Fungal Genes in Context: Genome Architecture Reflects Regulatory Complexity and Function

PubMed Central

Noble, Luke M.; Andrianopoulos, Alex

2013-01-01

Gene context determines gene expression, with local chromosomal environment most influential. Comparative genomic analysis is often limited in scope to conserved or divergent gene and protein families, and fungi are well suited to this approach with low functional redundancy and relatively streamlined genomes. We show here that one aspect of gene context, the amount of potential upstream regulatory sequence maintained through evolution, is highly predictive of both molecular function and biological process in diverse fungi. Orthologs with large upstream intergenic regions (UIRs) are strongly enriched in information processing functions, such as signal transduction and sequence-specific DNA binding, and, in the genus Aspergillus, include the majority of experimentally studied, high-level developmental and metabolic transcriptional regulators. Many uncharacterized genes are also present in this class and, by implication, may be of similar importance. Large intergenic regions also share two novel sequence characteristics, currently of unknown significance: they are enriched for plus-strand polypyrimidine tracts and an information-rich, putative regulatory motif that was present in the last common ancestor of the Pezizomycotina. Systematic consideration of gene UIR in comparative genomics, particularly for poorly characterized species, could help reveal organisms’ regulatory priorities. PMID:23699226

Comparative genome analysis in the integrated microbial genomes (IMG) system.

PubMed

Markowitz, Victor M; Kyrpides, Nikos C

2007-01-01

Comparative genome analysis is critical for the effective exploration of a rapidly growing number of complete and draft sequences for microbial genomes. The Integrated Microbial Genomes (IMG) system (img.jgi.doe.gov) has been developed as a community resource that provides support for comparative analysis of microbial genomes in an integrated context. IMG allows users to navigate the multidimensional microbial genome data space and focus their analysis on a subset of genes, genomes, and functions of interest. IMG provides graphical viewers, summaries, and occurrence profile tools for comparing genes, pathways, and functions (terms) across specific genomes. Genes can be further examined using gene neighborhoods and compared with sequence alignment tools.

Single-Cell and Single-Molecule Analysis of Gene Expression Regulation.

PubMed

Vera, Maria; Biswas, Jeetayu; Senecal, Adrien; Singer, Robert H; Park, Hye Yoon

2016-11-23

Recent advancements in single-cell and single-molecule imaging technologies have resolved biological processes in time and space that are fundamental to understanding the regulation of gene expression. Observations of single-molecule events in their cellular context have revealed highly dynamic aspects of transcriptional and post-transcriptional control in eukaryotic cells. This approach can relate transcription with mRNA abundance and lifetimes. Another key aspect of single-cell analysis is the cell-to-cell variability among populations of cells. Definition of heterogeneity has revealed stochastic processes, determined characteristics of under-represented cell types or transitional states, and integrated cellular behaviors in the context of multicellular organisms. In this review, we discuss novel aspects of gene expression of eukaryotic cells and multicellular organisms revealed by the latest advances in single-cell and single-molecule imaging technology.

Characterisation of the Context-Dependence of the Gene Concept in Research Articles. Possible Consequences for Teaching Concepts with Multiple Meanings

NASA Astrophysics Data System (ADS)

Flodin, Veronica S.

2017-03-01

The purpose of this study is to interpret and qualitatively characterise the content in some research articles and evaluate cases of possible difference in meanings of the gene concept used. Using a reformulation of Hirst's criteria of forms of knowledge, articles from five different sub-disciplines in biology (transmission genetic, molecular biology, genomics, developmental biology and population genetics) were characterised according to knowledge project, methods used and conceptual contexts. Depending on knowledge project, the gene may be used as a location of recombination, a target of regulatory proteins, a carrier of regulatory sequences, a cause in organ formation or a basis for a genetic map. Methods used range from catching wild birds and dissecting beetle larvae to growing yeast cells in 94 small wells as well as mapping of recombinants, doing statistical calculations, immunoblotting analysis of protein levels, analysis of gene expression with PCR, immunostaining of embryos and automated constructions of multi-locus linkage maps. The succeeding conceptual contexts focused around concepts as meiosis and chromosome, DNA and regulation, cell fitness and production, development and organ formation, conservation and evolution. These contextual differences lead to certain content leaps in relation to different conceptual schemes. The analysis of the various uses of the gene concept shows how differences in methodologies and questions entail a concept that escapes single definitions and "drift around" in meanings. These findings make it important to ask how science might use concepts as tools of specific inquiries and to discuss possible consequences for biology education.

GIANT 2.0: genome-scale integrated analysis of gene networks in tissues.

PubMed

Wong, Aaron K; Krishnan, Arjun; Troyanskaya, Olga G

2018-05-25

GIANT2 (Genome-wide Integrated Analysis of gene Networks in Tissues) is an interactive web server that enables biomedical researchers to analyze their proteins and pathways of interest and generate hypotheses in the context of genome-scale functional maps of human tissues. The precise actions of genes are frequently dependent on their tissue context, yet direct assay of tissue-specific protein function and interactions remains infeasible in many normal human tissues and cell-types. With GIANT2, researchers can explore predicted tissue-specific functional roles of genes and reveal changes in those roles across tissues, all through interactive multi-network visualizations and analyses. Additionally, the NetWAS approach available through the server uses tissue-specific/cell-type networks predicted by GIANT2 to re-prioritize statistical associations from GWAS studies and identify disease-associated genes. GIANT2 predicts tissue-specific interactions by integrating diverse functional genomics data from now over 61 400 experiments for 283 diverse tissues and cell-types. GIANT2 does not require any registration or installation and is freely available for use at http://giant-v2.princeton.edu.

Visualizing conserved gene location across microbe genomes

NASA Astrophysics Data System (ADS)

Shaw, Chris D.

2009-01-01

This paper introduces an analysis-based zoomable visualization technique for displaying the location of genes across many related species of microbes. The purpose of this visualizatiuon is to enable a biologist to examine the layout of genes in the organism of interest with respect to the gene organization of related organisms. During the genomic annotation process, the ability to observe gene organization in common with previously annotated genomes can help a biologist better confirm the structure and function of newly analyzed microbe DNA sequences. We have developed a visualization and analysis tool that enables the biologist to observe and examine gene organization among genomes, in the context of the primary sequence of interest. This paper describes the visualization and analysis steps, and presents a case study using a number of Rickettsia genomes.

[Genome-scale sequence data processing and epigenetic analysis of DNA methylation].

PubMed

Wang, Ting-Zhang; Shan, Gao; Xu, Jian-Hong; Xue, Qing-Zhong

2013-06-01

A new approach recently developed for detecting cytosine DNA methylation (mC) and analyzing the genome-scale DNA methylation profiling, is called BS-Seq which is based on bisulfite conversion of genomic DNA combined with next-generation sequencing. The method can not only provide an insight into the difference of genome-scale DNA methylation among different organisms, but also reveal the conservation of DNA methylation in all contexts and nucleotide preference for different genomic regions, including genes, exons, and repetitive DNA sequences. It will be helpful to under-stand the epigenetic impacts of cytosine DNA methylation on the regulation of gene expression and maintaining silence of repetitive sequences, such as transposable elements. In this paper, we introduce the preprocessing steps of DNA methylation data, by which cytosine (C) and guanine (G) in the reference sequence are transferred to thymine (T) and adenine (A), and cytosine in reads is transferred to thymine, respectively. We also comprehensively review the main content of the DNA methylation analysis on the genomic scale: (1) the cytosine methylation under the context of different sequences; (2) the distribution of genomic methylcytosine; (3) DNA methylation context and the preference for the nucleotides; (4) DNA- protein interaction sites of DNA methylation; (5) degree of methylation of cytosine in the different structural elements of genes. DNA methylation analysis technique provides a powerful tool for the epigenome study in human and other species, and genes and environment interaction, and founds the theoretical basis for further development of disease diagnostics and therapeutics in human.

Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues

PubMed Central

Lee, Je Hyuk; Daugharthy, Evan R.; Scheiman, Jonathan; Kalhor, Reza; Ferrante, Thomas C.; Terry, Richard; Turczyk, Brian M.; Yang, Joyce L.; Lee, Ho Suk; Aach, John; Zhang, Kun; Church, George M.

2014-01-01

RNA sequencing measures the quantitative change in gene expression over the whole transcriptome, but it lacks spatial context. On the other hand, in situ hybridization provides the location of gene expression, but only for a small number of genes. Here we detail a protocol for genome-wide profiling of gene expression in situ in fixed cells and tissues, in which RNA is converted into cross-linked cDNA amplicons and sequenced manually on a confocal microscope. Unlike traditional RNA-seq our method enriches for context-specific transcripts over house-keeping and/or structural RNA, and it preserves the tissue architecture for RNA localization studies. Our protocol is written for researchers experienced in cell microscopy with minimal computing skills. Library construction and sequencing can be completed within 14 d, with image analysis requiring an additional 2 d. PMID:25675209

Detecting recurrent gene mutation in interaction network context using multi-scale graph diffusion.

PubMed

Babaei, Sepideh; Hulsman, Marc; Reinders, Marcel; de Ridder, Jeroen

2013-01-23

Delineating the molecular drivers of cancer, i.e. determining cancer genes and the pathways which they deregulate, is an important challenge in cancer research. In this study, we aim to identify pathways of frequently mutated genes by exploiting their network neighborhood encoded in the protein-protein interaction network. To this end, we introduce a multi-scale diffusion kernel and apply it to a large collection of murine retroviral insertional mutagenesis data. The diffusion strength plays the role of scale parameter, determining the size of the network neighborhood that is taken into account. As a result, in addition to detecting genes with frequent mutations in their genomic vicinity, we find genes that harbor frequent mutations in their interaction network context. We identify densely connected components of known and putatively novel cancer genes and demonstrate that they are strongly enriched for cancer related pathways across the diffusion scales. Moreover, the mutations in the clusters exhibit a significant pattern of mutual exclusion, supporting the conjecture that such genes are functionally linked. Using multi-scale diffusion kernel, various infrequently mutated genes are found to harbor significant numbers of mutations in their interaction network neighborhood. Many of them are well-known cancer genes. The results demonstrate the importance of defining recurrent mutations while taking into account the interaction network context. Importantly, the putative cancer genes and networks detected in this study are found to be significant at different diffusion scales, confirming the necessity of a multi-scale analysis.

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

PubMed

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

2017-04-27

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

The context of transcription start site regions is crucial for transcription of a plant tRNA(Lys)(UUU) gene group both in vitro and in vivo.

PubMed

Yukawa, Yasushi; Akama, Kazuhito; Noguchi, Kanta; Komiya, Masaaki; Sugiura, Masahiro

2013-01-10

Nuclear tRNA genes are transcribed by RNA polymerase III. The A- and B-boxes located within the transcribed regions are essential promoter elements for nuclear tRNA gene transcription. The Arabidopsis genome contains ten annotated genes encoding identical tRNA(Lys)(UUU) molecules, which are scattered on the five chromosomes. In this study, we prepared ten tDNA constructs including each of the tRNA(Lys)(UUU) coding sequences with their individual 5' and 3' flanking sequences, and assayed tRNA expression using an in vitro RNA polymerase III-dependent transcription system. Transcription levels differed significantly among the ten genes and two of the tRNA genes were transcribed at a very low level, despite possessing A- and B-boxes identical to those of the other tRNA genes. To examine whether the in vitro results were reproducible in vivo, the 5' flanking sequence of an amber suppressor tRNA gene was then replaced with those of the ten tRNA(Lys) genes. An in vivo experiment based on an amber suppressor tRNA that mediates suppression of a premature amber codon in a β-glucuronidase (GUS) reporter gene in plant tissues generated nearly identical results to those obtained in vitro. Analysis of mutated versions of the amber suppressor tRNA gene, which contained base substitutions around the transcription start site (TSS), showed that the context around the transcription start sites is a crucial determinant for transcription of plant tRNA(Lys)(UUU) both in vitro and in vivo. The above transcription regulation by context around TSS differed between tRNA genes and other Pol III-dependent genes. Copyright © 2012 Elsevier B.V. All rights reserved.

Genome-wide comparative analysis of codon usage bias and codon context patterns among cyanobacterial genomes.

PubMed

Prabha, Ratna; Singh, Dhananjaya P; Sinha, Swati; Ahmad, Khurshid; Rai, Anil

2017-04-01

With the increasing accumulation of genomic sequence information of prokaryotes, the study of codon usage bias has gained renewed attention. The purpose of this study was to examine codon selection pattern within and across cyanobacterial species belonging to diverse taxonomic orders and habitats. We performed detailed comparative analysis of cyanobacterial genomes with respect to codon bias. Our analysis reflects that in cyanobacterial genomes, A- and/or T-ending codons were used predominantly in the genes whereas G- and/or C-ending codons were largely avoided. Variation in the codon context usage of cyanobacterial genes corresponded to the clustering of cyanobacteria as per their GC content. Analysis of codon adaptation index (CAI) and synonymous codon usage order (SCUO) revealed that majority of genes are associated with low codon bias. Codon selection pattern in cyanobacterial genomes reflected compositional constraints as major influencing factor. It is also identified that although, mutational constraint may play some role in affecting codon usage bias in cyanobacteria, compositional constraint in terms of genomic GC composition coupled with environmental factors affected codon selection pattern in cyanobacterial genomes. Copyright © 2016 Elsevier B.V. All rights reserved.

Microsatellite data analysis for population genetics

USDA-ARS?s Scientific Manuscript database

Theories and analytical tools of population genetics have been widely applied for addressing various questions in the fields of ecological genetics, conservation biology, and any context where the role of dispersal or gene flow is important. Underlying much of population genetics is the analysis of ...

Orthoscape: a cytoscape application for grouping and visualization KEGG based gene networks by taxonomy and homology principles.

PubMed

Mustafin, Zakhar Sergeevich; Lashin, Sergey Alexandrovich; Matushkin, Yury Georgievich; Gunbin, Konstantin Vladimirovich; Afonnikov, Dmitry Arkadievich

2017-01-27

There are many available software tools for visualization and analysis of biological networks. Among them, Cytoscape ( http://cytoscape.org/ ) is one of the most comprehensive packages, with many plugins and applications which extends its functionality by providing analysis of protein-protein interaction, gene regulatory and gene co-expression networks, metabolic, signaling, neural as well as ecological-type networks including food webs, communities networks etc. Nevertheless, only three plugins tagged 'network evolution' found in Cytoscape official app store and in literature. We have developed a new Cytoscape 3.0 application Orthoscape aimed to facilitate evolutionary analysis of gene networks and visualize the results. Orthoscape aids in analysis of evolutionary information available for gene sets and networks by highlighting: (1) the orthology relationships between genes; (2) the evolutionary origin of gene network components; (3) the evolutionary pressure mode (diversifying or stabilizing, negative or positive selection) of orthologous groups in general and/or branch-oriented mode. The distinctive feature of Orthoscape is the ability to control all data analysis steps via user-friendly interface. Orthoscape allows its users to analyze gene networks or separated gene sets in the context of evolution. At each step of data analysis, Orthoscape also provides for convenient visualization and data manipulation.

Gene function prediction with gene interaction networks: a context graph kernel approach.

PubMed

Li, Xin; Chen, Hsinchun; Li, Jiexun; Zhang, Zhu

2010-01-01

Predicting gene functions is a challenge for biologists in the postgenomic era. Interactions among genes and their products compose networks that can be used to infer gene functions. Most previous studies adopt a linkage assumption, i.e., they assume that gene interactions indicate functional similarities between connected genes. In this study, we propose to use a gene's context graph, i.e., the gene interaction network associated with the focal gene, to infer its functions. In a kernel-based machine-learning framework, we design a context graph kernel to capture the information in context graphs. Our experimental study on a testbed of p53-related genes demonstrates the advantage of using indirect gene interactions and shows the empirical superiority of the proposed approach over linkage-assumption-based methods, such as the algorithm to minimize inconsistent connected genes and diffusion kernels.

Outlier analysis of functional genomic profiles enriches for oncology targets and enables precision medicine.

PubMed

Zhu, Zhou; Ihle, Nathan T; Rejto, Paul A; Zarrinkar, Patrick P

2016-06-13

Genome-scale functional genomic screens across large cell line panels provide a rich resource for discovering tumor vulnerabilities that can lead to the next generation of targeted therapies. Their data analysis typically has focused on identifying genes whose knockdown enhances response in various pre-defined genetic contexts, which are limited by biological complexities as well as the incompleteness of our knowledge. We thus introduce a complementary data mining strategy to identify genes with exceptional sensitivity in subsets, or outlier groups, of cell lines, allowing an unbiased analysis without any a priori assumption about the underlying biology of dependency. Genes with outlier features are strongly and specifically enriched with those known to be associated with cancer and relevant biological processes, despite no a priori knowledge being used to drive the analysis. Identification of exceptional responders (outliers) may not lead only to new candidates for therapeutic intervention, but also tumor indications and response biomarkers for companion precision medicine strategies. Several tumor suppressors have an outlier sensitivity pattern, supporting and generalizing the notion that tumor suppressors can play context-dependent oncogenic roles. The novel application of outlier analysis described here demonstrates a systematic and data-driven analytical strategy to decipher large-scale functional genomic data for oncology target and precision medicine discoveries.

Using the gene ontology for microarray data mining: a comparison of methods and application to age effects in human prefrontal cortex.

PubMed

Pavlidis, Paul; Qin, Jie; Arango, Victoria; Mann, John J; Sibille, Etienne

2004-06-01

One of the challenges in the analysis of gene expression data is placing the results in the context of other data available about genes and their relationships to each other. Here, we approach this problem in the study of gene expression changes associated with age in two areas of the human prefrontal cortex, comparing two computational methods. The first method, "overrepresentation analysis" (ORA), is based on statistically evaluating the fraction of genes in a particular gene ontology class found among the set of genes showing age-related changes in expression. The second method, "functional class scoring" (FCS), examines the statistical distribution of individual gene scores among all genes in the gene ontology class and does not involve an initial gene selection step. We find that FCS yields more consistent results than ORA, and the results of ORA depended strongly on the gene selection threshold. Our findings highlight the utility of functional class scoring for the analysis of complex expression data sets and emphasize the advantage of considering all available genomic information rather than sets of genes that pass a predetermined "threshold of significance."

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

PubMed

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

2015-11-01

A meta-analysis of 13 independent microarray data sets was performed and gene expression profiles from cystic fibrosis (CF), similar disorders (COPD: chronic obstructive pulmonary disease, IPF: idiopathic pulmonary fibrosis, asthma), environmental conditions (smoking, epithelial injury), related cellular processes (epithelial differentiation/regeneration), and non-respiratory "control" conditions (schizophrenia, dieting), were compared. Similarity among differentially expressed (DE) gene lists was assessed using a permutation test, and a clustergram was constructed, identifying common gene markers. Global gene expression values were standardized using a novel approach, revealing that similarities between independent data sets run deeper than shared DE genes. Correlation of gene expression values identified putative gene regulators of the CF transmembrane conductance regulator (CFTR) gene, of potential therapeutic significance. Our study provides a novel perspective on CF epithelial gene expression in the context of other lung disorders and conditions, and highlights the contribution of differentiation/EMT and injury to gene signatures of respiratory disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further investigations. Conclusions The analysis on the contextual gene sets and characterization of networks of interaction composed of these sets discovered distinct functional differences underlying various types of cancer. The results show that our method successfully reveals many subtype-specific regions in the identified maps of biological contexts, which well represent biological functions that can be connected to specific subtypes. PMID:23418942

Copy-number and gene dependency analysis reveals partial copy loss of wild-type SF3B1 as a novel cancer vulnerability. | Office of Cancer Genomics

Cancer.gov

Genomic instability is a hallmark of human cancer, and results in widespread somatic copy number alterations. We used a genome-scale shRNA viability screen in human cancer cell lines to systematically identify genes that are essential in the context of particular copy-number alterations (copy-number associated gene dependencies). The most enriched class of copy-number associated gene dependencies was CYCLOPS (Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS) genes, and spliceosome components were the most prevalent.

Molecular profiles to biology and pathways: a systems biology approach.

PubMed

Van Laere, Steven; Dirix, Luc; Vermeulen, Peter

2016-06-16

Interpreting molecular profiles in a biological context requires specialized analysis strategies. Initially, lists of relevant genes were screened to identify enriched concepts associated with pathways or specific molecular processes. However, the shortcoming of interpreting gene lists by using predefined sets of genes has resulted in the development of novel methods that heavily rely on network-based concepts. These algorithms have the advantage that they allow a more holistic view of the signaling properties of the condition under study as well as that they are suitable for integrating different data types like gene expression, gene mutation, and even histological parameters.

Exploring Genetic Attributions Underlying Radiotherapy-Induced Fatigue in Prostate Cancer Patients.

PubMed

Hashemi, Sepehr; Fernandez Martinez, Juan Luis; Saligan, Leorey; Sonis, Stephen

2017-09-01

Despite numerous proposed mechanisms, no definitive pathophysiology underlying radiotherapy-induced fatigue (RIF) has been established. However, the dysregulation of a set of 35 genes was recently validated to predict development of fatigue in prostate cancer patients receiving radiotherapy. To hypothesize novel pathways, and provide genetic targets for currently proposed pathways implicated in RIF development through analysis of the previously validated gene set. The gene set was analyzed for all phenotypic attributions implicated in the phenotype of fatigue. Initially, a "directed" approach was used by querying specific fatigue-related sub-phenotypes against all known phenotypic attributions of the gene set. Then, an "undirected" approach, reviewing the entirety of the literature referencing the 35 genes, was used to increase analysis sensitivity. The dysregulated genes attribute to neural, immunological, mitochondrial, muscular, and metabolic pathways. In addition, certain genes suggest phenotypes not previously emphasized in the context of RIF, such as ionizing radiation sensitivity, DNA damage, and altered DNA repair frequency. Several genes also associated with prostate cancer depression, possibly emphasizing variable radiosensitivity by RIF-prone patients, which may have palliative care implications. Despite the relevant findings, many of the 35 RIF-predictive genes are poorly characterized, warranting their investigation. The implications of herein presented RIF pathways are purely theoretical until specific end-point driven experiments are conducted in more congruent contexts. Nevertheless, the presented attributions are informative, directing future investigation to definitively elucidate RIF's pathoetiology. This study demonstrates an arguably comprehensive method of approaching known differential expression underlying a complex phenotype, to correlate feasible pathophysiology. Copyright © 2017 American Academy of Hospice and Palliative Medicine. All rights reserved.

The gene patent controversy on Twitter: a case study of Twitter users' responses to the CHEO lawsuit against Long QT gene patents.

PubMed

Du, Li; Kamenova, Kalina; Caulfield, Timothy

2015-08-25

The recent Canadian lawsuit on patent infringement, filed by the Children's Hospital of Eastern Ontario (CHEO), has engendered a significant public debate on whether patenting genes should be legal in Canada. In part, this public debate has involved the use of social networking sites, such as Twitter. This case provides an opportunity to examine how Twitter was used in the context of this gene patent controversy. We collected 310 English-language tweets that contained the keyword "gene patents" by using TOPSY.com and Twitter's built-in search engine. A content analysis of the messages was conducted to establish the users' perspectives on both CHEO's court challenge and the broader controversy over the patenting of human DNA. More specifically, we analyzed the users' demographics, geographic locations, and attitudes toward the CHEO position on gene patents and the patentability of human genes in principle. Our analysis has shown that messages tweeted by news media and health care organizations were re-tweeted most frequently in Twitter discussions regarding both the CHEO patent infringement lawsuit and gene patents in general. 34.8% of tweets were supportive of CHEO, with 52.8% of the supportive tweets suggesting that gene patents contravene patients' rights to health care access. 17.6% of the supportive tweets cited ethical and social concerns against gene patents. Nearly 40% of tweets clearly expressed that human genes should not be patentable, and there were no tweets that presented perspectives favourable toward the patenting of human genes. Access to healthcare and the use of genetic testing were the most important concerns raised by Twitter users in the context of the CHEO case. Our analysis of tweets reveals an expectation that the CHEO lawsuit will provide an opportunity to clear the confusion on gene patents by establishing a legal precedent on the patentability of human genes in Canada. In general, there were no tweets arguing in favour of gene patents. Given the emerging role of social media in framing the public dialogue on these issues, this sentiment could potentially have an impact on the nature and tone of the Canadian policy debate.

Systematic prediction of control proteins and their DNA binding sites

PubMed Central

Sorokin, Valeriy; Severinov, Konstantin; Gelfand, Mikhail S.

2009-01-01

We present here the results of a systematic bioinformatics analysis of control (C) proteins, a class of DNA-binding regulators that control time-delayed transcription of their own genes as well as restriction endonuclease genes in many type II restriction-modification systems. More than 290 C protein homologs were identified and DNA-binding sites for ∼70% of new and previously known C proteins were predicted by a combination of phylogenetic footprinting and motif searches in DNA upstream of C protein genes. Additional analysis revealed that a large proportion of C protein genes are translated from leaderless RNA, which may contribute to time-delayed nature of genetic switches operated by these proteins. Analysis of genetic contexts of newly identified C protein genes revealed that they are not exclusively associated with restriction-modification genes; numerous instances of associations with genes originating from mobile genetic elements were observed. These instances might be vestiges of ancient horizontal transfers and indicate that during evolution ancestral restriction-modification system genes were the sites of mobile elements insertions. PMID:19056824

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

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

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

2008-05-12

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

Asymmetric latent semantic indexing for gene expression experiments visualization.

PubMed

González, Javier; Muñoz, Alberto; Martos, Gabriel

2016-08-01

We propose a new method to visualize gene expression experiments inspired by the latent semantic indexing technique originally proposed in the textual analysis context. By using the correspondence word-gene document-experiment, we define an asymmetric similarity measure of association for genes that accounts for potential hierarchies in the data, the key to obtain meaningful gene mappings. We use the polar decomposition to obtain the sources of asymmetry of the similarity matrix, which are later combined with previous knowledge. Genetic classes of genes are identified by means of a mixture model applied in the genes latent space. We describe the steps of the procedure and we show its utility in the Human Cancer dataset.

Using the Saccharomyces Genome Database (SGD) for analysis of genomic information

PubMed Central

Skrzypek, Marek S.; Hirschman, Jodi

2011-01-01

Analysis of genomic data requires access to software tools that place the sequence-derived information in the context of biology. The Saccharomyces Genome Database (SGD) integrates functional information about budding yeast genes and their products with a set of analysis tools that facilitate exploring their biological details. This unit describes how the various types of functional data available at SGD can be searched, retrieved, and analyzed. Starting with the guided tour of the SGD Home page and Locus Summary page, this unit highlights how to retrieve data using YeastMine, how to visualize genomic information with GBrowse, how to explore gene expression patterns with SPELL, and how to use Gene Ontology tools to characterize large-scale datasets. PMID:21901739

Bicluster Pattern of Codon Context Usages between Flavivirus and Vector Mosquito Aedes aegypti: Relevance to Infection and Transcriptional Response of Mosquito Genes

PubMed Central

Behura, Susanta K.; Severson, David W.

2014-01-01

The mosquito Aedes aegypti is the primary vector of dengue virus (DENV) infection in most of the subtropical and tropical countries. Besides DENV, yellow fever virus (YFV) is also transmitted by A. aegypti. Susceptibility of A. aegypti to West Nile virus (WNV) has also been confirmed. Although studies have indicated correlation of codon bias between flaviviridae and their animal/insect hosts, it is not clear if codon sequences have any relation to susceptibility of A. aegypti to DENV, YFV and WNV. In the current study, usages of codon context sequences (codon pairs for neighboring amino acids) of the vector (A. aegypti) genome as well as the flaviviral genomes are investigated. We used bioinformatics methods to quantify codon context bias in a genome-wide manner of A. aegypti as well as DENV, WNV and YFV sequences. Mutual information statistics was applied to perform bicluster analysis of codon context bias between vector and flaviviral sequences. Functional relevance of the bicluster pattern was inferred from published microarray data. Our study shows that codon context bias of DENV, WNV and YFV sequences varies in a bicluster manner with that of specific sets of genes of A. aegypti. Many of these mosquito genes are known to be differentially expressed in response to flaviviral infection suggesting that codon context sequences of A. aegypti and the flaviviruses may play a role in the susceptible interaction between flaviviruses and this mosquito. The bias inusages of codon context sequences likely has a functional association with susceptibility of A. aegypti to flaviviral infection. The results from this study will allow us to conduct hypothesis driven tests to examine the role of codon contexts bias in evolution of vector-virus interactions at the molecular level. PMID:24838953

Identification of functional modules that correlate with phenotypic difference: the influence of network topology

PubMed Central

2010-01-01

One of the important challenges to post-genomic biology is relating observed phenotypic alterations to the underlying collective alterations in genes. Current inferential methods, however, invariably omit large bodies of information on the relationships between genes. We present a method that takes account of such information - expressed in terms of the topology of a correlation network - and we apply the method in the context of current procedures for gene set enrichment analysis. PMID:20187943

Predicting Protein Function by Genomic Context: Quantitative Evaluation and Qualitative Inferences

PubMed Central

Huynen, Martijn; Snel, Berend; Lathe, Warren; Bork, Peer

2000-01-01

Various new methods have been proposed to predict functional interactions between proteins based on the genomic context of their genes. The types of genomic context that they use are Type I: the fusion of genes; Type II: the conservation of gene-order or co-occurrence of genes in potential operons; and Type III: the co-occurrence of genes across genomes (phylogenetic profiles). Here we compare these types for their coverage, their correlations with various types of functional interaction, and their overlap with homology-based function assignment. We apply the methods to Mycoplasma genitalium, the standard benchmarking genome in computational and experimental genomics. Quantitatively, conservation of gene order is the technique with the highest coverage, applying to 37% of the genes. By combining gene order conservation with gene fusion (6%), the co-occurrence of genes in operons in absence of gene order conservation (8%), and the co-occurrence of genes across genomes (11%), significant context information can be obtained for 50% of the genes (the categories overlap). Qualitatively, we observe that the functional interactions between genes are stronger as the requirements for physical neighborhood on the genome are more stringent, while the fraction of potential false positives decreases. Moreover, only in cases in which gene order is conserved in a substantial fraction of the genomes, in this case six out of twenty-five, does a single type of functional interaction (physical interaction) clearly dominate (>80%). In other cases, complementary function information from homology searches, which is available for most of the genes with significant genomic context, is essential to predict the type of interaction. Using a combination of genomic context and homology searches, new functional features can be predicted for 10% of M. genitalium genes. PMID:10958638

Estimation of gene induction enables a relevance-based ranking of gene sets.

PubMed

Bartholomé, Kilian; Kreutz, Clemens; Timmer, Jens

2009-07-01

In order to handle and interpret the vast amounts of data produced by microarray experiments, the analysis of sets of genes with a common biological functionality has been shown to be advantageous compared to single gene analyses. Some statistical methods have been proposed to analyse the differential gene expression of gene sets in microarray experiments. However, most of these methods either require threshhold values to be chosen for the analysis, or they need some reference set for the determination of significance. We present a method that estimates the number of differentially expressed genes in a gene set without requiring a threshold value for significance of genes. The method is self-contained (i.e., it does not require a reference set for comparison). In contrast to other methods which are focused on significance, our approach emphasizes the relevance of the regulation of gene sets. The presented method measures the degree of regulation of a gene set and is a useful tool to compare the induction of different gene sets and place the results of microarray experiments into the biological context. An R-package is available.

Ensembl Genomes: an integrative resource for genome-scale data from non-vertebrate species.

PubMed

Kersey, Paul J; Staines, Daniel M; Lawson, Daniel; Kulesha, Eugene; Derwent, Paul; Humphrey, Jay C; Hughes, Daniel S T; Keenan, Stephan; Kerhornou, Arnaud; Koscielny, Gautier; Langridge, Nicholas; McDowall, Mark D; Megy, Karine; Maheswari, Uma; Nuhn, Michael; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Wilson, Derek; Yates, Andrew; Birney, Ewan

2012-01-01

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes.

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

PubMed

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

2017-08-23

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

Multidimensional quantitative analysis of mRNA expression within intact vertebrate embryos.

PubMed

Trivedi, Vikas; Choi, Harry M T; Fraser, Scott E; Pierce, Niles A

2018-01-08

For decades, in situ hybridization methods have been essential tools for studies of vertebrate development and disease, as they enable qualitative analyses of mRNA expression in an anatomical context. Quantitative mRNA analyses typically sacrifice the anatomy, relying on embryo microdissection, dissociation, cell sorting and/or homogenization. Here, we eliminate the trade-off between quantitation and anatomical context, using quantitative in situ hybridization chain reaction (qHCR) to perform accurate and precise relative quantitation of mRNA expression with subcellular resolution within whole-mount vertebrate embryos. Gene expression can be queried in two directions: read-out from anatomical space to expression space reveals co-expression relationships in selected regions of the specimen; conversely, read-in from multidimensional expression space to anatomical space reveals those anatomical locations in which selected gene co-expression relationships occur. As we demonstrate by examining gene circuits underlying somitogenesis, quantitative read-out and read-in analyses provide the strengths of flow cytometry expression analyses, but by preserving subcellular anatomical context, they enable bi-directional queries that open a new era for in situ hybridization. © 2018. Published by The Company of Biologists Ltd.

Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins.

PubMed

Waks, Zeev; Weissbrod, Omer; Carmeli, Boaz; Norel, Raquel; Utro, Filippo; Goldschmidt, Yaara

2016-12-23

Compiling a comprehensive list of cancer driver genes is imperative for oncology diagnostics and drug development. While driver genes are typically discovered by analysis of tumor genomes, infrequently mutated driver genes often evade detection due to limited sample sizes. Here, we address sample size limitations by integrating tumor genomics data with a wide spectrum of gene-specific properties to search for rare drivers, functionally classify them, and detect features characteristic of driver genes. We show that our approach, CAnceR geNe similarity-based Annotator and Finder (CARNAF), enables detection of potentially novel drivers that eluded over a dozen pan-cancer/multi-tumor type studies. In particular, feature analysis reveals a highly concentrated pool of known and putative tumor suppressors among the <1% of genes that encode very large, chromatin-regulating proteins. Thus, our study highlights the need for deeper characterization of very large, epigenetic regulators in the context of cancer causality.

Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks.

PubMed

Yeung, Enoch; Dy, Aaron J; Martin, Kyle B; Ng, Andrew H; Del Vecchio, Domitilla; Beck, James L; Collins, James J; Murray, Richard M

2017-07-26

Synthetic gene expression is highly sensitive to intragenic compositional context (promoter structure, spacing regions between promoter and coding sequences, and ribosome binding sites). However, much less is known about the effects of intergenic compositional context (spatial arrangement and orientation of entire genes on DNA) on expression levels in synthetic gene networks. We compare expression of induced genes arranged in convergent, divergent, or tandem orientations. Induction of convergent genes yielded up to 400% higher expression, greater ultrasensitivity, and dynamic range than divergent- or tandem-oriented genes. Orientation affects gene expression whether one or both genes are induced. We postulate that transcriptional interference in divergent and tandem genes, mediated by supercoiling, can explain differences in expression and validate this hypothesis through modeling and in vitro supercoiling relaxation experiments. Treatment with gyrase abrogated intergenic context effects, bringing expression levels within 30% of each other. We rebuilt the toggle switch with convergent genes, taking advantage of supercoiling effects to improve threshold detection and switch stability. Copyright © 2017 Elsevier Inc. All rights reserved.

Social context affects behavior, preoptic area gene expression, and response to D2 receptor manipulation during territorial defense in a cichlid fish.

PubMed

Weitekamp, C A; Nguyen, J; Hofmann, H A

2017-07-01

Social context often has profound effects on behavior, yet the neural and molecular mechanisms which mediate flexible behavioral responses to different social environments are not well understood. We used the African cichlid fish, Astatotilapia burtoni, to examine aggressive defense behavior across three social contexts representing different motivational states: a reproductive opportunity, a familiar male and a neutral context. To elucidate how differences in behavior across contexts may be mediated by neural gene expression, we examined gene expression in the preoptic area, a brain region known to control male aggressive and sexual behavior. We show that social context has broad effects on preoptic gene expression. Specifically, we found that the expression of genes encoding nonapeptides and sex steroid receptors are upregulated in the familiar male context. Furthermore, circulating levels of testosterone and cortisol varied markedly depending on social context. We also manipulated the D2 receptor (D2R) in each social context, given that it has been implicated in mediating context-dependent behavior. We found that a D2R agonist reduced intruder-directed aggression in the reproductive opportunity and familiar male contexts, while a D2R antagonist inhibited intruder-directed aggression in the reproductive opportunity context and increased aggression in the neutral context. Our results demonstrate a critical role for preoptic gene expression, as well as circulating steroid hormone levels, in encoding information from the social environment and in shaping adaptive behavior. In addition, they provide further evidence for a role of D2R in context-dependent behavior. © 2017 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Antibiotic Resistance Gene Detection in the Microbiome Context.

PubMed

Do, Thi Thuy; Tamames, Javier; Stedtfeld, Robert D; Guo, Xueping; Murphy, Sinead; Tiedje, James M; Walsh, Fiona

2018-06-01

Within the past decade, microbiologists have moved from detecting single antibiotic resistance genes (ARGs) to detecting all known resistance genes within a sample due to advances in next generation sequencing. This has provided a wealth of data on the variation and relative abundances of ARGs present in a total bacterial population. However, to use these data in terms of therapy or risk to patients, they must be analyzed in the context of the background microbiome. Using a quantitative PCR ARG chip and 16S rRNA amplicon sequencing, we have sought to identify the ARGs and bacteria present in a fecal sample of a healthy adult using genomic tools. Of the 42 ARGs detected, 12 fitted into the ResCon1 category of ARGs: cfxA, cphA, bacA, sul3, aadE, bla TEM , aphA1, aphA3, aph(2')-Id, aacA/aphd, catA1, and vanC. Therefore, we describe these 12 genes as the core resistome of this person's fecal microbiome and the remaining 30 ARGs as descriptors of the microbial population within the fecal microbiome. The dominant phyla and genera agree with those previously detected in the greatest abundances in fecal samples of healthy humans. The majority of the ARGs detected were associated with the presence of specific bacterial taxa, which were confirmed using microbiome analysis. We acknowledge the limitations of the data in the context of the limited sample set. However, the principle of combining qPCR and microbiome analysis was shown to be helpful to identify the association of the ARGs with specific taxa.

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

PubMed Central

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

2016-01-01

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

Divergent cytosine DNA methylation patterns in single-cell, soybean root hairs.

PubMed

Hossain, Md Shakhawat; Kawakatsu, Taiji; Kim, Kyung Do; Zhang, Ning; Nguyen, Cuong T; Khan, Saad M; Batek, Josef M; Joshi, Trupti; Schmutz, Jeremy; Grimwood, Jane; Schmitz, Robert J; Xu, Dong; Jackson, Scott A; Ecker, Joseph R; Stacey, Gary

2017-04-01

Chromatin modifications, such as cytosine methylation of DNA, play a significant role in mediating gene expression in plants, which affects growth, development, and cell differentiation. As root hairs are single-cell extensions of the root epidermis and the primary organs for water uptake and nutrients, we sought to use root hairs as a single-cell model system to measure the impact of environmental stress. We measured changes in cytosine DNA methylation in single-cell root hairs as compared with multicellular stripped roots, as well as in response to heat stress. Differentially methylated regions (DMRs) in each methylation context showed very distinct methylation patterns between cell types and in response to heat stress. Intriguingly, at normal temperature, root hairs were more hypermethylated than were stripped roots. However, in response to heat stress, both root hairs and stripped roots showed hypomethylation in each context, especially in the CHH context. Moreover, expression analysis of mRNA from similar tissues and treatments identified some associations between DMRs, genes and transposons. Taken together, the data indicate that changes in DNA methylation are directly or indirectly associated with expression of genes and transposons within the context of either specific tissues/cells or stress (heat). © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Gene context conservation of a higher order than operons.

PubMed

Lathe, W C; Snel, B; Bork, P

2000-10-01

Operons, co-transcribed and co-regulated contiguous sets of genes, are poorly conserved over short periods of evolutionary time. The gene order, gene content and regulatory mechanisms of operons can be very different, even in closely related species. Here, we present several lines of evidence which suggest that, although an operon and its individual genes and regulatory structures are rearranged when comparing the genomes of different species, this rearrangement is a conservative process. Genomic rearrangements invariably maintain individual genes in very specific functional and regulatory contexts. We call this conserved context an uber-operon.

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

PubMed Central

Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; Taylor, Ronald C.; Weisenhorn, Pamela; Olson, Robert D.; Stevens, Rick L.; Rocha, Miguel; Rocha, Isabel; Best, Aaron A.; DeJongh, Matthew; Tintle, Nathan L.; Parrello, Bruce; Overbeek, Ross; Henry, Christopher S.

2016-01-01

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, Atomic Regulons (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here, we describe an approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: Hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB, showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness (CLR) analysis, finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms, we computed ARs for Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus, each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance, but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms, comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain. PMID:27933038

NEAT: an efficient network enrichment analysis test.

PubMed

Signorelli, Mirko; Vinciotti, Veronica; Wit, Ernst C

2016-09-05

Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be computationally slow and are based on normality assumptions. We propose NEAT, a test for network enrichment analysis. The test is based on the hypergeometric distribution, which naturally arises as the null distribution in this context. NEAT can be applied not only to undirected, but to directed and partially directed networks as well. Our simulations indicate that NEAT is considerably faster than alternative resampling-based methods, and that its capacity to detect enrichments is at least as good as the one of alternative tests. We discuss applications of NEAT to network analyses in yeast by testing for enrichment of the Environmental Stress Response target gene set with GO Slim and KEGG functional gene sets, and also by inspecting associations between functional sets themselves. NEAT is a flexible and efficient test for network enrichment analysis that aims to overcome some limitations of existing resampling-based tests. The method is implemented in the R package neat, which can be freely downloaded from CRAN ( https://cran.r-project.org/package=neat ).

Network Analysis of Rodent Transcriptomes in Spaceflight

NASA Technical Reports Server (NTRS)

Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

2017-01-01

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

oPOSSUM: integrated tools for analysis of regulatory motif over-representation

PubMed Central

Ho Sui, Shannan J.; Fulton, Debra L.; Arenillas, David J.; Kwon, Andrew T.; Wasserman, Wyeth W.

2007-01-01

The identification of over-represented transcription factor binding sites from sets of co-expressed genes provides insights into the mechanisms of regulation for diverse biological contexts. oPOSSUM, an internet-based system for such studies of regulation, has been improved and expanded in this new release. New features include a worm-specific version for investigating binding sites conserved between Caenorhabditis elegans and C. briggsae, as well as a yeast-specific version for the analysis of co-expressed sets of Saccharomyces cerevisiae genes. The human and mouse applications feature improvements in ortholog mapping, sequence alignments and the delineation of multiple alternative promoters. oPOSSUM2, introduced for the analysis of over-represented combinations of motifs in human and mouse genes, has been integrated with the original oPOSSUM system. Analysis using user-defined background gene sets is now supported. The transcription factor binding site models have been updated to include new profiles from the JASPAR database. oPOSSUM is available at http://www.cisreg.ca/oPOSSUM/ PMID:17576675

Inducible repression of multiple expansin genes leads to growth suppression during leaf development.

PubMed

Goh, Hoe-Han; Sloan, Jennifer; Dorca-Fornell, Carmen; Fleming, Andrew

2012-08-01

Expansins are cell wall proteins implicated in the control of plant growth via loosening of the extracellular matrix. They are encoded by a large gene family, and data linked to loss of single gene function to support a role of expansins in leaf growth remain limited. Here, we provide a quantitative growth analysis of transgenics containing an inducible artificial microRNA construct designed to down-regulate the expression of a number of expansin genes that an expression analysis indicated are expressed during the development of Arabidopsis (Arabidopsis thaliana) leaf 6. The results support the hypothesis that expansins are required for leaf growth and show that decreased expansin gene expression leads to a more marked repression of growth during the later stage of leaf development. In addition, a histological analysis of leaves in which expansin gene expression was suppressed indicates that, despite smaller leaves, mean cell size was increased. These data provide functional evidence for a role of expansins in leaf growth, indicate the importance of tissue/organ developmental context for the outcome of altered expansin gene expression, and highlight the separation of the outcome of expansin gene expression at the cellular and organ levels.

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

PubMed

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

2016-06-02

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

COGNAT: a web server for comparative analysis of genomic neighborhoods.

PubMed

Klimchuk, Olesya I; Konovalov, Kirill A; Perekhvatov, Vadim V; Skulachev, Konstantin V; Dibrova, Daria V; Mulkidjanian, Armen Y

2017-11-22

In prokaryotic genomes, functionally coupled genes can be organized in conserved gene clusters enabling their coordinated regulation. Such clusters could contain one or several operons, which are groups of co-transcribed genes. Those genes that evolved from a common ancestral gene by speciation (i.e. orthologs) are expected to have similar genomic neighborhoods in different organisms, whereas those copies of the gene that are responsible for dissimilar functions (i.e. paralogs) could be found in dissimilar genomic contexts. Comparative analysis of genomic neighborhoods facilitates the prediction of co-regulated genes and helps to discern different functions in large protein families. We intended, building on the attribution of gene sequences to the clusters of orthologous groups of proteins (COGs), to provide a method for visualization and comparative analysis of genomic neighborhoods of evolutionary related genes, as well as a respective web server. Here we introduce the COmparative Gene Neighborhoods Analysis Tool (COGNAT), a web server for comparative analysis of genomic neighborhoods. The tool is based on the COG database, as well as the Pfam protein families database. As an example, we show the utility of COGNAT in identifying a new type of membrane protein complex that is formed by paralog(s) of one of the membrane subunits of the NADH:quinone oxidoreductase of type 1 (COG1009) and a cytoplasmic protein of unknown function (COG3002). This article was reviewed by Drs. Igor Zhulin, Uri Gophna and Igor Rogozin.

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

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

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

C-State: an interactive web app for simultaneous multi-gene visualization and comparative epigenetic pattern search.

PubMed

Sowpati, Divya Tej; Srivastava, Surabhi; Dhawan, Jyotsna; Mishra, Rakesh K

2017-09-13

Comparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a challenge. We developed a fast and interactive web app, C-State (Chromatin-State), to query and plot chromatin landscapes across multiple loci and cell types. C-State has an interactive, JavaScript-based graphical user interface and runs locally in modern web browsers that are pre-installed on all computers, thus eliminating the need for cumbersome data transfer, pre-processing and prior programming knowledge. C-State is unique in its ability to extract and analyze multi-gene epigenetic information. It allows for powerful GUI-based pattern searching and visualization. We include a case study to demonstrate its potential for identifying user-defined epigenetic trends in context of gene expression profiles.

SBCDDB: Sleeping Beauty Cancer Driver Database for gene discovery in mouse models of human cancers

PubMed Central

Mann, Michael B

2018-01-01

Abstract Large-scale oncogenomic studies have identified few frequently mutated cancer drivers and hundreds of infrequently mutated drivers. Defining the biological context for rare driving events is fundamentally important to increasing our understanding of the druggable pathways in cancer. Sleeping Beauty (SB) insertional mutagenesis is a powerful gene discovery tool used to model human cancers in mice. Our lab and others have published a number of studies that identify cancer drivers from these models using various statistical and computational approaches. Here, we have integrated SB data from primary tumor models into an analysis and reporting framework, the Sleeping Beauty Cancer Driver DataBase (SBCDDB, http://sbcddb.moffitt.org), which identifies drivers in individual tumors or tumor populations. Unique to this effort, the SBCDDB utilizes a single, scalable, statistical analysis method that enables data to be grouped by different biological properties. This allows for SB drivers to be evaluated (and re-evaluated) under different contexts. The SBCDDB provides visual representations highlighting the spatial attributes of transposon mutagenesis and couples this functionality with analysis of gene sets, enabling users to interrogate relationships between drivers. The SBCDDB is a powerful resource for comparative oncogenomic analyses with human cancer genomics datasets for driver prioritization. PMID:29059366

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

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

Apolipoprotein C3 Gene Polymorphisms Are Not a Risk Factor for Developing Non-Alcoholic Fatty Liver Disease: A Meta-Analysis

PubMed Central

Zhang, Haiying; Chen, Lizhen; Xin, Yongning; Lou, Yuangui; Liu, Yang; Xuan, Shiying

2014-01-01

Context: Our objective was to evaluate the effect of gene polymorphisms of apolipoprotein C3 (APOC3) on the development of non-alcoholic fatty liver disease (NAFLD) in different populations. Evidence Acquisition: We performed a meta-analysis of all relevant studies published in the literature. A total of 115 clinical trials or reports were identified, but only seven trials met our inclusion criteria. A meta-analysis was performed according to the Cochrane Reviewers’ Handbook recommendations. Results: Five hospital-based and two population-based case-control studies were included in the final analysis. The overall frequency of APOC3 gene polymorphisms was 67.5% (1177/1745) in NAFLD and 68.8% (988/1437) in controls. The summary odds ratio for the association of gene polymorphisms of APOC3 and the risk of NAFLD was 1.03 (95% CI: 0.89-1.22),which was not statistically significant (P > 0.05). Conclusions: Our meta-analysis, while not ruling out possible publication bias, showed no association between gene polymorphisms of APOC3 and the risk of NAFLD development in different populations in the world. PMID:25477977

GCView: the genomic context viewer for protein homology searches

PubMed Central

Grin, Iwan; Linke, Dirk

2011-01-01

Genomic neighborhood can provide important insights into evolution and function of a protein or gene. When looking at operons, changes in operon structure and composition can only be revealed by looking at the operon as a whole. To facilitate the analysis of the genomic context of a query in multiple organisms we have developed Genomic Context Viewer (GCView). GCView accepts results from one or multiple protein homology searches such as BLASTp as input. For each hit, the neighboring protein-coding genes are extracted, the regions of homology are labeled for each input and the results are presented as a clear, interactive graphical output. It is also possible to add more searches to iteratively refine the output. GCView groups outputs by the hits for different proteins. This allows for easy comparison of different operon compositions and structures. The tool is embedded in the framework of the Bioinformatics Toolkit of the Max-Planck Institute for Developmental Biology (MPI Toolkit). Job results from the homology search tools inside the MPI Toolkit can be forwarded to GCView and results can be subsequently analyzed by sequence analysis tools. Results are stored online, allowing for later reinspection. GCView is freely available at http://toolkit.tuebingen.mpg.de/gcview. PMID:21609955

Sequence, distribution and chromosomal context of class I and class II pilin genes of Neisseria meningitidis identified in whole genome sequences

PubMed Central

2014-01-01

Background Neisseria meningitidis expresses type four pili (Tfp) which are important for colonisation and virulence. Tfp have been considered as one of the most variable structures on the bacterial surface due to high frequency gene conversion, resulting in amino acid sequence variation of the major pilin subunit (PilE). Meningococci express either a class I or a class II pilE gene and recent work has indicated that class II pilins do not undergo antigenic variation, as class II pilE genes encode conserved pilin subunits. The purpose of this work was to use whole genome sequences to further investigate the frequency and variability of the class II pilE genes in meningococcal isolate collections. Results We analysed over 600 publically available whole genome sequences of N. meningitidis isolates to determine the sequence and genomic organization of pilE. We confirmed that meningococcal strains belonging to a limited number of clonal complexes (ccs, namely cc1, cc5, cc8, cc11 and cc174) harbour a class II pilE gene which is conserved in terms of sequence and chromosomal context. We also identified pilS cassettes in all isolates with class II pilE, however, our analysis indicates that these do not serve as donor sequences for pilE/pilS recombination. Furthermore, our work reveals that the class II pilE locus lacks the DNA sequence motifs that enable (G4) or enhance (Sma/Cla repeat) pilin antigenic variation. Finally, through analysis of pilin genes in commensal Neisseria species we found that meningococcal class II pilE genes are closely related to pilE from Neisseria lactamica and Neisseria polysaccharea, suggesting horizontal transfer among these species. Conclusions Class II pilins can be defined by their amino acid sequence and genomic context and are present in meningococcal isolates which have persisted and spread globally. The absence of G4 and Sma/Cla sequences adjacent to the class II pilE genes is consistent with the lack of pilin subunit variation in these isolates, although horizontal transfer may generate class II pilin diversity. This study supports the suggestion that high frequency antigenic variation of pilin is not universal in pathogenic Neisseria. PMID:24690385

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

PubMed

Godard, Patrice; Page, Matthew

2016-12-07

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

Analytical workflow profiling gene expression in murine macrophages

PubMed Central

Nixon, Scott E.; González-Peña, Dianelys; Lawson, Marcus A.; McCusker, Robert H.; Hernandez, Alvaro G.; O’Connor, Jason C.; Dantzer, Robert; Kelley, Keith W.

2015-01-01

Comprehensive and simultaneous analysis of all genes in a biological sample is a capability of RNA-Seq technology. Analysis of the entire transcriptome benefits from summarization of genes at the functional level. As a cellular response of interest not previously explored with RNA-Seq, peritoneal macrophages from mice under two conditions (control and immunologically challenged) were analyzed for gene expression differences. Quantification of individual transcripts modeled RNA-Seq read distribution and uncertainty (using a Beta Negative Binomial distribution), then tested for differential transcript expression (False Discovery Rate-adjusted p-value < 0.05). Enrichment of functional categories utilized the list of differentially expressed genes. A total of 2079 differentially expressed transcripts representing 1884 genes were detected. Enrichment of 92 categories from Gene Ontology Biological Processes and Molecular Functions, and KEGG pathways were grouped into 6 clusters. Clusters included defense and inflammatory response (Enrichment Score = 11.24) and ribosomal activity (Enrichment Score = 17.89). Our work provides a context to the fine detail of individual gene expression differences in murine peritoneal macrophages during immunological challenge with high throughput RNA-Seq. PMID:25708305

Evolutionary genetic analyses of MEF2C gene: implications for learning and memory in Homo sapiens.

PubMed

Kalmady, Sunil V; Venkatasubramanian, Ganesan; Arasappa, Rashmi; Rao, Naren P

2013-02-01

MEF2C facilitates context-dependent fear conditioning (CFC) which is a salient aspect of hippocampus-dependent learning and memory. CFC might have played a crucial role in human evolution because of its advantageous influence on survival of species. In this study, we analyzed 23 orthologous mammalian gene sequences of MEF2C gene to examine the evidence for positive selection on this gene in Homo sapiens using Phylogenetic Analysis by Maximum Likelihood (PAML) and HyPhy software. Both PAML Bayes Empirical Bayes (BEB) and HyPhy Fixed Effects Likelihood (FEL) analyses supported significant positive selection on 4 codon sites in H. sapiens. Also, haplotter analysis revealed significant ongoing positive selection on this gene in Central European population. The study findings suggest that adaptive selective pressure on this gene might have influenced human evolution. Further research on this gene might unravel the potential role of this gene in learning and memory as well as its pathogenetic effect in certain hippocampal disorders with evolutionary basis like schizophrenia. Copyright © 2012 Elsevier B.V. All rights reserved.

Genomic response to Wnt signalling is highly context-dependent - Evidence from DNA microarray and chromatin immunoprecipitation screens of Wnt/TCF targets

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

Railo, Antti; Pajunen, Antti; Itaeranta, Petri

2009-10-01

Wnt proteins are important regulators of embryonic development, and dysregulated Wnt signalling is involved in the oncogenesis of several human cancers. Our knowledge of the downstream target genes is limited, however. We used a chromatin immunoprecipitation-based assay to isolate and characterize the actual gene segments through which Wnt-activatable transcription factors, TCFs, regulate transcription and an Affymetrix microarray analysis to study the global transcriptional response to the Wnt3a ligand. The anti-{beta}-catenin immunoprecipitation of DNA-protein complexes from mouse NIH3T3 fibroblasts expressing a fusion protein of {beta}-catenin and TCF7 resulted in the identification of 92 genes as putative TCF targets. GeneChip assays ofmore » gene expression performed on NIH3T3 cells and the rat pheochromocytoma cell line PC12 revealed 355 genes in NIH3T3 and 129 genes in the PC12 cells with marked changes in expression after Wnt3a stimulus. Only 2 Wnt-regulated genes were shared by both cell lines. Surprisingly, Disabled-2 was the only gene identified by the chromatin immunoprecipitation approach that displayed a marked change in expression in the GeneChip assay. Taken together, our approaches give an insight into the complex context-dependent nature of Wnt pathway transcriptional responses and identify Disabled-2 as a potential new direct target for Wnt signalling.« less

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology

PubMed Central

Roncaglia, Paola; Howe, Douglas G.; Laulederkind, Stanley J.F.; Khodiyar, Varsha K.; Berardini, Tanya Z.; Tweedie, Susan; Foulger, Rebecca E.; Osumi-Sutherland, David; Campbell, Nancy H.; Huntley, Rachael P.; Talmud, Philippa J.; Blake, Judith A.; Breckenridge, Ross; Riley, Paul R.; Lambiase, Pier D.; Elliott, Perry M.; Clapp, Lucie; Tinker, Andrew; Hill, David P.

2018-01-01

Background: A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. Methods and Results: In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. Conclusions: We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. PMID:29440116

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

PubMed

Lovering, Ruth C; Roncaglia, Paola; Howe, Douglas G; Laulederkind, Stanley J F; Khodiyar, Varsha K; Berardini, Tanya Z; Tweedie, Susan; Foulger, Rebecca E; Osumi-Sutherland, David; Campbell, Nancy H; Huntley, Rachael P; Talmud, Philippa J; Blake, Judith A; Breckenridge, Ross; Riley, Paul R; Lambiase, Pier D; Elliott, Perry M; Clapp, Lucie; Tinker, Andrew; Hill, David P

2018-02-01

A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. © 2018 The Authors.

Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways

PubMed Central

Kaushik, Abhinav; Ali, Shakir; Gupta, Dinesh

2017-01-01

Gene connection rewiring is an essential feature of gene network dynamics. Apart from its normal functional role, it may also lead to dysregulated functional states by disturbing pathway homeostasis. Very few computational tools measure rewiring within gene co-expression and its corresponding regulatory networks in order to identify and prioritize altered pathways which may or may not be differentially regulated. We have developed Altered Pathway Analyzer (APA), a microarray dataset analysis tool for identification and prioritization of altered pathways, including those which are differentially regulated by TFs, by quantifying rewired sub-network topology. Moreover, APA also helps in re-prioritization of APA shortlisted altered pathways enriched with context-specific genes. We performed APA analysis of simulated datasets and p53 status NCI-60 cell line microarray data to demonstrate potential of APA for identification of several case-specific altered pathways. APA analysis reveals several altered pathways not detected by other tools evaluated by us. APA analysis of unrelated prostate cancer datasets identifies sample-specific as well as conserved altered biological processes, mainly associated with lipid metabolism, cellular differentiation and proliferation. APA is designed as a cross platform tool which may be transparently customized to perform pathway analysis in different gene expression datasets. APA is freely available at http://bioinfo.icgeb.res.in/APA. PMID:28084397

Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

PubMed Central

Weniger, Markus; Engelmann, Julia C; Schultz, Jörg

2007-01-01

Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125

Comparative brain transcriptomic analyses of scouting across distinct behavioural and ecological contexts in honeybees

PubMed Central

Liang, Zhengzheng S.; Mattila, Heather R.; Rodriguez-Zas, Sandra L.; Southey, Bruce R.; Seeley, Thomas D.; Robinson, Gene E.

2014-01-01

Individual differences in behaviour are often consistent across time and contexts, but it is not clear whether such consistency is reflected at the molecular level. We explored this issue by studying scouting in honeybees in two different behavioural and ecological contexts: finding new sources of floral food resources and finding a new nest site. Brain gene expression profiles in food-source and nest-site scouts showed a significant overlap, despite large expression differences associated with the two different contexts. Class prediction and ‘leave-one-out’ cross-validation analyses revealed that a bee's role as a scout in either context could be predicted with 92.5% success using 89 genes at minimum. We also found that genes related to four neurotransmitter systems were part of a shared brain molecular signature in both types of scouts, and the two types of scouts were more similar for genes related to glutamate and GABA than catecholamine or acetylcholine signalling. These results indicate that consistent behavioural tendencies across different ecological contexts involve a mixture of similarities and differences in brain gene expression. PMID:25355476

Characterizing genes with distinct methylation patterns in the context of protein-protein interaction network: application to human brain tissues.

PubMed

Li, Yongsheng; Xu, Juan; Chen, Hong; Zhao, Zheng; Li, Shengli; Bai, Jing; Wu, Aiwei; Jiang, Chunjie; Wang, Yuan; Su, Bin; Li, Xia

2013-01-01

DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery. In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome. We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms.

Characterizing Genes with Distinct Methylation Patterns in the Context of Protein-Protein Interaction Network: Application to Human Brain Tissues

PubMed Central

Zhao, Zheng; Li, Shengli; Bai, Jing; Wu, Aiwei; Jiang, Chunjie; Wang, Yuan; Su, Bin; Li, Xia

2013-01-01

Background DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery. Results In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome. Conclusions We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms. PMID:23776563

Codon-Resolution Analysis Reveals a Direct and Context-Dependent Impact of Individual Synonymous Mutations on mRNA Level

PubMed Central

Chen, Siyu; Li, Ke; Cao, Wenqing; Wang, Jia; Zhao, Tong; Huan, Qing; Yang, Yu-Fei; Wu, Shaohuan; Qian, Wenfeng

2017-01-01

Abstract Codon usage bias (CUB) refers to the observation that synonymous codons are not used equally frequently in a genome. CUB is stronger in more highly expressed genes, a phenomenon commonly explained by stronger natural selection on translational accuracy and/or efficiency among these genes. Nevertheless, this phenomenon could also occur if CUB regulates gene expression at the mRNA level, a hypothesis that has not been tested until recently. Here, we attempt to quantify the impact of synonymous mutations on mRNA level in yeast using 3,556 synonymous variants of a heterologous gene encoding green fluorescent protein (GFP) and 523 synonymous variants of an endogenous gene TDH3. We found that mRNA level was positively correlated with CUB among these synonymous variants, demonstrating a direct role of CUB in regulating transcript concentration, likely via regulating mRNA degradation rate, as our additional experiments suggested. More importantly, we quantified the effects of individual synonymous mutations on mRNA level and found them dependent on 1) CUB and 2) mRNA secondary structure, both in proximal sequence contexts. Our study reveals the pleiotropic effects of synonymous codon usage and provides an additional explanation for the well-known correlation between CUB and gene expression level. PMID:28961875

Phanerochaete chrysosporium genomics

Treesearch

Luis F. Larrondo; Rafael Vicuna; Dan Cullen

2005-01-01

A high quality draft genome sequence has been generated for the lignocellulose-degrading basidiomycete Phanerochaete chrysosporium (Martinez et al. 2004). Analysis of the genome in the context of previously established genetics and physiology is presented. Transposable elements and their potential relationship to genes involved in lignin degradation are systematically...

Commentary: Gene-Environment Interplay in the Context of Genetics, Epigenetics, and Gene Expression.

ERIC Educational Resources Information Center

Kramer, Douglas A.

2005-01-01

Objective: To comment on the article in this issue of the Journal by Professor Michael Rutter, "Environmentally Mediated Risks for Psychopathology: Research Strategies and Findings," in the context of current research findings on gene-environment interaction, epigenetics, and gene expression. Method: Animal and human studies are reviewed that…

Network Analysis of Human Genes Influencing Susceptibility to Mycobacterial Infections

PubMed Central

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

2016-01-01

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

Expression of venom gene homologs in diverse python tissues suggests a new model for the evolution of snake venom.

PubMed

Reyes-Velasco, Jacobo; Card, Daren C; Andrew, Audra L; Shaney, Kyle J; Adams, Richard H; Schield, Drew R; Casewell, Nicholas R; Mackessy, Stephen P; Castoe, Todd A

2015-01-01

Snake venom gene evolution has been studied intensively over the past several decades, yet most previous studies have lacked the context of complete snake genomes and the full context of gene expression across diverse snake tissues. We took a novel approach to studying snake venom evolution by leveraging the complete genome of the Burmese python, including information from tissue-specific patterns of gene expression. We identified the orthologs of snake venom genes in the python genome, and conducted detailed analysis of gene expression of these venom homologs to identify patterns that differ between snake venom gene families and all other genes. We found that venom gene homologs in the python are expressed in many different tissues outside of oral glands, which illustrates the pitfalls of using transcriptomic data alone to define "venom toxins." We hypothesize that the python may represent an ancestral state prior to major venom development, which is supported by our finding that the expansion of venom gene families is largely restricted to highly venomous caenophidian snakes. Therefore, the python provides insight into biases in which genes were recruited for snake venom systems. Python venom homologs are generally expressed at lower levels, have higher variance among tissues, and are expressed in fewer organs compared with all other python genes. We propose a model for the evolution of snake venoms in which venom genes are recruited preferentially from genes with particular expression profile characteristics, which facilitate a nearly neutral transition toward specialized venom system expression. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Advances and perspectives on the use of CRISPR/Cas9 systems in plant genomics research

DOE PAGES

Liu, Degao; Hu, Rongbin; Palla, Kaitlin J.; ...

2016-02-18

Genome editing with site-specific nucleases has become a powerful tool for functional characterization of plant genes and genetic improvement of agricultural crops. Among the various site-specific nuclease-based technologies available for genome editing, the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) systems have shown the greatest potential for rapid and efficient editing of genomes in plant species. Here, this article reviews the current status of application of CRISPR/Cas9 to plant genomics research, with a focus on loss-of-function and gain-of-function analysis of individual genes in the context of perennial plants and the potential application of CRISPR/Cas9 to perturbation ofmore » gene expression, as well as identification and analysis of gene modules as part of an accelerated domestication and synthetic biology effort.« less

Advances and perspectives on the use of CRISPR/Cas9 systems in plant genomics research

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

Liu, Degao; Hu, Rongbin; Palla, Kaitlin J.

Genome editing with site-specific nucleases has become a powerful tool for functional characterization of plant genes and genetic improvement of agricultural crops. Among the various site-specific nuclease-based technologies available for genome editing, the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) systems have shown the greatest potential for rapid and efficient editing of genomes in plant species. Here, this article reviews the current status of application of CRISPR/Cas9 to plant genomics research, with a focus on loss-of-function and gain-of-function analysis of individual genes in the context of perennial plants and the potential application of CRISPR/Cas9 to perturbation ofmore » gene expression, as well as identification and analysis of gene modules as part of an accelerated domestication and synthetic biology effort.« less

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.

PubMed

Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees

2018-06-07

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

Descent graphs in pedigree analysis: applications to haplotyping, location scores, and marker-sharing statistics.

PubMed Central

Sobel, E.; Lange, K.

