanne

2017-02-01

We previously showed that cardiomyocyte-specific G protein-coupled estrogen receptor (GPER) gene deletion leads to sex-specific adverse effects on cardiac structure and function; alterations which may be due to distinct differences in mitochondrial and inflammatory processes between sexes. Here, we provide the results of Gene Set Enrichment Analysis (GSEA) based on the DNA microarray data from GPER-knockout versus GPER-intact (intact) cardiomyocytes. This article contains complete data on the mitochondrial and inflammatory response-related gene expression changes that were significant in GPER knockout versus intact cardiomyocytes from adult male and female mice. The data are supplemental to our original research article "Cardiomyocyte-specific deletion of the G protein-coupled estrogen receptor (GPER) leads to left ventricular dysfunction and adverse remodeling: a sex-specific gene profiling" (Wang et al., 2016) [1]. Data have been deposited to the Gene Expression Omnibus (GEO) database repository with the dataset identifier GSE86843.

Isolation, sequence identification and tissue expression profiles of 3 novel porcine genes: ASPA, NAGA, and HEXA.

PubMed

Shu, Xianghua; Liu, Yonggang; Yang, Liangyu; Song, Chunlian; Hou, Jiafa

2008-01-01

The complete coding sequences of 3 porcine genes - ASPA, NAGA, and HEXA - were amplified by the reverse transcriptase polymerase chain reaction (RT-PCR) based on the conserved sequence information of the mouse or other mammals and referenced pig ESTs. These 3 novel porcine genes were then deposited in the NCBI database and assigned GeneIDs: 100142661, 100142664 and 100142667. The phylogenetic tree analysis revealed that the porcine ASPA, NAGA, and HEXA all have closer genetic relationships with the ASPA, NAGA, and HEXA of cattle. Tissue expression profile analysis was also carried out and results revealed that swine ASPA, NAGA, and HEXA genes were differentially expressed in various organs, including skeletal muscle, the heart, liver, fat, kidney, lung, and small and large intestines. Our experiment is the first one to establish the foundation for further research on these 3 swine genes.

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.

Cloning and heterologous expression of a novel subgroup of class IV polyhydroxyalkanoate synthase genes from the genus Bacillus.

PubMed

Mizuno, Kouhei; Kihara, Takahiro; Tsuge, Takeharu; Lundgren, Benjamin R; Sarwar, Zaara; Pinto, Atahualpa; Nomura, Christopher T

2017-01-01

Many microorganisms harbor genes necessary to synthesize biodegradable plastics known as polyhydroxyalkanoates (PHAs). We surveyed a genomic database and discovered a new cluster of class IV PHA synthase genes (phaRC). These genes are different in sequence and operon structure from any previously reported PHA synthase. The newly discovered PhaRC synthase was demonstrated to produce PHAs in recombinant Escherichia coli.

Molecular characterization of nucleopolyhedrovirus of three lepidopteran pests using late expression factor-8 gene.

PubMed

Jose, Jency; Jalali, S K; Shivalingaswamy, T M; Kumar, N K Krishna; Bhatnagar, R; Bandyopadhyay, A

2013-06-01

A PCR based method for detection of viral DNA in nucleopolyhedrovirus of three lepidopterans, Spodoptera litura, Amsacta albistriga and Helicoverpa armigera, was developed by employing the late expression factor-8 (lef-8) gene of three NPV using specific primers. The amplicons of 689, 699 and 665 bp were amplified, respectively, and the nucleotide sequences were submitted to GenBank and the accession numbers were obtained. The sequences of lef-8 gene of S. litura NPV and H. armigera NPV matched with those of their respective references in the GenBank database, thereby confirming their identity, however, the sequence of A. albistriga NPV was the first sequence submitted to the GenBank database. The sequence similarity analysis between the three lef-8 gene of NPV sequenced in the present study revealed that there was no significant similarity between them, however A. albistriga NPV and S. litura NPV were found to be closely related. CLUSTAL alignment of the sequences generated revealed general relatedness among NPVs lef-8 gene. The study confirmed that lef-8 gene can be used for quick and correct discriminatory identification of insect viruses.

The top skin-associated genes: a comparative analysis of human and mouse skin transcriptomes.

PubMed

Gerber, Peter Arne; Buhren, Bettina Alexandra; Schrumpf, Holger; Homey, Bernhard; Zlotnik, Albert; Hevezi, Peter

2014-06-01

The mouse represents a key model system for the study of the physiology and biochemistry of skin. Comparison of skin between mouse and human is critical for interpretation and application of data from mouse experiments to human disease. Here, we review the current knowledge on structure and immunology of mouse and human skin. Moreover, we present a systematic comparison of human and mouse skin transcriptomes. To this end, we have recently used a genome-wide database of human gene expression to identify genes highly expressed in skin, with no, or limited expression elsewhere - human skin-associated genes (hSAGs). Analysis of our set of hSAGs allowed us to generate a comprehensive molecular characterization of healthy human skin. Here, we used a similar database to generate a list of mouse skin-associated genes (mSAGs). A comparative analysis between the top human (n=666) and mouse (n=873) skin-associated genes (SAGs) revealed a total of only 30.2% identity between the two lists. The majority of shared genes encode proteins that participate in structural and barrier functions. Analysis of the top functional annotation terms revealed an overlap for morphogenesis, cell adhesion, structure, and signal transduction. The results of this analysis, discussed in the context of published data, illustrate the diversity between the molecular make up of skin of both species and grants a probable explanation, why results generated in murine in vivo models often fail to translate into the human.

Genomics of Mature and Immature Olfactory Sensory Neurons

PubMed Central

Nickell, Melissa D.; Breheny, Patrick; Stromberg, Arnold J.; McClintock, Timothy S.

2014-01-01

The continuous replacement of neurons in the olfactory epithelium provides an advantageous model for investigating neuronal differentiation and maturation. By calculating the relative enrichment of every mRNA detected in samples of mature mouse olfactory sensory neurons (OSNs), immature OSNs, and the residual population of neighboring cell types, and then comparing these ratios against the known expression patterns of >300 genes, enrichment criteria that accurately predicted the OSN expression patterns of nearly all genes were determined. We identified 847 immature OSN-specific and 691 mature OSN-specific genes. The control of gene expression by chromatin modification and transcription factors, and neurite growth, protein transport, RNA processing, cholesterol biosynthesis, and apoptosis via death domain receptors, were overrepresented biological processes in immature OSNs. Ion transport (ion channels), presynaptic functions, and cilia-specific processes were overrepresented in mature OSNs. Processes overrepresented among the genes expressed by all OSNs were protein and ion transport, ER overload response, protein catabolism, and the electron transport chain. To more accurately represent gradations in mRNA abundance and identify all genes expressed in each cell type, classification methods were used to produce probabilities of expression in each cell type for every gene. These probabilities, which identified 9,300 genes expressed in OSNs, were 96% accurate at identifying genes expressed in OSNs and 86% accurate at discriminating genes specific to mature and immature OSNs. This OSN gene database not only predicts the genes responsible for the major biological processes active in OSNs, but also identifies thousands of never before studied genes that support OSN phenotypes. PMID:22252456

Bioinformatic analysis of the effects and mechanisms of decitabine and cytarabine on acute myeloid leukemia

PubMed Central

Zhou, Shiyong; Liu, Pengfei; Zhang, Huilai

2017-01-01

Acute myeloid leukemia (AML) is a frequently occurring malignant disease of the blood and may result from a variety of genetic disorders. The present study aimed to identify the underlying mechanisms associated with the therapeutic effects of decitabine and cytarabine on AML, using microarray analysis. The microarray datasets GSE40442 and GSE40870 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine via the Linear Models for Microarray Data package, following data pre-processing. Gene Ontology (GO) analysis of DEGs was performed using the Database for Annotation, Visualization and Integrated Analysis Discovery. Genes corresponding to the differentially methylated sites were obtained using the annotation package of the methylation microarray platform. The overlapping genes were identified, which exhibited the opposite variation trend between gene expression and DNA methylation. Important transcription factor (TF)-gene pairs were screened out, and a regulated network subsequently constructed. A total of 190 DEGs and 540 differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine. A total of 36 GO terms of DEGs were enriched, including nucleosomes, protein-DNA complexes and the nucleosome assembly. The 540 differentially methylated sites were located on 240 genes, including the acid-repeat containing protein (ACRC) gene that was additionally differentially expressed. In addition, 60 TF pairs and overlapped methylated sites, and 140 TF-pairs and DEGs were screened out. The regulated network included 68 nodes and 140 TF-gene pairs. The present study identified various genes including ACRC and proliferating cell nuclear antigen, in addition to various TFs, including TATA-box binding protein associated factor 1 and CCCTC-binding factor, which may be potential therapeutic targets of AML. PMID:28498449

Bioinformatic analysis of the effects and mechanisms of decitabine and cytarabine on acute myeloid leukemia.

PubMed

Zhou, Shiyong; Liu, Pengfei; Zhang, Huilai

2017-07-01

Acute myeloid leukemia (AML) is a frequently occurring malignant disease of the blood and may result from a variety of genetic disorders. The present study aimed to identify the underlying mechanisms associated with the therapeutic effects of decitabine and cytarabine on AML, using microarray analysis. The microarray datasets GSE40442 and GSE40870 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine via the Linear Models for Microarray Data package, following data pre‑processing. Gene Ontology (GO) analysis of DEGs was performed using the Database for Annotation, Visualization and Integrated Analysis Discovery. Genes corresponding to the differentially methylated sites were obtained using the annotation package of the methylation microarray platform. The overlapping genes were identified, which exhibited the opposite variation trend between gene expression and DNA methylation. Important transcription factor (TF)‑gene pairs were screened out, and a regulated network subsequently constructed. A total of 190 DEGs and 540 differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine. A total of 36 GO terms of DEGs were enriched, including nucleosomes, protein‑DNA complexes and the nucleosome assembly. The 540 differentially methylated sites were located on 240 genes, including the acid‑repeat containing protein (ACRC) gene that was additionally differentially expressed. In addition, 60 TF pairs and overlapped methylated sites, and 140 TF‑pairs and DEGs were screened out. The regulated network included 68 nodes and 140 TF‑gene pairs. The present study identified various genes including ACRC and proliferating cell nuclear antigen, in addition to various TFs, including TATA‑box binding protein associated factor 1 and CCCTC‑binding factor, which may be potential therapeutic targets of AML.

CoReCG: a comprehensive database of genes associated with colon-rectal cancer

PubMed Central

Agarwal, Rahul; Kumar, Binayak; Jayadev, Msk; Raghav, Dhwani; Singh, Ashutosh

2016-01-01

Cancer of large intestine is commonly referred as colorectal cancer, which is also the third most frequently prevailing neoplasm across the globe. Though, much of work is being carried out to understand the mechanism of carcinogenesis and advancement of this disease but, fewer studies has been performed to collate the scattered information of alterations in tumorigenic cells like genes, mutations, expression changes, epigenetic alteration or post translation modification, genetic heterogeneity. Earlier findings were mostly focused on understanding etiology of colorectal carcinogenesis but less emphasis were given for the comprehensive review of the existing findings of individual studies which can provide better diagnostics based on the suggested markers in discrete studies. Colon Rectal Cancer Gene Database (CoReCG), contains 2056 colon-rectal cancer genes information involved in distinct colorectal cancer stages sourced from published literature with an effective knowledge based information retrieval system. Additionally, interactive web interface enriched with various browsing sections, augmented with advance search facility for querying the database is provided for user friendly browsing, online tools for sequence similarity searches and knowledge based schema ensures a researcher friendly information retrieval mechanism. Colorectal cancer gene database (CoReCG) is expected to be a single point source for identification of colorectal cancer-related genes, thereby helping with the improvement of classification, diagnosis and treatment of human cancers. Database URL: lms.snu.edu.in/corecg PMID:27114494

T-cell lymphomas associated gene expression signature: Bioinformatics analysis based on gene expression Omnibus.

PubMed

Zhou, Lei-Lei; Xu, Xiao-Yue; Ni, Jie; Zhao, Xia; Zhou, Jian-Wei; Feng, Ji-Feng

2018-06-01

Due to the low incidence and the heterogeneity of subtypes, the biological process of T-cell lymphomas is largely unknown. Although many genes have been detected in T-cell lymphomas, the role of these genes in biological process of T-cell lymphomas was not further analyzed. Two qualified datasets were downloaded from Gene Expression Omnibus database. The biological functions of differentially expressed genes were evaluated by gene ontology enrichment and KEGG pathway analysis. The network for intersection genes was constructed by the cytoscape v3.0 software. Kaplan-Meier survival curves and log-rank test were employed to assess the association between differentially expressed genes and clinical characters. The intersection mRNAs were proved to be associated with fundamental processes of T-cell lymphoma cells. These intersection mRNAs were involved in the activation of some cancer-related pathways, including PI3K/AKT, Ras, JAK-STAT, and NF-kappa B signaling pathway. PDGFRA, CXCL12, and CCL19 were the most significant central genes in the signal-net analysis. The results of survival analysis are not entirely credible. Our findings uncovered aberrantly expressed genes and a complex RNA signal network in T-cell lymphomas and indicated cancer-related pathways involved in disease initiation and progression, providing a new insight for biotargeted therapy in T-cell lymphomas. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Molecular cloning of a putative gene encoding isopentenyltransferase from pingyitiancha (Malus hupehensis) and characterization of its response to nitrate.

PubMed

Peng, Jing; Peng, Futian; Zhu, Chunfu; Wei, Shaochong

2008-06-01

A putative isopentenyltransferase (IPT) encoding gene was identified from a pingyitiancha (Malus hupehensis Rehd.) expressed sequence tag database, and the full-length gene was cloned by RACE. Based on expression profile and sequence alignment, the nucleotide sequence of the clone, named MhIPT3, was most similar to AtIPT3, an IPT gene in Arabidopsis. The full-length cDNA contained a 963-bp open reading frame encoding a protein of 321 amino acids with a molecular mass of 37.3 kDa. Sequence analysis of genomic DNA revealed the absence of introns in the frame. Quantitative real-time PCR analysis demonstrated that the gene was expressed in roots, stems and leaves. Application of nitrate to roots of nitrogen-deprived seedlings strongly induced expression of MhIPT3 and was accompanied by the accumulation of cytokinins, whereas MhIPT3 expression was little affected by ammonium application to roots of nitrogen-deprived seedlings. Application of nitrate to leaves also up-regulated the expression of MhIPT3 and corresponded closely with the accumulation of isopentyladenine and isopentyladenosine in leaves.

Database resources of the National Center for Biotechnology Information.

PubMed

Sayers, Eric W; Barrett, Tanya; Benson, Dennis A; Bolton, Evan; Bryant, Stephen H; Canese, Kathi; Chetvernin, Vyacheslav; Church, Deanna M; DiCuccio, Michael; Federhen, Scott; Feolo, Michael; Fingerman, Ian M; Geer, Lewis Y; Helmberg, Wolfgang; Kapustin, Yuri; Landsman, David; Lipman, David J; Lu, Zhiyong; Madden, Thomas L; Madej, Tom; Maglott, Donna R; Marchler-Bauer, Aron; Miller, Vadim; Mizrachi, Ilene; Ostell, James; Panchenko, Anna; Phan, Lon; Pruitt, Kim D; Schuler, Gregory D; Sequeira, Edwin; Sherry, Stephen T; Shumway, Martin; Sirotkin, Karl; Slotta, Douglas; Souvorov, Alexandre; Starchenko, Grigory; Tatusova, Tatiana A; Wagner, Lukas; Wang, Yanli; Wilbur, W John; Yaschenko, Eugene; Ye, Jian

2011-01-01

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Electronic PCR, OrfFinder, Splign, ProSplign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), IBIS, Biosystems, Peptidome, OMSSA, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

The National NeuroAIDS Tissue Consortium (NNTC) Database: an integrated database for HIV-related studies.

PubMed

Cserhati, Matyas F; Pandey, Sanjit; Beaudoin, James J; Baccaglini, Lorena; Guda, Chittibabu; Fox, Howard S

2015-01-01

We herein present the National NeuroAIDS Tissue Consortium-Data Coordinating Center (NNTC-DCC) database, which is the only available database for neuroAIDS studies that contains data in an integrated, standardized form. This database has been created in conjunction with the NNTC, which provides human tissue and biofluid samples to individual researchers to conduct studies focused on neuroAIDS. The database contains experimental datasets from 1206 subjects for the following categories (which are further broken down into subcategories): gene expression, genotype, proteins, endo-exo-chemicals, morphometrics and other (miscellaneous) data. The database also contains a wide variety of downloadable data and metadata for 95 HIV-related studies covering 170 assays from 61 principal investigators. The data represent 76 tissue types, 25 measurement types, and 38 technology types, and reaches a total of 33,017,407 data points. We used the ISA platform to create the database and develop a searchable web interface for querying the data. A gene search tool is also available, which searches for NCBI GEO datasets associated with selected genes. The database is manually curated with many user-friendly features, and is cross-linked to the NCBI, HUGO and PubMed databases. A free registration is required for qualified users to access the database. © The Author(s) 2015. Published by Oxford University Press.

Functional network analysis of genes differentially expressed during xylogenesis in soc1ful woody Arabidopsis plants.

PubMed

Davin, Nicolas; Edger, Patrick P; Hefer, Charles A; Mizrachi, Eshchar; Schuetz, Mathias; Smets, Erik; Myburg, Alexander A; Douglas, Carl J; Schranz, Michael E; Lens, Frederic

2016-06-01

Many plant genes are known to be involved in the development of cambium and wood, but how the expression and functional interaction of these genes determine the unique biology of wood remains largely unknown. We used the soc1ful loss of function mutant - the woodiest genotype known in the otherwise herbaceous model plant Arabidopsis - to investigate the expression and interactions of genes involved in secondary growth (wood formation). Detailed anatomical observations of the stem in combination with mRNA sequencing were used to assess transcriptome remodeling during xylogenesis in wild-type and woody soc1ful plants. To interpret the transcriptome changes, we constructed functional gene association networks of differentially expressed genes using the STRING database. This analysis revealed functionally enriched gene association hubs that are differentially expressed in herbaceous and woody tissues. In particular, we observed the differential expression of genes related to mechanical stress and jasmonate biosynthesis/signaling during wood formation in soc1ful plants that may be an effect of greater tension within woody tissues. Our results suggest that habit shifts from herbaceous to woody life forms observed in many angiosperm lineages could have evolved convergently by genetic changes that modulate the gene expression and interaction network, and thereby redeploy the conserved wood developmental program. © 2016 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

Generation and analysis of expressed sequence tags from the bone marrow of Chinese Sika deer.

PubMed

Yao, Baojin; Zhao, Yu; Zhang, Mei; Li, Juan

2012-03-01

Sika deer is one of the best-known and highly valued animals of China. Despite its economic, cultural, and biological importance, there has not been a large-scale sequencing project for Sika deer to date. With the ultimate goal of sequencing the complete genome of this organism, we first established a bone marrow cDNA library for Sika deer and generated a total of 2,025 reads. After processing the sequences, 2,017 high-quality expressed sequence tags (ESTs) were obtained. These ESTs were assembled into 1,157 unigenes, including 238 contigs and 919 singletons. Comparative analyses indicated that 888 (76.75%) of the unigenes had significant matches to sequences in the non-redundant protein database, In addition to highly expressed genes, such as stearoyl-CoA desaturase, cytochrome c oxidase, adipocyte-type fatty acid-binding protein, adiponectin and thymosin beta-4, we also obtained vascular endothelial growth factor-A and heparin-binding growth-associated molecule, both of which are of great importance for angiogenesis research. There were 244 (21.09%) unigenes with no significant match to any sequence in current protein or nucleotide databases, and these sequences may represent genes with unknown function in Sika deer. Open reading frame analysis of the sequences was performed using the getorf program. In addition, the sequences were functionally classified using the gene ontology hierarchy, clusters of orthologous groups of proteins and Kyoto encyclopedia of genes and genomes databases. Analysis of ESTs described in this paper provides an important resource for the transcriptome exploration of Sika deer, and will also facilitate further studies on functional genomics, gene discovery and genome annotation of Sika deer.

Vascular Gene Expression in Nonneoplastic and Malignant Brain

PubMed Central

Madden, Stephen L.; Cook, Brian P.; Nacht, Mariana; Weber, William D.; Callahan, Michelle R.; Jiang, Yide; Dufault, Michael R.; Zhang, Xiaoming; Zhang, Wen; Walter-Yohrling, Jennifer; Rouleau, Cecile; Akmaev, Viatcheslav R.; Wang, Clarence J.; Cao, Xiaohong; St. Martin, Thia B.; Roberts, Bruce L.; Teicher, Beverly A.; Klinger, Katherine W.; Stan, Radu-Virgil; Lucey, Brenden; Carson-Walter, Eleanor B.; Laterra, John; Walter, Kevin A.

2004-01-01

Malignant gliomas are uniformly lethal tumors whose morbidity is mediated in large part by the angiogenic response of the brain to the invading tumor. This profound angiogenic response leads to aggressive tumor invasion and destruction of surrounding brain tissue as well as blood-brain barrier breakdown and life-threatening cerebral edema. To investigate the molecular mechanisms governing the proliferation of abnormal microvasculature in malignant brain tumor patients, we have undertaken a cell-specific transcriptome analysis from surgically harvested nonneoplastic and tumor-associated endothelial cells. SAGE-derived endothelial cell gene expression patterns from glioma and nonneoplastic brain tissue reveal distinct gene expression patterns and consistent up-regulation of certain glioma endothelial marker genes across patient samples. We define the G-protein-coupled receptor RDC1 as a tumor endothelial marker whose expression is distinctly induced in tumor endothelial cells of both brain and peripheral vasculature. Further, we demonstrate that the glioma-induced gene, PV1, shows expression both restricted to endothelial cells and coincident with endothelial cell tube formation. As PV1 provides a framework for endothelial cell caveolar diaphragms, this protein may serve to enhance glioma-induced disruption of the blood-brain barrier and transendothelial exchange. Additional characterization of this extensive brain endothelial cell gene expression database will provide unique molecular insights into vascular gene expression. PMID:15277233

Genes up-regulated during red coloration in UV-B irradiated lettuce leaves.

PubMed

Park, Jong-Sug; Choung, Myoung-Gun; Kim, Jung-Bong; Hahn, Bum-Soo; Kim, Jong-Bum; Bae, Shin-Chul; Roh, Kyung-Hee; Kim, Yong-Hwan; Cheon, Choong-Ill; Sung, Mi-Kyung; Cho, Kang-Jin

2007-04-01

Molecular analysis of gene expression differences between green and red lettuce leaves was performed using the SSH method. BlastX comparisons of subtractive expressed sequence tags (ESTs) indicated that 7.6% of clones encoded enzymes involved in secondary metabolism. Such clones had a particularly high abundance of flavonoid-metabolism proteins (6.5%). Following SSH, 566 clones were rescreened for differential gene expression using dot-blot hybridization. Of these, 53 were found to overexpressed during red coloration. The up-regulated expression of six genes was confirmed by Northern blot analyses. The expression of chalcone synthase (CHS), flavanone 3-hydroxylase (F3H), and dihydroflavonol 4-reductase (DFR) genes showed a positive correlation with anthocyanin accumulation in UV-B-irradiated lettuce leaves; flavonoid 3',5'-hydroxylase (F3',5'H) and anthocyanidin synthase (ANS) were expressed continuously in both samples. These results indicated that the genes CHS, F3H, and DFR coincided with increases in anthocyanin accumulation during the red coloration of lettuce leaves. This study show a relationship between red coloration and the expression of up-regulated genes in lettuce. The subtractive cDNA library and EST database described in this study represent a valuable resource for further research for secondary metabolism in the vegetable crops.