1996-01-01

The introduction of stochastic methods in pedigree analysis has enabled geneticists to tackle computations intractable by standard deterministic methods. Until now these stochastic techniques have worked by running a Markov chain on the set of genetic descent states of a pedigree. Each descent state specifies the paths of gene flow in the pedigree and the founder alleles dropped down each path. The current paper follows up on a suggestion by Elizabeth Thompson that genetic descent graphs offer a more appropriate space for executing a Markov chain. A descent graph specifies the paths of gene flow but not the particular founder alleles traveling down the paths. This paper explores algorithms for implementing Thompson's suggestion for codominant markers in the context of automatic haplotyping, estimating location scores, and computing gene-clustering statistics for robust linkage analysis. Realistic numerical examples demonstrate the feasibility of the algorithms. PMID:8651310

Encyclopedia of bacterial gene circuits whose presence or absence correlate with pathogenicity--a large-scale system analysis of decoded bacterial genomes.

PubMed

Shestov, Maksim; Ontañón, Santiago; Tozeren, Aydin

2015-10-13

Bacterial infections comprise a global health challenge as the incidences of antibiotic resistance increase. Pathogenic potential of bacteria has been shown to be context dependent, varying in response to environment and even within the strains of the same genus. We used the KEGG repository and extensive literature searches to identify among the 2527 bacterial genomes in the literature those implicated as pathogenic to the host, including those which show pathogenicity in a context dependent manner. Using data on the gene contents of these genomes, we identified sets of genes highly abundant in pathogenic but relatively absent in commensal strains and vice versa. In addition, we carried out genome comparison within a genus for the seventeen largest genera in our genome collection. We projected the resultant lists of ortholog genes onto KEGG bacterial pathways to identify clusters and circuits, which can be linked to either pathogenicity or synergy. Gene circuits relatively abundant in nonpathogenic bacteria often mediated biosynthesis of antibiotics. Other synergy-linked circuits reduced drug-induced toxicity. Pathogen-abundant gene circuits included modules in one-carbon folate, two-component system, type-3 secretion system, and peptidoglycan biosynthesis. Antibiotics-resistant bacterial strains possessed genes modulating phagocytosis, vesicle trafficking, cytoskeletal reorganization, and regulation of the inflammatory response. Our study also identified bacterial genera containing a circuit, elements of which were previously linked to Alzheimer's disease. Present study produces for the first time, a signature, in the form of a robust list of gene circuitry whose presence or absence could potentially define the pathogenicity of a microbiome. Extensive literature search substantiated a bulk majority of the commensal and pathogenic circuitry in our predicted list. Scanning microbiome libraries for these circuitry motifs will provide further insights into the complex and context dependent pathogenicity of bacteria.

DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis.

PubMed

Yu, Guangchuang; Wang, Li-Gen; Yan, Guang-Rong; He, Qing-Yu

2015-02-15

Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computations among DO terms and genes which allows biologists to explore the similarities of diseases and of gene functions in disease perspective. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented to support discovering disease associations of high-throughput biological data. This allows biologists to verify disease relevance in a biological experiment and identify unexpected disease associations. Comparison among gene clusters is also supported. DOSE is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (http://www.bioconductor.org/packages/release/bioc/html/DOSE.html). Supplementary data are available at Bioinformatics online. gcyu@connect.hku.hk or tqyhe@jnu.edu.cn. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

PubMed Central

Reif, David M.; Israel, Mark A.; Moore, Jason H.

2007-01-01

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org. PMID:19390666

WGCNA: an R package for weighted correlation network analysis.

PubMed

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

WGCNA: an R package for weighted correlation network analysis

PubMed Central

Langfelder, Peter; Horvath, Steve

2008-01-01

Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at . PMID:19114008

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.

Metabolomic Studies in Drosophila.

PubMed

Cox, James E; Thummel, Carl S; Tennessen, Jason M

2017-07-01

Metabolomic analysis provides a powerful new tool for studies of Drosophila physiology. This approach allows investigators to detect thousands of chemical compounds in a single sample, representing the combined contributions of gene expression, enzyme activity, and environmental context. Metabolomics has been used for a wide range of studies in Drosophila , often providing new insights into gene function and metabolic state that could not be obtained using any other approach. In this review, we survey the uses of metabolomic analysis since its entry into the field. We also cover the major methods used for metabolomic studies in Drosophila and highlight new directions for future research. Copyright © 2017 by the Genetics Society of America.

Methods for Genome-Wide Analysis of Gene Expression Changes in Polyploids

PubMed Central

Wang, Jianlin; Lee, Jinsuk J.; Tian, Lu; Lee, Hyeon-Se; Chen, Meng; Rao, Sheetal; Wei, Edward N.; Doerge, R. W.; Comai, Luca; Jeffrey Chen, Z.

2007-01-01

Polyploidy is an evolutionary innovation, providing extra sets of genetic material for phenotypic variation and adaptation. It is predicted that changes of gene expression by genetic and epigenetic mechanisms are responsible for novel variation in nascent and established polyploids (Liu and Wendel, 2002; Osborn et al., 2003; Pikaard, 2001). Studying gene expression changes in allopolyploids is more complicated than in autopolyploids, because allopolyploids contain more than two sets of genomes originating from divergent, but related, species. Here we describe two methods that are applicable to the genome-wide analysis of gene expression differences resulting from genome duplication in autopolyploids or interactions between homoeologous genomes in allopolyploids. First, we describe an amplified fragment length polymorphism (AFLP)–complementary DNA (cDNA) display method that allows the discrimination of homoeologous loci based on restriction polymorphisms between the progenitors. Second, we describe microarray analyses that can be used to compare gene expression differences between the allopolyploids and respective progenitors using appropriate experimental design and statistical analysis. We demonstrate the utility of these two complementary methods and discuss the pros and cons of using the methods to analyze gene expression changes in autopolyploids and allopolyploids. Furthermore, we describe these methods in general terms to be of wider applicability for comparative gene expression in a variety of evolutionary, genetic, biological, and physiological contexts. PMID:15865985

Identification of Reference Genes for Real-Time Quantitative PCR Experiments in the Liverwort Marchantia polymorpha

PubMed Central

Dolan, Liam; Langdale, Jane A.

2015-01-01

Real-time quantitative polymerase chain reaction (qPCR) has become widely used as a method to compare gene transcript levels across different conditions. However, selection of suitable reference genes to normalize qPCR data is required for accurate transcript level analysis. Recently, Marchantia polymorpha has been adopted as a model for the study of liverwort development and land plant evolution. Identification of appropriate reference genes has therefore become a necessity for gene expression studies. In this study, transcript levels of eleven candidate reference genes have been analyzed across a range of biological contexts that encompass abiotic stress, hormone treatment and different developmental stages. The consistency of transcript levels was assessed using both geNorm and NormFinder algorithms, and a consensus ranking of the different candidate genes was then obtained. MpAPT and MpACT showed relatively constant transcript levels across all conditions tested whereas the transcript levels of other candidate genes were clearly influenced by experimental conditions. By analyzing transcript levels of phosphate and nitrate starvation reporter genes, we confirmed that MpAPT and MpACT are suitable reference genes in M. polymorpha and also demonstrated that normalization with an inappropriate gene can lead to erroneous analysis of qPCR data. PMID:25798897

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

DOE PAGES

Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; ...

2016-11-24

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. A multitude of technologies, abstractions, and interpretive frameworks have emerged to answer the challenges presented by genome function and regulatory network inference. Here, we propose a new approach for producing biologically meaningful clusters of coexpressed genes, called Atomic Regulons (ARs), based on expression data, gene context, and functional relationships. We demonstrate this new approach by computing ARs for Escherichia coli, which we compare with the coexpressed gene clusters predicted by two prevalent existing methods: hierarchical clustering and k-meansmore » clustering. We test the consistency of ARs predicted by all methods against expected interactions predicted by the Context Likelihood of Relatedness (CLR) mutual information based method, finding that the ARs produced by our approach show better agreement with CLR interactions. We then apply our method to compute ARs for four other genomes: Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus. We compare the AR clusters from all genomes to study the similarity of coexpression among a phylogenetically diverse set of species, identifying subsystems that show remarkable similarity over wide phylogenetic distances. We also study the sensitivity of our method for computing ARs to the expression data used in the computation, showing that our new approach requires less data than competing approaches to converge to a near final configuration of ARs. We go on to use our sensitivity analysis to identify the specific experiments that lead most rapidly to the final set of ARs for E. coli. As a result, this analysis produces insights into improving the design of gene expression experiments.« less

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

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

Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. A multitude of technologies, abstractions, and interpretive frameworks have emerged to answer the challenges presented by genome function and regulatory network inference. Here, we propose a new approach for producing biologically meaningful clusters of coexpressed genes, called Atomic Regulons (ARs), based on expression data, gene context, and functional relationships. We demonstrate this new approach by computing ARs for Escherichia coli, which we compare with the coexpressed gene clusters predicted by two prevalent existing methods: hierarchical clustering and k-meansmore » clustering. We test the consistency of ARs predicted by all methods against expected interactions predicted by the Context Likelihood of Relatedness (CLR) mutual information based method, finding that the ARs produced by our approach show better agreement with CLR interactions. We then apply our method to compute ARs for four other genomes: Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus. We compare the AR clusters from all genomes to study the similarity of coexpression among a phylogenetically diverse set of species, identifying subsystems that show remarkable similarity over wide phylogenetic distances. We also study the sensitivity of our method for computing ARs to the expression data used in the computation, showing that our new approach requires less data than competing approaches to converge to a near final configuration of ARs. We go on to use our sensitivity analysis to identify the specific experiments that lead most rapidly to the final set of ARs for E. coli. As a result, this analysis produces insights into improving the design of gene expression experiments.« less

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

PubMed Central

He, Hao; Zhang, Lei; Li, Jian; Wang, Yu-Ping; Zhang, Ji-Gang; Shen, Jie; Guo, Yan-Fang

2014-01-01

Context: To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk. Methods: First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa. Results: In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value <.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation. Conclusion: We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis. PMID:25119315

Gene by Social-Context Interactions for Number of Sexual Partners Among White Male Youths: Genetics-informed Sociology

PubMed Central

Guo, Guang; Tong, Yuying; Cai, Tianji

2010-01-01

In this study, we set out to investigate whether introducing molecular genetic measures into an analysis of sexual partner variety will yield novel sociological insights. The data source is the white male DNA sample in the National Longitudinal Study of Adolescent Health. Our empirical analysis has produced a robust protective effect of the 9R/9R genotype relative to the Any10R genotype in the dopamine transporter gene (DAT1). The gene-environment interaction analysis demonstrates that the protective effect of 9R/9R tends to be lost in schools in which higher proportions of students start having sex early or among those with relatively low levels of cognitive ability. Our genetics-informed sociological analysis suggests that the “one size” of a single social theory may not fit all. Explaining a human trait or behavior may require a theory that accommodates the complex interplay between social contextual and individual influences and genetic predispositions. PMID:19569400

Seeking unique and common biological themes in multiple gene lists or datasets: pathway pattern extraction pipeline for pathway-level comparative analysis.

PubMed

Yi, Ming; Mudunuri, Uma; Che, Anney; Stephens, Robert M

2009-06-29

One of the challenges in the analysis of microarray data is to integrate and compare the selected (e.g., differential) gene lists from multiple experiments for common or unique underlying biological themes. A common way to approach this problem is to extract common genes from these gene lists and then subject these genes to enrichment analysis to reveal the underlying biology. However, the capacity of this approach is largely restricted by the limited number of common genes shared by datasets from multiple experiments, which could be caused by the complexity of the biological system itself. We now introduce a new Pathway Pattern Extraction Pipeline (PPEP), which extends the existing WPS application by providing a new pathway-level comparative analysis scheme. To facilitate comparing and correlating results from different studies and sources, PPEP contains new interfaces that allow evaluation of the pathway-level enrichment patterns across multiple gene lists. As an exploratory tool, this analysis pipeline may help reveal the underlying biological themes at both the pathway and gene levels. The analysis scheme provided by PPEP begins with multiple gene lists, which may be derived from different studies in terms of the biological contexts, applied technologies, or methodologies. These lists are then subjected to pathway-level comparative analysis for extraction of pathway-level patterns. This analysis pipeline helps to explore the commonality or uniqueness of these lists at the level of pathways or biological processes from different but relevant biological systems using a combination of statistical enrichment measurements, pathway-level pattern extraction, and graphical display of the relationships of genes and their associated pathways as Gene-Term Association Networks (GTANs) within the WPS platform. As a proof of concept, we have used the new method to analyze many datasets from our collaborators as well as some public microarray datasets. This tool provides a new pathway-level analysis scheme for integrative and comparative analysis of data derived from different but relevant systems. The tool is freely available as a Pathway Pattern Extraction Pipeline implemented in our existing software package WPS, which can be obtained at http://www.abcc.ncifcrf.gov/wps/wps_index.php.

Comparative study on gene set and pathway topology-based enrichment methods.

PubMed

Bayerlová, Michaela; Jung, Klaus; Kramer, Frank; Klemm, Florian; Bleckmann, Annalen; Beißbarth, Tim

2015-10-22

Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both types of methods for enrichment analysis require further improvements in order to deal with the problem of pathway overlaps.

A microarray whole-genome gene expression dataset in a rat model of inflammatory corneal angiogenesis.

PubMed

Mukwaya, Anthony; Lindvall, Jessica M; Xeroudaki, Maria; Peebo, Beatrice; Ali, Zaheer; Lennikov, Anton; Jensen, Lasse Dahl Ejby; Lagali, Neil

2016-11-22

In angiogenesis with concurrent inflammation, many pathways are activated, some linked to VEGF and others largely VEGF-independent. Pathways involving inflammatory mediators, chemokines, and micro-RNAs may play important roles in maintaining a pro-angiogenic environment or mediating angiogenic regression. Here, we describe a gene expression dataset to facilitate exploration of pro-angiogenic, pro-inflammatory, and remodelling/normalization-associated genes during both an active capillary sprouting phase, and in the restoration of an avascular phenotype. The dataset was generated by microarray analysis of the whole transcriptome in a rat model of suture-induced inflammatory corneal neovascularisation. Regions of active capillary sprout growth or regression in the cornea were harvested and total RNA extracted from four biological replicates per group. High quality RNA was obtained for gene expression analysis using microarrays. Fold change of selected genes was validated by qPCR, and protein expression was evaluated by immunohistochemistry. We provide a gene expression dataset that may be re-used to investigate corneal neovascularisation, and may also have implications in other contexts of inflammation-mediated angiogenesis.

Perturbed desmosomal cadherin expression in grainy head-like 1-null mice.

PubMed

Wilanowski, Tomasz; Caddy, Jacinta; Ting, Stephen B; Hislop, Nikki R; Cerruti, Loretta; Auden, Alana; Zhao, Lin-Lin; Asquith, Stephen; Ellis, Sarah; Sinclair, Rodney; Cunningham, John M; Jane, Stephen M

2008-03-19

In Drosophila, the grainy head (grh) gene plays a range of key developmental roles through the regulation of members of the cadherin gene family. We now report that mice lacking the grh homologue grainy head-like 1 (Grhl1) exhibit hair and skin phenotypes consistent with a reduction in expression of the genes encoding the desmosomal cadherin, desmoglein 1 (Dsg1). Grhl1-null mice show an initial delay in coat growth, and older mice exhibit hair loss as a result of poor anchoring of the hair shaft in the follicle. The mice also develop palmoplantar keratoderma, analogous to humans with DSG1 mutations. Sequence analysis, DNA binding, and chromatin immunoprecipitation experiments demonstrate that the human and mouse Dsg1 promoters are direct targets of GRHL1. Ultrastructural analysis reveals reduced numbers of abnormal desmosomes in the interfollicular epidermis. These findings establish GRHL1 as an important regulator of the Dsg1 genes in the context of hair anchorage and epidermal differentiation, and suggest that cadherin family genes are key targets of the grainy head-like genes across 700 million years of evolution.

Perturbed desmosomal cadherin expression in grainy head-like 1-null mice

PubMed Central

Wilanowski, Tomasz; Caddy, Jacinta; Ting, Stephen B; Hislop, Nikki R; Cerruti, Loretta; Auden, Alana; Zhao, Lin-Lin; Asquith, Stephen; Ellis, Sarah; Sinclair, Rodney; Cunningham, John M; Jane, Stephen M

2008-01-01

In Drosophila, the grainy head (grh) gene plays a range of key developmental roles through the regulation of members of the cadherin gene family. We now report that mice lacking the grh homologue grainy head-like 1 (Grhl1) exhibit hair and skin phenotypes consistent with a reduction in expression of the genes encoding the desmosomal cadherin, desmoglein 1 (Dsg1). Grhl1-null mice show an initial delay in coat growth, and older mice exhibit hair loss as a result of poor anchoring of the hair shaft in the follicle. The mice also develop palmoplantar keratoderma, analogous to humans with DSG1 mutations. Sequence analysis, DNA binding, and chromatin immunoprecipitation experiments demonstrate that the human and mouse Dsg1 promoters are direct targets of GRHL1. Ultrastructural analysis reveals reduced numbers of abnormal desmosomes in the interfollicular epidermis. These findings establish GRHL1 as an important regulator of the Dsg1 genes in the context of hair anchorage and epidermal differentiation, and suggest that cadherin family genes are key targets of the grainy head-like genes across 700 million years of evolution. PMID:18288204

Phylogenetic analysis at deep timescales: unreliable gene trees, bypassed hidden support, and the coalescence/concatalescence conundrum.

PubMed

Gatesy, John; Springer, Mark S

2014-11-01

Large datasets are required to solve difficult phylogenetic problems that are deep in the Tree of Life. Currently, two divergent systematic methods are commonly applied to such datasets: the traditional supermatrix approach (= concatenation) and "shortcut" coalescence (= coalescence methods wherein gene trees and the species tree are not co-estimated). When applied to ancient clades, these contrasting frameworks often produce congruent results, but in recent phylogenetic analyses of Placentalia (placental mammals), this is not the case. A recent series of papers has alternatively disputed and defended the utility of shortcut coalescence methods at deep phylogenetic scales. Here, we examine this exchange in the context of published phylogenomic data from Mammalia; in particular we explore two critical issues - the delimitation of data partitions ("genes") in coalescence analysis and hidden support that emerges with the combination of such partitions in phylogenetic studies. Hidden support - increased support for a clade in combined analysis of all data partitions relative to the support evident in separate analyses of the various data partitions, is a hallmark of the supermatrix approach and a primary rationale for concatenating all characters into a single matrix. In the most extreme cases of hidden support, relationships that are contradicted by all gene trees are supported when all of the genes are analyzed together. A valid fear is that shortcut coalescence methods might bypass or distort character support that is hidden in individual loci because small gene fragments are analyzed in isolation. Given the extensive systematic database for Mammalia, the assumptions and applicability of shortcut coalescence methods can be assessed with rigor to complement a small but growing body of simulation work that has directly compared these methods to concatenation. We document several remarkable cases of hidden support in both supermatrix and coalescence paradigms and argue that in most instances, the emergent support in the shortcut coalescence analyses is an artifact. By referencing rigorous molecular clock studies of Mammalia, we suggest that inaccurate gene trees that imply unrealistically deep coalescences debilitate shortcut coalescence analyses of the placental dataset. We document contradictory coalescence results for Placentalia, and outline a critical conundrum that challenges the general utility of shortcut coalescence methods at deep phylogenetic scales. In particular, the basic unit of analysis in coalescence analysis, the coalescence-gene, is expected to shrink in size as more taxa are analyzed, but as the amount of data for reconstruction of a gene tree ratchets downward, the number of nodes in the gene tree that need to be resolved ratchets upward. Some advocates of shortcut coalescence methods have attempted to address problems with inaccurate gene trees by concatenating multiple coalescence-genes to yield "gene trees" that better match the species tree. However, this hybrid concatenation/coalescence approach, "concatalescence," contradicts the most basic biological rationale for performing a coalescence analysis in the first place. We discuss this reality in the context of recent simulation work that also suggests inaccurate reconstruction of gene trees is more problematic for shortcut coalescence methods than deep coalescence of independently segregating loci is for concatenation methods. Copyright © 2014 Elsevier Inc. All rights reserved.

Mutation site and context dependent effects of ESR1 mutation in genome-edited breast cancer cell models.

PubMed

Bahreini, Amir; Li, Zheqi; Wang, Peilu; Levine, Kevin M; Tasdemir, Nilgun; Cao, Lan; Weir, Hazel M; Puhalla, Shannon L; Davidson, Nancy E; Stern, Andrew M; Chu, David; Park, Ben Ho; Lee, Adrian V; Oesterreich, Steffi

2017-05-23

Mutations in the estrogen receptor alpha (ERα) 1 gene (ESR1) are frequently detected in ER+ metastatic breast cancer, and there is increasing evidence that these mutations confer endocrine resistance in breast cancer patients with advanced disease. However, their functional role is not well-understood, at least in part due to a lack of ESR1 mutant models. Here, we describe the generation and characterization of genome-edited T47D and MCF7 breast cancer cell lines with the two most common ESR1 mutations, Y537S and D538G. Genome editing was performed using CRISPR and adeno-associated virus (AAV) technologies to knock-in ESR1 mutations into T47D and MCF7 cell lines, respectively. Various techniques were utilized to assess the activity of mutant ER, including transactivation, growth and chromatin-immunoprecipitation (ChIP) assays. The level of endocrine resistance was tested in mutant cells using a number of selective estrogen receptor modulators (SERMs) and degraders (SERDs). RNA sequencing (RNA-seq) was employed to study gene targets of mutant ER. Cells with ESR1 mutations displayed ligand-independent ER activity, and were resistant to several SERMs and SERDs, with cell line and mutation-specific differences with respect to magnitude of effect. The SERD AZ9496 showed increased efficacy compared to other drugs tested. Wild-type and mutant cell co-cultures demonstrated a unique evolution of mutant cells under estrogen deprivation and tamoxifen treatment. Transcriptome analysis confirmed ligand-independent regulation of ERα target genes by mutant ERα, but also identified novel target genes, some of which are involved in metastasis-associated phenotypes. Despite significant overlap in the ligand-independent genes between Y537S and D538G, the number of mutant ERα-target genes shared between the two cell lines was limited, suggesting context-dependent activity of the mutant receptor. Some genes and phenotypes were unique to one mutation within a given cell line, suggesting a mutation-specific effect. Taken together, ESR1 mutations in genome-edited breast cancer cell lines confer ligand-independent growth and endocrine resistance. These biologically relevant models can be used for further mechanistic and translational studies, including context-specific and mutation site-specific analysis of the ESR1 mutations.

Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells.

PubMed

Gatto, Sole; Puri, Pier Lorenzo; Malecova, Barbora

2017-01-01

Single cell gene expression profiling is a fundamental tool for studying the heterogeneity of a cell population by addressing the phenotypic and functional characteristics of each cell. Technological advances that have coupled microfluidic technologies with high-throughput quantitative RT-PCR analyses have enabled detailed analyses of single cells in various biological contexts. In this chapter, we describe the procedure for isolating the skeletal muscle interstitial cells termed Fibro-Adipogenic Progenitors (FAPs ) and their gene expression profiling at the single cell level. Moreover, we accompany our bench protocol with bioinformatics analysis designed to process raw data as well as to visualize single cell gene expression data. Single cell gene expression profiling is therefore a useful tool in the investigation of FAPs heterogeneity and their contribution to muscle homeostasis.

Analysis of Msx1 and Msx2 transactivation function in the context of the heat shock 70 (Hspa1b) gene promoter.

PubMed

Zhuang, Fengfeng; Nguyen, Manuel P; Shuler, Charles; Liu, Yi-Hsin

2009-04-03

Previous studies have shown that Msx proteins control gene transcription predominantly through repression mechanisms. However, gene expression studies using either the gain-of-function or the loss-of-function mutants revealed many gene targets whose expression require functional Msx proteins. To date, investigations into the mechanisms of Msx-dependent transactivation have been hindered by the lack of a responsive promoter. Here, we demonstrated the usefulness of the mouse Hspa1b promoter in probing Msx-dependent mechanisms of gene activation. We showed that Msx protein activates Hspa1b promoter via its C-terminal domain. The activation absolutely depends on the HSEs and physical interactions between Msx proteins and heat shock factors may play a contributing role.

The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation.

PubMed

McNeil, Leslie Klis; Reich, Claudia; Aziz, Ramy K; Bartels, Daniela; Cohoon, Matthew; Disz, Terry; Edwards, Robert A; Gerdes, Svetlana; Hwang, Kaitlyn; Kubal, Michael; Margaryan, Gohar Rem; Meyer, Folker; Mihalo, William; Olsen, Gary J; Olson, Robert; Osterman, Andrei; Paarmann, Daniel; Paczian, Tobias; Parrello, Bruce; Pusch, Gordon D; Rodionov, Dmitry A; Shi, Xinghua; Vassieva, Olga; Vonstein, Veronika; Zagnitko, Olga; Xia, Fangfang; Zinner, Jenifer; Overbeek, Ross; Stevens, Rick

2007-01-01

The National Microbial Pathogen Data Resource (NMPDR) (http://www.nmpdr.org) is a National Institute of Allergy and Infections Disease (NIAID)-funded Bioinformatics Resource Center that supports research in selected Category B pathogens. NMPDR contains the complete genomes of approximately 50 strains of pathogenic bacteria that are the focus of our curators, as well as >400 other genomes that provide a broad context for comparative analysis across the three phylogenetic Domains. NMPDR integrates complete, public genomes with expertly curated biological subsystems to provide the most consistent genome annotations. Subsystems are sets of functional roles related by a biologically meaningful organizing principle, which are built over large collections of genomes; they provide researchers with consistent functional assignments in a biologically structured context. Investigators can browse subsystems and reactions to develop accurate reconstructions of the metabolic networks of any sequenced organism. NMPDR provides a comprehensive bioinformatics platform, with tools and viewers for genome analysis. Results of precomputed gene clustering analyses can be retrieved in tabular or graphic format with one-click tools. NMPDR tools include Signature Genes, which finds the set of genes in common or that differentiates two groups of organisms. Essentiality data collated from genome-wide studies have been curated. Drug target identification and high-throughput, in silico, compound screening are in development.

Genetics and Genomics of Single-Gene Cardiovascular Diseases: Common Hereditary Cardiomyopathies as Prototypes of Single-Gene Disorders

PubMed Central

Marian, Ali J.; van Rooij, Eva; Roberts, Robert

2016-01-01

This is the first of 2 review papers on genetics and genomics appearing as part of the series on “omics.” Genomics pertains to all components of an organism’s genes, whereas genetics involves analysis of a specific gene(s) in the context of heredity. The paper provides introductory comments, describes the basis of human genetic diversity, and addresses the phenotypic consequences of genetic variants. Rare variants with large effect sizes are responsible for single-gene disorders, whereas complex polygenic diseases are typically due to multiple genetic variants, each exerting a modest effect size. To illustrate the clinical implications of genetic variants with large effect sizes, 3 common forms of hereditary cardiomyopathies are discussed as prototypic examples of single-gene disorders, including their genetics, clinical manifestations, pathogenesis, and treatment. The genetic basis of complex traits is discussed in a separate paper. PMID:28007145

Conserved noncoding sequences conserve biological networks and influence genome evolution.

PubMed

Xie, Jianbo; Qian, Kecheng; Si, Jingna; Xiao, Liang; Ci, Dong; Zhang, Deqiang

2018-05-01

Comparative genomics approaches have identified numerous conserved cis-regulatory sequences near genes in plant genomes. Despite the identification of these conserved noncoding sequences (CNSs), our knowledge of their functional importance and selection remains limited. Here, we used a combination of DNA methylome analysis, microarray expression analyses, and functional annotation to study these sequences in the model tree Populus trichocarpa. Methylation in CG contexts and non-CG contexts was lower in CNSs, particularly CNSs in the 5'-upstream regions of genes, compared with other sites in the genome. We observed that CNSs are enriched in genes with transcription and binding functions, and this also associated with syntenic genes and those from whole-genome duplications, suggesting that cis-regulatory sequences play a key role in genome evolution. We detected a significant positive correlation between CNS number and protein interactions, suggesting that CNSs may have roles in the evolution and maintenance of biological networks. The divergence of CNSs indicates that duplication-degeneration-complementation drives the subfunctionalization of a proportion of duplicated genes from whole-genome duplication. Furthermore, population genomics confirmed that most CNSs are under strong purifying selection and only a small subset of CNSs shows evidence of adaptive evolution. These findings provide a foundation for future studies exploring these key genomic features in the maintenance of biological networks, local adaptation, and transcription.

Integrative sparse principal component analysis of gene expression data.

PubMed

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

2017-12-01

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

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

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment

PubMed Central

Uddin, Raihan; Singh, Shiva M.

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in “learning and memory” related functions and pathways. Subsequent differential network analysis of this “learning and memory” module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they provide a new insight and generate new hypotheses into the molecular mechanisms responsible for age associated learning impairment, including spatial learning. PMID:29066959

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

PubMed

Uddin, Raihan; Singh, Shiva M

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they provide a new insight and generate new hypotheses into the molecular mechanisms responsible for age associated learning impairment, including spatial learning.

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.

The Tangled Tale of Genes and Environment: Moore's The Dependent Gene: The Fallacy of “nature VS. Nurture”

PubMed Central

Schneider, Susan M

2007-01-01

Nature–nurture views that smack of genetic determinism remain prevalent. Yet, the increasing knowledge base shows ever more clearly that environmental factors and genes form a fully interactional system at all levels. Moore's book covers the major topics of discovery and dispute, including behavior genetics and the twin studies, developmental psychobiology, and developmental systems theory. Knowledge of this larger life-sciences context for behavior principles will become increasingly important as the full complexity of gene–environment relations is revealed. Behavior analysis both contributes to and gains from the larger battle for the recognition of how nature and nurture really work.

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

Wullschleger, Stan D.; Difazio, Stephen P.

2003-01-01

Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less

Exploring codon context bias for synthetic gene design of a thermostable invertase in Escherichia coli.

PubMed

Pek, Han Bin; Klement, Maximilian; Ang, Kok Siong; Chung, Bevan Kai-Sheng; Ow, Dave Siak-Wei; Lee, Dong-Yup

2015-01-01

Various isoforms of invertases from prokaryotes, fungi, and higher plants has been expressed in Escherichia coli, and codon optimisation is a widely-adopted strategy for improvement of heterologous enzyme expression. Successful synthetic gene design for recombinant protein expression can be done by matching its translational elongation rate against heterologous host organisms via codon optimization. Amongst the various design parameters considered for the gene synthesis, codon context bias has been relatively overlooked compared to individual codon usage which is commonly adopted in most of codon optimization tools. In addition, matching the rates of transcription and translation based on secondary structure may lead to enhanced protein folding. In this study, we evaluated codon context fitness as design criterion for improving the expression of thermostable invertase from Thermotoga maritima in Escherichia coli and explored the relevance of secondary structure regions for folding and expression. We designed three coding sequences by using (1) a commercial vendor optimized gene algorithm, (2) codon context for the whole gene, and (3) codon context based on the secondary structure regions. Then, the codon optimized sequences were transformed and expressed in E. coli. From the resultant enzyme activities and protein yield data, codon context fitness proved to have the highest activity as compared to the wild-type control and other criteria while secondary structure-based strategy is comparable to the control. Codon context bias was shown to be a relevant parameter for enhancing enzyme production in Escherichia coli by codon optimization. Thus, we can effectively design synthetic genes within heterologous host organisms using this criterion. Copyright © 2015 Elsevier Inc. All rights reserved.

Transcriptional activation of Mina by Sp1/3 factors.

PubMed

Lian, Shangli; Potula, Hari Hara S K; Pillai, Meenu R; Van Stry, Melanie; Koyanagi, Madoka; Chung, Linda; Watanabe, Makiko; Bix, Mark

2013-01-01

Mina is an epigenetic gene regulatory protein known to function in multiple physiological and pathological contexts, including pulmonary inflammation, cell proliferation, cancer and immunity. We showed previously that the level of Mina gene expression is subject to natural genetic variation linked to 21 SNPs occurring in the Mina 5' region. In order to explore the mechanisms regulating Mina gene expression, we set out to molecularly characterize the Mina promoter in the region encompassing these SNPs. We used three kinds of assays--reporter, gel shift and chromatin immunoprecipitation--to analyze a 2 kb genomic fragment spanning the upstream and intron 1 regions flanking exon 1. Here we discovered a pair of Mina promoters (P1 and P2) and a P1-specific enhancer element (E1). Pharmacologic inhibition and siRNA knockdown experiments suggested that Sp1/3 transcription factors trigger Mina expression through additive activity targeted to a cluster of four Sp1/3 binding sites forming the P1 promoter. These results set the stage for comprehensive analysis of Mina gene regulation from the context of tissue specificity, the impact of inherited genetic variation and the nature of upstream signaling pathways.

Transcriptional Activation of Mina by Sp1/3 Factors

PubMed Central

Lian, Shangli; Potula, Hari Hara S. K.; Pillai, Meenu R.; Van Stry, Melanie; Koyanagi, Madoka; Chung, Linda; Watanabe, Makiko; Bix, Mark

2013-01-01

Mina is an epigenetic gene regulatory protein known to function in multiple physiological and pathological contexts, including pulmonary inflammation, cell proliferation, cancer and immunity. We showed previously that the level of Mina gene expression is subject to natural genetic variation linked to 21 SNPs occurring in the Mina 5′ region [1]. In order to explore the mechanisms regulating Mina gene expression, we set out to molecularly characterize the Mina promoter in the region encompassing these SNPs. We used three kinds of assays – reporter, gel shift and chromatin immunoprecipitation – to analyze a 2 kb genomic fragment spanning the upstream and intron 1 regions flanking exon 1. Here we discovered a pair of Mina promoters (P1 and P2) and a P1-specific enhancer element (E1). Pharmacologic inhibition and siRNA knockdown experiments suggested that Sp1/3 transcription factors trigger Mina expression through additive activity targeted to a cluster of four Sp1/3 binding sites forming the P1 promoter. These results set the stage for comprehensive analysis of Mina gene regulation from the context of tissue specificity, the impact of inherited genetic variation and the nature of upstream signaling pathways. PMID:24324617

Cancer Transcriptome Dataset Analysis: Comparing Methods of Pathway and Gene Regulatory Network-Based Cluster Identification.

PubMed

Nam, Seungyoon

2017-04-01

Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets. Network clustering is useful, but depends on the network topology in and of itself. Notably, the performance of different network-generating tools for network cluster (NC) identification has been little investigated to date. Hence, using gastric cancer (GC) transcriptomic datasets, we compared two algorithms for generating pathway versus gene regulatory network-based NCs, showing that the pathway-based approach better agrees with a reference set of cancer-functional contexts. Finally, by applying pathway-based NC identification to GC transcriptome datasets, we describe cancer NCs that associate with candidate therapeutic targets and biomarkers in GC. These observations collectively inform future research on cancer transcriptomics, drug discovery, and rational development of new analysis tools for optimal harnessing of omics data.

Causal network analysis of head and neck keloid tissue identifies potential master regulators.

PubMed

Garcia-Rodriguez, Laura; Jones, Lamont; Chen, Kang Mei; Datta, Indrani; Divine, George; Worsham, Maria J

2016-10-01

To generate novel insights and hypotheses in keloid development from potential master regulators. Prospective cohort. Six fresh keloid and six normal skin samples from 12 anonymous donors were used in a prospective cohort study. Genome-wide profiling was done previously on the cohort using the Infinium HumanMethylation450 BeadChip (Illumina, San Diego, CA). The 190 statistically significant CpG islands between keloid and normal tissue mapped to 152 genes (P < .05). The top 10 statistically significant genes (VAMP5, ACTR3C, GALNT3, KCNAB2, LRRC61, SCML4, SYNGR1, TNS1, PLEKHG5, PPP1R13-α, false discovery rate <.015) were uploaded into the Ingenuity Pathway Analysis software's Causal Network Analysis (QIAGEN, Redwood City, CA). To reflect expected gene expression direction in the context of methylation changes, the inverse of the methylation ratio from keloid versus normal tissue was used for the analysis. Causal Network Analysis identified disease-specific master regulator molecules based on downstream differentially expressed keloid-specific genes and expected directionality of expression (hypermethylated vs. hypomethylated). Causal Network Analysis software identified four hierarchical networks that included four master regulators (pyroxamide, tributyrin, PRKG2, and PENK) and 19 intermediate regulators. Causal Network Analysis of differentiated methylated gene data of keloid versus normal skin demonstrated four causal networks with four master regulators. These hierarchical networks suggest potential driver roles for their downstream keloid gene targets in the pathogenesis of the keloid phenotype, likely triggered due to perturbation/injury to normal tissue. NA Laryngoscope, 126:E319-E324, 2016. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium.

PubMed

Hohman, Timothy J; Bush, William S; Jiang, Lan; Brown-Gentry, Kristin D; Torstenson, Eric S; Dudek, Scott M; Mukherjee, Shubhabrata; Naj, Adam; Kunkle, Brian W; Ritchie, Marylyn D; Martin, Eden R; Schellenberg, Gerard D; Mayeux, Richard; Farrer, Lindsay A; Pericak-Vance, Margaret A; Haines, Jonathan L; Thornton-Wells, Tricia A

2016-02-01

Late-onset Alzheimer disease (AD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance, and gene-gene interactions; however, the investigation of interactions in recent genome-wide association studies has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across 13 data sets from the Alzheimer Disease Genetics Consortium. Fifteen single nucleotide polymorphism (SNP)-SNP pairs within 3 gene-gene combinations were identified: SIRT1 × ABCB1, PSAP × PEBP4, and GRIN2B × ADRA1A. In addition, we extend a previously identified interaction from an endophenotype analysis between RYR3 × CACNA1C. Finally, post hoc gene expression analyses of the implicated SNPs further implicate SIRT1 and ABCB1, and implicate CDH23 which was most recently identified as an AD risk locus in an epigenetic analysis of AD. The observed interactions in this article highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis. Copyright © 2016 Elsevier Inc. All rights reserved.

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

PubMed

Muetze, Tanja; Goenawan, Ivan H; Wiencko, Heather L; Bernal-Llinares, Manuel; Bryan, Kenneth; Lynn, David J

2016-01-01

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).

Insights into GATA-1 Mediated Gene Activation versus Repression via Genome-wide Chromatin Occupancy Analysis

PubMed Central

Yu, Ming; Riva, Laura; Xie, Huafeng; Schindler, Yocheved; Moran, Tyler B.; Cheng, Yong; Yu, Duonan; Hardison, Ross; Weiss, Mitchell J; Orkin, Stuart H.; Bernstein, Bradley E.; Fraenkel, Ernest; Cantor, Alan B.

2009-01-01

Summary The transcription factor GATA-1 is required for terminal erythroid maturation and functions as an activator or repressor depending on gene context. Yet its in vivo site selectivity and ability to distinguish between activated versus repressed genes remain incompletely understood. In this study, we performed GATA-1 ChIP-seq in erythroid cells and compared it to GATA-1 induced gene expression changes. Bound and differentially expressed genes contain a greater number of GATA binding motifs, a higher frequency of palindromic GATA sites, and closer occupancy to the transcriptional start site versus non-differentially expressed genes. Moreover, we show that the transcription factor Zbtb7a occupies GATA-1 bound regions of some direct GATA-1 target genes, that the presence of SCL/TAL1 helps distinguish transcriptional activation versus repression, and that Polycomb Repressive Complex 2 (PRC2) is involved in epigenetic silencing of a subset of GATA-1 repressed genes. These data provide insights into GATA-1 mediated gene regulation in vivo. PMID:19941827

BGDB: a database of bivalent genes.

PubMed

Li, Qingyan; Lian, Shuabin; Dai, Zhiming; Xiang, Qian; Dai, Xianhua

2013-01-01

Bivalent gene is a gene marked with both H3K4me3 and H3K27me3 epigenetic modification in the same area, and is proposed to play a pivotal role related to pluripotency in embryonic stem (ES) cells. Identification of these bivalent genes and understanding their functions are important for further research of lineage specification and embryo development. So far, lots of genome-wide histone modification data were generated in mouse and human ES cells. These valuable data make it possible to identify bivalent genes, but no comprehensive data repositories or analysis tools are available for bivalent genes currently. In this work, we develop BGDB, the database of bivalent genes. The database contains 6897 bivalent genes in human and mouse ES cells, which are manually collected from scientific literature. Each entry contains curated information, including genomic context, sequences, gene ontology and other relevant information. The web services of BGDB database were implemented with PHP + MySQL + JavaScript, and provide diverse query functions. Database URL: http://dailab.sysu.edu.cn/bgdb/

Functional Interaction Network Construction and Analysis for Disease Discovery.

PubMed

Wu, Guanming; Haw, Robin

2017-01-01

Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

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

PubMed

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

2012-12-24

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

Off and back-on again: a tumor suppressor's tale.

PubMed

Acosta, Jonuelle; Wang, Walter; Feldser, David M

2018-06-01

Tumor suppressor genes play critical roles orchestrating anti-cancer programs that are both context dependent and mechanistically diverse. Beyond canonical tumor suppressive programs that control cell division, cell death, and genome stability, unexpected tumor suppressor gene activities that regulate metabolism, immune surveillance, the epigenetic landscape, and others have recently emerged. This diversity underscores the important roles these genes play in maintaining cellular homeostasis to suppress cancer initiation and progression, but also highlights a tremendous challenge in discerning precise context-specific programs of tumor suppression controlled by a given tumor suppressor. Fortunately, the rapid sophistication of genetically engineered mouse models of cancer has begun to shed light on these context-dependent tumor suppressor activities. By using techniques that not only toggle "off" tumor suppressor genes in nascent tumors, but also facilitate the timely restoration of gene function "back-on again" in disease specific contexts, precise mechanisms of tumor suppression can be revealed in an unbiased manner. This review discusses the development and implementation of genetic systems designed to toggle tumor suppressor genes off and back-on again and their potential to uncover the tumor suppressor's tale.

A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations

PubMed Central

Thiel, Christoph; Cordes, Henrik; Fabbri, Lorenzo; Aschmann, Hélène Eloise; Baier, Vanessa; Atkinson, Francis; Blank, Lars Mathias; Kuepfer, Lars

2017-01-01

Drug-induced toxicity is a significant problem in clinical care. A key problem here is a general understanding of the molecular mechanisms accompanying the transition from desired drug effects to adverse events following administration of either therapeutic or toxic doses, in particular within a patient context. Here, a comparative toxicity analysis was performed for fifteen hepatotoxic drugs by evaluating toxic changes reflecting the transition from therapeutic drug responses to toxic reactions at the cellular level. By use of physiologically-based pharmacokinetic modeling, in vitro toxicity data were first contextualized to quantitatively describe time-resolved drug responses within a patient context. Comparatively studying toxic changes across the considered hepatotoxicants allowed the identification of subsets of drugs sharing similar perturbations on key cellular processes, functional classes of genes, and individual genes. The identified subsets of drugs were next analyzed with regard to drug-related characteristics and their physicochemical properties. Toxic changes were finally evaluated to predict both molecular biomarkers and potential drug-drug interactions. The results may facilitate the early diagnosis of adverse drug events in clinical application. PMID:28151932

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

PubMed

Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

2015-10-01

Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.

Network-based integration of GWAS and gene expression identifies a HOX-centric network associated with serous ovarian cancer risk

PubMed Central

Kar, Siddhartha P.; Tyrer, Jonathan P.; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie T.; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F.; Edwards, Robert P.; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K.; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K.; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain A.; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston-Campbell, Lara E.; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Monteiro, Alvaro N. A.; Freedman, Matthew L.; Gayther, Simon A.; Pharoah, Paul D. P.

2015-01-01

Background Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by co-expression may also be enriched for additional EOC risk associations. Methods We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly co-expressed with each selected TF gene in the unified microarray data set of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this data set were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P<0.05 and FDR<0.05). These results were replicated (P<0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact Network analysis integrating large, context-specific data sets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. PMID:26209509

Systems Level Analysis of Systemic Sclerosis Shows a Network of Immune and Profibrotic Pathways Connected with Genetic Polymorphisms

PubMed Central

Mahoney, J. Matthew; Taroni, Jaclyn; Martyanov, Viktor; Wood, Tammara A.; Greene, Casey S.; Pioli, Patricia A.; Hinchcliff, Monique E.; Whitfield, Michael L.

2015-01-01

Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6–12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk. PMID:25569146

IMG: the integrated microbial genomes database and comparative analysis system

PubMed Central

Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Grechkin, Yuri; Ratner, Anna; Jacob, Biju; Huang, Jinghua; Williams, Peter; Huntemann, Marcel; Anderson, Iain; Mavromatis, Konstantinos; Ivanova, Natalia N.; Kyrpides, Nikos C.

2012-01-01

The Integrated Microbial Genomes (IMG) system serves as a community resource for comparative analysis of publicly available genomes in a comprehensive integrated context. IMG integrates publicly available draft and complete genomes from all three domains of life with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and reviewing the annotations of genes and genomes in a comparative context. IMG's data content and analytical capabilities have been continuously extended through regular updates since its first release in March 2005. IMG is available at http://img.jgi.doe.gov. Companion IMG systems provide support for expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er), teaching courses and training in microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu) and analysis of genomes related to the Human Microbiome Project (IMG/HMP: http://www.hmpdacc-resources.org/img_hmp). PMID:22194640

IMG: the Integrated Microbial Genomes database and comparative analysis system.

PubMed

Markowitz, Victor M; Chen, I-Min A; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Grechkin, Yuri; Ratner, Anna; Jacob, Biju; Huang, Jinghua; Williams, Peter; Huntemann, Marcel; Anderson, Iain; Mavromatis, Konstantinos; Ivanova, Natalia N; Kyrpides, Nikos C

2012-01-01

The Integrated Microbial Genomes (IMG) system serves as a community resource for comparative analysis of publicly available genomes in a comprehensive integrated context. IMG integrates publicly available draft and complete genomes from all three domains of life with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and reviewing the annotations of genes and genomes in a comparative context. IMG's data content and analytical capabilities have been continuously extended through regular updates since its first release in March 2005. IMG is available at http://img.jgi.doe.gov. Companion IMG systems provide support for expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er), teaching courses and training in microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu) and analysis of genomes related to the Human Microbiome Project (IMG/HMP: http://www.hmpdacc-resources.org/img_hmp).

Gene expression profiling--Opening the black box of plant ecosystem responses to global change

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

Leakey, A.D.B.; Ainsworth, E.A.; Bernard, S.M.

The use of genomic techniques to address ecological questions is emerging as the field of genomic ecology. Experimentation under environmentally realistic conditions to investigate the molecular response of plants to meaningful changes in growth conditions and ecological interactions is the defining feature of genomic ecology. Since the impact of global change factors on plant performance are mediated by direct effects at the molecular, biochemical and physiological scales, gene expression analysis promises important advances in understanding factors that have previously been consigned to the 'black box' of unknown mechanism. Various tools and approaches are available for assessing gene expression in modelmore » and non-model species as part of global change biology studies. Each approach has its own unique advantages and constraints. A first generation of genomic ecology studies in managed ecosystems and mesocosms have provided a testbed for the approach and have begun to reveal how the experimental design and data analysis of gene expression studies can be tailored for use in an ecological context.« less

Network analysis of transcriptomics expands regulatory landscapes in Synechococcus sp. PCC 7002

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

McClure, Ryan S.; Overall, Christopher C.; McDermott, Jason E.

Cyanobacterial regulation of gene expression must contend with a genome organization that lacks apparent functional context, as the majority of cellular processes and metabolic pathways are encoded by genes found at disparate locations across the genome. In addition, the fact that coordinated regulation of cyanobacterial cellular machinery takes place with significantly fewer transcription factors, compared to other Eubacteria, suggests the involvement of post-transcriptional mechanisms and regulatory adaptations which are not fully understood. Global transcript abundance from model cyanobacterium Synechococcus sp. PCC 7002 grown under 42 different conditions was analyzed using context-likelihood of relatedness. The resulting 903-gene network, which was organizedmore » into 11 modules, not only allowed classification of cyanobacterial responses to specific environmental variables but provided insight into the transcriptional network topology and led to the expansion of predicted regulons. When used in conjunction with genome sequence, the global transcript abundance allowed identification of putative post-transcriptional changes in expression as well as novel potential targets of both DNA binding proteins and asRNA regulators. The results offer a new perspective into the multi-level regulation that governs cellular adaptations of fast-growing physiologically robust cyanobacterium Synechococcus sp. PCC 7002 to changing environmental variables. It also extends a methodological knowledge-based framework for studying multi-scale regulatory mechanisms that operate in cyanobacteria. Finally, it provides valuable context for integrating systems-level data to enhance evidence-driven genomic annotation, especially in organisms where traditional context analyses cannot be implemented due to lack of operon-based functional organization.« less

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

PubMed Central

Rioualen, Claire; Da Costa, Quentin; Chetrit, Bernard; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe

2017-01-01

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986

NaviGO: interactive tool for visualization and functional similarity and coherence analysis with gene ontology.

PubMed

Wei, Qing; Khan, Ishita K; Ding, Ziyun; Yerneni, Satwica; Kihara, Daisuke

2017-03-20

The number of genomics and proteomics experiments is growing rapidly, producing an ever-increasing amount of data that are awaiting functional interpretation. A number of function prediction algorithms were developed and improved to enable fast and automatic function annotation. With the well-defined structure and manual curation, Gene Ontology (GO) is the most frequently used vocabulary for representing gene functions. To understand relationship and similarity between GO annotations of genes, it is important to have a convenient pipeline that quantifies and visualizes the GO function analyses in a systematic fashion. NaviGO is a web-based tool for interactive visualization, retrieval, and computation of functional similarity and associations of GO terms and genes. Similarity of GO terms and gene functions is quantified with six different scores including protein-protein interaction and context based association scores we have developed in our previous works. Interactive navigation of the GO function space provides intuitive and effective real-time visualization of functional groupings of GO terms and genes as well as statistical analysis of enriched functions. We developed NaviGO, which visualizes and analyses functional similarity and associations of GO terms and genes. The NaviGO webserver is freely available at: http://kiharalab.org/web/navigo .

Reverse engineering and analysis of large genome-scale gene networks

PubMed Central

Aluru, Maneesha; Zola, Jaroslaw; Nettleton, Dan; Aluru, Srinivas

2013-01-01

Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of Arabidopsis thaliana from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 Arabidopsis AraCyc 8.0 pathways, and the results are made available through the web. PMID:23042249

Detecting gene subnetworks under selection in biological pathways.

PubMed

Gouy, Alexandre; Daub, Joséphine T; Excoffier, Laurent

2017-09-19

Advances in high throughput sequencing technologies have created a gap between data production and functional data analysis. Indeed, phenotypes result from interactions between numerous genes, but traditional methods treat loci independently, missing important knowledge brought by network-level emerging properties. Therefore, detecting selection acting on multiple genes affecting the evolution of complex traits remains challenging. In this context, gene network analysis provides a powerful framework to study the evolution of adaptive traits and facilitates the interpretation of genome-wide data. We developed a method to analyse gene networks that is suitable to evidence polygenic selection. The general idea is to search biological pathways for subnetworks of genes that directly interact with each other and that present unusual evolutionary features. Subnetwork search is a typical combinatorial optimization problem that we solve using a simulated annealing approach. We have applied our methodology to find signals of adaptation to high-altitude in human populations. We show that this adaptation has a clear polygenic basis and is influenced by many genetic components. Our approach, implemented in the R package signet, improves on gene-level classical tests for selection by identifying both new candidate genes and new biological processes involved in adaptation to altitude. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genetic structure of the carnivorous plant Pinguicula moranensis (Lentibulariaceae) on the transvolcanic Mexican belt.

PubMed

Alcalá, Raúl E; Domínguez, César A

2012-06-01

Most species of Pinguicula present a montane distribution with populations located at high altitudes. In this context, we proposed that populations of Pinguicula species could be genetically differentiated even at a local scale. This study supported that prediction, as a RAPD-based analysis of molecular variance revealed a high degree of genetic structure (Φ (st) = 0.157, P = 0.001) and low gene flow (Nm = 1.0) among four central populations of Pinguicula moranensis in Mexico, with a maximum geographic separation of about 140 km. The four populations also exhibited high levels of genetic diversity (mean Nei's genetic diversity = 0.3716; % polymorphism = 95.45%). The evolutionary implications of the genetic structure found in P. moranensis for other species in the genus are discussed in the context of the naturally fragmented distribution and a set of life history traits shared by most Pinguicula species that could promote geographic isolation and limited gene flow.

GreenPhylDB v2.0: comparative and functional genomics in plants.

PubMed

Rouard, Mathieu; Guignon, Valentin; Aluome, Christelle; Laporte, Marie-Angélique; Droc, Gaëtan; Walde, Christian; Zmasek, Christian M; Périn, Christophe; Conte, Matthieu G

2011-01-01

GreenPhylDB is a database designed for comparative and functional genomics based on complete genomes. Version 2 now contains sixteen full genomes of members of the plantae kingdom, ranging from algae to angiosperms, automatically clustered into gene families. Gene families are manually annotated and then analyzed phylogenetically in order to elucidate orthologous and paralogous relationships. The database offers various lists of gene families including plant, phylum and species specific gene families. For each gene cluster or gene family, easy access to gene composition, protein domains, publications, external links and orthologous gene predictions is provided. Web interfaces have been further developed to improve the navigation through information related to gene families. New analysis tools are also available, such as a gene family ontology browser that facilitates exploration. GreenPhylDB is a component of the South Green Bioinformatics Platform (http://southgreen.cirad.fr/) and is accessible at http://greenphyl.cirad.fr. It enables comparative genomics in a broad taxonomy context to enhance the understanding of evolutionary processes and thus tends to speed up gene discovery.

Functional Metagenomics Reveals Previously Unrecognized Diversity of Antibiotic Resistance Genes in Gulls

PubMed Central

Martiny, Adam C.; Martiny, Jennifer B. H.; Weihe, Claudia; Field, Andrew; Ellis, Julie C.

2011-01-01

Wildlife may facilitate the spread of antibiotic resistance (AR) between human-dominated habitats and the surrounding environment. Here, we use functional metagenomics to survey the diversity and genomic context of AR genes in gulls. Using this approach, we found a variety of AR genes not previously detected in gulls and wildlife, including class A and C β-lactamases as well as six tetracycline resistance gene types. An analysis of the flanking sequences indicates that most of these genes are present in Enterobacteriaceae and various Gram-positive bacteria. In addition to finding known gene types, we detected 31 previously undescribed AR genes. These undescribed genes include one most similar to an uncharacterized gene in Verrucomicrobium and another to a putative DNA repair protein in Lactobacillus. Overall, the study more than doubled the number of clinically relevant AR gene types known to be carried by gulls or by wildlife in general. Together with the propensity of gulls to visit human-dominated habitats, this high diversity of AR gene types suggests that gulls could facilitate the spread of AR. PMID:22347872

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.

MicroScope—an integrated microbial resource for the curation and comparative analysis of genomic and metabolic data

PubMed Central

Vallenet, David; Belda, Eugeni; Calteau, Alexandra; Cruveiller, Stéphane; Engelen, Stefan; Lajus, Aurélie; Le Fèvre, François; Longin, Cyrille; Mornico, Damien; Roche, David; Rouy, Zoé; Salvignol, Gregory; Scarpelli, Claude; Thil Smith, Adam Alexander; Weiman, Marion; Médigue, Claudine

2013-01-01

MicroScope is an integrated platform dedicated to both the methodical updating of microbial genome annotation and to comparative analysis. The resource provides data from completed and ongoing genome projects (automatic and expert annotations), together with data sources from post-genomic experiments (i.e. transcriptomics, mutant collections) allowing users to perfect and improve the understanding of gene functions. MicroScope (http://www.genoscope.cns.fr/agc/microscope) combines tools and graphical interfaces to analyse genomes and to perform the manual curation of gene annotations in a comparative context. Since its first publication in January 2006, the system (previously named MaGe for Magnifying Genomes) has been continuously extended both in terms of data content and analysis tools. The last update of MicroScope was published in 2009 in the Database journal. Today, the resource contains data for >1600 microbial genomes, of which ∼300 are manually curated and maintained by biologists (1200 personal accounts today). Expert annotations are continuously gathered in the MicroScope database (∼50 000 a year), contributing to the improvement of the quality of microbial genomes annotations. Improved data browsing and searching tools have been added, original tools useful in the context of expert annotation have been developed and integrated and the website has been significantly redesigned to be more user-friendly. Furthermore, in the context of the European project Microme (Framework Program 7 Collaborative Project), MicroScope is becoming a resource providing for the curation and analysis of both genomic and metabolic data. An increasing number of projects are related to the study of environmental bacterial (meta)genomes that are able to metabolize a large variety of chemical compounds that may be of high industrial interest. PMID:23193269

Loading-related regulation of gene expression in bone in the contexts of estrogen deficiency, lack of estrogen receptor α and disuse

PubMed Central

Zaman, Gul; Saxon, Leanne K.; Sunters, Andrew; Hilton, Helen; Underhill, Peter; Williams, Debbie; Price, Joanna S.; Lanyon, Lance E.

2010-01-01

Loading-related changes in gene expression in resident cells in the tibia of female mice in the contexts of normality (WT), estrogen deficiency (WT-OVX), absence of estrogen receptor α (ERα−/−) and disuse due to sciatic neurectomy (WT-SN) were established by microarray. Total RNA was extracted from loaded and contra-lateral non-loaded tibiae at selected time points after a single, short period of dynamic loading sufficient to engender an osteogenic response. There were marked changes in the expression of many genes according to context as well as in response to loading within those contexts. In WT mice at 3, 8, 12 and 24 h after loading the expression of 642, 341, 171 and 24 genes, respectively, were differentially regulated compared with contra-lateral bones which were not loaded. Only a few of the genes differentially regulated by loading in the tibiae of WT mice have recognized roles in bone metabolism or have been linked previously to osteogenesis (Opn, Sost, Esr1, Tgfb1, Lrp1, Ostn, Timp, Mmp, Ctgf, Postn and Irs1, BMP and DLX5). The canonical pathways showing the greatest loading-related regulation were those involving pyruvate metabolism, mitochondrial dysfunction, calcium-induced apoptosis, glycolysis/gluconeogenesis, aryl hydrocarbon receptor and oxidative phosphorylation. In the tibiae from WT-OVX, ERα−/− and WT-SN mice, 440, 439 and 987 genes respectively were differentially regulated by context alone compared to WT. The early response to loading in tibiae of WT-OVX mice involved differential regulation compared to their contra-lateral non-loaded pair of fewer genes than in WT, more down-regulation than up-regulation and a later response. This was shared by WT-SN. In tibiae of ERα−/− mice, the number of genes differentially regulated by loading was markedly reduced at all time points. These data indicate that in resident bone cells, both basal and loading-related gene expression is substantially modified by context. Many of the genes differentially regulated by the earliest loading-related response were primarily involved in energy metabolism and were not specific to bone. PMID:19857613

Gene Model Annotations for Drosophila melanogaster: The Rule-Benders

PubMed Central

Crosby, Madeline A.; Gramates, L. Sian; dos Santos, Gilberto; Matthews, Beverley B.; St. Pierre, Susan E.; Zhou, Pinglei; Schroeder, Andrew J.; Falls, Kathleen; Emmert, David B.; Russo, Susan M.; Gelbart, William M.

2015-01-01

In the context of the FlyBase annotated gene models in Drosophila melanogaster, we describe the many exceptional cases we have curated from the literature or identified in the course of FlyBase analysis. These range from atypical but common examples such as dicistronic and polycistronic transcripts, noncanonical splices, trans-spliced transcripts, noncanonical translation starts, and stop-codon readthroughs, to single exceptional cases such as ribosomal frameshifting and HAC1-type intron processing. In FlyBase, exceptional genes and transcripts are flagged with Sequence Ontology terms and/or standardized comments. Because some of the rule-benders create problems for handlers of high-throughput data, we discuss plans for flagging these cases in bulk data downloads. PMID:26109356

Injury-induced immune responses in Hydra.

PubMed

Wenger, Yvan; Buzgariu, Wanda; Reiter, Silke; Galliot, Brigitte

2014-08-01

The impact of injury-induced immune responses on animal regenerative processes is highly variable, positive or negative depending on the context. This likely reflects the complexity of the innate immune system that behaves as a sentinel in the transition from injury to regeneration. Early-branching invertebrates with high regenerative potential as Hydra provide a unique framework to dissect how injury-induced immune responses impact regeneration. A series of early cellular events likely require an efficient immune response after amputation, as antimicrobial defence, epithelial cell stretching for wound closure, migration of interstitial progenitors toward the wound, cell death, phagocytosis of cell debris, or reconstruction of the extracellular matrix. The analysis of the injury-induced transcriptomic modulations of 2636 genes annotated as immune genes in Hydra identified 43 genes showing an immediate/early pulse regulation in all regenerative contexts examined. These regulations point to an enhanced cytoprotection via ROS signaling (Nrf, C/EBP, p62/SQSMT1-l2), TNFR and TLR signaling (TNFR16-like, TRAF2l, TRAF5l, jun, fos-related, SIK2, ATF1/CREB, LRRC28, LRRC40, LRRK2), proteasomal activity (p62/SQSMT1-l1, Ced6/Gulf, NEDD8-conjugating enzyme Ubc12), stress proteins (CRYAB1, CRYAB2, HSP16.2, DnaJB9, HSP90a1), all potentially regulating NF-κB activity. Other genes encoding immune-annotated proteins such as NPYR4, GTPases, Swap70, the antiproliferative BTG1, enzymes involved in lipid metabolism (5-lipoxygenase, ACSF4), secreted clotting factors, secreted peptidases are also pulse regulated upon bisection. By contrast, metalloproteinases and antimicrobial peptide genes largely follow a context-dependent regulation, whereas the protease inhibitor α2macroglobulin gene exhibits a sustained up-regulation. Hence a complex immune response to injury is linked to wound healing and regeneration in Hydra. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

PSAT: A web tool to compare genomic neighborhoods of multiple prokaryotic genomes

PubMed Central

Fong, Christine; Rohmer, Laurence; Radey, Matthew; Wasnick, Michael; Brittnacher, Mitchell J

2008-01-01

Background The conservation of gene order among prokaryotic genomes can provide valuable insight into gene function, protein interactions, or events by which genomes have evolved. Although some tools are available for visualizing and comparing the order of genes between genomes of study, few support an efficient and organized analysis between large numbers of genomes. The Prokaryotic Sequence homology Analysis Tool (PSAT) is a web tool for comparing gene neighborhoods among multiple prokaryotic genomes. Results PSAT utilizes a database that is preloaded with gene annotation, BLAST hit results, and gene-clustering scores designed to help identify regions of conserved gene order. Researchers use the PSAT web interface to find a gene of interest in a reference genome and efficiently retrieve the sequence homologs found in other bacterial genomes. The tool generates a graphic of the genomic neighborhood surrounding the selected gene and the corresponding regions for its homologs in each comparison genome. Homologs in each region are color coded to assist users with analyzing gene order among various genomes. In contrast to common comparative analysis methods that filter sequence homolog data based on alignment score cutoffs, PSAT leverages gene context information for homologs, including those with weak alignment scores, enabling a more sensitive analysis. Features for constraining or ordering results are designed to help researchers browse results from large numbers of comparison genomes in an organized manner. PSAT has been demonstrated to be useful for helping to identify gene orthologs and potential functional gene clusters, and detecting genome modifications that may result in loss of function. Conclusion PSAT allows researchers to investigate the order of genes within local genomic neighborhoods of multiple genomes. A PSAT web server for public use is available for performing analyses on a growing set of reference genomes through any web browser with no client side software setup or installation required. Source code is freely available to researchers interested in setting up a local version of PSAT for analysis of genomes not available through the public server. Access to the public web server and instructions for obtaining source code can be found at . PMID:18366802

Discovering novel subsystems using comparative genomics

PubMed Central

Ferrer, Luciana; Shearer, Alexander G.; Karp, Peter D.

2011-01-01

Motivation: Key problems for computational genomics include discovering novel pathways in genome data, and discovering functional interaction partners for genes to define new members of partially elucidated pathways. Results: We propose a novel method for the discovery of subsystems from annotated genomes. For each gene pair, a score measuring the likelihood that the two genes belong to a same subsystem is computed using genome context methods. Genes are then grouped based on these scores, and the resulting groups are filtered to keep only high-confidence groups. Since the method is based on genome context analysis, it relies solely on structural annotation of the genomes. The method can be used to discover new pathways, find missing genes from a known pathway, find new protein complexes or other kinds of functional groups and assign function to genes. We tested the accuracy of our method in Escherichia coli K-12. In one configuration of the system, we find that 31.6% of the candidate groups generated by our method match a known pathway or protein complex closely, and that we rediscover 31.2% of all known pathways and protein complexes of at least 4 genes. We believe that a significant proportion of the candidates that do not match any known group in E.coli K-12 corresponds to novel subsystems that may represent promising leads for future laboratory research. We discuss in-depth examples of these findings. Availability: Predicted subsystems are available at http://brg.ai.sri.com/pwy-discovery/journal.html. Contact: lferrer@ai.sri.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21775308

Immediate-Early Gene Transcriptional Activation in Hippocampus Ca1 and Ca3 Does Not Accurately Reflect Rapid, Pattern Completion-Based Retrieval of Context Memory

ERIC Educational Resources Information Center

Pevzner, Aleksandr; Guzowski, John F.

2015-01-01

No studies to date have examined whether immediate-early gene (IEG) activation is driven by context memory recall. To address this question, we utilized the context preexposure facilitation effect (CPFE) paradigm. In CPFE, animals acquire contextual fear conditioning through hippocampus-dependent rapid retrieval of a previously formed contextual…

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

PubMed Central

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

2014-01-01

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

Comparison of dorsal root ganglion gene expression in rat models of traumatic and HIV-associated neuropathic pain

PubMed Central

Maratou, Klio; Wallace, Victoria C.J.; Hasnie, Fauzia S.; Okuse, Kenji; Hosseini, Ramine; Jina, Nipurna; Blackbeard, Julie; Pheby, Timothy; Orengo, Christine; Dickenson, Anthony H.; McMahon, Stephen B.; Rice, Andrew S.C.

2009-01-01

To elucidate the mechanisms underlying peripheral neuropathic pain in the context of HIV infection and antiretroviral therapy, we measured gene expression in dorsal root ganglia (DRG) of rats subjected to systemic treatment with the anti-retroviral agent, ddC (Zalcitabine) and concomitant delivery of HIV-gp120 to the rat sciatic nerve. L4 and L5 DRGs were collected at day 14 (time of peak behavioural change) and changes in gene expression were measured using Affymetrix whole genome rat arrays. Conventional analysis of this data set and Gene Set Enrichment Analysis (GSEA) was performed to discover biological processes altered in this model. Transcripts associated with G protein coupled receptor signalling and cell adhesion were enriched in the treated animals, while ribosomal proteins and proteasome pathways were associated with gene down-regulation. To identify genes that are directly relevant to neuropathic mechanical hypersensitivity, as opposed to epiphenomena associated with other aspects of the response to a sciatic nerve lesion, we compared the gp120 + ddC-evoked gene expression with that observed in a model of traumatic neuropathic pain (L5 spinal nerve transection), where hypersensitivity to a static mechanical stimulus is also observed. We identified 39 genes/expressed sequence tags that are differentially expressed in the same direction in both models. Most of these have not previously been implicated in mechanical hypersensitivity and may represent novel targets for therapeutic intervention. As an external control, the RNA expression of three genes was examined by RT-PCR, while the protein levels of two were studied using western blot analysis. PMID:18606552

Gene expression analysis of whole blood, peripheral blood mononuclear cells, and lymphoblastoid cell lines from the Framingham Heart Study

PubMed Central

Joehanes, Roby; Johnson, Andrew D.; Barb, Jennifer J.; Raghavachari, Nalini; Liu, Poching; Woodhouse, Kimberly A.; O'Donnell, Christopher J.; Munson, Peter J.

2012-01-01

Despite a growing number of reports of gene expression analysis from blood-derived RNA sources, there have been few systematic comparisons of various RNA sources in transcriptomic analysis or for biomarker discovery in the context of cardiovascular disease (CVD). As a pilot study of the Systems Approach to Biomarker Research (SABRe) in CVD Initiative, this investigation used Affymetrix Exon arrays to characterize gene expression of three blood-derived RNA sources: lymphoblastoid cell lines (LCL), whole blood using PAXgene tubes (PAX), and peripheral blood mononuclear cells (PBMC). Their performance was compared in relation to identifying transcript associations with sex and CVD risk factors, such as age, high-density lipoprotein, and smoking status, and the differential blood cell count. We also identified a set of exons that vary substantially between participants, but consistently in each RNA source. Such exons are thus stable phenotypes of the participant and may potentially become useful fingerprinting biomarkers. In agreement with previous studies, we found that each of the RNA sources is distinct. Unlike PAX and PBMC, LCL gene expression showed little association with the differential blood count. LCL, however, was able to detect two genes related to smoking status. PAX and PBMC identified Y-chromosome probe sets similarly and slightly better than LCL. PMID:22045913

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-01-01

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

Constraints on genes shape long-term conservation of macro-synteny in metazoan genomes.

PubMed

Lv, Jie; Havlak, Paul; Putnam, Nicholas H

2011-10-05

Many metazoan genomes conserve chromosome-scale gene linkage relationships ("macro-synteny") from the common ancestor of multicellular animal life 1234, but the biological explanation for this conservation is still unknown. Double cut and join (DCJ) is a simple, well-studied model of neutral genome evolution amenable to both simulation and mathematical analysis 5, but as we show here, it is not sufficent to explain long-term macro-synteny conservation. We examine a family of simple (one-parameter) extensions of DCJ to identify models and choices of parameters consistent with the levels of macro- and micro-synteny conservation observed among animal genomes. Our software implements a flexible strategy for incorporating genomic context into the DCJ model to incorporate various types of genomic context ("DCJ-[C]"), and is available as open source software from http://github.com/putnamlab/dcj-c. A simple model of genome evolution, in which DCJ moves are allowed only if they maintain chromosomal linkage among a set of constrained genes, can simultaneously account for the level of macro-synteny conservation and for correlated conservation among multiple pairs of species. Simulations under this model indicate that a constraint on approximately 7% of metazoan genes is sufficient to constrain genome rearrangement to an average rate of 25 inversions and 1.7 translocations per million years.

Smooth Muscle Cell Genome Browser: Enabling the Identification of Novel Serum Response Factor Target Genes

PubMed Central

Lee, Moon Young; Park, Chanjae; Berent, Robyn M.; Park, Paul J.; Fuchs, Robert; Syn, Hannah; Chin, Albert; Townsend, Jared; Benson, Craig C.; Redelman, Doug; Shen, Tsai-wei; Park, Jong Kun; Miano, Joseph M.; Sanders, Kenton M.; Ro, Seungil

2015-01-01

Genome-scale expression data on the absolute numbers of gene isoforms offers essential clues in cellular functions and biological processes. Smooth muscle cells (SMCs) perform a unique contractile function through expression of specific genes controlled by serum response factor (SRF), a transcription factor that binds to DNA sites known as the CArG boxes. To identify SRF-regulated genes specifically expressed in SMCs, we isolated SMC populations from mouse small intestine and colon, obtained their transcriptomes, and constructed an interactive SMC genome and CArGome browser. To our knowledge, this is the first online resource that provides a comprehensive library of all genetic transcripts expressed in primary SMCs. The browser also serves as the first genome-wide map of SRF binding sites. The browser analysis revealed novel SMC-specific transcriptional variants and SRF target genes, which provided new and unique insights into the cellular and biological functions of the cells in gastrointestinal (GI) physiology. The SRF target genes in SMCs, which were discovered in silico, were confirmed by proteomic analysis of SMC-specific Srf knockout mice. Our genome browser offers a new perspective into the alternative expression of genes in the context of SRF binding sites in SMCs and provides a valuable reference for future functional studies. PMID:26241044

Graphite Web: web tool for gene set analysis exploiting pathway topology

PubMed Central

Sales, Gabriele; Calura, Enrica; Martini, Paolo; Romualdi, Chiara

2013-01-01

Graphite web is a novel web tool for pathway analyses and network visualization for gene expression data of both microarray and RNA-seq experiments. Several pathway analyses have been proposed either in the univariate or in the global and multivariate context to tackle the complexity and the interpretation of expression results. These methods can be further divided into ‘topological’ and ‘non-topological’ methods according to their ability to gain power from pathway topology. Biological pathways are, in fact, not only gene lists but can be represented through a network where genes and connections are, respectively, nodes and edges. To this day, the most used approaches are non-topological and univariate although they miss the relationship among genes. On the contrary, topological and multivariate approaches are more powerful, but difficult to be used by researchers without bioinformatic skills. Here we present Graphite web, the first public web server for pathway analysis on gene expression data that combines topological and multivariate pathway analyses with an efficient system of interactive network visualizations for easy results interpretation. Specifically, Graphite web implements five different gene set analyses on three model organisms and two pathway databases. Graphite Web is freely available at http://graphiteweb.bio.unipd.it/. PMID:23666626

Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience

PubMed Central

Turm, Hagit; Mukherjee, Diptendu; Haritan, Doron; Tahor, Maayan; Citri, Ami

2014-01-01

The encoding of experiences in the brain and the consolidation of long-term memories depend on gene transcription. Identifying the function of specific genes in encoding experience is one of the main objectives of molecular neuroscience. Furthermore, the functional association of defined genes with specific behaviors has implications for understanding the basis of neuropsychiatric disorders. Induction of robust transcription programs has been observed in the brains of mice following various behavioral manipulations. While some genetic elements are utilized recurrently following different behavioral manipulations and in different brain nuclei, transcriptional programs are overall unique to the inducing stimuli and the structure in which they are studied1,2. In this publication, a protocol is described for robust and comprehensive transcriptional profiling from brain nuclei of mice in response to behavioral manipulation. The protocol is demonstrated in the context of analysis of gene expression dynamics in the nucleus accumbens following acute cocaine experience. Subsequent to a defined in vivo experience, the target neural tissue is dissected; followed by RNA purification, reverse transcription and utilization of microfluidic arrays for comprehensive qPCR analysis of multiple target genes. This protocol is geared towards comprehensive analysis (addressing 50-500 genes) of limiting quantities of starting material, such as small brain samples or even single cells. The protocol is most advantageous for parallel analysis of multiple samples (e.g. single cells, dynamic analysis following pharmaceutical, viral or behavioral perturbations). However, the protocol could also serve for the characterization and quality assurance of samples prior to whole-genome studies by microarrays or RNAseq, as well as validation of data obtained from whole-genome studies. PMID:25225819

BGDB: a database of bivalent genes

PubMed Central

Li, Qingyan; Lian, Shuabin; Dai, Zhiming; Xiang, Qian; Dai, Xianhua

2013-01-01

Bivalent gene is a gene marked with both H3K4me3 and H3K27me3 epigenetic modification in the same area, and is proposed to play a pivotal role related to pluripotency in embryonic stem (ES) cells. Identification of these bivalent genes and understanding their functions are important for further research of lineage specification and embryo development. So far, lots of genome-wide histone modification data were generated in mouse and human ES cells. These valuable data make it possible to identify bivalent genes, but no comprehensive data repositories or analysis tools are available for bivalent genes currently. In this work, we develop BGDB, the database of bivalent genes. The database contains 6897 bivalent genes in human and mouse ES cells, which are manually collected from scientific literature. Each entry contains curated information, including genomic context, sequences, gene ontology and other relevant information. The web services of BGDB database were implemented with PHP + MySQL + JavaScript, and provide diverse query functions. Database URL: http://dailab.sysu.edu.cn/bgdb/ PMID:23894186

A metabolomics-based method for studying the effect of yfcC gene in Escherichia coli on metabolism.

PubMed

Wang, Xiyue; Xie, Yuping; Gao, Peng; Zhang, Sufang; Tan, Haidong; Yang, Fengxu; Lian, Rongwei; Tian, Jing; Xu, Guowang

2014-04-15

Metabolomics is a potent tool to assist in identifying the function of unknown genes through analysis of metabolite changes in the context of varied genetic backgrounds. However, the availability of a universal unbiased profiling analysis is still a big challenge. In this study, we report an optimized metabolic profiling method based on gas chromatography-mass spectrometry for Escherichia coli. It was found that physiological saline at -80°C could ensure satisfied metabolic quenching with less metabolite leakage. A solution of methanol/water (21:79, v/v) was proved to be efficient for intracellular metabolite extraction. This method was applied to investigate the metabolome difference among wild-type E. coli, its yfcC deletion, and overexpression mutants. Statistical and bioinformatic analysis of the metabolic profiling data indicated that the expression of yfcC potentially affected the metabolism of glyoxylate shunt. This finding was further validated by real-time quantitative polymerase chain reactions showing that expression of aceA and aceB, the key genes in glyoxylate shunt, was upregulated by yfcC. This study exemplifies the robustness of the proposed metabolic profiling analysis strategy and its potential roles in investigating unknown gene functions in view of metabolome difference. Copyright © 2014 Elsevier Inc. All rights reserved.

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

ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis

PubMed Central

Han, Junwei; Shi, Xinrui; Zhang, Yunpeng; Xu, Yanjun; Jiang, Ying; Zhang, Chunlong; Feng, Li; Yang, Haixiu; Shang, Desi; Sun, Zeguo; Su, Fei; Li, Chunquan; Li, Xia

2015-01-01

Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Using real datasets from p53 mutation, Type 2 diabetes and lung cancer, we validate effectiveness of ESEA in identifying dysregulated pathways. We further compare our results with five other pathway enrichment analysis methods. With these analyses, we show that ESEA is able to help uncover dysregulated biological pathways underlying complex traits and human diseases via specific use of the dysregulated biological relationships. We develop a freely available R-based tool of ESEA. Currently, ESEA can support pathway analysis of the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther). PMID:26267116

Cogena, a novel tool for co-expressed gene-set enrichment analysis, applied to drug repositioning and drug mode of action discovery.

PubMed

Jia, Zhilong; Liu, Ying; Guan, Naiyang; Bo, Xiaochen; Luo, Zhigang; Barnes, Michael R

2016-05-27

Drug repositioning, finding new indications for existing drugs, has gained much recent attention as a potentially efficient and economical strategy for accelerating new therapies into the clinic. Although improvement in the sensitivity of computational drug repositioning methods has identified numerous credible repositioning opportunities, few have been progressed. Arguably the "black box" nature of drug action in a new indication is one of the main blocks to progression, highlighting the need for methods that inform on the broader target mechanism in the disease context. We demonstrate that the analysis of co-expressed genes may be a critical first step towards illumination of both disease pathology and mode of drug action. We achieve this using a novel framework, co-expressed gene-set enrichment analysis (cogena) for co-expression analysis of gene expression signatures and gene set enrichment analysis of co-expressed genes. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to illuminate coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework. We illustrate this using a psoriatic skin transcriptome, as an exemplar, and recover two widely used Psoriasis drugs (Methotrexate and Ciclosporin) with distinct modes of action. Cogena out-performs the results of Connectivity Map and NFFinder webservers in similar disease transcriptome analyses. Furthermore, we investigated the literature support for the other top-ranked compounds to treat psoriasis and showed how the outputs of cogena analysis can contribute new insight to support the progression of drugs into the clinic. We have made cogena freely available within Bioconductor or https://github.com/zhilongjia/cogena . In conclusion, by targeting co-expressed genes within disease transcriptomes, cogena offers novel biological insight, which can be effectively harnessed for drug discovery and repositioning, allowing the grouping and prioritisation of drug repositioning candidates on the basis of putative mode of action.

Analyzing the Role of MicroRNAs in Schizophrenia in the Context of Common Genetic Risk Variants.

PubMed

Hauberg, Mads Engel; Roussos, Panos; Grove, Jakob; Børglum, Anders Dupont; Mattheisen, Manuel

2016-04-01

The recent implication of 108 genomic loci in schizophrenia marked a great advancement in our understanding of the disease. Against the background of its polygenic nature there is a necessity to identify how schizophrenia risk genes interplay. As regulators of gene expression, microRNAs (miRNAs) have repeatedly been implicated in schizophrenia etiology. It is therefore of interest to establish their role in the regulation of schizophrenia risk genes in disease-relevant biological processes. To examine the role of miRNAs in schizophrenia in the context of disease-associated genetic variation. The basis of this study was summary statistics from the largest schizophrenia genome-wide association study meta-analysis to date (83 550 individuals in a meta-analysis of 52 genome-wide association studies) completed in 2014 along with publicly available data for predicted miRNA targets. We examined whether schizophrenia risk genes were more likely to be regulated by miRNA. Further, we used gene set analyses to identify miRNAs that are regulators of schizophrenia risk genes. Results from association tests for miRNA targetomes and related analyses. In line with previous studies, we found that similar to other complex traits, schizophrenia risk genes were more likely to be regulated by miRNAs (P < 2 × 10-16). Further, the gene set analyses revealed several miRNAs regulating schizophrenia risk genes, with the strongest enrichment for targets of miR-9-5p (P = .0056 for enrichment among the top 1% most-associated single-nucleotide polymorphisms, corrected for multiple testing). It is further of note that MIR9-2 is located in a genomic region showing strong evidence for association with schizophrenia (P = 7.1 × 10-8). The second and third strongest gene set signals were seen for the targets of miR-485-5p and miR-137, respectively. This study provides evidence for a role of miR-9-5p in the etiology of schizophrenia. Its implication is of particular interest as the functions of this neurodevelopmental miRNA tie in with established disease biology: it has a regulatory loop with the fragile X mental retardation homologue FXR1 and regulates dopamine D2 receptor density.

Discrimination between cocaine-associated context and cue in a modified conditioned place preference paradigm: role of the nNOS gene in cue conditioning.

PubMed

Itzhak, Yossef; Roger-Sánchez, Concepción; Kelley, Jonathan B; Anderson, Karen L

2010-03-01

The conditioned place preference (CPP) paradigm entails appetitive learning and is utilized to investigate the motivational effects of drug and natural reward in rodents. However, a typical CPP design does not allow dissociation between cue- and context-dependent appetitive learning. In humans, context and cues that had been associated with drug reward can elicit conditioned response and drug craving. Therefore, we investigated (a) methods by which to discriminate between cue- and context-dependent appetitive learning, and (b) the role of the neuronal nitric oxide synthase (nNOS) gene in appetitive learning. Wild-type (WT) and nNOS knockout (KO) mice were trained by cocaine (20 mg/kg) in a discrete context paired with a light cue (a compound context-cue stimulus). In test 1, approach behaviour to either the training context or to the cue in a novel context was determined. WT mice showed robust preference for both cocaine-associated context and cue. nNOS KO mice acquired approach behaviour for the cocaine-associated context but not cue. This finding suggests that the nNOS gene is required for cue-dependent appetitive learning. On the following day (test 2), mice were tested for approach behaviour to the compound context-cue stimulus. Context but not cue exposure in test 1 reduced approach behaviour to the compound context-cue stimulus in test 2, suggesting that repeated context but not cue exposures diminished the conditioned response. Hence, this modified CPP paradigm is useful for the investigation of approach behaviour for both drug-associated context and cue, and allows further investigation of mechanisms underlying cue- and context-dependent appetitive learning.

Inferring causal genomic alterations in breast cancer using gene expression data

PubMed Central

2011-01-01

Background One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies. Results We developed a framework for identifying recurrent regions of CNV and distinguishing the cancer driver genes from the passenger genes in the regions. By inferring CNV regions across many datasets we were able to identify 109 recurrent amplified/deleted CNV regions. Many of these regions are enriched for genes involved in many important processes associated with tumorigenesis and cancer progression. Genes in these recurrent CNV regions were then examined in the context of gene regulatory networks to prioritize putative cancer driver genes. The cancer driver genes uncovered by the framework include not only well-known oncogenes but also a number of novel cancer susceptibility genes validated via siRNA experiments. Conclusions To our knowledge, this is the first effort to systematically identify and validate drivers for expression based CNV regions in breast cancer. The framework where the wavelet analysis of copy number alteration based on expression coupled with the gene regulatory network analysis, provides a blueprint for leveraging genomic data to identify key regulatory components and gene targets. This integrative approach can be applied to many other large-scale gene expression studies and other novel types of cancer data such as next-generation sequencing based expression (RNA-Seq) as well as CNV data. PMID:21806811

Molecular definition of the identity and activation of natural killer cells.

PubMed

Bezman, Natalie A; Kim, Charles C; Sun, Joseph C; Min-Oo, Gundula; Hendricks, Deborah W; Kamimura, Yosuke; Best, J Adam; Goldrath, Ananda W; Lanier, Lewis L

2012-10-01

Using whole-genome microarray data sets of the Immunological Genome Project, we demonstrate a closer transcriptional relationship between NK cells and T cells than between any other leukocytes, distinguished by their shared expression of genes encoding molecules with similar signaling functions. Whereas resting NK cells are known to share expression of a few genes with cytotoxic CD8(+) T cells, our transcriptome-wide analysis demonstrates that the commonalities extend to hundreds of genes, many encoding molecules with unknown functions. Resting NK cells demonstrate a 'preprimed' state compared with naive T cells, which allows NK cells to respond more rapidly to viral infection. Collectively, our data provide a global context for known and previously unknown molecular aspects of NK cell identity and function by delineating the genome-wide repertoire of gene expression of NK cells in various states.

Improved detection of overrepresentation of Gene-Ontology annotations with parent child analysis.

PubMed

Grossmann, Steffen; Bauer, Sebastian; Robinson, Peter N; Vingron, Martin

2007-11-15

High-throughput experiments such as microarray hybridizations often yield long lists of genes found to share a certain characteristic such as differential expression. Exploring Gene Ontology (GO) annotations for such lists of genes has become a widespread practice to get first insights into the potential biological meaning of the experiment. The standard statistical approach to measuring overrepresentation of GO terms cannot cope with the dependencies resulting from the structure of GO because they analyze each term in isolation. Especially the fact that annotations are inherited from more specific descendant terms can result in certain types of false-positive results with potentially misleading biological interpretation, a phenomenon which we term the inheritance problem. We present here a novel approach to analysis of GO term overrepresentation that determines overrepresentation of terms in the context of annotations to the term's parents. This approach reduces the dependencies between the individual term's measurements, and thereby avoids producing false-positive results owing to the inheritance problem. ROC analysis using study sets with overrepresented GO terms showed a clear advantage for our approach over the standard algorithm with respect to the inheritance problem. Although there can be no gold standard for exploratory methods such as analysis of GO term overrepresentation, analysis of biological datasets suggests that our algorithm tends to identify the core GO terms that are most characteristic of the dataset being analyzed.

Rationalizing context-dependent performance of dynamic RNA regulatory devices.

PubMed

Kent, Ross; Halliwell, Samantha; Young, Kate; Swainston, Neil; Dixon, Neil

2018-06-21

The ability of RNA to sense, regulate and store information is an attractive attribute for a variety of functional applications including the development of regulatory control devices for synthetic biology. RNA folding and function is known to be highly context sensitive, which limits the modularity and reuse of RNA regulatory devices to control different heterologous sequences and genes. We explored the cause and effect of sequence context sensitivity for translational ON riboswitches located in the 5' UTR, by constructing and screening a library of N-terminal synonymous codon variants. By altering the N-terminal codon usage we were able to obtain RNA devices with a broad range of functional performance properties (ON, OFF, fold-change). Linear regression and calculated metrics were used to rationalize the major determining features leading to optimal riboswitch performance, and to identify multiple interactions between the explanatory metrics. Finally, partial least squared (PLS) analysis was employed in order to understand the metrics and their respective effect on performance. This PLS model was shown to provide good explanation of our library. This study provides a novel multi-variant analysis framework by which to rationalize the codon context performance of allosteric RNA-devices. The framework will also serve as a platform for future riboswitch context engineering endeavors.

The Sorghum bicolor genome and the diversification of grasses

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

Paterson, Andrew H.; Bowers, John E.; Bruggmann, Remy

2008-08-20

Sorghum, an African grass related to sugar cane and maize, is grown for food, feed, fibre and fuel. We present an initial analysis of the approx730-megabase Sorghum bicolor (L.) Moench genome, placing approx98percent of genes in their chromosomal context using whole-genome shotgun sequence validated by genetic, physical and syntenic information. Genetic recombination is largely confined to about one-third of the sorghum genome with gene order and density similar to those of rice. Retrotransposon accumulation in recombinationally recalcitrant heterochromatin explains the approx75percent larger genome size of sorghum compared with rice. Although gene and repetitive DNA distributions have been preserved since palaeopolyploidizationmore » approx70 million years ago, most duplicated gene sets lost one member before the sorghum rice divergence. Concerted evolution makes one duplicated chromosomal segment appear to be only a few million years old. About 24percent of genes are grass-specific and 7percent are sorghum-specific. Recent gene and microRNA duplications may contribute to sorghum's drought tolerance.« less

The Sorghum bicolor genome and the diversification of grasses.

PubMed

Paterson, Andrew H; Bowers, John E; Bruggmann, Rémy; Dubchak, Inna; Grimwood, Jane; Gundlach, Heidrun; Haberer, Georg; Hellsten, Uffe; Mitros, Therese; Poliakov, Alexander; Schmutz, Jeremy; Spannagl, Manuel; Tang, Haibao; Wang, Xiyin; Wicker, Thomas; Bharti, Arvind K; Chapman, Jarrod; Feltus, F Alex; Gowik, Udo; Grigoriev, Igor V; Lyons, Eric; Maher, Christopher A; Martis, Mihaela; Narechania, Apurva; Otillar, Robert P; Penning, Bryan W; Salamov, Asaf A; Wang, Yu; Zhang, Lifang; Carpita, Nicholas C; Freeling, Michael; Gingle, Alan R; Hash, C Thomas; Keller, Beat; Klein, Patricia; Kresovich, Stephen; McCann, Maureen C; Ming, Ray; Peterson, Daniel G; Mehboob-ur-Rahman; Ware, Doreen; Westhoff, Peter; Mayer, Klaus F X; Messing, Joachim; Rokhsar, Daniel S

2009-01-29

Sorghum, an African grass related to sugar cane and maize, is grown for food, feed, fibre and fuel. We present an initial analysis of the approximately 730-megabase Sorghum bicolor (L.) Moench genome, placing approximately 98% of genes in their chromosomal context using whole-genome shotgun sequence validated by genetic, physical and syntenic information. Genetic recombination is largely confined to about one-third of the sorghum genome with gene order and density similar to those of rice. Retrotransposon accumulation in recombinationally recalcitrant heterochromatin explains the approximately 75% larger genome size of sorghum compared with rice. Although gene and repetitive DNA distributions have been preserved since palaeopolyploidization approximately 70 million years ago, most duplicated gene sets lost one member before the sorghum-rice divergence. Concerted evolution makes one duplicated chromosomal segment appear to be only a few million years old. About 24% of genes are grass-specific and 7% are sorghum-specific. Recent gene and microRNA duplications may contribute to sorghum's drought tolerance.

Activation of silenced cytokine gene promoters by the synergistic effect of TBP-TALE and VP64-TALE activators.

PubMed

Anthony, Kim; More, Abhijit; Zhang, Xiaoliu

2014-01-01

Recent work has shown that the combinatorial use of multiple TALE activators can selectively activate certain cellular genes in inaccessible chromatin regions. In this study, we aimed to interrogate the activation potential of TALEs upon transcriptionally silenced immune genes in the context of non-immune cells. We designed a unique strategy, in which a single TALE fused to the TATA-box binding protein (TBP-TALE) is coupled with multiple VP64-TALE activators. We found that our strategy is significantly more potent than multiple TALE activators alone in activating expression of IL-2 and GM-CSF in diverse cell origins in which both genes are otherwise completely silenced. Chromatin analysis revealed that the gene activation was due in part to displacement of a distinctly positioned nucleosome. These studies provide a novel epigenetic mechanism for artificial gene induction and have important implications for targeted cancer immunotherapy, DNA vaccine development, as well as rational design of TALE activators.

Activation of Silenced Cytokine Gene Promoters by the Synergistic Effect of TBP-TALE and VP64-TALE Activators

PubMed Central

Anthony, Kim; More, Abhijit; Zhang, Xiaoliu

2014-01-01

Recent work has shown that the combinatorial use of multiple TALE activators can selectively activate certain cellular genes in inaccessible chromatin regions. In this study, we aimed to interrogate the activation potential of TALEs upon transcriptionally silenced immune genes in the context of non-immune cells. We designed a unique strategy, in which a single TALE fused to the TATA-box binding protein (TBP-TALE) is coupled with multiple VP64-TALE activators. We found that our strategy is significantly more potent than multiple TALE activators alone in activating expression of IL-2 and GM-CSF in diverse cell origins in which both genes are otherwise completely silenced. Chromatin analysis revealed that the gene activation was due in part to displacement of a distinctly positioned nucleosome. These studies provide a novel epigenetic mechanism for artificial gene induction and have important implications for targeted cancer immunotherapy, DNA vaccine development, as well as rational design of TALE activators. PMID:24755922

From Biophysics to Evolutionary Genetics: Statistical Aspects of Gene Regulation

NASA Astrophysics Data System (ADS)

Lässig, Michael

Genomic functions often cannot be understood at the level of single genes but require the study of gene networks. This systems biology credo is nearly commonplace by now. Evidence comes from the comparative analysis of entire genomes: current estimates put, for example, the number of human genes at around 22,000, hardly more than the 14,000 of the fruit fly, and not even an order of magnitude higher than the 6,000 of baker's yeast. The complexity and diversity of higher animals, therefore, cannot be explained in terms of their gene numbers. If, however, a biological function requires the concerted action of several genes, and conversely, a gene takes part in several functional contexts, an organism may be defined less by its individual genes but by their interactions. The emerging picture of the genome as a strongly interacting system with many degrees of freedom brings new challenges for experiment and theory, many of which are of a statistical nature. And indeed, this picture continues to make the subject attractive to a growing number of statistical physicists.

Updated regulation curation model at the Saccharomyces Genome Database

PubMed Central

Engel, Stacia R; Skrzypek, Marek S; Hellerstedt, Sage T; Wong, Edith D; Nash, Robert S; Weng, Shuai; Binkley, Gail; Sheppard, Travis K; Karra, Kalpana; Cherry, J Michael

2018-01-01

Abstract The Saccharomyces Genome Database (SGD) provides comprehensive, integrated biological information for the budding yeast Saccharomyces cerevisiae, along with search and analysis tools to explore these data, enabling the discovery of functional relationships between sequence and gene products in fungi and higher organisms. We have recently expanded our data model for regulation curation to address regulation at the protein level in addition to transcription, and are presenting the expanded data on the ‘Regulation’ pages at SGD. These pages include a summary describing the context under which the regulator acts, manually curated and high-throughput annotations showing the regulatory relationships for that gene and a graphical visualization of its regulatory network and connected networks. For genes whose products regulate other genes or proteins, the Regulation page includes Gene Ontology enrichment analysis of the biological processes in which those targets participate. For DNA-binding transcription factors, we also provide other information relevant to their regulatory function, such as DNA binding site motifs and protein domains. As with other data types at SGD, all regulatory relationships and accompanying data are available through YeastMine, SGD’s data warehouse based on InterMine. Database URL: http://www.yeastgenome.org PMID:29688362

Gene networks and developmental context: the importance of understanding complex gene expression patterns in evolution.

PubMed

Signor, Sarah A; Arbeitman, Michelle N; Nuzhdin, Sergey V

2016-05-01

Animal development is the product of distinct components and interactions-genes, regulatory networks, and cells-and it exhibits emergent properties that cannot be inferred from the components in isolation. Often the focus is on the genotype-to-phenotype map, overlooking the process of development that turns one into the other. We propose a move toward micro-evolutionary analysis of development, incorporating new tools that enable cell type resolution and single-cell microscopy. Using the sex determination pathway in Drosophila to illustrate potential avenues of research, we highlight some of the questions that these emerging technologies can address. For example, they provide an unprecedented opportunity to study heterogeneity within cell populations, and the potential to add the dimension of time to gene regulatory network analysis. Challenges still remain in developing methods to analyze this data and to increase the throughput. However this line of research has the potential to bridge the gaps between previously more disparate fields, such as population genetics and development, opening up new avenues of research. © 2016 Wiley Periodicals, Inc.

Codon usage bias reveals genomic adaptations to environmental conditions in an acidophilic consortium.

PubMed

Hart, Andrew; Cortés, María Paz; Latorre, Mauricio; Martinez, Servet

2018-01-01

The analysis of codon usage bias has been widely used to characterize different communities of microorganisms. In this context, the aim of this work was to study the codon usage bias in a natural consortium of five acidophilic bacteria used for biomining. The codon usage bias of the consortium was contrasted with genes from an alternative collection of acidophilic reference strains and metagenome samples. Results indicate that acidophilic bacteria preferentially have low codon usage bias, consistent with both their capacity to live in a wide range of habitats and their slow growth rate, a characteristic probably acquired independently from their phylogenetic relationships. In addition, the analysis showed significant differences in the unique sets of genes from the autotrophic species of the consortium in relation to other acidophilic organisms, principally in genes which code for proteins involved in metal and oxidative stress resistance. The lower values of codon usage bias obtained in this unique set of genes suggest higher transcriptional adaptation to living in extreme conditions, which was probably acquired as a measure for resisting the elevated metal conditions present in the mine.

Systems Genetics Reveals the Functional Context of PCOS Loci and Identifies Genetic and Molecular Mechanisms of Disease Heterogeneity.

PubMed

Jones, Michelle R; Brower, Meredith A; Xu, Ning; Cui, Jinrui; Mengesha, Emebet; Chen, Yii-Der I; Taylor, Kent D; Azziz, Ricardo; Goodarzi, Mark O

2015-08-01

Genome wide association studies (GWAS) have revealed 11 independent risk loci for polycystic ovary syndrome (PCOS), a common disorder in young women characterized by androgen excess and oligomenorrhea. To put these risk loci and the single nucleotide polymorphisms (SNPs) therein into functional context, we measured DNA methylation and gene expression in subcutaneous adipose tissue biopsies to identify PCOS-specific alterations. Two genes from the LHCGR region, STON1-GTF2A1L and LHCGR, were overexpressed in PCOS. In analysis stratified by obesity, LHCGR was overexpressed only in non-obese PCOS women. Although not differentially expressed in the entire PCOS group, INSR was underexpressed in obese PCOS subjects only. Alterations in gene expression in the LHCGR, RAB5B and INSR regions suggest that SNPs in these loci may be functional and could affect gene expression directly or indirectly via epigenetic alterations. We identified reduced methylation in the LHCGR locus and increased methylation in the INSR locus, changes that are concordant with the altered gene expression profiles. Complex patterns of meQTL and eQTL were identified in these loci, suggesting that local genetic variation plays an important role in gene regulation. We propose that non-obese PCOS women possess significant alterations in LH receptor expression, which drives excess androgen secretion from the ovary. Alternatively, obese women with PCOS possess alterations in insulin receptor expression, with underexpression in metabolic tissues and overexpression in the ovary, resulting in peripheral insulin resistance and excess ovarian androgen production. These studies provide a genetic and molecular basis for the reported clinical heterogeneity of PCOS.

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

Gene regulatory networks in lactation: identification of global principles using bioinformatics.

PubMed

Lemay, Danielle G; Neville, Margaret C; Rudolph, Michael C; Pollard, Katherine S; German, J Bruce

2007-11-27

The molecular events underlying mammary development during pregnancy, lactation, and involution are incompletely understood. Mammary gland microarray data, cellular localization data, protein-protein interactions, and literature-mined genes were integrated and analyzed using statistics, principal component analysis, gene ontology analysis, pathway analysis, and network analysis to identify global biological principles that govern molecular events during pregnancy, lactation, and involution. Several key principles were derived: (1) nearly a third of the transcriptome fluctuates to build, run, and disassemble the lactation apparatus; (2) genes encoding the secretory machinery are transcribed prior to lactation; (3) the diversity of the endogenous portion of the milk proteome is derived from fewer than 100 transcripts; (4) while some genes are differentially transcribed near the onset of lactation, the lactation switch is primarily post-transcriptionally mediated; (5) the secretion of materials during lactation occurs not by up-regulation of novel genomic functions, but by widespread transcriptional suppression of functions such as protein degradation and cell-environment communication; (6) the involution switch is primarily transcriptionally mediated; and (7) during early involution, the transcriptional state is partially reverted to the pre-lactation state. A new hypothesis for secretory diminution is suggested - milk production gradually declines because the secretory machinery is not transcriptionally replenished. A comprehensive network of protein interactions during lactation is assembled and new regulatory gene targets are identified. Less than one fifth of the transcriptionally regulated nodes in this lactation network have been previously explored in the context of lactation. Implications for future research in mammary and cancer biology are discussed.

LENS: web-based lens for enrichment and network studies of human proteins

PubMed Central

2015-01-01

Background Network analysis is a common approach for the study of genetic view of diseases and biological pathways. Typically, when a set of genes are identified to be of interest in relation to a disease, say through a genome wide association study (GWAS) or a different gene expression study, these genes are typically analyzed in the context of their protein-protein interaction (PPI) networks. Further analysis is carried out to compute the enrichment of known pathways and disease-associations in the network. Having tools for such analysis at the fingertips of biologists without the requirement for computer programming or curation of data would accelerate the characterization of genes of interest. Currently available tools do not integrate network and enrichment analysis and their visualizations, and most of them present results in formats not most conducive to human cognition. Results We developed the tool Lens for Enrichment and Network Studies of human proteins (LENS) that performs network and pathway and diseases enrichment analyses on genes of interest to users. The tool creates a visualization of the network, provides easy to read statistics on network connectivity, and displays Venn diagrams with statistical significance values of the network's association with drugs, diseases, pathways, and GWASs. We used the tool to analyze gene sets related to craniofacial development, autism, and schizophrenia. Conclusion LENS is a web-based tool that does not require and download or plugins to use. The tool is free and does not require login for use, and is available at http://severus.dbmi.pitt.edu/LENS. PMID:26680011

A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis

PubMed Central

Ni, Ying; Aghamirzaie, Delasa; Elmarakeby, Haitham; Collakova, Eva; Li, Song; Grene, Ruth; Heath, Lenwood S.

2016-01-01

Gene regulatory networks (GRNs) provide a representation of relationships between regulators and their target genes. Several methods for GRN inference, both unsupervised and supervised, have been developed to date. Because regulatory relationships consistently reprogram in diverse tissues or under different conditions, GRNs inferred without specific biological contexts are of limited applicability. In this report, a machine learning approach is presented to predict GRNs specific to developing Arabidopsis thaliana embryos. We developed the Beacon GRN inference tool to predict GRNs occurring during seed development in Arabidopsis based on a support vector machine (SVM) model. We developed both global and local inference models and compared their performance, demonstrating that local models are generally superior for our application. Using both the expression levels of the genes expressed in developing embryos and prior known regulatory relationships, GRNs were predicted for specific embryonic developmental stages. The targets that are strongly positively correlated with their regulators are mostly expressed at the beginning of seed development. Potential direct targets were identified based on a match between the promoter regions of these inferred targets and the cis elements recognized by specific regulators. Our analysis also provides evidence for previously unknown inhibitory effects of three positive regulators of gene expression. The Beacon GRN inference tool provides a valuable model system for context-specific GRN inference and is freely available at https://github.com/BeaconProjectAtVirginiaTech/beacon_network_inference.git. PMID:28066488

Gene patents still alive and kicking: their impact on provision of genetic testing for long QT syndrome in the Canadian public health-care system

PubMed Central

Ali-Khan, Sarah E; Gold, E Richard

2017-01-01

Purpose Although the Supreme Court of the United States limited their availability in Association for Molecular Pathology v. Myriad Genetics, gene patents remain important around the world. We examine the situation in Canada, where gene patents continue to exist, in light of recent litigation relating to familial long QT syndrome (LQTS). Methods We conducted in-depth semistructured interviews with 25 stakeholders across five Canadian provinces and supplemented this with a case analysis of the litigation. Results The majority of LQTS testing was carried out outside Canada. Rising costs prompted several provinces to attempt to repatriate testing. However, LQTS gene patents stymied efforts, particularly in provinces where testing was more centralized, increasing costs and lowering innovation. It was in this context that a hospital launched a test case against the LQTS patents, resulting in a novel agreement to free Canadian hospitals from the effects of patents. Conclusion Our analysis reveals a rapidly evolving genetic test provision landscape under pressure from gene patents, strained budgets and poor collaboration. The litigation resulted in a blueprint for free public use of gene patents throughout Canada's health-care system, but it will only have value if governments are proactive in its use. PMID:28492533

Transcriptome-wide analysis of alternative RNA splicing events in Epstein-Barr virus-associated gastric carcinomas

PubMed Central

Armero, Victoria E. S.; Tremblay, Marie-Pier; Allaire, Andréa; Boudreault, Simon; Martenon-Brodeur, Camille; Duval, Cyntia; Durand, Mathieu; Lapointe, Elvy; Thibault, Philippe; Tremblay-Létourneau, Maude; Perreault, Jean-Pierre; Scott, Michelle S.

2017-01-01

Multiple human diseases including cancer have been associated with a dysregulation in RNA splicing patterns. In the current study, modifications to the global RNA splicing landscape of cellular genes were investigated in the context of Epstein-Barr virus-associated gastric cancer. Global alterations to the RNA splicing landscape of cellular genes was examined in a large-scale screen from 295 primary gastric adenocarcinomas using high-throughput RNA sequencing data. RT-PCR analysis, mass spectrometry, and co-immunoprecipitation studies were also used to experimentally validate and investigate the differential alternative splicing (AS) events that were observed through RNA-seq studies. Our study identifies alterations in the AS patterns of approximately 900 genes such as tumor suppressor genes, transcription factors, splicing factors, and kinases. These findings allowed the identification of unique gene signatures for which AS is misregulated in both Epstein-Barr virus-associated gastric cancer and EBV-negative gastric cancer. Moreover, we show that the expression of Epstein–Barr nuclear antigen 1 (EBNA1) leads to modifications in the AS profile of cellular genes and that the EBNA1 protein interacts with cellular splicing factors. These findings provide insights into the molecular differences between various types of gastric cancer and suggest a role for the EBNA1 protein in the dysregulation of cellular AS. PMID:28493890

Transcriptome-wide analysis of alternative RNA splicing events in Epstein-Barr virus-associated gastric carcinomas.

PubMed

Armero, Victoria E S; Tremblay, Marie-Pier; Allaire, Andréa; Boudreault, Simon; Martenon-Brodeur, Camille; Duval, Cyntia; Durand, Mathieu; Lapointe, Elvy; Thibault, Philippe; Tremblay-Létourneau, Maude; Perreault, Jean-Pierre; Scott, Michelle S; Bisaillon, Martin

2017-01-01

Multiple human diseases including cancer have been associated with a dysregulation in RNA splicing patterns. In the current study, modifications to the global RNA splicing landscape of cellular genes were investigated in the context of Epstein-Barr virus-associated gastric cancer. Global alterations to the RNA splicing landscape of cellular genes was examined in a large-scale screen from 295 primary gastric adenocarcinomas using high-throughput RNA sequencing data. RT-PCR analysis, mass spectrometry, and co-immunoprecipitation studies were also used to experimentally validate and investigate the differential alternative splicing (AS) events that were observed through RNA-seq studies. Our study identifies alterations in the AS patterns of approximately 900 genes such as tumor suppressor genes, transcription factors, splicing factors, and kinases. These findings allowed the identification of unique gene signatures for which AS is misregulated in both Epstein-Barr virus-associated gastric cancer and EBV-negative gastric cancer. Moreover, we show that the expression of Epstein-Barr nuclear antigen 1 (EBNA1) leads to modifications in the AS profile of cellular genes and that the EBNA1 protein interacts with cellular splicing factors. These findings provide insights into the molecular differences between various types of gastric cancer and suggest a role for the EBNA1 protein in the dysregulation of cellular AS.

Tissue-enriched expression profiles in Aedes aegypti identify hemocyte-specific transcriptome responses to infection

PubMed Central

Choi, Young-Jun; Fuchs, Jeremy F.; Mayhew, George F.; Yu, Helen E.; Christensen, Bruce M.

2012-01-01

Hemocytes are integral components of mosquito immune mechanisms such as phagocytosis, melanization, and production of antimicrobial peptides. However, our understanding of hemocyte-specific molecular processes and their contribution to shaping the host immune response remains limited. To better understand the immunophysiological features distinctive of hemocytes, we conducted genome-wide analysis of hemocyte-enriched transcripts, and examined how tissue-enriched expression patterns change with the immune status of the host. Our microarray data indicate that the hemocyte-enriched trascriptome is dynamic and context-dependent. Analysis of transcripts enriched after bacterial challenge in circulating hemocytes with respect to carcass added a dimension to evaluating infection-responsive genes and immune-related gene families. We resolved patterns of transcriptional change unique to hemocytes from those that are likely shared by other immune responsive tissues, and identified clusters of genes preferentially induced in hemocytes, likely reflecting their involvement in cell type specific functions. In addition, the study revealed conserved hemocyte-enriched molecular repertoires which might be implicated in core hemocyte function by cross-species meta-analysis of microarray expression data from Anopheles gambiae and Drosophila melanogaster. PMID:22796331

Gene regulatory networks: a coarse-grained, equation-free approach to multiscale computation.

PubMed

Erban, Radek; Kevrekidis, Ioannis G; Adalsteinsson, David; Elston, Timothy C

2006-02-28

We present computer-assisted methods for analyzing stochastic models of gene regulatory networks. The main idea that underlies this equation-free analysis is the design and execution of appropriately initialized short bursts of stochastic simulations; the results of these are processed to estimate coarse-grained quantities of interest, such as mesoscopic transport coefficients. In particular, using a simple model of a genetic toggle switch, we illustrate the computation of an effective free energy Phi and of a state-dependent effective diffusion coefficient D that characterize an unavailable effective Fokker-Planck equation. Additionally we illustrate the linking of equation-free techniques with continuation methods for performing a form of stochastic "bifurcation analysis"; estimation of mean switching times in the case of a bistable switch is also implemented in this equation-free context. The accuracy of our methods is tested by direct comparison with long-time stochastic simulations. This type of equation-free analysis appears to be a promising approach to computing features of the long-time, coarse-grained behavior of certain classes of complex stochastic models of gene regulatory networks, circumventing the need for long Monte Carlo simulations.

1,25-dihydroxyvitamin D3 is an autonomous regulator of the transcriptional changes leading to a tolerogenic dendritic cell phenotype.

PubMed

Széles, Lajos; Keresztes, Gábor; Töröcsik, Dániel; Balajthy, Zoltán; Krenács, László; Póliska, Szilárd; Steinmeyer, Andreas; Zuegel, Ulrich; Pruenster, Monika; Rot, Antal; Nagy, László

2009-02-15

Activation of vitamin D receptor (VDR) by 1,25-dihydroxyvitamin D(3) (1,25-vitD) reprograms dendritic cells (DC) to become tolerogenic. Previous studies suggested that 1,25-vitD could inhibit the changes brought about by differentiation and maturation of DCs. Underpinning the described phenotypic and functional alterations, there must be 1,25-vitD-coordinated transcriptional events. However, this transcriptional program has not been systematically investigated, particularly not in a developmental context. Hence, it has not been explored how 1,25-vitD-regulated genes, particularly the ones bringing about the tolerogenic phenotype, are connected to differentiation. We conducted global gene expression analysis followed by comprehensive quantitative PCR validation to clarify the interrelationship between 1,25-vitD and differentiation-driven gene expression patterns in developing human monocyte-derived and blood myeloid DCs. In this study we show that 1,25-vitD regulates a large set of genes that are not affected by differentiation. Interestingly, several genes, impacted both by the ligand and by differentiation, appear to be regulated by 1,25-vitD independently of the developmental context. We have also characterized the kinetics of generation of 1,25-vitD by using three early and robustly regulated genes, the chemokine CCL22, the inhibitory receptors CD300LF and CYP24A1. We found that monocyte-derived DCs are able to turn on 1,25-vitD sensitive genes in early phases of differentiation if the precursor is present. Our data collectively suggest that exogenous or endogenously generated 1,25-vitD regulates a large set of its targets autonomously and not via inhibition of differentiation and maturation, leading to the previously characterized tolerogenic state.

ISAAC - InterSpecies Analysing Application using Containers.

PubMed

Baier, Herbert; Schultz, Jörg

2014-01-15

Information about genes, transcripts and proteins is spread over a wide variety of databases. Different tools have been developed using these databases to identify biological signals in gene lists from large scale analysis. Mostly, they search for enrichments of specific features. But, these tools do not allow an explorative walk through different views and to change the gene lists according to newly upcoming stories. To fill this niche, we have developed ISAAC, the InterSpecies Analysing Application using Containers. The central idea of this web based tool is to enable the analysis of sets of genes, transcripts and proteins under different biological viewpoints and to interactively modify these sets at any point of the analysis. Detailed history and snapshot information allows tracing each action. Furthermore, one can easily switch back to previous states and perform new analyses. Currently, sets can be viewed in the context of genomes, protein functions, protein interactions, pathways, regulation, diseases and drugs. Additionally, users can switch between species with an automatic, orthology based translation of existing gene sets. As todays research usually is performed in larger teams and consortia, ISAAC provides group based functionalities. Here, sets as well as results of analyses can be exchanged between members of groups. ISAAC fills the gap between primary databases and tools for the analysis of large gene lists. With its highly modular, JavaEE based design, the implementation of new modules is straight forward. Furthermore, ISAAC comes with an extensive web-based administration interface including tools for the integration of third party data. Thus, a local installation is easily feasible. In summary, ISAAC is tailor made for highly explorative interactive analyses of gene, transcript and protein sets in a collaborative environment.

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

PubMed

Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

2015-09-01

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

Global analysis of gene expression in maize leaves treated with low temperature. II. Combined effect of severe cold (8 °C) and circadian rhythm.

PubMed

Jończyk, M; Sobkowiak, A; Trzcinska-Danielewicz, J; Skoneczny, M; Solecka, D; Fronk, J; Sowiński, P

2017-10-01

In maize seedlings, severe cold results in dysregulation of circadian pattern of gene expression causing profound modulation of transcription of genes related to photosynthesis and other key biological processes. Plants live highly cyclic life and their response to environmental stresses must allow for underlying biological rhythms. To study the interplay of a stress and a rhythmic cue we investigated transcriptomic response of maize seedlings to low temperature in the context of diurnal gene expression. Severe cold stress had pronounced effect on the circadian rhythm of a substantial proportion of genes. Their response was strikingly dual, comprising either flattening (partial or complete) of the diel amplitude or delay of expression maximum/minimum by several hours. Genes encoding central oscillator components behaved in the same dual manner, unlike their Arabidopsis counterparts reported earlier to cease cycling altogether upon cold treatment. Also numerous genes lacking circadian rhythm responded to the cold by undergoing up- or down-regulation. Notably, the transcriptome changes preceded major physiological manifestations of cold stress. In silico analysis of metabolic processes likely affected by observed gene expression changes indicated major down-regulation of photosynthesis, profound and multifarious modulation of plant hormone levels, and of chromatin structure, transcription, and translation. A role of trehalose and stachyose in cold stress signaling was also suggested. Meta-analysis of published transcriptomic data allowed discrimination between general stress response of maize and that unique to severe cold. Several cis- and trans-factors likely involved in the latter were predicted, albeit none of them seemed to have a major role. These results underscore a key role of modulation of diel gene expression in maize response to severe cold and the unique character of the cold-response of the maize circadian clock.

Graphical modeling of gene expression in monocytes suggests molecular mechanisms explaining increased atherosclerosis in smokers.

PubMed

Verdugo, Ricardo A; Zeller, Tanja; Rotival, Maxime; Wild, Philipp S; Münzel, Thomas; Lackner, Karl J; Weidmann, Henri; Ninio, Ewa; Trégouët, David-Alexandre; Cambien, François; Blankenberg, Stefan; Tiret, Laurence

2013-01-01

Smoking is a risk factor for atherosclerosis with reported widespread effects on gene expression in circulating blood cells. We hypothesized that a molecular signature mediating the relation between smoking and atherosclerosis may be found in the transcriptome of circulating monocytes. Genome-wide expression profiles and counts of atherosclerotic plaques in carotid arteries were collected in 248 smokers and 688 non-smokers from the general population. Patterns of co-expressed genes were identified by Independent Component Analysis (ICA) and network structure of the pattern-specific gene modules was inferred by the PC-algorithm. A likelihood-based causality test was implemented to select patterns that fit models containing a path "smoking→gene expression→plaques". Robustness of the causal inference was assessed by bootstrapping. At a FDR ≤0.10, 3,368 genes were associated to smoking or plaques, of which 93% were associated to smoking only. SASH1 showed the strongest association to smoking and PPARG the strongest association to plaques. Twenty-nine gene patterns were identified by ICA. Modules containing SASH1 and PPARG did not show evidence for the "smoking→gene expression→plaques" causality model. Conversely, three modules had good support for causal effects and exhibited a network topology consistent with gene expression mediating the relation between smoking and plaques. The network with the strongest support for causal effects was connected to plaques through SLC39A8, a gene with known association to HDL-cholesterol and cellular uptake of cadmium from tobacco, while smoking was directly connected to GAS6, a gene reported to have anti-inflammatory effects in atherosclerosis and to be up-regulated in the placenta of women smoking during pregnancy. Our analysis of the transcriptome of monocytes recovered genes relevant for association to smoking and atherosclerosis, and connected genes that before, were only studied in separate contexts. Inspection of correlation structure revealed candidates that would be missed by expression-phenotype association analysis alone.

Graphical Modeling of Gene Expression in Monocytes Suggests Molecular Mechanisms Explaining Increased Atherosclerosis in Smokers

PubMed Central

Verdugo, Ricardo A.; Zeller, Tanja; Rotival, Maxime; Wild, Philipp S.; Münzel, Thomas; Lackner, Karl J.; Weidmann, Henri; Ninio, Ewa; Trégouët, David-Alexandre; Cambien, François; Blankenberg, Stefan; Tiret, Laurence

2013-01-01

Smoking is a risk factor for atherosclerosis with reported widespread effects on gene expression in circulating blood cells. We hypothesized that a molecular signature mediating the relation between smoking and atherosclerosis may be found in the transcriptome of circulating monocytes. Genome-wide expression profiles and counts of atherosclerotic plaques in carotid arteries were collected in 248 smokers and 688 non-smokers from the general population. Patterns of co-expressed genes were identified by Independent Component Analysis (ICA) and network structure of the pattern-specific gene modules was inferred by the PC-algorithm. A likelihood-based causality test was implemented to select patterns that fit models containing a path “smoking→gene expression→plaques”. Robustness of the causal inference was assessed by bootstrapping. At a FDR ≤0.10, 3,368 genes were associated to smoking or plaques, of which 93% were associated to smoking only. SASH1 showed the strongest association to smoking and PPARG the strongest association to plaques. Twenty-nine gene patterns were identified by ICA. Modules containing SASH1 and PPARG did not show evidence for the “smoking→gene expression→plaques” causality model. Conversely, three modules had good support for causal effects and exhibited a network topology consistent with gene expression mediating the relation between smoking and plaques. The network with the strongest support for causal effects was connected to plaques through SLC39A8, a gene with known association to HDL-cholesterol and cellular uptake of cadmium from tobacco, while smoking was directly connected to GAS6, a gene reported to have anti-inflammatory effects in atherosclerosis and to be up-regulated in the placenta of women smoking during pregnancy. Our analysis of the transcriptome of monocytes recovered genes relevant for association to smoking and atherosclerosis, and connected genes that before, were only studied in separate contexts. Inspection of correlation structure revealed candidates that would be missed by expression-phenotype association analysis alone. PMID:23372645

Gene regulation is governed by a core network in hepatocellular carcinoma.

PubMed

Gu, Zuguang; Zhang, Chenyu; Wang, Jin

2012-05-01

Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide, and the mechanisms that lead to the disease are still relatively unclear. However, with the development of high-throughput technologies it is possible to gain a systematic view of biological systems to enhance the understanding of the roles of genes associated with HCC. Thus, analysis of the mechanism of molecule interactions in the context of gene regulatory networks can reveal specific sub-networks that lead to the development of HCC. In this study, we aimed to identify the most important gene regulations that are dysfunctional in HCC generation. Our method for constructing gene regulatory network is based on predicted target interactions, experimentally-supported interactions, and co-expression model. Regulators in the network included both transcription factors and microRNAs to provide a complete view of gene regulation. Analysis of gene regulatory network revealed that gene regulation in HCC is highly modular, in which different sets of regulators take charge of specific biological processes. We found that microRNAs mainly control biological functions related to mitochondria and oxidative reduction, while transcription factors control immune responses, extracellular activity and the cell cycle. On the higher level of gene regulation, there exists a core network that organizes regulations between different modules and maintains the robustness of the whole network. There is direct experimental evidence for most of the regulators in the core gene regulatory network relating to HCC. We infer it is the central controller of gene regulation. Finally, we explored the influence of the core gene regulatory network on biological pathways. Our analysis provides insights into the mechanism of transcriptional and post-transcriptional control in HCC. In particular, we highlight the importance of the core gene regulatory network; we propose that it is highly related to HCC and we believe further experimental validation is worthwhile.

A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis

PubMed Central

Chun, Sunwoo; Bamba, Takeshi; Suyama, Tatsuya; Ishijima, Tomoko; Fukusaki, Eiichiro; Abe, Keiko; Nakai, Yuji

2016-01-01

A high phosphorus (HP) diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus) or a HP diet (containing 1.2% phosphorus). Gene Ontology analysis of differentially expressed genes (DEGs) revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα), a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054) in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty acids released via lipolysis of white adipose tissue. PMID:27187182

VISMapper: ultra-fast exhaustive cartography of viral insertion sites for gene therapy.

PubMed

Juanes, José M; Gallego, Asunción; Tárraga, Joaquín; Chaves, Felipe J; Marín-Garcia, Pablo; Medina, Ignacio; Arnau, Vicente; Dopazo, Joaquín

2017-09-20

The possibility of integrating viral vectors to become a persistent part of the host genome makes them a crucial element of clinical gene therapy. However, viral integration has associated risks, such as the unintentional activation of oncogenes that can result in cancer. Therefore, the analysis of integration sites of retroviral vectors is a crucial step in developing safer vectors for therapeutic use. Here we present VISMapper, a vector integration site analysis web server, to analyze next-generation sequencing data for retroviral vector integration sites. VISMapper can be found at: http://vismapper.babelomics.org . Because it uses novel mapping algorithms VISMapper is remarkably faster than previous available programs. It also provides a useful graphical interface to analyze the integration sites found in the genomic context.

Pathway-driven gene stability selection of two rheumatoid arthritis GWAS identifies and validates new susceptibility genes in receptor mediated signalling pathways.

PubMed

Eleftherohorinou, Hariklia; Hoggart, Clive J; Wright, Victoria J; Levin, Michael; Coin, Lachlan J M

2011-09-01

Rheumatoid arthritis (RA) is the commonest chronic, systemic, inflammatory disorder affecting ∼1% of the world population. It has a strong genetic component and a growing number of associated genes have been discovered in genome-wide association studies (GWAS), which nevertheless only account for 23% of the total genetic risk. We aimed to identify additional susceptibility loci through the analysis of GWAS in the context of biological function. We bridge the gap between pathway and gene-oriented analyses of GWAS, by introducing a pathway-driven gene stability-selection methodology that identifies potential causal genes in the top-associated disease pathways that may be driving the pathway association signals. We analysed the WTCCC and the NARAC studies of ∼5000 and ∼2000 subjects, respectively. We examined 700 pathways comprising ∼8000 genes. Ranking pathways by significance revealed that the NARAC top-ranked ∼6% laid within the top 10% of WTCCC. Gene selection on those pathways identified 58 genes in WTCCC and 61 in NARAC; 21 of those were common (P(overlap)< 10(-21)), of which 16 were novel discoveries. Among the identified genes, we validated 10 known RA associations in WTCCC and 13 in NARAC, not discovered using single-SNP approaches on the same data. Gene ontology functional enrichment analysis on the identified genes showed significant over-representation of signalling activity (P< 10(-29)) in both studies. Our findings suggest a novel model of RA genetic predisposition, which involves cell-membrane receptors and genes in second messenger signalling systems, in addition to genes that regulate immune responses, which have been the focus of interest previously.

Chromatin immunoprecipitation assays: application of ChIP-on-chip for defining dynamic transcriptional mechanisms in bone cells.

PubMed

van der Deen, Margaretha; Hassan, Mohammad Q; Pratap, Jitesh; Teplyuk, Nadiya M; Young, Daniel W; Javed, Amjad; Zaidi, Sayyed K; Lian, Jane B; Montecino, Martin; Stein, Janet L; Stein, Gary S; van Wijnen, Andre J

2008-01-01

Normal cell growth and differentiation of bone cells requires the sequential expression of cell type specific genes to permit lineage specification and development of cellular phenotypes. Transcriptional activation and repression of distinct sets of genes support the anabolic functions of osteoblasts and the catabolic properties of osteoclasts. Furthermore, metastasis of tumors to the bone environment is controlled by transcriptional mechanisms. Insights into the transcriptional regulation of genes in bone cells may provide a conceptual basis for improved therapeutic approaches to treat bone fractures, genetic osteopathologies, and/or cancer metastases to bone. Chromatin immunoprecipitation (ChIP) is a powerful technique to establish in vivo binding of transcription factors to the promoters of genes that are either activated or repressed in bone cells. Combining ChIP with genomic microarray analysis, colloquially referred to as "ChIP-on-chip," has become a valuable method for analysis of endogenous protein/DNA interactions. This technique permits assessment of chromosomal binding sites for transcription factors or the location of histone modifications at a genomic scale. This chapter discusses protocols for performing chromatin immunoprecipitation experiments, with a focus on ChIP-on-chip analysis. The information presented is based on the authors' experience with defining interactions of Runt-related (RUNX) transcription factors with bone-related genes within the context of the native nucleosomal organization of intact osteoblastic cells.

Tools to covisualize and coanalyze proteomic data with genomes and transcriptomes: validation of genes and alternative mRNA splicing.

PubMed

Pang, Chi Nam Ignatius; Tay, Aidan P; Aya, Carlos; Twine, Natalie A; Harkness, Linda; Hart-Smith, Gene; Chia, Samantha Z; Chen, Zhiliang; Deshpande, Nandan P; Kaakoush, Nadeem O; Mitchell, Hazel M; Kassem, Moustapha; Wilkins, Marc R

2014-01-03

Direct links between proteomic and genomic/transcriptomic data are not frequently made, partly because of lack of appropriate bioinformatics tools. To help address this, we have developed the PG Nexus pipeline. The PG Nexus allows users to covisualize peptides in the context of genomes or genomic contigs, along with RNA-seq reads. This is done in the Integrated Genome Viewer (IGV). A Results Analyzer reports the precise base position where LC-MS/MS-derived peptides cover genes or gene isoforms, on the chromosomes or contigs where this occurs. In prokaryotes, the PG Nexus pipeline facilitates the validation of genes, where annotation or gene prediction is available, or the discovery of genes using a "virtual protein"-based unbiased approach. We illustrate this with a comprehensive proteogenomics analysis of two strains of Campylobacter concisus . For higher eukaryotes, the PG Nexus facilitates gene validation and supports the identification of mRNA splice junction boundaries and splice variants that are protein-coding. This is illustrated with an analysis of splice junctions covered by human phosphopeptides, and other examples of relevance to the Chromosome-Centric Human Proteome Project. The PG Nexus is open-source and available from https://github.com/IntersectAustralia/ap11_Samifier. It has been integrated into Galaxy and made available in the Galaxy tool shed.

Gene Fusion: A Genome Wide Survey

NASA Technical Reports Server (NTRS)

Liang, Ping; Riley, Monica

2001-01-01

As a well known fact, organisms form larger and complex multimodular (composite or chimeric) and mostly multi-functional proteins through gene fusion of two or more individual genes which have independent evolution histories and functions. We call each of these components a module. The existence of multimodular proteins may improves the efficiency in gene regulation and in cellular functions, and thus may give the host organism advantages in adaptation to environments. Analysis of all gene fusions in present-day organisms should allow us to examine the patterns of gene fusion in context with cellular functions, to trace back the evolution processes from the ancient smaller and uni-functional proteins to the present-day larger and complex multi-functional proteins, and to estimate the minimal number of ancestor proteins that existed in the last common ancestor for all life on earth. Although many multimodular proteins have been experimentally known, identification of gene fusion events systematically at genome scale had not been possible until recently when large number of completed genome sequences have been becoming available. In addition, technical difficulties for such analysis also exist due to the complexity of this biological and evolutionary process. We report from this study a new strategy to computationally identify multimodular proteins using completed genome sequences and the results surveyed from 22 organisms with the data from over 40 organisms to be presented during the meeting. Additional information is contained in the original extended abstract.

Immune response of the Caribbean sea fan, Gorgonia ventalina, exposed to an Aplanochytrium parasite as revealed by transcriptome sequencing

PubMed Central

Burge, Colleen A.; Mouchka, Morgan E.; Harvell, C. Drew; Roberts, Steven

2013-01-01

Coral reef communities are undergoing marked declines due to a variety of stressors including disease. The sea fan coral, Gorgonia ventalina, is a tractable study system to investigate mechanisms of immunity to a naturally occurring pathogen. Functional studies in Gorgonia ventalina immunity indicate that several key pathways and cellular components are involved in response to natural microbial invaders, although to date the functional and regulatory pathways remain largely un-described. This study used short-read sequencing (Illumina GAIIx) to identify genes involved in the response of G. ventalina to a naturally occurring Aplanochytrium spp. parasite. De novo assembly of the G. ventalina transcriptome yielded 90,230 contigs of which 40,142 were annotated. RNA-Seq analysis revealed 210 differentially expressed genes in sea fans exposed to the Aplanochytrium parasite. Differentially expressed genes involved in immunity include pattern recognition molecules, anti-microbial peptides, and genes involved in wound repair and reactive oxygen species formation. Gene enrichment analysis indicated eight biological processes were enriched representing 36 genes, largely involved with protein translation and energy production. This is the first report using high-throughput sequencing to characterize the host response of a coral to a natural pathogen. Furthermore, we have generated the first transcriptome for a soft (octocoral or non-scleractinian) coral species. Expression analysis revealed genes important in invertebrate innate immune pathways, as well as those whose role is previously un-described in cnidarians. This resource will be valuable in characterizing G. ventalina immune response to infection and co-infection of pathogens in the context of environmental change. PMID:23898300

Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline

PubMed Central

Rahmatallah, Yasir; Emmert-Streib, Frank

2016-01-01

Transcriptome sequencing (RNA-seq) is gradually replacing microarrays for high-throughput studies of gene expression. The main challenge of analyzing microarray data is not in finding differentially expressed genes, but in gaining insights into the biological processes underlying phenotypic differences. To interpret experimental results from microarrays, gene set analysis (GSA) has become the method of choice, in particular because it incorporates pre-existing biological knowledge (in a form of functionally related gene sets) into the analysis. Here we provide a brief review of several statistically different GSA approaches (competitive and self-contained) that can be adapted from microarrays practice as well as those specifically designed for RNA-seq. We evaluate their performance (in terms of Type I error rate, power, robustness to the sample size and heterogeneity, as well as the sensitivity to different types of selection biases) on simulated and real RNA-seq data. Not surprisingly, the performance of various GSA approaches depends only on the statistical hypothesis they test and does not depend on whether the test was developed for microarrays or RNA-seq data. Interestingly, we found that competitive methods have lower power as well as robustness to the samples heterogeneity than self-contained methods, leading to poor results reproducibility. We also found that the power of unsupervised competitive methods depends on the balance between up- and down-regulated genes in tested gene sets. These properties of competitive methods have been overlooked before. Our evaluation provides a concise guideline for selecting GSA approaches, best performing under particular experimental settings in the context of RNA-seq. PMID:26342128

Positional orthology: putting genomic evolutionary relationships into context.

PubMed

Dewey, Colin N

2011-09-01

Orthology is a powerful refinement of homology that allows us to describe more precisely the evolution of genomes and understand the function of the genes they contain. However, because orthology is not concerned with genomic position, it is limited in its ability to describe genes that are likely to have equivalent roles in different genomes. Because of this limitation, the concept of 'positional orthology' has emerged, which describes the relation between orthologous genes that retain their ancestral genomic positions. In this review, we formally define this concept, for which we introduce the shorter term 'toporthology', with respect to the evolutionary events experienced by a gene's ancestors. Through a discussion of recent studies on the role of genomic context in gene evolution, we show that the distinction between orthology and toporthology is biologically significant. We then review a number of orthology prediction methods that take genomic context into account and thus that may be used to infer the important relation of toporthology.

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

PubMed

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

2016-06-01

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

Pathway-based variant enrichment analysis on the example of dilated cardiomyopathy.

PubMed

Backes, Christina; Meder, Benjamin; Lai, Alan; Stoll, Monika; Rühle, Frank; Katus, Hugo A; Keller, Andreas

2016-01-01

Genome-wide association (GWA) studies have significantly contributed to the understanding of human genetic variation and its impact on clinical traits. Frequently only a limited number of highly significant associations were considered as biologically relevant. Increasingly, network analysis of affected genes is used to explore the potential role of the genetic background on disease mechanisms. Instead of first determining affected genes or calculating scores for genes and performing pathway analysis on the gene level, we integrated both steps and directly calculated enrichment on the genetic variant level. The respective approach has been tested on dilated cardiomyopathy (DCM) GWA data as showcase. To compute significance values, 5000 permutation tests were carried out and p values were adjusted for multiple testing. For 282 KEGG pathways, we computed variant enrichment scores and significance values. Of these, 65 were significant. Surprisingly, we discovered the "nucleotide excision repair" and "tuberculosis" pathways to be most significantly associated with DCM (p = 10(-9)). The latter pathway is driven by genes of the HLA-D antigen group, a finding that closely resembles previous discoveries made by expression quantitative trait locus analysis in the context of DCM-GWA. Next, we implemented a sub-network-based analysis, which searches for affected parts of KEGG, however, independent on the pre-defined pathways. Here, proteins of the contractile apparatus of cardiac cells as well as the FAS sub-network were found to be affected by common polymorphisms in DCM. In this work, we performed enrichment analysis directly on variants, leveraging the potential to discover biological information in thousands of published GWA studies. The applied approach is cutoff free and considers a ranked list of genetic variants as input.