Characterization of Adelphocoris suturalis (Hemiptera: Miridae) Transcriptome from Different Developmental Stages

NASA Astrophysics Data System (ADS)

Tian, Caihong; Tek Tay, Wee; Feng, Hongqiang; Wang, Ying; Hu, Yongmin; Li, Guoping

2015-06-01

Adelphocoris suturalis is one of the most serious pest insects of Bt cotton in China, however its molecular genetics, biochemistry and physiology are poorly understood. We used high throughput sequencing platform to perform de novo transcriptome assembly and gene expression analyses across different developmental stages (eggs, 2nd and 5th instar nymphs, female and male adults). We obtained 20 GB of clean data and revealed 88,614 unigenes, including 23,830 clusters and 64,784 singletons. These unigene sequences were annotated and classified by Gene Ontology, Clusters of Orthologous Groups, and Kyoto Encyclopedia of Genes and Genomes databases. A large number of differentially expressed genes were discovered through pairwise comparisons between these developmental stages. Gene expression profiles were dramatically different between life stage transitions, with some of these most differentially expressed genes being associated with sex difference, metabolism and development. Quantitative real-time PCR results confirm deep-sequencing findings based on relative expression levels of nine randomly selected genes. Furthermore, over 791,390 single nucleotide polymorphisms and 2,682 potential simple sequence repeats were identified. Our study provided comprehensive transcriptional gene expression information for A. suturalis that will form the basis to better understanding of development pathways, hormone biosynthesis, sex differences and wing formation in mirid bugs.

Characterization of Adelphocoris suturalis (Hemiptera: Miridae) Transcriptome from Different Developmental Stages

PubMed Central

Tian, Caihong; Tek Tay, Wee; Feng, Hongqiang; Wang, Ying; Hu, Yongmin; Li, Guoping

2015-01-01

Adelphocoris suturalis is one of the most serious pest insects of Bt cotton in China, however its molecular genetics, biochemistry and physiology are poorly understood. We used high throughput sequencing platform to perform de novo transcriptome assembly and gene expression analyses across different developmental stages (eggs, 2nd and 5th instar nymphs, female and male adults). We obtained 20 GB of clean data and revealed 88,614 unigenes, including 23,830 clusters and 64,784 singletons. These unigene sequences were annotated and classified by Gene Ontology, Clusters of Orthologous Groups, and Kyoto Encyclopedia of Genes and Genomes databases. A large number of differentially expressed genes were discovered through pairwise comparisons between these developmental stages. Gene expression profiles were dramatically different between life stage transitions, with some of these most differentially expressed genes being associated with sex difference, metabolism and development. Quantitative real-time PCR results confirm deep-sequencing findings based on relative expression levels of nine randomly selected genes. Furthermore, over 791,390 single nucleotide polymorphisms and 2,682 potential simple sequence repeats were identified. Our study provided comprehensive transcriptional gene expression information for A. suturalis that will form the basis to better understanding of development pathways, hormone biosynthesis, sex differences and wing formation in mirid bugs. PMID:26047353

An elm EST database for identifying leaf beetle egg-induced defense genes

PubMed Central

2012-01-01

Background Plants can defend themselves against herbivorous insects prior to the onset of larval feeding by responding to the eggs laid on their leaves. In the European field elm (Ulmus minor), egg laying by the elm leaf beetle ( Xanthogaleruca luteola) activates the emission of volatiles that attract specialised egg parasitoids, which in turn kill the eggs. Little is known about the transcriptional changes that insect eggs trigger in plants and how such indirect defense mechanisms are orchestrated in the context of other biological processes. Results Here we present the first large scale study of egg-induced changes in the transcriptional profile of a tree. Five cDNA libraries were generated from leaves of (i) untreated control elms, and elms treated with (ii) egg laying and feeding by elm leaf beetles, (iii) feeding, (iv) artificial transfer of egg clutches, and (v) methyl jasmonate. A total of 361,196 ESTs expressed sequence tags (ESTs) were identified which clustered into 52,823 unique transcripts (Unitrans) and were stored in a database with a public web interface. Among the analyzed Unitrans, 73% could be annotated by homology to known genes in the UniProt (Plant) database, particularly to those from Vitis, Ricinus, Populus and Arabidopsis. Comparative in silico analysis among the different treatments revealed differences in Gene Ontology term abundances. Defense- and stress-related gene transcripts were present in high abundance in leaves after herbivore egg laying, but transcripts involved in photosynthesis showed decreased abundance. Many pathogen-related genes and genes involved in phytohormone signaling were expressed, indicative of jasmonic acid biosynthesis and activation of jasmonic acid responsive genes. Cross-comparisons between different libraries based on expression profiles allowed the identification of genes with a potential relevance in egg-induced defenses, as well as other biological processes, including signal transduction, transport and primary metabolism. Conclusion Here we present a dataset for a large-scale study of the mechanisms of plant defense against insect eggs in a co-evolved, natural ecological plant–insect system. The EST database analysis provided here is a first step in elucidating the transcriptional responses of elm to elm leaf beetle infestation, and adds further to our knowledge on insect egg-induced transcriptomic changes in plants. The sequences identified in our comparative analysis give many hints about novel defense mechanisms directed towards eggs. PMID:22702658

An elm EST database for identifying leaf beetle egg-induced defense genes.

PubMed

Büchel, Kerstin; McDowell, Eric; Nelson, Will; Descour, Anne; Gershenzon, Jonathan; Hilker, Monika; Soderlund, Carol; Gang, David R; Fenning, Trevor; Meiners, Torsten

2012-06-15

Plants can defend themselves against herbivorous insects prior to the onset of larval feeding by responding to the eggs laid on their leaves. In the European field elm (Ulmus minor), egg laying by the elm leaf beetle ( Xanthogaleruca luteola) activates the emission of volatiles that attract specialised egg parasitoids, which in turn kill the eggs. Little is known about the transcriptional changes that insect eggs trigger in plants and how such indirect defense mechanisms are orchestrated in the context of other biological processes. Here we present the first large scale study of egg-induced changes in the transcriptional profile of a tree. Five cDNA libraries were generated from leaves of (i) untreated control elms, and elms treated with (ii) egg laying and feeding by elm leaf beetles, (iii) feeding, (iv) artificial transfer of egg clutches, and (v) methyl jasmonate. A total of 361,196 ESTs expressed sequence tags (ESTs) were identified which clustered into 52,823 unique transcripts (Unitrans) and were stored in a database with a public web interface. Among the analyzed Unitrans, 73% could be annotated by homology to known genes in the UniProt (Plant) database, particularly to those from Vitis, Ricinus, Populus and Arabidopsis. Comparative in silico analysis among the different treatments revealed differences in Gene Ontology term abundances. Defense- and stress-related gene transcripts were present in high abundance in leaves after herbivore egg laying, but transcripts involved in photosynthesis showed decreased abundance. Many pathogen-related genes and genes involved in phytohormone signaling were expressed, indicative of jasmonic acid biosynthesis and activation of jasmonic acid responsive genes. Cross-comparisons between different libraries based on expression profiles allowed the identification of genes with a potential relevance in egg-induced defenses, as well as other biological processes, including signal transduction, transport and primary metabolism. Here we present a dataset for a large-scale study of the mechanisms of plant defense against insect eggs in a co-evolved, natural ecological plant-insect system. The EST database analysis provided here is a first step in elucidating the transcriptional responses of elm to elm leaf beetle infestation, and adds further to our knowledge on insect egg-induced transcriptomic changes in plants. The sequences identified in our comparative analysis give many hints about novel defense mechanisms directed towards eggs.

An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer

PubMed Central

2010-01-01

Background Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse. Methods We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models. Results An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database. Conclusions This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples. PMID:20584321

Genome-Wide Identification and Expression Analysis of NBS-Encoding Genes in Malus x domestica and Expansion of NBS Genes Family in Rosaceae

PubMed Central

Arya, Preeti; Kumar, Gulshan; Acharya, Vishal; Singh, Anil K.

2014-01-01

Nucleotide binding site leucine-rich repeats (NBS-LRR) disease resistance proteins play an important role in plant defense against pathogen attack. A number of recent studies have been carried out to identify and characterize NBS-LRR gene families in many important plant species. In this study, we identified NBS-LRR gene family comprising of 1015 NBS-LRRs using highly stringent computational methods. These NBS-LRRs were characterized on the basis of conserved protein motifs, gene duplication events, chromosomal locations, phylogenetic relationships and digital gene expression analysis. Surprisingly, equal distribution of Toll/interleukin-1 receptor (TIR) and coiled coil (CC) (1∶1) was detected in apple while the unequal distribution was reported in majority of all other known plant genome studies. Prediction of gene duplication events intriguingly revealed that not only tandem duplication but also segmental duplication may equally be responsible for the expansion of the apple NBS-LRR gene family. Gene expression profiling using expressed sequence tags database of apple and quantitative real-time PCR (qRT-PCR) revealed the expression of these genes in wide range of tissues and disease conditions, respectively. Taken together, this study will provide a blueprint for future efforts towards improvement of disease resistance in apple. PMID:25232838

Plant Genome Resources at the National Center for Biotechnology Information

PubMed Central

Wheeler, David L.; Smith-White, Brian; Chetvernin, Vyacheslav; Resenchuk, Sergei; Dombrowski, Susan M.; Pechous, Steven W.; Tatusova, Tatiana; Ostell, James

2005-01-01

The National Center for Biotechnology Information (NCBI) integrates data from more than 20 biological databases through a flexible search and retrieval system called Entrez. A core Entrez database, Entrez Nucleotide, includes GenBank and is tightly linked to the NCBI Taxonomy database, the Entrez Protein database, and the scientific literature in PubMed. A suite of more specialized databases for genomes, genes, gene families, gene expression, gene variation, and protein domains dovetails with the core databases to make Entrez a powerful system for genomic research. Linked to the full range of Entrez databases is the NCBI Map Viewer, which displays aligned genetic, physical, and sequence maps for eukaryotic genomes including those of many plants. A specialized plant query page allow maps from all plant genomes covered by the Map Viewer to be searched in tandem to produce a display of aligned maps from several species. PlantBLAST searches against the sequences shown in the Map Viewer allow BLAST alignments to be viewed within a genomic context. In addition, precomputed sequence similarities, such as those for proteins offered by BLAST Link, enable fluid navigation from unannotated to annotated sequences, quickening the pace of discovery. NCBI Web pages for plants, such as Plant Genome Central, complete the system by providing centralized access to NCBI's genomic resources as well as links to organism-specific Web pages beyond NCBI. PMID:16010002

Gene expression analysis of colorectal cancer by bioinformatics strategy.

PubMed

Cui, Meng; Yuan, Junhua; Li, Jun; Sun, Bing; Li, Tao; Li, Yuantao; Wu, Guoliang

2014-10-01

We used bioinformatics technology to analyze gene expression profiles involved in colorectal cancer tissue samples and healthy controls. In this paper, we downloaded the gene expression profile GSE4107 from Gene Expression Omnibus (GEO) database, in which a total of 22 chips were available, including normal colonic mucosa tissue from normal healthy donors (n=10), colorectal cancer tissue samples from colorectal patients (n=33). To further understand the biological functions of the screened DGEs, the KEGG pathway enrichment analysis were conducted. Then we built a transcriptome network to study differentially co-expressed links. A total of 3151 DEGs of CRC were selected. Besides, total 164 DCGs (Differentially Coexpressed Gene, DCG) and 29279 DCLs (Differentially Co-expressed Link, DCL) were obtained. Furthermore, the significantly enriched KEGG pathways were Endocytosis, Calcium signaling pathway, Vascular smooth muscle contraction, Linoleic acid metabolism, Arginine and proline metabolism, Inositol phosphate metabolism and MAPK signaling pathway. Our results show that the generation of CRC involves multiple genes, TFs and pathways. Several signal and immune pathways are linked to CRC and give us more clues in the process of CRC. Hence, our work would pave ways for novel diagnosis of CRC, and provided theoretical guidance into cancer therapy.

Molecular Characterization, Gene Evolution, and Expression Analysis of the Fructose-1, 6-bisphosphate Aldolase (FBA) Gene Family in Wheat (Triticum aestivum L.)

PubMed Central

Lv, Geng-Yin; Guo, Xiao-Guang; Xie, Li-Ping; Xie, Chang-Gen; Zhang, Xiao-Hong; Yang, Yuan; Xiao, Lei; Tang, Yu-Ying; Pan, Xing-Lai; Guo, Ai-Guang; Xu, Hong

2017-01-01

Fructose-1, 6-bisphosphate aldolase (FBA) is a key plant enzyme that is involved in glycolysis, gluconeogenesis, and the Calvin cycle. It plays significant roles in biotic and abiotic stress responses, as well as in regulating growth and development processes. In the present paper, 21 genes encoding TaFBA isoenzymes were identified, characterized, and categorized into three groups: class I chloroplast/plastid FBA (CpFBA), class I cytosol FBA (cFBA), and class II chloroplast/plastid FBA. By using a prediction online database and genomic PCR analysis of Chinese Spring nulli-tetrasomic lines, we have confirmed the chromosomal location of these genes in 12 chromosomes of four homologous groups. Sequence and genomic structure analysis revealed the high identity of the allelic TaFBA genes and the origin of different TaFBA genes. Numerous putative environment stimulus-responsive cis-elements have been identified in 1,500-bp regions of TaFBA gene promoters, of which the most abundant are the light-regulated elements (LREs). Phylogenetic reconstruction using the deduced protein sequence of 245 FBA genes indicated an independent evolutionary pathway for the class I and class II groups. Although, earlier studies have indicated that class II FBA only occurs in prokaryote and fungi, our results have demonstrated that a few class II CpFBAs exist in wheat and other closely related species. Class I TaFBA was predicted to be tetramers and class II to be dimers. Gene expression analysis based on microarray and transcriptome databases suggested the distinct role of TaFBAs in different tissues and developmental stages. The TaFBA 4–9 genes were highly expressed in leaves and might play important roles in wheat development. The differential expression patterns of the TaFBA genes in light/dark and a few abiotic stress conditions were also analyzed. The results suggested that LRE cis-elements of TaFBA gene promoters were not directly related to light responses. Most TaFBA genes had higher expression levels in the roots than in the shoots when under various stresses. Class I cytosol TaFBA genes, particularly TaFBA10/12/18 and TaFBA13/16, and three class II TaFBA genes are involved in responses to various abiotic stresses. Class I CpFBA genes in wheat are apparently sensitive to different stress conditions. PMID:28659962

Glioma IL13Rα2 Is Associated with Mesenchymal Signature Gene Expression and Poor Patient Prognosis

PubMed Central

Starr, Renate; Deng, Xutao; Badie, Behnam; Yuan, Yate-Ching; Forman, Stephen J.; Barish, Michael E.

2013-01-01

A major challenge for successful immunotherapy against glioma is the identification and characterization of validated targets. We have taken a bioinformatics approach towards understanding the biological context of IL-13 receptor α2 (IL13Rα2) expression in brain tumors, and its functional significance for patient survival. Querying multiple gene expression databases, we show that IL13Rα2 expression increases with glioma malignancy grade, and expression for high-grade tumors is bimodal, with approximately 58% of WHO grade IV gliomas over-expressing this receptor. By several measures, IL13Rα2 expression in patient samples and low-passage primary glioma lines most consistently correlates with the expression of signature genes defining mesenchymal subclass tumors and negatively correlates with proneural signature genes as defined by two studies. Positive associations were also noted with proliferative signature genes, whereas no consistent associations were found with either classical or neural signature genes. Probing the potential functional consequences of this mesenchymal association through IPA analysis suggests that IL13Rα2 expression is associated with activation of proinflammatory and immune pathways characteristic of mesenchymal subclass tumors. In addition, survival analyses indicate that IL13Rα2 over-expression is associated with poor patient prognosis, a single gene correlation ranking IL13Rα2 in the top ~1% of total gene expression probes with regard to survival association with WHO IV gliomas. This study better defines the functional consequences of IL13Rα2 expression by demonstrating association with mesenchymal signature gene expression and poor patient prognosis. It thus highlights the utility of IL13Rα2 as a therapeutic target, and helps define patient populations most likely to respond to immunotherapy in present and future clinical trials. PMID:24204956

Glioma IL13Rα2 is associated with mesenchymal signature gene expression and poor patient prognosis.

PubMed

Brown, Christine E; Warden, Charles D; Starr, Renate; Deng, Xutao; Badie, Behnam; Yuan, Yate-Ching; Forman, Stephen J; Barish, Michael E

2013-01-01

A major challenge for successful immunotherapy against glioma is the identification and characterization of validated targets. We have taken a bioinformatics approach towards understanding the biological context of IL-13 receptor α2 (IL13Rα2) expression in brain tumors, and its functional significance for patient survival. Querying multiple gene expression databases, we show that IL13Rα2 expression increases with glioma malignancy grade, and expression for high-grade tumors is bimodal, with approximately 58% of WHO grade IV gliomas over-expressing this receptor. By several measures, IL13Rα2 expression in patient samples and low-passage primary glioma lines most consistently correlates with the expression of signature genes defining mesenchymal subclass tumors and negatively correlates with proneural signature genes as defined by two studies. Positive associations were also noted with proliferative signature genes, whereas no consistent associations were found with either classical or neural signature genes. Probing the potential functional consequences of this mesenchymal association through IPA analysis suggests that IL13Rα2 expression is associated with activation of proinflammatory and immune pathways characteristic of mesenchymal subclass tumors. In addition, survival analyses indicate that IL13Rα2 over-expression is associated with poor patient prognosis, a single gene correlation ranking IL13Rα2 in the top ~1% of total gene expression probes with regard to survival association with WHO IV gliomas. This study better defines the functional consequences of IL13Rα2 expression by demonstrating association with mesenchymal signature gene expression and poor patient prognosis. It thus highlights the utility of IL13Rα2 as a therapeutic target, and helps define patient populations most likely to respond to immunotherapy in present and future clinical trials.

Identifying arsenic trioxide (ATO) functions in leukemia cells by using time series gene expression profiles.

PubMed

Yang, Hong; Lin, Shan; Cui, Jingru

2014-02-10

Arsenic trioxide (ATO) is presently the most active single agent in the treatment of acute promyelocytic leukemia (APL). In order to explore the molecular mechanism of ATO in leukemia cells with time series, we adopted bioinformatics strategy to analyze expression changing patterns and changes in transcription regulation modules of time series genes filtered from Gene Expression Omnibus database (GSE24946). We totally screened out 1847 time series genes for subsequent analysis. The KEGG (Kyoto encyclopedia of genes and genomes) pathways enrichment analysis of these genes showed that oxidative phosphorylation and ribosome were the top 2 significantly enriched pathways. STEM software was employed to compare changing patterns of gene expression with assigned 50 expression patterns. We screened out 7 significantly enriched patterns and 4 tendency charts of time series genes. The result of Gene Ontology showed that functions of times series genes mainly distributed in profiles 41, 40, 39 and 38. Seven genes with positive regulation of cell adhesion function were enriched in profile 40, and presented the same first increased model then decreased model as profile 40. The transcription module analysis showed that they mainly involved in oxidative phosphorylation pathway and ribosome pathway. Overall, our data summarized the gene expression changes in ATO treated K562-r cell lines with time and suggested that time series genes mainly regulated cell adhesive. Furthermore, our result may provide theoretical basis of molecular biology in treating acute promyelocytic leukemia. Copyright © 2013 Elsevier B.V. All rights reserved.

Expression of glutathione S-transferases in poplar trees (Populus trichocarpa) exposed to 2,4,6-trinitrotoluene (TNT).

PubMed

Brentner, Laura B; Mukherji, Sachiyo T; Merchie, Kate M; Yoon, Jong Moon; Schnoor, Jerald L; Van Aken, Benoit

2008-10-01

Twelve Populus genes were identified from Arabidopsis thaliana sequences previously shown to be induced by exposure to 2,4,6-trinitrotoluene (TNT). Using the resources of the Poplar Genome Project and National Center for Biotechnology Information databases, Populus conserved domains were identified and used to design gene specific primers. RNA extracted from root tissues of TNT-exposed hydroponic poplar plants was used to quantify the expression of genes by reverse-transcriptase real-time polymerase chain reaction. Cyclophilin and 18S ribosomal DNA genes were used as internal standards. Exposure to TNT resulted in a significant increase of gene expression of two glutathione S-transferases (GST), peaking at levels of 25.0 +/- 13.1 and 10 +/- 0.7 fold the expression level of non-exposed plants after 24 h for each of the GST genes, respectively. This paper demonstrates the use of functional genomics information from the model plant species, Arabidopsis, to identify genes which may be important in detoxification of TNT in the model phytoremediation species, Populus trichocarpa.

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.

Digital gene expression analysis of corky split vein caused by boron deficiency in 'Newhall' Navel Orange (Citrus sinensis Osbeck) for selecting differentially expressed genes related to vascular hypertrophy.

PubMed

Yang, Cheng-Quan; Liu, Yong-Zhong; An, Ji-Cui; Li, Shuang; Jin, Long-Fei; Zhou, Gao-Feng; Wei, Qing-Jiang; Yan, Hui-Qing; Wang, Nan-Nan; Fu, Li-Na; Liu, Xiao; Hu, Xiao-Mei; Yan, Ting-Shuai; Peng, Shu-Ang

2013-01-01

Corky split vein caused by boron (B) deficiency in 'Newhall' Navel Orange was studied in the present research. The boron-deficient citrus exhibited a symptom of corky split vein in mature leaves. Morphologic and anatomical surveys at four representative phases of corky split veins showed that the symptom was the result of vascular hypertrophy. Digital gene expression (DGE) analysis was performed based on the Illumina HiSeq™ 2000 platform, which was applied to analyze the gene expression profilings of corky split veins at four morphologic phases. Over 5.3 million clean reads per library were successfully mapped to the reference database and more than 22897 mapped genes per library were simultaneously obtained. Analysis of the differentially expressed genes (DEGs) revealed that the expressions of genes associated with cytokinin signal transduction, cell division, vascular development, lignin biosynthesis and photosynthesis in corky split veins were all affected. The expressions of WOL and ARR12 involved in the cytokinin signal transduction pathway were up-regulated at 1(st) phase of corky split vein development. Furthermore, the expressions of some cell cycle genes, CYCs and CDKB, and vascular development genes, WOX4 and VND7, were up-regulated at the following 2(nd) and 3(rd) phases. These findings indicated that the cytokinin signal transduction pathway may play a role in initiating symptom observed in our study.

Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes.

PubMed

Chandran, Anil Kumar Nalini; Yoo, Yo-Han; Cao, Peijian; Sharma, Rita; Sharma, Manoj; Dardick, Christopher; Ronald, Pamela C; Jung, Ki-Hong

2016-12-01

Protein kinases catalyze the transfer of a phosphate moiety from a phosphate donor to the substrate molecule, thus playing critical roles in cell signaling and metabolism. Although plant genomes contain more than 1000 genes that encode kinases, knowledge is limited about the function of each of these kinases. A major obstacle that hinders progress towards kinase characterization is functional redundancy. To address this challenge, we previously developed the rice kinase database (RKD) that integrated omics-scale data within a phylogenetics context. An updated version of rice kinase database (RKD) that contains metadata derived from NCBI GEO expression datasets has been developed. RKD 2.0 facilitates in-depth transcriptomic analyses of kinase-encoding genes in diverse rice tissues and in response to biotic and abiotic stresses and hormone treatments. We identified 261 kinases specifically expressed in particular tissues, 130 that are significantly up- regulated in response to biotic stress, 296 in response to abiotic stress, and 260 in response to hormones. Based on this update and Pearson correlation coefficient (PCC) analysis, we estimated that 19 out of 26 genes characterized through loss-of-function studies confer dominant functions. These were selected because they either had paralogous members with PCC values of <0.5 or had no paralog. Compared with the previous version of RKD, RKD 2.0 enables more effective estimations of functional redundancy or dominance because it uses comprehensive expression profiles rather than individual profiles. The integrated analysis of RKD with PCC establishes a single platform for researchers to select rice kinases for functional analyses.

Coordination of Gene Expression of Arachidonic and Docosahexaenoic Acid Cascade Enzymes during Human Brain Development and Aging

PubMed Central

Ryan, Veronica H.; Primiani, Christopher T.; Rao, Jagadeesh S.; Ahn, Kwangmi; Rapoport, Stanley I.; Blanchard, Helene

2014-01-01

Background The polyunsaturated arachidonic and docosahexaenoic acids (AA and DHA) participate in cell membrane synthesis during neurodevelopment, neuroplasticity, and neurotransmission throughout life. Each is metabolized via coupled enzymatic reactions within separate but interacting metabolic cascades. Hypothesis AA and DHA pathway genes are coordinately expressed and underlie cascade interactions during human brain development and aging. Methods The BrainCloud database for human non-pathological prefrontal cortex gene expression was used to quantify postnatal age changes in mRNA expression of 34 genes involved in AA and DHA metabolism. Results Expression patterns were split into Development (0 to 20 years) and Aging (21 to 78 years) intervals. Expression of genes for cytosolic phospholipases A2 (cPLA2), cyclooxygenases (COX)-1 and -2, and other AA cascade enzymes, correlated closely with age during Development, less so during Aging. Expression of DHA cascade enzymes was less inter-correlated in each period, but often changed in the opposite direction to expression of AA cascade genes. Except for the PLA2G4A (cPLA2 IVA) and PTGS2 (COX-2) genes at 1q25, highly inter-correlated genes were at distant chromosomal loci. Conclusions Coordinated age-related gene expression during the brain Development and Aging intervals likely underlies coupled changes in enzymes of the AA and DHA cascades and largely occur through distant transcriptional regulation. Healthy brain aging does not show upregulation of PLA2G4 or PTGS2 expression, which was found in Alzheimer's disease. PMID:24963629

Protein-protein interaction network of gene expression in the hydrocortisone-treated keloid.

PubMed

Chen, Rui; Zhang, Zhiliang; Xue, Zhujia; Wang, Lin; Fu, Mingang; Lu, Yi; Bai, Ling; Zhang, Ping; Fan, Zhihong

2015-01-01

In order to explore the molecular mechanism of hydrocortisone in keloid tissue, the gene expression profiles of keloid samples treated with hydrocortisone were subjected to bioinformatics analysis. Firstly, the gene expression profiles (GSE7890) of five samples of keloid treated with hydrocortisone and five untreated keloid samples were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, data were preprocessed using packages in R language and differentially expressed genes (DEGs) were screened using a significance analysis of microarrays (SAM) protocol. Thirdly, the DEGs were subjected to gene ontology (GO) function and KEGG pathway enrichment analysis. Finally, the interactions of DEGs in samples of keloid treated with hydrocortisone were explored in a human protein-protein interaction (PPI) network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software. Based on the analysis, 572 DEGs in the hydrocortisone-treated samples were screened; most of these were involved in the signal transduction and cell cycle. Furthermore, three critical genes in the module, including COL1A1, NID1, and PRELP, were screened in the PPI network analysis. These findings enhance understanding of the pathogenesis of the keloid and provide references for keloid therapy. © 2015 The International Society of Dermatology.

Bioinformatics approach reveals systematic mechanism underlying lung adenocarcinoma.

PubMed

Wu, Xiya; Zhang, Wei; Hu, Yunhua; Yi, Xianghua

2015-01-01

The purpose of this work was to explore the systematic molecular mechanism of lung adenocarcinoma and gain a deeper insight into it. Comprehensive bioinformatics methods were applied. Initially, significant differentially expressed genes (DEGs) were analyzed from the Affymetrix microarray data (GSE27262) deposited in the Gene Expression Omnibus (GEO). Subsequently, gene ontology (GO) analysis was performed using online Database for Annotation, Visualization and Integration Discovery (DAVID) software. Finally, significant pathway crosstalk was investigated based on the information derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. According to our results, the N-terminal globular domain of the type X collagen (COL10A1) gene and transmembrane protein 100 (TMEM100) gene were identified to be the most significant DEGs in tumor tissue compared with the adjacent normal tissues. The main GO categories were biological process, cellular component and molecular function. In addition, the crosstalk was significantly different between non-small cell lung cancer pathways and inositol phosphate metabolism pathway, focal adhesion signal pathway, vascular smooth muscle contraction signal pathway, peroxisome proliferator-activated receptor (PPAR) signaling pathway and calcium signaling pathway in tumor. Dysfunctional genes and pathways may play key roles in the progression and development of lung adenocarcinoma. Our data provide a systematic perspective for understanding this mechanism and may be helpful in discovering an effective treatment for lung adenocarcinoma.

Phenome-genome association studies of pancreatic cancer: new targets for therapy and diagnosis.

PubMed

Narayanan, Ramaswamy

2015-01-01

Pancreatic cancer, has a very high mortality rate and requires novel molecular targets for diagnosis and therapy. Genetic association studies over databases offer an attractive starting point for gene discovery. The National Center for Biotechnology Information (NCBI) Phenome Genome Integrator (PheGenI) tool was enriched for pancreatic cancer-associated traits. The genes associated with the trait were characterized using diverse bioinformatics tools for Genome-Wide Association (GWA), transcriptome and proteome profile and protein classes for motif and domain. Two hundred twenty-six genes were identified that had a genetic association with pancreatic cancer in the human genome. This included 25 uncharacterized open reading frames (ORFs). Bioinformatics analysis of these ORFs identified putative druggable proteins and biomarkers including enzymes, transporters and G-protein-coupled receptor signaling proteins. Secreted proteins including a neuroendocrine factor and a chemokine were identified. Five out of these ORFs encompassed non coding RNAs. The ORF protein expression was detected in numerous body fluids, such as ascites, bile, pancreatic juice, milk, plasma, serum and saliva. Transcriptome and proteome analyses showed a correlation of mRNA and protein expression for nine ORFs. Analysis of the Catalogue of Somatic Mutations in Cancer (COSMIC) database revealed a strong correlation across copy number variations and mRNA over-expression for four ORFs. Mining of the International Cancer Gene Consortium (ICGC) database identified somatic mutations in a significant number of pancreatic patients' tumors for most of these ORFs. The pancreatic cancer-associated ORFs were also found to be genetically associated with other neoplasms, including leukemia, malignant melanoma, neuroblastoma and prostate carcinomas, as well as other unrelated diseases and disorders, such as Alzheimer's disease, Crohn's disease, coronary diseases, attention deficit disorder and addiction. Based on Genome-Wide Association Studies (GWAS), copy number variations, somatic mutational status and correlation of gene expression in pancreatic tumors at the mRNA and protein level, expression specificity in normal tissues and detection in body fluids, six ORFs emerged as putative leads for pancreatic cancer. These six targets provide a basis for accelerated drug discovery and diagnostic marker development for pancreatic cancer. Copyright© 2015, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

sscMap: an extensible Java application for connecting small-molecule drugs using gene-expression signatures.

PubMed

Zhang, Shu-Dong; Gant, Timothy W

2009-07-31

Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap.

Discovering the Deregulated Molecular Functions Involved in Malignant Transformation of Endometriosis to Endometriosis-Associated Ovarian Carcinoma Using a Data-Driven, Function-Based Analysis

PubMed Central

Chang, Chia-Ming; Yang, Yi-Ping; Chuang, Jen-Hua; Chuang, Chi-Mu; Lin, Tzu-Wei; Wang, Peng-Hui; Yu, Mu-Hsien

2017-01-01

The clinical characteristics of clear cell carcinoma (CCC) and endometrioid carcinoma EC) are concomitant with endometriosis (ES), which leads to the postulation of malignant transformation of ES to endometriosis-associated ovarian carcinoma (EAOC). Different deregulated functional areas were proposed accounting for the pathogenesis of EAOC transformation, and there is still a lack of a data-driven analysis with the accumulated experimental data in publicly-available databases to incorporate the deregulated functions involved in the malignant transformation of EOAC. We used the microarray gene expression datasets of ES, CCC and EC downloaded from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) database. Then, we investigated the pathogenesis of EAOC by a data-driven, function-based analytic model with the quantified molecular functions defined by 1454 Gene Ontology (GO) term gene sets. This model converts the gene expression profiles to the functionome consisting of 1454 quantified GO functions, and then, the key functions involving the malignant transformation of EOAC can be extracted by a series of filters. Our results demonstrate that the deregulated oxidoreductase activity, metabolism, hormone activity, inflammatory response, innate immune response and cell-cell signaling play the key roles in the malignant transformation of EAOC. These results provide the evidence supporting the specific molecular pathways involved in the malignant transformation of EAOC. PMID:29113136

Comparative Analysis of Gene Expression for Convergent Evolution of Camera Eye Between Octopus and Human

PubMed Central

Ogura, Atsushi; Ikeo, Kazuho; Gojobori, Takashi

2004-01-01

Although the camera eye of the octopus is very similar to that of humans, phylogenetic and embryological analyses have suggested that their camera eyes have been acquired independently. It has been known as a typical example of convergent evolution. To study the molecular basis of convergent evolution of camera eyes, we conducted a comparative analysis of gene expression in octopus and human camera eyes. We sequenced 16,432 ESTs of the octopus eye, leading to 1052 nonredundant genes that have matches in the protein database. Comparing these 1052 genes with 13,303 already-known ESTs of the human eye, 729 (69.3%) genes were commonly expressed between the human and octopus eyes. On the contrary, when we compared octopus eye ESTs with human connective tissue ESTs, the expression similarity was quite low. To trace the evolutionary changes that are potentially responsible for camera eye formation, we also compared octopus-eye ESTs with the completed genome sequences of other organisms. We found that 1019 out of the 1052 genes had already existed at the common ancestor of bilateria, and 875 genes were conserved between humans and octopuses. It suggests that a larger number of conserved genes and their similar gene expression may be responsible for the convergent evolution of the camera eye. PMID:15289475

The Expression of Glyceraldehyde-3-Phosphate Dehydrogenase Associated Cell Cycle (GACC) Genes Correlates with Cancer Stage and Poor Survival in Patients with Solid Tumors

PubMed Central

Wang, Dunrui; Moothart, Daniel R.; Lowy, Douglas R.; Qian, Xiaolan

2013-01-01

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is often used as a stable housekeeping marker for constant gene expression. However, the transcriptional levels of GAPDH may be highly up-regulated in some cancers, including non-small cell lung cancers (NSCLC). Using a publically available microarray database, we identified a group of genes whose expression levels in some cancers are highly correlated with GAPDH up-regulation. The majority of the identified genes are cell cycle-dependent (GAPDH Associated Cell Cycle, or GACC). The up-regulation pattern of GAPDH positively associated genes in NSCLC is similar to that observed in cultured fibroblasts grown under conditions that induce anti-senescence. Data analysis demonstrated that up-regulated GAPDH levels are correlated with aberrant gene expression related to both glycolysis and gluconeogenesis pathways. Down-regulation of fructose-1,6-bisphosphatase (FBP1) in gluconeogenesis in conjunction with up-regulation of most glycolytic genes is closely related to high expression of GAPDH in the tumors. The data presented demonstrate that up-regulation of GAPDH positively associated genes is proportional to the malignant stage of various tumors and is associated with an unfavourable prognosis. Thus, this work suggests that GACC genes represent a potential new signature for cancer stage identification and disease prognosis. PMID:23620736

Gene Expression Omnibus (GEO): Microarray data storage, submission, retrieval, and analysis

PubMed Central

Barrett, Tanya

2006-01-01

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely distributes high-throughput molecular abundance data, predominantly gene expression data generated by DNA microarray technology. The database has a flexible design that can handle diverse styles of both unprocessed and processed data in a MIAME- (Minimum Information About a Microarray Experiment) supportive infrastructure that promotes fully annotated submissions. GEO currently stores about a billion individual gene expression measurements, derived from over 100 organisms, submitted by over 1,500 laboratories, addressing a wide range of biological phenomena. To maximize the utility of these data, several user-friendly Web-based interfaces and applications have been implemented that enable effective exploration, query, and visualization of these data, at the level of individual genes or entire studies. This chapter describes how the data are stored, submission procedures, and mechanisms for data retrieval and query. GEO is publicly accessible at http://www.ncbi.nlm.nih.gov/projects/geo/. PMID:16939800

Targetome Analysis Revealed Involvement of MiR-126 in Neurotrophin Signaling Pathway: A Possible Role in Prevention of Glioma Development.

PubMed

Rouigari, Maedeh; Dehbashi, Moein; Ghaedi, Kamran; Pourhossein, Meraj

2018-07-01

For the first time, we used molecular signaling pathway enrichment analysis to determine possible involvement of miR-126 and IRS-1 in neurotrophin pathway. In this prospective study, Validated and predicted targets (targetome) of miR-126 were collected following searching miRtarbase (http://mirtarbase.mbc.nctu.edu.tw/) and miRWalk 2.0 databases, respectively. Then, approximate expression of miR-126 targeting in Glioma tissue was examined using UniGene database (http://www.ncbi. nlm.nih.gov/unigene). In silico molecular pathway enrichment analysis was carried out by DAVID 6.7 database (http://david. abcc.ncifcrf.gov/) to explore which signaling pathway is related to miR-126 targeting and how miR-126 attributes to glioma development. MiR-126 exerts a variety of functions in cancer pathogenesis via suppression of expression of target gene including PI3K, KRAS, EGFL7, IRS-1 and VEGF. Our bioinformatic studies implementing DAVID database, showed the involvement of miR-126 target genes in several signaling pathways including cancer pathogenesis, neurotrophin functions, Glioma formation, insulin function, focal adhesion production, chemokine synthesis and secretion and regulation of the actin cytoskeleton. Taken together, we concluded that miR-126 enhances the formation of glioma cancer stem cell probably via down regulation of IRS-1 in neurotrophin signaling pathway. Copyright© by Royan Institute. All rights reserved.

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.

Investigation of miR-136-5p key target genes and pathways in lung squamous cell cancer based on TCGA database and bioinformatics analysis.

PubMed

Xie, Zu-Cheng; Li, Tian-Tian; Gan, Bin-Liang; Gao, Xiang; Gao, Li; Chen, Gang; Hu, Xiao-Hua

2018-05-01

Lung squamous cell cancer (LUSC) is a common but challenging malignancy. It is important to illuminate the molecular mechanism of LUSC. Thus, we aim to explore the molecular mechanism of miR-136-5p in relation to LUSC. We used the Cancer Genome Atlas (TCGA) database to investigate the expression of miR-136-5p in relation to LUSC. Then, we identified the possible miR-136-5p target genes through intersection of the predicted miR-136-5p target genes and LUSC upregulated genes from TCGA. Bioinformatics analysis was performed to determine the key miR-136-5p targets and pathways associated with LUSC. Finally, the expression of hub genes, correlation between miR-136-5p and hub genes, and expected significance of hub genes were evaluated via the TCGA and Genotype-Tissue Expression (GTEx) project. MiR-136-5p was significantly downregulated in LUSC patients. Glucuronidation, glucuronosyltransferase, and the retinoic acid metabolic process were the most enriched metabolic interactions in LUSC patients. Ascorbate and aldarate metabolism, pentose and glucuronate interconversions, and retinol metabolism were identified as crucial pathways. Seven hub genes (UGT1A1, UGT1A3, UGT1A6, UGT1A7, UGT1A10, SRD5A1, and ADH7) were found to be upregulated, and UGT1A1, UGT1A3, UGT1A6, UGT1A7, and ADH7 were negatively correlated with miR-136-5p. UGT1A7 and ADH7 were the most significantly involved miR-136-5p target genes, and high expression of these genes was correlated with better overall survival and disease-free survival of LUSC patients. Downregulated miR-136-5p may target UGT1A7 and ADH7 and participate in ascorbate and aldarate metabolism, pentose and glucuronate interconversions, and retinol metabolism. High expression of UGT1A7 and ADH7 may indicate better prognosis of LUSC patients. Copyright © 2018. Published by Elsevier GmbH.

Comparison of TCDD-elicited genome-wide hepatic gene expression in Sprague–Dawley rats and C57BL/6 mice

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

Nault, Rance; Kim, Suntae; Zacharewski, Timothy R., E-mail: tzachare@msu.edu

2013-03-01

Although the structure and function of the AhR are conserved, emerging evidence suggests that downstream effects are species-specific. In this study, rat hepatic gene expression data from the DrugMatrix database (National Toxicology Program) were compared to mouse hepatic whole-genome gene expression data following treatment with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). For the DrugMatrix study, male Sprague–Dawley rats were gavaged daily with 20 μg/kg TCDD for 1, 3 and 5 days, while female C57BL/6 ovariectomized mice were examined 1, 3 and 7 days after a single oral gavage of 30 μg/kg TCDD. A total of 649 rat and 1386 mouse genes (|fold change| ≥more » 1.5, P1(t) ≥ 0.99) were differentially expressed following treatment. HomoloGene identified 11,708 orthologs represented across the rat Affymetrix 230 2.0 GeneChip (12,310 total orthologs), and the mouse 4 × 44K v.1 Agilent oligonucleotide array (17,578 total orthologs). Comparative analysis found 563 and 922 orthologs differentially expressed in response to TCDD in the rat and mouse, respectively, with 70 responses associated with immune function and lipid metabolism in common to both. Moreover, QRTPCR analysis of Ceacam1, showed divergent expression (induced in rat; repressed in mouse) functionally consistent with TCDD-elicited hepatic steatosis in the mouse but not the rat. Functional analysis identified orthologs involved in nucleotide binding and acetyltransferase activity in rat, while mouse-specific responses were associated with steroid, phospholipid, fatty acid, and carbohydrate metabolism. These results provide further evidence that TCDD elicits species-specific regulation of distinct gene networks, and outlines considerations for future comparisons of publicly available microarray datasets. - Highlights: ► We performed a whole-genome comparison of TCDD-regulated genes in mice and rats. ► Previous species comparisons were extended using data from the DrugMatrix database. ► Less than 15% of TCDD-regulated orthologs were common to mice and rats. ► Considerations for the comparison of publicly available datasets are described.« less

Isolation and Identification of miRNAs in Jatropha curcas

PubMed Central

Wang, Chun Ming; Liu, Peng; Sun, Fei; Li, Lei; Liu, Peng; Ye, Jian; Yue, Gen Hua

2012-01-01

MicroRNAs (miRNAs) are small noncoding RNAs that play crucial regulatory roles by targeting mRNAs for silencing. To identify miRNAs in Jatropha curcas L, a bioenergy crop, cDNA clones from two small RNA libraries of leaves and seeds were sequenced and analyzed using bioinformatic tools. Fifty-two putative miRNAs were found from the two libraries, among them six were identical to known miRNAs and 46 were novel. Differential expression patterns of 15 miRNAs in root, stem, leave, fruit and seed were detected using quantitative real-time PCR. Ten miRNAs were highly expressed in fruit or seed, implying that they may be involved in seed development or fatty acids synthesis in seed. Moreover, 28 targets of the isolated miRNAs were predicted from a jatropha cDNA library database. The miRNA target genes were predicted to encode a broad range of proteins. Sixteen targets had clear BLASTX hits to the Uniprot database and were associated with genes belonging to the three major gene ontology categories of biological process, cellular component, and molecular function. Four targets were identified for JcumiR004. By silencing JcumiR004 primary miRNA, expressions of the four target genes were up-regulated and oil composition were modulated significantly, indicating diverse functions of JcumiR004. PMID:22419887

Generation and Analysis of Expressed Sequence Tags from Olea europaea L.

PubMed Central

Ozdemir Ozgenturk, Nehir; Oruç, Fatma; Sezerman, Ugur; Kuçukural, Alper; Vural Korkut, Senay; Toksoz, Feriha; Un, Cemal

2010-01-01

Olive (Olea europaea L.) is an important source of edible oil which was originated in Near-East region. In this study, two cDNA libraries were constructed from young olive leaves and immature olive fruits for generation of ESTs to discover the novel genes and search the function of unknown genes of olive. The randomly selected 3840 colonies were sequenced for EST collection from both libraries. Readable 2228 sequences for olive leaf and 1506 sequences for olive fruit were assembled into 205 and 69 contigs, respectively, whereas 2478 were singletons. Putative functions of all 2752 differentially expressed unique sequences were designated by gene homology based on BLAST and annotated using BLAST2GO. While 1339 ESTs show no homology to the database, 2024 ESTs have homology (under 80%) with hypothetical proteins, putative proteins, expressed proteins, and unknown proteins in NCBI-GenBank. 635 EST's unique genes sequence have been identified by over 80% homology to known function in other species which were not previously described in Olea family. Only 3.1% of total EST's was shown similarity with olive database existing in NCBI. This generated EST's data and consensus sequences were submitted to NCBI as valuable source for functional genome studies of olive. PMID:21197085

Preparing and Analyzing Expressed Sequence Tags (ESTs) Library for the Mammary Tissue of Local Turkish Kivircik Sheep

PubMed Central

Omeroglu Ulu, Zehra; Ulu, Salih; Un, Cemal; Ozdem Oztabak, Kemal; Altunatmaz, Kemal

2017-01-01

Kivircik sheep is an important local Turkish sheep according to its meat quality and milk productivity. The aim of this study was to analyze gene expression profiles of both prenatal and postnatal stages for the Kivircik sheep. Therefore, two different cDNA libraries, which were taken from the same Kivircik sheep mammary gland tissue at prenatal and postnatal stages, were constructed. Total 3072 colonies which were randomly selected from the two libraries were sequenced for developing a sheep ESTs collection. We used Phred/Phrap computer programs for analysis of the raw EST and readable EST sequences were assembled with the CAP3 software. Putative functions of all unique sequences and statistical analysis were determined by Geneious software. Total 422 ESTs have over 80% similarity to known sequences of other organisms in NCBI classified by Panther database for the Gene Ontology (GO) category. By comparing gene expression profiles, we observed some putative genes that may be relative to reproductive performance or play important roles in milk synthesis and secretion. A total of 2414 ESTs have been deposited to the NCBI GenBank database (GW996847–GW999260). EST data in this study have provided a new source of information to functional genome studies of sheep. PMID:28239610

Computational analysis of microRNA function in heart development.