Unsupervised text mining for assessing and augmenting GWAS results.

PubMed

Ailem, Melissa; Role, François; Nadif, Mohamed; Demenais, Florence

2016-04-01

Text mining can assist in the analysis and interpretation of large-scale biomedical data, helping biologists to quickly and cheaply gain confirmation of hypothesized relationships between biological entities. We set this question in the context of genome-wide association studies (GWAS), an actively emerging field that contributed to identify many genes associated with multifactorial diseases. These studies allow to identify groups of genes associated with the same phenotype, but provide no information about the relationships between these genes. Therefore, our objective is to leverage unsupervised text mining techniques using text-based cosine similarity comparisons and clustering applied to candidate and random gene vectors, in order to augment the GWAS results. We propose a generic framework which we used to characterize the relationships between 10 genes reported associated with asthma by a previous GWAS. The results of this experiment showed that the similarities between these 10 genes were significantly stronger than would be expected by chance (one-sided p-value<0.01). The clustering of observed and randomly selected gene also allowed to generate hypotheses about potential functional relationships between these genes and thus contributed to the discovery of new candidate genes for asthma. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis of Msx1; Msx2 double mutants reveals multiple roles for Msx genes in limb development.

PubMed

Lallemand, Yvan; Nicola, Marie-Anne; Ramos, Casto; Bach, Antoine; Cloment, Cécile Saint; Robert, Benoît

2005-07-01

The homeobox-containing genes Msx1 and Msx2 are highly expressed in the limb field from the earliest stages of limb formation and, subsequently, in both the apical ectodermal ridge and underlying mesenchyme. However, mice homozygous for a null mutation in either Msx1 or Msx2 do not display abnormalities in limb development. By contrast, Msx1; Msx2 double mutants exhibit a severe limb phenotype. Our analysis indicates that these genes play a role in crucial processes during limb morphogenesis along all three axes. Double mutant limbs are shorter and lack anterior skeletal elements (radius/tibia, thumb/hallux). Gene expression analysis confirms that there is no formation of regions with anterior identity. This correlates with the absence of dorsoventral boundary specification in the anterior ectoderm, which precludes apical ectodermal ridge formation anteriorly. As a result, anterior mesenchyme is not maintained, leading to oligodactyly. Paradoxically, polydactyly is also frequent and appears to be associated with extended Fgf activity in the apical ectodermal ridge, which is maintained up to 14.5 dpc. This results in a major outgrowth of the mesenchyme anteriorly, which nevertheless maintains a posterior identity, and leads to formation of extra digits. These defects are interpreted in the context of an impairment of Bmp signalling.

Transcriptomic responses to wounding: meta-analysis of gene expression microarray data.

PubMed

Sass, Piotr Andrzej; Dąbrowski, Michał; Charzyńska, Agata; Sachadyn, Paweł

2017-11-07

A vast amount of microarray data on transcriptomic response to injury has been collected so far. We designed the analysis in order to identify the genes displaying significant changes in expression after wounding in different organisms and tissues. This meta-analysis is the first study to compare gene expression profiles in response to wounding in as different tissues as heart, liver, skin, bones, and spinal cord, and species, including rat, mouse and human. We collected available microarray transcriptomic profiles obtained from different tissue injury experiments and selected the genes showing a minimum twofold change in expression in response to wounding in prevailing number of experiments for each of five wound healing stages we distinguished: haemostasis & early inflammation, inflammation, early repair, late repair and remodelling. During the initial phases after wounding, haemostasis & early inflammation and inflammation, the transcriptomic responses showed little consistency between different tissues and experiments. For the later phases, wound repair and remodelling, we identified a number of genes displaying similar transcriptional responses in all examined tissues. As revealed by ontological analyses, activation of certain pathways was rather specific for selected phases of wound healing, such as e.g. responses to vitamin D pronounced during inflammation. Conversely, we observed induction of genes encoding inflammatory agents and extracellular matrix proteins in all wound healing phases. Further, we selected several genes differentially upregulated throughout different stages of wound response, including established factors of wound healing in addition to those previously unreported  in this context such as PTPRC and AQP4. We found that transcriptomic responses to wounding showed similar traits in a diverse selection of tissues including skin, muscles, internal organs and nervous system. Notably, we distinguished transcriptional induction of inflammatory genes not only in the initial response to wounding, but also later, during wound repair and tissue remodelling.

Contemporary Network Proteomics and Its Requirements

PubMed Central

Goh, Wilson Wen Bin; Wong, Limsoon; Sng, Judy Chia Ghee

2013-01-01

The integration of networks with genomics (network genomics) is a familiar field. Conventional network analysis takes advantage of the larger coverage and relative stability of gene expression measurements. Network proteomics on the other hand has to develop further on two critical factors: (1) expanded data coverage and consistency, and (2) suitable reference network libraries, and data mining from them. Concerning (1) we discuss several contemporary themes that can improve data quality, which in turn will boost the outcome of downstream network analysis. For (2), we focus on network analysis developments, specifically, the need for context-specific networks and essential considerations for localized network analysis. PMID:24833333

Transcriptional master regulator analysis in breast cancer genetic networks.

PubMed

Tovar, Hugo; García-Herrera, Rodrigo; Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique

2015-12-01

Gene regulatory networks account for the delicate mechanisms that control gene expression. Under certain circumstances, gene regulatory programs may give rise to amplification cascades. Such transcriptional cascades are events in which activation of key-responsive transcription factors called master regulators trigger a series of gene expression events. The action of transcriptional master regulators is then important for the establishment of certain programs like cell development and differentiation. However, such cascades have also been related with the onset and maintenance of cancer phenotypes. Here we present a systematic implementation of a series of algorithms aimed at the inference of a gene regulatory network and analysis of transcriptional master regulators in the context of primary breast cancer cells. Such studies were performed in a highly curated database of 880 microarray gene expression experiments on biopsy-captured tissue corresponding to primary breast cancer and healthy controls. Biological function and biochemical pathway enrichment analyses were also performed to study the role that the processes controlled - at the transcriptional level - by such master regulators may have in relation to primary breast cancer. We found that transcription factors such as AGTR2, ZNF132, TFDP3 and others are master regulators in this gene regulatory network. Sets of genes controlled by these regulators are involved in processes that are well-known hallmarks of cancer. This kind of analyses may help to understand the most upstream events in the development of phenotypes, in particular, those regarding cancer biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluating Risks of Insertional Mutagenesis by DNA Transposons in Gene Therapy

PubMed Central

Hackett, Perry B.; Largaespada, David A.; Switzer, Kirsten C.; Cooper, Laurence J.N.

2013-01-01

Investigational therapy can be successfully undertaken using viral- and non-viral-mediated ex vivo gene transfer. Indeed, recent clinical trials have established the potential for genetically modified T cells to improve and restore health. Recently the Sleeping Beauty (SB) transposon/transposase system has been applied in clinical trials to stably insert a chimeric antigen receptor (CAR) to redirect T-cell specificity. We discuss the context in which the SB system can be harnessed for gene therapy and describe the human application of SB-modified CAR+ T cells. We have focused on theoretical issues relating to insertional mutagenesis in the context of human genomes that are naturally subjected to remobilization of transposons and the experimental evidence over the last decade of employing SB transposons for defining genes that induce cancer. These findings are put into the context of the use of SB transposons in the treatment of human disease. PMID:23313630

Identification of drought-response genes and a study of their expression during sucrose accumulation and water deficit in sugarcane culms.

PubMed

Iskandar, Hayati M; Casu, Rosanne E; Fletcher, Andrew T; Schmidt, Susanne; Xu, Jingsheng; Maclean, Donald J; Manners, John M; Bonnett, Graham D

2011-01-13

The ability of sugarcane to accumulate high concentrations of sucrose in its culm requires adaptation to maintain cellular function under the high solute load. We have investigated the expression of 51 genes implicated in abiotic stress to determine their expression in the context of sucrose accumulation by studying mature and immature culm internodes of a high sucrose accumulating sugarcane cultivar. Using a sub-set of eight genes, expression was examined in mature internode tissues of sugarcane cultivars as well as ancestral and more widely related species with a range of sucrose contents. Expression of these genes was also analysed in internode tissue from a high sucrose cultivar undergoing water deficit stress to compare effects of sucrose accumulation and water deficit. A sub-set of stress-related genes that are potentially associated with sucrose accumulation in sugarcane culms was identified through correlation analysis, and these included genes encoding enzymes involved in amino acid metabolism, a sugar transporter and a transcription factor. Subsequent analysis of the expression of these stress-response genes in sugarcane plants that were under water deficit stress revealed a different transcriptional profile to that which correlated with sucrose accumulation. For example, genes with homology to late embryogenesis abundant-related proteins and dehydrin were strongly induced under water deficit but this did not correlate with sucrose content. The expression of genes encoding proline biosynthesis was associated with both sucrose accumulation and water deficit, but amino acid analysis indicated that proline was negatively correlated with sucrose concentration, and whilst total amino acid concentrations increased about seven-fold under water deficit, the relatively low concentration of proline suggested that it had no osmoprotectant role in sugarcane culms. The results show that while there was a change in stress-related gene expression associated with sucrose accumulation, different mechanisms are responding to the stress induced by water deficit, because different genes had altered expression under water deficit.

Identification of drought-response genes and a study of their expression during sucrose accumulation and water deficit in sugarcane culms

PubMed Central

2011-01-01

Background The ability of sugarcane to accumulate high concentrations of sucrose in its culm requires adaptation to maintain cellular function under the high solute load. We have investigated the expression of 51 genes implicated in abiotic stress to determine their expression in the context of sucrose accumulation by studying mature and immature culm internodes of a high sucrose accumulating sugarcane cultivar. Using a sub-set of eight genes, expression was examined in mature internode tissues of sugarcane cultivars as well as ancestral and more widely related species with a range of sucrose contents. Expression of these genes was also analysed in internode tissue from a high sucrose cultivar undergoing water deficit stress to compare effects of sucrose accumulation and water deficit. Results A sub-set of stress-related genes that are potentially associated with sucrose accumulation in sugarcane culms was identified through correlation analysis, and these included genes encoding enzymes involved in amino acid metabolism, a sugar transporter and a transcription factor. Subsequent analysis of the expression of these stress-response genes in sugarcane plants that were under water deficit stress revealed a different transcriptional profile to that which correlated with sucrose accumulation. For example, genes with homology to late embryogenesis abundant-related proteins and dehydrin were strongly induced under water deficit but this did not correlate with sucrose content. The expression of genes encoding proline biosynthesis was associated with both sucrose accumulation and water deficit, but amino acid analysis indicated that proline was negatively correlated with sucrose concentration, and whilst total amino acid concentrations increased about seven-fold under water deficit, the relatively low concentration of proline suggested that it had no osmoprotectant role in sugarcane culms. Conclusions The results show that while there was a change in stress-related gene expression associated with sucrose accumulation, different mechanisms are responding to the stress induced by water deficit, because different genes had altered expression under water deficit. PMID:21226964

Systems Genetics Reveals the Functional Context of PCOS Loci and Identifies Genetic and Molecular Mechanisms of Disease Heterogeneity

PubMed Central

Xu, Ning; Cui, Jinrui; Mengesha, Emebet; Chen, Yii-Der I.; Taylor, Kent D.; Azziz, Ricardo; Goodarzi, Mark O.

2015-01-01

Genome wide association studies (GWAS) have revealed 11 independent risk loci for polycystic ovary syndrome (PCOS), a common disorder in young women characterized by androgen excess and oligomenorrhea. To put these risk loci and the single nucleotide polymorphisms (SNPs) therein into functional context, we measured DNA methylation and gene expression in subcutaneous adipose tissue biopsies to identify PCOS-specific alterations. Two genes from the LHCGR region, STON1-GTF2A1L and LHCGR, were overexpressed in PCOS. In analysis stratified by obesity, LHCGR was overexpressed only in non-obese PCOS women. Although not differentially expressed in the entire PCOS group, INSR was underexpressed in obese PCOS subjects only. Alterations in gene expression in the LHCGR, RAB5B and INSR regions suggest that SNPs in these loci may be functional and could affect gene expression directly or indirectly via epigenetic alterations. We identified reduced methylation in the LHCGR locus and increased methylation in the INSR locus, changes that are concordant with the altered gene expression profiles. Complex patterns of meQTL and eQTL were identified in these loci, suggesting that local genetic variation plays an important role in gene regulation. We propose that non-obese PCOS women possess significant alterations in LH receptor expression, which drives excess androgen secretion from the ovary. Alternatively, obese women with PCOS possess alterations in insulin receptor expression, with underexpression in metabolic tissues and overexpression in the ovary, resulting in peripheral insulin resistance and excess ovarian androgen production. These studies provide a genetic and molecular basis for the reported clinical heterogeneity of PCOS. PMID:26305227

Analysis of phylogeny and codon usage bias and relationship of GC content, amino acid composition with expression of the structural nif genes.

PubMed

Mondal, Sunil Kanti; Kundu, Sudip; Das, Rabindranath; Roy, Sujit

2016-08-01

Bacteria and archaea have evolved with the ability to fix atmospheric dinitrogen in the form of ammonia, catalyzed by the nitrogenase enzyme complex which comprises three structural genes nifK, nifD and nifH. The nifK and nifD encodes for the beta and alpha subunits, respectively, of component 1, while nifH encodes for component 2 of nitrogenase. Phylogeny based on nifDHK have indicated that Cyanobacteria is closer to Proteobacteria alpha and gamma but not supported by the tree based on 16SrRNA. The evolutionary ancestor for the different trees was also different. The GC1 and GC2% analysis showed more consistency than GC3% which appeared to below for Firmicutes, Cyanobacteria and Euarchaeota while highest in Proteobacteria beta and clearly showed the proportional effect on the codon usage with a few exceptions. Few genes from Firmicutes, Euryarchaeota, Proteobacteria alpha and delta were found under mutational pressure. These nif genes with low and high GC3% from different classes of organisms showed similar expected number of codons. Distribution of the genes and codons, based on codon usage demonstrated opposite pattern for different orientation of mirror plane when compared with each other. Overall our results provide a comprehensive analysis on the evolutionary relationship of the three structural nif genes, nifK, nifD and nifH, respectively, in the context of codon usage bias, GC content relationship and amino acid composition of the encoded proteins and exploration of crucial statistical method for the analysis of positive data with non-constant variance to identify the shape factors of codon adaptation index.

Comprehensive comparative-genomic analysis of type 2 toxin-antitoxin systems and related mobile stress response systems in prokaryotes.

PubMed

Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

2009-06-03

The prokaryotic toxin-antitoxin systems (TAS, also referred to as TA loci) are widespread, mobile two-gene modules that can be viewed as selfish genetic elements because they evolved mechanisms to become addictive for replicons and cells in which they reside, but also possess "normal" cellular functions in various forms of stress response and management of prokaryotic population. Several distinct TAS of type 1, where the toxin is a protein and the antitoxin is an antisense RNA, and numerous, unrelated TAS of type 2, in which both the toxin and the antitoxin are proteins, have been experimentally characterized, and it is suspected that many more remain to be identified. We report a comprehensive comparative-genomic analysis of Type 2 toxin-antitoxin systems in prokaryotes. Using sensitive methods for distant sequence similarity search, genome context analysis and a new approach for the identification of mobile two-component systems, we identified numerous, previously unnoticed protein families that are homologous to toxins and antitoxins of known type 2 TAS. In addition, we predict 12 new families of toxins and 13 families of antitoxins, and also, predict a TAS or TAS-like activity for several gene modules that were not previously suspected to function in that capacity. In particular, we present indications that the two-gene module that encodes a minimal nucleotidyl transferase and the accompanying HEPN protein, and is extremely abundant in many archaea and bacteria, especially, thermophiles might comprise a novel TAS. We present a survey of previously known and newly predicted TAS in 750 complete genomes of archaea and bacteria, quantitatively demonstrate the exceptional mobility of the TAS, and explore the network of toxin-antitoxin pairings that combines plasticity with selectivity. The defining properties of the TAS, namely, the typically small size of the toxin and antitoxin genes, fast evolution, and extensive horizontal mobility, make the task of comprehensive identification of these systems particularly challenging. However, these same properties can be exploited to develop context-based computational approaches which, combined with exhaustive analysis of subtle sequence similarities were employed in this work to substantially expand the current collection of TAS by predicting both previously unnoticed, derived versions of known toxins and antitoxins, and putative novel TAS-like systems. In a broader context, the TAS belong to the resistome domain of the prokaryotic mobilome which includes partially selfish, addictive gene cassettes involved in various aspects of stress response and organized under the same general principles as the TAS. The "selfish altruism", or "responsible selfishness", of TAS-like systems appears to be a defining feature of the resistome and an important characteristic of the entire prokaryotic pan-genome given that in the prokaryotic world the mobilome and the "stable" chromosomes form a dynamic continuum. This paper was reviewed by Kenn Gerdes (nominated by Arcady Mushegian), Daniel Haft, Arcady Mushegian, and Andrei Osterman. For full reviews, go to the Reviewers' Reports section.

Comprehensive comparative-genomic analysis of Type 2 toxin-antitoxin systems and related mobile stress response systems in prokaryotes

PubMed Central

Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

2009-01-01

Background The prokaryotic toxin-antitoxin systems (TAS, also referred to as TA loci) are widespread, mobile two-gene modules that can be viewed as selfish genetic elements because they evolved mechanisms to become addictive for replicons and cells in which they reside, but also possess "normal" cellular functions in various forms of stress response and management of prokaryotic population. Several distinct TAS of type 1, where the toxin is a protein and the antitoxin is an antisense RNA, and numerous, unrelated TAS of type 2, in which both the toxin and the antitoxin are proteins, have been experimentally characterized, and it is suspected that many more remain to be identified. Results We report a comprehensive comparative-genomic analysis of Type 2 toxin-antitoxin systems in prokaryotes. Using sensitive methods for distant sequence similarity search, genome context analysis and a new approach for the identification of mobile two-component systems, we identified numerous, previously unnoticed protein families that are homologous to toxins and antitoxins of known type 2 TAS. In addition, we predict 12 new families of toxins and 13 families of antitoxins, and also, predict a TAS or TAS-like activity for several gene modules that were not previously suspected to function in that capacity. In particular, we present indications that the two-gene module that encodes a minimal nucleotidyl transferase and the accompanying HEPN protein, and is extremely abundant in many archaea and bacteria, especially, thermophiles might comprise a novel TAS. We present a survey of previously known and newly predicted TAS in 750 complete genomes of archaea and bacteria, quantitatively demonstrate the exceptional mobility of the TAS, and explore the network of toxin-antitoxin pairings that combines plasticity with selectivity. Conclusion The defining properties of the TAS, namely, the typically small size of the toxin and antitoxin genes, fast evolution, and extensive horizontal mobility, make the task of comprehensive identification of these systems particularly challenging. However, these same properties can be exploited to develop context-based computational approaches which, combined with exhaustive analysis of subtle sequence similarities were employed in this work to substantially expand the current collection of TAS by predicting both previously unnoticed, derived versions of known toxins and antitoxins, and putative novel TAS-like systems. In a broader context, the TAS belong to the resistome domain of the prokaryotic mobilome which includes partially selfish, addictive gene cassettes involved in various aspects of stress response and organized under the same general principles as the TAS. The "selfish altruism", or "responsible selfishness", of TAS-like systems appears to be a defining feature of the resistome and an important characteristic of the entire prokaryotic pan-genome given that in the prokaryotic world the mobilome and the "stable" chromosomes form a dynamic continuum. Reviewers This paper was reviewed by Kenn Gerdes (nominated by Arcady Mushegian), Daniel Haft, Arcady Mushegian, and Andrei Osterman. For full reviews, go to the Reviewers' Reports section. PMID:19493340

Genome-wide analysis of trans-splicing in the nematode Pristionchus pacificus unravels conserved gene functions for germline and dauer development in divergent operons.

PubMed

Sinha, Amit; Langnick, Claudia; Sommer, Ralf J; Dieterich, Christoph

2014-09-01

Discovery of trans-splicing in multiple metazoan lineages led to the identification of operon-like gene organization in diverse organisms, including trypanosomes, tunicates, and nematodes, but the functional significance of such operons is not completely understood. To see whether the content or organization of operons serves similar roles across species, we experimentally defined operons in the nematode model Pristionchus pacificus. We performed affinity capture experiments on mRNA pools to specifically enrich for transcripts that are trans-spliced to either the SL1- or SL2-spliced leader, using spliced leader-specific probes. We obtained distinct trans-splicing patterns from the analysis of three mRNA pools (total mRNA, SL1 and SL2 fraction) by RNA-seq. This information was combined with a genome-wide analysis of gene orientation and spacing. We could confirm 2219 operons by RNA-seq data out of 6709 candidate operons, which were predicted by sequence information alone. Our gene order comparison of the Caenorhabditis elegans and P. pacificus genomes shows major changes in operon organization in the two species. Notably, only 128 out of 1288 operons in C. elegans are conserved in P. pacificus. However, analysis of gene-expression profiles identified conserved functions such as an enrichment of germline-expressed genes and higher expression levels of operonic genes during recovery from dauer arrest in both species. These results provide support for the model that a necessity for increased transcriptional efficiency in the context of certain developmental processes could be a selective constraint for operon evolution in metazoans. Our method is generally applicable to other metazoans to see if similar functional constraints regulate gene organization into operons. © 2014 Sinha et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Columbia University: Direct Reversal of Glucocorticoid Resistance by AKT inhibition in Acute Lymphoblastic Leukemia (T-ALL) | Office of Cancer Genomics

Cancer.gov

The goal of this project is to identify key druggable regulators of glucocorticoid resistance in T-ALL. To this end, a reverse-engineered T-ALL context-specific regulatory interaction network was created from a phenotypically diverse T-ALL gene expression dataset, and then this network was interrogated using master regulator analysis to find drivers of glucocorticoid resistance.

Understanding ZHENG in traditional Chinese medicine in the context of neuro-endocrine-immune network.

PubMed

Li, S; Zhang, Z Q; Wu, L J; Zhang, X G; Li, Y D; Wang, Y Y

2007-01-01

Traditional Chinese medicine uses ZHENG as the key pathological principle to understand the human homeostasis and guide the applications of Chinese herbs. Here, a systems biology approach with the combination of computational analysis and animal experiment is used to investigate this complex issue, ZHENG, in the context of the neuro-endocrine-immune (NEI) system. By using the methods of literature mining, network analysis and topological comparison, it is found that hormones are predominant in the Cold ZHENG network, immune factors are predominant in the Hot ZHENG network, and these two networks are connected by neuro-transmitters. In addition, genes related to Hot ZHENG-related diseases are mainly present in the cytokine-cytokine receptor interaction pathway, whereas genes related to both the Cold-related and Hot-related diseases are linked to the neuroactive ligand-receptor interaction pathway. These computational findings were subsequently verified by experiments on a rat model of collagen-induced arthritis, which indicate that the Cold ZHENG-oriented herbs tend to affect the hub nodes in the Cold ZHENG network, and the Hot ZHENG-oriented herbs tend to affect the hub nodes in the Hot ZHENG network. These investigations demonstrate that the thousand-year-old concept of ZHENG may have a molecular basis with NEI as background.

Designer TAL effectors induce disease susceptibility and resistance to Xanthomonas oryzae pv. oryzae in rice.

PubMed

Li, Ting; Huang, Sheng; Zhou, Junhui; Yang, Bing

2013-05-01

TAL (transcription activator-like) effectors from Xanthomonas bacteria activate the cognate host genes, leading to disease susceptibility or resistance dependent on the genetic context of host target genes. The modular nature and DNA recognition code of TAL effectors enable custom-engineering of designer TAL effectors (dTALE) for gene activation. However, the feasibility of dTALEs as transcription activators for gene functional analysis has not been demonstrated. Here, we report the use of dTALEs, as expressed and delivered by the pathogenic Xanthomonas oryzae pv. oryzae (Xoo), in revealing the new function of two previously identified disease-related genes and the potential of one developmental gene for disease susceptibility in rice/Xoo interactions. The dTALE gene dTALE-xa27, designed to target the susceptible allele of the resistance gene Xa27, elicited a resistant reaction in the otherwise susceptible rice cultivar IR24. Four dTALE genes were made to induce the four annotated Xa27 homologous genes in rice cultivar Nipponbare, but none of the four induced Xa27-like genes conferred resistance to the dTALE-containing Xoo strains. A dTALE gene was also generated to activate the recessive resistance gene xa13, an allele of the disease-susceptibility gene Os8N3 (also named Xa13 or OsSWEET11, a member of sucrose efflux transporter SWEET gene family). The induction of xa13 by the dTALE rendered the resistant rice IRBB13 (xa13/xa13) susceptible to Xoo. Finally, OsSWEET12, an as-yet uncharacterized SWEET gene with no corresponding naturally occurring TAL effector identified, conferred susceptibility to the Xoo strains expressing the corresponding dTALE genes. Our results demonstrate that dTALEs can be delivered through the bacterial secretion system to activate genes of interest for functional analysis in plants.

A new VCAN/versican splice acceptor site mutation in a French Wagner family associated with vascular and inflammatory ocular features

PubMed Central

Brézin, Antoine P.; Nedelec, Brigitte; Barjol, Amandine; Rothschild, Pierre-Raphael; Delpech, Marc

2011-01-01

Purpose To detail the highly variable ocular phenotypes of a French family affected with an autosomal dominantly inherited vitreoretinopathy and to identify the disease gene. Methods Sixteen family members with ten affected individuals underwent detailed ophthalmic evaluation. Genetic linkage analysis and gene screening were undertaken for genes known to be involved in degenerative and exudative vitreoretinopathies. Qualitative reverse transcriptase-PCR analysis of the versiscan (VCAN) transcripts was performed after mutation detection in the VCAN gene. Results The first index patient of this French family was referred to us because of a chronic uveitis since infancy; this uveitis was associated with exudative retinal detachment in the context of a severe uncharacterized familial vitreoretinopathy. Genetic linkage was obtained to the VCAN locus, and we further identified a new pathogenic mutation at the highly conserved splice acceptor site in intron 7 of the VCAN gene (c.4004–2A>T), which produced aberrantly spliced VCAN transcripts. Conclusions Extensive molecular investigation allowed us to classify this familial vitreoretinopathy as Wagner syndrome. This study illustrates the need to confirm clinical diagnosis by molecular genetic testing and adds new ocular phenotypes to the Wagner syndrome, such as vascular and inflammatory features. PMID:21738396

Early developmental gene regulation in Strongylocentrotus purpuratus embryos in response to elevated CO₂ seawater conditions.

PubMed

Hammond, LaTisha M; Hofmann, Gretchen E

2012-07-15

Ocean acidification, or the increased uptake of CO(2) by the ocean due to elevated atmospheric CO(2) concentrations, may variably impact marine early life history stages, as they may be especially susceptible to changes in ocean chemistry. Investigating the regulatory mechanisms of early development in an environmental context, or ecological development, will contribute to increased understanding of potential organismal responses to such rapid, large-scale environmental changes. We examined transcript-level responses to elevated seawater CO(2) during gastrulation and the initiation of spiculogenesis, two crucial developmental processes in the purple sea urchin, Strongylocentrotus purpuratus. Embryos were reared at the current, accepted oceanic CO(2) concentration of 380 microatmospheres (μatm), and at the elevated levels of 1000 and 1350 μatm, simulating predictions for oceans and upwelling regions, respectively. The seven genes of interest comprised a subset of pathways in the primary mesenchyme cell gene regulatory network (PMC GRN) shown to be necessary for the regulation and execution of gastrulation and spiculogenesis. Of the seven genes, qPCR analysis indicated that elevated CO(2) concentrations only had a significant but subtle effect on two genes, one important for early embryo patterning, Wnt8, and the other an integral component in spiculogenesis and biomineralization, SM30b. Protein levels of another spicule matrix component, SM50, demonstrated significant variable responses to elevated CO(2). These data link the regulation of crucial early developmental processes with the environment that these embryos would be developing within, situating the study of organismal responses to ocean acidification in a developmental context.

ITEP: an integrated toolkit for exploration of microbial pan-genomes.

PubMed

Benedict, Matthew N; Henriksen, James R; Metcalf, William W; Whitaker, Rachel J; Price, Nathan D

2014-01-03

Comparative genomics is a powerful approach for studying variation in physiological traits as well as the evolution and ecology of microorganisms. Recent technological advances have enabled sequencing large numbers of related genomes in a single project, requiring computational tools for their integrated analysis. In particular, accurate annotations and identification of gene presence and absence are critical for understanding and modeling the cellular physiology of newly sequenced genomes. Although many tools are available to compare the gene contents of related genomes, new tools are necessary to enable close examination and curation of protein families from large numbers of closely related organisms, to integrate curation with the analysis of gain and loss, and to generate metabolic networks linking the annotations to observed phenotypes. We have developed ITEP, an Integrated Toolkit for Exploration of microbial Pan-genomes, to curate protein families, compute similarities to externally-defined domains, analyze gene gain and loss, and generate draft metabolic networks from one or more curated reference network reconstructions in groups of related microbial species among which the combination of core and variable genes constitute the their "pan-genomes". The ITEP toolkit consists of: (1) a series of modular command-line scripts for identification, comparison, curation, and analysis of protein families and their distribution across many genomes; (2) a set of Python libraries for programmatic access to the same data; and (3) pre-packaged scripts to perform common analysis workflows on a collection of genomes. ITEP's capabilities include de novo protein family prediction, ortholog detection, analysis of functional domains, identification of core and variable genes and gene regions, sequence alignments and tree generation, annotation curation, and the integration of cross-genome analysis and metabolic networks for study of metabolic network evolution. ITEP is a powerful, flexible toolkit for generation and curation of protein families. ITEP's modular design allows for straightforward extension as analysis methods and tools evolve. By integrating comparative genomics with the development of draft metabolic networks, ITEP harnesses the power of comparative genomics to build confidence in links between genotype and phenotype and helps disambiguate gene annotations when they are evaluated in both evolutionary and metabolic network contexts.

Cellular context-dependent consequences of Apc mutations on gene regulation and cellular behavior.

PubMed

Hashimoto, Kyoichi; Yamada, Yosuke; Semi, Katsunori; Yagi, Masaki; Tanaka, Akito; Itakura, Fumiaki; Aoki, Hitomi; Kunisada, Takahiro; Woltjen, Knut; Haga, Hironori; Sakai, Yoshiharu; Yamamoto, Takuya; Yamada, Yasuhiro

2017-01-24

The spectrum of genetic mutations differs among cancers in different organs, implying a cellular context-dependent effect for genetic aberrations. However, the extent to which the cellular context affects the consequences of oncogenic mutations remains to be fully elucidated. We reprogrammed colon tumor cells in an Apc Min/+ (adenomatous polyposis coli) mouse model, in which the loss of the Apc gene plays a critical role in tumor development and subsequently, established reprogrammed tumor cells (RTCs) that exhibit pluripotent stem cell (PSC)-like signatures of gene expression. We show that the majority of the genes in RTCs that were affected by Apc mutations did not overlap with the genes affected in the intestine. RTCs lacked pluripotency but exhibited an increased expression of Cdx2 and a differentiation propensity that was biased toward the trophectoderm cell lineage. Genetic rescue of the mutated Apc allele conferred pluripotency on RTCs and enabled their differentiation into various cell types in vivo. The redisruption of Apc in RTC-derived differentiated cells resulted in neoplastic growth that was exclusive to the intestine, but the majority of the intestinal lesions remained as pretumoral microadenomas. These results highlight the significant influence of cellular context on gene regulation, cellular plasticity, and cellular behavior in response to the loss of the Apc function. Our results also imply that the transition from microadenomas to macroscopic tumors is reprogrammable, which underscores the importance of epigenetic regulation on tumor promotion.

Cellular context-dependent consequences of Apc mutations on gene regulation and cellular behavior

PubMed Central

Hashimoto, Kyoichi; Yamada, Yosuke; Semi, Katsunori; Yagi, Masaki; Tanaka, Akito; Itakura, Fumiaki; Aoki, Hitomi; Kunisada, Takahiro; Woltjen, Knut; Haga, Hironori; Sakai, Yoshiharu; Yamamoto, Takuya; Yamada, Yasuhiro

2017-01-01

The spectrum of genetic mutations differs among cancers in different organs, implying a cellular context-dependent effect for genetic aberrations. However, the extent to which the cellular context affects the consequences of oncogenic mutations remains to be fully elucidated. We reprogrammed colon tumor cells in an ApcMin/+ (adenomatous polyposis coli) mouse model, in which the loss of the Apc gene plays a critical role in tumor development and subsequently, established reprogrammed tumor cells (RTCs) that exhibit pluripotent stem cell (PSC)-like signatures of gene expression. We show that the majority of the genes in RTCs that were affected by Apc mutations did not overlap with the genes affected in the intestine. RTCs lacked pluripotency but exhibited an increased expression of Cdx2 and a differentiation propensity that was biased toward the trophectoderm cell lineage. Genetic rescue of the mutated Apc allele conferred pluripotency on RTCs and enabled their differentiation into various cell types in vivo. The redisruption of Apc in RTC-derived differentiated cells resulted in neoplastic growth that was exclusive to the intestine, but the majority of the intestinal lesions remained as pretumoral microadenomas. These results highlight the significant influence of cellular context on gene regulation, cellular plasticity, and cellular behavior in response to the loss of the Apc function. Our results also imply that the transition from microadenomas to macroscopic tumors is reprogrammable, which underscores the importance of epigenetic regulation on tumor promotion. PMID:28057861

Chitinase-like (CTL) and cellulose synthase (CESA) gene expression in gelatinous-type cellulosic walls of flax (Linum usitatissimum L.) bast fibers.

PubMed

Mokshina, Natalia; Gorshkova, Tatyana; Deyholos, Michael K

2014-01-01

Plant chitinases (EC 3.2.1.14) and chitinase-like (CTL) proteins have diverse functions including cell wall biosynthesis and disease resistance. We analyzed the expression of 34 chitinase and chitinase-like genes of flax (collectively referred to as LusCTLs), belonging to glycoside hydrolase family 19 (GH19). Analysis of the transcript expression patterns of LusCTLs in the stem and other tissues identified three transcripts (LusCTL19, LusCTL20, LusCTL21) that were highly enriched in developing bast fibers, which form cellulose-rich gelatinous-type cell walls. The same three genes had low relative expression in tissues with primary cell walls and in xylem, which forms a xylan type of secondary cell wall. Phylogenetic analysis of the LusCTLs identified a flax-specific sub-group that was not represented in any of other genomes queried. To provide further context for the gene expression analysis, we also conducted phylogenetic and expression analysis of the cellulose synthase (CESA) family genes of flax, and found that expression of secondary wall-type LusCESAs (LusCESA4, LusCESA7 and LusCESA8) was correlated with the expression of two LusCTLs (LusCTL1, LusCTL2) that were the most highly enriched in xylem. The expression of LusCTL19, LusCTL20, and LusCTL21 was not correlated with that of any CESA subgroup. These results defined a distinct type of CTLs that may have novel functions specific to the development of the gelatinous (G-type) cellulosic walls.

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer

PubMed Central

Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-01-01

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies. PMID:26397224

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

PubMed

Nguyen, Minh Nam; Choi, Tae Gyu; Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-10-13

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

PhytoPath: an integrative resource for plant pathogen genomics.

PubMed

Pedro, Helder; Maheswari, Uma; Urban, Martin; Irvine, Alistair George; Cuzick, Alayne; McDowall, Mark D; Staines, Daniel M; Kulesha, Eugene; Hammond-Kosack, Kim Elizabeth; Kersey, Paul Julian

2016-01-04

PhytoPath (www.phytopathdb.org) is a resource for genomic and phenotypic data from plant pathogen species, that integrates phenotypic data for genes from PHI-base, an expertly curated catalog of genes with experimentally verified pathogenicity, with the Ensembl tools for data visualization and analysis. The resource is focused on fungi, protists (oomycetes) and bacterial plant pathogens that have genomes that have been sequenced and annotated. Genes with associated PHI-base data can be easily identified across all plant pathogen species using a BioMart-based query tool and visualized in their genomic context on the Ensembl genome browser. The PhytoPath resource contains data for 135 genomic sequences from 87 plant pathogen species, and 1364 genes curated for their role in pathogenicity and as targets for chemical intervention. Support for community annotation of gene models is provided using the WebApollo online gene editor, and we are working with interested communities to improve reference annotation for selected species. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Gene regulation in amphioxus: An insight from transgenic studies in amphioxus and vertebrates.

PubMed

Kozmikova, Iryna; Kozmik, Zbynek

2015-12-01

Cephalochordates, commonly known as amphioxus or lancelets, are the most basal subphylum of chordates. Cephalochordates are thus key to understanding the origin of vertebrates and molecular mechanisms underlying vertebrate evolution. The evolution of developmental control mechanisms during invertebrate-to-vertebrate transition involved not only gene duplication events, but also specific changes in spatial and temporal expression of many genes. To get insight into the spatiotemporal regulation of gene expression during invertebrate-to-vertebrate transition, functional studies of amphioxus gene regulatory elements are highly warranted. Here, we review transgenic studies performed in amphioxus and vertebrates using promoters and enhancers derived from the genome of Branchiostoma floridae. We describe the current methods of transgenesis in amphioxus, provide evidence of Tol2 transposon-generated transgenic embryos of Branchiostoma lanceolatum and discuss possible future directions. We envision that comparative transgenic analysis of gene regulatory sequences in the context of amphioxus and vertebrate embryos will likely provide an important mechanistic insight into the evolution of vertebrate body plan. Copyright © 2015 Elsevier B.V. All rights reserved.

Genome-wide analysis of heat shock proteins in C4 model, foxtail millet identifies potential candidates for crop improvement under abiotic stress.

PubMed

Singh, Roshan Kumar; Jaishankar, Jananee; Muthamilarasan, Mehanathan; Shweta, Shweta; Dangi, Anand; Prasad, Manoj

2016-09-02

Heat shock proteins (HSPs) perform significant roles in conferring abiotic stress tolerance to crop plants. In view of this, HSPs and their encoding genes were extensively characterized in several plant species; however, understanding their structure, organization, evolution and expression profiling in a naturally stress tolerant crop is necessary to delineate their precise roles in stress-responsive molecular machinery. In this context, the present study has been performed in C4 panicoid model, foxtail millet, which resulted in identification of 20, 9, 27, 20 and 37 genes belonging to SiHSP100, SiHSP90, SiHSP70, SiHSP60 and SisHSP families, respectively. Comprehensive in silico characterization of these genes followed by their expression profiling in response to dehydration, heat, salinity and cold stresses in foxtail millet cultivars contrastingly differing in stress tolerance revealed significant upregulation of several genes in tolerant cultivar. SisHSP-27 showed substantial higher expression in response to heat stress in tolerant cultivar, and its over-expression in yeast system conferred tolerance to several abiotic stresses. Methylation analysis of SiHSP genes suggested that, in susceptible cultivar, higher levels of methylation might be the reason for reduced expression of these genes during stress. Altogether, the study provides novel clues on the role of HSPs in conferring stress tolerance.

Dissociation between Complete Hippocampal Context Memory Formation and Context Fear Acquisition

ERIC Educational Resources Information Center

Leake, Jessica; Zinn, Raphael; Corbit, Laura; Vissel, Bryce

2017-01-01

Rodents require a minimal time period to explore a context prior to footshock to display plateau-level context fear at test. To investigate whether this rapid fear plateau reflects complete memory formation within that short time-frame, we used the immediate-early gene product Arc as an indicator of hippocampal context memory formation-related…

Biodiversity of genes encoding anti-microbial traits within plant associated microbes

PubMed Central

Mousa, Walaa K.; Raizada, Manish N.

2015-01-01

The plant is an attractive versatile home for diverse associated microbes. A subset of these microbes produces a diversity of anti-microbial natural products including polyketides, non-ribosomal peptides, terpenoids, heterocylic nitrogenous compounds, volatile compounds, bacteriocins, and lytic enzymes. In recent years, detailed molecular analysis has led to a better understanding of the underlying genetic mechanisms. New genomic and bioinformatic tools have permitted comparisons of orthologous genes between species, leading to predictions of the associated evolutionary mechanisms responsible for diversification at the genetic and corresponding biochemical levels. The purpose of this review is to describe the biodiversity of biosynthetic genes of plant-associated bacteria and fungi that encode selected examples of antimicrobial natural products. For each compound, the target pathogen and biochemical mode of action are described, in order to draw attention to the complexity of these phenomena. We review recent information of the underlying molecular diversity and draw lessons through comparative genomic analysis of the orthologous coding sequences (CDS). We conclude by discussing emerging themes and gaps, discuss the metabolic pathways in the context of the phylogeny and ecology of their microbial hosts, and discuss potential evolutionary mechanisms that led to the diversification of biosynthetic gene clusters. PMID:25914708

Identification of differentially expressed genes and false discovery rate in microarray studies.

PubMed

Gusnanto, Arief; Calza, Stefano; Pawitan, Yudi

2007-04-01

To highlight the development in microarray data analysis for the identification of differentially expressed genes, particularly via control of false discovery rate. The emergence of high-throughput technology such as microarrays raises two fundamental statistical issues: multiplicity and sensitivity. We focus on the biological problem of identifying differentially expressed genes. First, multiplicity arises due to testing tens of thousands of hypotheses, rendering the standard P value meaningless. Second, known optimal single-test procedures such as the t-test perform poorly in the context of highly multiple tests. The standard approach of dealing with multiplicity is too conservative in the microarray context. The false discovery rate concept is fast becoming the key statistical assessment tool replacing the P value. We review the false discovery rate approach and argue that it is more sensible for microarray data. We also discuss some methods to take into account additional information from the microarrays to improve the false discovery rate. There is growing consensus on how to analyse microarray data using the false discovery rate framework in place of the classical P value. Further research is needed on the preprocessing of the raw data, such as the normalization step and filtering, and on finding the most sensitive test procedure.

HER2 missense mutations have distinct effects on oncogenic signaling and migration

PubMed Central

Zabransky, Daniel J.; Yankaskas, Christopher L.; Cochran, Rory L.; Wong, Hong Yuen; Croessmann, Sarah; Chu, David; Kavuri, Shyam M.; Red Brewer, Monica; Rosen, D. Marc; Dalton, W. Brian; Cimino-Mathews, Ashley; Cravero, Karen; Button, Berry; Kyker-Snowman, Kelly; Cidado, Justin; Erlanger, Bracha; Parsons, Heather A.; Manto, Kristen M.; Bose, Ron; Lauring, Josh; Arteaga, Carlos L.; Konstantopoulos, Konstantinos; Park, Ben Ho

2015-01-01

Recurrent human epidermal growth factor receptor 2 (HER2) missense mutations have been reported in human cancers. These mutations occur primarily in the absence of HER2 gene amplification such that most HER2-mutant tumors are classified as “negative” by FISH or immunohistochemistry assays. It remains unclear whether nonamplified HER2 missense mutations are oncogenic and whether they are targets for HER2-directed therapies that are currently approved for the treatment of HER2 gene-amplified breast cancers. Here we functionally characterize HER2 kinase and extracellular domain mutations through gene editing of the endogenous loci in HER2 nonamplified human breast epithelial cells. In in vitro and in vivo assays, the majority of HER2 missense mutations do not impart detectable oncogenic changes. However, the HER2 V777L mutation increased biochemical pathway activation and, in the context of a PIK3CA mutation, enhanced migratory features in vitro. However, the V777L mutation did not alter in vivo tumorigenicity or sensitivity to HER2-directed therapies in proliferation assays. Our results suggest the oncogenicity and potential targeting of HER2 missense mutations should be considered in the context of cooperating genetic alterations and provide previously unidentified insights into functional analysis of HER2 mutations and strategies to target them. PMID:26508629

Adeno-associated virus inverted terminal repeats stimulate gene editing.

PubMed

Hirsch, M L

2015-02-01

Advancements in genome editing have relied on technologies to specifically damage DNA which, in turn, stimulates DNA repair including homologous recombination (HR). As off-target concerns complicate the therapeutic translation of site-specific DNA endonucleases, an alternative strategy to stimulate gene editing based on fragile DNA was investigated. To do this, an episomal gene-editing reporter was generated by a disruptive insertion of the adeno-associated virus (AAV) inverted terminal repeat (ITR) into the egfp gene. Compared with a non-structured DNA control sequence, the ITR induced DNA damage as evidenced by increased gamma-H2AX and Mre11 foci formation. As local DNA damage stimulates HR, ITR-mediated gene editing was investigated using DNA oligonucleotides as repair substrates. The AAV ITR stimulated gene editing >1000-fold in a replication-independent manner and was not biased by the polarity of the repair oligonucleotide. Analysis of additional human DNA sequences demonstrated stimulation of gene editing to varying degrees. In particular, inverted yet not direct, Alu repeats induced gene editing, suggesting a role for DNA structure in the repair event. Collectively, the results demonstrate that inverted DNA repeats stimulate gene editing via double-strand break repair in an episomal context and allude to efficient gene editing of the human chromosome using fragile DNA sequences.

In Silico Analysis Identifies a Novel Role for Androgens in the Regulation of Human Endometrial Apoptosis

PubMed Central

Marshall, Elaine; Lowrey, Jacqueline; MacPherson, Sheila; Maybin, Jacqueline A.; Collins, Frances; Critchley, Hilary O. D.

2011-01-01

Context: The endometrium is a multicellular, steroid-responsive tissue that undergoes dynamic remodeling every menstrual cycle in preparation for implantation and, in absence of pregnancy, menstruation. Androgen receptors are present in the endometrium. Objective: The objective of the study was to investigate the impact of androgens on human endometrial stromal cells (hESC). Design: Bioinformatics was used to identify an androgen-regulated gene set and processes associated with their function. Regulation of target genes and impact of androgens on cell function were validated using primary hESC. Setting: The study was conducted at the University Research Institute. Patients: Endometrium was collected from women with regular menses; tissues were used for recovery of cells, total mRNA, or protein and for immunohistochemistry. Results: A new endometrial androgen target gene set (n = 15) was identified. Bioinformatics revealed 12 of these genes interacted in one pathway and identified an association with control of cell survival. Dynamic androgen-dependent changes in expression of the gene set were detected in hESC with nine significantly down-regulated at 2 and/or 8 h. Treatment of hESC with dihydrotestosterone reduced staurosporine-induced apoptosis and cell migration/proliferation. Conclusions: Rigorous in silico analysis resulted in identification of a group of androgen-regulated genes expressed in human endometrium. Pathway analysis and functional assays suggest androgen-dependent changes in gene expression may have a significant impact on stromal cell proliferation, migration, and survival. These data provide the platform for further studies on the role of circulatory or local androgens in the regulation of endometrial function and identify androgens as candidates in the pathogenesis of common endometrial disorders including polycystic ovarian syndrome, cancer, and endometriosis. PMID:21865353

Defining the gene expression signature of rhabdomyosarcoma by meta-analysis

PubMed Central

Romualdi, Chiara; De Pittà, Cristiano; Tombolan, Lucia; Bortoluzzi, Stefania; Sartori, Francesca; Rosolen, Angelo; Lanfranchi, Gerolamo

2006-01-01

Background Rhabdomyosarcoma is a highly malignant soft tissue sarcoma in childhood and arises as a consequence of regulatory disruption of the growth and differentiation pathways of myogenic precursor cells. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of RMS gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets have opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated. Results In this work we performed a meta-analysis on four microarray and two SAGE datasets of gene expression data on RMS in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Regulatory pathways and biological processes significantly enriched has been investigated and a list of differentially meta-profiles have been identified as possible candidate of aggressiveness of RMS. Conclusion Our results point to a general down regulation of the energy production pathways, suggesting a hypoxic physiology for RMS cells. This result agrees with the high malignancy of RMS and with its resistance to most of the therapeutic treatments. In this context, different isoforms of the ANT gene have been consistently identified for the first time as differentially expressed in RMS. This gene is involved in anti-apoptotic processes when cells grow in low oxygen conditions. These new insights in the biological processes responsible of RMS growth and development demonstrate the effective advantage of the use of integrated analysis of gene expression studies. PMID:17090319

Use of mutation spectra analysis software.

PubMed

Rogozin, I; Kondrashov, F; Glazko, G

2001-02-01

The study and comparison of mutation(al) spectra is an important problem in molecular biology, because these spectra often reflect on important features of mutations and their fixation. Such features include the interaction of DNA with various mutagens, the function of repair/replication enzymes, and properties of target proteins. It is known that mutability varies significantly along nucleotide sequences, such that mutations often concentrate at certain positions, called "hotspots," in a sequence. In this paper, we discuss in detail two approaches for mutation spectra analysis: the comparison of mutation spectra with a HG-PUBL program, (FTP: sunsite.unc.edu/pub/academic/biology/dna-mutations/hyperg) and hotspot prediction with the CLUSTERM program (www.itba.mi.cnr.it/webmutation; ftp.bionet.nsc.ru/pub/biology/dbms/clusterm.zip). Several other approaches for mutational spectra analysis, such as the analysis of a target protein structure, hotspot context revealing, multiple spectra comparisons, as well as a number of mutation databases are briefly described. Mutation spectra in the lacI gene of E. coli and the human p53 gene are used for illustration of various difficulties of such analysis. Copyright 2001 Wiley-Liss, Inc.

Genomic analysis of the type VI secretion systems in Pseudomonas spp.: novel clusters and putative effectors uncovered.

PubMed

Barret, Matthieu; Egan, Frank; Fargier, Emilie; Morrissey, John P; O'Gara, Fergal

2011-06-01

Bacteria encode multiple protein secretion systems that are crucial for interaction with the environment and with hosts. In recent years, attention has focused on type VI secretion systems (T6SSs), which are specialized transporters widely encoded in Proteobacteria. The myriad of processes associated with these secretion systems could be explained by subclasses of T6SS, each involved in specialized functions. To assess diversity and predict function associated with different T6SSs, comparative genomic analysis of 34 Pseudomonas genomes was performed. This identified 70 T6SSs, with at least one locus in every strain, except for Pseudomonas stutzeri A1501. By comparing 11 core genes of the T6SS, it was possible to identify five main Pseudomonas phylogenetic clusters, with strains typically carrying T6SSs from more than one clade. In addition, most strains encode additional vgrG and hcp genes, which encode extracellular structural components of the secretion apparatus. Using a combination of phylogenetic and meta-analysis of transcriptome datasets it was possible to associate specific subsets of VgrG and Hcp proteins with each Pseudomonas T6SS clade. Moreover, a closer examination of the genomic context of vgrG genes in multiple strains highlights a number of additional genes associated with these regions. It is proposed that these genes may play a role in secretion or alternatively could be new T6S effectors.

TMPRSS2:ERG Gene Fusions in Prostate Cancer of West African Men and a Meta-Analysis of Racial Differences

PubMed Central

Zhou, Cindy Ke; Young, Denise; Yeboah, Edward D; Coburn, Sally B; Tettey, Yao; Biritwum, Richard B; Adjei, Andrew A; Tay, Evelyn; Niwa, Shelley; Truelove, Ann; Welsh, Judith; Mensah, James E; Hoover, Robert N; Sesterhenn, Isabell A; Hsing, Ann W; Srivastava, Shiv; Cook, Michael B

2017-01-01

Abstract The prevalence of fusions of the transmembrane protease, serine 2, gene (TMPRSS2) with the erythroblast transformation-specific–related gene (ERG), or TMPRSS2:ERG, in prostate cancer varies by race. However, such somatic aberration and its association with prognostic factors have neither been studied in a West African population nor been systematically reviewed in the context of racial differences. We used immunohistochemistry to assess oncoprotein encoded by the ERG gene as the established surrogate of ERG fusion genes among 262 prostate cancer biopsies from the Ghana Prostate Study (2004–2006). Poisson regression with robust variance estimation provided prevalence ratios and 95% confidence intervals of ERG expression in relation to patient characteristics. We found that 47 of 262 (18%) prostate cancers were ERG-positive, and being negative for ERG staining was associated with higher Gleason score. We further conducted a systematic review and meta-analysis of TMPRSS2:ERG fusions in relation to race, Gleason score, and tumor stage, combining results from Ghana with 40 additional studies. Meta-analysis showed the prevalence of TMPRSS2:ERG fusions in prostate cancer to be highest in men of European descent (49%), followed by men of Asian (27%) and then African (25%) descent. The lower prevalence of TMPRSS2:ERG fusions in men of African descent implies that alternative genomic mechanisms might explain the disproportionately high prostate cancer burden in such populations. PMID:28633309

Transcriptional activation of rat creatine kinase B by 17beta-estradiol in MCF-7 cells involves an estrogen responsive element and GC-rich sites.

PubMed

Wang, F; Samudio, I; Safe, S

2001-01-01

The rat creatine kinase B (CKB) gene is induced by estrogen in the uterus, and constructs containing rat CKB gene promoter inserts are highly estrogen-responsive in cell culture. Analysis of the upstream -568 to -523 region of the promoter in HeLa cells has identified an imperfect palindromic estrogen response element (ERE) that is required for hormone inducibility. Analysis of the CKB gene promoter in MCF-7 breast cancer cells confirmed that pCKB7 (containing the -568 to -523 promoter insert) was estrogen-responsive in transient transfection studies. However, mutation and deletion analysis of this region of the promoter showed that two GC-rich sites and the concensus ERE were functional cis-elements that bound estrogen receptor alpha (ERalpha)/Sp1 and ERalpha proteins, respectively. The role of these elements was confirmed in gel mobility shift and chromatin immunoprecipitation assays and transfection studies in MDA-MB-231 and Schneider Drosophila SL-2 cells. These results show that transcriptional activation of CKB by estrogen is dependent, in part, on ERalpha/Sp1 action which is cell context-dependent. Copyright 2001 Wiley-Liss, Inc.

Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies.

PubMed

Smith, Jennifer A; Zhao, Wei; Yasutake, Kalyn; August, Carmella; Ratliff, Scott M; Faul, Jessica D; Boerwinkle, Eric; Chakravarti, Aravinda; Diez Roux, Ana V; Gao, Yan; Griswold, Michael E; Heiss, Gerardo; Kardia, Sharon L R; Morrison, Alanna C; Musani, Solomon K; Mwasongwe, Stanford; North, Kari E; Rose, Kathryn M; Sims, Mario; Sun, Yan V; Weir, David R; Needham, Belinda L

2017-12-18

Inter-individual variability in blood pressure (BP) is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS), to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region ( p = 0.0019). In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region ( p = 0.0048). This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.

Pathway Analysis in Attention Deficit Hyperactivity Disorder: An Ensemble Approach

PubMed Central

Mooney, Michael A.; McWeeney, Shannon K.; Faraone, Stephen V.; Hinney, Anke; Hebebrand, Johannes; Nigg, Joel T.; Wilmot, Beth

2016-01-01

Despite a wealth of evidence for the role of genetics in attention deficit hyperactivity disorder (ADHD), specific and definitive genetic mechanisms have not been identified. Pathway analyses, a subset of gene-set analyses, extend the knowledge gained from genome-wide association studies (GWAS) by providing functional context for genetic associations. However, there are numerous methods for association testing of gene sets and no real consensus regarding the best approach. The present study applied six pathway analysis methods to identify pathways associated with ADHD in two GWAS datasets from the Psychiatric Genomics Consortium. Methods that utilize genotypes to model pathway-level effects identified more replicable pathway associations than methods using summary statistics. In addition, pathways implicated by more than one method were significantly more likely to replicate. A number of brain-relevant pathways, such as RhoA signaling, glycosaminoglycan biosynthesis, fibroblast growth factor receptor activity, and pathways containing potassium channel genes, were nominally significant by multiple methods in both datasets. These results support previous hypotheses about the role of regulation of neurotransmitter release, neurite outgrowth and axon guidance in contributing to the ADHD phenotype and suggest the value of cross-method convergence in evaluating pathway analysis results. PMID:27004716

Petunia, Your Next Supermodel?

PubMed Central

Vandenbussche, Michiel; Chambrier, Pierre; Rodrigues Bento, Suzanne; Morel, Patrice

2016-01-01

Plant biology in general, and plant evo–devo in particular would strongly benefit from a broader range of available model systems. In recent years, technological advances have facilitated the analysis and comparison of individual gene functions in multiple species, representing now a fairly wide taxonomic range of the plant kingdom. Because genes are embedded in gene networks, studying evolution of gene function ultimately should be put in the context of studying the evolution of entire gene networks, since changes in the function of a single gene will normally go together with further changes in its network environment. For this reason, plant comparative biology/evo–devo will require the availability of a defined set of ‘super’ models occupying key taxonomic positions, in which performing gene functional analysis and testing genetic interactions ideally is as straightforward as, e.g., in Arabidopsis. Here we review why petunia has the potential to become one of these future supermodels, as a representative of the Asterid clade. We will first detail its intrinsic qualities as a model system. Next, we highlight how the revolution in sequencing technologies will now finally allows exploitation of the petunia system to its full potential, despite that petunia has already a long history as a model in plant molecular biology and genetics. We conclude with a series of arguments in favor of a more diversified multi-model approach in plant biology, and we point out where the petunia model system may further play a role, based on its biological features and molecular toolkit. PMID:26870078

The ethics of human gene transfer.

PubMed

Kimmelman, Jonathan

2008-03-01

Almost 20 years since the first gene-transfer trial was carried out in humans, the field has made significant advances towards clinical application. Nevertheless, it continues to face numerous unresolved ethical challenges--among them are the question of when to initiate human testing, the acceptability of germline modification and whether the technique should be applied to the enhancement of traits. Although such issues have precedents in other medical contexts, they take on a different character in gene transfer, in part because of the scientific uncertainty and the social context of innovation.

Comprehensive analysis of pathway or functionally related gene expression in the National Cancer Institute's anticancer screen.

PubMed

Huang, Ruili; Wallqvist, Anders; Covell, David G

2006-03-01

We have analyzed the level of gene coregulation, using gene expression patterns measured across the National Cancer Institute's 60 tumor cell panels (NCI(60)), in the context of predefined pathways or functional categories annotated by KEGG (Kyoto Encyclopedia of Genes and Genomes), BioCarta, and GO (Gene Ontology). Statistical methods were used to evaluate the level of gene expression coherence (coordinated expression) by comparing intra- and interpathway gene-gene correlations. Our results show that gene expression in pathways, or groups of functionally related genes, has a significantly higher level of coherence than that of a randomly selected set of genes. Transcriptional-level gene regulation appears to be on a "need to be" basis, such that pathways comprising genes encoding closely interacting proteins and pathways responsible for vital cellular processes or processes that are related to growth or proliferation, specifically in cancer cells, such as those engaged in genetic information processing, cell cycle, energy metabolism, and nucleotide metabolism, tend to be more modular (lower degree of gene sharing) and to have genes significantly more coherently expressed than most signaling and regular metabolic pathways. Hierarchical clustering of pathways based on their differential gene expression in the NCI(60) further revealed interesting interpathway communications or interactions indicative of a higher level of pathway regulation. The knowledge of the nature of gene expression regulation and biological pathways can be applied to understanding the mechanism by which small drug molecules interfere with biological systems.

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

Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes.

PubMed

Feuermann, Marc; Gaudet, Pascale; Mi, Huaiyu; Lewis, Suzanna E; Thomas, Paul D

2016-01-01

We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This 'GO Phylogenetic Annotation' approach integrates GO annotations from evolutionarily related genes across ∼100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations.Database URL: http://amigo.geneontology.org/amigo. © The Author(s) 2016. Published by Oxford University Press.

Broad genomic and transcriptional analysis reveals a highly derived genome in dinoflagellate mitochondria

PubMed Central

Jackson, Christopher J; Norman, John E; Schnare, Murray N; Gray, Michael W; Keeling, Patrick J; Waller, Ross F

2007-01-01

Background Dinoflagellates comprise an ecologically significant and diverse eukaryotic phylum that is sister to the phylum containing apicomplexan endoparasites. The mitochondrial genome of apicomplexans is uniquely reduced in gene content and size, encoding only three proteins and two ribosomal RNAs (rRNAs) within a highly compacted 6 kb DNA. Dinoflagellate mitochondrial genomes have been comparatively poorly studied: limited available data suggest some similarities with apicomplexan mitochondrial genomes but an even more radical type of genomic organization. Here, we investigate structure, content and expression of dinoflagellate mitochondrial genomes. Results From two dinoflagellates, Crypthecodinium cohnii and Karlodinium micrum, we generated over 42 kb of mitochondrial genomic data that indicate a reduced gene content paralleling that of mitochondrial genomes in apicomplexans, i.e., only three protein-encoding genes and at least eight conserved components of the highly fragmented large and small subunit rRNAs. Unlike in apicomplexans, dinoflagellate mitochondrial genes occur in multiple copies, often as gene fragments, and in numerous genomic contexts. Analysis of cDNAs suggests several novel aspects of dinoflagellate mitochondrial gene expression. Polycistronic transcripts were found, standard start codons are absent, and oligoadenylation occurs upstream of stop codons, resulting in the absence of termination codons. Transcripts of at least one gene, cox3, are apparently trans-spliced to generate full-length mRNAs. RNA substitutional editing, a process previously identified for mRNAs in dinoflagellate mitochondria, is also implicated in rRNA expression. Conclusion The dinoflagellate mitochondrial genome shares the same gene complement and fragmentation of rRNA genes with its apicomplexan counterpart. However, it also exhibits several unique characteristics. Most notable are the expansion of gene copy numbers and their arrangements within the genome, RNA editing, loss of stop codons, and use of trans-splicing. PMID:17897476

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

PubMed Central

2012-01-01

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods. Reviewers This article was reviewed by Arcady Mushegian, Byung-Soo Kim and Joel Bader. PMID:23227854

Shotgun Bisulfite Sequencing of the Betula platyphylla Genome Reveals the Tree’s DNA Methylation Patterning

PubMed Central

Su, Chang; Wang, Chao; He, Lin; Yang, Chuanping; Wang, Yucheng

2014-01-01

DNA methylation plays a critical role in the regulation of gene expression. Most studies of DNA methylation have been performed in herbaceous plants, and little is known about the methylation patterns in tree genomes. In the present study, we generated a map of methylated cytosines at single base pair resolution for Betula platyphylla (white birch) by bisulfite sequencing combined with transcriptomics to analyze DNA methylation and its effects on gene expression. We obtained a detailed view of the function of DNA methylation sequence composition and distribution in the genome of B. platyphylla. There are 34,460 genes in the whole genome of birch, and 31,297 genes are methylated. Conservatively, we estimated that 14.29% of genomic cytosines are methylcytosines in birch. Among the methylation sites, the CHH context accounts for 48.86%, and is the largest proportion. Combined transcriptome and methylation analysis showed that the genes with moderate methylation levels had higher expression levels than genes with high and low methylation. In addition, methylated genes are highly enriched for the GO subcategories of binding activities, catalytic activities, cellular processes, response to stimulus and cell death, suggesting that methylation mediates these pathways in birch trees. PMID:25514241

Distinct effects of struvite and biochar amendment on the class 1 integron antibiotic resistance gene cassettes in phyllosphere and rhizosphere.

PubMed

An, Xin-Li; Chen, Qing-Lin; Zhu, Dong; Su, Jian-Qiang

2018-08-01

Struvite recovered from wastewater is promising for recycling phosphorus into soil as fertilizers. However, struvite application may prompt the proliferation of antibiotic resistance in soil and plant. This study examined the impacts of struvite application and biochar amendment on integrons abundance and gene cassette contexts in rhizosphere soil and phyllosphere using quantitative PCR and clone library analysis. Microcosm experiments revealed that class 1 integron was the most prevalent in all samples, with higher concentration and higher relative abundance in rhizosphere than those in phyllosphere. The majority of resistance gene cassettes were associated with genes encoding resistance to aminoglycosides, beta-lactams and chloramphenicols. Struvite application significantly increased the genetic diversity of antibiotic resistance gene cassettes in both rhizosphere and phyllosphere. However, biochar amendment attenuated the increasing effect of struvite application exerting on the class 1 integron antibiotic resistance gene cassette pool in phyllosphere. These findings highlighted human activities to be the source of integron gene cassette pool and raised the possibility of using biochar amendment as an alternative mean for mitigating antibiotic resistance in environments. Copyright © 2018 Elsevier B.V. All rights reserved.

Aniline exposure associated with up-regulated transcriptional responses of three glutathione S-transferase Delta genes in Drosophila melanogaster.

PubMed

Chan, Wen-Chiao; Chien, Yi-Chih; Chien, Cheng-I

2015-03-01

Complex transcriptional profile of glutathione S-transferase Delta cluster genes occurred in the developmental process of the fruit fly Drosophila melanogaster. The purpose of this project was to quantify the expression levels of Gst Delta class genes altered by aniline exposure and to understand the relationship between aniline dosages and the variation of Gst Delta genes expressed in D. melanogaster. Using RT-PCR expression assays, the expression patterns of the transcript mRNAs of the glutathione S-transferase Delta genes were revealed and their expression levels were measured at eggs, larvae, pupae and adults. The adult stage was selected for further dose-response assays. After analysis, the results indicated that three Gst Delta genes (Gst D2, Gst D5 and Gst D6) were found to show a peak of up-regulated transcriptional response at 6-8h of exposure of aniline. Furthermore, the dose-response relationship of their induction levels within the dose regiments (from 1.2 to 2.0 μl/tube) had been measured. The expression patterns and annotations of these genes were discussed in the context. Copyright © 2015 Elsevier B.V. All rights reserved.

A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

PubMed Central

Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H.; Asselbergs, Folkert W.; Gilbert-Diamond, Diane

2013-01-01

We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR’s constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR’s testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. PMID:23805232

Expression of interest: transcriptomics and the designation of conservation units.

PubMed

Hansen, Michael M

2010-05-01

An important task within conservation genetics consists in defining intraspecific conservation units. Most conceptual frameworks involve two steps: (i) identifying demographically independent units, and (ii) evaluating their degree of adaptive divergence. Whereas a plethora of methods are available for delineating genetic population structure, assessment of functional genetic divergence remains a challenge. In this issue, Tymchuk et al. (2010) study Atlantic salmon (Salmo salar) populations using both microsatellite markers and analysis of global gene expression. They show that important gene expression differences exist that can be interpreted in the context of different ecological conditions experienced by the populations, along with the populations' histories. This demonstrates an important potential role of transcriptomics for designating conservation units.

The application of transcriptomic data in the authentication of beef derived from contrasting production systems.