PubMed

Liu, Ganqiang; Ding, Min; Chen, Jiajia; Huang, Jinyan; Wang, Haiyun; Jing, Qing; Shen, Bairong

2010-09-01

Emerging evidence suggests that specific spatio-temporal microRNA (miRNA) expression is required for heart development. In recent years, hundreds of miRNAs have been discovered. In contrast, functional annotations are available only for a very small fraction of these regulatory molecules. In order to provide a global perspective for the biologists who study the relationship between differentially expressed miRNAs and heart development, we employed computational analysis to uncover the specific cellular processes and biological pathways targeted by miRNAs in mouse heart development. Here, we utilized Gene Ontology (GO) categories, KEGG Pathway, and GeneGo Pathway Maps as a gene functional annotation system for miRNA target enrichment analysis. The target genes of miRNAs were found to be enriched in functional categories and pathway maps in which miRNAs could play important roles during heart development. Meanwhile, we developed miRHrt (http://sysbio.suda.edu.cn/mirhrt/), a database aiming to provide a comprehensive resource of miRNA function in regulating heart development. These computational analysis results effectively illustrated the correlation of differentially expressed miRNAs with cellular functions and heart development. We hope that the identified novel heart development-associated pathways and the database presented here would facilitate further understanding of the roles and mechanisms of miRNAs in heart development.

cDNA-AFLP analysis reveals differential gene expression in compatible interaction of wheat challenged with Puccinia striiformis f. sp. tritici

PubMed Central

Wang, Xiaojie; Tang, Chunlei; Zhang, Gang; Li, Yingchun; Wang, Chenfang; Liu, Bo; Qu, Zhipeng; Zhao, Jie; Han, Qingmei; Huang, Lili; Chen, Xianming; Kang, Zhensheng

2009-01-01

Background Puccinia striiformis f. sp. tritici is a fungal pathogen causing stripe rust, one of the most important wheat diseases worldwide. The fungus is strictly biotrophic and thus, completely dependent on living host cells for its reproduction, which makes it difficult to study genes of the pathogen. In spite of its economic importance, little is known about the molecular basis of compatible interaction between the pathogen and wheat host. In this study, we identified wheat and P. striiformis genes associated with the infection process by conducting a large-scale transcriptomic analysis using cDNA-AFLP. Results Of the total 54,912 transcript derived fragments (TDFs) obtained using cDNA-AFLP with 64 primer pairs, 2,306 (4.2%) displayed altered expression patterns after inoculation, of which 966 showed up-regulated and 1,340 down-regulated. 186 TDFs produced reliable sequences after sequencing of 208 TDFs selected, of which 74 (40%) had known functions through BLAST searching the GenBank database. Majority of the latter group had predicted gene products involved in energy (13%), signal transduction (5.4%), disease/defence (5.9%) and metabolism (5% of the sequenced TDFs). BLAST searching of the wheat stem rust fungus genome database identified 18 TDFs possibly from the stripe rust pathogen, of which 9 were validated of the pathogen origin using PCR-based assays followed by sequencing confirmation. Of the 186 reliable TDFs, 29 homologous to genes known to play a role in disease/defense, signal transduction or uncharacterized genes were further selected for validation of cDNA-AFLP expression patterns using qRT-PCR analyses. Results confirmed the altered expression patterns of 28 (96.5%) genes revealed by the cDNA-AFLP technique. Conclusion The results show that cDNA-AFLP is a reliable technique for studying expression patterns of genes involved in the wheat-stripe rust interactions. Genes involved in compatible interactions between wheat and the stripe rust pathogen were identified and their expression patterns were determined. The present study should be helpful in elucidating the molecular basis of the infection process, and identifying genes that can be targeted for inhibiting the growth and reproduction of the pathogen. Moreover, this study can also be used to elucidate the defence responses of the genes that were of plant origin. PMID:19566949

Generation of a total of 6483 expressed sequence tags from 60 day-old bovine whole fetus and fetal placenta.

PubMed

Oishi, M; Gohma, H; Lejukole, H Y; Taniguchi, Y; Yamada, T; Suzuki, K; Shinkai, H; Uenishi, H; Yasue, H; Sasaki, Y

2004-05-01

Expressed sequence tags (ESTs) generated based on characterization of clones isolated randomly from cDNA libraries are used to study gene expression profiles in specific tissues and to provide useful information for characterizing tissue physiology. In this study, two directionally cloned cDNA libraries were constructed from 60 day-old bovine whole fetus and fetal placenta. We have characterized 5357 and 1126 clones, and then identified 3464 and 795 unique sequences for the fetus and placenta cDNA libraries: 1851 and 504 showed homology to already identified genes, and 1613 and 291 showed no significant matches to any of the sequences in DNA databases, respectively. Further, we found 94 unique sequences overlapping in both the fetus and the placenta, leading to a catalog of 4165 genes expressed in 60 day-old fetus and placenta. The catalog is used to examine expression profile of genes in 60 day-old bovine fetus and placenta.

Comprehensive Transcriptome Analysis of Sex-Biased Expressed Genes Reveals Discrete Biological and Physiological Features of Male and Female Schistosoma japonicum.

PubMed

Cai, Pengfei; Liu, Shuai; Piao, Xianyu; Hou, Nan; Gobert, Geoffrey N; McManus, Donald P; Chen, Qijun

2016-04-01

Schistosomiasis is a chronic and debilitating disease caused by blood flukes (digenetic trematodes) of the genus Schistosoma. Schistosomes are sexually dimorphic and exhibit dramatic morphological changes during a complex lifecycle which requires subtle gene regulatory mechanisms to fulfil these complex biological processes. In the current study, a 41,982 features custom DNA microarray, which represents the most comprehensive probe coverage for any schistosome transcriptome study, was designed based on public domain and local databases to explore differential gene expression in S. japonicum. We found that approximately 1/10 of the total annotated genes in the S. japonicum genome are differentially expressed between adult males and females. In general, genes associated with the cytoskeleton, and motor and neuronal activities were readily expressed in male adult worms, whereas genes involved in amino acid metabolism, nucleotide biosynthesis, gluconeogenesis, glycosylation, cell cycle processes, DNA synthesis and genome fidelity and stability were enriched in females. Further, miRNAs target sites within these gene sets were predicted, which provides a scenario whereby the miRNAs potentially regulate these sex-biased expressed genes. The study significantly expands the expressional and regulatory characteristics of gender-biased expressed genes in schistosomes with high accuracy. The data provide a better appreciation of the biological and physiological features of male and female schistosome parasites, which may lead to novel vaccine targets and the development of new therapeutic interventions.

Transcriptome-Wide Identification of Reference Genes for Expression Analysis of Soybean Responses to Drought Stress along the Day.

PubMed

Marcolino-Gomes, Juliana; Rodrigues, Fabiana Aparecida; Fuganti-Pagliarini, Renata; Nakayama, Thiago Jonas; Ribeiro Reis, Rafaela; Bouças Farias, Jose Renato; Harmon, Frank G; Correa Molinari, Hugo Bruno; Correa Molinari, Mayla Daiane; Nepomuceno, Alexandre

2015-01-01

The soybean transcriptome displays strong variation along the day in optimal growth conditions and also in response to adverse circumstances, like drought stress. However, no study conducted to date has presented suitable reference genes, with stable expression along the day, for relative gene expression quantification in combined studies on drought stress and diurnal oscillations. Recently, water deficit responses have been associated with circadian clock oscillations at the transcription level, revealing the existence of hitherto unknown processes and increasing the demand for studies on plant responses to drought stress and its oscillation during the day. We performed data mining from a transcriptome-wide background using microarrays and RNA-seq databases to select an unpublished set of candidate reference genes, specifically chosen for the normalization of gene expression in studies on soybean under both drought stress and diurnal oscillations. Experimental validation and stability analysis in soybean plants submitted to drought stress and sampled during a 24 h timecourse showed that four of these newer reference genes (FYVE, NUDIX, Golgin-84 and CYST) indeed exhibited greater expression stability than the conventionally used housekeeping genes (ELF1-β and β-actin) under these conditions. We also demonstrated the effect of using reference candidate genes with different stability values to normalize the relative expression data from a drought-inducible soybean gene (DREB5) evaluated in different periods of the day.

Expression of uncharacterized male germ cell-specific genes and discovery of novel sperm-tail proteins in mice.

PubMed

Kwon, Jun Tae; Ham, Sera; Jeon, Suyeon; Kim, Youil; Oh, Seungmin; Cho, Chunghee

2017-01-01

The identification and characterization of germ cell-specific genes are essential if we hope to comprehensively understand the mechanisms of spermatogenesis and fertilization. Here, we searched the mouse UniGene databases and identified 13 novel genes as being putatively testis-specific or -predominant. Our in silico and in vitro analyses revealed that the expressions of these genes are testis- and germ cell-specific, and that they are regulated in a stage-specific manner during spermatogenesis. We generated antibodies against the proteins encoded by seven of the genes to facilitate their characterization in male germ cells. Immunoblotting and immunofluorescence analyses revealed that one of these proteins was expressed only in testicular germ cells, three were expressed in both testicular germ cells and testicular sperm, and the remaining three were expressed in sperm of the testicular stages and in mature sperm from the epididymis. Further analysis of the latter three proteins showed that they were all associated with cytoskeletal structures in the sperm flagellum. Among them, MORN5, which is predicted to contain three MORN motifs, is conserved between mouse and human sperm. In conclusion, we herein identify 13 authentic genes with male germ cell-specific expression, and provide comprehensive information about these genes and their encoded products. Our finding will facilitate future investigations into the functional roles of these novel genes in spermatogenesis and sperm functions.

Identification of Key Pathways and Genes in L4 Dorsal Root Ganglion (DRG) After Sciatic Nerve Injury via Microarray Analysis.

PubMed

Zhao, He; Duan, Li-Jun; Sun, Qing-Ling; Gao, Yu-Shan; Yang, Yong-Dong; Tang, Xiang-Sheng; Zhao, Ding-Yan; Xiong, Yang; Hu, Zhen-Guo; Li, Chuan-Hong; Chen, Si-Xue; Liu, Tao; Yu, Xing

2018-04-19

Peripheral nerve injury (PNI) has devastating consequences. Dorsal root ganglion as a pivotal locus participates in the process of neuropathic pain and nerve regeneration. In recent years, gene sequencing technology has seen rapid rise in the biomedicine field. So, we attempt to gain insight into in the mechanism of neuropathic pain and nerve regeneration in the transcriptional level and to explore novel genes through bioinformatics analysis. The gene expression profiles of GSE96051 were downloaded from GEO database. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed by Cytoscape software. Our results showed that both IL-6 and Jun genes and the signaling pathway of MAPK, apoptosis, P53 present their vital modulatory role in nerve regeneration and neuropathic pain. Noteworthy, 13 hub genes associated with neuropathic pain and nerve regeneration, including Ccl12, Ppp1r15a, Cdkn1a, Atf3, Nts, Dusp1, Ccl7, Csf, Gadd45a, Serpine1, Timp1 were rarely reported in PubMed database, these genes may provide us the new orientation in experimental research and clinical study. Our results may provide more deep insight into the mechanism and a promising therapeutic target. The next step is to put our emphasis on an experiment level and to verify the novel genes from 13 hub genes.

Gene function in early mouse embryonic stem cell differentiation

PubMed Central

Sene, Kagnew Hailesellasse; Porter, Christopher J; Palidwor, Gareth; Perez-Iratxeta, Carolina; Muro, Enrique M; Campbell, Pearl A; Rudnicki, Michael A; Andrade-Navarro, Miguel A

2007-01-01

Background Little is known about the genes that drive embryonic stem cell differentiation. However, such knowledge is necessary if we are to exploit the therapeutic potential of stem cells. To uncover the genetic determinants of mouse embryonic stem cell (mESC) differentiation, we have generated and analyzed 11-point time-series of DNA microarray data for three biologically equivalent but genetically distinct mESC lines (R1, J1, and V6.5) undergoing undirected differentiation into embryoid bodies (EBs) over a period of two weeks. Results We identified the initial 12 hour period as reflecting the early stages of mESC differentiation and studied probe sets showing consistent changes of gene expression in that period. Gene function analysis indicated significant up-regulation of genes related to regulation of transcription and mRNA splicing, and down-regulation of genes related to intracellular signaling. Phylogenetic analysis indicated that the genes showing the largest expression changes were more likely to have originated in metazoans. The probe sets with the most consistent gene changes in the three cell lines represented 24 down-regulated and 12 up-regulated genes, all with closely related human homologues. Whereas some of these genes are known to be involved in embryonic developmental processes (e.g. Klf4, Otx2, Smn1, Socs3, Tagln, Tdgf1), our analysis points to others (such as transcription factor Phf21a, extracellular matrix related Lama1 and Cyr61, or endoplasmic reticulum related Sc4mol and Scd2) that have not been previously related to mESC function. The majority of identified functions were related to transcriptional regulation, intracellular signaling, and cytoskeleton. Genes involved in other cellular functions important in ESC differentiation such as chromatin remodeling and transmembrane receptors were not observed in this set. Conclusion Our analysis profiles for the first time gene expression at a very early stage of mESC differentiation, and identifies a functional and phylogenetic signature for the genes involved. The data generated constitute a valuable resource for further studies. All DNA microarray data used in this study are available in the StemBase database of stem cell gene expression data [1] and in the NCBI's GEO database. PMID:17394647

The DNA methylation profile of liver tumors in C3H mice and identification of differentially methylated regions involved in the regulation of tumorigenic genes.

PubMed

Matsushita, Junya; Okamura, Kazuyuki; Nakabayashi, Kazuhiko; Suzuki, Takehiro; Horibe, Yu; Kawai, Tomoko; Sakurai, Toshihiro; Yamashita, Satoshi; Higami, Yoshikazu; Ichihara, Gaku; Hata, Kenichiro; Nohara, Keiko

2018-03-22

C3H mice have been frequently used in cancer studies as animal models of spontaneous liver tumors and chemically induced hepatocellular carcinoma (HCC). Epigenetic modifications, including DNA methylation, are among pivotal control mechanisms of gene expression leading to carcinogenesis. Although information on somatic mutations in liver tumors of C3H mice is available, epigenetic aspects are yet to be clarified. We performed next generation sequencing-based analysis of DNA methylation and microarray analysis of gene expression to explore genes regulated by DNA methylation in spontaneous liver tumors of C3H mice. Overlaying these data, we selected cancer-related genes whose expressions are inversely correlated with DNA methylation levels in the associated differentially methylated regions (DMRs) located around transcription start sites (TSSs) (promoter DMRs). We further assessed mutuality of the selected genes for expression and DNA methylation in human HCC using the Cancer Genome Atlas (TCGA) database. We obtained data on genome-wide DNA methylation profiles in the normal and tumor livers of C3H mice. We identified promoter DMRs of genes which are reported to be related to cancer and whose expressions are inversely correlated with the DNA methylation, including Mst1r, Slpi and Extl1. The association between DNA methylation and gene expression was confirmed using a DNA methylation inhibitor 5-aza-2'-deoxycytidine (5-aza-dC) in Hepa1c1c7 cells and Hepa1-6 cells. Overexpression of Mst1r in Hepa1c1c7 cells illuminated a novel downstream pathway via IL-33 upregulation. Database search indicated that gene expressions of Mst1r and Slpi are upregulated and the TSS upstream regions are hypomethylated also in human HCC. These results suggest that DMRs, including those of Mst1r and Slpi, are involved in liver tumorigenesis in C3H mice, and also possibly in human HCC. Our study clarified genome wide DNA methylation landscape of C3H mice. The data provide useful information for further epigenetic studies of mice models of HCC. The present study particularly proposed novel DNA methylation-regulated pathways for Mst1r and Slpi, which may be applied not only to mouse HCC but also to human HCC.

Tumor SHB gene expression affects disease characteristics in human acute myeloid leukemia.

PubMed

Jamalpour, Maria; Li, Xiujuan; Cavelier, Lucia; Gustafsson, Karin; Mostoslavsky, Gustavo; Höglund, Martin; Welsh, Michael

2017-10-01

The mouse Shb gene coding for the Src Homology 2-domain containing adapter protein B has recently been placed in context of BCRABL1-induced myeloid leukemia in mice and the current study was performed in order to relate SHB to human acute myeloid leukemia (AML). Publicly available AML databases were mined for SHB gene expression and patient survival. SHB gene expression was determined in the Uppsala cohort of AML patients by qPCR. Cell proliferation was determined after SHB gene knockdown in leukemic cell lines. Despite a low frequency of SHB gene mutations, many tumors overexpressed SHB mRNA compared with normal myeloid blood cells. AML patients with tumors expressing low SHB mRNA displayed longer survival times. A subgroup of AML exhibiting a favorable prognosis, acute promyelocytic leukemia (APL) with a PMLRARA translocation, expressed less SHB mRNA than AML tumors in general. When examining genes co-expressed with SHB in AML tumors, four other genes ( PAX5, HDAC7, BCORL1, TET1) related to leukemia were identified. A network consisting of these genes plus SHB was identified that relates to certain phenotypic characteristics, such as immune cell, vascular and apoptotic features. SHB knockdown in the APL PMLRARA cell line NB4 and the monocyte/macrophage cell line MM6 adversely affected proliferation, linking SHB gene expression to tumor cell expansion and consequently to patient survival. It is concluded that tumor SHB gene expression relates to AML survival and its subgroup APL. Moreover, this gene is included in a network of genes that plays a role for an AML phenotype exhibiting certain immune cell, vascular and apoptotic characteristics.

[Identification of genes that are specifically/preferentially expressed in developing cotton fibers by mRNA fluorescence differential display (FDD)].

PubMed

Sun, Jie; Li, Yuan-Li; Wang, Ruo-Hai; Xia, Gui-Xian

2004-01-01

Fluorescence differential display (FDD) technique was used to identify genes that are specifically or preferentially expressed in different developmental stages of cotton fiber cells. One hundred and nine differentially displayed cDNA fragments were isolated using 9, 21 and 27 DPA (days postanthesis) fibers as experimental materials. By a combination of two rounds of reverse Northern hybridization and Northern blot analyses, a number of such cDNA fragments were proved to represent fiber-specific/preferential genes. Sequencing determination and database searching indicated that most of these genes are novel. This work is an important step towards cloning the full-length cDNAs and characterizing the cellular functions of aforementioned genes in fiber development.

A dehydration-inducible gene in the truffle Tuber borchii identifies a novel group of dehydrins

PubMed Central

Abba', Simona; Ghignone, Stefano; Bonfante, Paola

2006-01-01

Background The expressed sequence tag M6G10 was originally isolated from a screening for differentially expressed transcripts during the reproductive stage of the white truffle Tuber borchii. mRNA levels for M6G10 increased dramatically during fruiting body maturation compared to the vegetative mycelial stage. Results Bioinformatics tools, phylogenetic analysis and expression studies were used to support the hypothesis that this sequence, named TbDHN1, is the first dehydrin (DHN)-like coding gene isolated in fungi. Homologs of this gene, all defined as "coding for hypothetical proteins" in public databases, were exclusively found in ascomycetous fungi and in plants. Although complete (or almost complete) fungal genomes and EST collections of some Basidiomycota and Glomeromycota are already available, DHN-like proteins appear to be represented only in Ascomycota. A new and previously uncharacterized conserved signature pattern was identified and proposed to Uniprot database as the main distinguishing feature of this new group of DHNs. Expression studies provide experimental evidence of a transcript induction of TbDHN1 during cellular dehydration. Conclusion Expression pattern and sequence similarities to known plant DHNs indicate that TbDHN1 is the first characterized DHN-like protein in fungi. The high similarity of TbDHN1 with homolog coding sequences implies the existence of a novel fungal/plant group of LEA Class II proteins characterized by a previously undescribed signature pattern. PMID:16512918

An effective fuzzy kernel clustering analysis approach for gene expression data.

PubMed

Sun, Lin; Xu, Jiucheng; Yin, Jiaojiao

2015-01-01

Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First of all, to optimize characteristic differences and estimate optimal cluster number, Gaussian kernel function is introduced to improve spectrum analysis method (SAM). By combining subtractive clustering with max-min distance mean, maximum distance method (MDM) is proposed to determine cluster centers. Then, the corresponding steps of improved SAM (ISAM) and MDM are given respectively, whose superiority and stability are illustrated through performing experimental comparisons on gene expression data. Finally, by introducing ISAM and MDM into FKCA, an effective improved FKCA algorithm is proposed. Experimental results from public gene expression data and UCI database show that the proposed algorithms are feasible for cluster analysis, and the clustering accuracy is higher than the other related clustering algorithms.

Identification of Regulatory Genes Implicated in Continuous Flowering of Longan (Dimocarpus longan L.)

PubMed Central

Jia, Tianqi; Wei, Danfeng; Meng, Shan; Allan, Andrew C.; Zeng, Lihui

2014-01-01

Longan (Dimocarpus longan L.) is a tropical/subtropical fruit tree of significant economic importance in Southeast Asia. However, a lack of transcriptomic and genomic information hinders research on longan traits, such as the control of flowering. In this study, high-throughput RNA sequencing (RNA-Seq) was used to investigate differentially expressed genes between a unique longan cultivar ‘Sijimi’(S) which flowers throughout the year and a more typical cultivar ‘Lidongben’(L) which flowers only once in the season, with the aim of identifying candidate genes associated with continuous flowering. 36,527 and 40,982 unigenes were obtained by de novo assembly of the clean reads from cDNA libraries of L and S cultivars. Additionally 40,513 unigenes were assembled from combined reads of these libraries. A total of 32,475 unigenes were annotated by BLAST search to NCBI non-redundant protein (NR), Swiss-Prot, Clusters of Orthologous Groups (COGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Of these, almost fifteen thousand unigenes were identified as significantly differentially expressed genes (DEGs) by using Reads Per kb per Million reads (RPKM) method. A total of 6,415 DEGs were mapped to 128 KEGG pathways, and 8,743 DEGs were assigned to 54 Gene Ontology categories. After blasting the DEGs to public sequence databases, 539 potential flowering-related DEGs were identified. In addition, 107 flowering-time genes were identified in longan, their expression levels between two longan samples were compared by RPKM method, of which the expression levels of 15 were confirmed by real-time quantitative PCR. Our results suggest longan homologues of SHORT VEGETATIVE PHASE (SVP), GIGANTEA (GI), F-BOX 1 (FKF1) and EARLY FLOWERING 4 (ELF4) may be involved this flowering trait and ELF4 may be a key gene. The identification of candidate genes related to continuous flowering will provide new insight into the molecular process of regulating flowering time in woody plants. PMID:25479005

Prostate cancer-associated gene expression alterations determined from needle biopsies.

PubMed

Qian, David Z; Huang, Chung-Ying; O'Brien, Catherine A; Coleman, Ilsa M; Garzotto, Mark; True, Lawrence D; Higano, Celestia S; Vessella, Robert; Lange, Paul H; Nelson, Peter S; Beer, Tomasz M

2009-05-01

To accurately identify gene expression alterations that differentiate neoplastic from normal prostate epithelium using an approach that avoids contamination by unwanted cellular components and is not compromised by acute gene expression changes associated with tumor devascularization and resulting ischemia. Approximately 3,000 neoplastic and benign prostate epithelial cells were isolated using laser capture microdissection from snap-frozen prostate biopsy specimens provided by 31 patients who subsequently participated in a clinical trial of preoperative chemotherapy. cDNA synthesized from amplified total RNA was hybridized to custom-made microarrays composed of 6,200 clones derived from the Prostate Expression Database. Expression differences for selected genes were verified using quantitative reverse transcription-PCR. Comparative analyses identified 954 transcript alterations associated with cancer (q < 0.01%), including 149 differentially expressed genes with no known functional roles. Gene expression changes associated with ischemia and surgical removal of the prostate gland were absent. Genes up-regulated in prostate cancer were statistically enriched in categories related to cellular metabolism, energy use, signal transduction, and molecular transport. Genes down-regulated in prostate cancers were enriched in categories related to immune response, cellular responses to pathogens, and apoptosis. A heterogeneous pattern of androgen receptor expression changes was noted. In exploratory analyses, androgen receptor down-regulation was associated with a lower probability of cancer relapse after neoadjuvant chemotherapy followed by radical prostatectomy. Assessments of tumor phenotypes based on gene expression for treatment stratification and drug targeting of oncogenic alterations may best be ascertained using biopsy-based analyses where the effects of ischemia do not complicate interpretation.

Prostate Cancer-Associated Gene Expression Alterations Determined from Needle Biopsies

PubMed Central

Qian, David Z.; Huang, Chung-Ying; O'Brien, Catherine A.; Coleman, Ilsa M.; Garzotto, Mark; True, Lawrence D.; Higano, Celestia S.; Vessella, Robert; Lange, Paul H.; Nelson, Peter S.; Beer, Tomasz M.

2010-01-01

Purpose To accurately identify gene expression alterations that differentiate neoplastic from normal prostate epithelium using an approach that avoids contamination by unwanted cellular components and is not compromised by acute gene expression changes associated with tumor devascularization and resulting ischemia. Experimental Design Approximately 3,000 neoplastic and benign prostate epithelial cells were isolated using laser capture microdissection from snap-frozen prostate biopsy specimens provided by 31 patients who subsequently participated in a clinical trial of preoperative chemotherapy. cDNA synthesized from amplified total RNA was hybridized to custom-made microarrays comprised of 6200 clones derived from the Prostate Expression Database. Expression differences for selected genes were verified using quantitative RT-PCR. Results Comparative analyses identified 954 transcript alterations associated with cancer (q value <0.01%) including 149 differentially expressed genes with no known functional roles. Gene expression changes associated with ischemia and surgical removal of the prostate gland were absent. Genes up-regulated in prostate cancer were statistically enriched in categories related to cellular metabolism, energy utilization, signal transduction, and molecular transport. Genes down-regulated in prostate cancers were enriched in categories related to immune response, cellular responses to pathogens, and apoptosis. A heterogeneous pattern of AR expression changes was noted. In exploratory analyses, AR down regulation was associated with a lower probability of cancer relapse after neoadjuvant chemotherapy followed by radical prostatectomy. Conclusions Assessments of tumor phenotypes based on gene expression for treatment stratification and drug targeting of oncogenic alterations may best be ascertained using biopsy-based analyses where the effects of ischemia do not complicate interpretation. PMID:19366833

Porcine transcriptome analysis based on 97 non-normalized cDNA libraries and assembly of 1,021,891 expressed sequence tags

PubMed Central

Gorodkin, Jan; Cirera, Susanna; Hedegaard, Jakob; Gilchrist, Michael J; Panitz, Frank; Jørgensen, Claus; Scheibye-Knudsen, Karsten; Arvin, Troels; Lumholdt, Steen; Sawera, Milena; Green, Trine; Nielsen, Bente J; Havgaard, Jakob H; Rosenkilde, Carina; Wang, Jun; Li, Heng; Li, Ruiqiang; Liu, Bin; Hu, Songnian; Dong, Wei; Li, Wei; Yu, Jun; Wang, Jian; Stærfeldt, Hans-Henrik; Wernersson, Rasmus; Madsen, Lone B; Thomsen, Bo; Hornshøj, Henrik; Bujie, Zhan; Wang, Xuegang; Wang, Xuefei; Bolund, Lars; Brunak, Søren; Yang, Huanming; Bendixen, Christian; Fredholm, Merete

2007-01-01

Background Knowledge of the structure of gene expression is essential for mammalian transcriptomics research. We analyzed a collection of more than one million porcine expressed sequence tags (ESTs), of which two-thirds were generated in the Sino-Danish Pig Genome Project and one-third are from public databases. The Sino-Danish ESTs were generated from one normalized and 97 non-normalized cDNA libraries representing 35 different tissues and three developmental stages. Results Using the Distiller package, the ESTs were assembled to roughly 48,000 contigs and 73,000 singletons, of which approximately 25% have a high confidence match to UniProt. Approximately 6,000 new porcine gene clusters were identified. Expression analysis based on the non-normalized libraries resulted in the following findings. The distribution of cluster sizes is scaling invariant. Brain and testes are among the tissues with the greatest number of different expressed genes, whereas tissues with more specialized function, such as developing liver, have fewer expressed genes. There are at least 65 high confidence housekeeping gene candidates and 876 cDNA library-specific gene candidates. We identified differential expression of genes between different tissues, in particular brain/spinal cord, and found patterns of correlation between genes that share expression in pairs of libraries. Finally, there was remarkable agreement in expression between specialized tissues according to Gene Ontology categories. Conclusion This EST collection, the largest to date in pig, represents an essential resource for annotation, comparative genomics, assembly of the pig genome sequence, and further porcine transcription studies. PMID:17407547

Intrinsic and extrinsic approaches for detecting genes in a bacterial genome.

PubMed Central

Borodovsky, M; Rudd, K E; Koonin, E V

1994-01-01

The unannotated regions of the Escherichia coli genome DNA sequence from the EcoSeq6 database, totaling 1,278 'intergenic' sequences of the combined length of 359,279 basepairs, were analyzed using computer-assisted methods with the aim of identifying putative unknown genes. The proposed strategy for finding new genes includes two key elements: i) prediction of expressed open reading frames (ORFs) using the GeneMark method based on Markov chain models for coding and non-coding regions of Escherichia coli DNA, and ii) search for protein sequence similarities using programs based on the BLAST algorithm and programs for motif identification. A total of 354 putative expressed ORFs were predicted by GeneMark. Using the BLASTX and TBLASTN programs, it was shown that 208 ORFs located in the unannotated regions of the E. coli chromosome are significantly similar to other protein sequences. Identification of 182 ORFs as probable genes was supported by GeneMark and BLAST, comprising 51.4% of the GeneMark 'hits' and 87.5% of the BLAST 'hits'. 73 putative new genes, comprising 20.6% of the GeneMark predictions, belong to ancient conserved protein families that include both eubacterial and eukaryotic members. This value is close to the overall proportion of highly conserved sequences among eubacterial proteins, indicating that the majority of the putative expressed ORFs that are predicted by GeneMark, but have no significant BLAST hits, nevertheless are likely to be real genes. The majority of the putative genes identified by BLAST search have been described since the release of the EcoSeq6 database, but about 70 genes have not been detected so far. Among these new identifications are genes encoding proteins with a variety of predicted functions including dehydrogenases, kinases, several other metabolic enzymes, ATPases, rRNA methyltransferases, membrane proteins, and different types of regulatory proteins. Images PMID:7984428

BμG@Sbase—a microbial gene expression and comparative genomic database

PubMed Central

Witney, Adam A.; Waldron, Denise E.; Brooks, Lucy A.; Tyler, Richard H.; Withers, Michael; Stoker, Neil G.; Wren, Brendan W.; Butcher, Philip D.; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future. PMID:21948792

BμG@Sbase--a microbial gene expression and comparative genomic database.

PubMed

Witney, Adam A; Waldron, Denise E; Brooks, Lucy A; Tyler, Richard H; Withers, Michael; Stoker, Neil G; Wren, Brendan W; Butcher, Philip D; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future.

Expression of alpha-expansin and expansin-like genes in deepwater rice.

PubMed

Lee, Yi; Kende, Hans

2002-11-01

Previously, we have studied the expression and regulation of four alpha- and 14 beta-expansin genes in deepwater rice (Oryza sativa). We now report on the structure, expression, and regulation of 22 additional alpha-expansin (Os-EXP) genes, four expansin-like (Os-EXPL) genes, and one expansin-related (Os-EXPR) gene, which have recently been identified in the expressed sequence tag and genomic databases of rice. Alpha-expansins are characterized by a series of conserved Cys residues in the N-terminal half of the protein, a histidine-phenylalanine-aspartate (HFD) motif in the central region, and a series of tryptophan residues near the carboxyl terminus. Of the 22 additional alpha-expansin genes, five are expressed in internodes and leaves, three in coleoptiles, and nine in roots, with high transcript levels in the growing regions of these organs. Transcripts of five alpha-expansin genes were found in roots only. Expression of five alpha-expansin genes was induced in the internode by treatment with gibberellin (GA) and by wounding. The wound response resulted from excising stem sections or from piercing pinholes into the stem of intact plants. EXPL proteins lack the HFD motif and have two additional Cys residues in their C- and N-terminal regions. The positions of conserved tryptophan residues at the C-terminal region are different from those of alpha- and beta-expansins. Expression of the Os-EXPL3 gene is correlated with elongation and slightly induced by applied GA. However, the expression of the Os-EXPL1 and Os-EXPL2 genes showed limited correlation with cell elongation and was not induced by GA. We found no expression of the Os-EXPR1 gene in the organs examined.

De novo sequencing and analysis of the transcriptome during the browning of fresh-cut Luffa cylindrica 'Fusi-3' fruits.

PubMed

Zhu, Haisheng; Liu, Jianting; Wen, Qingfang; Chen, Mindong; Wang, Bin; Zhang, Qianrong; Xue, Zhuzheng

2017-01-01

Fresh-cut luffa (Luffa cylindrica) fruits commonly undergo browning. However, little is known about the molecular mechanisms regulating this process. We used the RNA-seq technique to analyze the transcriptomic changes occurring during the browning of fresh-cut fruits from luffa cultivar 'Fusi-3'. Over 90 million high-quality reads were assembled into 58,073 Unigenes, and 60.86% of these were annotated based on sequences in four public databases. We detected 35,282 Unigenes with significant hits to sequences in the NCBInr database, and 24,427 Unigenes encoded proteins with sequences that were similar to those of known proteins in the Swiss-Prot database. Additionally, 20,546 and 13,021 Unigenes were similar to existing sequences in the Eukaryotic Orthologous Groups of proteins and Kyoto Encyclopedia of Genes and Genomes databases, respectively. Furthermore, 27,301 Unigenes were differentially expressed during the browning of fresh-cut luffa fruits (i.e., after 1-6 h). Moreover, 11 genes from five gene families (i.e., PPO, PAL, POD, CAT, and SOD) identified as potentially associated with enzymatic browning as well as four WRKY transcription factors were observed to be differentially regulated in fresh-cut luffa fruits. With the assistance of rapid amplification of cDNA ends technology, we obtained the full-length sequences of the 15 Unigenes. We also confirmed these Unigenes were expressed by quantitative real-time polymerase chain reaction analysis. This study provides a comprehensive transcriptome sequence resource, and may facilitate further studies aimed at identifying genes affecting luffa fruit browning for the exploitation of the underlying mechanism.

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

PubMed Central

2010-01-01

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

METEORIN-LIKE is a cytokine associated with barrier tissues and alternatively activated macrophages

PubMed Central

Ushach, Irina; Burkhardt, Amanda M.; Martinez, Cynthia; Hevezi, Peter A.; Gerber, Peter Arne; Buhren, Bettina Alexandra; Schrumpf, Holger; Valle-Rios, Ricardo; Vazquez, Monica I.; Homey, Bernhard; Zlotnik, Albert

2014-01-01

Cytokines are involved in many functions of the immune system including initiating, amplifying and resolving immune responses. Through bioinformatics analyses of a comprehensive database of gene expression (BIGE: Body Index of Gene Expression) we observed that a small secreted protein encoded by a poorly characterized gene called meteorin-like (METRNL), is highly expressed in mucosal tissues, skin and activated macrophages. Further studies indicate that Metrnl is produced by Alternatively Activated Macrophages (AAM) and M-CSF cultured bone marrow macrophages (M2-like macrophages). In the skin, METRNL is expressed by resting fibroblasts and IFNγ-treated keratinocytes. A screen of human skin-associated diseases showed significant over-expression of METRNL in psoriasis, prurigo nodularis, actinic keratosis and atopic dermatitis. METRNL is also up-regulated in synovial membranes of human rheumatoid arthritis. Taken together, these results indicate that Metrnl represents a novel cytokine, which is likely involved in both innate and acquired immune responses. PMID:25486603

Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations

PubMed Central

Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir

2004-01-01

Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586

Molecular time-course and the metabolic basis of entry into dauer in Caenorhabditis elegans.

PubMed

Jeong, Pan-Young; Kwon, Min-Seok; Joo, Hyoe-Jin; Paik, Young-Ki

2009-01-01

When Caenorhabditis elegans senses dauer pheromone (daumone), signaling inadequate growth conditions, it enters the dauer state, which is capable of long-term survival. However, the molecular pathway of dauer entry in C. elegans has remained elusive. To systematically monitor changes in gene expression in dauer paths, we used a DNA microarray containing 22,625 gene probes corresponding to 22,150 unique genes from C. elegans. We employed two different paths: direct exposure to daumone (Path 1) and normal growth media plus liquid culture (Path 2). Our data reveal that entry into dauer is accomplished through the multi-step process, which appears to be compartmentalized in time and according to metabolic flux. That is, a time-course of dauer entry in Path 1 shows that dauer larvae formation begins at post-embryonic stage S4 (48 h) and is complete at S6 (72 h). Our results also suggest the presence of a unique adaptive metabolic control mechanism that requires both stage-specific expression of specific genes and tight regulation of different modes of fuel metabolite utilization to sustain the energy balance in the context of prolonged survival under adverse growth conditions. It is apparent that worms entering dauer stage may rely heavily on carbohydrate-based energy reserves, whereas dauer larvae utilize fat or glyoxylate cycle-based energy sources. We created a comprehensive web-based dauer metabolic database for C. elegans (www.DauerDB.org) that makes it possible to search any gene and compare its relative expression at a specific stage, or evaluate overall patterns of gene expression in both paths. This database can be accessed by the research community and could be widely applicable to other related nematodes as a molecular atlas.

Altered Molecular Expression of the TLR4/NF-κB Signaling Pathway in Mammary Tissue of Chinese Holstein Cattle with Mastitis

PubMed Central

Wu, Jie; Li, Lian; Sun, Yu; Huang, Shuai; Tang, Juan; Yu, Pan; Wang, Genlin

2015-01-01

Toll-like receptor 4 (TLR4) mediated activation of the nuclear transcription factor κB (NF-κB) signaling pathway by mastitis initiates expression of genes associated with inflammation and the innate immune response. In this study, the profile of mastitis-induced differential gene expression in the mammary tissue of Chinese Holstein cattle was investigated by Gene-Chip microarray and bioinformatics. The microarray results revealed that 79 genes associated with the TLR4/NF-κB signaling pathway were differentially expressed. Of these genes, 19 were up-regulated and 29 were down-regulated in mastitis tissue compared to normal, healthy tissue. Statistical analysis of transcript and protein level expression changes indicated that 10 genes, namely TLR4, MyD88, IL-6, and IL-10, were up-regulated, while, CD14, TNF-α, MD-2, IL-β, NF-κB, and IL-12 were significantly down-regulated in mastitis tissue in comparison with normal tissue. Analyses using bioinformatics database resources, such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and the Gene Ontology Consortium (GO) for term enrichment analysis, suggested that these differently expressed genes implicate different regulatory pathways for immune function in the mammary gland. In conclusion, our study provides new evidence for better understanding the differential expression and mechanisms of the TLR4 /NF-κB signaling pathway in Chinese Holstein cattle with mastitis. PMID:25706977

Altered molecular expression of the TLR4/NF-κB signaling pathway in mammary tissue of Chinese Holstein cattle with mastitis.

PubMed

Wu, Jie; Li, Lian; Sun, Yu; Huang, Shuai; Tang, Juan; Yu, Pan; Wang, Genlin

2015-01-01

Toll-like receptor 4 (TLR4) mediated activation of the nuclear transcription factor κB (NF-κB) signaling pathway by mastitis initiates expression of genes associated with inflammation and the innate immune response. In this study, the profile of mastitis-induced differential gene expression in the mammary tissue of Chinese Holstein cattle was investigated by Gene-Chip microarray and bioinformatics. The microarray results revealed that 79 genes associated with the TLR4/NF-κB signaling pathway were differentially expressed. Of these genes, 19 were up-regulated and 29 were down-regulated in mastitis tissue compared to normal, healthy tissue. Statistical analysis of transcript and protein level expression changes indicated that 10 genes, namely TLR4, MyD88, IL-6, and IL-10, were up-regulated, while, CD14, TNF-α, MD-2, IL-β, NF-κB, and IL-12 were significantly down-regulated in mastitis tissue in comparison with normal tissue. Analyses using bioinformatics database resources, such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and the Gene Ontology Consortium (GO) for term enrichment analysis, suggested that these differently expressed genes implicate different regulatory pathways for immune function in the mammary gland. In conclusion, our study provides new evidence for better understanding the differential expression and mechanisms of the TLR4 /NF-κB signaling pathway in Chinese Holstein cattle with mastitis.

PACAP Interactions in the Mouse Brain: Implications for Behavioral and Other Disorders

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

Acquaah-Mensah, George; Taylor, Ronald C.; Bhave, Sanjiv V.

2012-01-10

As an activator of adenylate cyclase, the neuropeptide Pituitary Adenylate Cyclase Activating Peptide (PACAP) impacts levels of cyclic AMP, a key second messenger available in brain cells. PACAP is involved in certain adult behaviors. To elucidate PACAP interactions, a compendium of microarrays representing mRNA expression in the adult mouse whole brain was pooled from the Phenogen database for analysis. A regulatory network was computed based on mutual information between gene pairs using gene expression data across the compendium. Clusters among genes directly linked to PACAP, and probable interactions between corresponding proteins were computed. Database 'experts' affirmed some of the inferredmore » relationships. The findings suggest ADCY7 is probably the adenylate cyclase isoform most relevant to PACAP's action. They also support intervening roles for kinases including GSK3B, PI 3-kinase, SGK3 and AMPK. Other high-confidence interactions are hypothesized for future testing. This new information has implications for certain behavioral and other disorders.« less

Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods.

PubMed

Tuo, Youlin; An, Ning; Zhang, Ming

2018-03-01

The aim of the present study was to investigate the feature genes in metastatic breast cancer samples. A total of 5 expression profiles of metastatic breast cancer samples were downloaded from the Gene Expression Omnibus database, which were then analyzed using the MetaQC and MetaDE packages in R language. The feature genes between metastasis and non‑metastasis samples were screened under the threshold of P<0.05. Based on the protein‑protein interactions (PPIs) in the Biological General Repository for Interaction Datasets, Human Protein Reference Database and Biomolecular Interaction Network Database, the PPI network of the feature genes was constructed. The feature genes identified by topological characteristics were then used for support vector machine (SVM) classifier training and verification. The accuracy of the SVM classifier was then evaluated using another independent dataset from The Cancer Genome Atlas database. Finally, function and pathway enrichment analyses for genes in the SVM classifier were performed. A total of 541 feature genes were identified between metastatic and non‑metastatic samples. The top 10 genes with the highest betweenness centrality values in the PPI network of feature genes were Nuclear RNA Export Factor 1, cyclin‑dependent kinase 2 (CDK2), myelocytomatosis proto‑oncogene protein (MYC), Cullin 5, SHC Adaptor Protein 1, Clathrin heavy chain, Nucleolin, WD repeat domain 1, proteasome 26S subunit non‑ATPase 2 and telomeric repeat binding factor 2. The cyclin‑dependent kinase inhibitor 1A (CDKN1A), E2F transcription factor 1 (E2F1), and MYC interacted with CDK2. The SVM classifier constructed by the top 30 feature genes was able to distinguish metastatic samples from non‑metastatic samples [correct rate, specificity, positive predictive value and negative predictive value >0.89; sensitivity >0.84; area under the receiver operating characteristic curve (AUROC) >0.96]. The verification of the SVM classifier in an independent dataset (35 metastatic samples and 143 non‑metastatic samples) revealed an accuracy of 94.38% and AUROC of 0.958. Cell cycle associated functions and pathways were the most significant terms of the 30 feature genes. A SVM classifier was constructed to assess the possibility of breast cancer metastasis, which presented high accuracy in several independent datasets. CDK2, CDKN1A, E2F1 and MYC were indicated as the potential feature genes in metastatic breast cancer.

From 20th century metabolic wall charts to 21st century systems biology: database of mammalian metabolic enzymes

PubMed Central

Corcoran, Callan C.; Grady, Cameron R.; Pisitkun, Trairak; Parulekar, Jaya

2017-01-01

The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database (https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1,647 genes to these pathways, representing ~7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database (Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct. PMID:27974320

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data.

PubMed

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian

2017-01-01

In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.

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.

An emerging cyberinfrastructure for biodefense pathogen and pathogen–host data

PubMed Central

Zhang, C.; Crasta, O.; Cammer, S.; Will, R.; Kenyon, R.; Sullivan, D.; Yu, Q.; Sun, W.; Jha, R.; Liu, D.; Xue, T.; Zhang, Y.; Moore, M.; McGarvey, P.; Huang, H.; Chen, Y.; Zhang, J.; Mazumder, R.; Wu, C.; Sobral, B.

2008-01-01

The NIAID-funded Biodefense Proteomics Resource Center (RC) provides storage, dissemination, visualization and analysis capabilities for the experimental data deposited by seven Proteomics Research Centers (PRCs). The data and its publication is to support researchers working to discover candidates for the next generation of vaccines, therapeutics and diagnostics against NIAID's Category A, B and C priority pathogens. The data includes transcriptional profiles, protein profiles, protein structural data and host–pathogen protein interactions, in the context of the pathogen life cycle in vivo and in vitro. The database has stored and supported host or pathogen data derived from Bacillus, Brucella, Cryptosporidium, Salmonella, SARS, Toxoplasma, Vibrio and Yersinia, human tissue libraries, and mouse macrophages. These publicly available data cover diverse data types such as mass spectrometry, yeast two-hybrid (Y2H), gene expression profiles, X-ray and NMR determined protein structures and protein expression clones. The growing database covers over 23 000 unique genes/proteins from different experiments and organisms. All of the genes/proteins are annotated and integrated across experiments using UniProt Knowledgebase (UniProtKB) accession numbers. The web-interface for the database enables searching, querying and downloading at the level of experiment, group and individual gene(s)/protein(s) via UniProtKB accession numbers or protein function keywords. The system is accessible at http://www.proteomicsresource.org/. PMID:17984082

An improved Pearson's correlation proximity-based hierarchical clustering for mining biological association between genes.

PubMed

Booma, P M; Prabhakaran, S; Dhanalakshmi, R

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.

An Improved Pearson's Correlation Proximity-Based Hierarchical Clustering for Mining Biological Association between Genes

PubMed Central

Booma, P. M.; Prabhakaran, S.; Dhanalakshmi, R.

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality. PMID:25136661

A database of expressed genes from the new world screwworm, Cochliomyia hominivorax (Coquerel) (Diptera: Calliphoridae)

USDA-ARS?s Scientific Manuscript database

We used an expressed sequence tag and 454 pyrosequencing approach to initiate a study of the genome of the New World Screwworm, Cochliomyia hominivorax (Coquerel). Two normalized cDNA libraries were constructed from RNA isolated from embryos and 2nd instar larvae from the Panama 95 strain. Approxima...

Effective biomedical document classification for identifying publications relevant to the mouse Gene Expression Database (GXD).

PubMed

Jiang, Xiangying; Ringwald, Martin; Blake, Judith; Shatkay, Hagit

2017-01-01

The Gene Expression Database (GXD) is a comprehensive online database within the Mouse Genome Informatics resource, aiming to provide available information about endogenous gene expression during mouse development. The information stems primarily from many thousands of biomedical publications that database curators must go through and read. Given the very large number of biomedical papers published each year, automatic document classification plays an important role in biomedical research. Specifically, an effective and efficient document classifier is needed for supporting the GXD annotation workflow. We present here an effective yet relatively simple classification scheme, which uses readily available tools while employing feature selection, aiming to assist curators in identifying publications relevant to GXD. We examine the performance of our method over a large manually curated dataset, consisting of more than 25 000 PubMed abstracts, of which about half are curated as relevant to GXD while the other half as irrelevant to GXD. In addition to text from title-and-abstract, we also consider image captions, an important information source that we integrate into our method. We apply a captions-based classifier to a subset of about 3300 documents, for which the full text of the curated articles is available. The results demonstrate that our proposed approach is robust and effectively addresses the GXD document classification. Moreover, using information obtained from image captions clearly improves performance, compared to title and abstract alone, affirming the utility of image captions as a substantial evidence source for automatically determining the relevance of biomedical publications to a specific subject area. www.informatics.jax.org. © The Author(s) 2017. Published by Oxford University Press.

Identification and expression analysis of cold and freezing stress responsive genes of Brassica oleracea.

PubMed

Ahmed, Nasar Uddin; Jung, Hee-Jeong; Park, Jong-In; Cho, Yong-Gu; Hur, Yoonkang; Nou, Ill-Sup

2015-01-10

Cold and freezing stress is a major environmental constraint to the production of Brassica crops. Enhancement of tolerance by exploiting cold and freezing tolerance related genes offers the most efficient approach to address this problem. Cold-induced transcriptional profiling is a promising approach to the identification of potential genes related to cold and freezing stress tolerance. In this study, 99 highly expressed genes were identified from a whole genome microarray dataset of Brassica rapa. Blast search analysis of the Brassica oleracea database revealed the corresponding homologous genes. To validate their expression, pre-selected cold tolerant and susceptible cabbage lines were analyzed. Out of 99 BoCRGs, 43 were differentially expressed in response to varying degrees of cold and freezing stress in the contrasting cabbage lines. Among the differentially expressed genes, 18 were highly up-regulated in the tolerant lines, which is consistent with their microarray expression. Additionally, 12 BoCRGs were expressed differentially after cold stress treatment in two contrasting cabbage lines, and BoCRG54, 56, 59, 62, 70, 72 and 99 were predicted to be involved in cold regulatory pathways. Taken together, the cold-responsive genes identified in this study provide additional direction for elucidating the regulatory network of low temperature stress tolerance and developing cold and freezing stress resistant Brassica crops. Copyright © 2014 Elsevier B.V. All rights reserved.