PubMed

Sweeney, Torres; Lejeune, Alex; Moloney, Aidan P; Monahan, Frank J; Gettigan, Paul Mc; Downey, Gerard; Park, Stephen D E; Ryan, Marion T

2016-09-21

Differences between cattle production systems can influence the nutritional and sensory characteristics of beef, in particular its fatty acid (FA) composition. As beef products derived from pasture-based systems can demand a higher premium from consumers, there is a need to understand the biological characteristics of pasture produced meat and subsequently to develop methods of authentication for these products. Here, we describe an approach to authentication that focuses on differences in the transcriptomic profile of muscle from animals finished in different systems of production of practical relevance to the Irish beef industry. The objectives of this study were to identify a panel of differentially expressed (DE) genes/networks in the muscle of cattle raised outdoors on pasture compared to animals raised indoors on a concentrate based diet and to subsequently identify an optimum panel which can classify the meat based on a production system. A comparison of the muscle transcriptome of outdoor/pasture-fed and Indoor/concentrate-fed cattle resulted in the identification of 26 DE genes. Functional analysis of these genes identified two significant networks (1: Energy Production, Lipid Metabolism, Small Molecule Biochemistry; and 2: Lipid Metabolism, Molecular Transport, Small Molecule Biochemistry), both of which are involved in FA metabolism. The expression of selected up-regulated genes in the outdoor/pasture-fed animals correlated positively with the total n-3 FA content of the muscle. The pathway and network analysis of the DE genes indicate that peroxisome proliferator-activated receptor (PPAR) and FYN/AMPK could be implicit in the regulation of these alterations to the lipid profile. In terms of authentication, the expression profile of three DE genes (ALAD, EIF4EBP1 and NPNT) could almost completely separate the samples based on production system (95 % authentication for animals on pasture-based and 100 % for animals on concentrate- based diet) in this context. The majority of DE genes between muscle of the outdoor/pasture-fed and concentrate-fed cattle were related to lipid metabolism and in particular β-oxidation. In this experiment the combined expression profiles of ALAD, EIF4EBP1 and NPNT were optimal in classifying the muscle transcriptome based on production system. Given the overall lack of comparable studies and variable concordance with those that do exist, the use of transcriptomic data in authenticating production systems requires more exploration across a range of contexts and breeds.

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

PubMed

Dey-Rao, Rama; Sinha, Animesh A

2017-01-28

Significant gaps remain regarding the pathomechanisms underlying the autoimmune response in vitiligo (VL), where the loss of self-tolerance leads to the targeted killing of melanocytes. Specifically, there is incomplete information regarding alterations in the systemic environment that are relevant to the disease state. We undertook a genome-wide profiling approach to examine gene expression in the peripheral blood of VL patients and healthy controls in the context of our previously published VL-skin gene expression profile. We used several in silico bioinformatics-based analyses to provide new insights into disease mechanisms and suggest novel targets for future therapy. Unsupervised clustering methods of the VL-blood dataset demonstrate a "disease-state"-specific set of co-expressed genes. Ontology enrichment analysis of 99 differentially expressed genes (DEGs) uncovers a down-regulated immune/inflammatory response, B-Cell antigen receptor (BCR) pathways, apoptosis and catabolic processes in VL-blood. There is evidence for both type I and II interferon (IFN) playing a role in VL pathogenesis. We used interactome analysis to identify several key blood associated transcriptional factors (TFs) from within (STAT1, STAT6 and NF-kB), as well as "hidden" (CREB1, MYC, IRF4, IRF1, and TP53) from the dataset that potentially affect disease pathogenesis. The TFs overlap with our reported lesional-skin transcriptional circuitry, underscoring their potential importance to the disease. We also identify a shared VL-blood and -skin transcriptional "hot spot" that maps to chromosome 6, and includes three VL-blood dysregulated genes (PSMB8, PSMB9 and TAP1) described as potential VL-associated genetic susceptibility loci. Finally, we provide bioinformatics-based support for prioritizing dysregulated genes in VL-blood or skin as potential therapeutic targets. We examined the VL-blood transcriptome in context with our (previously published) VL-skin transcriptional profile to address a major gap in knowledge regarding the systemic changes underlying skin-specific manifestation of vitiligo. Several transcriptional "hot spots" observed in both environments offer prioritized targets for identifying disease risk genes. Finally, within the transcriptional framework of VL, we identify five novel molecules (STAT1, PRKCD, PTPN6, MYC and FGFR2) that lend themselves to being targeted by drugs for future potential VL-therapy.

Outcome-Driven Cluster Analysis with Application to Microarray Data.

PubMed

Hsu, Jessie J; Finkelstein, Dianne M; Schoenfeld, David A

2015-01-01

One goal of cluster analysis is to sort characteristics into groups (clusters) so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes) into groups of highly correlated genes that have the same effect on the outcome (recovery). We propose a random effects model where the genes within each group (cluster) equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome.

Positional orthology: putting genomic evolutionary relationships into context

PubMed Central

2011-01-01

Orthology is a powerful refinement of homology that allows us to describe more precisely the evolution of genomes and understand the function of the genes they contain. However, because orthology is not concerned with genomic position, it is limited in its ability to describe genes that are likely to have equivalent roles in different genomes. Because of this limitation, the concept of ‘positional orthology’ has emerged, which describes the relation between orthologous genes that retain their ancestral genomic positions. In this review, we formally define this concept, for which we introduce the shorter term ‘toporthology’, with respect to the evolutionary events experienced by a gene’s ancestors. Through a discussion of recent studies on the role of genomic context in gene evolution, we show that the distinction between orthology and toporthology is biologically significant. We then review a number of orthology prediction methods that take genomic context into account and thus that may be used to infer the important relation of toporthology. PMID:21705766

ProbCD: enrichment analysis accounting for categorization uncertainty.

PubMed

Vêncio, Ricardo Z N; Shmulevich, Ilya

2007-10-12

As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test. We developed an open-source R-based software to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: http://xerad.systemsbiology.net/ProbCD/. We present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation.

Modifier gene study of meconium ileus in cystic fibrosis: statistical considerations and gene mapping results

PubMed Central

Dorfman, Ruslan; Li, Weili; Sun, Lei; Lin, Fan; Wang, Yongqian; Sandford, Andrew; Paré, Peter D.; McKay, Karen; Kayserova, Hana; Piskackova, Tereza; Macek, Milan; Czerska, Kamila; Sands, Dorota; Tiddens, Harm; Margarit, Sonia; Repetto, Gabriela; Sontag, Marci K.; Accurso, Frank J.; Blackman, Scott; Cutting, Garry R.; Tsui, Lap-Chee; Corey, Mary; Durie, Peter; Zielenski, Julian; Strug, Lisa J.

2010-01-01

Cystic fibrosis (CF) is a monogenic disease due to mutations in the CFTR gene. Yet, variability in CF disease presentation is presumed to be affected by modifier genes, such as those recently demonstrated for the pulmonary aspect. Here, we conduct a modifier gene study for meconium ileus (MI), an intestinal obstruction that occurs in 16–20% of CF newborns, providing linkage and association results from large family and case–control samples. Linkage analysis of modifier traits is different than linkage analysis of primary traits on which a sample was ascertained. Here, we articulate a source of confounding unique to modifier gene studies and provide an example of how one might overcome the confounding in the context of linkage studies. Our linkage analysis provided evidence of a MI locus on chromosome 12p13.3, which was segregating in up to 80% of MI families with at least one affected offspring (HLOD = 2.9). Fine mapping of the 12p13.3 region in a large case–control sample of pancreatic insufficient Canadian CF patients with and without MI pointed to the involvement of ADIPOR2 in MI (p = 0.002). This marker was substantially out of Hardy–Weinberg equilibrium in the cases only, and provided evidence of a cohort effect. The association with rs9300298 in the ADIPOR2 gene at the 12p13.3 locus was replicated in an independent sample of CF families. A protective locus, using the phenotype of no-MI, mapped to 4q13.3 (HLOD = 3.19), with substantial heterogeneity. A candidate gene in the region, SLC4A4, provided preliminary evidence of association (p = 0.002), warranting further follow-up studies. Our linkage approach was used to direct our fine-mapping studies, which uncovered two potential modifier genes worthy of follow-up. PMID:19662435

Systems genomics analysis centered on epigenetic inheritance supports development of a unified theory of biology.

PubMed

Sharma, Abhay

2015-11-01

New discoveries are increasingly demanding integration of epigenetics, molecular biology, genomic networks and physiology with evolution. This article provides a proof of concept for evolutionary transgenerational systems biology, proposed recently in the context of epigenetic inheritance in mammals. Gene set enrichment analysis of available genome-level mammalian data presented here seem consistent with the concept that: (1) heritable information about environmental effects in somatic cells is communicated to the germline by circulating microRNAs (miRNAs) or other RNAs released in physiological fluids; (2) epigenetic factors including miRNA-like small RNAs, DNA methylation and histone modifications are propagated across generations via gene networks; and (3) inherited epigenetic variations in the form of methylated cytosines are fixed in the population as thymines over the evolutionary time course. The analysis supports integration of physiology and epigenetics with inheritance and evolution. This may catalyze efforts to develop a unified theory of biology. © 2015. Published by The Company of Biologists Ltd.

Prioritizing GWAS Results: A Review of Statistical Methods and Recommendations for Their Application

PubMed Central

Cantor, Rita M.; Lange, Kenneth; Sinsheimer, Janet S.

2010-01-01

Genome-wide association studies (GWAS) have rapidly become a standard method for disease gene discovery. A substantial number of recent GWAS indicate that for most disorders, only a few common variants are implicated and the associated SNPs explain only a small fraction of the genetic risk. This review is written from the viewpoint that findings from the GWAS provide preliminary genetic information that is available for additional analysis by statistical procedures that accumulate evidence, and that these secondary analyses are very likely to provide valuable information that will help prioritize the strongest constellations of results. We review and discuss three analytic methods to combine preliminary GWAS statistics to identify genes, alleles, and pathways for deeper investigations. Meta-analysis seeks to pool information from multiple GWAS to increase the chances of finding true positives among the false positives and provides a way to combine associations across GWAS, even when the original data are unavailable. Testing for epistasis within a single GWAS study can identify the stronger results that are revealed when genes interact. Pathway analysis of GWAS results is used to prioritize genes and pathways within a biological context. Following a GWAS, association results can be assigned to pathways and tested in aggregate with computational tools and pathway databases. Reviews of published methods with recommendations for their application are provided within the framework for each approach. PMID:20074509

Systems Genetics Analysis of GWAS reveals Novel Associations between Key Biological Processes and Coronary Artery Disease

PubMed Central

Ghosh, Sujoy; Vivar, Juan; Nelson, Christopher P; Willenborg, Christina; Segrè, Ayellet V; Mäkinen, Ville-Petteri; Nikpay, Majid; Erdmann, Jeannette; Blankenberg, Stefan; O'Donnell, Christopher; März, Winfried; Laaksonen, Reijo; Stewart, Alexandre FR; Epstein, Stephen E; Shah, Svati H; Granger, Christopher B; Hazen, Stanley L; Kathiresan, Sekar; Reilly, Muredach P; Yang, Xia; Quertermous, Thomas; Samani, Nilesh J; Schunkert, Heribert; Assimes, Themistocles L; McPherson, Ruth

2016-01-01

Objective Genome-wide association (GWA) studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks. Approaches and Results Employing pathways (gene sets) from Reactome, we carried out a two-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CADGWAS data sets (9,889 cases/11,089 controls), nominally significant gene-sets were tested for replication in a meta-analysis of 9 additional studies (15,502 cases/55,730 controls) from the CARDIoGRAM Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication p<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix integrity, innate immunity, axon guidance, and signaling by PDRF, NOTCH, and the TGF-β/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (e.g. semaphorin regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared to random networks (p<0.001). Network centrality analysis (‘degree’ and ‘betweenness’) further identified genes (e.g. NCAM1, FYN, FURIN etc.) likely to play critical roles in the maintenance and functioning of several of the replicated pathways. Conclusions These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD. PMID:25977570

Legal issues regarding gene editing at the beginning of life: an EU perspective.

PubMed

De Miguel Beriain, Iñigo

2017-09-01

The development of clustered regularly interspaced short palindromic repeats (CRISPR)-Cas gene-modification technologies has opened impressive possibilities for the biomedical sciences. However, their application to human embryos and early fetuses has raised huge ethical and legal discussions because it affects the human germline. This paper provides a critical and in-depth analysis of the current legal framework on this topic in the EU context and at the national level in the member states. It also offers an alternative interpretation of the regulation, so as to help researchers, practitioners, policy makers and society as a whole to find efficient responses to challenges that cannot wait for a legally updated answer. As a final result, this paper will show that eugenic uses of CRISP-Cas and any kind of modification intended to alter the human germ line are generally banned in the EU context, while basic research on human embryos is mostly permitted. The legal status of therapeutic applications of CRISPR-Cas on early fetuses, however, has not been adequately addressed by the EU zone regulation.

Identification, characterization and phylogenetic analysis of antifungal Trichoderma from tomato rhizosphere.

PubMed

Rai, Shalini; Kashyap, Prem Lal; Kumar, Sudheer; Srivastava, Alok Kumar; Ramteke, Pramod W

2016-01-01

The use of Trichoderma isolates with efficient antagonistic activity represents a potentially effective and alternative disease management strategy to replace health hazardous chemical control. In this context, twenty isolates were obtained from tomato rhizosphere and evaluated by their antagonistic activity against four fungal pathogens ( Fusarium oxysporum f. sp. lycopersici , Alternaria alternata , Colletotrichum gloeosporoides and Rhizoctonia solani ). The production of extracellular cell wall degrading enzymes of tested isolates was also measured. All the isolates significantly reduced the mycelial growth of tested pathogens but the amount of growth reduction varied significantly as well. There was a positive correlation between the antagonistic capacity of Trichoderma isolates towards fungal pathogens and their lytic enzyme production. The Trichoderma isolates were initially sorted according to morphology and based on the translation elongation factor 1-α gene sequence similarity, the isolates were designated as Trichoderma harzianum , T. koningii , T. asperellum , T. virens and T. viride . PCA analysis explained 31.53, 61.95, 62.22 and 60.25% genetic variation among Trichoderma isolates based on RAPD, REP-, ERIC- and BOX element analysis, respectively. ERG - 1 gene, encoding a squalene epoxidase has been used for the first time for diversity analysis of antagonistic Trichoderma from tomato rhizosphere. Phylogenetic analysis of ERG -1 gene sequences revealed close relatedness of ERG -1sequences with earlier reported sequences of Hypocrea lixii , T. arundinaceum and T. reesei. However, ERG -1 gene also showed heterogeneity among some antagonistic isolates and indicated the possibility of occurrence of squalene epoxidase driven triterpene biosynthesis as an alternative biocontrol mechanism in Trichoderma species.

Tissue- and stage-specific Wnt target gene expression is controlled subsequent to β-catenin recruitment to cis-regulatory modules.

PubMed

Nakamura, Yukio; de Paiva Alves, Eduardo; Veenstra, Gert Jan C; Hoppler, Stefan

2016-06-01

Key signalling pathways, such as canonical Wnt/β-catenin signalling, operate repeatedly to regulate tissue- and stage-specific transcriptional responses during development. Although recruitment of nuclear β-catenin to target genomic loci serves as the hallmark of canonical Wnt signalling, mechanisms controlling stage- or tissue-specific transcriptional responses remain elusive. Here, a direct comparison of genome-wide occupancy of β-catenin with a stage-matched Wnt-regulated transcriptome reveals that only a subset of β-catenin-bound genomic loci are transcriptionally regulated by Wnt signalling. We demonstrate that Wnt signalling regulates β-catenin binding to Wnt target genes not only when they are transcriptionally regulated, but also in contexts in which their transcription remains unaffected. The transcriptional response to Wnt signalling depends on additional mechanisms, such as BMP or FGF signalling for the particular genes we investigated, which do not influence β-catenin recruitment. Our findings suggest a more general paradigm for Wnt-regulated transcriptional mechanisms, which is relevant for tissue-specific functions of Wnt/β-catenin signalling in embryonic development but also for stem cell-mediated homeostasis and cancer. Chromatin association of β-catenin, even to functional Wnt-response elements, can no longer be considered a proxy for identifying transcriptionally Wnt-regulated genes. Context-dependent mechanisms are crucial for transcriptional activation of Wnt/β-catenin target genes subsequent to β-catenin recruitment. Our conclusions therefore also imply that Wnt-regulated β-catenin binding in one context can mark Wnt-regulated transcriptional target genes for different contexts. © 2016. Published by The Company of Biologists Ltd.

MicroScope-an integrated resource for community expertise of gene functions and comparative analysis of microbial genomic and metabolic data.

PubMed

Médigue, Claudine; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Gautreau, Guillaume; Josso, Adrien; Lajus, Aurélie; Langlois, Jordan; Pereira, Hugo; Planel, Rémi; Roche, David; Rollin, Johan; Rouy, Zoe; Vallenet, David

2017-09-12

The overwhelming list of new bacterial genomes becoming available on a daily basis makes accurate genome annotation an essential step that ultimately determines the relevance of thousands of genomes stored in public databanks. The MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Starting from the results of our syntactic, functional and relational annotation pipelines, MicroScope provides an integrated environment for the expert annotation and comparative analysis of prokaryotic genomes. It combines tools and graphical interfaces to analyze genomes and to perform the manual curation of gene function in a comparative genomics and metabolic context. In this article, we describe the free-of-charge MicroScope services for the annotation and analysis of microbial (meta)genomes, transcriptomic and re-sequencing data. Then, the functionalities of the platform are presented in a way providing practical guidance and help to the nonspecialists in bioinformatics. Newly integrated analysis tools (i.e. prediction of virulence and resistance genes in bacterial genomes) and original method recently developed (the pan-genome graph representation) are also described. Integrated environments such as MicroScope clearly contribute, through the user community, to help maintaining accurate resources. © The Author 2017. Published by Oxford University Press.

Systems Biology Approach to the Dissection of the Complexity of Regulatory Networks in the S. scrofa Cardiocirculatory System

PubMed Central

Martini, Paolo; Sales, Gabriele; Calura, Enrica; Brugiolo, Mattia; Lanfranchi, Gerolamo; Romualdi, Chiara; Cagnin, Stefano

2013-01-01

Genome-wide experiments are routinely used to increase the understanding of the biological processes involved in the development and maintenance of a variety of pathologies. Although the technical feasibility of this type of experiment has improved in recent years, data analysis remains challenging. In this context, gene set analysis has emerged as a fundamental tool for the interpretation of the results. Here, we review strategies used in the gene set approach, and using datasets for the pig cardiocirculatory system as a case study, we demonstrate how the use of a combination of these strategies can enhance the interpretation of results. Gene set analyses are able to distinguish vessels from the heart and arteries from veins in a manner that is consistent with the different cellular composition of smooth muscle cells. By integrating microRNA elements in the regulatory circuits identified, we find that vessel specificity is maintained through specific miRNAs, such as miR-133a and miR-143, which show anti-correlated expression with their mRNA targets. PMID:24284405

The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison

PubMed Central

Sioson, Allan A; Mane, Shrinivasrao P; Li, Pinghua; Sha, Wei; Heath, Lenwood S; Bohnert, Hans J; Grene, Ruth

2006-01-01

Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In one experiment, MIV is a better choice than IIV as input to data normalization and statistical analysis methods, as it yields as greater number of statistically significant differentially expressed genes; TM4 does not support the choice of MIV input data. Overall, the more flexible and extensive statistical models of Expresso achieve more accurate analytical results, when judged by the yardstick of qRT-PCR data, in the context of an experimental design of modest complexity. PMID:16626497

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

PubMed

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both local and global learning strategies, able to exploit the overall topology of the network. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Genome-wide network analysis of Wnt signaling in three pediatric cancers

NASA Astrophysics Data System (ADS)

Bao, Ju; Lee, Ho-Jin; Zheng, Jie J.

2013-10-01

Genomic structural alteration is common in pediatric cancers, and analysis of data generated by the Pediatric Cancer Genome Project reveals such tumor-related alterations in many Wnt signaling-associated genes. Most pediatric cancers are thought to arise within developing tissues that undergo substantial expansion during early organ formation, growth and maturation, and Wnt signaling plays an important role in this development. We examined three pediatric tumors--medullobastoma, early T-cell precursor acute lymphoblastic leukemia, and retinoblastoma--that show multiple genomic structural variations within Wnt signaling pathways. We mathematically modeled this pathway to investigate the effects of cancer-related structural variations on Wnt signaling. Surprisingly, we found that an outcome measure of canonical Wnt signaling was consistently similar in matched cancer cells and normal cells, even in the context of different cancers, different mutations, and different Wnt-related genes. Our results suggest that the cancer cells maintain a normal level of Wnt signaling by developing multiple mutations.

The Aquaporin Channel Repertoire of the Tardigrade Milnesium tardigradum

PubMed Central

Grohme, Markus A.; Mali, Brahim; Wełnicz, Weronika; Michel, Stephanie; Schill, Ralph O.; Frohme, Marcus

2013-01-01

Limno-terrestrial tardigrades are small invertebrates that are subjected to periodic drought of their micro-environment. They have evolved to cope with these unfavorable conditions by anhydrobiosis, an ametabolic state of low cellular water. During drying and rehydration, tardigrades go through drastic changes in cellular water content. By our transcriptome sequencing effort of the limno-terrestrial tardigrade Milnesium tardigradum and by a combination of cloning and targeted sequence assembly, we identified transcripts encoding eleven putative aquaporins. Analysis of these sequences proposed 2 classical aquaporins, 8 aquaglyceroporins and a single potentially intracellular unorthodox aquaporin. Using quantitative real-time PCR we analyzed aquaporin transcript expression in the anhydrobiotic context. We have identified additional unorthodox aquaporins in various insect genomes and have identified a novel common conserved structural feature in these proteins. Analysis of the genomic organization of insect aquaporin genes revealed several conserved gene clusters. PMID:23761966

Investigation of the biological properties of Cinnulin PF in the context of diabetes: mechanistic insights by genome-wide mRNA-Seq analysis.

PubMed

Rafehi, Haloom; Ververis, Katherine; Balcerczyk, Aneta; Ziemann, Mark; Ooi, Jenny; Hu, Sean; Kwa, Faith A A; Loveridge, Shanon J; Georgiadis, George T; El-Osta, Assam; Karagiannis, Tom C

2012-01-01

The accumulating evidence of the beneficial effects of cinnamon (Cinnamomum burmanni) in type-2 diabetes, a chronic age-associated disease, has prompted the commercialisation of various supplemental forms of the spice. One such supplement, Cinnulin PF(®), represents the water soluble fraction containing relatively high levels of the double-linked procyanidin type-A polymers of flavanoids. The overall aim of this study was to utilize genome-wide mRNA-Seq analysis to characterise the changes in gene expression caused by Cinnulin PF in immortalised human keratinocytes and microvascular endothelial cells, which are relevant with respect to diabetic complications. In summary, our findings provide insights into the mechanisms of action of Cinnulin PF in diabetes and diabetic complications. More generally, we identify relevant candidate genes which could provide the basis for further investigation.

Investigation of the biological properties of Cinnulin PF in the context of diabetes: mechanistic insights by genome-wide mRNA-Seq analysis

PubMed Central

Rafehi, Haloom; Ververis, Katherine; Balcerczyk, Aneta; Ziemann, Mark; Ooi, Jenny; Hu, Sean; Kwa, Faith A. A.; Loveridge, Shanon J.; Georgiadis, George T.; El-Osta, Assam; Karagiannis, Tom C.

2012-01-01

The accumulating evidence of the beneficial effects of cinnamon (Cinnamomum burmanni) in type-2 diabetes, a chronic age-associated disease, has prompted the commercialisation of various supplemental forms of the spice. One such supplement, Cinnulin PF®, represents the water soluble fraction containing relatively high levels of the double-linked procyanidin type-A polymers of flavanoids. The overall aim of this study was to utilize genome-wide mRNA-Seq analysis to characterise the changes in gene expression caused by Cinnulin PF in immortalised human keratinocytes and microvascular endothelial cells, which are relevant with respect to diabetic complications. In summary, our findings provide insights into the mechanisms of action of Cinnulin PF in diabetes and diabetic complications. More generally, we identify relevant candidate genes which could provide the basis for further investigation. PMID:22953038

A transcriptional dynamic network during Arabidopsis thaliana pollen development.

PubMed

Wang, Jigang; Qiu, Xiaojie; Li, Yuhua; Deng, Youping; Shi, Tieliu

2011-01-01

To understand transcriptional regulatory networks (TRNs), especially the coordinated dynamic regulation between transcription factors (TFs) and their corresponding target genes during development, computational approaches would represent significant advances in the genome-wide expression analysis. The major challenges for the experiments include monitoring the time-specific TFs' activities and identifying the dynamic regulatory relationships between TFs and their target genes, both of which are currently not yet available at the large scale. However, various methods have been proposed to computationally estimate those activities and regulations. During the past decade, significant progresses have been made towards understanding pollen development at each development stage under the molecular level, yet the regulatory mechanisms that control the dynamic pollen development processes remain largely unknown. Here, we adopt Networks Component Analysis (NCA) to identify TF activities over time course, and infer their regulatory relationships based on the coexpression of TFs and their target genes during pollen development. We carried out meta-analysis by integrating several sets of gene expression data related to Arabidopsis thaliana pollen development (stages range from UNM, BCP, TCP, HP to 0.5 hr pollen tube and 4 hr pollen tube). We constructed a regulatory network, including 19 TFs, 101 target genes and 319 regulatory interactions. The computationally estimated TF activities were well correlated to their coordinated genes' expressions during the development process. We clustered the expression of their target genes in the context of regulatory influences, and inferred new regulatory relationships between those TFs and their target genes, such as transcription factor WRKY34, which was identified that specifically expressed in pollen, and regulated several new target genes. Our finding facilitates the interpretation of the expression patterns with more biological relevancy, since the clusters corresponding to the activity of specific TF or the combination of TFs suggest the coordinated regulation of TFs to their target genes. Through integrating different resources, we constructed a dynamic regulatory network of Arabidopsis thaliana during pollen development with gene coexpression and NCA. The network illustrated the relationships between the TFs' activities and their target genes' expression, as well as the interactions between TFs, which provide new insight into the molecular mechanisms that control the pollen development.

The coffee genome hub: a resource for coffee genomes

PubMed Central

Dereeper, Alexis; Bocs, Stéphanie; Rouard, Mathieu; Guignon, Valentin; Ravel, Sébastien; Tranchant-Dubreuil, Christine; Poncet, Valérie; Garsmeur, Olivier; Lashermes, Philippe; Droc, Gaëtan

2015-01-01

The whole genome sequence of Coffea canephora, the perennial diploid species known as Robusta, has been recently released. In the context of the C. canephora genome sequencing project and to support post-genomics efforts, we developed the Coffee Genome Hub (http://coffee-genome.org/), an integrative genome information system that allows centralized access to genomics and genetics data and analysis tools to facilitate translational and applied research in coffee. We provide the complete genome sequence of C. canephora along with gene structure, gene product information, metabolism, gene families, transcriptomics, syntenic blocks, genetic markers and genetic maps. The hub relies on generic software (e.g. GMOD tools) for easy querying, visualizing and downloading research data. It includes a Genome Browser enhanced by a Community Annotation System, enabling the improvement of automatic gene annotation through an annotation editor. In addition, the hub aims at developing interoperability among other existing South Green tools managing coffee data (phylogenomics resources, SNPs) and/or supporting data analyses with the Galaxy workflow manager. PMID:25392413

The future: genetics advances in MEN1 therapeutic approaches and management strategies.

PubMed

Agarwal, Sunita K

2017-10-01

The identification of the multiple endocrine neoplasia type 1 ( MEN1 ) gene in 1997 has shown that germline heterozygous mutations in the MEN1 gene located on chromosome 11q13 predisposes to the development of tumors in the MEN1 syndrome. Tumor development occurs upon loss of the remaining normal copy of the MEN1 gene in MEN1-target tissues. Therefore, MEN1 is a classic tumor suppressor gene in the context of MEN1. This tumor suppressor role of the protein encoded by the MEN1 gene, menin, holds true in mouse models with germline heterozygous Men1 loss, wherein MEN1-associated tumors develop in adult mice after spontaneous loss of the remaining non-targeted copy of the Men1 gene. The availability of genetic testing for mutations in the MEN1 gene has become an essential part of the diagnosis and management of MEN1. Genetic testing is also helping to exclude mutation-negative cases in MEN1 families from the burden of lifelong clinical screening. In the past 20 years, efforts of various groups world-wide have been directed at mutation analysis, molecular genetic studies, mouse models, gene expression studies, epigenetic regulation analysis, biochemical studies and anti-tumor effects of candidate therapies in mouse models. This review will focus on the findings and advances from these studies to identify MEN1 germline and somatic mutations, the genetics of MEN1-related states, several protein partners of menin, the three-dimensional structure of menin and menin-dependent target genes. The ongoing impact of all these studies on disease prediction, management and outcomes will continue in the years to come. © 2017 Society for Endocrinology.

Characterization and Comparison of the CPK Gene Family in the Apple (Malus × domestica) and Other Rosaceae Species and Its Response to Alternaria alternata Infection.

PubMed

Wei, Menghan; Wang, Sanhong; Dong, Hui; Cai, Binhua; Tao, Jianmin

2016-01-01

As one of the Ca2+ sensors, calcium-dependent protein kinase (CPK) plays vital roles in immune and stress signaling, growth and development, and hormone responses, etc. Recently, the whole genome of apple (Malus × domestica), pear (Pyrus communis), peach (Prunus persica), plum (Prunus mume) and strawberry (Fragaria vesca) in Rosaceae family has been fully sequenced. However, little is known about the CPK gene family in these Rosaceae species. In this study, 123 CPK genes were identified from five Rosaceae species, including 37 apple CPKs, 37 pear CPKs, 17 peach CPKs, 16 strawberry CPKs, and 16 plum CPKs. Based on the phylogenetic tree topology and structural characteristics, we divided the CPK gene family into 4 distinct subfamilies: Group I, II, III, and IV. Whole-genome duplication (WGD) or segmental duplication played vital roles in the expansion of the CPK in these Rosaceae species. Most of segmental duplication pairs in peach and plum may have arisen from the γ triplication (~140 million years ago [MYA]), while in apple genome, many duplicated genes may have been derived from a recent WGD (30~45 MYA). Purifying selection also played a critical role in the function evolution of CPK family genes. Expression of apple CPK genes in response to apple pathotype of Alternaria alternata was verified by analysis of quantitative real-time RT-PCR (qPCR). Expression data demonstrated that CPK genes in apple might have evolved independently in different biological contexts. The analysis of evolution history and expression profile laid a foundation for further examining the function and complexity of the CPK gene family in Rosaceae.

Characterization and Comparison of the CPK Gene Family in the Apple (Malus × domestica) and Other Rosaceae Species and Its Response to Alternaria alternata Infection

PubMed Central

Wei, Menghan; Wang, Sanhong; Dong, Hui; Cai, Binhua; Tao, Jianmin

2016-01-01

As one of the Ca2+ sensors, calcium-dependent protein kinase (CPK) plays vital roles in immune and stress signaling, growth and development, and hormone responses, etc. Recently, the whole genome of apple (Malus × domestica), pear (Pyrus communis), peach (Prunus persica), plum (Prunus mume) and strawberry (Fragaria vesca) in Rosaceae family has been fully sequenced. However, little is known about the CPK gene family in these Rosaceae species. In this study, 123 CPK genes were identified from five Rosaceae species, including 37 apple CPKs, 37 pear CPKs, 17 peach CPKs, 16 strawberry CPKs, and 16 plum CPKs. Based on the phylogenetic tree topology and structural characteristics, we divided the CPK gene family into 4 distinct subfamilies: Group I, II, III, and IV. Whole-genome duplication (WGD) or segmental duplication played vital roles in the expansion of the CPK in these Rosaceae species. Most of segmental duplication pairs in peach and plum may have arisen from the γ triplication (~140 million years ago [MYA]), while in apple genome, many duplicated genes may have been derived from a recent WGD (30~45 MYA). Purifying selection also played a critical role in the function evolution of CPK family genes. Expression of apple CPK genes in response to apple pathotype of Alternaria alternata was verified by analysis of quantitative real-time RT-PCR (qPCR). Expression data demonstrated that CPK genes in apple might have evolved independently in different biological contexts. The analysis of evolution history and expression profile laid a foundation for further examining the function and complexity of the CPK gene family in Rosaceae. PMID:27186637

Discovering semantic features in the literature: a foundation for building functional associations

PubMed Central

Chagoyen, Monica; Carmona-Saez, Pedro; Shatkay, Hagit; Carazo, Jose M; Pascual-Montano, Alberto

2006-01-01

Background Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics, among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental approach, it is necessary to analyze these data in the context of previously known information about the biological entities under study. The literature is a particularly valuable source of information for experiment validation and interpretation. Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research. Results We present a method to create literature profiles for large sets of genes or proteins based on common semantic features extracted from a corpus of relevant documents. These profiles can be used to establish pair-wise similarities among genes, utilized in gene/protein classification or can be even combined with experimental measurements. Semantic features can be used by researchers to facilitate the understanding of the commonalities indicated by experimental results. Our approach is based on non-negative matrix factorization (NMF), a machine-learning algorithm for data analysis, capable of identifying local patterns that characterize a subset of the data. The literature is thus used to establish putative relationships among subsets of genes or proteins and to provide coherent justification for this clustering into subsets. We demonstrate the utility of the method by applying it to two independent and vastly different sets of genes. Conclusion The presented method can create literature profiles from documents relevant to sets of genes. The representation of genes as additive linear combinations of semantic features allows for the exploration of functional associations as well as for clustering, suggesting a valuable methodology for the validation and interpretation of high-throughput experimental data. PMID:16438716

Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules

PubMed Central

Bersanelli, Matteo; Mosca, Ettore; Remondini, Daniel; Castellani, Gastone; Milanesi, Luciano

2016-01-01

A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular interaction networks. We introduce the network smoothing index, a network-based quantity that allows to jointly quantify the amount of omics information in genes and in their network neighbourhood, using network diffusion to define network proximity. The approach is applicable to both descriptive and inferential statistics calculated on omics data. We also show that network resampling, applied to gene lists ranked by quantities derived from the network smoothing index, indicates the presence of significantly connected genes. As a proof of principle, we identified gene modules enriched in somatic mutations and transcriptional variations observed in samples of prostate adenocarcinoma (PRAD). In line with the local hypothesis, network smoothing index and network resampling underlined the existence of a connected component of genes harbouring molecular alterations in PRAD. PMID:27731320

Genome editing reveals a role for OCT4 in human embryogenesis.

PubMed

Fogarty, Norah M E; McCarthy, Afshan; Snijders, Kirsten E; Powell, Benjamin E; Kubikova, Nada; Blakeley, Paul; Lea, Rebecca; Elder, Kay; Wamaitha, Sissy E; Kim, Daesik; Maciulyte, Valdone; Kleinjung, Jens; Kim, Jin-Soo; Wells, Dagan; Vallier, Ludovic; Bertero, Alessandro; Turner, James M A; Niakan, Kathy K

2017-10-05

Despite their fundamental biological and clinical importance, the molecular mechanisms that regulate the first cell fate decisions in the human embryo are not well understood. Here we use CRISPR-Cas9-mediated genome editing to investigate the function of the pluripotency transcription factor OCT4 during human embryogenesis. We identified an efficient OCT4-targeting guide RNA using an inducible human embryonic stem cell-based system and microinjection of mouse zygotes. Using these refined methods, we efficiently and specifically targeted the gene encoding OCT4 (POU5F1) in diploid human zygotes and found that blastocyst development was compromised. Transcriptomics analysis revealed that, in POU5F1-null cells, gene expression was downregulated not only for extra-embryonic trophectoderm genes, such as CDX2, but also for regulators of the pluripotent epiblast, including NANOG. By contrast, Pou5f1-null mouse embryos maintained the expression of orthologous genes, and blastocyst development was established, but maintenance was compromised. We conclude that CRISPR-Cas9-mediated genome editing is a powerful method for investigating gene function in the context of human development.

Conversion events in gene clusters

PubMed Central

2011-01-01

Background Gene clusters containing multiple similar genomic regions in close proximity are of great interest for biomedical studies because of their associations with inherited diseases. However, such regions are difficult to analyze due to their structural complexity and their complicated evolutionary histories, reflecting a variety of large-scale mutational events. In particular, conversion events can mislead inferences about the relationships among these regions, as traced by traditional methods such as construction of phylogenetic trees or multi-species alignments. Results To correct the distorted information generated by such methods, we have developed an automated pipeline called CHAP (Cluster History Analysis Package) for detecting conversion events. We used this pipeline to analyze the conversion events that affected two well-studied gene clusters (α-globin and β-globin) and three gene clusters for which comparative sequence data were generated from seven primate species: CCL (chemokine ligand), IFN (interferon), and CYP2abf (part of cytochrome P450 family 2). CHAP is freely available at http://www.bx.psu.edu/miller_lab. Conclusions These studies reveal the value of characterizing conversion events in the context of studying gene clusters in complex genomes. PMID:21798034

Sequential social experiences interact to modulate aggression but not brain gene expression in the honey bee (Apis mellifera).

PubMed

Rittschof, Clare C

2017-01-01

In highly structured societies, individuals behave flexibly and cooperatively in order to achieve a particular group-level outcome. However, even in social species, environmental inputs can have long lasting effects on individual behavior, and variable experiences can even result in consistent individual differences and constrained behavioral flexibility. Despite the fact that such constraints on behavior could have implications for behavioral optimization at the social group level, few studies have explored how social experiences accumulate over time, and the mechanistic basis of these effects. In the current study, I evaluate how sequential social experiences affect individual and group level aggressive phenotypes, and individual brain gene expression, in the highly social honey bee ( Apis mellifera ). To do this, I combine a whole colony chronic predator disturbance treatment with a lab-based manipulation of social group composition. Compared to the undisturbed control, chronically disturbed individuals show lower aggression levels overall, but also enhanced behavioral flexibility in the second, lab-based social context. Disturbed bees display aggression levels that decline with increasing numbers of more aggressive, undisturbed group members. However, group level aggressive phenotypes are similar regardless of the behavioral tendencies of the individuals that make up the group, suggesting a combination of underlying behavioral tendency and negative social feedback influences the aggressive behaviors displayed, particularly in the case of disturbed individuals. An analysis of brain gene expression showed that aggression related biomarker genes reflect an individual's disturbance history, but not subsequent social group experience or behavioral outcomes. In highly social animals with collective behavioral phenotypes, social context may mask underlying variation in individual behavioral tendencies. Moreover, gene expression patterns may reflect behavioral tendency, while behavioral outcomes are further regulated by social cues perceived in real-time.

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

Vamathevan, Jessica J., E-mail: jessica.j.vamathevan@gsk.com; Hall, Matthew D.; Hasan, Samiul

Improving drug attrition remains a challenge in pharmaceutical discovery and development. A major cause of early attrition is the demonstration of safety signals which can negate any therapeutic index previously established. Safety attrition needs to be put in context of clinical translation (i.e. human relevance) and is negatively impacted by differences between animal models and human. In order to minimize such an impact, an earlier assessment of pharmacological target homology across animal model species will enhance understanding of the context of animal safety signals and aid species selection during later regulatory toxicology studies. Here we sequenced the genomes of themore » Sus scrofa Göttingen minipig and the Canis familiaris beagle, two widely used animal species in regulatory safety studies. Comparative analyses of these new genomes with other key model organisms, namely mouse, rat, cynomolgus macaque, rhesus macaque, two related breeds (S. scrofa Duroc and C. familiaris boxer) and human reveal considerable variation in gene content. Key genes in toxicology and metabolism studies, such as the UGT2 family, CYP2D6, and SLCO1A2, displayed unique duplication patterns. Comparisons of 317 known human drug targets revealed surprising variation such as species-specific positive selection, duplication and higher occurrences of pseudogenized targets in beagle (41 genes) relative to minipig (19 genes). These data will facilitate the more effective use of animals in biomedical research. - Highlights: • Genomes of the minipig and beagle dog, two species used in pharmaceutical studies. • First systematic comparative genome analysis of human and six experimental animals. • Key drug toxicology genes display unique duplication patterns across species. • Comparison of 317 drug targets show species-specific evolutionary patterns.« less

Reversal of the hair loss phenotype by modulating the estradiol-ANGPT2 axis in the mouse model of female pattern hair loss.

PubMed

Endo, Yujiro; Obayashi, Yuko; Ono, Tomoji; Serizawa, Tetsushi; Murakoshi, Michiaki; Ohyama, Manabu

2018-07-01

Despite high demand for a remedy, the treatment options for female pattern hair loss (FPHL) are limited. FPHL is frequent in postmenopausal women. In ovariectomized (OVX) mice, which lack β-estradiol (E2) and manifest hair loss mimicking FPHL, E2 supplementation has been shown to increase hair density. However, the mechanism by which E2 exhibits its biological activity remains elusive. To identify the downstream targets of E2 in the context of FPHL pathophysiology and discover a potential therapeutic agent for the E2-dependent subtype of FPHL. Human dermal papilla cells (hDPCs) were cultured with E2, and a microarray analysis was performed to identify the genes regulated by E2. Using OVX mice, the identified gene product was intradermally administered and then quantitative image analysis of hair density was conducted. In silico analysis to link E2 and the identified gene was performed. Global gene expression and bioinformatics analyses revealed that the genes associated with the angiopoietin-2 (ANGPT2) pathway were upregulated by E2 in hDPCs. ANGPT2 was significantly downregulated in OVX mice than in sham-operated mice (P < 0.01). Importantly, hair density was higher in OVX mice treated with ANGPT2 than in control mice (P < 0.05). In silico analysis showed DNA sequences with high possibility of estrogen receptor binding in the promoter region of ANGPT2. The E2-ANGPT2 axis is present in hair follicles. ANGPT2 provides a strategy for the management of E2-dependent and postmenopausal subsets of FPHL. Copyright © 2018 Japanese Society for Investigative Dermatology. Published by Elsevier B.V. All rights reserved.

atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

iCanPlot: Visual Exploration of High-Throughput Omics Data Using Interactive Canvas Plotting

PubMed Central

Sinha, Amit U.; Armstrong, Scott A.

2012-01-01

Increasing use of high throughput genomic scale assays requires effective visualization and analysis techniques to facilitate data interpretation. Moreover, existing tools often require programming skills, which discourages bench scientists from examining their own data. We have created iCanPlot, a compelling platform for visual data exploration based on the latest technologies. Using the recently adopted HTML5 Canvas element, we have developed a highly interactive tool to visualize tabular data and identify interesting patterns in an intuitive fashion without the need of any specialized computing skills. A module for geneset overlap analysis has been implemented on the Google App Engine platform: when the user selects a region of interest in the plot, the genes in the region are analyzed on the fly. The visualization and analysis are amalgamated for a seamless experience. Further, users can easily upload their data for analysis—which also makes it simple to share the analysis with collaborators. We illustrate the power of iCanPlot by showing an example of how it can be used to interpret histone modifications in the context of gene expression. PMID:22393367

Exogenous Restoration of TUSC2 Expression Induces Responsiveness to Erlotinib in Wildtype Epidermal Growth Factor Receptor (EGFR) Lung Cancer Cells through Context Specific Pathways Resulting in Enhanced Therapeutic Efficacy

PubMed Central

Lara-Guerra, Humberto; Kawashima, Hiroyuki; Sakai, Ryo; Jayachandran, Gitanjali; Majidi, Mourad; Mehran, Reza; Wang, Jing; Bekele, B. Nebiyou; Baladandayuthapani, Veerabhadran; Yoo, Suk-Young; Wang, Ying; Ying, Jun; Meng, Feng; Ji, Lin; Roth, Jack A.

2015-01-01

Expression of the tumor suppressor gene TUSC2 is reduced or absent in most lung cancers and is associated with worse overall survival. In this study, we restored TUSC2 gene expression in several wild type EGFR non-small cell lung cancer (NSCLC) cell lines resistant to the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor erlotinib and analyzed their sensitivity to erlotinib in vitro and in vivo. A significant inhibition of cell growth and colony formation was observed with TUSC2 transient and stable expression. TUSC2-erlotinib cooperativity in vitro could be reproduced in vivo in subcutaneous tumor growth and lung metastasis formation lung cancer xenograft mouse models. Combination treatment with intravenous TUSC2 nanovesicles and erlotinib synergistically inhibited tumor growth and metastasis, and increased apoptotic activity. High-throughput qRT-PCR array analysis enabling multi-parallel expression profile analysis of eighty six receptor and non-receptor tyrosine kinase genes revealed a significant decrease of FGFR2 expression level, suggesting a potential role of FGFR2 in TUSC2-enhanced sensitivity to erlotinib. Western blots showed inhibition of FGFR2 by TUSC2 transient transfection, and marked increase of PARP, an apoptotic marker, cleavage level after TUSC2-erlotinb combined treatment. Suppression of FGFR2 by AZD4547 or gene knockdown enhanced sensitivity to erlotinib in some but not all tested cell lines. TUSC2 inhibits mTOR activation and the latter cell lines were responsive to the mTOR inhibitor rapamycin combined with erlotinib. These results suggest that TUSC2 restoration in wild type EGFR NSCLC may overcome erlotinib resistance, and identify FGFR2 and mTOR as critical regulators of this activity in varying cellular contexts. The therapeutic activity of TUSC2 could extend the use of erlotinib to lung cancer patients with wildtype EGFR. PMID:26053020

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures.

PubMed

Mazandu, Gaston K; Mulder, Nicola J

2013-09-25

The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.

RNA sample preparation applied to gene expression profiling for the horse biological passport.

PubMed

Bailly-Chouriberry, Ludovic; Baudoin, Florent; Cormant, Florence; Glavieux, Yohan; Loup, Benoit; Garcia, Patrice; Popot, Marie-Agnès; Bonnaire, Yves

2017-09-01

The improvement of doping control is an ongoing race. Techniques to fight doping are usually based on the direct detection of drugs or their metabolites by analytical methods such as chromatography hyphenated to mass spectrometry after ad hoc sample preparation. Nowadays, omic methods constitute an attractive development and advances have been achieved particularly by application of molecular biology tools for detection of anabolic androgenic steroids (AAS), erythropoiesis-stimulating agent (ESA), or to control human growth hormone misuses. These interesting results across different animal species have suggested that modification of gene expression offers promising new methods of improving the window of detection of banned substances by targeting their effects on blood cell gene expression. In this context, the present study describes the possibility of using a modified version of the dedicated Human IVD (in vitro Diagnostics) PAXgene® Blood RNA Kit for horse gene expression analysis in blood collected on PAXgene® tubes applied to the horse biological passport. The commercial kit was only approved for human blood samples and has required an optimization of specific technical requirements for equine blood samples. Improvements and recommendations were achieved for sample collection, storage and RNA extraction procedure. Following these developments, RNA yield and quality were demonstrated to be suitable for downstream gene expression analysis by qPCR techniques. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

EARLY BUD-BREAK 1 (EBB1) is a regulator of release from seasonal dormancy in poplar trees

PubMed Central

Yordanov, Yordan S.; Ma, Cathleen; Strauss, Steven H.; Busov, Victor B.

2014-01-01

Trees from temperate latitudes transition between growth and dormancy to survive dehydration and freezing stress during winter months. We used activation tagging to isolate a dominant mutation affecting release from dormancy and identified the corresponding gene EARLY BUD-BREAK 1 (EBB1). We demonstrate through positioning of the tag, expression analysis, and retransformation experiments that EBB1 encodes a putative APETALA2/Ethylene responsive factor transcription factor. Transgenic up-regulation of the gene caused early bud-flush, whereas down-regulation delayed bud-break. Native EBB1 expression was highest in actively growing apices, undetectable during the dormancy period, but rapidly increased before bud-break. The EBB1 transcript was localized in the L1/L2 layers of the shoot meristem and leaf primordia. EBB1-overexpressing transgenic plants displayed enlarged shoot meristems, open and poorly differentiated buds, and a higher rate of cell division in the apex. Transcriptome analyses of the EBB1 transgenics identified 971 differentially expressed genes whose expression correlated with the EBB1 expression changes in the transgenic plants. Promoter analysis among the differentially expressed genes for the presence of a canonical EBB1-binding site identified 65 putative target genes, indicative of a broad regulatory context of EBB1 function. Our results suggest that EBB1 has a major and integrative role in reactivation of meristem activity after winter dormancy. PMID:24951507

[The evolution of heat shock genes and expression patterns of heat shock proteins in the species from temperature contrasting habitats].

PubMed

Garbuz, D G; Evgen’ev, M B

2017-01-01

Heat shock genes are the most evolutionarily ancient among the systems responsible for adaptation of organisms to a harsh environment. The encoded proteins (heat shock proteins, Hsps) represent the most important factors of adaptation to adverse environmental conditions. They serve as molecular chaperones, providing protein folding and preventing aggregation of damaged cellular proteins. Structural analysis of the heat shock genes in individuals from both phylogenetically close and very distant taxa made it possible to reveal the basic trends of the heat shock gene organization in the context of adaptation to extreme conditions. Using different model objects and nonmodel species from natural populations, it was demonstrated that modulation of the Hsps expression during adaptation to different environmental conditions could be achieved by changing the number and structural organization of heat shock genes in the genome, as well as the structure of their promoters. It was demonstrated that thermotolerant species were usually characterized by elevated levels of Hsps under normal temperature or by the increase in the synthesis of these proteins in response to heat shock. Analysis of the heat shock genes in phylogenetically distant organisms is of great interest because, on one hand, it contributes to the understanding of the molecular mechanisms of evolution of adaptogenes and, on the other hand, sheds the light on the role of different Hsps families in the development of thermotolerance and the resistance to other stress factors.

Identification and molecular characterization of MYB Transcription Factor Superfamily in C4 model plant foxtail millet (Setaria italica L.).

PubMed

Muthamilarasan, Mehanathan; Khandelwal, Rohit; Yadav, Chandra Bhan; Bonthala, Venkata Suresh; Khan, Yusuf; Prasad, Manoj

2014-01-01

MYB proteins represent one of the largest transcription factor families in plants, playing important roles in diverse developmental and stress-responsive processes. Considering its significance, several genome-wide analyses have been conducted in almost all land plants except foxtail millet. Foxtail millet (Setaria italica L.) is a model crop for investigating systems biology of millets and bioenergy grasses. Further, the crop is also known for its potential abiotic stress-tolerance. In this context, a comprehensive genome-wide survey was conducted and 209 MYB protein-encoding genes were identified in foxtail millet. All 209 S. italica MYB (SiMYB) genes were physically mapped onto nine chromosomes of foxtail millet. Gene duplication study showed that segmental- and tandem-duplication have occurred in genome resulting in expansion of this gene family. The protein domain investigation classified SiMYB proteins into three classes according to number of MYB repeats present. The phylogenetic analysis categorized SiMYBs into ten groups (I-X). SiMYB-based comparative mapping revealed a maximum orthology between foxtail millet and sorghum, followed by maize, rice and Brachypodium. Heat map analysis showed tissue-specific expression pattern of predominant SiMYB genes. Expression profiling of candidate MYB genes against abiotic stresses and hormone treatments using qRT-PCR revealed specific and/or overlapping expression patterns of SiMYBs. Taken together, the present study provides a foundation for evolutionary and functional characterization of MYB TFs in foxtail millet to dissect their functions in response to environmental stimuli.

Editor's Highlight: Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment.

PubMed

Dean, Jeffry L; Zhao, Q Jay; Lambert, Jason C; Hawkins, Belinda S; Thomas, Russell S; Wesselkamper, Scott C

2017-05-01

The rate of new chemical development in commerce combined with a paucity of toxicity data for legacy chemicals presents a unique challenge for human health risk assessment. There is a clear need to develop new technologies and incorporate novel data streams to more efficiently inform derivation of toxicity values. One avenue of exploitation lies in the field of transcriptomics and the application of gene expression analysis to characterize biological responses to chemical exposures. In this context, gene set enrichment analysis (GSEA) was employed to evaluate tissue-specific, dose-response gene expression data generated following exposure to multiple chemicals for various durations. Patterns of transcriptional enrichment were evident across time and with increasing dose, and coordinated enrichment plausibly linked to the etiology of the biological responses was observed. GSEA was able to capture both transient and sustained transcriptional enrichment events facilitating differentiation between adaptive versus longer term molecular responses. When combined with benchmark dose (BMD) modeling of gene expression data from key drivers of biological enrichment, GSEA facilitated characterization of dose ranges required for enrichment of biologically relevant molecular signaling pathways, and promoted comparison of the activation dose ranges required for individual pathways. Median transcriptional BMD values were calculated for the most sensitive enriched pathway as well as the overall median BMD value for key gene members of significantly enriched pathways, and both were observed to be good estimates of the most sensitive apical endpoint BMD value. Together, these efforts support the application of GSEA to qualitative and quantitative human health risk assessment. Published by Oxford University Press on behalf of the Society of Toxicology 2017. This work is written by US Government employees and is in the public domain in the US.

Patenting human genes: Chinese academic articles' portrayal of gene patents.

PubMed

Du, Li

2018-04-24

The patenting of human genes has been the subject of debate for decades. While China has gradually come to play an important role in the global genomics-based testing and treatment market, little is known about Chinese scholars' perspectives on patent protection for human genes. A content analysis of academic literature was conducted to identify Chinese scholars' concerns regarding gene patents, including benefits and risks of patenting human genes, attitudes that researchers hold towards gene patenting, and any legal and policy recommendations offered for the gene patent regime in China. 57.2% of articles were written by law professors, but scholars from health sciences, liberal arts, and ethics also participated in discussions on gene patent issues. While discussions of benefits and risks were relatively balanced in the articles, 63.5% of the articles favored gene patenting in general and, of the articles (n = 41) that explored gene patents in the Chinese context, 90.2% supported patent protections for human genes in China. The patentability of human genes was discussed in 33 articles, and 75.8% of these articles reached the conclusion that human genes are patentable. Chinese scholars view the patent regime as an important legal tool to protect the interests of inventors and inventions as well as the genetic resources of China. As such, many scholars support a gene patent system in China. These attitudes towards gene patents remain unchanged following the court ruling in the Myriad case in 2013, but arguments have been raised about the scope of gene patents, in particular that the increasing numbers of gene patents may negatively impact public health in China.

The Genome of Naegleria gruberi Illuminates Early Eukaryotic Versatility

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

Fritz-Laylin, Lillian K.; Prochnik, Simon E.; Ginger, Michael L.

2010-03-01

Genome sequences of diverse free-living protists are essential for understanding eukaryotic evolution and molecular and cell biology. The free-living amoeboflagellate Naegleria gruberi belongs to a varied and ubiquitous protist clade (Heterolobosea) that diverged from other eukaryotic lineages over a billion years ago. Analysis of the 15,727 protein-coding genes encoded by Naegleria's 41 Mb nuclear genome indicates a capacity for both aerobic respiration and anaerobic metabolism with concomitant hydrogen production, with fundamental implications for the evolution of organelle metabolism. The Naegleria genome facilitates substantially broader phylogenomic comparisons of free-living eukaryotes than previously possible, allowing us to identify thousands of genes likelymore » present in the pan-eukaryotic ancestor, with 40% likely eukaryotic inventions. Moreover, we construct a comprehensive catalog of amoeboid-motility genes. The Naegleria genome, analyzed in the context of other protists, reveals a remarkably complex ancestral eukaryote with a rich repertoire of cytoskeletal, sexual, signaling, and metabolic modules.« less

Roles for Msx and Dlx homeoproteins in vertebrate development.

PubMed

Bendall, A J; Abate-Shen, C

2000-04-18

This review provides a comparative analysis of the expression patterns, functions, and biochemical properties of Msx and Dlx homeobox genes. These comprise multi-gene families that are closely related with respect to sequence features as well as expression patterns during vertebrate development. Thus, members of the Msx and Dlx families are expressed in overlapping, but distinct, patterns and display complementary or antagonistic functions, depending upon the context. A common theme shared among Msx and Dlx genes is that they are required during early, middle, and late phases of development where their differential expression mediates patterning, morphogenesis, and histogenesis of tissues in which they are expressed. With respect to their biochemical properties, Msx proteins function as transcriptional repressors, while Dlx proteins are transcriptional activators. Moreover, their ability to oppose each other's transcriptional actions implies a mechanism underlying their complementary or antagonistic functions during development.

Insight into Genotype-Phenotype Associations through eQTL Mapping in Multiple Cell Types in Health and Immune-Mediated Disease

PubMed Central

Peters, James E.; Lyons, Paul A.; Lee, James C.; Richard, Arianne C.; Fortune, Mary D.; Newcombe, Paul J.; Richardson, Sylvia; Smith, Kenneth G. C.

2016-01-01

Genome-wide association studies (GWAS) have transformed our understanding of the genetics of complex traits such as autoimmune diseases, but how risk variants contribute to pathogenesis remains largely unknown. Identifying genetic variants that affect gene expression (expression quantitative trait loci, or eQTLs) is crucial to addressing this. eQTLs vary between tissues and following in vitro cellular activation, but have not been examined in the context of human inflammatory diseases. We performed eQTL mapping in five primary immune cell types from patients with active inflammatory bowel disease (n = 91), anti-neutrophil cytoplasmic antibody-associated vasculitis (n = 46) and healthy controls (n = 43), revealing eQTLs present only in the context of active inflammatory disease. Moreover, we show that following treatment a proportion of these eQTLs disappear. Through joint analysis of expression data from multiple cell types, we reveal that previous estimates of eQTL immune cell-type specificity are likely to have been exaggerated. Finally, by analysing gene expression data from multiple cell types, we find eQTLs not previously identified by database mining at 34 inflammatory bowel disease-associated loci. In summary, this parallel eQTL analysis in multiple leucocyte subsets from patients with active disease provides new insights into the genetic basis of immune-mediated diseases. PMID:27015630

Differential DNA methylation and transcription profiles in date palm roots exposed to salinity

PubMed Central

Al-Harrasi, Ibtisam; Al-Yahyai, Rashid

2018-01-01

As a salt-adaptive plant, the date palm (Phoenix dactylifera L.) requires a suitable mechanism to adapt to the stress of saline soils. There is growing evidence that DNA methylation plays an important role in regulating gene expression in response to abiotic stresses, including salinity. Thus, the present study sought to examine the differential methylation status that occurs in the date palm genome when plants are exposed to salinity, and to identify salinity responsive genes that are regulated by DNA methylation. To achieve these, whole-genome bisulfite sequencing (WGBS) was employed and mRNA was sequenced from salinity-treated and untreated roots. The WGBS analysis included 324,987,795 and 317,056,091 total reads of the control and the salinity-treated samples, respectively. The analysis covered about 81% of the total genomic DNA with about 40% of mapping efficiency of the sequenced reads and an average read depth of 17-fold coverage per DNA strand, and with a bisulfite conversion rate of around 99%. The level of methylation within the differentially methylated regions (DMRs) was significantly (p < 0.05, FDR ≤ 0.05) increased in response to salinity specifically at the mCHG and mCHH sequence contexts. Consistently, the mass spectrometry and the enzyme-linked immunosorbent assay (ELISA) showed that there was a significant (p < 0.05) increase in the global DNA methylation in response to salinity. mRNA sequencing revealed the presence of 6,405 differentially regulated genes with a significant value (p < 0.001, FDR ≤ 0.05) in response to salinity. Integration of high-resolution methylome and transcriptome analyses revealed a negative correlation between mCG methylation located within the promoters and the gene expression, while a positive correlation was noticed between mCHG/mCHH methylation rations and gene expression specifically when plants grew under control conditions. Therefore, the methylome and transcriptome relationships vary based on the methylated sequence context, the methylated region within the gene, the protein-coding ability of the gene, and the salinity treatment. These results provide insights into interplay among DNA methylation and gene expression, and highlight the effect of salinity on the nature of this relationship, which may involve other genetic and epigenetic players under salt stress conditions. The results obtained from this project provide the first draft map of the differential methylome and transcriptome of date palm when exposed to an abiotic stress. PMID:29352281

Differential DNA methylation and transcription profiles in date palm roots exposed to salinity.

PubMed

Al-Harrasi, Ibtisam; Al-Yahyai, Rashid; Yaish, Mahmoud W

2018-01-01

As a salt-adaptive plant, the date palm (Phoenix dactylifera L.) requires a suitable mechanism to adapt to the stress of saline soils. There is growing evidence that DNA methylation plays an important role in regulating gene expression in response to abiotic stresses, including salinity. Thus, the present study sought to examine the differential methylation status that occurs in the date palm genome when plants are exposed to salinity, and to identify salinity responsive genes that are regulated by DNA methylation. To achieve these, whole-genome bisulfite sequencing (WGBS) was employed and mRNA was sequenced from salinity-treated and untreated roots. The WGBS analysis included 324,987,795 and 317,056,091 total reads of the control and the salinity-treated samples, respectively. The analysis covered about 81% of the total genomic DNA with about 40% of mapping efficiency of the sequenced reads and an average read depth of 17-fold coverage per DNA strand, and with a bisulfite conversion rate of around 99%. The level of methylation within the differentially methylated regions (DMRs) was significantly (p < 0.05, FDR ≤ 0.05) increased in response to salinity specifically at the mCHG and mCHH sequence contexts. Consistently, the mass spectrometry and the enzyme-linked immunosorbent assay (ELISA) showed that there was a significant (p < 0.05) increase in the global DNA methylation in response to salinity. mRNA sequencing revealed the presence of 6,405 differentially regulated genes with a significant value (p < 0.001, FDR ≤ 0.05) in response to salinity. Integration of high-resolution methylome and transcriptome analyses revealed a negative correlation between mCG methylation located within the promoters and the gene expression, while a positive correlation was noticed between mCHG/mCHH methylation rations and gene expression specifically when plants grew under control conditions. Therefore, the methylome and transcriptome relationships vary based on the methylated sequence context, the methylated region within the gene, the protein-coding ability of the gene, and the salinity treatment. These results provide insights into interplay among DNA methylation and gene expression, and highlight the effect of salinity on the nature of this relationship, which may involve other genetic and epigenetic players under salt stress conditions. The results obtained from this project provide the first draft map of the differential methylome and transcriptome of date palm when exposed to an abiotic stress.

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

PubMed

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

2017-12-01

Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric phenotypes and reduces the risk of false-positive findings. We apply this method focusing on the role of perceived parental support, psychological control, and harsh punishment in depressive symptoms in adolescence. Analyses were conducted on 982 adolescents of Caucasian origin (M age (SD) = 13.78 (.94) years) genotyped for 4,947 SNPs in 263 genes, selected based on a literature survey. The Leuven Adolescent Perceived Parenting Scale (LAPPS) and the Parental Behavior Scale (PBS) were used to assess perceived parental psychological control, harsh punishment, and support. The Center for Epidemiologic Studies Depression Scale (CES-D) was the outcome. We used gene-based testing taking into account linkage disequilibrium to identify genes containing SNPs exhibiting an interaction with environmental factors yielding a p-value per single gene. Significant results at the corrected p-value of p < 1.90 × 10 -4 were examined in an independent replication sample of Dutch adolescents (N = 1354). Two genes showed evidence for interaction with perceived support: GABRR1 (p = 4.62 × 10 -5 ) and GABRR2 (p = 9.05 × 10 -6 ). No genes interacted significantly with psychological control or harsh punishment. Gene-based analysis was unable to confirm the interaction of GABRR1 or GABRR2 with support in the replication sample. However, for GABRR2, but not GABRR1, the correlation of the estimates between the two datasets was significant (r (46) = .32; p = .027) and a gene-based analysis of the combined datasets supported GABRR2 × support interaction (p = 1.63 × 10 -4 ). We present a gene-based method for gene-environment interactions in a polygenic context and show that genes interact differently with particular aspects of parenting. This accentuates the importance of polygenic approaches and the need to accurately assess environmental exposure in G × E. © 2017 Association for Child and Adolescent Mental Health.

Alteration of peripheral blood monocyte gene expression in humans following diesel exhaust inhalation

PubMed Central

Pettit, Ashley P.; Brooks, Andrew; Laumbach, Robert; Fiedler, Nancy; Wang, Qi; Strickland, Pamela Ohman; Madura, Kiran; Zhang, Junfeng; Kipen, Howard M.

2013-01-01

Context Epidemiologic associations between acutely increased cardiorespiratory morbidity and mortality and particulate air pollution are well established, but the effects of acute pollution exposure on human gene expression changes are not well understood. Objective In order to identify potential mechanisms underlying epidemiologic associations between air pollution and morbidity, we explored changes in gene expression in humans following inhalation of fresh diesel exhaust (DE), a model for particulate air pollution. Materials and methods Fourteen ethnically homogeneous (white males), young, healthy subjects underwent 60-min inhalation exposures on 2 separate days with clean filtered air (CA) or freshly generated and diluted DE at a concentration of 300 μg/m3 PM2.5. Prior to and 24 h following each session, whole blood was sampled and fractionated for peripheral blood mononuclear cell (PBMC) isolation, RNA extraction, and generation of cDNA, followed by hybridization with Agilent Whole Human Genome (4X44K) arrays. Results Oxidative stress and the ubiquitin proteasome pathway, as well as the coagulation system, were among hypothesized pathways identified by analysis of differentially expressed genes. Nine genes from these pathways were validated using real-time polymerase chain reaction (PCR) to compare fold change in expression between DE exposed and CA days. Quantitative gene fold changes generated by real-time PCR were directionally consistent with the fold changes from the microarray analysis. Discussion and conclusion Changes in gene expression connected with key oxidative stress, protein degradation, and coagulation pathways are likely to underlie observed physiologic and clinical outcomes and suggest specific avenues and sensitive time points for further physiologic exploration. PMID:22369193

Analysis of gene expression in a developmental context emphasizes distinct biological leitmotifs in human cancers

PubMed Central

Naxerova, Kamila; Bult, Carol J; Peaston, Anne; Fancher, Karen; Knowles, Barbara B; Kasif, Simon; Kohane, Isaac S

2008-01-01

Background In recent years, the molecular underpinnings of the long-observed resemblance between neoplastic and immature tissue have begun to emerge. Genome-wide transcriptional profiling has revealed similar gene expression signatures in several tumor types and early developmental stages of their tissue of origin. However, it remains unclear whether such a relationship is a universal feature of malignancy, whether heterogeneities exist in the developmental component of different tumor types and to which degree the resemblance between cancer and development is a tissue-specific phenomenon. Results We defined a developmental landscape by summarizing the main features of ten developmental time courses and projected gene expression from a variety of human tumor types onto this landscape. This comparison demonstrates a clear imprint of developmental gene expression in a wide range of tumors and with respect to different, even non-cognate developmental backgrounds. Our analysis reveals three classes of cancers with developmentally distinct transcriptional patterns. We characterize the biological processes dominating these classes and validate the class distinction with respect to a new time series of murine embryonic lung development. Finally, we identify a set of genes that are upregulated in most cancers and we show that this signature is active in early development. Conclusion This systematic and quantitative overview of the relationship between the neoplastic and developmental transcriptome spanning dozens of tissues provides a reliable outline of global trends in cancer gene expression, reveals potentially clinically relevant differences in the gene expression of different cancer types and represents a reference framework for interpretation of smaller-scale functional studies. PMID:18611264

Analysis of functional importance of binding sites in the Drosophila gap gene network model.