Similar compounds searching system by using the gene expression microarray database.

PubMed

Toyoshiba, Hiroyoshi; Sawada, Hiroshi; Naeshiro, Ichiro; Horinouchi, Akira

2009-04-10

Numbers of microarrays have been examined and several public and commercial databases have been developed. However, it is not easy to compare in-house microarray data with those in a database because of insufficient reproducibility due to differences in the experimental conditions. As one of the approach to use these databases, we developed the similar compounds searching system (SCSS) on a toxicogenomics database. The datasets of 55 compounds administered to rats in the Toxicogenomics Project (TGP) database in Japan were used in this study. Using the fold-change ranking method developed by Lamb et al. [Lamb, J., Crawford, E.D., Peck, D., Modell, J.W., Blat, I.C., Wrobel, M.J., Lerner, J., Brunet, J.P., Subramanian, A., Ross, K.N., Reich, M., Hieronymus, H., Wei, G., Armstrong, S.A., Haggarty, S.J., Clemons, P.A., Wei, R., Carr, S.A., Lander, E.S., Golub, T.R., 2006. The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313, 1929-1935] and criteria called hit ratio, the system let us compare in-house microarray data and those in the database. In-house generated data for clofibrate, phenobarbital, and a proprietary compound were tested to evaluate the performance of the SCSS method. Phenobarbital and clofibrate, which were included in the TGP database, scored highest by the SCSS method. Other high scoring compounds had effects similar to either phenobarbital (a cytochrome P450s inducer) or clofibrate (a peroxisome proliferator). Some of high scoring compounds identified using the proprietary compound-administered rats have been known to cause similar toxicological changes in different species. Our results suggest that the SCSS method could be used in drug discovery and development. Moreover, this method may be a powerful tool to understand the mechanisms by which biological systems respond to various chemical compounds and may also predict adverse effects of new compounds.

VIZARD: analysis of Affymetrix Arabidopsis GeneChip data

NASA Technical Reports Server (NTRS)

Moseyko, Nick; Feldman, Lewis J.

2002-01-01

SUMMARY: The Affymetrix GeneChip Arabidopsis genome array has proved to be a very powerful tool for the analysis of gene expression in Arabidopsis thaliana, the most commonly studied plant model organism. VIZARD is a Java program created at the University of California, Berkeley, to facilitate analysis of Arabidopsis GeneChip data. It includes several integrated tools for filtering, sorting, clustering and visualization of gene expression data as well as tools for the discovery of regulatory motifs in upstream sequences. VIZARD also includes annotation and upstream sequence databases for the majority of genes represented on the Affymetrix Arabidopsis GeneChip array. AVAILABILITY: VIZARD is available free of charge for educational, research, and not-for-profit purposes, and can be downloaded at http://www.anm.f2s.com/research/vizard/ CONTACT: moseyko@uclink4.berkeley.edu.

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

PubMed

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

2013-05-01

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

Genome-wide identification and evolution of the PIN-FORMED (PIN) gene family in Glycine max.

PubMed

Liu, Yuan; Wei, Haichao

2017-07-01

Soybean (Glycine max) is one of the most important crop plants. Wild and cultivated soybean varieties have significant differences worth further investigation, such as plant morphology, seed size, and seed coat development; these characters may be related to auxin biology. The PIN gene family encodes essential transport proteins in cell-to-cell auxin transport, but little research on soybean PIN genes (GmPIN genes) has been done, especially with respect to the evolution and differences between wild and cultivated soybean. In this study, we retrieved 23 GmPIN genes from the latest updated G. max genome database; six GmPIN protein sequences were changed compared with the previous database. Based on the Plant Genome Duplication Database, 18 GmPIN genes have been involved in segment duplication. Three pairs of GmPIN genes arose after the second soybean genome duplication, and six occurred after the first genome duplication. The duplicated GmPIN genes retained similar expression patterns. All the duplicated GmPIN genes experienced purifying selection (K a /K s < 1) to prevent accumulation of non-synonymous mutations and thus remained more similar. In addition, we also focused on the artificial selection of the soybean PIN genes. Five artificially selected GmPIN genes were identified by comparing the genome sequence of 17 wild and 14 cultivated soybean varieties. Our research provides useful and comprehensive basic information for understanding GmPIN genes.

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

PubMed

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

openSputnik--a database to ESTablish comparative plant genomics using unsaturated sequence collections.

PubMed

Rudd, Stephen

2005-01-01

The public expressed sequence tag collections are continually being enriched with high-quality sequences that represent an ever-expanding range of taxonomically diverse plant species. While these sequence collections provide biased insight into the populations of expressed genes available within individual species and their associated tissues, the information is conceivably of wider relevance in a comparative context. When we consider the available expressed sequence tag (EST) collections of summer 2004, most of the major plant taxonomic clades are at least superficially represented. Investigation of the five million available plant ESTs provides a wealth of information that has applications in modelling the routes of plant genome evolution and the identification of lineage-specific genes and gene families. Over four million ESTs from over 50 distinct plant species have been collated within an EST analysis pipeline called openSputnik. The ESTs were resolved down into approximately one million unigene sequences. These have been annotated using orthology-based annotation transfer from reference plant genomes and using a variety of contemporary bioinformatics methods to assign peptide, structural and functional attributes. The openSputnik database is available at http://sputnik.btk.fi.

Comprehensive analysis of the long noncoding RNA HOXA11-AS gene interaction regulatory network in NSCLC cells.

PubMed

Zhang, Yu; He, Rong-Quan; Dang, Yi-Wu; Zhang, Xiu-Ling; Wang, Xiao; Huang, Su-Ning; Huang, Wen-Ting; Jiang, Meng-Tong; Gan, Xiao-Ning; Xie, You; Li, Ping; Luo, Dian-Zhong; Chen, Gang; Gan, Ting-Qing

2016-01-01

Long noncoding RNAs (lncRNAs) are related to different biological processes in non-small cell lung cancer (NSCLC). However, the possible molecular mechanisms underlying the effects of the long noncoding RNA HOXA11-AS (HOXA11 antisense RNA) in NSCLC are unknown. HOXA11-AS was knocked down in the NSCLC A549 cell line and a high throughput microarray assay was applied to detect changes in the gene profiles of the A549 cells. Bioinformatics analyses (gene ontology (GO), pathway, Kyoto Encyclopedia of Genes and Genomes (KEGG), and network analyses) were performed to investigate the potential pathways and networks of the differentially expressed genes. The molecular signatures database (MSigDB) was used to display the expression profiles of these differentially expressed genes. Furthermore, the relationships between the HOXA11-AS, de-regulated genes and clinical NSCLC parameters were verified by using NSCLC patient information from The Cancer Genome Atlas (TCGA) database. In addition, the relationship between HOXA11-AS expression and clinical diagnostic value was analyzed by receiver operating characteristic (ROC) curve. Among the differentially expressed genes, 277 and 80 genes were upregulated and downregulated in NSCLC, respectively (fold change ≥2.0, P < 0.05 and false discovery rate (FDR) < 0.05). According to the degree of the fold change, six upregulated and three downregulated genes were selected for further investigation. Only four genes (RSPO3, ADAMTS8, DMBT1, and DOCK8) were reported to be related with the development or progression of NSCLC based on a PubMed search. Among all possible pathways, three pathways (the PI3K-Akt, TGF-beta and Hippo signaling pathways) were the most likely to be involved in NSCLC development and progression. Furthermore, we found that HOXA11-AS was highly expressed in both lung adenocarcinoma and squamous cell carcinoma based on TCGA database. The ROC curve showed that the area under curve (AUC) of HOXA11-AS was 0.727 (95% CI 0.663-0.790) for lung adenocarcinoma and 0.933 (95% CI 0.906-0.960) for squamous cell carcinoma patients. Additionally, the original data from TCGA verified that ADAMTS8, DMBT1 and DOCK8 were downregulated in both lung adenocarcinoma and squamous cell carcinoma, whereas RSPO3 expression was upregulated in lung adenocarcinoma and downregulated in lung squamous cell carcinoma. For the other five genes (STMN2, SPINK6, TUSC3, LOC100128054, and C8orf22), we found that STMN2, TUSC3 and C8orf22 were upregulated in squamous cell carcinoma and that STMN2 and USC3 were upregulated in lung adenocarcinoma. Furthermore, we compared the correlation between HOXA11-AS and de-regulated genes in NSCLC based on TCGA. The results showed that the HOXA11-AS expression was negatively correlated with DOCK8 in squamous cell carcinoma (r = -0.124, P = 0.048) and lung adenocarcinoma (r = -0.176, P = 0.005). In addition, RSPO3, ADAMTS8 and DOCK8 were related to overall survival and disease-free survival (all P < 0.05) of lung adenocarcinoma patients in TCGA. Our results showed that the gene profiles were significantly changed after HOXA11-AS knock-down in NSCLC cells. We speculated that HOXA11-AS may play an important role in NSCLC development and progression by regulating the expression of various pathways and genes, especially DOCK8 and TGF-beta pathway. However, the exact mechanism should be verified by functional experiments.

Cloning of a gene (RIG-G) associated with retinoic acid-induced differentiation of acute promyelocytic leukemia cells and representing a new member of a family of interferon-stimulated genes

PubMed Central

Yu, Man; Tong, Jian-Hua; Mao, Mao; Kan, Li-Xin; Liu, Meng-Min; Sun, Yi-Wu; Fu, Gang; Jing, Yong-Kui; Yu, Long; Lepaslier, Denis; Lanotte, Michel; Wang, Zhen-Yi; Chen, Zhu; Waxman, Samuel; Wang, Ya-Xin; Tan, Jia-Zhen; Chen, Sai-Juan

1997-01-01

In a cell line (NB4) derived from a patient with acute promyelocytic leukemia, all-trans-retinoic acid (ATRA) and interferon (IFN) induce the expression of a novel gene we call RIG-G (for retinoic acid-induced gene G). This gene codes for a 58-kDa protein containing 490 amino acids with several potential sites for post-translational modification. In untreated NB4 cells, the expression of RIG-G is undetectable. ATRA treatment induces the transcriptional expression of RIG-G relatively late (12–24 hr) in a protein synthesis-dependent manner, whereas IFN-α induces its expression early (30 min to 3 hr). Database search has revealed a high-level homology between RIG-G and several IFN-stimulated genes in human (ISG54K, ISG56K, and IFN-inducible and retinoic acid-inducible 58K gene) and some other species, defining a well conserved gene family. The gene is composed of two exons and has been mapped by fluorescence in situ hybridization to chromosome 10q24, where two other human IFN-stimulated gene members are localized. A synergistic induction of RIG-G expression in NB4 cells by combined treatment with ATRA and IFNs suggests that a collaboration exists between their respective signaling pathways. PMID:9207104

A Modified ABCDE Model of Flowering in Orchids Based on Gene Expression Profiling Studies of the Moth Orchid Phalaenopsis aphrodite

PubMed Central

Lee, Ann-Ying; Chen, Chun-Yi; Chang, Yao-Chien Alex; Chao, Ya-Ting; Shih, Ming-Che

2013-01-01

Previously we developed genomic resources for orchids, including transcriptomic analyses using next-generation sequencing techniques and construction of a web-based orchid genomic database. Here, we report a modified molecular model of flower development in the Orchidaceae based on functional analysis of gene expression profiles in Phalaenopsis aphrodite (a moth orchid) that revealed novel roles for the transcription factors involved in floral organ pattern formation. Phalaenopsis orchid floral organ-specific genes were identified by microarray analysis. Several critical transcription factors including AP3, PI, AP1 and AGL6, displayed distinct spatial distribution patterns. Phylogenetic analysis of orchid MADS box genes was conducted to infer the evolutionary relationship among floral organ-specific genes. The results suggest that gene duplication MADS box genes in orchid may have resulted in their gaining novel functions during evolution. Based on these analyses, a modified model of orchid flowering was proposed. Comparison of the expression profiles of flowers of a peloric mutant and wild-type Phalaenopsis orchid further identified genes associated with lip morphology and peloric effects. Large scale investigation of gene expression profiles revealed that homeotic genes from the ABCDE model of flower development classes A and B in the Phalaenopsis orchid have novel functions due to evolutionary diversification, and display differential expression patterns. PMID:24265826

Projecting 2D gene expression data into 3D and 4D space.

PubMed

Gerth, Victor E; Katsuyama, Kaori; Snyder, Kevin A; Bowes, Jeff B; Kitayama, Atsushi; Ueno, Naoto; Vize, Peter D

2007-04-01

Video games typically generate virtual 3D objects by texture mapping an image onto a 3D polygonal frame. The feeling of movement is then achieved by mathematically simulating camera movement relative to the polygonal frame. We have built customized scripts that adapt video game authoring software to texture mapping images of gene expression data onto b-spline based embryo models. This approach, known as UV mapping, associates two-dimensional (U and V) coordinates within images to the three dimensions (X, Y, and Z) of a b-spline model. B-spline model frameworks were built either from confocal data or de novo extracted from 2D images, once again using video game authoring approaches. This system was then used to build 3D models of 182 genes expressed in developing Xenopus embryos and to implement these in a web-accessible database. Models can be viewed via simple Internet browsers and utilize openGL hardware acceleration via a Shockwave plugin. Not only does this database display static data in a dynamic and scalable manner, the UV mapping system also serves as a method to align different images to a common framework, an approach that may make high-throughput automated comparisons of gene expression patterns possible. Finally, video game systems also have elegant methods for handling movement, allowing biomechanical algorithms to drive the animation of models. With further development, these biomechanical techniques offer practical methods for generating virtual embryos that recapitulate morphogenesis.

A Genome-Wide Screen Indicates Correlation between Differentiation and Expression of Metabolism Related Genes

PubMed Central

Shende, Akhilesh; Singh, Anupama; Meena, Anil; Ghosal, Ritika; Ranganathan, Madhav; Bandyopadhyay, Amitabha

2013-01-01

Differentiated tissues may be considered as materials with distinct properties. The differentiation program of a given tissue ensures that it acquires material properties commensurate with its function. It may be hypothesized that some of these properties are acquired through production of tissue-specific metabolites synthesized by metabolic enzymes. To establish correlation between metabolism and organogenesis we have carried out a genome-wide expression study of metabolism related genes by RNA in-situ hybridization. 23% of the metabolism related genes studied are expressed in a tissue-restricted but not tissue-exclusive manner. We have conducted the screen on whole mount chicken (Gallus gallus) embryos from four distinct developmental stages to correlate dynamic changes in expression patterns of metabolic enzymes with spatio-temporally unique developmental events. Our data strongly suggests that unique combinations of metabolism related genes, and not specific metabolic pathways, are upregulated during differentiation. Further, expression of metabolism related genes in well established signaling centers that regulate different aspects of morphogenesis indicates developmental roles of some of the metabolism related genes. The database of tissue-restricted expression patterns of metabolism related genes, generated in this study, should serve as a resource for systematic identification of these genes with tissue-specific functions during development. Finally, comprehensive understanding of differentiation is not possible unless the downstream genes of a differentiation cascade are identified. We propose, metabolic enzymes constitute a significant portion of these downstream target genes. Thus our study should help elucidate different aspects of tissue differentiation. PMID:23717462

A genome-wide screen indicates correlation between differentiation and expression of metabolism related genes.

PubMed

Roy, Priti; Kumar, Brijesh; Shende, Akhilesh; Singh, Anupama; Meena, Anil; Ghosal, Ritika; Ranganathan, Madhav; Bandyopadhyay, Amitabha

2013-01-01

Differentiated tissues may be considered as materials with distinct properties. The differentiation program of a given tissue ensures that it acquires material properties commensurate with its function. It may be hypothesized that some of these properties are acquired through production of tissue-specific metabolites synthesized by metabolic enzymes. To establish correlation between metabolism and organogenesis we have carried out a genome-wide expression study of metabolism related genes by RNA in-situ hybridization. 23% of the metabolism related genes studied are expressed in a tissue-restricted but not tissue-exclusive manner. We have conducted the screen on whole mount chicken (Gallus gallus) embryos from four distinct developmental stages to correlate dynamic changes in expression patterns of metabolic enzymes with spatio-temporally unique developmental events. Our data strongly suggests that unique combinations of metabolism related genes, and not specific metabolic pathways, are upregulated during differentiation. Further, expression of metabolism related genes in well established signaling centers that regulate different aspects of morphogenesis indicates developmental roles of some of the metabolism related genes. The database of tissue-restricted expression patterns of metabolism related genes, generated in this study, should serve as a resource for systematic identification of these genes with tissue-specific functions during development. Finally, comprehensive understanding of differentiation is not possible unless the downstream genes of a differentiation cascade are identified. We propose, metabolic enzymes constitute a significant portion of these downstream target genes. Thus our study should help elucidate different aspects of tissue differentiation.

Genome-wide identification of suitable zebrafish Danio rerio reference genes for normalization of gene expression data by RT-qPCR.

PubMed

Xu, H; Li, C; Zeng, Q; Agrawal, I; Zhu, X; Gong, Z

2016-06-01

In this study, to systematically identify the most stably expressed genes for internal reference in zebrafish Danio rerio investigations, 37 D. rerio transcriptomic datasets (both RNA sequencing and microarray data) were collected from gene expression omnibus (GEO) database and unpublished data, and gene expression variations were analysed under three experimental conditions: tissue types, developmental stages and chemical treatments. Forty-four putative candidate genes were identified with the c.v. <0·2 from all datasets. Following clustering into different functional groups, 21 genes, in addition to four conventional housekeeping genes (eef1a1l1, b2m, hrpt1l and actb1), were selected from different functional groups for further quantitative real-time (qrt-)PCR validation using 25 RNA samples from different adult tissues, developmental stages and chemical treatments. The qrt-PCR data were then analysed using the statistical algorithm refFinder for gene expression stability. Several new candidate genes showed better expression stability than the conventional housekeeping genes in all three categories. It was found that sep15 and metap1 were the top two stable genes for tissue types, ube2a and tmem50a the top two for different developmental stages, and rpl13a and rp1p0 the top two for chemical treatments. Thus, based on the extensive transcriptomic analyses and qrt-PCR validation, these new reference genes are recommended for normalization of D. rerio qrt-PCR data respectively for the three different experimental conditions. © 2016 The Fisheries Society of the British Isles.

ESTuber db: an online database for Tuber borchii EST sequences.

PubMed

Lazzari, Barbara; Caprera, Andrea; Cosentino, Cristian; Stella, Alessandra; Milanesi, Luciano; Viotti, Angelo

2007-03-08

The ESTuber database (http://www.itb.cnr.it/estuber) includes 3,271 Tuber borchii expressed sequence tags (EST). The dataset consists of 2,389 sequences from an in-house prepared cDNA library from truffle vegetative hyphae, and 882 sequences downloaded from GenBank and representing four libraries from white truffle mycelia and ascocarps at different developmental stages. An automated pipeline was prepared to process EST sequences using public software integrated by in-house developed Perl scripts. Data were collected in a MySQL database, which can be queried via a php-based web interface. Sequences included in the ESTuber db were clustered and annotated against three databases: the GenBank nr database, the UniProtKB database and a third in-house prepared database of fungi genomic sequences. An algorithm was implemented to infer statistical classification among Gene Ontology categories from the ontology occurrences deduced from the annotation procedure against the UniProtKB database. Ontologies were also deduced from the annotation of more than 130,000 EST sequences from five filamentous fungi, for intra-species comparison purposes. Further analyses were performed on the ESTuber db dataset, including tandem repeats search and comparison of the putative protein dataset inferred from the EST sequences to the PROSITE database for protein patterns identification. All the analyses were performed both on the complete sequence dataset and on the contig consensus sequences generated by the EST assembly procedure. The resulting web site is a resource of data and links related to truffle expressed genes. The Sequence Report and Contig Report pages are the web interface core structures which, together with the Text search utility and the Blast utility, allow easy access to the data stored in the database.

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.

Genome-Wide Identification and Expression Analysis of WRKY Transcription Factors under Multiple Stresses in Brassica napus

PubMed Central

He, Yajun; Mao, Shaoshuai; Gao, Yulong; Zhu, Liying; Wu, Daoming; Cui, Yixin; Li, Jiana; Qian, Wei

2016-01-01

WRKY transcription factors play important roles in responses to environmental stress stimuli. Using a genome-wide domain analysis, we identified 287 WRKY genes with 343 WRKY domains in the sequenced genome of Brassica napus, 139 in the A sub-genome and 148 in the C sub-genome. These genes were classified into eight groups based on phylogenetic analysis. In the 343 WRKY domains, a total of 26 members showed divergence in the WRKY domain, and 21 belonged to group I. This finding suggested that WRKY genes in group I are more active and variable compared with genes in other groups. Using genome-wide identification and analysis of the WRKY gene family in Brassica napus, we observed genome duplication, chromosomal/segmental duplications and tandem duplication. All of these duplications contributed to the expansion of the WRKY gene family. The duplicate segments that were detected indicated that genome duplication events occurred in the two diploid progenitors B. rapa and B. olearecea before they combined to form B. napus. Analysis of the public microarray database and EST database for B. napus indicated that 74 WRKY genes were induced or preferentially expressed under stress conditions. According to the public QTL data, we identified 77 WRKY genes in 31 QTL regions related to various stress tolerance. We further evaluated the expression of 26 BnaWRKY genes under multiple stresses by qRT-PCR. Most of the genes were induced by low temperature, salinity and drought stress, indicating that the WRKYs play important roles in B. napus stress responses. Further, three BnaWRKY genes were strongly responsive to the three multiple stresses simultaneously, which suggests that these 3 WRKY may have multi-functional roles in stress tolerance and can potentially be used in breeding new rapeseed cultivars. We also found six tandem repeat pairs exhibiting similar expression profiles under the various stress conditions, and three pairs were mapped in the stress related QTL regions, indicating tandem duplicate WRKYs in the adaptive responses to environmental stimuli during the evolution process. Our results provide a framework for future studies regarding the function of WRKY genes in response to stress in B. napus. PMID:27322342

Genome-Wide Identification and Expression Analysis of WRKY Transcription Factors under Multiple Stresses in Brassica napus.

PubMed

He, Yajun; Mao, Shaoshuai; Gao, Yulong; Zhu, Liying; Wu, Daoming; Cui, Yixin; Li, Jiana; Qian, Wei

2016-01-01

WRKY transcription factors play important roles in responses to environmental stress stimuli. Using a genome-wide domain analysis, we identified 287 WRKY genes with 343 WRKY domains in the sequenced genome of Brassica napus, 139 in the A sub-genome and 148 in the C sub-genome. These genes were classified into eight groups based on phylogenetic analysis. In the 343 WRKY domains, a total of 26 members showed divergence in the WRKY domain, and 21 belonged to group I. This finding suggested that WRKY genes in group I are more active and variable compared with genes in other groups. Using genome-wide identification and analysis of the WRKY gene family in Brassica napus, we observed genome duplication, chromosomal/segmental duplications and tandem duplication. All of these duplications contributed to the expansion of the WRKY gene family. The duplicate segments that were detected indicated that genome duplication events occurred in the two diploid progenitors B. rapa and B. olearecea before they combined to form B. napus. Analysis of the public microarray database and EST database for B. napus indicated that 74 WRKY genes were induced or preferentially expressed under stress conditions. According to the public QTL data, we identified 77 WRKY genes in 31 QTL regions related to various stress tolerance. We further evaluated the expression of 26 BnaWRKY genes under multiple stresses by qRT-PCR. Most of the genes were induced by low temperature, salinity and drought stress, indicating that the WRKYs play important roles in B. napus stress responses. Further, three BnaWRKY genes were strongly responsive to the three multiple stresses simultaneously, which suggests that these 3 WRKY may have multi-functional roles in stress tolerance and can potentially be used in breeding new rapeseed cultivars. We also found six tandem repeat pairs exhibiting similar expression profiles under the various stress conditions, and three pairs were mapped in the stress related QTL regions, indicating tandem duplicate WRKYs in the adaptive responses to environmental stimuli during the evolution process. Our results provide a framework for future studies regarding the function of WRKY genes in response to stress in B. napus.

Identification and profiling of novel microRNAs in the Brassica rapa genome based on small RNA deep sequencing

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are one of the functional non-coding small RNAs involved in the epigenetic control of the plant genome. Although plants contain both evolutionary conserved miRNAs and species-specific miRNAs within their genomes, computational methods often only identify evolutionary conserved miRNAs. The recent sequencing of the Brassica rapa genome enables us to identify miRNAs and their putative target genes. In this study, we sought to provide a more comprehensive prediction of B. rapa miRNAs based on high throughput small RNA deep sequencing. Results We sequenced small RNAs from five types of tissue: seedlings, roots, petioles, leaves, and flowers. By analyzing 2.75 million unique reads that mapped to the B. rapa genome, we identified 216 novel and 196 conserved miRNAs that were predicted to target approximately 20% of the genome’s protein coding genes. Quantitative analysis of miRNAs from the five types of tissue revealed that novel miRNAs were expressed in diverse tissues but their expression levels were lower than those of the conserved miRNAs. Comparative analysis of the miRNAs between the B. rapa and Arabidopsis thaliana genomes demonstrated that redundant copies of conserved miRNAs in the B. rapa genome may have been deleted after whole genome triplication. Novel miRNA members seemed to have spontaneously arisen from the B. rapa and A. thaliana genomes, suggesting the species-specific expansion of miRNAs. We have made this data publicly available in a miRNA database of B. rapa called BraMRs. The database allows the user to retrieve miRNA sequences, their expression profiles, and a description of their target genes from the five tissue types investigated here. Conclusions This is the first report to identify novel miRNAs from Brassica crops using genome-wide high throughput techniques. The combination of computational methods and small RNA deep sequencing provides robust predictions of miRNAs in the genome. The finding of numerous novel miRNAs, many with few target genes and low expression levels, suggests the rapid evolution of miRNA genes. The development of a miRNA database, BraMRs, enables us to integrate miRNA identification, target prediction, and functional annotation of target genes. BraMRs will represent a valuable public resource with which to study the epigenetic control of B. rapa and other closely related Brassica species. The database is available at the following link: http://bramrs.rna.kr [1]. PMID:23163954

Small RNA and transcriptome deep sequencing proffers insight into floral gene regulation in Rosa cultivars

PubMed Central

2012-01-01

Background Roses (Rosa sp.), which belong to the family Rosaceae, are the most economically important ornamental plants—making up 30% of the floriculture market. However, given high demand for roses, rose breeding programs are limited in molecular resources which can greatly enhance and speed breeding efforts. A better understanding of important genes that contribute to important floral development and desired phenotypes will lead to improved rose cultivars. For this study, we analyzed rose miRNAs and the rose flower transcriptome in order to generate a database to expound upon current knowledge regarding regulation of important floral characteristics. A rose genetic database will enable comprehensive analysis of gene expression and regulation via miRNA among different Rosa cultivars. Results We produced more than 0.5 million reads from expressed sequences, totalling more than 110 million bp. From these, we generated 35,657, 31,434, 34,725, and 39,722 flower unigenes from Rosa hybrid: ‘Vital’, ‘Maroussia’, and ‘Sympathy’ and Rosa rugosa Thunb. , respectively. The unigenes were assigned functional annotations, domains, metabolic pathways, Gene Ontology (GO) terms, Plant Ontology (PO) terms, and MIPS Functional Catalogue (FunCat) terms. Rose flower transcripts were compared with genes from whole genome sequences of Rosaceae members (apple, strawberry, and peach) and grape. We also produced approximately 40 million small RNA reads from flower tissue for Rosa, representing 267 unique miRNA tags. Among identified miRNAs, 25 of them were novel and 242 of them were conserved miRNAs. Statistical analyses of miRNA profiles revealed both shared and species-specific miRNAs, which presumably effect flower development and phenotypes. Conclusions In this study, we constructed a Rose miRNA and transcriptome database, and we analyzed the miRNAs and transcriptome generated from the flower tissues of four Rosa cultivars. The database provides a comprehensive genetic resource which can be used to better understand rose flower development and to identify candidate genes for important phenotypes. PMID:23171001

Small RNA and transcriptome deep sequencing proffers insight into floral gene regulation in Rosa cultivars.

PubMed

Kim, Jungeun; Park, June Hyun; Lim, Chan Ju; Lim, Jae Yun; Ryu, Jee-Youn; Lee, Bong-Woo; Choi, Jae-Pil; Kim, Woong Bom; Lee, Ha Yeon; Choi, Yourim; Kim, Donghyun; Hur, Cheol-Goo; Kim, Sukweon; Noh, Yoo-Sun; Shin, Chanseok; Kwon, Suk-Yoon

2012-11-21

Roses (Rosa sp.), which belong to the family Rosaceae, are the most economically important ornamental plants--making up 30% of the floriculture market. However, given high demand for roses, rose breeding programs are limited in molecular resources which can greatly enhance and speed breeding efforts. A better understanding of important genes that contribute to important floral development and desired phenotypes will lead to improved rose cultivars. For this study, we analyzed rose miRNAs and the rose flower transcriptome in order to generate a database to expound upon current knowledge regarding regulation of important floral characteristics. A rose genetic database will enable comprehensive analysis of gene expression and regulation via miRNA among different Rosa cultivars. We produced more than 0.5 million reads from expressed sequences, totalling more than 110 million bp. From these, we generated 35,657, 31,434, 34,725, and 39,722 flower unigenes from Rosa hybrid: 'Vital', 'Maroussia', and 'Sympathy' and Rosa rugosa Thunb., respectively. The unigenes were assigned functional annotations, domains, metabolic pathways, Gene Ontology (GO) terms, Plant Ontology (PO) terms, and MIPS Functional Catalogue (FunCat) terms. Rose flower transcripts were compared with genes from whole genome sequences of Rosaceae members (apple, strawberry, and peach) and grape. We also produced approximately 40 million small RNA reads from flower tissue for Rosa, representing 267 unique miRNA tags. Among identified miRNAs, 25 of them were novel and 242 of them were conserved miRNAs. Statistical analyses of miRNA profiles revealed both shared and species-specific miRNAs, which presumably effect flower development and phenotypes. In this study, we constructed a Rose miRNA and transcriptome database, and we analyzed the miRNAs and transcriptome generated from the flower tissues of four Rosa cultivars. The database provides a comprehensive genetic resource which can be used to better understand rose flower development and to identify candidate genes for important phenotypes.

Chasing Migration Genes: A Brain Expressed Sequence Tag Resource for Summer and Migratory Monarch Butterflies (Danaus plexippus)

PubMed Central

Zhu, Haisun; Casselman, Amy; Reppert, Steven M.

2008-01-01

North American monarch butterflies (Danaus plexippus) undergo a spectacular fall migration. In contrast to summer butterflies, migrants are juvenile hormone (JH) deficient, which leads to reproductive diapause and increased longevity. Migrants also utilize time-compensated sun compass orientation to help them navigate to their overwintering grounds. Here, we describe a brain expressed sequence tag (EST) resource to identify genes involved in migratory behaviors. A brain EST library was constructed from summer and migrating butterflies. Of 9,484 unique sequences, 6068 had positive hits with the non-redundant protein database; the EST database likely represents ∼52% of the gene-encoding potential of the monarch genome. The brain transcriptome was cataloged using Gene Ontology and compared to Drosophila. Monarch genes were well represented, including those implicated in behavior. Three genes involved in increased JH activity (allatotropin, juvenile hormone acid methyltransfersase, and takeout) were upregulated in summer butterflies, compared to migrants. The locomotion-relevant turtle gene was marginally upregulated in migrants, while the foraging and single-minded genes were not differentially regulated. Many of the genes important for the monarch circadian clock mechanism (involved in sun compass orientation) were in the EST resource, including the newly identified cryptochrome 2. The EST database also revealed a novel Na+/K+ ATPase allele predicted to be more resistant to the toxic effects of milkweed than that reported previously. Potential genetic markers were identified from 3,486 EST contigs and included 1599 double-hit single nucleotide polymorphisms (SNPs) and 98 microsatellite polymorphisms. These data provide a template of the brain transcriptome for the monarch butterfly. Our “snap-shot” analysis of the differential regulation of candidate genes between summer and migratory butterflies suggests that unbiased, comprehensive transcriptional profiling will inform the molecular basis of migration. The identified SNPs and microsatellite polymorphisms can be used as genetic markers to address questions of population and subspecies structure. PMID:18183285

Transcriptional Analysis of In vivo Plasmodium yoelii Liver Stage Gene Expression

DTIC Science & Technology

2005-04-26

reaction was added to a PCR master mix with one of several oligonucleotide primer pairs (Table S6). The primers were designed and the specific conditions ...Koonin EV. Using the COG database to improve gene recognition in complete genomes. Genetica 2000;108:9–17. 26] Florens L, Washburn MP, Raine JD, et al

Screening the molecular targets of ovarian cancer based on bioinformatics analysis.

PubMed

Du, Lei; Qian, Xiaolei; Dai, Chenyang; Wang, Lihua; Huang, Ding; Wang, Shuying; Shen, Xiaowei

2015-01-01

Ovarian cancer (OC) is the most lethal gynecologic malignancy. This study aims to explore the molecular mechanisms of OC and identify potential molecular targets for OC treatment. Microarray gene expression data (GSE14407) including 12 normal ovarian surface epithelia samples and 12 OC epithelia samples were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) between 2 kinds of ovarian tissue were identified by using limma package in R language (|log2 fold change| gt;1 and false discovery rate [FDR] lt;0.05). Protein-protein interactions (PPIs) and known OC-related genes were screened from COXPRESdb and GenBank database, respectively. Furthermore, PPI network of top 10 upregulated DEGs and top 10 downregulated DEGs was constructed and visualized through Cytoscape software. Finally, for the genes involved in PPI network, functional enrichment analysis was performed by using DAVID (FDR lt;0.05). In total, 1136 DEGs were identified, including 544 downregulated and 592 upregulated DEGs. Then, PPI network was constructed, and DEGs CDKN2A, MUC1, OGN, ZIC1, SOX17, and TFAP2A interacted with known OC-related genes CDK4, EGFR/JUN, SRC, CLI1, CTNNB1, and TP53, respectively. Moreover, functions about oxygen transport and embryonic development were enriched by the genes involved in the network of downregulated DEGs. We propose that 4 DEGs (OGN, ZIC1, SOX17, and TFAP2A) and 2 functions (oxygen transport and embryonic development) might play a role in the development of OC. These 4 DEGs and known OC-related genes might serve as therapeutic targets for OC. Further studies are required to validate these predictions.

CicerTransDB 1.0: a resource for expression and functional study of chickpea transcription factors.

PubMed

Gayali, Saurabh; Acharya, Shankar; Lande, Nilesh Vikram; Pandey, Aarti; Chakraborty, Subhra; Chakraborty, Niranjan

2016-07-29

Transcription factor (TF) databases are major resource for systematic studies of TFs in specific species as well as related family members. Even though there are several publicly available multi-species databases, the information on the amount and diversity of TFs within individual species is fragmented, especially for newly sequenced genomes of non-model species of agricultural significance. We constructed CicerTransDB (Cicer Transcription Factor Database), the first database of its kind, which would provide a centralized putatively complete list of TFs in a food legume, chickpea. CicerTransDB, available at www.cicertransdb.esy.es , is based on chickpea (Cicer arietinum L.) annotation v 1.0. The database is an outcome of genome-wide domain study and manual classification of TF families. This database not only provides information of the gene, but also gene ontology, domain and motif architecture. CicerTransDB v 1.0 comprises information of 1124 genes of chickpea and enables the user to not only search, browse and download sequences but also retrieve sequence features. CicerTransDB also provides several single click interfaces, transconnecting to various other databases to ease further analysis. Several webAPI(s) integrated in the database allow end-users direct access of data. A critical comparison of CicerTransDB with PlantTFDB (Plant Transcription Factor Database) revealed 68 novel TFs in the chickpea genome, hitherto unexplored. Database URL: http://www.cicertransdb.esy.es.

WormQTLHD—a web database for linking human disease to natural variation data in C. elegans

PubMed Central

van der Velde, K. Joeri; de Haan, Mark; Zych, Konrad; Arends, Danny; Snoek, L. Basten; Kammenga, Jan E.; Jansen, Ritsert C.; Swertz, Morris A.; Li, Yang

2014-01-01

Interactions between proteins are highly conserved across species. As a result, the molecular basis of multiple diseases affecting humans can be studied in model organisms that offer many alternative experimental opportunities. One such organism—Caenorhabditis elegans—has been used to produce much molecular quantitative genetics and systems biology data over the past decade. We present WormQTLHD (Human Disease), a database that quantitatively and systematically links expression Quantitative Trait Loci (eQTL) findings in C. elegans to gene–disease associations in man. WormQTLHD, available online at http://www.wormqtl-hd.org, is a user-friendly set of tools to reveal functionally coherent, evolutionary conserved gene networks. These can be used to predict novel gene-to-gene associations and the functions of genes underlying the disease of interest. We created a new database that links C. elegans eQTL data sets to human diseases (34 337 gene–disease associations from OMIM, DGA, GWAS Central and NHGRI GWAS Catalogue) based on overlapping sets of orthologous genes associated to phenotypes in these two species. We utilized QTL results, high-throughput molecular phenotypes, classical phenotypes and genotype data covering different developmental stages and environments from WormQTL database. All software is available as open source, built on MOLGENIS and xQTL workbench. PMID:24217915

Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data

PubMed Central

Hassane, Duane C.; Guzman, Monica L.; Corbett, Cheryl; Li, Xiaojie; Abboud, Ramzi; Young, Fay; Liesveld, Jane L.; Carroll, Martin

2008-01-01

Increasing evidence indicates that malignant stem cells are important for the pathogenesis of acute myelogenous leukemia (AML) and represent a reservoir of cells that drive the development of AML and relapse. Therefore, new treatment regimens are necessary to prevent relapse and improve therapeutic outcomes. Previous studies have shown that the sesquiterpene lactone, parthenolide (PTL), ablates bulk, progenitor, and stem AML cells while causing no appreciable toxicity to normal hematopoietic cells. Thus, PTL must evoke cellular responses capable of mediating AML selective cell death. Given recent advances in chemical genomics such as gene expression-based high-throughput screening (GE-HTS) and the Connectivity Map, we hypothesized that the gene expression signature resulting from treatment of primary AML with PTL could be used to search for similar signatures in publicly available gene expression profiles deposited into the Gene Expression Omnibus (GEO). We therefore devised a broad in silico screen of the GEO database using the PTL gene expression signature as a template and discovered 2 new agents, celastrol and 4-hydroxy-2-nonenal, that effectively eradicate AML at the bulk, progenitor, and stem cell level. These findings suggest the use of multicenter collections of high-throughput data to facilitate discovery of leukemia drugs and drug targets. PMID:18305216

Evaluation of Suitable Reference Genes for Normalization of qPCR Gene Expression Studies in Brinjal (Solanum melongena L.) During Fruit Developmental Stages.

PubMed

Kanakachari, Mogilicherla; Solanke, Amolkumar U; Prabhakaran, Narayanasamy; Ahmad, Israr; Dhandapani, Gurusamy; Jayabalan, Narayanasamy; Kumar, Polumetla Ananda

2016-02-01

Brinjal/eggplant/aubergine is one of the major solanaceous vegetable crops. Recent availability of genome information greatly facilitates the fundamental research on brinjal. Gene expression patterns during different stages of fruit development can provide clues towards the understanding of its biological functions. Quantitative real-time PCR (qPCR) has become one of the most widely used methods for rapid and accurate quantification of gene expression. However, its success depends on the use of a suitable reference gene for data normalization. For qPCR analysis, a single reference gene is not universally suitable for all experiments. Therefore, reference gene validation is a crucial step. Suitable reference genes for qPCR analysis of brinjal fruit development have not been investigated so far. In this study, we have selected 21 candidate reference genes from the Brinjal (Solanum melongena) Plant Gene Indices database (compbio.dfci.harvard.edu/tgi/plant.html) and studied their expression profiles by qPCR during six different fruit developmental stages (0, 5, 10, 20, 30, and 50 days post anthesis) along with leaf samples of the Pusa Purple Long (PPL) variety. To evaluate the stability of gene expression, geNorm and NormFinder analytical softwares were used. geNorm identified SAND (SAND family protein) and TBP (TATA binding protein) as the best pairs of reference genes in brinjal fruit development. The results showed that for brinjal fruit development, individual or a combination of reference genes should be selected for data normalization. NormFinder identified Expressed gene (expressed sequence) as the best single reference gene in brinjal fruit development. In this study, we have identified and validated for the first time reference genes to provide accurate transcript normalization and quantification at various fruit developmental stages of brinjal which can also be useful for gene expression studies in other Solanaceae plant species.

Hypergravity-induced changes in gene expression in Arabidopsis hypocotyls

NASA Astrophysics Data System (ADS)

Yoshioka, R.; Soga, K.; Wakabayashi, K.; Takeba, G.; Hoson, T.

2003-05-01

Under hypergravity conditions, the cell wall of stem organs becomes mechanically rigid and elongation growth is suppressed, which can be recognized as the mechanism for plants to resist gravitational force. The changes in gene expression by hypergravity treatment were analyzed in Arabidopsis hypocotyls by the differential display method, for identifying genes involved in hypergravity-induced growth suppression. Sixty-two cDNA clones were expressed differentially between the control and 300 g conditions: the expression levels of 39 clones increased, whereas those of 23 clones decreased under hypergravity conditions. Sequence analysis and database searching revealed that 12 clones, 9 up-regulated and 3 down-regulated, have homology to known proteins. The expression of these genes was further analyzed using RT-PCR. Finally, six genes were confirmed to be up-regulated by hypergravity. One of such genes encoded 3-hydroxy-3-methylglutaryl-Coenzyme A reductase (HMGR), which catalyzes a reaction producing mevalonic acid, a key precursor ofterpenoids such as membrane sterols and several types of hormones. The expression of HMGR gene increased within several hours after hypergravity treatment. Also, compactin, an inhibitor of HMGR, prevented hypergravity-induced growth suppression, suggesting that HMGR is involved in suppression of Arabidopsis hypocotyl growth by hypergravity. In addition, hypergravity increased the expression levels of genes encoding CCR1 and ERD15, which were shown to take part in the signaling pathway of environmental stimuli such as temperature and water, and those of the α-tubulin gene. These genes may be involved in a series of cellular events leading to growth suppression of stem organs under hypergravity conditions.

A Functional and Regulatory Network Associated with PIP Expression in Human Breast Cancer

PubMed Central

Debily, Marie-Anne; Marhomy, Sandrine El; Boulanger, Virginie; Eveno, Eric; Mariage-Samson, Régine; Camarca, Alessandra; Auffray, Charles; Piatier-Tonneau, Dominique; Imbeaud, Sandrine

2009-01-01

Background The PIP (prolactin-inducible protein) gene has been shown to be expressed in breast cancers, with contradictory results concerning its implication. As both the physiological role and the molecular pathways in which PIP is involved are poorly understood, we conducted combined gene expression profiling and network analysis studies on selected breast cancer cell lines presenting distinct PIP expression levels and hormonal receptor status, to explore the functional and regulatory network of PIP co-modulated genes. Principal Findings Microarray analysis allowed identification of genes co-modulated with PIP independently of modulations resulting from hormonal treatment or cell line heterogeneity. Relevant clusters of genes that can discriminate between [PIP+] and [PIP−] cells were identified. Functional and regulatory network analyses based on a knowledge database revealed a master network of PIP co-modulated genes, including many interconnecting oncogenes and tumor suppressor genes, half of which were detected as differentially expressed through high-precision measurements. The network identified appears associated with an inhibition of proliferation coupled with an increase of apoptosis and an enhancement of cell adhesion in breast cancer cell lines, and contains many genes with a STAT5 regulatory motif in their promoters. Conclusions Our global exploratory approach identified biological pathways modulated along with PIP expression, providing further support for its good prognostic value of disease-free survival in breast cancer. Moreover, our data pointed to the importance of a regulatory subnetwork associated with PIP expression in which STAT5 appears as a potential transcriptional regulator. PMID:19262752

PvTFDB: a Phaseolus vulgaris transcription factors database for expediting functional genomics in legumes

PubMed Central

Bhawna; Bonthala, V.S.; Gajula, MNV Prasad

2016-01-01

The common bean [Phaseolus vulgaris (L.)] is one of the essential proteinaceous vegetables grown in developing countries. However, its production is challenged by low yields caused by numerous biotic and abiotic stress conditions. Regulatory transcription factors (TFs) symbolize a key component of the genome and are the most significant targets for producing stress tolerant crop and hence functional genomic studies of these TFs are important. Therefore, here we have constructed a web-accessible TFs database for P. vulgaris, called PvTFDB, which contains 2370 putative TF gene models in 49 TF families. This database provides a comprehensive information for each of the identified TF that includes sequence data, functional annotation, SSRs with their primer sets, protein physical properties, chromosomal location, phylogeny, tissue-specific gene expression data, orthologues, cis-regulatory elements and gene ontology (GO) assignment. Altogether, this information would be used in expediting the functional genomic studies of a specific TF(s) of interest. The objectives of this database are to understand functional genomics study of common bean TFs and recognize the regulatory mechanisms underlying various stress responses to ease breeding strategy for variety production through a couple of search interfaces including gene ID, functional annotation and browsing interfaces including by family and by chromosome. This database will also serve as a promising central repository for researchers as well as breeders who are working towards crop improvement of legume crops. In addition, this database provide the user unrestricted public access and the user can download entire data present in the database freely. Database URL: http://www.multiomics.in/PvTFDB/ PMID:27465131

Detection of alternative splice variants at the proteome level in Aspergillus flavus.

PubMed

Chang, Kung-Yen; Georgianna, D Ryan; Heber, Steffen; Payne, Gary A; Muddiman, David C

2010-03-05

Identification of proteins from proteolytic peptides or intact proteins plays an essential role in proteomics. Researchers use search engines to match the acquired peptide sequences to the target proteins. However, search engines depend on protein databases to provide candidates for consideration. Alternative splicing (AS), the mechanism where the exon of pre-mRNAs can be spliced and rearranged to generate distinct mRNA and therefore protein variants, enable higher eukaryotic organisms, with only a limited number of genes, to have the requisite complexity and diversity at the proteome level. Multiple alternative isoforms from one gene often share common segments of sequences. However, many protein databases only include a limited number of isoforms to keep minimal redundancy. As a result, the database search might not identify a target protein even with high quality tandem MS data and accurate intact precursor ion mass. We computationally predicted an exhaustive list of putative isoforms of Aspergillus flavus proteins from 20 371 expressed sequence tags to investigate whether an alternative splicing protein database can assign a greater proportion of mass spectrometry data. The newly constructed AS database provided 9807 new alternatively spliced variants in addition to 12 832 previously annotated proteins. The searches of the existing tandem MS spectra data set using the AS database identified 29 new proteins encoded by 26 genes. Nine fungal genes appeared to have multiple protein isoforms. In addition to the discovery of splice variants, AS database also showed potential to improve genome annotation. In summary, the introduction of an alternative splicing database helps identify more proteins and unveils more information about a proteome.