PubMed

Kozlov, Konstantin; Gursky, Vitaly V; Kulakovskiy, Ivan V; Dymova, Arina; Samsonova, Maria

2015-01-01

The statistical thermodynamics based approach provides a promising framework for construction of the genotype-phenotype map in many biological systems. Among important aspects of a good model connecting the DNA sequence information with that of a molecular phenotype (gene expression) is the selection of regulatory interactions and relevant transcription factor bindings sites. As the model may predict different levels of the functional importance of specific binding sites in different genomic and regulatory contexts, it is essential to formulate and study such models under different modeling assumptions. We elaborate a two-layer model for the Drosophila gap gene network and include in the model a combined set of transcription factor binding sites and concentration dependent regulatory interaction between gap genes hunchback and Kruppel. We show that the new variants of the model are more consistent in terms of gene expression predictions for various genetic constructs in comparison to previous work. We quantify the functional importance of binding sites by calculating their impact on gene expression in the model and calculate how these impacts correlate across all sites under different modeling assumptions. The assumption about the dual interaction between hb and Kr leads to the most consistent modeling results, but, on the other hand, may obscure existence of indirect interactions between binding sites in regulatory regions of distinct genes. The analysis confirms the previously formulated regulation concept of many weak binding sites working in concert. The model predicts a more or less uniform distribution of functionally important binding sites over the sets of experimentally characterized regulatory modules and other open chromatin domains.

Extraordinary diversity of visual opsin genes in dragonflies

PubMed Central

Futahashi, Ryo; Kawahara-Miki, Ryouka; Kinoshita, Michiyo; Yoshitake, Kazutoshi; Yajima, Shunsuke; Arikawa, Kentaro; Fukatsu, Takema

2015-01-01

Dragonflies are colorful and large-eyed animals strongly dependent on color vision. Here we report an extraordinary large number of opsin genes in dragonflies and their characteristic spatiotemporal expression patterns. Exhaustive transcriptomic and genomic surveys of three dragonflies of the family Libellulidae consistently identified 20 opsin genes, consisting of 4 nonvisual opsin genes and 16 visual opsin genes of 1 UV, 5 short-wavelength (SW), and 10 long-wavelength (LW) type. Comprehensive transcriptomic survey of the other dragonflies representing an additional 10 families also identified as many as 15–33 opsin genes. Molecular phylogenetic analysis revealed dynamic multiplications and losses of the opsin genes in the course of evolution. In contrast to many SW and LW genes expressed in adults, only one SW gene and several LW genes were expressed in larvae, reflecting less visual dependence and LW-skewed light conditions for their lifestyle under water. In this context, notably, the sand-burrowing or pit-dwelling species tended to lack SW gene expression in larvae. In adult visual organs: (i) many SW genes and a few LW genes were expressed in the dorsal region of compound eyes, presumably for processing SW-skewed light from the sky; (ii) a few SW genes and many LW genes were expressed in the ventral region of compound eyes, probably for perceiving terrestrial objects; and (iii) expression of a specific LW gene was associated with ocelli. Our findings suggest that the stage- and region-specific expressions of the diverse opsin genes underlie the behavior, ecology, and adaptation of dragonflies. PMID:25713365

Genetic rhetoric: Science, authority, and genes

NASA Astrophysics Data System (ADS)

Shea, Elizabeth Parthenia

This dissertation is an analysis of how the cultural authority of genetics works through language. An analysis of the rhetorical construction of knowledge and authority in cultural contexts, the study is intended to contribute to a larger discussion aimed at keeping the intersections of science and culture within the realm of rhetoric, that is within the realm of communication and dialogue. Of special concern is the influence of genetic rhetoric on the cultural momentum of biological determinism to explain away social organization, class inequalities, racial differences, gender differences, and stigmatized behaviors by rooting them in the construct of the biological individual. This study separates questions of legitimacy from questions of authority and focuses on the way that authority of genetics works through language. With authority defined as the function of resisting challenges to legitimacy and/or power, the study consists of three parts. First, a historical analysis of the terms science, genetics, and gene, shows how these words came to refer not only to areas and objects of study but also to sources of epistemological legitimacy outside culture and language. The relationships between these words and their referents are examined in socio-historical context to illustrate how the function of signaling authority was inscribed in the literal definition of these terms. Second, introductory chapters of contemporary Genetics textbooks are examined. In these texts the foundations of legitimacy associated with genetics and science are maintained as the authors articulate idealized views of science and genetics in relation to society. Finally, articles in the popular press reporting on and discussing recent research correlating genetics and homosexuality are examined. The popular press reports of "gay gene" research serve as textual examples of figurative representations of genetics concepts shaping discourse about social issues. I argue that the cultural authority of genetics, as well as the power of science to shape culture, is not necessarily a matter of the persuasiveness of material truths but rather a mobilization of rhetorical figures that are linked to but not literally representing ideas of material truth.

Evolution of context dependent regulation by expansion of feast/famine regulatory proteins

DOE PAGES

Plaisier, Christopher L.; Lo, Fang -Yin; Ashworth, Justin; ...

2014-11-14

Expansion of transcription factors is believed to have played a crucial role in evolution of all organisms by enabling them to deal with dynamic environments and colonize new environments. We investigated how the expansion of the Feast/Famine Regulatory Protein (FFRP) or Lrp-like proteins into an eight-member family in Halobacterium salinarum NRC-1 has aided in niche-adaptation of this archaeon to a complex and dynamically changing hypersaline environment. We mapped genome-wide binding locations for all eight FFRPs, investigated their preference for binding different effector molecules, and identified the contexts in which they act by analyzing transcriptional responses across 35 growth conditions thatmore » mimic different environmental and nutritional conditions this organism is likely to encounter in the wild. Integrative analysis of these data constructed an FFRP regulatory network with conditionally active states that reveal how interrelated variations in DNA-binding domains, effector-molecule preferences, and binding sites in target gene promoters have tuned the functions of each FFRP to the environments in which they act. We demonstrate how conditional regulation of similar genes by two FFRPs, AsnC (an activator) and VNG1237C (a repressor), have striking environment-specific fitness consequences for oxidative stress management and growth, respectively. This study provides a systems perspective into the evolutionary process by which gene duplication within a transcription factor family contributes to environment-specific adaptation of an organism.« less

The Urinary Bladder Transcriptome and Proteome Defined by Transcriptomics and Antibody-Based Profiling

PubMed Central

Habuka, Masato; Fagerberg, Linn; Hallström, Björn M.; Pontén, Fredrik; Yamamoto, Tadashi; Uhlen, Mathias

2015-01-01

To understand functions and diseases of urinary bladder, it is important to define its molecular constituents and their roles in urinary bladder biology. Here, we performed genome-wide deep RNA sequencing analysis of human urinary bladder samples and identified genes up-regulated in the urinary bladder by comparing the transcriptome data to those of all other major human tissue types. 90 protein-coding genes were elevated in the urinary bladder, either with enhanced expression uniquely in the urinary bladder or elevated expression together with at least one other tissue (group enriched). We further examined the localization of these proteins by immunohistochemistry and tissue microarrays and 20 of these 90 proteins were localized to the whole urothelium with a majority not yet described in the context of the urinary bladder. Four additional proteins were found specifically in the umbrella cells (Uroplakin 1a, 2, 3a, and 3b), and three in the intermediate/basal cells (KRT17, PCP4L1 and ATP1A4). 61 of the 90 elevated genes have not been previously described in the context of urinary bladder and the corresponding proteins are interesting targets for more in-depth studies. In summary, an integrated omics approach using transcriptomics and antibody-based profiling has been used to define a comprehensive list of proteins elevated in the urinary bladder. PMID:26694548

Evolution of context dependent regulation by expansion of feast/famine regulatory proteins.

PubMed

Plaisier, Christopher L; Lo, Fang-Yin; Ashworth, Justin; Brooks, Aaron N; Beer, Karlyn D; Kaur, Amardeep; Pan, Min; Reiss, David J; Facciotti, Marc T; Baliga, Nitin S

2014-11-14

Expansion of transcription factors is believed to have played a crucial role in evolution of all organisms by enabling them to deal with dynamic environments and colonize new environments. We investigated how the expansion of the Feast/Famine Regulatory Protein (FFRP) or Lrp-like proteins into an eight-member family in Halobacterium salinarum NRC-1 has aided in niche-adaptation of this archaeon to a complex and dynamically changing hypersaline environment. We mapped genome-wide binding locations for all eight FFRPs, investigated their preference for binding different effector molecules, and identified the contexts in which they act by analyzing transcriptional responses across 35 growth conditions that mimic different environmental and nutritional conditions this organism is likely to encounter in the wild. Integrative analysis of these data constructed an FFRP regulatory network with conditionally active states that reveal how interrelated variations in DNA-binding domains, effector-molecule preferences, and binding sites in target gene promoters have tuned the functions of each FFRP to the environments in which they act. We demonstrate how conditional regulation of similar genes by two FFRPs, AsnC (an activator) and VNG1237C (a repressor), have striking environment-specific fitness consequences for oxidative stress management and growth, respectively. This study provides a systems perspective into the evolutionary process by which gene duplication within a transcription factor family contributes to environment-specific adaptation of an organism.

TLM-Tracker: software for cell segmentation, tracking and lineage analysis in time-lapse microscopy movies.

PubMed

Klein, Johannes; Leupold, Stefan; Biegler, Ilona; Biedendieck, Rebekka; Münch, Richard; Jahn, Dieter

2012-09-01

Time-lapse imaging in combination with fluorescence microscopy techniques enable the investigation of gene regulatory circuits and uncovered phenomena like culture heterogeneity. In this context, computational image processing for the analysis of single cell behaviour plays an increasing role in systems biology and mathematical modelling approaches. Consequently, we developed a software package with graphical user interface for the analysis of single bacterial cell behaviour. A new software called TLM-Tracker allows for the flexible and user-friendly interpretation for the segmentation, tracking and lineage analysis of microbial cells in time-lapse movies. The software package, including manual, tutorial video and examples, is available as Matlab code or executable binaries at http://www.tlmtracker.tu-bs.de.

iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data

PubMed Central

Saha, Ashis; Jeon, Minji; Tan, Aik Choon; Kang, Jaewoo

2015-01-01

Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes. Users can visualize the subnetworks to understand the biology of the difference. PMID:26147457

Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

PubMed

Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

2010-10-24

Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary context to determine how modeling results should be interpreted in biological systems.

Epigenetic variation, inheritance, and parent-of-origin effects of cytosine methylation in maize (Zea mays).

PubMed

Lauria, Massimiliano; Piccinini, Sara; Pirona, Raul; Lund, Gertrud; Viotti, Angelo; Motto, Mario

2014-03-01

Pure epigenetic variation, or epigenetic variation that is independent of genetic context, may provide a mechanism for phenotypic variation in the absence of DNA mutations. To estimate the extent of pure epigenetic variation within and across generations and to identify the DNA regions targeted, a group of eight plants derived from a highly inbred line of maize (Zea mays) was analyzed by the methylation-sensitive amplified polymorphism (MSAP) technique. We found that cytosine methylation (mC) differences among individuals accounted for up to 7.4% of CCGG sites investigated by MSAP. Of the differentially methylated fragments (DMFs) identified in the S0 generation, ∼12% were meiotically inherited for at least six generations. We show that meiotically heritable mC variation was consistently generated for an average of 0.5% CCGG sites per generation and that it largely occurred somatically. We provide evidence that mC variation can be established and inherited in a parent-of-origin manner, given that the paternal lineage is more prone to both forward and reverse mC changes. The molecular characterization of selected DMFs revealed that the variation was largely determined by CG methylation changes that map within gene regions. The expression analysis of genes overlapping with DMFs did not reveal an obvious correlation between mC variation and transcription, reinforcing the idea that the primary function of gene-body methylation is not to control gene expression. Because this study focuses on epigenetic variation in field-grown plants, the data presented herein pertain to spontaneous epigenetic changes of the maize genome in a natural context.

Epigenetic Variation, Inheritance, and Parent-of-Origin Effects of Cytosine Methylation in Maize (Zea mays)

PubMed Central

Lauria, Massimiliano; Piccinini, Sara; Pirona, Raul; Lund, Gertrud; Viotti, Angelo; Motto, Mario

2014-01-01

Pure epigenetic variation, or epigenetic variation that is independent of genetic context, may provide a mechanism for phenotypic variation in the absence of DNA mutations. To estimate the extent of pure epigenetic variation within and across generations and to identify the DNA regions targeted, a group of eight plants derived from a highly inbred line of maize (Zea mays) was analyzed by the methylation-sensitive amplified polymorphism (MSAP) technique. We found that cytosine methylation (mC) differences among individuals accounted for up to 7.4% of CCGG sites investigated by MSAP. Of the differentially methylated fragments (DMFs) identified in the S0 generation, ∼12% were meiotically inherited for at least six generations. We show that meiotically heritable mC variation was consistently generated for an average of 0.5% CCGG sites per generation and that it largely occurred somatically. We provide evidence that mC variation can be established and inherited in a parent-of-origin manner, given that the paternal lineage is more prone to both forward and reverse mC changes. The molecular characterization of selected DMFs revealed that the variation was largely determined by CG methylation changes that map within gene regions. The expression analysis of genes overlapping with DMFs did not reveal an obvious correlation between mC variation and transcription, reinforcing the idea that the primary function of gene-body methylation is not to control gene expression. Because this study focuses on epigenetic variation in field-grown plants, the data presented herein pertain to spontaneous epigenetic changes of the maize genome in a natural context. PMID:24374354

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

PubMed

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

2012-01-01

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

Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease.

PubMed

Ghosh, Sujoy; Vivar, Juan; Nelson, Christopher P; Willenborg, Christina; Segrè, Ayellet V; Mäkinen, Ville-Petteri; Nikpay, Majid; Erdmann, Jeannette; Blankenberg, Stefan; O'Donnell, Christopher; März, Winfried; Laaksonen, Reijo; Stewart, Alexandre F R; Epstein, Stephen E; Shah, Svati H; Granger, Christopher B; Hazen, Stanley L; Kathiresan, Sekar; Reilly, Muredach P; Yang, Xia; Quertermous, Thomas; Samani, Nilesh J; Schunkert, Heribert; Assimes, Themistocles L; McPherson, Ruth

2015-07-01

Genome-wide association studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks. Using pathways (gene sets) from Reactome, we carried out a 2-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CAD genome-wide association study data sets (9889 cases/11 089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15 502 cases/55 730 controls) from the Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication P<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix (ECM) integrity, innate immunity, axon guidance, and signaling by PDRF (platelet-derived growth factor), NOTCH, and the transforming growth factor-β/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (eg, semaphoring-regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared with random networks (P<0.001). Network centrality analysis (degree and betweenness) further identified genes (eg, NCAM1, FYN, FURIN, etc) likely to play critical roles in the maintenance and functioning of several of the replicated pathways. These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD. © 2015 American Heart Association, Inc.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PubMed

Hughes, Christopher S; Morin, Gregg B

2018-03-01

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme.

PubMed

Ovaska, Kristian; Laakso, Marko; Haapa-Paananen, Saija; Louhimo, Riku; Chen, Ping; Aittomäki, Viljami; Valo, Erkka; Núñez-Fontarnau, Javier; Rantanen, Ville; Karinen, Sirkku; Nousiainen, Kari; Lahesmaa-Korpinen, Anna-Maria; Miettinen, Minna; Saarinen, Lilli; Kohonen, Pekka; Wu, Jianmin; Westermarck, Jukka; Hautaniemi, Sampsa

2010-09-07

Coordinated efforts to collect large-scale data sets provide a basis for systems level understanding of complex diseases. In order to translate these fragmented and heterogeneous data sets into knowledge and medical benefits, advanced computational methods for data analysis, integration and visualization are needed. We introduce a novel data integration framework, Anduril, for translating fragmented large-scale data into testable predictions. The Anduril framework allows rapid integration of heterogeneous data with state-of-the-art computational methods and existing knowledge in bio-databases. Anduril automatically generates thorough summary reports and a website that shows the most relevant features of each gene at a glance, allows sorting of data based on different parameters, and provides direct links to more detailed data on genes, transcripts or genomic regions. Anduril is open-source; all methods and documentation are freely available. We have integrated multidimensional molecular and clinical data from 338 subjects having glioblastoma multiforme, one of the deadliest and most poorly understood cancers, using Anduril. The central objective of our approach is to identify genetic loci and genes that have significant survival effect. Our results suggest several novel genetic alterations linked to glioblastoma multiforme progression and, more specifically, reveal Moesin as a novel glioblastoma multiforme-associated gene that has a strong survival effect and whose depletion in vitro significantly inhibited cell proliferation. All analysis results are available as a comprehensive website. Our results demonstrate that integrated analysis and visualization of multidimensional and heterogeneous data by Anduril enables drawing conclusions on functional consequences of large-scale molecular data. Many of the identified genetic loci and genes having significant survival effect have not been reported earlier in the context of glioblastoma multiforme. Thus, in addition to generally applicable novel methodology, our results provide several glioblastoma multiforme candidate genes for further studies.Anduril is available at http://csbi.ltdk.helsinki.fi/anduril/The glioblastoma multiforme analysis results are available at http://csbi.ltdk.helsinki.fi/anduril/tcga-gbm/

The transcriptome of the novel dinoflagellate Oxyrrhis marina (Alveolata: Dinophyceae): response to salinity examined by 454 sequencing

PubMed Central

2011-01-01

Background The heterotrophic dinoflagellate Oxyrrhis marina is increasingly studied in experimental, ecological and evolutionary contexts. Its basal phylogenetic position within the dinoflagellates make O. marina useful for understanding the origin of numerous unusual features of the dinoflagellate lineage; its broad distribution has lent O. marina to the study of protist biogeography; and nutritive flexibility and eurytopy have made it a common lab rat for the investigation of physiological responses of marine heterotrophic flagellates. Nevertheless, genome-scale resources for O. marina are scarce. Here we present a 454-based transcriptome survey for this organism. In addition, we assess sequence read abundance, as a proxy for gene expression, in response to salinity, an environmental factor potentially important in determining O. marina spatial distributions. Results Sequencing generated ~57 Mbp of data which assembled into 7, 398 contigs. Approximately 24% of contigs were nominally identified by BLAST. A further clustering of contigs (at ≥ 90% identity) revealed 164 transcript variant clusters, the largest of which (Phosphoribosylaminoimidazole-succinocarboxamide synthase) was composed of 28 variants displaying predominately synonymous variation. In a genomic context, a sample of 5 different genes were demonstrated to occur as tandem repeats, separated by short (~200-340 bp) inter-genic regions. For HSP90 several intergenic variants were detected suggesting a potentially complex genomic arrangement. In response to salinity, analysis of 454 read abundance highlighted 9 and 20 genes over or under expressed at 50 PSU, respectively. However, 454 read abundance and subsequent qPCR validation did not correlate well - suggesting that measures of gene expression via ad hoc analysis of sequence read abundance require careful interpretation. Conclusion Here we indicate that tandem gene arrangements and the occurrence of multiple transcribed gene variants are common and indicate potentially complex genomic arrangements in O. marina. Comparison of the reported data set with existing O. marina and other dinoflagellates ESTs indicates little sequence overlap likely as a result of the relatively limited extent of genome scale sequence data currently available for the dinoflagellates. This is one of the first 454-based transcriptome surveys of an ancestral dinoflagellate taxon and will undoubtedly prove useful for future comparative studies aimed at reconstructing the origin of novel features of the dinoflagellates. PMID:22014029

Analysis of lamprey clustered Fox genes: insight into Fox gene evolution and expression in vertebrates.

PubMed

Wotton, Karl R; Shimeld, Sebastian M

2011-12-01

In the human genome, members of the FoxC, FoxF, FoxL1, and FoxQ1 gene families are found in two paralagous clusters. One cluster contains the genes FOXQ1, FOXF2, FOXC1 and the second consists of FOXF1, FOXC2, and FOXL1. In jawed vertebrates these genes are known to be expressed in different pharyngeal tissues and all, except FoxQ1, are involved in patterning the early embryonic mesoderm. We have previously traced the evolution of this cluster in the bony vertebrates, and the gene content is identical in the dogfish, a member of the most basally branching lineage of the jawed vertebrates. Here we extend these analyses to jawless vertebrates. Using genomic searches and molecular approaches we have identified homologues of these genes from lampreys. We identify two FoxC genes, two FoxF genes, two FoxQ1 genes and single FoxL1 gene. We examine the embryonic expression of one predominantly mesodermally expressed gene family, FoxC, and the endodermally expressed member of the cluster, FoxQ1. We identified FoxQ1 transcripts in the pharyngeal endoderm, while the two FoxC genes are differentially expressed in the pharyngeal mesenchyme and ectoderm. Furthermore we identify conserved expression of lamprey FoxC genes in the paraxial and intermediate mesoderms. We interpret our results through a chordate-wide comparison of expression patterns and discuss gene content in the context of theories on the evolution of the vertebrate genome. 2011 Elsevier B.V. All rights reserved.

Statistical assessment of crosstalk enrichment between gene groups in biological networks.

PubMed

McCormack, Theodore; Frings, Oliver; Alexeyenko, Andrey; Sonnhammer, Erik L L

2013-01-01

Analyzing groups of functionally coupled genes or proteins in the context of global interaction networks has become an important aspect of bioinformatic investigations. Assessing the statistical significance of crosstalk enrichment between or within groups of genes can be a valuable tool for functional annotation of experimental gene sets. Here we present CrossTalkZ, a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA). CrossTalkZ (available at http://sonnhammer.sbc.su.se/download/software/CrossTalkZ/) is implemented in C++, easy to use, fast, accepts various input file formats, and produces a number of statistics. These include z-score, p-value, false discovery rate, and a test of normality for the null distributions.

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes.

PubMed

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice.

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes

PubMed Central

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice. PMID:25374455

The first myriapod genome sequence reveals conservative arthropod gene content and genome organisation in the centipede Strigamia maritima.

PubMed

Chipman, Ariel D; Ferrier, David E K; Brena, Carlo; Qu, Jiaxin; Hughes, Daniel S T; Schröder, Reinhard; Torres-Oliva, Montserrat; Znassi, Nadia; Jiang, Huaiyang; Almeida, Francisca C; Alonso, Claudio R; Apostolou, Zivkos; Aqrawi, Peshtewani; Arthur, Wallace; Barna, Jennifer C J; Blankenburg, Kerstin P; Brites, Daniela; Capella-Gutiérrez, Salvador; Coyle, Marcus; Dearden, Peter K; Du Pasquier, Louis; Duncan, Elizabeth J; Ebert, Dieter; Eibner, Cornelius; Erikson, Galina; Evans, Peter D; Extavour, Cassandra G; Francisco, Liezl; Gabaldón, Toni; Gillis, William J; Goodwin-Horn, Elizabeth A; Green, Jack E; Griffiths-Jones, Sam; Grimmelikhuijzen, Cornelis J P; Gubbala, Sai; Guigó, Roderic; Han, Yi; Hauser, Frank; Havlak, Paul; Hayden, Luke; Helbing, Sophie; Holder, Michael; Hui, Jerome H L; Hunn, Julia P; Hunnekuhl, Vera S; Jackson, LaRonda; Javaid, Mehwish; Jhangiani, Shalini N; Jiggins, Francis M; Jones, Tamsin E; Kaiser, Tobias S; Kalra, Divya; Kenny, Nathan J; Korchina, Viktoriya; Kovar, Christie L; Kraus, F Bernhard; Lapraz, François; Lee, Sandra L; Lv, Jie; Mandapat, Christigale; Manning, Gerard; Mariotti, Marco; Mata, Robert; Mathew, Tittu; Neumann, Tobias; Newsham, Irene; Ngo, Dinh N; Ninova, Maria; Okwuonu, Geoffrey; Ongeri, Fiona; Palmer, William J; Patil, Shobha; Patraquim, Pedro; Pham, Christopher; Pu, Ling-Ling; Putman, Nicholas H; Rabouille, Catherine; Ramos, Olivia Mendivil; Rhodes, Adelaide C; Robertson, Helen E; Robertson, Hugh M; Ronshaugen, Matthew; Rozas, Julio; Saada, Nehad; Sánchez-Gracia, Alejandro; Scherer, Steven E; Schurko, Andrew M; Siggens, Kenneth W; Simmons, DeNard; Stief, Anna; Stolle, Eckart; Telford, Maximilian J; Tessmar-Raible, Kristin; Thornton, Rebecca; van der Zee, Maurijn; von Haeseler, Arndt; Williams, James M; Willis, Judith H; Wu, Yuanqing; Zou, Xiaoyan; Lawson, Daniel; Muzny, Donna M; Worley, Kim C; Gibbs, Richard A; Akam, Michael; Richards, Stephen

2014-11-01

Myriapods (e.g., centipedes and millipedes) display a simple homonomous body plan relative to other arthropods. All members of the class are terrestrial, but they attained terrestriality independently of insects. Myriapoda is the only arthropod class not represented by a sequenced genome. We present an analysis of the genome of the centipede Strigamia maritima. It retains a compact genome that has undergone less gene loss and shuffling than previously sequenced arthropods, and many orthologues of genes conserved from the bilaterian ancestor that have been lost in insects. Our analysis locates many genes in conserved macro-synteny contexts, and many small-scale examples of gene clustering. We describe several examples where S. maritima shows different solutions from insects to similar problems. The insect olfactory receptor gene family is absent from S. maritima, and olfaction in air is likely effected by expansion of other receptor gene families. For some genes S. maritima has evolved paralogues to generate coding sequence diversity, where insects use alternate splicing. This is most striking for the Dscam gene, which in Drosophila generates more than 100,000 alternate splice forms, but in S. maritima is encoded by over 100 paralogues. We see an intriguing linkage between the absence of any known photosensory proteins in a blind organism and the additional absence of canonical circadian clock genes. The phylogenetic position of myriapods allows us to identify where in arthropod phylogeny several particular molecular mechanisms and traits emerged. For example, we conclude that juvenile hormone signalling evolved with the emergence of the exoskeleton in the arthropods and that RR-1 containing cuticle proteins evolved in the lineage leading to Mandibulata. We also identify when various gene expansions and losses occurred. The genome of S. maritima offers us a unique glimpse into the ancestral arthropod genome, while also displaying many adaptations to its specific life history.

The First Myriapod Genome Sequence Reveals Conservative Arthropod Gene Content and Genome Organisation in the Centipede Strigamia maritima

PubMed Central

Chipman, Ariel D.; Ferrier, David E. K.; Brena, Carlo; Qu, Jiaxin; Hughes, Daniel S. T.; Schröder, Reinhard; Torres-Oliva, Montserrat; Znassi, Nadia; Jiang, Huaiyang; Almeida, Francisca C.; Alonso, Claudio R.; Apostolou, Zivkos; Aqrawi, Peshtewani; Arthur, Wallace; Barna, Jennifer C. J.; Blankenburg, Kerstin P.; Brites, Daniela; Capella-Gutiérrez, Salvador; Coyle, Marcus; Dearden, Peter K.; Du Pasquier, Louis; Duncan, Elizabeth J.; Ebert, Dieter; Eibner, Cornelius; Erikson, Galina; Evans, Peter D.; Extavour, Cassandra G.; Francisco, Liezl; Gabaldón, Toni; Gillis, William J.; Goodwin-Horn, Elizabeth A.; Green, Jack E.; Griffiths-Jones, Sam; Grimmelikhuijzen, Cornelis J. P.; Gubbala, Sai; Guigó, Roderic; Han, Yi; Hauser, Frank; Havlak, Paul; Hayden, Luke; Helbing, Sophie; Holder, Michael; Hui, Jerome H. L.; Hunn, Julia P.; Hunnekuhl, Vera S.; Jackson, LaRonda; Javaid, Mehwish; Jhangiani, Shalini N.; Jiggins, Francis M.; Jones, Tamsin E.; Kaiser, Tobias S.; Kalra, Divya; Kenny, Nathan J.; Korchina, Viktoriya; Kovar, Christie L.; Kraus, F. Bernhard; Lapraz, François; Lee, Sandra L.; Lv, Jie; Mandapat, Christigale; Manning, Gerard; Mariotti, Marco; Mata, Robert; Mathew, Tittu; Neumann, Tobias; Newsham, Irene; Ngo, Dinh N.; Ninova, Maria; Okwuonu, Geoffrey; Ongeri, Fiona; Palmer, William J.; Patil, Shobha; Patraquim, Pedro; Pham, Christopher; Pu, Ling-Ling; Putman, Nicholas H.; Rabouille, Catherine; Ramos, Olivia Mendivil; Rhodes, Adelaide C.; Robertson, Helen E.; Robertson, Hugh M.; Ronshaugen, Matthew; Rozas, Julio; Saada, Nehad; Sánchez-Gracia, Alejandro; Scherer, Steven E.; Schurko, Andrew M.; Siggens, Kenneth W.; Simmons, DeNard; Stief, Anna; Stolle, Eckart; Telford, Maximilian J.; Tessmar-Raible, Kristin; Thornton, Rebecca; van der Zee, Maurijn; von Haeseler, Arndt; Williams, James M.; Willis, Judith H.; Wu, Yuanqing; Zou, Xiaoyan; Lawson, Daniel; Muzny, Donna M.; Worley, Kim C.; Gibbs, Richard A.; Akam, Michael; Richards, Stephen

2014-01-01

Myriapods (e.g., centipedes and millipedes) display a simple homonomous body plan relative to other arthropods. All members of the class are terrestrial, but they attained terrestriality independently of insects. Myriapoda is the only arthropod class not represented by a sequenced genome. We present an analysis of the genome of the centipede Strigamia maritima. It retains a compact genome that has undergone less gene loss and shuffling than previously sequenced arthropods, and many orthologues of genes conserved from the bilaterian ancestor that have been lost in insects. Our analysis locates many genes in conserved macro-synteny contexts, and many small-scale examples of gene clustering. We describe several examples where S. maritima shows different solutions from insects to similar problems. The insect olfactory receptor gene family is absent from S. maritima, and olfaction in air is likely effected by expansion of other receptor gene families. For some genes S. maritima has evolved paralogues to generate coding sequence diversity, where insects use alternate splicing. This is most striking for the Dscam gene, which in Drosophila generates more than 100,000 alternate splice forms, but in S. maritima is encoded by over 100 paralogues. We see an intriguing linkage between the absence of any known photosensory proteins in a blind organism and the additional absence of canonical circadian clock genes. The phylogenetic position of myriapods allows us to identify where in arthropod phylogeny several particular molecular mechanisms and traits emerged. For example, we conclude that juvenile hormone signalling evolved with the emergence of the exoskeleton in the arthropods and that RR-1 containing cuticle proteins evolved in the lineage leading to Mandibulata. We also identify when various gene expansions and losses occurred. The genome of S. maritima offers us a unique glimpse into the ancestral arthropod genome, while also displaying many adaptations to its specific life history. PMID:25423365

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions.

PubMed

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-11-26

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

The complex physiology of Cellvibrio japonicus xylan degradation relies on a single cytoplasmic β-xylosidase for xylo-oligosaccharide utilization

DOE PAGES

Blake, Andrew D.; Beri, Nina R.; Guttman, Hadassa S.; ...

2017-12-21

Lignocellulose degradation by microbes plays a central role in global carbon cycling, human gut metabolism, and renewable energy technologies. While considerable effort has been put into understanding the biochemical aspects of lignocellulose degradation, much less work has been done to understand how these enzymes work in an in vivo context. Here in this paper, we report a systems level study of xylan degradation in the saprophytic bacterium Cellvibrio japonicus. Transcriptome analysis indicated seven genes that encode carbohydrate active enzymes were up-regulated during growth with xylan containing media. In-frame deletion analysis of these genes found that only gly43F is critical formore » utilization of xylo-oligosaccharides, xylan, and arabinoxylan. Heterologous expression of gly43F was sufficient for the utilization of xylo-oligosaccharides in Escherichia coli. Additional analysis found that the xyn11A, xyn11B, abf43L, abf43K, and abf51A gene products were critical for utilization of arabinoxylan. Furthermore, a predicted transporter (CJA_1315) was required for effective utilization of xylan substrates, and we propose this unannotated gene be called xntA (xylan transporter A). Our major findings are 1) C. japonicus employs both secreted and surface associated enzymes for xylan degradation, which differs from the strategy used for cellulose degradation, and 2) a single cytoplasmic β-xylosidase is essential for the utilization of xylo-oligosaccharides.« less

The complex physiology of Cellvibrio japonicus xylan degradation relies on a single cytoplasmic β-xylosidase for xylo-oligosaccharide utilization

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

Blake, Andrew D.; Beri, Nina R.; Guttman, Hadassa S.

Lignocellulose degradation by microbes plays a central role in global carbon cycling, human gut metabolism, and renewable energy technologies. While considerable effort has been put into understanding the biochemical aspects of lignocellulose degradation, much less work has been done to understand how these enzymes work in an in vivo context. Here in this paper, we report a systems level study of xylan degradation in the saprophytic bacterium Cellvibrio japonicus. Transcriptome analysis indicated seven genes that encode carbohydrate active enzymes were up-regulated during growth with xylan containing media. In-frame deletion analysis of these genes found that only gly43F is critical formore » utilization of xylo-oligosaccharides, xylan, and arabinoxylan. Heterologous expression of gly43F was sufficient for the utilization of xylo-oligosaccharides in Escherichia coli. Additional analysis found that the xyn11A, xyn11B, abf43L, abf43K, and abf51A gene products were critical for utilization of arabinoxylan. Furthermore, a predicted transporter (CJA_1315) was required for effective utilization of xylan substrates, and we propose this unannotated gene be called xntA (xylan transporter A). Our major findings are 1) C. japonicus employs both secreted and surface associated enzymes for xylan degradation, which differs from the strategy used for cellulose degradation, and 2) a single cytoplasmic β-xylosidase is essential for the utilization of xylo-oligosaccharides.« less

Gene regulatory network architecture in different developmental contexts influences the genetic basis of morphological evolution.

PubMed

Kittelmann, Sebastian; Buffry, Alexandra D; Franke, Franziska A; Almudi, Isabel; Yoth, Marianne; Sabaris, Gonzalo; Couso, Juan Pablo; Nunes, Maria D S; Frankel, Nicolás; Gómez-Skarmeta, José Luis; Pueyo-Marques, Jose; Arif, Saad; McGregor, Alistair P

2018-05-01

Convergent phenotypic evolution is often caused by recurrent changes at particular nodes in the underlying gene regulatory networks (GRNs). The genes at such evolutionary 'hotspots' are thought to maximally affect the phenotype with minimal pleiotropic consequences. This has led to the suggestion that if a GRN is understood in sufficient detail, the path of evolution may be predictable. The repeated evolutionary loss of larval trichomes among Drosophila species is caused by the loss of shavenbaby (svb) expression. svb is also required for development of leg trichomes, but the evolutionary gain of trichomes in the 'naked valley' on T2 femurs in Drosophila melanogaster is caused by reduced microRNA-92a (miR-92a) expression rather than changes in svb. We compared the expression and function of components between the larval and leg trichome GRNs to investigate why the genetic basis of trichome pattern evolution differs in these developmental contexts. We found key differences between the two networks in both the genes employed, and in the regulation and function of common genes. These differences in the GRNs reveal why mutations in svb are unlikely to contribute to leg trichome evolution and how instead miR-92a represents the key evolutionary switch in this context. Our work shows that variability in GRNs across different developmental contexts, as well as whether a morphological feature is lost versus gained, influence the nodes at which a GRN evolves to cause morphological change. Therefore, our findings have important implications for understanding the pathways and predictability of evolution.

Developing a PTEN-ERG Signature to Improve Molecular Risk Stratification in Prostate Cancer

DTIC Science & Technology

2017-10-01

that there exist distinctive molecular correlates of PTEN loss in the context of ETS-negative versus ETS-positive human prostate cancers and that...distinctive molecular correlates of PTEN loss in the context of ETS-negative versus ETS-positive human PCa and that these may drive prognosis...and MSKCC cohort, correlate these data with gene expression data from the same cohort to confirm ETS status and enable full gene expression analyses of

Identification and Characterization of the V(D)J Recombination Activating Gene 1 in Long-Term Memory of Context Fear Conditioning

PubMed Central

Castro-Pérez, Edgardo; Soto-Soto, Emilio; Pérez-Carambot, Marizabeth; Dionisio-Santos, Dawling; Saied-Santiago, Kristian; Ortiz-Zuazaga, Humberto G.; Peña de Ortiz, Sandra

2016-01-01

An increasing body of evidence suggests that mechanisms related to the introduction and repair of DNA double strand breaks (DSBs) may be associated with long-term memory (LTM) processes. Previous studies from our group suggested that factors known to function in DNA recombination/repair machineries, such as DNA ligases, polymerases, and DNA endonucleases, play a role in LTM. Here we report data using C57BL/6 mice showing that the V(D)J recombination-activating gene 1 (RAG1), which encodes a factor that introduces DSBs in immunoglobulin and T-cell receptor genes, is induced in the amygdala, but not in the hippocampus, after context fear conditioning. Amygdalar induction of RAG1 mRNA, measured by real-time PCR, was not observed in context-only or shock-only controls, suggesting that the context fear conditioning response is related to associative learning processes. Furthermore, double immunofluorescence studies demonstrated the neuronal localization of RAG1 protein in amygdalar sections prepared after perfusion and fixation. In functional studies, intra-amygdalar injections of RAG1 gapmer antisense oligonucleotides, given 1 h prior to conditioning, resulted in amygdalar knockdown of RAG1 mRNA and a significant impairment in LTM, tested 24 h after training. Overall, these findings suggest that the V(D)J recombination-activating gene 1, RAG1, may play a role in LTM consolidation. PMID:26843989

Analysis of Gastric Adenocarcinoma Data in a Pan-GI Context to Reveal Genes, Pathways, and Interactions that Yield Novel Therapeutic Advantages

DTIC Science & Technology

2017-09-01

that Yield Novel Therapeutic Advantages PRINCIPAL INVESTIGATOR: Rehan Akbani CONTRACTING ORGANIZATION: University of Texas MD Anderson Cancer ...mdanderson.org, jajani@mdanderson.org 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) The University of Texas MD Anderson Cancer Center...is the study of gastric cancer , where the purpose is to reveal new insights into the biology of the disease that could potentially have therapeutic

Maneuvering in the Complex Path from Genotype to Phenotype

NASA Astrophysics Data System (ADS)

Strohman, Richard

2002-04-01

Human disease phenotypes are controlled not only by genes but by lawful self-organizing networks that display system-wide dynamics. These networks range from metabolic pathways to signaling pathways that regulate hormone action. When perturbed, networks alter their output of matter and energy which, depending on the environmental context, can produce either a pathological or a normal phenotype. Study of the dynamics of these networks by approaches such as metabolic control analysis may provide new insights into the pathogenesis and treatment of complex diseases.

Attitudes towards human reproductive cloning, assisted reproduction and gene selection: a survey of 4600 British twins.

PubMed

Prainsack, B; Cherkas, L F; Spector, T D

2007-08-01

Surveys have shown opposition to human reproductive cloning (HRC) in many countries. Views of identical (monozygotic, MZ) twins are of particular interest, as they naturally share 100% of their genes. We investigated attitudes of British twins towards HRC in the context of assisted reproduction technologies (ART) and gene selection. About 4651 identical and non-identical (dizygotic, DZ) twins expressed their degree of agreement or disagreement to nine statements relating to ART, gene selection and HRC in a self-completion questionnaire. Most subjects (70% and 78% respectively) did not regard the use of medical technologies to treat infertility as interfering with either nature or God's will, despite believing that infertility is not a disease (54%). Attitudes to gene selection and HRC were context dependent, with more favourable views towards preventing serious diseases than towards enhancing traits. About 44% supported a permanent ban of HRC. MZ twins were significantly more likely to agree that HRC should be allowed for medical purposes, such as saving a sibling's life, than were DZ twins. Increasing religiosity generally correlated with more negative attitudes. Many attitudes are context dependent. More positive views of MZ twins towards HRC could be linked to their experience with being genetically identical.

Effect of oxytocin receptor blockade on appetite for sugar is modified by social context.

PubMed

Olszewski, Pawel K; Allen, Kerry; Levine, Allen S

2015-03-01

Research on oxytocin (OT) has yielded two seemingly unrelated sets of discoveries: OT has prosocial effects, and it elicits termination of feeding, especially of food rich in carbohydrates. Here we investigated whether OT's involvement in food intake is affected by the social context in mice, with particular focus on the role of dominance. We used two approaches: injections and gene expression analysis. We housed two males per cage and determined a dominant one. Then we injected a blood-brain barrier penetrant OT receptor antagonist L-368,899 in either dominant or subordinate animals and gave them 10-min access to a sucrose solution in the apparatus in which social exposure was modified and it ranged from none to unrestricted contact. L-368,899 increased the amount of consumed sugar in dominant mice regardless of whether these animals had access to sucrose in the non-social or social contexts (olfactory-derived or partial social exposure). The antagonist also increased the proportion of time that dominant mice spent drinking the sweet solution in the paradigm in which both mice had to share a single source of sucrose. L-368,899-treated subordinate mice consumed more sucrose solution than saline controls only when the environment in which sugar was presented was devoid of social cues related to the dominant animal. Finally, we investigated whether hypothalamic OT gene expression differs between dominant and subordinate mice consuming sugar and found OT mRNA levels to be higher in dominant mice. We conclude that social context and dominance affect OT's effect on appetite for sucrose. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.

PubMed

Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi

2007-10-04

In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Modeling adaptive kernels from probabilistic phylogenetic trees.

PubMed

Nicotra, Luca; Micheli, Alessio

2009-01-01

Modeling phylogenetic interactions is an open issue in many computational biology problems. In the context of gene function prediction we introduce a class of kernels for structured data leveraging on a hierarchical probabilistic modeling of phylogeny among species. We derive three kernels belonging to this setting: a sufficient statistics kernel, a Fisher kernel, and a probability product kernel. The new kernels are used in the context of support vector machine learning. The kernels adaptivity is obtained through the estimation of the parameters of a tree structured model of evolution using as observed data phylogenetic profiles encoding the presence or absence of specific genes in a set of fully sequenced genomes. We report results obtained in the prediction of the functional class of the proteins of the budding yeast Saccharomyces cerevisae which favorably compare to a standard vector based kernel and to a non-adaptive tree kernel function. A further comparative analysis is performed in order to assess the impact of the different components of the proposed approach. We show that the key features of the proposed kernels are the adaptivity to the input domain and the ability to deal with structured data interpreted through a graphical model representation.

Transcriptome Analysis of Arabidopsis GCR1 Mutant Reveals Its Roles in Stress, Hormones, Secondary Metabolism and Phosphate Starvation

PubMed Central

Chakraborty, Navjyoti; Sharma, Priyanka; Kanyuka, Kostya; Pathak, Ravi R.; Choudhury, Devapriya; Hooley, Richard A.; Raghuram, Nandula

2015-01-01

The controversy over the existence or the need for G-protein coupled receptors (GPCRs) in plant G-protein signalling has overshadowed a more fundamental quest for the role of AtGCR1, the most studied and often considered the best candidate for GPCR in plants. Our whole transcriptome microarray analysis of the GCR1-knock-out mutant (gcr1-5) in Arabidopsis thaliana revealed 350 differentially expressed genes spanning all chromosomes. Many of them were hitherto unknown in the context of GCR1 or G-protein signalling, such as in phosphate starvation, storage compound and fatty acid biosynthesis, cell fate, etc. We also found some GCR1-responsive genes/processes that are reported to be regulated by heterotrimeric G-proteins, such as biotic and abiotic stress, hormone response and secondary metabolism. Thus, GCR1 could have G-protein-mediated as well as independent roles and regardless of whether it works as a GPCR, further analysis of the organism-wide role of GCR1 has a significance of its own. PMID:25668726

Identification and Molecular Characterization of MYB Transcription Factor Superfamily in C4 Model Plant Foxtail Millet (Setaria italica L.)

PubMed Central

Muthamilarasan, Mehanathan; Khandelwal, Rohit; Yadav, Chandra Bhan; Bonthala, Venkata Suresh; Khan, Yusuf; Prasad, Manoj

2014-01-01

MYB proteins represent one of the largest transcription factor families in plants, playing important roles in diverse developmental and stress-responsive processes. Considering its significance, several genome-wide analyses have been conducted in almost all land plants except foxtail millet. Foxtail millet (Setaria italica L.) is a model crop for investigating systems biology of millets and bioenergy grasses. Further, the crop is also known for its potential abiotic stress-tolerance. In this context, a comprehensive genome-wide survey was conducted and 209 MYB protein-encoding genes were identified in foxtail millet. All 209 S. italica MYB (SiMYB) genes were physically mapped onto nine chromosomes of foxtail millet. Gene duplication study showed that segmental- and tandem-duplication have occurred in genome resulting in expansion of this gene family. The protein domain investigation classified SiMYB proteins into three classes according to number of MYB repeats present. The phylogenetic analysis categorized SiMYBs into ten groups (I - X). SiMYB-based comparative mapping revealed a maximum orthology between foxtail millet and sorghum, followed by maize, rice and Brachypodium. Heat map analysis showed tissue-specific expression pattern of predominant SiMYB genes. Expression profiling of candidate MYB genes against abiotic stresses and hormone treatments using qRT-PCR revealed specific and/or overlapping expression patterns of SiMYBs. Taken together, the present study provides a foundation for evolutionary and functional characterization of MYB TFs in foxtail millet to dissect their functions in response to environmental stimuli. PMID:25279462

The prognostic significance of specific HOX gene expression patterns in ovarian cancer.

PubMed

Kelly, Zoe; Moller-Levet, Carla; McGrath, Sophie; Butler-Manuel, Simon; Kavitha Madhuri, Thumuluru; Kierzek, Andrzej M; Pandha, Hardev; Morgan, Richard; Michael, Agnieszka

2016-10-01

HOX genes are vital for all aspects of mammalian growth and differentiation, and their dysregulated expression is related to ovarian carcinogenesis. The aim of the current study was to establish the prognostic value of HOX dysregulation as well as its role in platinum resistance. The potential to target HOX proteins through the HOX/PBX interaction was also explored in the context of platinum resistance. HOX gene expression was determined in ovarian cancer cell lines and primary EOCs by QPCR, and compared to expression in normal ovarian epithelium and fallopian tube tissue samples. Statistical analysis included one-way ANOVA and t-tests, using statistical software R and GraphPad. The analysis identified 36 of the 39 HOX genes as being overexpressed in high grade serous EOC compared to normal tissue. We detected a molecular HOX gene-signature that predicted poor outcome. Overexpression of HOXB4 and HOXB9 was identified in high grade serous cell lines after platinum resistance developed. Targeting the HOX/PBX dimer with the HXR9 peptide enhanced the cytotoxicity of cisplatin in platinum-resistant ovarian cancer. In conclusion, this study has shown the HOX genes are highly dysregulated in ovarian cancer with high expression of HOXA13, B6, C13, D1 and D13 being predictive of poor clinical outcome. Targeting the HOX/PBX dimer in platinum-resistant cancer represents a potentially new therapeutic option that should be further developed and tested in clinical trials. © 2016 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

High time for a roll call: gene duplication and phylogenetic relationships of TCP-like genes in monocots

PubMed Central

Mondragón-Palomino, Mariana; Trontin, Charlotte

2011-01-01

Background and Aims The TCP family is an ancient group of plant developmental transcription factors that regulate cell division in vegetative and reproductive structures and are essential in the establishment of flower zygomorphy. In-depth research on eudicot TCPs has documented their evolutionary and developmental role. This has not happened to the same extent in monocots, although zygomorphy has been critical for the diversification of Orchidaceae and Poaceae, the largest families of this group. Investigating the evolution and function of TCP-like genes in a wider group of monocots requires a detailed phylogenetic analysis of all available sequence information and a system that facilitates comparing genetic and functional information. Methods The phylogenetic relationships of TCP-like genes in monocots were investigated by analysing sequences from the genomes of Zea mays, Brachypodium distachyon, Oryza sativa and Sorghum bicolor, as well as EST data from several other monocot species. Key Results All available monocot TCP-like sequences are associated in 20 major groups with an average identity ≥64 % and most correspond to well-supported clades of the phylogeny. Their sequence motifs and relationships of orthology were documented and it was found that 67 % of the TCP-like genes of Sorghum, Oryza, Zea and Brachypodium are in microsyntenic regions. This analysis suggests that two rounds of whole genome duplication drove the expansion of TCP-like genes in these species. Conclusions A system of classification is proposed where putative or recognized monocot TCP-like genes are assigned to a specific clade of PCF-, CIN- or CYC/tb1-like genes. Specific biases in sequence data of this family that must be tackled when studying its molecular evolution and phylogeny are documented. Finally, the significant retention of duplicated TCP genes from Zea mays is considered in the context of balanced gene drive. PMID:21444336

Immediate early gene activation throughout the brain is associated with dynamic changes in social context.

PubMed

Williamson, Cait M; Klein, Inbal S; Lee, Won; Curley, James P

2018-05-31

Social competence is dependent on successful processing of social context information. The social opportunity paradigm is a methodology in which dynamic shifts in social context are induced through removal of the alpha male in a dominance hierarchy, leading to rapid ascent in the hierarchy of the beta male and of other subordinate males in the social group. In the current study, we use the social opportunity paradigm to determine what brain regions respond to this dynamic change in social context, allowing an individual to recognize the absence of the alpha male and subsequently perform status-appropriate social behaviors. Replicating our previous work, we show that following removal of the alpha male, beta males rapidly ascend the social hierarchy and attain dominant status by increasing aggression towards more subordinate individuals. Analysis of patterns of Fos immunoreactivity throughout the brain indicates that in individuals undergoing social ascent, there is increased activity in regions of the social behavior network, as well as the infralimbic and prelimbic regions of the prefrontal cortex and areas of the hippocampus. Our findings demonstrate that male mice are able to respond to changes in social context and provide insight into the how the brain processes these complex behavioral changes.

Genomic and Network Patterns of Schizophrenia Genetic Variation in Human Evolutionary Accelerated Regions

PubMed Central

Xu, Ke; Schadt, Eric E.; Pollard, Katherine S.; Roussos, Panos; Dudley, Joel T.

2015-01-01

The population persistence of schizophrenia despite associated reductions in fitness and fecundity suggests that the genetic basis of schizophrenia has a complex evolutionary history. A recent meta-analysis of schizophrenia genome-wide association studies offers novel opportunities for assessment of the evolutionary trajectories of schizophrenia-associated loci. In this study, we hypothesize that components of the genetic architecture of schizophrenia are attributable to human lineage-specific evolution. Our results suggest that schizophrenia-associated loci enrich in genes near previously identified human accelerated regions (HARs). Specifically, we find that genes near HARs conserved in nonhuman primates (pHARs) are enriched for schizophrenia-associated loci, and that pHAR-associated schizophrenia genes are under stronger selective pressure than other schizophrenia genes and other pHAR-associated genes. We further evaluate pHAR-associated schizophrenia genes in regulatory network contexts to investigate associated molecular functions and mechanisms. We find that pHAR-associated schizophrenia genes significantly enrich in a GABA-related coexpression module that was previously found to be differentially regulated in schizophrenia affected individuals versus healthy controls. In another two independent networks constructed from gene expression profiles from prefrontal cortex samples, we find that pHAR-associated schizophrenia genes are located in more central positions and their average path lengths to the other nodes are significantly shorter than those of other schizophrenia genes. Together, our results suggest that HARs are associated with potentially important functional roles in the genetic architecture of schizophrenia. PMID:25681384

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures

PubMed Central

2013-01-01

Background The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. Results We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. Conclusions The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis. PMID:24067102

Disentangling methodological and biological sources of gene tree discordance on Oryza (Poaceae) chromosome 3.

PubMed

Zwickl, Derrick J; Stein, Joshua C; Wing, Rod A; Ware, Doreen; Sanderson, Michael J

2014-09-01

We describe new methods for characterizing gene tree discordance in phylogenomic data sets, which screen for deviations from neutral expectations, summarize variation in statistical support among gene trees, and allow comparison of the patterns of discordance induced by various analysis choices. Using an exceptionally complete set of genome sequences for the short arm of chromosome 3 in Oryza (rice) species, we applied these methods to identify the causes and consequences of differing patterns of discordance in the sets of gene trees inferred using a panel of 20 distinct analysis pipelines. We found that discordance patterns were strongly affected by aspects of data selection, alignment, and alignment masking. Unusual patterns of discordance evident when using certain pipelines were reduced or eliminated by using alternative pipelines, suggesting that they were the product of methodological biases rather than evolutionary processes. In some cases, once such biases were eliminated, evolutionary processes such as introgression could be implicated. Additionally, patterns of gene tree discordance had significant downstream impacts on species tree inference. For example, inference from supermatrices was positively misleading when pipelines that led to biased gene trees were used. Several results may generalize to other data sets: we found that gene tree and species tree inference gave more reasonable results when intron sequence was included during sequence alignment and tree inference, the alignment software PRANK was used, and detectable "block-shift" alignment artifacts were removed. We discuss our findings in the context of well-established relationships in Oryza and continuing controversies regarding the domestication history of O. sativa. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The dam replacing gene product enhances Neisseria gonorrhoeae FA1090 viability and biofilm formation

PubMed Central

Kwiatek, Agnieszka; Bacal, Pawel; Wasiluk, Adrian; Trybunko, Anastasiya; Adamczyk-Poplawska, Monika

2014-01-01

Many Neisseriaceae do not exhibit Dam methyltransferase activity and, instead of the dam gene, possess drg (dam replacing gene) inserted in the leuS/dam locus. The drg locus in Neisseria gonorrhoeae FA1090 has a lower GC-pairs content (40.5%) compared to the whole genome of N. gonorrhoeae FA1090 (52%). The gonococcal drg gene encodes a DNA endonuclease Drg, with GmeATC specificity. Disruption of drg or insertion of the dam gene in gonococcal genome changes the level of expression of genes as shown by transcriptome analysis. For the drg-deficient N. gonorrhoeae mutant, a total of 195 (8.94% of the total gene pool) genes exhibited an altered expression compared to the wt strain by at least 1.5 fold. In dam-expressing N. gonorrhoeae mutant, the expression of 240 genes (11% of total genes) was deregulated. Most of these deregulated genes were involved in translation, DNA repair, membrane biogenesis and energy production as shown by cluster of orthologous group analysis. In vivo, the inactivation of drg gene causes the decrease of the number of live neisserial cells and long lag phase of growth. The insertion of dam gene instead of drg locus restores cell viability. We have also shown that presence of the drg gene product is important for N. gonorrhoeae FA1090 in adhesion, including human epithelial cells, and biofilm formation. Biofilm produced by drg-deficient strain is formed by more dispersed cells, compared to this one formed by parental strain as shown by scanning electron and confocal microscopy. Also adherence assays show a significantly smaller biomass of formed biofilm (OD570 = 0.242 ± 0.038) for drg-deficient strain, compared to wild-type strain (OD570 = 0.378 ± 0.057). Dam-expressing gonococcal cells produce slightly weaker biofilm with cells embedded in an extracellular matrix. This strain has also a five times reduced ability for adhesion to human epithelial cells. In this context, the presence of Drg is more advantageous for N. gonorrhoeae biology than Dam presence. PMID:25566225

Draft genome sequences of bacteria isolated from the Deschampsia antarctica phyllosphere.

PubMed

Cid, Fernanda P; Maruyama, Fumito; Murase, Kazunori; Graether, Steffen P; Larama, Giovanni; Bravo, Leon A; Jorquera, Milko A

2018-05-01

Genome analyses are being used to characterize plant growth-promoting (PGP) bacteria living in different plant compartiments. In this context, we have recently isolated bacteria from the phyllosphere of an Antarctic plant (Deschampsia antarctica) showing ice recrystallization inhibition (IRI), an activity related to the presence of antifreeze proteins (AFPs). In this study, the draft genomes of six phyllospheric bacteria showing IRI activity were sequenced and annotated according to their functional gene categories. Genome sizes ranged from 5.6 to 6.3 Mbp, and based on sequence analysis of the 16S rRNA genes, five strains were identified as Pseudomonas and one as Janthinobacterium. Interestingly, most strains showed genes associated with PGP traits, such as nutrient uptake (ammonia assimilation, nitrogen fixing, phosphatases, and organic acid production), bioactive metabolites (indole acetic acid and 1-aminocyclopropane-1-carboxylate deaminase), and antimicrobial compounds (hydrogen cyanide and pyoverdine). In relation with IRI activity, a search of putative AFPs using current bioinformatic tools was also carried out. Despite that genes associated with reported AFPs were not found in these genomes, genes connected to ice-nucleation proteins (InaA) were found in all Pseudomonas strains, but not in the Janthinobacterium strain.

Sex- and brain region-specific patterns of gene expression associated with socially-mediated puberty in a eusocial mammal

PubMed Central

Monks, D. Ashley; Zovkic, Iva B.; Holmes, Melissa M.

2018-01-01

The social environment can alter pubertal timing through neuroendocrine mechanisms that are not fully understood; it is thought that stress hormones (e.g., glucocorticoids or corticotropin-releasing hormone) influence the hypothalamic-pituitary-gonadal axis to inhibit puberty. Here, we use the eusocial naked mole-rat, a unique species in which social interactions in a colony (i.e. dominance of a breeding female) suppress puberty in subordinate animals. Removing subordinate naked mole-rats from this social context initiates puberty, allowing for experimental control of pubertal timing. The present study quantified gene expression for reproduction- and stress-relevant genes acting upstream of gonadotropin-releasing hormone in brain regions with reproductive and social functions in pre-pubertal, post-pubertal, and opposite sex-paired animals (which are in various stages of pubertal transition). Results indicate sex differences in patterns of neural gene expression. Known functions of genes in brain suggest stress as a key contributing factor in regulating male pubertal delay. Network analysis implicates neurokinin B (Tac3) in the arcuate nucleus of the hypothalamus as a key node in this pathway. Results also suggest an unappreciated role for the nucleus accumbens in regulating puberty. PMID:29474488

Splice Site Variants in the KCNQ1 and SCN5A Genes: Transcript Analysis as a Tool in Supporting Pathogenicity

PubMed Central

Leong, Ivone U.S.; Dryland, Philippa A.; Prosser, Debra O.; Lai, Stella W.-S.; Graham, Mandy; Stiles, Martin; Crawford, Jackie; Skinner, Jonathan R.; Love, Donald R.

2017-01-01

Background Approximately 75% of clinically definite long QT syndrome (LQTS) cases are caused by mutations in the KCNQ1, KCNH2 and SCN5A genes. Of these mutations, a small proportion (3.2-9.2%) are predicted to affect splicing. These mutations present a particular challenge in ascribing pathogenicity. Methods Here we report an analysis of the transcriptional consequences of two mutations, one in the KCNQ1 gene (c.781_782delinsTC) and one in the SCN5A gene (c.2437-5C>A), which are predicted to affect splicing. We isolated RNA from lymphocytes and used a directed PCR amplification strategy of cDNA to show mis-spliced transcripts in mutation-positive patients. Results The loss of an exon in each mis-spliced transcript had no deduced effect on the translational reading frame. The clinical phenotype corresponded closely with genotypic status in family members carrying the KCNQ1 splice variant, but not in family members with the SCN5A splice variant. These results are put in the context of a literature review, where only 20% of all splice variants reported in the KCNQ1, KCNH2 and SCN5A gene entries in the HGMDPro 2015.4 database have been evaluated using transcriptional assays. Conclusions Prediction programmes play a strong role in most diagnostic laboratories in classifying variants located at splice sites; however, transcriptional analysis should be considered critical to confirm mis-splicing. Critically, this study shows that genuine mis- splicing may not always imply clinical significance, and genotype/phenotype cosegregation remains important even when mis-splicing is confirmed. PMID:28725320

Petri net modelling of gene regulation of the Duchenne muscular dystrophy.

PubMed

Grunwald, Stefanie; Speer, Astrid; Ackermann, Jörg; Koch, Ina

2008-05-01

Searching for therapeutic strategies for Duchenne muscular dystrophy, it is of great interest to understand the responsible molecular pathways down-stream of dystrophin completely. For this reason we have performed real-time PCR experiments to compare mRNA expression levels of relevant genes in tissues of affected patients and controls. To bring experimental data in context with the underlying pathway theoretical models are needed. Modelling of biological processes in the cell at higher description levels is still an open problem in the field of systems biology. In this paper, a new application of Petri net theory is presented to model gene regulatory processes of Duchenne muscular dystrophy. We have developed a Petri net model, which is based mainly on own experimental and literature data. We distinguish between up- and down-regulated states of gene expression. The analysis of the model comprises the computation of structural and dynamic properties with focus on a thorough T-invariant analysis, including clustering techniques and the decomposition of the network into maximal common transition sets (MCT-sets), which can be interpreted as functionally related building blocks. All possible pathways, which reflect the complex net behaviour in dependence of different gene expression patterns, are discussed. We introduce Mauritius maps of T-invariants, which enable, for example, theoretical knockout analysis. The resulted model serves as basis for a better understanding of pathological processes, and thereby for planning next experimental steps in searching for new therapeutic possibilities. Free availability of the Petri net editor and animator Snoopy and the clustering tool PInA via http://www-dssz.informatik.tu-cottbus.de/~ wwwdssz/. The Petri net models used can be accessed via http://www.tfh-berlin.de/bi/duchenne/.

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

PubMed

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

2016-06-01

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

Herpesvirus papio 2 encodes a virion host shutoff function.

PubMed

Bigger, John E; Martin, David W

2002-12-05

Infection of baboons with herpesvirus papio 2 (HVP-2) produces a disease that is similar to human infection with herpes simplex viruses (HSV). Molecular characterization of HVP-2 has demonstrated that the virion contains a factor which rapidly shuts off host cell protein synthesis after infection. Reduction of host cell protein synthesis occurs in parallel with the degradation of mRNA species. A homolog of the HSV virion host shutoff (vhs) gene was identified by Southern and DNA sequence analysis. The sequence of the HVP-2 vhs gene homolog had greater than 70% identity with the vhs genes of HSV 1 and 2. Disruption of the HVP-2 vhs open reading frame diminished the ability of the virus to shut off protein synthesis and degrade cellular mRNA, indicating that this gene was responsible for the vhs activity. The HVP-2 model system provides the opportunity to study the biological role of vhs in the context of a natural primate host. Further development of this system will provide a platform for proof-of-concept studies that will test the efficacy of vaccines that utilize vhs-deficient viruses.

Changing Faces of Transcriptional Regulation Reflected by Zic3

PubMed Central

Winata, Cecilia Lanny; Kondrychyn, Igor; Deddens, J.C.; Korzh, Vladimir

2015-01-01

The advent of genomics in the study of developmental mechanisms has brought a trove of information on gene datasets and regulation during development, where the Zic family of zinc-finger proteins plays an important role. Genomic analysis of the modes of action of Zic3 in pluripotent cells demonstrated its requirement for maintenance of stem cells pluripotency upon binding to the proximal regulatory regions (promoters) of genes associated with cell pluripotency (Nanog, Sox2, Oct4, etc.) as well as cell cycle, proliferation, oncogenesis and early embryogenesis. In contrast, during gastrulation and neurulation Zic3 acts by binding the distal regulatory regions (enhancers, etc) associated with control of gene transcription in the Nodal and Wnt signaling pathways, including genes that act to break body symmetry. This illustrates a general role of Zic3 as a transcriptional regulator that acts not only alone, but in many instances in conjunction with other transcription factors. The latter is done by binding to adjacent sites in the context of multi-transcription factor complexes associated with regulatory elements. PMID:26085810

Relations between Three Dopaminergic System Genes, School Attachment, and Adolescent Delinquency

ERIC Educational Resources Information Center

Fine, Adam; Mahler, Alissa; Simmons, Cortney; Chen, Chuansheng; Moyzis, Robert; Cauffman, Elizabeth

2016-01-01

Both environmental factors and genetic variation, particularly in genes responsible for the dopaminergic system such as "DRD4," "DRD2," and "DAT1" ("SLC6A3"), affect adolescent delinquency. The school context, despite its developmental importance, has been overlooked in gene-environment research. Using data…

Conserved Non-Coding Regulatory Signatures in Arabidopsis Co-Expressed Gene Modules

PubMed Central

Spangler, Jacob B.; Ficklin, Stephen P.; Luo, Feng; Freeling, Michael; Feltus, F. Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome. PMID:23024789

Conserved non-coding regulatory signatures in Arabidopsis co-expressed gene modules.

PubMed

Spangler, Jacob B; Ficklin, Stephen P; Luo, Feng; Freeling, Michael; Feltus, F Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome.

Metabolic Context of the Competence-Induced Checkpoint for Cell Replication in Streptococcus suis.

PubMed

Zaccaria, Edoardo; Wells, Jerry M; van Baarlen, Peter

2016-01-01

Natural genetic transformation is a transient, rapidly progressing energy-consuming process characterized by expression of the transformasome and competence-associated regulatory genes. This transient state is tightly controlled to avoid potentially adverse effects of genetic recombination on genome integrity during cell division. We investigated the global response of Streptococcus suis to exposure to the SigX competence-inducing peptide (XIP), and thus to the activation of the competence machinery, using time series analysis together with PCA analysis, gene clustering followed by heatmap visualisation, and GO enrichment analysis. We explored the possible regulatory link between metabolism and competence, and predicted the physiological adaptation of S. suis during competence induction, progression and exit using transcriptome analysis. We showed that competence development is associated with a suppression of basal metabolism, which may have consequences for the microbe's resilience to fluctuations in the environment, as competence is costly in terms of use of energy and protein translation. Furthermore our data suggest that several basal metabolic pathways are incompatible with activation of competence in S. suis. This study also showed that targeting specific pathways during the development of competence, might render S. suis more vulnerable toward novel antibiotic therapies.

Metabolic Context of the Competence-Induced Checkpoint for Cell Replication in Streptococcus suis

PubMed Central

Zaccaria, Edoardo; Wells, Jerry M.

2016-01-01

Natural genetic transformation is a transient, rapidly progressing energy-consuming process characterized by expression of the transformasome and competence-associated regulatory genes. This transient state is tightly controlled to avoid potentially adverse effects of genetic recombination on genome integrity during cell division. We investigated the global response of Streptococcus suis to exposure to the SigX competence-inducing peptide (XIP), and thus to the activation of the competence machinery, using time series analysis together with PCA analysis, gene clustering followed by heatmap visualisation, and GO enrichment analysis. We explored the possible regulatory link between metabolism and competence, and predicted the physiological adaptation of S. suis during competence induction, progression and exit using transcriptome analysis. We showed that competence development is associated with a suppression of basal metabolism, which may have consequences for the microbe's resilience to fluctuations in the environment, as competence is costly in terms of use of energy and protein translation. Furthermore our data suggest that several basal metabolic pathways are incompatible with activation of competence in S. suis. This study also showed that targeting specific pathways during the development of competence, might render S. suis more vulnerable toward novel antibiotic therapies. PMID:27149631

htsint: a Python library for sequencing pipelines that combines data through gene set generation.

PubMed

Richards, Adam J; Herrel, Anthony; Bonneaud, Camille

2015-09-24

Sequencing technologies provide a wealth of details in terms of genes, expression, splice variants, polymorphisms, and other features. A standard for sequencing analysis pipelines is to put genomic or transcriptomic features into a context of known functional information, but the relationships between ontology terms are often ignored. For RNA-Seq, considering genes and their genetic variants at the group level enables a convenient way to both integrate annotation data and detect small coordinated changes between experimental conditions, a known caveat of gene level analyses. We introduce the high throughput data integration tool, htsint, as an extension to the commonly used gene set enrichment frameworks. The central aim of htsint is to compile annotation information from one or more taxa in order to calculate functional distances among all genes in a specified gene space. Spectral clustering is then used to partition the genes, thereby generating functional modules. The gene space can range from a targeted list of genes, like a specific pathway, all the way to an ensemble of genomes. Given a collection of gene sets and a count matrix of transcriptomic features (e.g. expression, polymorphisms), the gene sets produced by htsint can be tested for 'enrichment' or conditional differences using one of a number of commonly available packages. The database and bundled tools to generate functional modules were designed with sequencing pipelines in mind, but the toolkit nature of htsint allows it to also be used in other areas of genomics. The software is freely available as a Python library through GitHub at https://github.com/ajrichards/htsint.

Identification of a PEAK1/ZEB1 signaling axis during TGFβ/fibronectin-induced EMT in breast cancer

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

Agajanian, Megan; Runa, Farhana; Kelber, Jonathan A., E-mail: jonathan.kelber@csun.edu

Transforming Growth Factor beta (TGFβ) is the archetypal member of the TGFβ superfamily of ligands and has pleiotropic functions during normal development, adult tissue homeostasis and pathophysiological processes such as cancer. In epithelial cancers TGFβ signaling can either suppress tumor growth or promote metastasis via the induction of a well-characterized epithelial–mesenchymal transition (EMT) program. We recently reported that PEAK1 kinase mediates signaling cross talk between TGFβ receptors and integrin/Src/MAPK pathways and functions as a critical molecular regulator of TGFβ-induced breast cancer cell proliferation, migration, EMT and metastasis. Here, we examined the breast cancer cell contexts in which TGFβ induces bothmore » EMT and PEAK1, and discovered this event to be unique to oncogene-transformed mammary epithelial cells and triple-negative breast cancer cells. Using the Cancer BioPortal database, we identified PEAK1 co-expressors across multiple malignancies that are also common to the TGFβ response gene signature (TBRS). We then used the ScanSite database to identify predicted protein–protein binding partners of PEAK1 and the PEAK1-TBRS co-expressors. Analysis of the Cytoscape interactome and Babelomics-derived gene ontologies for a novel gene set including PEAK1, CRK, ZEB1, IL11 and COL4A1 enabled us to hypothesize that PEAK1 may be regulating TGFβ-induced EMT via its interaction with or regulation of these other genes. In this regard, we have demonstrated that PEAK1 is necessary for TGFβ to induce ZEB1-mediated EMT in the context of fibronectin/ITGB3 activation. These studies and future mechanistic studies will pave the way toward identifying the context in which TGFβ blockade may significantly improve breast cancer patient outcomes. - Highlights: • PEAK1 is upregulated in mammary epithelial cells during TGFβ-induced EMT. • TGFβ-induced EMT upregulates PEAK1 in triple negative breast cancer. • PEAK1 is necessary for TGFβ/fibronectin-induced ZEB1 expression during EMT. • The PEAK1/CRK/ZEB1 pathway is a novel target for blocking EMT in breast cancer.« less

A genome-wide resource for the analysis of protein localisation in Drosophila

PubMed Central

Sarov, Mihail; Barz, Christiane; Jambor, Helena; Hein, Marco Y; Schmied, Christopher; Suchold, Dana; Stender, Bettina; Janosch, Stephan; KJ, Vinay Vikas; Krishnan, RT; Krishnamoorthy, Aishwarya; Ferreira, Irene RS; Ejsmont, Radoslaw K; Finkl, Katja; Hasse, Susanne; Kämpfer, Philipp; Plewka, Nicole; Vinis, Elisabeth; Schloissnig, Siegfried; Knust, Elisabeth; Hartenstein, Volker; Mann, Matthias; Ramaswami, Mani; VijayRaghavan, K; Tomancak, Pavel; Schnorrer, Frank

2016-01-01

The Drosophila genome contains >13000 protein-coding genes, the majority of which remain poorly investigated. Important reasons include the lack of antibodies or reporter constructs to visualise these proteins. Here, we present a genome-wide fosmid library of 10000 GFP-tagged clones, comprising tagged genes and most of their regulatory information. For 880 tagged proteins, we created transgenic lines, and for a total of 207 lines, we assessed protein expression and localisation in ovaries, embryos, pupae or adults by stainings and live imaging approaches. Importantly, we visualised many proteins at endogenous expression levels and found a large fraction of them localising to subcellular compartments. By applying genetic complementation tests, we estimate that about two-thirds of the tagged proteins are functional. Moreover, these tagged proteins enable interaction proteomics from developing pupae and adult flies. Taken together, this resource will boost systematic analysis of protein expression and localisation in various cellular and developmental contexts. DOI: http://dx.doi.org/10.7554/eLife.12068.001 PMID:26896675

High-throughput metagenomic technologies for complex microbial community analysis: open and closed formats.

PubMed

Zhou, Jizhong; He, Zhili; Yang, Yunfeng; Deng, Ye; Tringe, Susannah G; Alvarez-Cohen, Lisa

2015-01-27

Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied "open-format" and "closed-format" detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications and focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions. Copyright © 2015 Zhou et al.

High-Throughput Metagenomic Technologies for Complex Microbial Community Analysis: Open and Closed Formats

PubMed Central

He, Zhili; Yang, Yunfeng; Deng, Ye; Tringe, Susannah G.; Alvarez-Cohen, Lisa

2015-01-01

ABSTRACT   Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied “open-format” and “closed-format” detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications and focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions. PMID:25626903

High-throughput metagenomic technologies for complex microbial community analysis. Open and closed formats

DOE PAGES

Zhou, Jizhong; He, Zhili; Yang, Yunfeng; ...

2015-01-27

Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied “open-format” and “closed-format” detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications andmore » focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions.« less

Regulation of expression of two LY-6 family genes by intron retention and transcription induced chimerism

PubMed Central

Calvanese, Vincenzo; Mallya, Meera; Campbell, R Duncan; Aguado, Begoña

2008-01-01

Background Regulation of the expression of particular genes can rely on mechanisms that are different from classical transcriptional and translational control. The LY6G5B and LY6G6D genes encode LY-6 domain proteins, whose expression seems to be regulated in an original fashion, consisting of an intron retention event which generates, through an early premature stop codon, a non-coding transcript, preventing expression in most cell lines and tissues. Results The MHC LY-6 non-coding transcripts have shown to be stable and very abundant in the cell, and not subject to Nonsense Mediated Decay (NMD). This retention event appears not to be solely dependent on intron features, because in the case of LY6G5B, when the intron is inserted in the artificial context of a luciferase expression plasmid, it is fully spliced but strongly stabilises the resulting luciferase transcript. In addition, by quantitative PCR we found that the retained and spliced forms are differentially expressed in tissues indicating an active regulation of the non-coding transcript. EST database analysis revealed that these genes have an alternative expression pathway with the formation of Transcription Induced Chimeras (TIC). This data was confirmed by RT-PCR, revealing the presence of different transcripts that would encode the chimeric proteins CSNKβ-LY6G5B and G6F-LY6G6D, in which the LY-6 domain would join to a kinase domain and an Ig-like domain, respectively. Conclusion In conclusion, the LY6G5B and LY6G6D intron-retained transcripts are not subjected to NMD and are more abundant than the properly spliced forms. In addition, these genes form chimeric transcripts with their neighbouring same orientation 5' genes. Of interest is the fact that the 5' genes (CSNKβ or G6F) undergo differential splicing only in the context of the chimera (CSNKβ-LY6G5B or G6F-LY6G6C) and not on their own. PMID:18817541

Real-time PCR based on SYBR-Green I fluorescence: an alternative to the TaqMan assay for a relative quantification of gene rearrangements, gene amplifications and micro gene deletions.

PubMed

Ponchel, Frederique; Toomes, Carmel; Bransfield, Kieran; Leong, Fong T; Douglas, Susan H; Field, Sarah L; Bell, Sandra M; Combaret, Valerie; Puisieux, Alain; Mighell, Alan J; Robinson, Philip A; Inglehearn, Chris F; Isaacs, John D; Markham, Alex F

2003-10-13

Real-time PCR is increasingly being adopted for RNA quantification and genetic analysis. At present the most popular real-time PCR assay is based on the hybridisation of a dual-labelled probe to the PCR product, and the development of a signal by loss of fluorescence quenching as PCR degrades the probe. Though this so-called 'TaqMan' approach has proved easy to optimise in practice, the dual-labelled probes are relatively expensive. We have designed a new assay based on SYBR-Green I binding that is quick, reliable, easily optimised and compares well with the published assay. Here we demonstrate its general applicability by measuring copy number in three different genetic contexts; the quantification of a gene rearrangement (T-cell receptor excision circles (TREC) in peripheral blood mononuclear cells); the detection and quantification of GLI, MYC-C and MYC-N gene amplification in cell lines and cancer biopsies; and detection of deletions in the OPA1 gene in dominant optic atrophy. Our assay has important clinical applications, providing accurate diagnostic results in less time, from less biopsy material and at less cost than assays currently employed such as FISH or Southern blotting.

Histone deacetylases regulate multicellular development in the social amoeba Dictyostelium discoideum.

PubMed

Sawarkar, Ritwick; Visweswariah, Sandhya S; Nellen, Wolfgang; Nanjundiah, Vidyanand

2009-09-04

Epigenetic modifications of histones regulate gene expression and lead to the establishment and maintenance of cellular phenotypes during development. Histone acetylation depends on a balance between the activities of histone acetyltransferases and histone deacetylases (HDACs) and influences transcriptional regulation. In this study, we analyse the roles of HDACs during growth and development of one of the cellular slime moulds, the social amoeba Dictyostelium discoideum. The inhibition of HDAC activity by trichostatin A results in histone hyperacetylation and a delay in cell aggregation and differentiation. Cyclic AMP oscillations are normal in starved amoebae treated with trichostatin A but the expression of a subset of cAMP-regulated genes is delayed. Bioinformatic analysis indicates that there are four genes encoding putative HDACs in D. discoideum. Using biochemical, genetic and developmental approaches, we demonstrate that one of these four genes, hdaB, is dispensable for growth and development under laboratory conditions. A knockout of the hdaB gene results in a social context-dependent phenotype: hdaB(-) cells develop normally but sporulate less efficiently than the wild type in chimeras. We infer that HDAC activity is important for regulating the timing of gene expression during the development of D. discoideum and for defining aspects of the phenotype that mediate social behaviour in genetically heterogeneous groups.

A high-resolution network model for global gene regulation in Mycobacterium tuberculosis

PubMed Central

Peterson, Eliza J.R.; Reiss, David J.; Turkarslan, Serdar; Minch, Kyle J.; Rustad, Tige; Plaisier, Christopher L.; Longabaugh, William J.R.; Sherman, David R.; Baliga, Nitin S.

2014-01-01

The resilience of Mycobacterium tuberculosis (MTB) is largely due to its ability to effectively counteract and even take advantage of the hostile environments of a host. In order to accelerate the discovery and characterization of these adaptive mechanisms, we have mined a compendium of 2325 publicly available transcriptome profiles of MTB to decipher a predictive, systems-scale gene regulatory network model. The resulting modular organization of 98% of all MTB genes within this regulatory network was rigorously tested using two independently generated datasets: a genome-wide map of 7248 DNA-binding locations for 143 transcription factors (TFs) and global transcriptional consequences of overexpressing 206 TFs. This analysis has discovered specific TFs that mediate conditional co-regulation of genes within 240 modules across 14 distinct environmental contexts. In addition to recapitulating previously characterized regulons, we discovered 454 novel mechanisms for gene regulation during stress, cholesterol utilization and dormancy. Significantly, 183 of these mechanisms act uniquely under conditions experienced during the infection cycle to regulate diverse functions including 23 genes that are essential to host-pathogen interactions. These and other insights underscore the power of a rational, model-driven approach to unearth novel MTB biology that operates under some but not all phases of infection. PMID:25232098

Phenotypic and Genotypic Analysis of Antimicrobial Resistance among Listeria monocytogenes Isolated from Australian Food Production Chains

PubMed Central

Wilson, Annaleise; Gray, Jessica; Chandry, P. Scott; Fox, Edward M.

2018-01-01

The current global crisis of antimicrobial resistance (AMR) among important human bacterial pathogens has been amplified by an increased resistance prevalence. In recent years, a number of studies have reported higher resistance levels among Listeria monocytogenes isolates, which may have implications for treatment of listeriosis infection where resistance to key treatment antimicrobials is noted. This study examined the genotypic and phenotypic AMR patterns of 100 L. monocytogenes isolates originating from food production supplies in Australia and examined this in the context of global population trends. Low levels of resistance were noted to ciprofloxacin (2%) and erythromycin (1%); however, no resistance was observed to penicillin G or tetracycline. Resistance to ciprofloxacin was associated with a mutation in the fepR gene in one isolate; however, no genetic basis for resistance in the other isolate was identified. Resistance to erythromycin was correlated with the presence of the ermB resistance gene. Both resistant isolates belonged to clonal complex 1 (CC1), and analysis of these in the context of global CC1 isolates suggested that they were more similar to isolates from India rather than the other CC1 isolates included in this study. This study provides baseline AMR data for L. monocytogenes isolated in Australia, identifies key genetic markers underlying this resistance, and highlights the need for global molecular surveillance of resistance patterns to maintain control over the potential dissemination of AMR isolates. PMID:29425131

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

PubMed Central

Frech, Christian; Chen, Nansheng

2011-01-01

Genes underlying important phenotypic differences between Plasmodium species, the causative agents of malaria, are frequently found in only a subset of species and cluster at dynamically evolving subtelomeric regions of chromosomes. We hypothesized that chromosome-internal regions of Plasmodium genomes harbour additional species subset-specific genes that underlie differences in human pathogenicity, human-to-human transmissibility, and human virulence. We combined sequence similarity searches with synteny block analyses to identify species subset-specific genes in chromosome-internal regions of six published Plasmodium genomes, including Plasmodium falciparum, Plasmodium vivax, Plasmodium knowlesi, Plasmodium yoelii, Plasmodium berghei, and Plasmodium chabaudi. To improve comparative analysis, we first revised incorrectly annotated gene models using homology-based gene finders and examined putative subset-specific genes within syntenic contexts. Confirmed subset-specific genes were then analyzed for their role in biological pathways and examined for molecular functions using publicly available databases. We identified 16 genes that are well conserved in the three primate parasites but not found in rodent parasites, including three key enzymes of the thiamine (vitamin B1) biosynthesis pathway. Thirteen genes were found to be present in both human parasites but absent in the monkey parasite P. knowlesi, including genes specifically upregulated in sporozoites or gametocytes that could be linked to parasite transmission success between humans. Furthermore, we propose 15 chromosome-internal P. falciparum-specific genes as new candidate genes underlying increased human virulence and detected a currently uncharacterized cluster of P. vivax-specific genes on chromosome 6 likely involved in erythrocyte invasion. In conclusion, Plasmodium species harbour many chromosome-internal differences in the form of protein-coding genes, some of which are potentially linked to human disease and thus promising leads for future laboratory research. PMID:22215999

Insight into Energy Conservation via Alternative Carbon Monoxide Metabolism in Carboxydothermus pertinax Revealed by Comparative Genome Analysis.

PubMed

Fukuyama, Yuto; Omae, Kimiho; Yoneda, Yasuko; Yoshida, Takashi; Sako, Yoshihiko

2018-05-04

Carboxydothermus species are some of the most studied thermophilic carboxydotrophs. Their varied carboxydotrophic growth properties suggest distinct strategies for energy conservation via CO metabolism. In this study, we used comparative genome analysis of the genus Carboxydothermus to show variations in the CO dehydrogenase/energy-converting hydrogenase gene cluster, which is responsible for CO metabolism with H 2 production (hydrogenogenic CO metabolism). Indeed, ability or inability to produce H 2 with CO oxidation is explained by the presence or absence of this gene cluster in C. hydrogenoformans , C. islandicus , and C. ferrireducens Interestingly, despite its hydrogenogenic CO metabolism, C. pertinax lacks the Ni-CO dehydrogenase catalytic subunit (CooS-I) and its transcriptional regulator encoding genes in this gene cluster probably due to inversion. Transcriptional analysis in C. pertinax showed that the Ni-CO dehydrogenase gene ( cooS-II ) and distantly encoded energy-converting hydrogenase related genes were remarkably upregulated under 100% CO. In addition, when thiosulfate was available as a terminal electron acceptor under 100% CO, C. pertinax maximum cell density and maximum specific growth rate were 3.1-fold and 1.5-fold higher, respectively, than when thiosulfate was absent. The amount of H 2 produced was only 63% of the consumed CO, less than expected according to hydrogenogenic CO oxidation: CO + H 2 O → CO 2 + H 2 Accordingly, C. pertinax would couple CO oxidation by Ni-CO dehydrogenase-II with simultaneous reduction of not only H 2 O but thiosulfate when grown under 100% CO. IMPORTANCE Anaerobic hydrogenogenic carboxydotrophs are thought to fill a vital niche with scavenging potentially toxic CO and producing H 2 as available energy source for thermophilic microbes. This hydrogenogenic carboxydotrophy relies on a Ni-CO dehydrogenase/energy-converting hydrogenase gene cluster. This feature is thought to be as common to these organisms. However, hydrogenogenic carboxydotroph, Carboxydothermus pertinax lacks the gene for the Ni-CO dehydrogenase catalytic subunit encoded in the gene cluster. Here, we performed a comparative genome analysis of the genus Carboxydothermus , transcriptional analysis, and cultivation study under 100% CO to prove their hydrogenogenic CO metabolism. Results revealed that C. pertinax could couple Ni-CO dehydrogenase-II alternatively to the distal energy-converting hydrogenase. Furthermore, C. pertinax represents an example of the functioning of Ni-CO dehydrogenase which does not always correspond with its genomic context owing to the versatility of CO metabolism and the low redox potential of CO. Copyright © 2018 American Society for Microbiology.

Unraveling the Specific Ischemic Core and Penumbra Transcriptome in the Permanent Middle Cerebral Artery Occlusion Mouse Model Brain Treated with the Neuropeptide PACAP38

PubMed Central

Hori, Motohide; Nakamachi, Tomoya; Shibato, Junko; Rakwal, Randeep; Shioda, Seiji; Numazawa, Satoshi

2015-01-01

Our group has been systematically investigating the effects of the neuropeptide pituitary adenylate-cyclase activating polypeptide (PACAP) on the ischemic brain. To do so, we have established and utilized the permanent middle cerebral artery occlusion (PMCAO) mouse model, in which PACAP38 (1 pmol) injection is given intracerebroventrically and compared to a control saline (0.9% sodium chloride, NaCl) injection, to unravel genome-wide gene expression changes using a high-throughput DNA microarray analysis approach. In our previous studies, we have accumulated a large volume of data (gene inventory) from the whole brain (ipsilateral and contralateral hemispheres) after both PMCAO and post-PACAP38 injection. In our latest research, we have targeted specifically infarct or ischemic core (hereafter abbreviated IC) and penumbra (hereafter abbreviated P) post-PACAP38 injections in order to re-examine the transcriptome at 6 and 24 h post injection. The current study aims to delineate the specificity of expression and localization of differentially expressed molecular factors influenced by PACAP38 in the IC and P regions. Utilizing the mouse 4 × 44 K whole genome DNA chip we show numerous changes (≧/≦ 1.5/0.75-fold) at both 6 h (654 and 456, and 522 and 449 up- and down-regulated genes for IC and P, respectively) and 24 h (2568 and 2684, and 1947 and 1592 up- and down-regulated genes for IC and P, respectively) after PACAP38 treatment. Among the gene inventories obtained here, two genes, brain-derived neurotrophic factor (Bdnf) and transthyretin (Ttr) were found to be induced by PACAP38 treatment, which we had not been able to identify previously using the whole hemisphere transcriptome analysis. Using bioinformatics analysis by pathway- or specific-disease-state focused gene classifications and Ingenuity Pathway Analysis (IPA) the differentially expressed genes are functionally classified and discussed. Among these, we specifically discuss some novel and previously identified genes, such as alpha hemoglobin stabilizing protein (Ahsp), cathelicidin antimicrobial peptide (Camp), chemokines, interferon beta 1 (Ifnb1), and interleukin 6 (Il6) in context of PACAP38-mediated neuroprotection in the ischemic brain. Taken together, the DNA microarray analysis provides not only a great resource for further study, but also reinforces the importance of region-specific analyses in genome-wide identification of target molecular factors that might play a role in the neuroprotective function of PACAP38. PMID:27600210

Genome-wide effects of MELK-inhibitor in triple-negative breast cancer cells indicate context-dependent response with p53 as a key determinant

PubMed Central

Simon, Marisa; Mesmar, Fahmi; Helguero, Luisa

2017-01-01

Triple-negative breast cancer (TNBC) is an aggressive, highly recurrent breast cancer subtype, affecting approximately one-fifth of all breast cancer patients. Subpopulations of treatment-resistant cancer stem cells within the tumors are considered to contribute to disease recurrence. A potential druggable target for such cells is the maternal embryonic leucine-zipper kinase (MELK). MELK expression is upregulated in mammary stem cells and in undifferentiated cancers, where it correlates with poor prognosis and potentially mediates treatment resistance. Several MELK inhibitors have been developed, of which one, OTSSP167, is currently in clinical trials. In order to better understand how MELK and its inhibition influence TNBC, we verified its anti-proliferative and apoptotic effects in claudin-low TNBC cell lines MDA-MB-231 and SUM-159 using MTS assays and/or trypan blue viability assays together with analysis of PARP cleavage. Then, using microarrays, we explored which genes were affected by OTSSP167. We demonstrate that different sets of genes are regulated in MDA-MB-231 and SUM-159, but in both cell lines genes involved in cell cycle, mitosis and protein metabolism and folding were regulated. We identified p53 (TP53) as a potential upstream regulator of the regulated genes. Using western blot we found that OTSSP167 downregulates mutant p53 in all tested TNBC cell lines (MDA-MB-231, SUM-159, and BT-549), but upregulates wild-type p53 in the luminal A subtype MCF-7 cell line. We propose that OTSSP167 might have context-dependent or off-target effects, but that one consistent mechanism of action could involve the destabilization of mutant p53. PMID:28235006

High-Throughput Screening Using iPSC-Derived Neuronal Progenitors to Identify Compounds Counteracting Epigenetic Gene Silencing in Fragile X Syndrome.

PubMed

Kaufmann, Markus; Schuffenhauer, Ansgar; Fruh, Isabelle; Klein, Jessica; Thiemeyer, Anke; Rigo, Pierre; Gomez-Mancilla, Baltazar; Heidinger-Millot, Valerie; Bouwmeester, Tewis; Schopfer, Ulrich; Mueller, Matthias; Fodor, Barna D; Cobos-Correa, Amanda

2015-10-01

Fragile X syndrome (FXS) is the most common form of inherited mental retardation, and it is caused in most of cases by epigenetic silencing of the Fmr1 gene. Today, no specific therapy exists for FXS, and current treatments are only directed to improve behavioral symptoms. Neuronal progenitors derived from FXS patient induced pluripotent stem cells (iPSCs) represent a unique model to study the disease and develop assays for large-scale drug discovery screens since they conserve the Fmr1 gene silenced within the disease context. We have established a high-content imaging assay to run a large-scale phenotypic screen aimed to identify compounds that reactivate the silenced Fmr1 gene. A set of 50,000 compounds was tested, including modulators of several epigenetic targets. We describe an integrated drug discovery model comprising iPSC generation, culture scale-up, and quality control and screening with a very sensitive high-content imaging assay assisted by single-cell image analysis and multiparametric data analysis based on machine learning algorithms. The screening identified several compounds that induced a weak expression of fragile X mental retardation protein (FMRP) and thus sets the basis for further large-scale screens to find candidate drugs or targets tackling the underlying mechanism of FXS with potential for therapeutic intervention. © 2015 Society for Laboratory Automation and Screening.

The significance of alternative transcripts for Caenorhabditis elegans transcription factor genes, based on expression pattern analysis

PubMed Central

2013-01-01

Background Sequence-specific DNA-binding proteins, with their paramount importance in the regulation of expression of the genetic material, are encoded by approximately 5% of the genes in an animal’s genome. But it is unclear to what extent alternative transcripts from these genes may further increase the complexity of the transcription factor complement. Results Of the 938 potential C. elegans transcription factor genes, 197 were annotated in WormBase as encoding at least two distinct isoforms. Evaluation of prior evidence identified, with different levels of confidence, 50 genes with alternative transcript starts, 23 with alternative transcript ends, 35 with alternative splicing and 34 with alternative transcripts generated by a combination of mechanisms, leaving 55 that were discounted. Expression patterns were determined for transcripts for a sample of 29 transcription factor genes, concentrating on those with alternative transcript starts for which the evidence was strongest. Seamless fosmid recombineering was used to generate reporter gene fusions with minimal modification to assay expression of specific transcripts while maintaining the broad genomic DNA context and alternative transcript production. Alternative transcription factor gene transcripts were typically expressed with identical or substantially overlapping distributions rather than in distinct domains. Conclusions Increasingly sensitive sequencing technologies will reveal rare transcripts but many of these are clearly non-productive. The majority of the transcription factor gene alternative transcripts that are productive may represent tolerable noise rather than encoding functionally distinct isoforms. PMID:23586691

geneCommittee: a web-based tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification.

PubMed

Reboiro-Jato, Miguel; Arrais, Joel P; Oliveira, José Luis; Fdez-Riverola, Florentino

2014-01-30

The diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools. geneCommittee is a web-based interactive tool for routinely evaluating the discriminative classification power of custom hypothesis in the form of biologically relevant gene sets. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. Provided with a straightforward and intuitive interface, geneCommittee is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research. geneCommittee allows the enrichment of microarrays raw data with gene functional annotations, producing integrated datasets that simplify the construction of better discriminative hypothesis, and allows the creation of a set of complementary classifiers. The trained committees can then be used for clinical research and diagnosis. Full documentation including common use cases and guided analysis workflows is freely available at http://sing.ei.uvigo.es/GC/.

Targeted Changes of the Cell Wall Proteome Influence Candida albicans Ability to Form Single- and Multi-strain Biofilms

PubMed Central

Walker, Louise A.; Martin-Yken, Hélène; Dague, Etienne; Legrand, Mélanie; Lee, Keunsook; Chauvel, Murielle; Firon, Arnaud; Rossignol, Tristan; Richard, Mathias L.; Munro, Carol A.; Bachellier-Bassi, Sophie; d'Enfert, Christophe

2014-01-01

Biofilm formation is an important virulence trait of the pathogenic yeast Candida albicans. We have combined gene overexpression, strain barcoding and microarray profiling to screen a library of 531 C. albicans conditional overexpression strains (∼10% of the genome) for genes affecting biofilm development in mixed-population experiments. The overexpression of 16 genes increased strain occupancy within a multi-strain biofilm, whereas overexpression of 4 genes decreased it. The set of 16 genes was significantly enriched for those encoding predicted glycosylphosphatidylinositol (GPI)-modified proteins, namely Ihd1/Pga36, Phr2, Pga15, Pga19, Pga22, Pga32, Pga37, Pga42 and Pga59; eight of which have been classified as pathogen-specific. Validation experiments using either individually- or competitively-grown overexpression strains revealed that the contribution of these genes to biofilm formation was variable and stage-specific. Deeper functional analysis of PGA59 and PGA22 at a single-cell resolution using atomic force microscopy showed that overexpression of either gene increased C. albicans ability to adhere to an abiotic substrate. However, unlike PGA59, PGA22 overexpression led to cell cluster formation that resulted in increased sensitivity to shear forces and decreased ability to form a single-strain biofilm. Within the multi-strain environment provided by the PGA22-non overexpressing cells, PGA22-overexpressing cells were protected from shear forces and fitter for biofilm development. Ultrastructural analysis, genome-wide transcript profiling and phenotypic analyses in a heterologous context suggested that PGA22 affects cell adherence through alteration of cell wall structure and/or function. Taken together, our findings reveal that several novel predicted GPI-modified proteins contribute to the cooperative behaviour between biofilm cells and are important participants during C. albicans biofilm formation. Moreover, they illustrate the power of using signature tagging in conjunction with gene overexpression for the identification of novel genes involved in processes pertaining to C. albicans virulence. PMID:25502890

Microarray profiling of human white adipose tissue after exogenous leptin injection.

PubMed

Taleb, S; Van Haaften, R; Henegar, C; Hukshorn, C; Cancello, R; Pelloux, V; Hanczar, B; Viguerie, N; Langin, D; Evelo, C; Zucker, J; Clément, K; Saris, W H M

2006-03-01

Leptin is a secreted adipocyte hormone that plays a key role in the regulation of body weight homeostasis. The leptin effect on human white adipose tissue (WAT) is still debated. The aim of this study was to assess whether the administration of polyethylene glycol-leptin (PEG-OB) in a single supraphysiological dose has transcriptional effects on genes of WAT and to identify its target genes and functional pathways in WAT. Blood samples and WAT biopsies were obtained from 10 healthy nonobese men before treatment and 72 h after the PEG-OB injection, leading to an approximate 809-fold increase in circulating leptin. The WAT gene expression profile before and after the PEG-OB injection was compared using pangenomic microarrays. Functional gene annotations based on the gene ontology of the PEG-OB regulated genes were performed using both an 'in house' automated procedure and GenMAPP (Gene Microarray Pathway Profiler), designed for viewing and analyzing gene expression data in the context of biological pathways. Statistical analysis of microarray data revealed that PEG-OB had a major down-regulated effect on WAT gene expression, as we obtained 1,822 and 100 down- and up-regulated genes, respectively. Microarray data were validated using reverse transcription quantitative PCR. Functional gene annotations of PEG-OB regulated genes revealed that the functional class related to immunity and inflammation was among the most mobilized PEG-OB pathway in WAT. These genes are mainly expressed in the cell of the stroma vascular fraction in comparison with adipocytes. Our observations support the hypothesis that leptin could act on WAT, particularly on genes related to inflammation and immunity, which may suggest a novel leptin target pathway in human WAT.

GSA-PCA: gene set generation by principal component analysis of the Laplacian matrix of a metabolic network

PubMed Central

2012-01-01

Background Gene Set Analysis (GSA) has proven to be a useful approach to microarray analysis. However, most of the method development for GSA has focused on the statistical tests to be used rather than on the generation of sets that will be tested. Existing methods of set generation are often overly simplistic. The creation of sets from individual pathways (in isolation) is a poor reflection of the complexity of the underlying metabolic network. We have developed a novel approach to set generation via the use of Principal Component Analysis of the Laplacian matrix of a metabolic network. We have analysed a relatively simple data set to show the difference in results between our method and the current state-of-the-art pathway-based sets. Results The sets generated with this method are semi-exhaustive and capture much of the topological complexity of the metabolic network. The semi-exhaustive nature of this method has also allowed us to design a hypergeometric enrichment test to determine which genes are likely responsible for set significance. We show that our method finds significant aspects of biology that would be missed (i.e. false negatives) and addresses the false positive rates found with the use of simple pathway-based sets. Conclusions The set generation step for GSA is often neglected but is a crucial part of the analysis as it defines the full context for the analysis. As such, set generation methods should be robust and yield as complete a representation of the extant biological knowledge as possible. The method reported here achieves this goal and is demonstrably superior to previous set analysis methods. PMID:22876834

Differential susceptibility to plasticity: a 'missing link' between gene-culture co-evolution and neuropsychiatric spectrum disorders?

PubMed Central

2012-01-01

Brüne's proposal that erstwhile 'vulnerability' genes need to be reconsidered as 'plasticity' genes, given the potential for certain environments to yield increased positive function in the same domain as potential dysfunction, has implications for psychiatric nosology as well as a more dynamic understanding of the relationship between genes and culture. In addition to validating neuropsychiatric spectrum disorder nosologies by calling for similar methodological shifts in gene-environment-interaction studies, Brüne's position elevates the importance of environmental contexts - inclusive of socio-cultural variables - as mechanisms that contribute to clinical presentation. We assert that when models of susceptibility to plasticity and neuropsychiatric spectrum disorders are concomitantly considered, a new line of inquiry emerges into the co-evolution and co-determination of socio-cultural contexts and endophenotypes. This presents potentially unique opportunities, benefits, challenges, and responsibilities for research and practice in psychiatry. Please see related manuscript: http://www.biomedcentral.com/1741-7015/10/38 PMID:22510307

Differential susceptibility to plasticity: a 'missing link' between gene-culture co-evolution and neuropsychiatric spectrum disorders?

PubMed

Wurzman, Rachel; Giordano, James

2012-04-17

Brüne's proposal that erstwhile 'vulnerability' genes need to be reconsidered as 'plasticity' genes, given the potential for certain environments to yield increased positive function in the same domain as potential dysfunction, has implications for psychiatric nosology as well as a more dynamic understanding of the relationship between genes and culture. In addition to validating neuropsychiatric spectrum disorder nosologies by calling for similar methodological shifts in gene-environment-interaction studies, Brüne's position elevates the importance of environmental contexts - inclusive of socio-cultural variables - as mechanisms that contribute to clinical presentation. We assert that when models of susceptibility to plasticity and neuropsychiatric spectrum disorders are concomitantly considered, a new line of inquiry emerges into the co-evolution and co-determination of socio-cultural contexts and endophenotypes. This presents potentially unique opportunities, benefits, challenges, and responsibilities for research and practice in psychiatry. Please see related manuscript: http://www.biomedcentral.com/1741-7015/10/38.

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions

PubMed Central

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-01-01

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field. DOI: http://dx.doi.org/10.7554/eLife.08411.001 PMID:26609814

Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.

PubMed

Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A; Kardia, Sharon L R; Allison, Matthew; Diez Roux, Ana V

2016-11-01

There has been an increased interest in identifying gene-environment interaction (G × E) in the context of multiple environmental exposures. Most G × E studies analyze one exposure at a time, but we are exposed to multiple exposures in reality. Efficient analysis strategies for complex G × E with multiple environmental factors in a single model are still lacking. Using the data from the Multiethnic Study of Atherosclerosis, we illustrate a two-step approach for modeling G × E with multiple environmental factors. First, we utilize common clustering and classification strategies (e.g., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. Second, we illustrate the use of an additive main effects and multiplicative interaction model, instead of the conventional saturated interaction model using product terms of factors, to study G × E with the data-driven exposure subgroups defined in the first step. We demonstrate useful analytical approaches to translate multiple environmental exposures into one summary class. These tools not only allow researchers to consider several environmental exposures in G × E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead of examining effect modification for each exposure in isolation.

A novel de novo mutation in ATP1A3 and childhood-onset schizophrenia

PubMed Central

Smedemark-Margulies, Niklas; Brownstein, Catherine A.; Vargas, Sigella; Tembulkar, Sahil K.; Towne, Meghan C.; Shi, Jiahai; Gonzalez-Cuevas, Elisa; Liu, Kevin X.; Bilguvar, Kaya; Kleiman, Robin J.; Han, Min-Joon; Torres, Alcy; Berry, Gerard T.; Yu, Timothy W.; Beggs, Alan H.; Agrawal, Pankaj B.; Gonzalez-Heydrich, Joseph

2016-01-01

We describe a child with onset of command auditory hallucinations and behavioral regression at 6 yr of age in the context of longer standing selective mutism, aggression, and mild motor delays. His genetic evaluation included chromosomal microarray analysis and whole-exome sequencing. Sequencing revealed a previously unreported heterozygous de novo mutation c.385G>A in ATP1A3, predicted to result in a p.V129M amino acid change. This gene codes for a neuron-specific isoform of the catalytic α-subunit of the ATP-dependent transmembrane sodium–potassium pump. Heterozygous mutations in this gene have been reported as causing both sporadic and inherited forms of alternating hemiplegia of childhood and rapid-onset dystonia parkinsonism. We discuss the literature on phenotypes associated with known variants in ATP1A3, examine past functional studies of the role of ATP1A3 in neuronal function, and describe a novel clinical presentation associated with mutation of this gene. PMID:27626066

Functional characterization of CCR in birch (Betula platyphylla × Betula pendula) through overexpression and suppression analysis.

PubMed

Zhang, Wenbo; Wei, Rui; Chen, Su; Jiang, Jing; Li, Huiyu; Huang, Haijiao; Yang, Guang; Wang, Shuo; Wei, Hairong; Liu, Guifeng

2015-06-01

We cloned a Cinnamoyl-CoA Reductase gene (BpCCR1) from an apical meristem and first internode of Betula platyphylla and characterized its functions in lignin biosynthesis, wood formation and tree growth through transgenic approaches. We generated overexpression and suppression transgenic lines and analyzed them in comparison with the wild-type in terms of lignin content, anatomical characteristics, height and biomass. We found that BpCCR1 overexpression could increase lignin content up to 14.6%, and its underexpression decreased lignin content by 6.3%. Surprisingly, modification of BpCCR1 expression led to conspicuous changes in wood characteristics, including xylem vessel number and arrangement, and secondary wall thickness. The growth of transgenic trees in terms of height was also significantly influenced by the modification of BpCCR1 genes. We discuss the functions of BpCCR1 in the context of a phylogenetic tree built with CCR genes from multiple species. © 2014 Scandinavian Plant Physiology Society.

Neuronal inhibition of the autophagy nucleation complex extends life span in post-reproductive C. elegans

PubMed Central

Byrne, Jonathan; Medina, Rebeca; Kolundžić, Ena; Geisinger, Johannes; Hajduskova, Martina; Tursun, Baris; Richly, Holger

2017-01-01

Autophagy is a ubiquitous catabolic process that causes cellular bulk degradation of cytoplasmic components and is generally associated with positive effects on health and longevity. Inactivation of autophagy has been linked with detrimental effects on cells and organisms. The antagonistic pleiotropy theory postulates that some fitness-promoting genes during youth are harmful during aging. On this basis, we examined genes mediating post-reproductive longevity using an RNAi screen. From this screen, we identified 30 novel regulators of post-reproductive longevity, including pha-4. Through downstream analysis of pha-4, we identified that the inactivation of genes governing the early stages of autophagy up until the stage of vesicle nucleation, such as bec-1, strongly extend both life span and health span. Furthermore, our data demonstrate that the improvements in health and longevity are mediated through the neurons, resulting in reduced neurodegeneration and sarcopenia. We propose that autophagy switches from advantageous to harmful in the context of an age-associated dysfunction. PMID:28882853

Gene expression analysis of the ovary of hybrid females of Xenopus laevis and X. muelleri

PubMed Central

2008-01-01

Background Interspecific hybrids of frogs of the genus Xenopus result in sterile hybrid males and fertile hybrid females. Previous work has demonstrated a dramatic asymmetrical pattern of misexpression in hybrid males compared to the two parental species with relatively few genes misexpressed in comparisons of hybrids and the maternal species (X. laevis) and dramatically more genes misexpressed in hybrids compared to the paternal species (X. muelleri). In this work, we examine the gene expression pattern in hybrid females of X. laevis × X. muelleri to determine if this asymmetrical pattern of expression also occurs in hybrid females. Results We find a similar pattern of asymmetry in expression compared to males in that there were more genes differentially expressed between hybrids and X. muelleri compared to hybrids and X. laevis. We also found a dramatic increase in the number of misexpressed genes with hybrid females having about 20 times more genes misexpressed in ovaries compared to testes of hybrid males and therefore the match between phenotype and expression pattern is not supported. Conclusion We discuss these intriguing findings in the context of reproductive isolation and suggest that divergence in female expression may be involved in sterility of hybrid males due to the inherent sensitivity of spermatogenesis as defined by the faster male evolution hypothesis for Haldane's rule. PMID:18331635

Genetic adaptation of the antibacterial human innate immunity network.

PubMed

Casals, Ferran; Sikora, Martin; Laayouni, Hafid; Montanucci, Ludovica; Muntasell, Aura; Lazarus, Ross; Calafell, Francesc; Awadalla, Philip; Netea, Mihai G; Bertranpetit, Jaume

2011-07-11

Pathogens have represented an important selective force during the adaptation of modern human populations to changing social and other environmental conditions. The evolution of the immune system has therefore been influenced by these pressures. Genomic scans have revealed that immune system is one of the functions enriched with genes under adaptive selection. Here, we describe how the innate immune system has responded to these challenges, through the analysis of resequencing data for 132 innate immunity genes in two human populations. Results are interpreted in the context of the functional and interaction networks defined by these genes. Nucleotide diversity is lower in the adaptors and modulators functional classes, and is negatively correlated with the centrality of the proteins within the interaction network. We also produced a list of candidate genes under positive or balancing selection in each population detected by neutrality tests and showed that some functional classes are preferential targets for selection. We found evidence that the role of each gene in the network conditions the capacity to evolve or their evolvability: genes at the core of the network are more constrained, while adaptation mostly occurred at particular positions at the network edges. Interestingly, the functional classes containing most of the genes with signatures of balancing selection are involved in autoinflammatory and autoimmune diseases, suggesting a counterbalance between the beneficial and deleterious effects of the immune response.

Genetic adaptation of the antibacterial human innate immunity network

PubMed Central

2011-01-01

Background Pathogens have represented an important selective force during the adaptation of modern human populations to changing social and other environmental conditions. The evolution of the immune system has therefore been influenced by these pressures. Genomic scans have revealed that immune system is one of the functions enriched with genes under adaptive selection. Results Here, we describe how the innate immune system has responded to these challenges, through the analysis of resequencing data for 132 innate immunity genes in two human populations. Results are interpreted in the context of the functional and interaction networks defined by these genes. Nucleotide diversity is lower in the adaptors and modulators functional classes, and is negatively correlated with the centrality of the proteins within the interaction network. We also produced a list of candidate genes under positive or balancing selection in each population detected by neutrality tests and showed that some functional classes are preferential targets for selection. Conclusions We found evidence that the role of each gene in the network conditions the capacity to evolve or their evolvability: genes at the core of the network are more constrained, while adaptation mostly occurred at particular positions at the network edges. Interestingly, the functional classes containing most of the genes with signatures of balancing selection are involved in autoinflammatory and autoimmune diseases, suggesting a counterbalance between the beneficial and deleterious effects of the immune response. PMID:21745391

Transcriptional Enhancers Induce Insertional Gene Deregulation Independently From the Vector Type and Design

PubMed Central

Maruggi, Giulietta; Porcellini, Simona; Facchini, Giulia; Perna, Serena K; Cattoglio, Claudia; Sartori, Daniela; Ambrosi, Alessandro; Schambach, Axel; Baum, Christopher; Bonini, Chiara; Bovolenta, Chiara; Mavilio, Fulvio; Recchia, Alessandra

2009-01-01

The integration characteristics of retroviral (RV) vectors increase the probability of interfering with the regulation of cellular genes, and account for a tangible risk of insertional mutagenesis in treated patients. To assess the potential genotoxic risk of conventional or self-inactivating (SIN) γ-RV and lentiviral (LV) vectors independently from the biological consequences of the insertion event, we developed a quantitative assay based on real-time reverse transcriptase—PCR on low-density arrays to evaluate alterations of gene expression in individual primary T-cell clones. We show that the Moloney leukemia virus long terminal repeat (LTR) enhancer has the strongest activity in both a γ-RV and a LV vector context, while an internal cellular promoter induces deregulation of gene expression less frequently, at a shorter range and to a lower extent in both vector types. Downregulation of gene expression was observed only in the context of LV vectors. This study indicates that insertional gene activation is determined by the characteristics of the transcriptional regulatory elements carried by the vector, and is largely independent from the vector type or design. PMID:19293778

Higher order genomic organization and regulatory compartmentalization for cell cycle control at the G1/S-phase transition.

PubMed

Ghule, Prachi N; Seward, David J; Fritz, Andrew J; Boyd, Joseph R; van Wijnen, Andre J; Lian, Jane B; Stein, Janet L; Stein, Gary S

2018-05-10

Fidelity of histone gene regulation, and ultimately of histone protein biosynthesis, is obligatory for packaging of newly replicated DNA into chromatin. Control of histone gene expression within the 3-dimensional context of nuclear organization is reflected by two well documented observations. DNA replication-dependent histone mRNAs are synthesized at specialized subnuclear domains designated histone locus bodies (HLBs), in response to activation of the growth factor dependent Cyclin E/CDK2/HINFP/NPAT pathway at the G1/S transition in mammalian cells. Complete loss of the histone gene regulatory factors HINFP or NPAT disrupts HLB integrity that is necessary for coordinate control of DNA replication and histone gene transcription. Here we review the molecular histone-related requirements for G1/S-phase progression during the cell cycle. Recently developed experimental strategies, now enable us to explore mechanisms involved in dynamic control of histone gene expression in the context of the temporal (cell cycle) and spatial (HLBs) remodeling of the histone gene loci. © 2018 Wiley Periodicals, Inc.

Information-dependent enrichment analysis reveals time-dependent transcriptional regulation of the estrogen pathway of toxicity.

PubMed

Pendse, Salil N; Maertens, Alexandra; Rosenberg, Michael; Roy, Dipanwita; Fasani, Rick A; Vantangoli, Marguerite M; Madnick, Samantha J; Boekelheide, Kim; Fornace, Albert J; Odwin, Shelly-Ann; Yager, James D; Hartung, Thomas; Andersen, Melvin E; McMullen, Patrick D

2017-04-01

The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts. Traditionally, transcription factor identification is achieved via chromatin immunoprecipitation studies and summarized by calculating which transcription factors are statistically associated with up- and downregulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be as useful for determining transcription factor associations. To move away from an arbitrary statistical or fold-change-based cutoff, we developed, in the context of the Mapping the Human Toxome project, an enrichment paradigm called information-dependent enrichment analysis (IDEA) to guide identification of the transcription factor network. We used a test case of activation in MCF-7 cells by 17β estradiol (E2). Using this new approach, we established a time course for transcriptional and functional responses to E2. ERα and ERβ were associated with short-term transcriptional changes in response to E2. Sustained exposure led to recruitment of additional transcription factors and alteration of cell cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose. E2F7, E2F1, and Foxm1, which are involved in cell proliferation, were enriched only at 24 h. IDEA should be useful for identifying candidate pathways of toxicity. IDEA outperforms gene set enrichment analysis (GSEA) and provides similar results to weighted gene correlation network analysis, a platform that helps to identify genes not annotated to pathways.

Transcriptional analysis of late ripening stages of grapevine berry

PubMed Central

2011-01-01

Background The composition of grapevine berry at harvest is a major determinant of wine quality. Optimal oenological maturity of berries is characterized by a high sugar/acidity ratio, high anthocyanin content in the skin, and low astringency. However, harvest time is still mostly determined empirically, based on crude biochemical composition and berry tasting. In this context, it is interesting to identify genes that are expressed/repressed specifically at the late stages of ripening and which may be used as indicators of maturity. Results Whole bunches and berries sorted by density were collected in vineyard on Chardonnay (white cultivar) grapevines for two consecutive years at three stages of ripening (7-days before harvest (TH-7), harvest (TH), and 10-days after harvest (TH+10)). Microvinification and sensory analysis indicate that the quality of the wines made from the whole bunches collected at TH-7, TH and TH+10 differed, TH providing the highest quality wines. In parallel, gene expression was studied with Qiagen/Operon microarrays using two types of samples, i.e. whole bunches and berries sorted by density. Only 12 genes were consistently up- or down-regulated in whole bunches and density sorted berries for the two years studied in Chardonnay. 52 genes were differentially expressed between the TH-7 and TH samples. In order to determine whether these genes followed a similar pattern of expression during the late stages of berry ripening in a red cultivar, nine genes were selected for RT-PCR analysis with Cabernet Sauvignon grown under two different temperature regimes affecting the precocity of ripening. The expression profiles and their relationship to ripening were confirmed in Cabernet Sauvignon for seven genes, encoding a carotenoid cleavage dioxygenase, a galactinol synthase, a late embryogenesis abundant protein, a dirigent-like protein, a histidine kinase receptor, a valencene synthase and a putative S-adenosyl-L-methionine:salicylic acid carboxyl methyltransferase. Conclusions This set of up- and down-regulated genes characterize the late stages of berry ripening in the two cultivars studied, and are indirectly linked to wine quality. They might be used directly or indirectly to design immunological, biochemical or molecular tools aimed at the determination of optimal ripening in these cultivars. PMID:22098939

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.

Genome-wide expression profiling of in vivo-derived bloodstream parasite stages and dynamic analysis of mRNA alterations during synchronous differentiation in Trypanosoma brucei

PubMed Central

Kabani, Sarah; Fenn, Katelyn; Ross, Alan; Ivens, Al; Smith, Terry K; Ghazal, Peter; Matthews, Keith

2009-01-01

Background Trypanosomes undergo extensive developmental changes during their complex life cycle. Crucial among these is the transition between slender and stumpy bloodstream forms and, thereafter, the differentiation from stumpy to tsetse-midgut procyclic forms. These developmental events are highly regulated, temporally reproducible and accompanied by expression changes mediated almost exclusively at the post-transcriptional level. Results In this study we have examined, by whole-genome microarray analysis, the mRNA abundance of genes in slender and stumpy forms of T.brucei AnTat1.1 cells, and also during their synchronous differentiation to procyclic forms. In total, five biological replicates representing the differentiation of matched parasite populations derived from five individual mouse infections were assayed, with RNAs being derived at key biological time points during the time course of their synchronous differentiation to procyclic forms. Importantly, the biological context of these mRNA profiles was established by assaying the coincident cellular events in each population (surface antigen exchange, morphological restructuring, cell cycle re-entry), thereby linking the observed gene expression changes to the well-established framework of trypanosome differentiation. Conclusion Using stringent statistical analysis and validation of the derived profiles against experimentally-predicted gene expression and phenotypic changes, we have established the profile of regulated gene expression during these important life-cycle transitions. The highly synchronous nature of differentiation between stumpy and procyclic forms also means that these studies of mRNA profiles are directly relevant to the changes in mRNA abundance within individual cells during this well-characterised developmental transition. PMID:19747379

Heterogeneous Genetic Background of the Association of Pheochromocytoma/Paraganglioma and Pituitary Adenoma: Results From a Large Patient Cohort

PubMed Central

Dénes, Judit; Swords, Francesca; Rattenberry, Eleanor; Stals, Karen; Owens, Martina; Cranston, Treena; Xekouki, Paraskevi; Moran, Linda; Kumar, Ajith; Wassif, Christopher; Fersht, Naomi; Baldeweg, Stephanie E.; Morris, Damian; Lightman, Stafford; Agha, Amar; Rees, Aled; Grieve, Joan; Powell, Michael; Boguszewski, Cesar Luiz; Dutta, Pinaki; Thakker, Rajesh V.; Srirangalingam, Umasuthan; Thompson, Chris J.; Druce, Maralyn; Higham, Claire; Davis, Julian; Eeles, Rosalind; Stevenson, Mark; O'Sullivan, Brendan; Taniere, Phillipe; Skordilis, Kassiani; Gabrovska, Plamena; Barlier, Anne; Webb, Susan M.; Aulinas, Anna; Drake, William M.; Bevan, John S.; Preda, Cristina; Dalantaeva, Nadezhda; Ribeiro-Oliveira, Antônio; Garcia, Isabel Tena; Yordanova, Galina; Iotova, Violeta; Evanson, Jane; Grossman, Ashley B.; Trouillas, Jacqueline; Ellard, Sian; Stratakis, Constantine A.; Maher, Eamonn R.; Roncaroli, Federico

2015-01-01

Context: Pituitary adenomas and pheochromocytomas/paragangliomas (pheo/PGL) can occur in the same patient or in the same family. Coexistence of the two diseases could be due to either a common pathogenic mechanism or a coincidence. Objective: The objective of the investigation was to study the possible coexistence of pituitary adenoma and pheo/PGL. Design: Thirty-nine cases of sporadic or familial pheo/PGL and pituitary adenomas were investigated. Known pheo/PGL genes (SDHA-D, SDHAF2, RET, VHL, TMEM127, MAX, FH) and pituitary adenoma genes (MEN1, AIP, CDKN1B) were sequenced using next generation or Sanger sequencing. Loss of heterozygosity study and pathological studies were performed on the available tumor samples. Setting: The study was conducted at university hospitals. Patients: Thirty-nine patients with sporadic of familial pituitary adenoma and pheo/PGL participated in the study. Outcome: Outcomes included genetic screening and clinical characteristics. Results: Eleven germline mutations (five SDHB, one SDHC, one SDHD, two VHL, and two MEN1) and four variants of unknown significance (two SDHA, one SDHB, and one SDHAF2) were identified in the studied genes in our patient cohort. Tumor tissue analysis identified LOH at the SDHB locus in three pituitary adenomas and loss of heterozygosity at the MEN1 locus in two pheochromocytomas. All the pituitary adenomas of patients affected by SDHX alterations have a unique histological feature not previously described in this context. Conclusions: Mutations in the genes known to cause pheo/PGL can rarely be associated with pituitary adenomas, whereas mutation in a gene predisposing to pituitary adenomas (MEN1) can be associated with pheo/PGL. Our findings suggest that genetic testing should be considered in all patients or families with the constellation of pheo/PGL and a pituitary adenoma. PMID:25494863

NIBBS-search for fast and accurate prediction of phenotype-biased metabolic systems.

PubMed

Schmidt, Matthew C; Rocha, Andrea M; Padmanabhan, Kanchana; Shpanskaya, Yekaterina; Banfield, Jill; Scott, Kathleen; Mihelcic, James R; Samatova, Nagiza F

2012-01-01

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS.

NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

PubMed Central

Padmanabhan, Kanchana; Shpanskaya, Yekaterina; Banfield, Jill; Scott, Kathleen; Mihelcic, James R.; Samatova, Nagiza F.

2012-01-01

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS. PMID:22589706

Interactions between environmental factors and maternal-fetal genetic variations: strategies to elucidate risks of preterm birth.

PubMed

Pereyra, Silvana; Bertoni, Bernardo; Sapiro, Rossana

2016-07-01

Preterm birth (PTB) is a complex disease in which medical, social, cultural, and hereditary factors contribute to the pathogenesis of this adverse event. Interactions between genes and environmental factors may complicate our understanding of the relative influence of both effects on PTB. To overcome this, we combined data obtained from a cohort of newborns and their mothers with multiplex analysis of inflammatory-related genes and several environmental risk factors of PTB to describe the environmental-genetic influence on PTB. The study aimed to investigate the association between maternal and fetal genetic variations in genes related to the inflammation pathway with PTB and to assess the interaction between environmental factors with these variations. We conducted a case-control study at the Pereira Rossell Hospital Center, Montevideo, Uruguay. The study included 143 mother-offspring dyads who delivered at preterm (gestational age<37 weeks) and 108 mother-offspring dyads who delivered at term. We used real-time PCR followed by a high-resolution melting analysis to simultaneously identify gene variations involved in inflammatory pathways in the context of environmental variables. The genes analyzed were: Toll-like receptor 4 (TLR4), Interleukin 6 (IL6), Interleukin 1 beta (IL1B) and Interleukin 12 receptor beta (IL12RB). We detected a significant interaction between IL1B rs16944 polymorphism in maternal samples and IL6 rs1800795 polymorphism in newborns, emphasizing the role of the interaction of maternal and fetal genomes in PTB. In addition, smoke exposure and premature rupture of membranes (PROM) were significantly different between the premature group and controls. IL1B and IL6 polymorphisms in mothers were significantly associated with PTB when controlling for smoke exposure. TLR4 polymorphism and PROM were significantly associated with PTB when controlling for PROM, but only in the case of severe PTB. Interactions between maternal and fetal genomes may influence the timing of birth. By incorporating environmental data, we revealed genetic associations with PTB, a finding not found when we analyzed genetic data alone. Our results stress the importance of studying the effect of genotype interactions between mothers and children in the context of environmental factors because they substantially contribute to phenotype variability. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Targeted Mutagenesis of Duplicated Genes in Soybean with Zinc-Finger Nucleases1[W][OA

PubMed Central

Curtin, Shaun J.; Zhang, Feng; Sander, Jeffry D.; Haun, William J.; Starker, Colby; Baltes, Nicholas J.; Reyon, Deepak; Dahlborg, Elizabeth J.; Goodwin, Mathew J.; Coffman, Andrew P.; Dobbs, Drena; Joung, J. Keith; Voytas, Daniel F.; Stupar, Robert M.

2011-01-01

We performed targeted mutagenesis of a transgene and nine endogenous soybean (Glycine max) genes using zinc-finger nucleases (ZFNs). A suite of ZFNs were engineered by the recently described context-dependent assembly platform—a rapid, open-source method for generating zinc-finger arrays. Specific ZFNs targeting DICER-LIKE (DCL) genes and other genes involved in RNA silencing were cloned into a vector under an estrogen-inducible promoter. A hairy-root transformation system was employed to investigate the efficiency of ZFN mutagenesis at each target locus. Transgenic roots exhibited somatic mutations localized at the ZFN target sites for seven out of nine targeted genes. We next introduced a ZFN into soybean via whole-plant transformation and generated independent mutations in the paralogous genes DCL4a and DCL4b. The dcl4b mutation showed efficient heritable transmission of the ZFN-induced mutation in the subsequent generation. These findings indicate that ZFN-based mutagenesis provides an efficient method for making mutations in duplicate genes that are otherwise difficult to study due to redundancy. We also developed a publicly accessible Web-based tool to identify sites suitable for engineering context-dependent assembly ZFNs in the soybean genome. PMID:21464476

Unraveling the evolutionary history of the phosphoryl-transfer chain of the phosphoenolpyruvate:phosphotransferase system through phylogenetic analyses and genome context

PubMed Central

2008-01-01

Background The phosphoenolpyruvate phosphotransferase system (PTS) plays a major role in sugar transport and in the regulation of essential physiological processes in many bacteria. The PTS couples solute transport to its phosphorylation at the expense of phosphoenolpyruvate (PEP) and it consists of general cytoplasmic phosphoryl transfer proteins and specific enzyme II complexes which catalyze the uptake and phosphorylation of solutes. Previous studies have suggested that the evolution of the constituents of the enzyme II complexes has been driven largely by horizontal gene transfer whereas vertical inheritance has been prevalent in the general phosphoryl transfer proteins in some bacterial groups. The aim of this work is to test this hypothesis by studying the evolution of the phosphoryl transfer proteins of the PTS. Results We have analyzed the evolutionary history of the PTS phosphoryl transfer chain (PTS-ptc) components in 222 complete genomes by combining phylogenetic methods and analysis of genomic context. Phylogenetic analyses alone were not conclusive for the deepest nodes but when complemented with analyses of genomic context and functional information, the main evolutionary trends of this system could be depicted. Conclusion The PTS-ptc evolved in bacteria after the divergence of early lineages such as Aquificales, Thermotogales and Thermus/Deinococcus. The subsequent evolutionary history of the PTS-ptc varied in different bacterial lineages: vertical inheritance and lineage-specific gene losses mainly explain the current situation in Actinobacteria and Firmicutes whereas horizontal gene transfer (HGT) also played a major role in Proteobacteria. Most remarkably, we have identified a HGT event from Firmicutes or Fusobacteria to the last common ancestor of the Enterobacteriaceae, Pasteurellaceae, Shewanellaceae and Vibrionaceae. This transfer led to extensive changes in the metabolic and regulatory networks of these bacteria including the development of a novel carbon catabolite repression system. Hence, this example illustrates that HGT can drive major physiological modifications in bacteria. PMID:18485189

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

PubMed

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

2017-10-01

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

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

Draft genome sequence of a KPC-2-producing Klebsiella pneumoniae ST340 carrying blaCTX-M-15 and blaCTX-M-59 genes: a rich genome of mobile genetic elements and genes encoding antibiotic resistance.

PubMed

Casella, Tiago; de Morais, Andressa Batista Zequini; de Paula Barcelos, Diego Diniz; Tolentino, Fernanda Modesto; Cerdeira, Louise Teixeira; Bueno, Maria Fernanda Campagnari; Francisco, Gabriela Rodrigues; de Andrade, Leonardo Neves; da Costa Darini, Ana Lucia; de Oliveira Garcia, Doroti; Lincopan, Nilton; Nogueira, Mara Corrêa Lelles

2018-06-01

Klebsiella pneumoniae is considered an opportunistic pathogen and an important agent of nosocomial and community infections. It presents the ability to capture and harbour several antimicrobial resistance genes and, in this context, the extensive use of carbapenems to treat serious infections has been responsible for the selection of several resistance genes. This study reports the draft genome sequence of a KPC-2-producing K. pneumoniae strain (Kp10) simultaneously harbouring bla CTX-M-15 and bla CTX-M-59 genes isolated from urine culture of a patient with Parkinson's disease. Classical microbiological methods were applied to isolate and identify the strain, and PCR and sequencing were used to identify and characterise the genes and the genetic environment. Whole-genome sequencing (WGS) was performed using a Nextera XT DNA library and a NextSeq platform. WGS analysis revealed the presence of 5915 coding genes, 46 RNA-encoding genes and 255 pseudogenes. Kp10 belonged to sequence type 340 (ST340) of clonal complex 258 (CC258) and carried 20 transferable genes associated with antimicrobial resistance, comprising seven drug classes. Although the simultaneous presence of different bla CTX-M genes in the same strain is rarely reported, the bla KPC-2 , bla CTX-M-15 and bla CTX-M-59 genes were not associated with the same genetic mobile structure in Kp10. These results confirm the capacity of K. pneumoniae to harbour several antimicrobial resistance genes. Thus, this draft genome could help in future epidemiological studies regarding the dissemination of clinically relevant resistance genes. Copyright © 2018 International Society for Chemotherapy of Infection and Cancer. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-10-01

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

Context-sensitive network-based disease genetics prediction and its implications in drug discovery

PubMed Central

Chen, Yang; Xu, Rong

2017-01-01

Abstract Motivation: Disease phenotype networks play an important role in computational approaches to identifying new disease-gene associations. Current disease phenotype networks often model disease relationships based on pairwise similarities, therefore ignore the specific context on how two diseases are connected. In this study, we propose a new strategy to model disease associations using context-sensitive networks (CSNs). We developed a CSN-based phenome-driven approach for disease genetics prediction, and investigated the translational potential of the predicted genes in drug discovery. Results: We constructed CSNs by directly connecting diseases with associated phenotypes. Here, we constructed two CSNs using different data sources; the two networks contain 26 790 and 13 822 nodes respectively. We integrated the CSNs with a genetic functional relationship network and predicted disease genes using a network-based ranking algorithm. For comparison, we built Similarity-Based disease Networks (SBN) using the same disease phenotype data. In a de novo cross validation for 3324 diseases, the CSN-based approach significantly increased the average rank from top 12.6 to top 8.8% for all tested genes comparing with the SBN-based approach (p

Dynamics of Wolbachia pipientis Gene Expression Across the Drosophila melanogaster Life Cycle

PubMed Central

Gutzwiller, Florence; Carmo, Catarina R.; Miller, Danny E.; Rice, Danny W.; Newton, Irene L. G.; Hawley, R. Scott; Teixeira, Luis; Bergman, Casey M.

2015-01-01

Symbiotic interactions between microbes and their multicellular hosts have manifold biological consequences. To better understand how bacteria maintain symbiotic associations with animal hosts, we analyzed genome-wide gene expression for the endosymbiotic α-proteobacteria Wolbachia pipientis across the entire life cycle of Drosophila melanogaster. We found that the majority of Wolbachia genes are expressed stably across the D. melanogaster life cycle, but that 7.8% of Wolbachia genes exhibit robust stage- or sex-specific expression differences when studied in the whole-organism context. Differentially-expressed Wolbachia genes are typically up-regulated after Drosophila embryogenesis and include many bacterial membrane, secretion system, and ankyrin repeat-containing proteins. Sex-biased genes are often organized as small operons of uncharacterized genes and are mainly up-regulated in adult Drosophila males in an age-dependent manner. We also systematically investigated expression levels of previously-reported candidate genes thought to be involved in host-microbe interaction, including those in the WO-A and WO-B prophages and in the Octomom region, which has been implicated in regulating bacterial titer and pathogenicity. Our work provides comprehensive insight into the developmental dynamics of gene expression for a widespread endosymbiont in its natural host context, and shows that public gene expression data harbor rich resources to probe the functional basis of the Wolbachia-Drosophila symbiosis and annotate the transcriptional outputs of the Wolbachia genome. PMID:26497146

Characterizing the Grape Transcriptome. Analysis of Expressed Sequence Tags from Multiple Vitis Species and Development of a Compendium of Gene Expression during Berry Development1[w

PubMed Central

Silva, Francisco Goes da; Iandolino, Alberto; Al-Kayal, Fadi; Bohlmann, Marlene C.; Cushman, Mary Ann; Lim, Hyunju; Ergul, Ali; Figueroa, Rubi; Kabuloglu, Elif K.; Osborne, Craig; Rowe, Joan; Tattersall, Elizabeth; Leslie, Anna; Xu, Jane; Baek, JongMin; Cramer, Grant R.; Cushman, John C.; Cook, Douglas R.