Xenopus microRNA genes are predominantly located within introns and are differentially expressed in adult frog tissues via post-transcriptional regulation

PubMed Central

Tang, Guo-Qing; Maxwell, E. Stuart

2008-01-01

The amphibian Xenopus provides a model organism for investigating microRNA expression during vertebrate embryogenesis and development. Searching available Xenopus genome databases using known human pre-miRNAs as query sequences, more than 300 genes encoding 142 Xenopus tropicalis miRNAs were identified. Analysis of Xenopus tropicalis miRNA genes revealed a predominate positioning within introns of protein-coding and nonprotein-coding RNA Pol II-transcribed genes. MiRNA genes were also located in pre-mRNA exons and positioned intergenically between known protein-coding genes. Many miRNA species were found in multiple locations and in more than one genomic context. MiRNA genes were also clustered throughout the genome, indicating the potential for the cotranscription and coordinate expression of miRNAs located in a given cluster. Northern blot analysis confirmed the expression of many identified miRNAs in both X. tropicalis and X. laevis. Comparison of X. tropicalis and X. laevis blots revealed comparable expression profiles, although several miRNAs exhibited species-specific expression in different tissues. More detailed analysis revealed that for some miRNAs, the tissue-specific expression profile of the pri-miRNA precursor was distinctly different from that of the mature miRNA profile. Differential miRNA precursor processing in both the nucleus and cytoplasm was implicated in the observed tissue-specific differences. These observations indicated that post-transcriptional processing plays an important role in regulating miRNA expression in the amphibian Xenopus. PMID:18032731

Too much data, but little inter-changeability: a lesson learned from mining public data on tissue specificity of gene expression.

PubMed

Li, Shuyu; Li, Yiqun Helen; Wei, Tao; Su, Eric Wen; Duffin, Kevin; Liao, Birong

2006-10-25

The tissue expression pattern of a gene often provides an important clue to its potential role in a biological process. A vast amount of gene expression data have been and are being accumulated in public repository through different technology platforms. However, exploitations of these rich data sources remain limited in part due to issues of technology standardization. Our objective is to test the data comparability between SAGE and microarray technologies, through examining the expression pattern of genes under normal physiological states across variety of tissues. There are 42-54% of genes showing significant correlations in tissue expression patterns between SAGE and GeneChip, with 30-40% of genes whose expression patterns are positively correlated and 10-15% of genes whose expression patterns are negatively correlated at a statistically significant level (p = 0.05). Our analysis suggests that the discrepancy on the expression patterns derived from technology platforms is not likely from the heterogeneity of tissues used in these technologies, or other spurious correlations resulting from microarray probe design, abundance of genes, or gene function. The discrepancy can be partially explained by errors in the original assignment of SAGE tags to genes due to the evolution of sequence databases. In addition, sequence analysis has indicated that many SAGE tags and Affymetrix array probe sets are mapped to different splice variants or different sequence regions although they represent the same gene, which also contributes to the observed discrepancies between SAGE and array expression data. To our knowledge, this is the first report attempting to mine gene expression patterns across tissues using public data from different technology platforms. Unlike previous similar studies that only demonstrated the discrepancies between the two gene expression platforms, we carried out in-depth analysis to further investigate the cause for such discrepancies. Our study shows that the exploitation of rich public expression resource requires extensive knowledge about the technologies, and experiment. Informatic methodologies for better interoperability among platforms still remain a gap. One of the areas that can be improved practically is the accurate sequence mapping of SAGE tags and array probes to full-length genes.

Integrated database for identifying candidate genes for Aspergillus flavus resistance in maize

PubMed Central

2010-01-01

Background Aspergillus flavus Link:Fr, an opportunistic fungus that produces aflatoxin, is pathogenic to maize and other oilseed crops. Aflatoxin is a potent carcinogen, and its presence markedly reduces the value of grain. Understanding and enhancing host resistance to A. flavus infection and/or subsequent aflatoxin accumulation is generally considered an efficient means of reducing grain losses to aflatoxin. Different proteomic, genomic and genetic studies of maize (Zea mays L.) have generated large data sets with the goal of identifying genes responsible for conferring resistance to A. flavus, or aflatoxin. Results In order to maximize the usage of different data sets in new studies, including association mapping, we have constructed a relational database with web interface integrating the results of gene expression, proteomic (both gel-based and shotgun), Quantitative Trait Loci (QTL) genetic mapping studies, and sequence data from the literature to facilitate selection of candidate genes for continued investigation. The Corn Fungal Resistance Associated Sequences Database (CFRAS-DB) (http://agbase.msstate.edu/) was created with the main goal of identifying genes important to aflatoxin resistance. CFRAS-DB is implemented using MySQL as the relational database management system running on a Linux server, using an Apache web server, and Perl CGI scripts as the web interface. The database and the associated web-based interface allow researchers to examine many lines of evidence (e.g. microarray, proteomics, QTL studies, SNP data) to assess the potential role of a gene or group of genes in the response of different maize lines to A. flavus infection and subsequent production of aflatoxin by the fungus. Conclusions CFRAS-DB provides the first opportunity to integrate data pertaining to the problem of A. flavus and aflatoxin resistance in maize in one resource and to support queries across different datasets. The web-based interface gives researchers different query options for mining the database across different types of experiments. The database is publically available at http://agbase.msstate.edu. PMID:20946609

Integrated database for identifying candidate genes for Aspergillus flavus resistance in maize.

PubMed

Kelley, Rowena Y; Gresham, Cathy; Harper, Jonathan; Bridges, Susan M; Warburton, Marilyn L; Hawkins, Leigh K; Pechanova, Olga; Peethambaran, Bela; Pechan, Tibor; Luthe, Dawn S; Mylroie, J E; Ankala, Arunkanth; Ozkan, Seval; Henry, W B; Williams, W P

2010-10-07

Aspergillus flavus Link:Fr, an opportunistic fungus that produces aflatoxin, is pathogenic to maize and other oilseed crops. Aflatoxin is a potent carcinogen, and its presence markedly reduces the value of grain. Understanding and enhancing host resistance to A. flavus infection and/or subsequent aflatoxin accumulation is generally considered an efficient means of reducing grain losses to aflatoxin. Different proteomic, genomic and genetic studies of maize (Zea mays L.) have generated large data sets with the goal of identifying genes responsible for conferring resistance to A. flavus, or aflatoxin. In order to maximize the usage of different data sets in new studies, including association mapping, we have constructed a relational database with web interface integrating the results of gene expression, proteomic (both gel-based and shotgun), Quantitative Trait Loci (QTL) genetic mapping studies, and sequence data from the literature to facilitate selection of candidate genes for continued investigation. The Corn Fungal Resistance Associated Sequences Database (CFRAS-DB) (http://agbase.msstate.edu/) was created with the main goal of identifying genes important to aflatoxin resistance. CFRAS-DB is implemented using MySQL as the relational database management system running on a Linux server, using an Apache web server, and Perl CGI scripts as the web interface. The database and the associated web-based interface allow researchers to examine many lines of evidence (e.g. microarray, proteomics, QTL studies, SNP data) to assess the potential role of a gene or group of genes in the response of different maize lines to A. flavus infection and subsequent production of aflatoxin by the fungus. CFRAS-DB provides the first opportunity to integrate data pertaining to the problem of A. flavus and aflatoxin resistance in maize in one resource and to support queries across different datasets. The web-based interface gives researchers different query options for mining the database across different types of experiments. The database is publically available at http://agbase.msstate.edu.

Soybean DREB1/CBF-type transcription factors function in heat and drought as well as cold stress-responsive gene expression.

PubMed

Kidokoro, Satoshi; Watanabe, Keitaro; Ohori, Teppei; Moriwaki, Takashi; Maruyama, Kyonoshin; Mizoi, Junya; Myint Phyu Sin Htwe, Nang; Fujita, Yasunari; Sekita, Sachiko; Shinozaki, Kazuo; Yamaguchi-Shinozaki, Kazuko

2015-02-01

Soybean (Glycine max) is a globally important crop, and its growth and yield are severely reduced by abiotic stresses, such as drought, heat, and cold. The cis-acting element DRE (dehydration-responsive element)/CRT plays an important role in activating gene expression in response to these stresses. The Arabidopsis DREB1/CBF genes that encode DRE-binding proteins function as transcriptional activators in the cold stress responsive gene expression. In this study, we identified 14 DREB1-type transcription factors (GmDREB1s) from a soybean genome database. The expression of most GmDREB1 genes in soybean was strongly induced by a variety of abiotic stresses, such as cold, drought, high salt, and heat. The GmDREB1 proteins activated transcription via DREs (dehydration-responsive element) in Arabidopsis and soybean protoplasts. Transcriptome analyses using transgenic Arabidopsis plants overexpressing GmDREB1s indicated that many of the downstream genes are cold-inducible and overlap with those of Arabidopsis DREB1A. We then comprehensively analyzed the downstream genes of GmDREB1B;1, which is closely related to DREB1A, using a transient expression system in soybean protoplasts. The expression of numerous genes induced by various abiotic stresses were increased by overexpressing GmDREB1B;1 in soybean, and DREs were the most conserved element in the promoters of these genes. The downstream genes of GmDREB1B;1 included numerous soybean-specific stress-inducible genes that encode an ABA receptor family protein, GmPYL21, and translation-related genes, such as ribosomal proteins. We confirmed that GmDREB1B;1 directly activates GmPYL21 expression and enhances ABRE-mediated gene expression in an ABA-independent manner. These results suggest that GmDREB1 proteins activate the expression of numerous soybean-specific stress-responsive genes under diverse abiotic stress conditions. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

Design and evaluation of Actichip, a thematic microarray for the study of the actin cytoskeleton

PubMed Central

Muller, Jean; Mehlen, André; Vetter, Guillaume; Yatskou, Mikalai; Muller, Arnaud; Chalmel, Frédéric; Poch, Olivier; Friederich, Evelyne; Vallar, Laurent

2007-01-01

Background The actin cytoskeleton plays a crucial role in supporting and regulating numerous cellular processes. Mutations or alterations in the expression levels affecting the actin cytoskeleton system or related regulatory mechanisms are often associated with complex diseases such as cancer. Understanding how qualitative or quantitative changes in expression of the set of actin cytoskeleton genes are integrated to control actin dynamics and organisation is currently a challenge and should provide insights in identifying potential targets for drug discovery. Here we report the development of a dedicated microarray, the Actichip, containing 60-mer oligonucleotide probes for 327 genes selected for transcriptome analysis of the human actin cytoskeleton. Results Genomic data and sequence analysis features were retrieved from GenBank and stored in an integrative database called Actinome. From these data, probes were designed using a home-made program (CADO4MI) allowing sequence refinement and improved probe specificity by combining the complementary information recovered from the UniGene and RefSeq databases. Actichip performance was analysed by hybridisation with RNAs extracted from epithelial MCF-7 cells and human skeletal muscle. Using thoroughly standardised procedures, we obtained microarray images with excellent quality resulting in high data reproducibility. Actichip displayed a large dynamic range extending over three logs with a limit of sensitivity between one and ten copies of transcript per cell. The array allowed accurate detection of small changes in gene expression and reliable classification of samples based on the expression profiles of tissue-specific genes. When compared to two other oligonucleotide microarray platforms, Actichip showed similar sensitivity and concordant expression ratios. Moreover, Actichip was able to discriminate the highly similar actin isoforms whereas the two other platforms did not. Conclusion Our data demonstrate that Actichip is a powerful alternative to commercial high density microarrays for cytoskeleton gene profiling in normal or pathological samples. Actichip is available upon request. PMID:17727702

Interactive knowledge discovery and data mining on genomic expression data with numeric formal concept analysis.

PubMed

González-Calabozo, Jose M; Valverde-Albacete, Francisco J; Peláez-Moreno, Carmen

2016-09-15

Gene Expression Data (GED) analysis poses a great challenge to the scientific community that can be framed into the Knowledge Discovery in Databases (KDD) and Data Mining (DM) paradigm. Biclustering has emerged as the machine learning method of choice to solve this task, but its unsupervised nature makes result assessment problematic. This is often addressed by means of Gene Set Enrichment Analysis (GSEA). We put forward a framework in which GED analysis is understood as an Exploratory Data Analysis (EDA) process where we provide support for continuous human interaction with data aiming at improving the step of hypothesis abduction and assessment. We focus on the adaptation to human cognition of data interpretation and visualization of the output of EDA. First, we give a proper theoretical background to bi-clustering using Lattice Theory and provide a set of analysis tools revolving around [Formula: see text]-Formal Concept Analysis ([Formula: see text]-FCA), a lattice-theoretic unsupervised learning technique for real-valued matrices. By using different kinds of cost structures to quantify expression we obtain different sequences of hierarchical bi-clusterings for gene under- and over-expression using thresholds. Consequently, we provide a method with interleaved analysis steps and visualization devices so that the sequences of lattices for a particular experiment summarize the researcher's vision of the data. This also allows us to define measures of persistence and robustness of biclusters to assess them. Second, the resulting biclusters are used to index external omics databases-for instance, Gene Ontology (GO)-thus offering a new way of accessing publicly available resources. This provides different flavors of gene set enrichment against which to assess the biclusters, by obtaining their p-values according to the terminology of those resources. We illustrate the exploration procedure on a real data example confirming results previously published. The GED analysis problem gets transformed into the exploration of a sequence of lattices enabling the visualization of the hierarchical structure of the biclusters with a certain degree of granularity. The ability of FCA-based bi-clustering methods to index external databases such as GO allows us to obtain a quality measure of the biclusters, to observe the evolution of a gene throughout the different biclusters it appears in, to look for relevant biclusters-by observing their genes and what their persistence is-to infer, for instance, hypotheses on their function.

[Analysis of tissue-specific differentially methylated genes with differential gene expression in non-small cell lung cancer].

PubMed

Yin, L G; Zou, Z Q; Zhao, H Y; Zhang, C L; Shen, J G; Qi, L; Qi, M; Xue, Z Q

2014-01-01

Adenocarcinoma (ADC) and squamous cell carcinomas (SCC) are two subtypes of non-small cell lung carcinomas which are regarded as the leading cause of cancer-related malignancy worldwide. The aim of this study is to detect the differentially methylated loci (DMLs) and differentially methylated genes (DMGs) of these two tumor sets, and then to illustrate the different expression level of specific methylated genes. Using TCGA database and Illumina HumanMethylation 27 arrays, we first screened the DMGs and DMLs in tumor samples. Then, we explored the BiologicalProcess terms of hypermethylated and hypomethylated genes using Functional Gene Ontology (GO) catalogues. Hypermethylation intensively occurred in CpG-island, whereas hypomethylation was located in non-CpG-island. Most SCC and ADC hypermethylated genes involved GO function of DNA dependenit regulation of transcription, and hypomethylated genes mainly 'enriched in the term of immune responses. Additionally, the expression level of specific differentially methylated genesis distinctbetween ADC and SCC. It is concluded that ADC and SCC have different methylated status that might play an important role in carcinogenesis.

pseudoMap: an innovative and comprehensive resource for identification of siRNA-mediated mechanisms in human transcribed pseudogenes.

PubMed

Chan, Wen-Ling; Yang, Wen-Kuang; Huang, Hsien-Da; Chang, Jan-Gowth

2013-01-01

RNA interference (RNAi) is a gene silencing process within living cells, which is controlled by the RNA-induced silencing complex with a sequence-specific manner. In flies and mice, the pseudogene transcripts can be processed into short interfering RNAs (siRNAs) that regulate protein-coding genes through the RNAi pathway. Following these findings, we construct an innovative and comprehensive database to elucidate siRNA-mediated mechanism in human transcribed pseudogenes (TPGs). To investigate TPG producing siRNAs that regulate protein-coding genes, we mapped the TPGs to small RNAs (sRNAs) that were supported by publicly deep sequencing data from various sRNA libraries and constructed the TPG-derived siRNA-target interactions. In addition, we also presented that TPGs can act as a target for miRNAs that actually regulate the parental gene. To enable the systematic compilation and updating of these results and additional information, we have developed a database, pseudoMap, capturing various types of information, including sequence data, TPG and cognate annotation, deep sequencing data, RNA-folding structure, gene expression profiles, miRNA annotation and target prediction. As our knowledge, pseudoMap is the first database to demonstrate two mechanisms of human TPGs: encoding siRNAs and decoying miRNAs that target the parental gene. pseudoMap is freely accessible at http://pseudomap.mbc.nctu.edu.tw/. Database URL: http://pseudomap.mbc.nctu.edu.tw/

MIRNA-DISTILLER: A Stand-Alone Application to Compile microRNA Data from Databases.

PubMed

Rieger, Jessica K; Bodan, Denis A; Zanger, Ulrich M

2011-01-01

MicroRNAs (miRNA) are small non-coding RNA molecules of ∼22 nucleotides which regulate large numbers of genes by binding to seed sequences at the 3'-untranslated region of target gene transcripts. The target mRNA is then usually degraded or translation is inhibited, although thus resulting in posttranscriptional down regulation of gene expression at the mRNA and/or protein level. Due to the bioinformatic difficulties in predicting functional miRNA binding sites, several publically available databases have been developed that predict miRNA binding sites based on different algorithms. The parallel use of different databases is currently indispensable, but highly uncomfortable and time consuming, especially when working with numerous genes of interest. We have therefore developed a new stand-alone program, termed MIRNA-DISTILLER, which allows to compile miRNA data for given target genes from public databases. Currently implemented are TargetScan, microCosm, and miRDB, which may be queried independently, pairwise, or together to calculate the respective intersections. Data are stored locally for application of further analysis tools including freely definable biological parameter filters, customized output-lists for both miRNAs and target genes, and various graphical facilities. The software, a data example file and a tutorial are freely available at http://www.ikp-stuttgart.de/content/language1/html/10415.asp.

MIRNA-DISTILLER: A Stand-Alone Application to Compile microRNA Data from Databases

PubMed Central

Rieger, Jessica K.; Bodan, Denis A.; Zanger, Ulrich M.

2011-01-01

MicroRNAs (miRNA) are small non-coding RNA molecules of ∼22 nucleotides which regulate large numbers of genes by binding to seed sequences at the 3′-untranslated region of target gene transcripts. The target mRNA is then usually degraded or translation is inhibited, although thus resulting in posttranscriptional down regulation of gene expression at the mRNA and/or protein level. Due to the bioinformatic difficulties in predicting functional miRNA binding sites, several publically available databases have been developed that predict miRNA binding sites based on different algorithms. The parallel use of different databases is currently indispensable, but highly uncomfortable and time consuming, especially when working with numerous genes of interest. We have therefore developed a new stand-alone program, termed MIRNA-DISTILLER, which allows to compile miRNA data for given target genes from public databases. Currently implemented are TargetScan, microCosm, and miRDB, which may be queried independently, pairwise, or together to calculate the respective intersections. Data are stored locally for application of further analysis tools including freely definable biological parameter filters, customized output-lists for both miRNAs and target genes, and various graphical facilities. The software, a data example file and a tutorial are freely available at http://www.ikp-stuttgart.de/content/language1/html/10415.asp PMID:22303335

In silico identification and comparative analysis of differentially expressed genes in human and mouse tissues

PubMed Central

Pao, Sheng-Ying; Lin, Win-Li; Hwang, Ming-Jing

2006-01-01

Background Screening for differentially expressed genes on the genomic scale and comparative analysis of the expression profiles of orthologous genes between species to study gene function and regulation are becoming increasingly feasible. Expressed sequence tags (ESTs) are an excellent source of data for such studies using bioinformatic approaches because of the rich libraries and tremendous amount of data now available in the public domain. However, any large-scale EST-based bioinformatics analysis must deal with the heterogeneous, and often ambiguous, tissue and organ terms used to describe EST libraries. Results To deal with the issue of tissue source, in this work, we carefully screened and organized more than 8 million human and mouse ESTs into 157 human and 108 mouse tissue/organ categories, to which we applied an established statistic test using different thresholds of the p value to identify genes differentially expressed in different tissues. Further analysis of the tissue distribution and level of expression of human and mouse orthologous genes showed that tissue-specific orthologs tended to have more similar expression patterns than those lacking significant tissue specificity. On the other hand, a number of orthologs were found to have significant disparity in their expression profiles, hinting at novel functions, divergent regulation, or new ortholog relationships. Conclusion Comprehensive statistics on the tissue-specific expression of human and mouse genes were obtained in this very large-scale, EST-based analysis. These statistical results have been organized into a database, freely accessible at our website , for easy searching of human and mouse tissue-specific genes and for investigating gene expression profiles in the context of comparative genomics. Comparative analysis showed that, although highly tissue-specific genes tend to exhibit similar expression profiles in human and mouse, there are significant exceptions, indicating that orthologous genes, while sharing basic genomic properties, could result in distinct phenotypes. PMID:16626500

BloodChIP: a database of comparative genome-wide transcription factor binding profiles in human blood cells.

PubMed

Chacon, Diego; Beck, Dominik; Perera, Dilmi; Wong, Jason W H; Pimanda, John E

2014-01-01

The BloodChIP database (http://www.med.unsw.edu.au/CRCWeb.nsf/page/BloodChIP) supports exploration and visualization of combinatorial transcription factor (TF) binding at a particular locus in human CD34-positive and other normal and leukaemic cells or retrieval of target gene sets for user-defined combinations of TFs across one or more cell types. Increasing numbers of genome-wide TF binding profiles are being added to public repositories, and this trend is likely to continue. For the power of these data sets to be fully harnessed by experimental scientists, there is a need for these data to be placed in context and easily accessible for downstream applications. To this end, we have built a user-friendly database that has at its core the genome-wide binding profiles of seven key haematopoietic TFs in human stem/progenitor cells. These binding profiles are compared with binding profiles in normal differentiated and leukaemic cells. We have integrated these TF binding profiles with chromatin marks and expression data in normal and leukaemic cell fractions. All queries can be exported into external sites to construct TF-gene and protein-protein networks and to evaluate the association of genes with cellular processes and tissue expression.

Genomic resources for songbird research and their use in characterizing gene expression during brain development

PubMed Central

Li, XiaoChing; Wang, Xiu-Jie; Tannenhauser, Jonathan; Podell, Sheila; Mukherjee, Piali; Hertel, Moritz; Biane, Jeremy; Masuda, Shoko; Nottebohm, Fernando; Gaasterland, Terry

2007-01-01

Vocal learning and neuronal replacement have been studied extensively in songbirds, but until recently, few molecular and genomic tools for songbird research existed. Here we describe new molecular/genomic resources developed in our laboratory. We made cDNA libraries from zebra finch (Taeniopygia guttata) brains at different developmental stages. A total of 11,000 cDNA clones from these libraries, representing 5,866 unique gene transcripts, were randomly picked and sequenced from the 3′ ends. A web-based database was established for clone tracking, sequence analysis, and functional annotations. Our cDNA libraries were not normalized. Sequencing ESTs without normalization produced many developmental stage-specific sequences, yielding insights into patterns of gene expression at different stages of brain development. In particular, the cDNA library made from brains at posthatching day 30–50, corresponding to the period of rapid song system development and song learning, has the most diverse and richest set of genes expressed. We also identified five microRNAs whose sequences are highly conserved between zebra finch and other species. We printed cDNA microarrays and profiled gene expression in the high vocal center of both adult male zebra finches and canaries (Serinus canaria). Genes differentially expressed in the high vocal center were identified from the microarray hybridization results. Selected genes were validated by in situ hybridization. Networks among the regulated genes were also identified. These resources provide songbird biologists with tools for genome annotation, comparative genomics, and microarray gene expression analysis. PMID:17426146