2005-01-01

We report the analysis and annotation of 146,075 expressed sequence tags from Vitis species. The majority of these sequences were derived from different cultivars of Vitis vinifera, comprising an estimated 25,746 unique contig and singleton sequences that survey transcription in various tissues and developmental stages and during biotic and abiotic stress. Putatively homologous proteins were identified for over 17,752 of the transcripts, with 1,962 transcripts further subdivided into one or more Gene Ontology categories. A simple structured vocabulary, with modules for plant genotype, plant development, and stress, was developed to describe the relationship between individual expressed sequence tags and cDNA libraries; the resulting vocabulary provides query terms to facilitate data mining within the context of a relational database. As a measure of the extent to which characterized metabolic pathways were encompassed by the data set, we searched for homologs of the enzymes leading from glycolysis, through the oxidative/nonoxidative pentose phosphate pathway, and into the general phenylpropanoid pathway. Homologs were identified for 65 of these 77 enzymes, with 86% of enzymatic steps represented by paralogous genes. Differentially expressed transcripts were identified by means of a stringent believability index cutoff of ≥98.4%. Correlation analysis and two-dimensional hierarchical clustering grouped these transcripts according to similarity of expression. In the broadest analysis, 665 differentially expressed transcripts were identified across 29 cDNA libraries, representing a range of developmental and stress conditions. The groupings revealed expected associations between plant developmental stages and tissue types, with the notable exception of abiotic stress treatments. A more focused analysis of flower and berry development identified 87 differentially expressed transcripts and provides the basis for a compendium that relates gene expression and annotation to previously characterized aspects of berry development and physiology. Comparison with published results for select genes, as well as correlation analysis between independent data sets, suggests that the inferred in silico patterns of expression are likely to be an accurate representation of transcript abundance for the conditions surveyed. Thus, the combined data set reveals the in silico expression patterns for hundreds of genes in V. vinifera, the majority of which have not been previously studied within this species. PMID:16219919

Ecological transcriptomics of lake-type and riverine sockeye salmon (Oncorhynchus nerka)

PubMed Central

2011-01-01

Background There are a growing number of genomes sequenced with tentative functions assigned to a large proportion of the individual genes. Model organisms in laboratory settings form the basis for the assignment of gene function, and the ecological context of gene function is lacking. This work addresses this shortcoming by investigating expressed genes of sockeye salmon (Oncorhynchus nerka) muscle tissue. We compared morphology and gene expression in natural juvenile sockeye populations related to river and lake habitats. Based on previously documented divergent morphology, feeding strategy, and predation in association with these distinct environments, we expect that burst swimming is favored in riverine population and continuous swimming is favored in lake-type population. In turn we predict that morphology and expressed genes promote burst swimming in riverine sockeye and continuous swimming in lake-type sockeye. Results We found the riverine sockeye population had deep, robust bodies and lake-type had shallow, streamlined bodies. Gene expression patterns were measured using a 16K microarray, discovering 141 genes with significant differential expression. Overall, the identity and function of these genes was consistent with our hypothesis. In addition, Gene Ontology (GO) enrichment analyses with a larger set of differentially expressed genes found the "biosynthesis" category enriched for the riverine population and the "metabolism" category enriched for the lake-type population. Conclusions This study provides a framework for understanding sockeye life history from a transcriptomic perspective and a starting point for more extensive, targeted studies determining the ecological context of genes. PMID:22136247

Ecological transcriptomics of lake-type and riverine sockeye salmon (Oncorhynchus nerka).

PubMed

Pavey, Scott A; Sutherland, Ben J G; Leong, Jong; Robb, Adrienne; von Schalburg, Kris; Hamon, Troy R; Koop, Ben F; Nielsen, Jennifer L

2011-12-02

There are a growing number of genomes sequenced with tentative functions assigned to a large proportion of the individual genes. Model organisms in laboratory settings form the basis for the assignment of gene function, and the ecological context of gene function is lacking. This work addresses this shortcoming by investigating expressed genes of sockeye salmon (Oncorhynchus nerka) muscle tissue. We compared morphology and gene expression in natural juvenile sockeye populations related to river and lake habitats. Based on previously documented divergent morphology, feeding strategy, and predation in association with these distinct environments, we expect that burst swimming is favored in riverine population and continuous swimming is favored in lake-type population. In turn we predict that morphology and expressed genes promote burst swimming in riverine sockeye and continuous swimming in lake-type sockeye. We found the riverine sockeye population had deep, robust bodies and lake-type had shallow, streamlined bodies. Gene expression patterns were measured using a 16 k microarray, discovering 141 genes with significant differential expression. Overall, the identity and function of these genes was consistent with our hypothesis. In addition, Gene Ontology (GO) enrichment analyses with a larger set of differentially expressed genes found the "biosynthesis" category enriched for the riverine population and the "metabolism" category enriched for the lake-type population. This study provides a framework for understanding sockeye life history from a transcriptomic perspective and a starting point for more extensive, targeted studies determining the ecological context of genes.

PhenomeExpress: a refined network analysis of expression datasets by inclusion of known disease phenotypes.

PubMed

Soul, Jamie; Hardingham, Timothy E; Boot-Handford, Raymond P; Schwartz, Jean-Marc

2015-01-29

We describe a new method, PhenomeExpress, for the analysis of transcriptomic datasets to identify pathogenic disease mechanisms. Our analysis method includes input from both protein-protein interaction and phenotype similarity networks. This introduces valuable information from disease relevant phenotypes, which aids the identification of sub-networks that are significantly enriched in differentially expressed genes and are related to the disease relevant phenotypes. This contrasts with many active sub-network detection methods, which rely solely on protein-protein interaction networks derived from compounded data of many unrelated biological conditions and which are therefore not specific to the context of the experiment. PhenomeExpress thus exploits readily available animal model and human disease phenotype information. It combines this prior evidence of disease phenotypes with the experimentally derived disease data sets to provide a more targeted analysis. Two case studies, in subchondral bone in osteoarthritis and in Pax5 in acute lymphoblastic leukaemia, demonstrate that PhenomeExpress identifies core disease pathways in both mouse and human disease expression datasets derived from different technologies. We also validate the approach by comparison to state-of-the-art active sub-network detection methods, which reveals how it may enhance the detection of molecular phenotypes and provide a more detailed context to those previously identified as possible candidates.

An in silico assessment of gene function and organization of the phenylpropanoid pathway metabolic networks in Arabidopsis thaliana and limitations thereof

NASA Technical Reports Server (NTRS)

Costa, Michael A.; Collins, R. Eric; Anterola, Aldwin M.; Cochrane, Fiona C.; Davin, Laurence B.; Lewis, Norman G.

2003-01-01

The Arabidopsis genome sequencing in 2000 gave to science the first blueprint of a vascular plant. Its successful completion also prompted the US National Science Foundation to launch the Arabidopsis 2010 initiative, the goal of which is to identify the function of each gene by 2010. In this study, an exhaustive analysis of The Institute for Genomic Research (TIGR) and The Arabidopsis Information Resource (TAIR) databases, together with all currently compiled EST sequence data, was carried out in order to determine to what extent the various metabolic networks from phenylalanine ammonia lyase (PAL) to the monolignols were organized and/or could be predicted. In these databases, there are some 65 genes which have been annotated as encoding putative enzymatic steps in monolignol biosynthesis, although many of them have only very low homology to monolignol pathway genes of known function in other plant systems. Our detailed analysis revealed that presently only 13 genes (two PALs, a cinnamate-4-hydroxylase, a p-coumarate-3-hydroxylase, a ferulate-5-hydroxylase, three 4-coumarate-CoA ligases, a cinnamic acid O-methyl transferase, two cinnamoyl-CoA reductases) and two cinnamyl alcohol dehydrogenases can be classified as having a bona fide (definitive) function; the remaining 52 genes currently have undetermined physiological roles. The EST database entries for this particular set of genes also provided little new insight into how the monolignol pathway was organized in the different tissues and organs, this being perhaps a consequence of both limitations in how tissue samples were collected and in the incomplete nature of the EST collections. This analysis thus underscores the fact that even with genomic sequencing, presumed to provide the entire suite of putative genes in the monolignol-forming pathway, a very large effort needs to be conducted to establish actual catalytic roles (including enzyme versatility), as well as the physiological function(s) for each member of the (multi)gene families present and the metabolic networks that are operative. Additionally, one key to identifying physiological functions for many of these (and other) unknown genes, and their corresponding metabolic networks, awaits the development of technologies to comprehensively study molecular processes at the single cell level in particular tissues and organs, in order to establish the actual metabolic context.

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.

Bisphenol A effects on gene expression in adipocytes from children: association with metabolic disorders.

PubMed

Menale, Ciro; Piccolo, Maria Teresa; Cirillo, Grazia; Calogero, Raffaele A; Papparella, Alfonso; Mita, Luigi; Del Giudice, Emanuele Miraglia; Diano, Nadia; Crispi, Stefania; Mita, Damiano Gustavo

2015-06-01

Bisphenol A (BPA) is a xenobiotic endocrine-disrupting chemical. In vitro and in vivo studies have indicated that BPA alters endocrine-metabolic pathways in adipose tissue, which increases the risk of metabolic disorders and obesity. BPA can affect adipose tissue and increase fat cell numbers or sizes by regulating the expression of the genes that are directly involved in metabolic homeostasis and obesity. Several studies performed in animal models have accounted for an obesogen role of BPA, but its effects on human adipocytes - especially in children - have been poorly investigated. The aim of this study is to understand the molecular mechanisms by which environmentally relevant doses of BPA can interfere with the canonical endocrine function that regulates metabolism in mature human adipocytes from prepubertal, non-obese children. BPA can act as an estrogen agonist or antagonist depending on the physiological context. To identify the molecular signatures associated with metabolism, transcriptional modifications of mature adipocytes from prepubertal children exposed to estrogen were evaluated by means of microarray analysis. The analysis of deregulated genes associated with metabolic disorders allowed us to identify a small group of genes that are expressed in an opposite manner from that of adipocytes treated with BPA. In particular, we found that BPA increases the expression of pro-inflammatory cytokines and the expression of FABP4 and CD36, two genes involved in lipid metabolism. In addition, BPA decreases the expression of PCSK1, a gene involved in insulin production. These results indicate that exposure to BPA may be an important risk factor for developing metabolic disorders that are involved in childhood metabolism dysregulation. © 2015 Society for Endocrinology.

Effects of Drought on Gene Expression in Maize Reproductive and Leaf Meristem Tissue Revealed by RNA-Seq1[W][OA

PubMed Central

Kakumanu, Akshay; Ambavaram, Madana M.R.; Klumas, Curtis; Krishnan, Arjun; Batlang, Utlwang; Myers, Elijah; Grene, Ruth; Pereira, Andy

2012-01-01

Drought stress affects cereals especially during the reproductive stage. The maize (Zea mays) drought transcriptome was studied using RNA-Seq analysis to compare drought-treated and well-watered fertilized ovary and basal leaf meristem tissue. More drought-responsive genes responded in the ovary compared with the leaf meristem. Gene Ontology enrichment analysis revealed a massive decrease in transcript abundance of cell division and cell cycle genes in the drought-stressed ovary only. Among Gene Ontology categories related to carbohydrate metabolism, changes in starch and Suc metabolism-related genes occurred in the ovary, consistent with a decrease in starch levels, and in Suc transporter function, with no comparable changes occurring in the leaf meristem. Abscisic acid (ABA)-related processes responded positively, but only in the ovaries. Related responses suggested the operation of low glucose sensing in drought-stressed ovaries. The data are discussed in the context of the susceptibility of maize kernel to drought stress leading to embryo abortion and the relative robustness of dividing vegetative tissue taken at the same time from the same plant subjected to the same conditions. Our working hypothesis involves signaling events associated with increased ABA levels, decreased glucose levels, disruption of ABA/sugar signaling, activation of programmed cell death/senescence through repression of a phospholipase C-mediated signaling pathway, and arrest of the cell cycle in the stressed ovary at 1 d after pollination. Increased invertase levels in the stressed leaf meristem, on the other hand, resulted in that tissue maintaining hexose levels at an “unstressed” level, and at lower ABA levels, which was correlated with successful resistance to drought stress. PMID:22837360

Survey of the Heritability and Sparse Architecture of Gene Expression Traits across Human Tissues.

PubMed

Wheeler, Heather E; Shah, Kaanan P; Brenner, Jonathon; Garcia, Tzintzuni; Aquino-Michaels, Keston; Cox, Nancy J; Nicolae, Dan L; Im, Hae Kyung

2016-11-01

Understanding the genetic architecture of gene expression traits is key to elucidating the underlying mechanisms of complex traits. Here, for the first time, we perform a systematic survey of the heritability and the distribution of effect sizes across all representative tissues in the human body. We find that local h2 can be relatively well characterized with 59% of expressed genes showing significant h2 (FDR < 0.1) in the DGN whole blood cohort. However, current sample sizes (n ≤ 922) do not allow us to compute distal h2. Bayesian Sparse Linear Mixed Model (BSLMM) analysis provides strong evidence that the genetic contribution to local expression traits is dominated by a handful of genetic variants rather than by the collective contribution of a large number of variants each of modest size. In other words, the local architecture of gene expression traits is sparse rather than polygenic across all 40 tissues (from DGN and GTEx) examined. This result is confirmed by the sparsity of optimal performing gene expression predictors via elastic net modeling. To further explore the tissue context specificity, we decompose the expression traits into cross-tissue and tissue-specific components using a novel Orthogonal Tissue Decomposition (OTD) approach. Through a series of simulations we show that the cross-tissue and tissue-specific components are identifiable via OTD. Heritability and sparsity estimates of these derived expression phenotypes show similar characteristics to the original traits. Consistent properties relative to prior GTEx multi-tissue analysis results suggest that these traits reflect the expected biology. Finally, we apply this knowledge to develop prediction models of gene expression traits for all tissues. The prediction models, heritability, and prediction performance R2 for original and decomposed expression phenotypes are made publicly available (https://github.com/hakyimlab/PrediXcan).

Religion priming and an oxytocin receptor gene (OXTR) polymorphism interact to affect self-control in a social context.

PubMed

Sasaki, Joni Y; Mojaverian, Taraneh; Kim, Heejung S

2015-02-01

Using a genetic moderation approach, this study examines how an experimental prime of religion impacts self-control in a social context, and whether this effect differs depending on the genotype of an oxytocin receptor gene (OXTR) polymorphism (rs53576). People with different genotypes of OXTR seem to have different genetic orientations toward sociality, which may have consequences for the way they respond to religious cues in the environment. In order to determine whether the influence of religion priming on self-control is socially motivated, we examine whether this effect is stronger for people who have OXTR genotypes that should be linked to greater rather than less social sensitivity (i.e., GG vs. AA/AG genotypes). The results showed that experimentally priming religion increased self-control behaviors for people with GG genotypes more so than people with AA/AG genotypes. Furthermore, this Gene × Religion interaction emerged in a social context, when people were interacting face to face with another person. This research integrates genetic moderation and social psychological approaches to address a novel question about religion's influence on self-control behavior, which has implications for coping with distress and psychopathology. These findings also highlight the importance of the social context for understanding genetic moderation of psychological effects.

PRISM offers a comprehensive genomic approach to transcription factor function prediction

PubMed Central

Wenger, Aaron M.; Clarke, Shoa L.; Guturu, Harendra; Chen, Jenny; Schaar, Bruce T.; McLean, Cory Y.; Bejerano, Gill

2013-01-01

The human genome encodes 1500–2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells. PMID:23382538

Combinatorial approaches to gene recognition.

PubMed

Roytberg, M A; Astakhova, T V; Gelfand, M S

1997-01-01

Recognition of genes via exon assembly approaches leads naturally to the use of dynamic programming. We consider the general graph-theoretical formulation of the exon assembly problem and analyze in detail some specific variants: multicriterial optimization in the case of non-linear gene-scoring functions; context-dependent schemes for scoring exons and related procedures for exon filtering; and highly specific recognition of arbitrary gene segments, oligonucleotide probes and polymerase chain reaction (PCR) primers.

Transcriptome analyses and differential gene expression in a non-model fish species with alternative mating tactics

PubMed Central

2014-01-01

Background Social dominance is important for the reproductive success of males in many species. In the black-faced blenny (Tripterygion delaisi) during the reproductive season, some males change color and invest in nest making and defending a territory, whereas others do not change color and ‘sneak’ reproductions when females lay their eggs. Using RNAseq, we profiled differential gene expression between the brains of territorial males, sneaker males, and females to study the molecular signatures of male dimorphism. Results We found that more genes were differentially expressed between the two male phenotypes than between males and females, suggesting that during the reproductive period phenotypic plasticity is a more important factor in differential gene expression than sexual dimorphism. The territorial male overexpresses genes related to synaptic plasticity and the sneaker male overexpresses genes involved in differentiation and development. Conclusions Previously suggested candidate genes for social dominance in the context of alternative mating strategies seem to be predominantly species-specific. We present a list of novel genes which are differentially expressed in Tripterygion delaisi. This is the first genome-wide study for a molecular non-model species in the context of alternative mating strategies and provides essential information for further studies investigating the molecular basis of social dominance. PMID:24581002

Transcriptome analyses and differential gene expression in a non-model fish species with alternative mating tactics.

PubMed

Schunter, Celia; Vollmer, Steven V; Macpherson, Enrique; Pascual, Marta

2014-02-28

Social dominance is important for the reproductive success of males in many species. In the black-faced blenny (Tripterygion delaisi) during the reproductive season, some males change color and invest in nest making and defending a territory, whereas others do not change color and 'sneak' reproductions when females lay their eggs. Using RNAseq, we profiled differential gene expression between the brains of territorial males, sneaker males, and females to study the molecular signatures of male dimorphism. We found that more genes were differentially expressed between the two male phenotypes than between males and females, suggesting that during the reproductive period phenotypic plasticity is a more important factor in differential gene expression than sexual dimorphism. The territorial male overexpresses genes related to synaptic plasticity and the sneaker male overexpresses genes involved in differentiation and development. Previously suggested candidate genes for social dominance in the context of alternative mating strategies seem to be predominantly species-specific. We present a list of novel genes which are differentially expressed in Tripterygion delaisi. This is the first genome-wide study for a molecular non-model species in the context of alternative mating strategies and provides essential information for further studies investigating the molecular basis of social dominance.

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

PubMed

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

2010-10-01

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

cDNA Microarray Gene Expression Profiling of Hedgehog Signaling Pathway Inhibition in Human Colon Cancer Cells

PubMed Central

Shi, Ting; Mazumdar, Tapati; DeVecchio, Jennifer; Duan, Zhong-Hui; Agyeman, Akwasi; Aziz, Mohammad; Houghton, Janet A.

2010-01-01

Background Hedgehog (HH) signaling plays a critical role in normal cellular processes, in normal mammalian gastrointestinal development and differentiation, and in oncogenesis and maintenance of the malignant phenotype in a variety of human cancers. Increasing evidence further implicates the involvement of HH signaling in oncogenesis and metastatic behavior of colon cancers. However, genomic approaches to elucidate the role of HH signaling in cancers in general are lacking, and data derived on HH signaling in colon cancer is extremely limited. Methodology/Principal Findings To identify unique downstream targets of the GLI genes, the transcriptional regulators of HH signaling, in the context of colon carcinoma, we employed a small molecule inhibitor of both GLI1 and GLI2, GANT61, in two human colon cancer cell lines, HT29 and GC3/c1. Cell cycle analysis demonstrated accumulation of GANT61-treated cells at the G1/S boundary. cDNA microarray gene expression profiling of 18,401 genes identified Differentially Expressed Genes (DEGs) both common and unique to HT29 and GC3/c1. Analyses using GenomeStudio (statistics), Matlab (heat map), Ingenuity (canonical pathway analysis), or by qRT-PCR, identified p21Cip1 (CDKN1A) and p15Ink4b (CDKN2B), which play a role in the G1/S checkpoint, as up-regulated genes at the G1/S boundary. Genes that determine further cell cycle progression at G1/S including E2F2, CYCLIN E2 (CCNE2), CDC25A and CDK2, and genes that regulate passage of cells through G2/M (CYCLIN A2 [CCNA2], CDC25C, CYCLIN B2 [CCNB2], CDC20 and CDC2 [CDK1], were down-regulated. In addition, novel genes involved in stress response, DNA damage response, DNA replication and DNA repair were identified following inhibition of HH signaling. Conclusions/Significance This study identifies genes that are involved in HH-dependent cellular proliferation in colon cancer cells, and following its inhibition, genes that regulate cell cycle progression and events downstream of the G1/S boundary. PMID:20957031

Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort.

PubMed

Cong, Wang; Meng, Xianglian; Li, Jin; Zhang, Qiushi; Chen, Feng; Liu, Wenjie; Wang, Ying; Cheng, Sipu; Yao, Xiaohui; Yan, Jingwen; Kim, Sungeun; Saykin, Andrew J; Liang, Hong; Shen, Li

2017-05-30

The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ 1-42 are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks. The CSF and genotyping data of 843 study subjects (199 CN, 85 SMC, 239 EMCI, 207 LMCI, 113 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were analyzed. PLINK was used to perform GWAS on the t-tau/Aβ 1-42 ratio using quality controlled genotype data, including 563,980 single nucleotide polymorphisms (SNPs), with age, sex and diagnosis as covariates. Gene-level p-values were obtained by VEGAS2. Genes with p-value ≤ 0.05 were mapped on to a protein-protein interaction (PPI) network (9,617 nodes, 39,240 edges, from the HPRD Database). We integrated a consensus model strategy into the iPINBPA network analysis framework, and named it as CM-iPINBPA. Four consensus modules (CMs) were discovered by CM-iPINBPA, and were functionally annotated using the pathway analysis tool Enrichr. The intersection of four CMs forms a common subnetwork of 29 genes, including those related to tau phosphorylation (GSK3B, SUMO1, AKAP5, CALM1 and DLG4), amyloid beta production (CASP8, PIK3R1, PPA1, PARP1, CSNK2A1, NGFR, and RHOA), and AD (BCL3, CFLAR, SMAD1, and HIF1A). This study coupled a consensus module (CM) strategy with the iPINBPA network analysis framework, and applied it to the GWAS of CSF t-tau/Aβ1-42 ratio in an AD study. The genome-wide network analysis yielded 4 enriched CMs that share not only genes related to tau phosphorylation or amyloid beta production but also multiple genes enriching several KEGG pathways such as Alzheimer's disease, colorectal cancer, gliomas, renal cell carcinoma, Huntington's disease, and others. This study demonstrated that integration of gene-level associations with CMs could yield statistically significant findings to offer valuable biological insights (e.g., functional interaction among the protein products of these genes) and suggest high confidence candidates for subsequent analyses.

Identification of the Consistently Altered Metabolic Targets in Human Hepatocellular Carcinoma.

PubMed

Nwosu, Zeribe Chike; Megger, Dominik Andre; Hammad, Seddik; Sitek, Barbara; Roessler, Stephanie; Ebert, Matthias Philip; Meyer, Christoph; Dooley, Steven

2017-09-01

Cancer cells rely on metabolic alterations to enhance proliferation and survival. Metabolic gene alterations that repeatedly occur in liver cancer are largely unknown. We aimed to identify metabolic genes that are consistently deregulated, and are of potential clinical significance in human hepatocellular carcinoma (HCC). We studied the expression of 2,761 metabolic genes in 8 microarray datasets comprising 521 human HCC tissues. Genes exclusively up-regulated or down-regulated in 6 or more datasets were defined as consistently deregulated. The consistent genes that correlated with tumor progression markers ( ECM2 and MMP9) (Pearson correlation P < .05) were used for Kaplan-Meier overall survival analysis in a patient cohort. We further compared proteomic expression of metabolic genes in 19 tumors vs adjacent normal liver tissues. We identified 634 consistent metabolic genes, ∼60% of which are not yet described in HCC. The down-regulated genes (n = 350) are mostly involved in physiologic hepatocyte metabolic functions (eg, xenobiotic, fatty acid, and amino acid metabolism). In contrast, among consistently up-regulated metabolic genes (n = 284) are those involved in glycolysis, pentose phosphate pathway, nucleotide biosynthesis, tricarboxylic acid cycle, oxidative phosphorylation, proton transport, membrane lipid, and glycan metabolism. Several metabolic genes (n = 434) correlated with progression markers, and of these, 201 predicted overall survival outcome in the patient cohort analyzed. Over 90% of the metabolic targets significantly altered at the protein level were similarly up- or down-regulated as in genomic profile. We provide the first exposition of the consistently altered metabolic genes in HCC and show that these genes are potentially relevant targets for onward studies in preclinical and clinical contexts.

A gene-specific non-enhancer sequence is critical for expression from the promoter of the small heat shock protein gene αB-crystallin

PubMed Central

2014-01-01

Background Deciphering of the information content of eukaryotic promoters has remained confined to universal landmarks and conserved sequence elements such as enhancers and transcription factor binding motifs, which are considered sufficient for gene activation and regulation. Gene-specific sequences, interspersed between the canonical transacting factor binding sites or adjoining them within a promoter, are generally taken to be devoid of any regulatory information and have therefore been largely ignored. An unanswered question therefore is, do gene-specific sequences within a eukaryotic promoter have a role in gene activation? Here, we present an exhaustive experimental analysis of a gene-specific sequence adjoining the heat shock element (HSE) in the proximal promoter of the small heat shock protein gene, αB-crystallin (cryab). These sequences are highly conserved between the rodents and the humans. Results Using human retinal pigment epithelial cells in culture as the host, we have identified a 10-bp gene-specific promoter sequence (GPS), which, unlike an enhancer, controls expression from the promoter of this gene, only when in appropriate position and orientation. Notably, the data suggests that GPS in comparison with the HSE works in a context-independent fashion. Additionally, when moved upstream, about a nucleosome length of DNA (−154 bp) from the transcription start site (TSS), the activity of the promoter is markedly inhibited, suggesting its involvement in local promoter access. Importantly, we demonstrate that deletion of the GPS results in complete loss of cryab promoter activity in transgenic mice. Conclusions These data suggest that gene-specific sequences such as the GPS, identified here, may have critical roles in regulating gene-specific activity from eukaryotic promoters. PMID:24589182

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

PubMed Central

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

2012-01-01

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

Association of Single-Nucleotide Polymorphisms of the Tau Gene With Late-Onset Parkinson Disease

PubMed Central

Martin, Eden R.; Scott, William K.; Nance, Martha A.; Watts, Ray L.; Hubble, Jean P.; Koller, William C.; Lyons, Kelly; Pahwa, Rajesh; Stern, Matthew B.; Colcher, Amy; Hiner, Bradley C.; Jankovic, Joseph; Ondo, William G.; Allen, Fred H.; Goetz, Christopher G.; Small, Gary W.; Masterman, Donna; Mastaglia, Frank; Laing, Nigel G.; Stajich, Jeffrey M.; Ribble, Robert C.; Booze, Michael W.; Rogala, Allison; Hauser, Michael A.; Zhang, Fengyu; Gibson, Rachel A.; Middleton, Lefkos T.; Roses, Allen D.; Haines, Jonathan L.; Scott, Burton L.; Pericak-Vance, Margaret A.; Vance, Jeffery M.

2013-01-01

Context The human tau gene, which promotes assembly of neuronal microtubules, has been associated with several rare neurologic diseases that clinically include parkinsonian features. We recently observed linkage in idiopathic Parkinson disease (PD) to a region on chromosome 17q21 that contains the tau gene. These factors make tau a good candidate for investigation as a susceptibility gene for idiopathic PD, the most common form of the disease. Objective To investigate whether the tau gene is involved in idiopathic PD. Design, Setting, and Participants Among a sample of 1056 individuals from 235 families selected from 13 clinical centers in the United States and Australia and from a family ascertainment core center, we tested 5 single-nucleotide polymorphisms (SNPs) within the tau gene for association with PD, using family-based tests of association. Both affected (n = 426) and unaffected (n = 579) family members were included; 51 individuals had unclear PD status. Analyses were conducted to test individual SNPs and SNP haplotypes within the tau gene. Main Outcome Measure Family-based tests of association, calculated using asymptotic distributions. Results Analysis of association between the SNPs and PD yielded significant evidence of association for 3 of the 5 SNPs tested: SNP 3, P = .03; SNP 9i, P = .04; and SNP 11, P = .04. The 2 other SNPs did not show evidence of significant association (SNP 9ii, P = .11, and SNP 9iii, P = .87). Strong evidence of association was found with haplotype analysis, with a positive association with one haplotype (P = .009) and a negative association with another haplotype (P = .007). Substantial linkage disequilibrium (P<.001) was detected between 4 of the 5 SNPs (SNPs 3,9i, 9ii, and 11). Conclusions This integrated approach of genetic linkage and positional association analyses implicates tau as a susceptibility gene for idiopathic PD. PMID:11710889

CXCR4 expression is associated with time-course permanent and temporary myocardial infarction in rats.

PubMed

Kiani, Ali Asghar; Babaei, Fereshteh; Sedighi, Mehrnoosh; Soleimani, Azam; Ahmadi, Kolsum; Shahrokhi, Somayeh; Anbari, Khatereh; Nazari, Afshin

2017-06-01

Experimental myocardial infarction triggers secretion of Stromal cell-derived factor1 and lead to increase in the expression of its receptor "CXCR4" on the surface of various cells. The aim of this study was to evaluate the expression pattern of CXCR4 in peripheral blood cells following time-course permanent and temporary ischemia in rats. Fourteen male Wistar rats were divided into two groups of seven and were placed under permanent and transient ischemia. Peripheral blood mononuclear cells were isolated at different time points, RNAs extracted and applied to qRT-PCR analysis of the CXCR4 gene. Based on repeated measures analysis of variance, the differences in the expression levels of the gene in each of the groups were statistically significant over time (the effect of time) ( P <0.001). Additionally, the difference in gene expression between the two groups was statistically significant (the effect of group), such that at all times, the expression levels of the gene were significantly higher in the permanent ischemia than in the transient ischemia group ( P <0.001). Moreover, the interactive effect of time-group on gene expression was statistically significant ( P <0.001). CXCR4 is modulated in an induced ischemia context implying a possible association with myocardial infarction. Checking of CXCR4 expression in the ischemic changes shows that damage to the heart tissue trigger the secretion of inflammatory chemokine SDF, Followed by it CXCR4 expression in blood cells. These observations suggest that changes in the expression of CXCR4 may be considered a valuable marker for monitoring myocardial infarction.

IMG/M-HMP: a metagenome comparative analysis system for the Human Microbiome Project.

PubMed

Markowitz, Victor M; Chen, I-Min A; Chu, Ken; Szeto, Ernest; Palaniappan, Krishna; Jacob, Biju; Ratner, Anna; Liolios, Konstantinos; Pagani, Ioanna; Huntemann, Marcel; Mavromatis, Konstantinos; Ivanova, Natalia N; Kyrpides, Nikos C

2012-01-01

The Integrated Microbial Genomes and Metagenomes (IMG/M) resource is a data management system that supports the analysis of sequence data from microbial communities in the integrated context of all publicly available draft and complete genomes from the three domains of life as well as a large number of plasmids and viruses. IMG/M currently contains thousands of genomes and metagenome samples with billions of genes. IMG/M-HMP is an IMG/M data mart serving the US National Institutes of Health (NIH) Human Microbiome Project (HMP), focussed on HMP generated metagenome datasets, and is one of the central resources provided from the HMP Data Analysis and Coordination Center (DACC). IMG/M-HMP is available at http://www.hmpdacc-resources.org/imgm_hmp/.

Enhancing dopaminergic signaling and histone acetylation promotes long-term rescue of deficient fear extinction.

PubMed

Whittle, N; Maurer, V; Murphy, C; Rainer, J; Bindreither, D; Hauschild, M; Scharinger, A; Oberhauser, M; Keil, T; Brehm, C; Valovka, T; Striessnig, J; Singewald, N

2016-12-06

Extinction-based exposure therapy is used to treat anxiety- and trauma-related disorders; however, there is the need to improve its limited efficacy in individuals with impaired fear extinction learning and to promote greater protection against return-of-fear phenomena. Here, using 129S1/SvImJ mice, which display impaired fear extinction acquisition and extinction consolidation, we revealed that persistent and context-independent rescue of deficient fear extinction in these mice was associated with enhanced expression of dopamine-related genes, such as dopamine D1 (Drd1a) and -D2 (Drd2) receptor genes in the medial prefrontal cortex (mPFC) and amygdala, but not hippocampus. Moreover, enhanced histone acetylation was observed in the promoter of the extinction-regulated Drd2 gene in the mPFC, revealing a potential gene-regulatory mechanism. Although enhancing histone acetylation, via administering the histone deacetylase (HDAC) inhibitor MS-275, does not induce fear reduction during extinction training, it promoted enduring and context-independent rescue of deficient fear extinction consolidation/retrieval once extinction learning was initiated as shown following a mild conditioning protocol. This was associated with enhanced histone acetylation in neurons of the mPFC and amygdala. Finally, as a proof-of-principle, mimicking enhanced dopaminergic signaling by L-dopa treatment rescued deficient fear extinction and co-administration of MS-275 rendered this effect enduring and context-independent. In summary, current data reveal that combining dopaminergic and epigenetic mechanisms is a promising strategy to improve exposure-based behavior therapy in extinction-impaired individuals by initiating the formation of an enduring and context-independent fear-inhibitory memory.

Flexibility and symmetry of prokaryotic genome rearrangement reveal lineage-associated core-gene-defined genome organizational frameworks.

PubMed

Kang, Yu; Gu, Chaohao; Yuan, Lina; Wang, Yue; Zhu, Yanmin; Li, Xinna; Luo, Qibin; Xiao, Jingfa; Jiang, Daquan; Qian, Minping; Ahmed Khan, Aftab; Chen, Fei; Zhang, Zhang; Yu, Jun

2014-11-25

The prokaryotic pangenome partitions genes into core and dispensable genes. The order of core genes, albeit assumed to be stable under selection in general, is frequently interrupted by horizontal gene transfer and rearrangement, but how a core-gene-defined genome maintains its stability or flexibility remains to be investigated. Based on data from 30 species, including 425 genomes from six phyla, we grouped core genes into syntenic blocks in the context of a pangenome according to their stability across multiple isolates. A subset of the core genes, often species specific and lineage associated, formed a core-gene-defined genome organizational framework (cGOF). Such cGOFs are either single segmental (one-third of the species analyzed) or multisegmental (the rest). Multisegment cGOFs were further classified into symmetric or asymmetric according to segment orientations toward the origin-terminus axis. The cGOFs in Gram-positive species are exclusively symmetric and often reversible in orientation, as opposed to those of the Gram-negative bacteria, which are all asymmetric and irreversible. Meanwhile, all species showing strong strand-biased gene distribution contain symmetric cGOFs and often specific DnaE (α subunit of DNA polymerase III) isoforms. Furthermore, functional evaluations revealed that cGOF genes are hub associated with regard to cellular activities, and the stability of cGOF provides efficient indexes for scaffold orientation as demonstrated by assembling virtual and empirical genome drafts. cGOFs show species specificity, and the symmetry of multisegmental cGOFs is conserved among taxa and constrained by DNA polymerase-centric strand-biased gene distribution. The definition of species-specific cGOFs provides powerful guidance for genome assembly and other structure-based analysis. Prokaryotic genomes are frequently interrupted by horizontal gene transfer (HGT) and rearrangement. To know whether there is a set of genes not only conserved in position among isolates but also functionally essential for a given species and to further evaluate the stability or flexibility of such genome structures across lineages are of importance. Based on a large number of multi-isolate pangenomic data, our analysis reveals that a subset of core genes is organized into a core-gene-defined genome organizational framework, or cGOF. Furthermore, the lineage-associated cGOFs among Gram-positive and Gram-negative bacteria behave differently: the former, composed of 2 to 4 segments, have their fragments symmetrically rearranged around the origin-terminus axis, whereas the latter show more complex segmentation and are partitioned asymmetrically into chromosomal structures. The definition of cGOFs provides new insights into prokaryotic genome organization and efficient guidance for genome assembly and analysis. Copyright © 2014 Kang et al.

Integrated Module and Gene-Specific Regulatory Inference Implicates Upstream Signaling Networks

PubMed Central

Roy, Sushmita; Lagree, Stephen; Hou, Zhonggang; Thomson, James A.; Stewart, Ron; Gasch, Audrey P.

2013-01-01

Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development. PMID:24146602

Immune activation of the host cell induces drug tolerance in Mycobacterium tuberculosis both in vitro and in vivo

PubMed Central

Liu, Yancheng; Tan, Shumin; Huang, Lu; Abramovitch, Robert B.; Rohde, Kyle H.; Zimmerman, Matthew D.; Chen, Chao; Dartois, Véronique; VanderVen, Brian C.

2016-01-01

Successful chemotherapy against Mycobacterium tuberculosis (Mtb) must eradicate the bacterium within the context of its host cell. However, our understanding of the impact of this environment on antimycobacterial drug action remains incomplete. Intriguingly, we find that Mtb in myeloid cells isolated from the lungs of experimentally infected mice exhibit tolerance to both isoniazid and rifampin to a degree proportional to the activation status of the host cells. These data are confirmed by in vitro infections of resting versus activated macrophages where cytokine-mediated activation renders Mtb tolerant to four frontline drugs. Transcriptional analysis of intracellular Mtb exposed to drugs identified a set of genes common to all four drugs. The data imply a causal linkage between a loss of fitness caused by drug action and Mtb’s sensitivity to host-derived stresses. Interestingly, the environmental context exerts a more dominant impact on Mtb gene expression than the pressure on the drugs’ primary targets. Mtb’s stress responses to drugs resemble those mobilized after cytokine activation of the host cell. Although host-derived stresses are antimicrobial in nature, they negatively affect drug efficacy. Together, our findings demonstrate that the macrophage environment dominates Mtb’s response to drug pressure and suggest novel routes for future drug discovery programs. PMID:27114608

Identification of cis-suppression of human disease mutations by comparative genomics.

PubMed

Jordan, Daniel M; Frangakis, Stephan G; Golzio, Christelle; Cassa, Christopher A; Kurtzberg, Joanne; Davis, Erica E; Sunyaev, Shamil R; Katsanis, Nicholas

2015-08-13

Patterns of amino acid conservation have served as a tool for understanding protein evolution. The same principles have also found broad application in human genomics, driven by the need to interpret the pathogenic potential of variants in patients. Here we performed a systematic comparative genomics analysis of human disease-causing missense variants. We found that an appreciable fraction of disease-causing alleles are fixed in the genomes of other species, suggesting a role for genomic context. We developed a model of genetic interactions that predicts most of these to be simple pairwise compensations. Functional testing of this model on two known human disease genes revealed discrete cis amino acid residues that, although benign on their own, could rescue the human mutations in vivo. This approach was also applied to ab initio gene discovery to support the identification of a de novo disease driver in BTG2 that is subject to protective cis-modification in more than 50 species. Finally, on the basis of our data and models, we developed a computational tool to predict candidate residues subject to compensation. Taken together, our data highlight the importance of cis-genomic context as a contributor to protein evolution; they provide an insight into the complexity of allele effect on phenotype; and they are likely to assist methods for predicting allele pathogenicity.

Identification of upstream transcription factors (TFs) for expression signature genes in breast cancer.

PubMed

Zang, Hongyan; Li, Ning; Pan, Yuling; Hao, Jingguang

2017-03-01

Breast cancer is a common malignancy among women with a rising incidence. Our intention was to detect transcription factors (TFs) for deeper understanding of the underlying mechanisms of breast cancer. Integrated analysis of gene expression datasets of breast cancer was performed. Then, functional annotation of differentially expressed genes (DEGs) was conducted, including Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, TFs were identified and a global transcriptional regulatory network was constructed. Seven publically available GEO datasets were obtained, and a set of 1196 DEGs were identified (460 up-regulated and 736 down-regulated). Functional annotation results showed that cell cycle was the most significantly enriched pathway, which was consistent with the fact that cell cycle is closely related to various tumors. Fifty-three differentially expressed TFs were identified, and the regulatory networks consisted of 817 TF-target interactions between 46 TFs and 602 DEGs in the context of breast cancer. Top 10 TFs covering the most downstream DEGs were SOX10, NFATC2, ZNF354C, ARID3A, BRCA1, FOXO3, GATA3, ZEB1, HOXA5 and EGR1. The transcriptional regulatory networks could enable a better understanding of regulatory mechanisms of breast cancer pathology and provide an opportunity for the development of potential therapy.

Modulation of Immune Signaling and Metabolism Highlights Host and Fungal Transcriptional Responses in Mouse Models of Invasive Pulmonary Aspergillosis.

PubMed

Kale, Shiv D; Ayubi, Tariq; Chung, Dawoon; Tubau-Juni, Nuria; Leber, Andrew; Dang, Ha X; Karyala, Saikumar; Hontecillas, Raquel; Lawrence, Christopher B; Cramer, Robert A; Bassaganya-Riera, Josep

2017-12-06

Incidences of invasive pulmonary aspergillosis, an infection caused predominantly by Aspergillus fumigatus, have increased due to the growing number of immunocompromised individuals. While A. fumigatus is reliant upon deficiencies in the host to facilitate invasive disease, the distinct mechanisms that govern the host-pathogen interaction remain enigmatic, particularly in the context of distinct immune modulating therapies. To gain insights into these mechanisms, RNA-Seq technology was utilized to sequence RNA derived from lungs of 2 clinically relevant, but immunologically distinct murine models of IPA on days 2 and 3 post inoculation when infection is established and active disease present. Our findings identify notable differences in host gene expression between the chemotherapeutic and steroid models at the interface of immunity and metabolism. RT-qPCR verified model specific and nonspecific expression of 23 immune-associated genes. Deep sequencing facilitated identification of highly expressed fungal genes. We utilized sequence similarity and gene expression to categorize the A. fumigatus putative in vivo secretome. RT-qPCR suggests model specific gene expression for nine putative fungal secreted proteins. Our analysis identifies contrasting responses by the host and fungus from day 2 to 3 between the two models. These differences may help tailor the identification, development, and deployment of host- and/or fungal-targeted therapeutics.

An Efficient Test for Gene-Environment Interaction in Generalized Linear Mixed Models with Family Data.

PubMed

Mazo Lopera, Mauricio A; Coombes, Brandon J; de Andrade, Mariza

2017-09-27

Gene-environment (GE) interaction has important implications in the etiology of complex diseases that are caused by a combination of genetic factors and environment variables. Several authors have developed GE analysis in the context of independent subjects or longitudinal data using a gene-set. In this paper, we propose to analyze GE interaction for discrete and continuous phenotypes in family studies by incorporating the relatedness among the relatives for each family into a generalized linear mixed model (GLMM) and by using a gene-based variance component test. In addition, we deal with collinearity problems arising from linkage disequilibrium among single nucleotide polymorphisms (SNPs) by considering their coefficients as random effects under the null model estimation. We show that the best linear unbiased predictor (BLUP) of such random effects in the GLMM is equivalent to the ridge regression estimator. This equivalence provides a simple method to estimate the ridge penalty parameter in comparison to other computationally-demanding estimation approaches based on cross-validation schemes. We evaluated the proposed test using simulation studies and applied it to real data from the Baependi Heart Study consisting of 76 families. Using our approach, we identified an interaction between BMI and the Peroxisome Proliferator Activated Receptor Gamma ( PPARG ) gene associated with diabetes.

Functional analysis of rare variants in mismatch repair proteins augments results from computation-based predictive methods

PubMed Central

Arora, Sanjeevani; Huwe, Peter J.; Sikder, Rahmat; Shah, Manali; Browne, Amanda J.; Lesh, Randy; Nicolas, Emmanuelle; Deshpande, Sanat; Hall, Michael J.; Dunbrack, Roland L.; Golemis, Erica A.

2017-01-01

ABSTRACT The cancer-predisposing Lynch Syndrome (LS) arises from germline mutations in DNA mismatch repair (MMR) genes, predominantly MLH1, MSH2, MSH6, and PMS2. A major challenge for clinical diagnosis of LS is the frequent identification of variants of uncertain significance (VUS) in these genes, as it is often difficult to determine variant pathogenicity, particularly for missense variants. Generic programs such as SIFT and PolyPhen-2, and MMR gene-specific programs such as PON-MMR and MAPP-MMR, are often used to predict deleterious or neutral effects of VUS in MMR genes. We evaluated the performance of multiple predictive programs in the context of functional biologic data for 15 VUS in MLH1, MSH2, and PMS2. Using cell line models, we characterized VUS predicted to range from neutral to pathogenic on mRNA and protein expression, basal cellular viability, viability following treatment with a panel of DNA-damaging agents, and functionality in DNA damage response (DDR) signaling, benchmarking to wild-type MMR proteins. Our results suggest that the MMR gene-specific classifiers do not always align with the experimental phenotypes related to DDR. Our study highlights the importance of complementary experimental and computational assessment to develop future predictors for the assessment of VUS. PMID:28494185

Induction of the neural crest state: Control of stem cell attributes by gene regulatory, post-transcriptional and epigenetic interactions

PubMed Central

Prasad, Maneeshi S.; Sauka-Spengler, Tatjana; LaBonne, Carole

2012-01-01

Neural crest cells are a population of multipotent stem cell-like progenitors that arise at the neural plate border in vertebrates, migrate extensively, and give rise to diverse derivatives such as melanocytes, craniofacial cartilage and bone, smooth muscle, peripheral and enteric neurons and glia. The neural crest gene regulatory network (NC-GRN) includes a number of key factors that are used reiteratively to control multiple steps in the development of neural crest cells, including the acquisition of stem cell attributes. It is therefore essential to understand the mechanisms that control the distinct functions of such reiteratively used factors in different cellular contexts. The context-dependent control of neural crest specification is achieved through combinatorial interaction with other factors, post-transcriptional and post-translational modifications, and the epigenetic status and chromatin state of target genes. Here we review the current understanding of the NC-GRN, including the role of the neural crest specifiers, their links to the control of “stemness,” and their dynamic context-dependent regulation during the formation of neural crest progenitors. PMID:22583479

DCGL v2.0: an R package for unveiling differential regulation from differential co-expression.

PubMed

Yang, Jing; Yu, Hui; Liu, Bao-Hong; Zhao, Zhongming; Liu, Lei; Ma, Liang-Xiao; Li, Yi-Xue; Li, Yuan-Yuan

2013-01-01

Differential co-expression analysis (DCEA) has emerged in recent years as a novel, systematic investigation into gene expression data. While most DCEA studies or tools focus on the co-expression relationships among genes, some are developing a potentially more promising research domain, differential regulation analysis (DRA). In our previously proposed R package DCGL v1.0, we provided functions to facilitate basic differential co-expression analyses; however, the output from DCGL v1.0 could not be translated into differential regulation mechanisms in a straightforward manner. To advance from DCEA to DRA, we upgraded the DCGL package from v1.0 to v2.0. A new module named "Differential Regulation Analysis" (DRA) was designed, which consists of three major functions: DRsort, DRplot, and DRrank. DRsort selects differentially regulated genes (DRGs) and differentially regulated links (DRLs) according to the transcription factor (TF)-to-target information. DRrank prioritizes the TFs in terms of their potential relevance to the phenotype of interest. DRplot graphically visualizes differentially co-expressed links (DCLs) and/or TF-to-target links in a network context. In addition to these new modules, we streamlined the codes from v1.0. The evaluation results proved that our differential regulation analysis is able to capture the regulators relevant to the biological subject. With ample functions to facilitate differential regulation analysis, DCGL v2.0 was upgraded from a DCEA tool to a DRA tool, which may unveil the underlying differential regulation from the observed differential co-expression. DCGL v2.0 can be applied to a wide range of gene expression data in order to systematically identify novel regulators that have not yet been documented as critical. DCGL v2.0 package is available at http://cran.r-project.org/web/packages/DCGL/index.html or at our project home page http://lifecenter.sgst.cn/main/en/dcgl.jsp.

Aberration hubs in protein interaction networks highlight actionable targets in cancer.

PubMed

Karimzadeh, Mehran; Jandaghi, Pouria; Papadakis, Andreas I; Trainor, Sebastian; Rung, Johan; Gonzàlez-Porta, Mar; Scelo, Ghislaine; Vasudev, Naveen S; Brazma, Alvis; Huang, Sidong; Banks, Rosamonde E; Lathrop, Mark; Najafabadi, Hamed S; Riazalhosseini, Yasser

2018-05-18

Despite efforts for extensive molecular characterization of cancer patients, such as the international cancer genome consortium (ICGC) and the cancer genome atlas (TCGA), the heterogeneous nature of cancer and our limited knowledge of the contextual function of proteins have complicated the identification of targetable genes. Here, we present Aberration Hub Analysis for Cancer (AbHAC) as a novel integrative approach to pinpoint aberration hubs, i.e. individual proteins that interact extensively with genes that show aberrant mutation or expression. Our analysis of the breast cancer data of the TCGA and the renal cancer data from the ICGC shows that aberration hubs are involved in relevant cancer pathways, including factors promoting cell cycle and DNA replication in basal-like breast tumors, and Src kinase and VEGF signaling in renal carcinoma. Moreover, our analysis uncovers novel functionally relevant and actionable targets, among which we have experimentally validated abnormal splicing of spleen tyrosine kinase as a key factor for cell proliferation in renal cancer. Thus, AbHAC provides an effective strategy to uncover novel disease factors that are only identifiable by examining mutational and expression data in the context of biological networks.

Transcriptional Profiling of Midguts Prepared from Trypanosoma/T. congolense-Positive Glossina palpalis palpalis Collected from Two Distinct Cameroonian Foci: Coordinated Signatures of the Midguts’ Remodeling As T. congolense-Supportive Niches

PubMed Central

Tsagmo Ngoune, Jean M.; Njiokou, Flobert; Loriod, Béatrice; Kame-Ngasse, Ginette; Fernandez-Nunez, Nicolas; Rioualen, Claire; van Helden, Jacques; Geiger, Anne

2017-01-01

Our previous transcriptomic analysis of Glossina palpalis gambiensis experimentally infected or not with Trypanosoma brucei gambiense aimed to detect differentially expressed genes (DEGs) associated with infection. Specifically, we selected candidate genes governing tsetse fly vector competence that could be used in the context of an anti-vector strategy, to control human and/or animal trypanosomiasis. The present study aimed to verify whether gene expression in field tsetse flies (G. p. palpalis) is modified in response to natural infection by trypanosomes (T. congolense), as reported when insectary-raised flies (G. p. gambiensis) are experimentally infected with T. b. gambiense. This was achieved using the RNA-seq approach, which identified 524 DEGs in infected vs. non-infected tsetse flies, including 285 downregulated genes and 239 upregulated genes (identified using DESeq2). Several of these genes were highly differentially expressed, with log2 fold change values in the vicinity of either +40 or −40. Downregulated genes were primarily involved in transcription/translation processes, whereas encoded upregulated genes governed amino acid and nucleotide biosynthesis pathways. The BioCyc metabolic pathways associated with infection also revealed that downregulated genes were mainly involved in fly immunity processes. Importantly, our study demonstrates that data on the molecular cross-talk between the host and the parasite (as well as the always present fly microbiome) recorded from an experimental biological model has a counterpart in field flies, which in turn validates the use of experimental host/parasite couples. PMID:28804485

Juxtaposed Polycomb complexes co-regulate vertebral identity.

PubMed

Kim, Se Young; Paylor, Suzanne W; Magnuson, Terry; Schumacher, Armin

2006-12-01

Best known as epigenetic repressors of developmental Hox gene transcription, Polycomb complexes alter chromatin structure by means of post-translational modification of histone tails. Depending on the cellular context, Polycomb complexes of diverse composition and function exhibit cooperative interaction or hierarchical interdependency at target loci. The present study interrogated the genetic, biochemical and molecular interaction of BMI1 and EED, pivotal constituents of heterologous Polycomb complexes, in the regulation of vertebral identity during mouse development. Despite a significant overlap in dosage-sensitive homeotic phenotypes and co-repression of a similar set of Hox genes, genetic analysis implicated eed and Bmi1 in parallel pathways, which converge at the level of Hox gene regulation. Whereas EED and BMI1 formed separate biochemical entities with EzH2 and Ring1B, respectively, in mid-gestation embryos, YY1 engaged in both Polycomb complexes. Strikingly, methylated lysine 27 of histone H3 (H3-K27), a mediator of Polycomb complex recruitment to target genes, stably associated with the EED complex during the maintenance phase of Hox gene repression. Juxtaposed EED and BMI1 complexes, along with YY1 and methylated H3-K27, were detected in upstream regulatory regions of Hoxc8 and Hoxa5. The combined data suggest a model wherein epigenetic and genetic elements cooperatively recruit and retain juxtaposed Polycomb complexes in mammalian Hox gene clusters toward co-regulation of vertebral identity.

The CAPN10 Gene Is Associated with Insulin Resistance Phenotypes in the Spanish Population

PubMed Central

Sáez, María E.; González-Sánchez, José L.; Ramírez-Lorca, Reposo; Martínez-Larrad, María T.; Zabena, Carina; González, Alejandro; Morón, Francisco J.; Ruiz, Agustín; Serrano-Ríos, Manuel

2008-01-01

Cardiovascular disease is the leading cause of morbidity and mortality in the industrialized world. Familial aggregation of cardiovascular risk factors is a frequent finding, but genetic factors affecting its presentation are still poorly understood. The calpain 10 gene (CAPN10) has been associated with type 2 diabetes (T2DM), a complex metabolic disorder with increased risk of cardiovascular disease. Moreover, the CAPN10 gene has been associated with the presence of metabolic syndrome (MS) in T2DM and in polycystic ovary syndrome (PCOS). In this work, we have analysed whether the polymorphisms UCSNP44, -43, -19 and -63 are related to several cardiovascular risk factors in the context of MS. Molecular analysis of CAPN10 gene was performed in 899 individuals randomly chosen from a cross-sectional population-based epidemiological survey. We have found that CAPN10 gene in our population is mainly associated with two indicators of the presence of insulin resistance: glucose levels two hours after a 75-g oral glucose tolerance test (OGTT) and HOMA values, although cholesterol levels and blood pressure values are also influenced by CAPN10 variants. In addition, the 1221/1121 haplogenotype is under-represented in individuals that fulfil the International Diabetes Federation (IDF) diagnostic criteria for MS. Our results suggest that CAPN10 gene is associated with insulin resistance phenotypes in the Spanish population. PMID:18698425

Transcriptome analysis of olive flounder (Paralichthys olivaceus) head kidney infected with moderate and high virulent strains of infectious viral hemorrhagic septicaemia virus (VHSV).

PubMed

Hwang, Jee Youn; Markkandan, Kesavan; Kwon, Mun Gyeong; Seo, Jung Soo; Yoo, Seung-Il; Hwang, Seong Don; Son, Maeng-Hyun; Park, Junhyung

2018-05-01

Olive flounder (Paralichthys olivaceus) is one of the most valuable marine aquatic species in South Korea and faces tremendous exposure to the viral hemorrhagic septicemia virus (VHSV). Given the growing importance of flounder, it is therefore essential to understand the host defense of P. olivaceus against VHSV infection, but studies on its immune mechanism are hindered by the lack of genomic resources. In this study, the P. olivaceus was infected with disease-causing VHSV isolates, ADC-VHS2012-11 and ADC-VHS2014-5 which showed moderate virulent (20% mortality) and high virulent (65% mortality), in order to investigate the effect of difference in pathogenicity in head kidney during 1, 3, 7 days of post-infection using Illumina sequencing. After removing low-quality sequences, we obtained 144,933,160 high quality reads from thirty-six libraries which were further assembled into 53,384 unigenes with an average length of 563 bp with a range of 200 to 9605 bp. Transcriptome annotation revealed that 30,475 unigenes with a cut-off e-value of 10 -5 were functionally annotated. In total, 10,046 unigenes were clustered into 26 functional categories by searching against the eggNOG database, and 22,233 unigenes to 52 GO terms. In addition, 12,985 unigenes were grouped into 387 KEGG pathways. Among the 13,270 differently expressed genes, 6578 and 6692 were differentially expressed only in moderate and high virulent, respectively. Based on our sequence analysis, many candidate genes with fundamental roles in innate immune system including, pattern recognition receptors (TLRs & RLRs), Mx, complement proteins, lectins, and cytokines (chemokines, IFN, IRF, IL, TRF) were differentially expressed. Furthermore, GO enrichment analysis for these genes revealed gene response to defense response to virus, apoptotic process and transcription factor activity. In summary, this study identifies several putative immune pathways and candidate genes deserving further investigation in the context of novel gene discovery, gene expression and regulation studies and lays the foundation for fish immunology especially in P. olivaceus against VHSV. Copyright © 2018. Published by Elsevier Ltd.

Deciphering the Origin of Dogs: From Fossils to Genomes.

PubMed

Freedman, Adam H; Wayne, Robert K

2017-02-08

Understanding the timing and geographic context of dog origins is a crucial component for understanding human history, as well as the evolutionary context in which the morphological and behavioral divergence of dogs from wolves occurred. A substantial challenge to understanding domestication is that dogs have experienced a complicated demographic history. An initial severe bottleneck was associated with domestication followed by postdivergence gene flow between dogs and wolves, as well as population expansions, contractions, and replacements. In addition, because the domestication of dogs occurred in the relatively recent past, much of the observed polymorphism may be shared between dogs and wolves, limiting the power to distinguish between alternative models of dog history. Greater insight into the domestication process will require explicit tests of alternative models of domestication through the joint analysis of whole genomes from modern lineages and ancient wolves and dogs from across Eurasia.

Comprehensive discovery of subsample gene expression components by information explanation: therapeutic implications in cancer.

PubMed

Pepke, Shirley; Ver Steeg, Greg

2017-03-15

De novo inference of clinically relevant gene function relationships from tumor RNA-seq remains a challenging task. Current methods typically either partition patient samples into a few subtypes or rely upon analysis of pairwise gene correlations that will miss some groups in noisy data. Leveraging higher dimensional information can be expected to increase the power to discern targetable pathways, but this is commonly thought to be an intractable computational problem. In this work we adapt a recently developed machine learning algorithm for sensitive detection of complex gene relationships. The algorithm, CorEx, efficiently optimizes over multivariate mutual information and can be iteratively applied to generate a hierarchy of relatively independent latent factors. The learned latent factors are used to stratify patients for survival analysis with respect to both single factors and combinations. These analyses are performed and interpreted in the context of biological function annotations and protein network interactions that might be utilized to match patients to multiple therapies. Analysis of ovarian tumor RNA-seq samples demonstrates the algorithm's power to infer well over one hundred biologically interpretable gene cohorts, several times more than standard methods such as hierarchical clustering and k-means. The CorEx factor hierarchy is also informative, with related but distinct gene clusters grouped by upper nodes. Some latent factors correlate with patient survival, including one for a pathway connected with the epithelial-mesenchymal transition in breast cancer that is regulated by a microRNA that modulates epigenetics. Further, combinations of factors lead to a synergistic survival advantage in some cases. In contrast to studies that attempt to partition patients into a small number of subtypes (typically 4 or fewer) for treatment purposes, our approach utilizes subgroup information for combinatoric transcriptional phenotyping. Considering only the 66 gene expression groups that are found to both have significant Gene Ontology enrichment and are small enough to indicate specific drug targets implies a computational phenotype for ovarian cancer that allows for 3 66 possible patient profiles, enabling truly personalized treatment. The findings here demonstrate a new technique that sheds light on the complexity of gene expression dependencies in tumors and could eventually enable the use of patient RNA-seq profiles for selection of personalized and effective cancer treatments.

Kinetics of lipid-nanoparticle-mediated intracellular mRNA delivery and function

NASA Astrophysics Data System (ADS)

Zhdanov, Vladimir P.

2017-10-01

mRNA delivery into cells forms the basis for one of the new and promising ways to treat various diseases. Among suitable carriers, lipid nanoparticles (LNPs) with a size of about 100 nm are now often employed. Despite high current interest in this area, the understanding of the basic details of LNP-mediated mRNA delivery and function is limited. To clarify the kinetics of mRNA release from LNPs, the author uses three generic models implying (i) exponential, (ii) diffusion-controlled, and (iii) detachment-controlled kinetic regimes, respectively. Despite the distinct differences in these kinetics, the associated transient kinetics of mRNA translation to the corresponding protein and its degradation are shown to be not too sensitive to the details of the mRNA delivery by LNPs (or other nanocarriers). In addition, the author illustrates how this protein may temporarily influence the expression of one gene or a few equivalent genes. The analysis includes positive or negative regulation of the gene transcription via the attachment of the protein without or with positive or negative feedback in the gene expression. Stable, bistable, and oscillatory schemes have been scrutinized in this context.

The patent is political: the consequences of patenting the BRCA genes in Britain.

PubMed

Parthasarathy, Shobita

2005-01-01

The paper explores the attempt by an American biotechnology company, Myriad Genetics, to use its patent rights over the BRCA genes to transfer its technology of genetic testing for breast and ovarian cancer to Britain. It also investigates the responses of British scientists, health care professionals and patient advocates to this attempted technology transfer. This paper is based on approximately 100 in-depth interviews, document analysis and ethnographic observation conducted in the United States and Britain from 1998 to 2001. The BRCA gene patents inspired political resistance and mobilized opposition to the patenting of genes in general. They also provided an opportunity for the British to assert their national identity as they argued that a British BRCA testing service needed to be available within the context of the National Health Service to all citizens equally. Patents are not only legal documents and technical descriptions, but political tools as well. As they are increasingly deemed vital to economic globalization, patents have become mobilizing tools for anti-globalization activists and non-governmental organizations from less developed countries, and for asserting local and national identities. Copyright 2005 S. Karger AG, Basel

Transcriptome analysis of a wild bird reveals physiological responses to the urban environment

PubMed Central

Watson, Hannah; Videvall, Elin; Andersson, Martin N.; Isaksson, Caroline

2017-01-01

Identifying the molecular basis of environmentally induced phenotypic variation presents exciting opportunities for furthering our understanding of how ecological processes and the environment can shape the phenotype. Urban and rural environments present free-living organisms with different challenges and opportunities, which have marked consequences for the phenotype, yet little is known about responses at the molecular level. We characterised transcriptomes from an urban and a rural population of great tits Parus major, demonstrating striking differences in gene expression profiles in both blood and liver tissues. Differentially expressed genes had functions related to immune and inflammatory responses, detoxification, protection against oxidative stress, lipid metabolism, and regulation of gene expression. Many genes linked to stress responses were expressed at higher levels in the urban birds, in accordance with our prediction that urban animals are exposed to greater environmental stress. This is one of the first studies to reveal transcriptional differences between urban- and rural-dwelling animals and suggests an important role for epigenetics in mediating environmentally induced physiological variation. The study provides valuable resources for developing further in-depth studies of the mechanisms driving phenotypic variation in the urban context at larger spatial and temporal scales. PMID:28290496

Assessment of Direct-to-Consumer Genetic Testing Policy in Korea Based on Consumer Preference.

PubMed

Jeong, Gicheol

2017-01-01

In June 2016, Korea permitted direct-to-consumer genetic testing (DTC-GT) on 42 genes. However, both the market and industry have not yet been fully activated. Considering the aforementioned context, this study provides important insights. The Korean DTC-GT policy assessment is based on consumer preference analysis using a discrete choice experiment. In August 2016, a web-based survey was conducted to collect data from 1,200 respondents. The estimation results show that consumers prefer a DTC-GT product that is cheap, tests various items or genes, offers accurate test results, and guarantees the confidentiality of all information. However, consumers are not entirely satisfied by current DTC-GT products due to the existence of insufficient and/or inadequate policies. First, the permitted testing of 42 genes is insufficient to satisfy consumers' curiosity regarding their genes. Second, the accuracy of the DTC-GT products has not been fully verified, assessed, and communicated to consumers. Finally, regulatory loopholes that allow information leaks in the DTC-GT process can occur. These findings imply that DTC-GT requires an improvement in government policy-making criteria and the implementation of practical measures to guarantee test accuracy and genetic information. © 2017 S. Karger AG, Basel.

Role of habitat and great oxidation event on the occurrence of three multisubunit inorganic carbon-uptake systems in cyanobacteria.

PubMed

Tomar, Vandana; Sidhu, Gurpreet Kaur; Nogia, Panchsheela; Mehrotra, Rajesh; Mehrotra, Sandhya

2016-03-01

The oxygenase reaction catalyzed by RuBisCO became an issue only after the evolution of the oxygenic photosynthesis in cyanobacteria. Several strategies were developed by autotrophic organisms as an evolutionary response to increase oxygen levels to help RuBisCO maximize its net carboxylation rate. One of the crucial advancements in this context was the development of more efficient inorganic carbon transporters which could help in increasing the influx of inorganic carbon (Ci) at the site of CO₂ fixation.We conducted a survey to find out the genes coding for cyanobacterial Ci transporters in 40 cyanobacterial phyla with respect to transporters present in Gloeobacter violaceous PCC 7421, an early-diverging cyanobacterium. An attempt was also made to correlate the prevalence of the kind of transporter present in the species with its habitat. Basically, two types of cyanobacterial inorganic carbon transporters exist, i.e. bicarbonate transporters and CO₂-uptake systems. The transporters also show variation in context to their structure as some exist as single subunit proteins (BicA and SbtA), while others exist as multisubunit proteins (namely BCT1, NdhI₃ and NdhI₄). The phylogeny and dist ribution of the former have been extensively studied and the present analysis provides an insight into the latter ones. The in silico analysis of the genes under study revealed that their distribution was greatly influenced by the habitat and major environmental changes such as the great oxidation event (GOE) in the course of their evolution.

Phylogeny and origin of 82 zygomycetes from all 54 genera of the Mucorales and Mortierellales based on combined analysis of actin and translation elongation factor EF-1alpha genes.

PubMed

Voigt, K; Wöstemeyer, J

2001-05-30

True fungi (Eumycota) are heterotrophic eukaryotic microorganisms encompassing ascomycetes, basidiomycetes, chytridiomycetes and zygomycetes. The natural systematics of the latter group, Zygomycota, are very poorly understood due to the lack of distinguishing morphological characters. We have determined sequences for the nuclear-encoded genes actin (act) from 82 zygomycetes representing all 54 currently recognized genera from the two zygomycetous orders Mucorales and Mortierellales. We also determined sequences for translation elongation factor EF-1alpha (tef) from 16 zygomycetes (total of 96,837 bp). Phylogenetic analysis in the context of available sequence data (total 2,062 nucleotide positions per species) revealed that current classification schemes for the mucoralean fungi are highly unnatural at the family and, to a large extent, at the genus level. The data clearly indicate a deep, ancient and distinct dichotomy of the orders Mucorales and Mortierellales, which are recognized only in some zygomycete systems. Yet at the same time the data show that two genera - Umbelopsis and Micromucor - previously placed within the Mortierellales on the basis of their weakly developed columella (a morphological structure of the sporangiophore well-developed within all Mucorales) are in fact members of the Mucorales. Phylogenetic analyses of the encoded amino acid sequences in the context of homologues from eukaryotes and archaebacterial outgroups indicate that the Eumycota studied here are a natural group but provide little or no support for the monophyly of either zygomycetes, ascomycetes or basidiomycetes. The data clearly indicate that a complete revision of zygomycete natural systematics is necessary.

CAFÉ-Map: Context Aware Feature Mapping for mining high dimensional biomedical data.

PubMed

Minhas, Fayyaz Ul Amir Afsar; Asif, Amina; Arif, Muhammad

2016-12-01

Feature selection and ranking is of great importance in the analysis of biomedical data. In addition to reducing the number of features used in classification or other machine learning tasks, it allows us to extract meaningful biological and medical information from a machine learning model. Most existing approaches in this domain do not directly model the fact that the relative importance of features can be different in different regions of the feature space. In this work, we present a context aware feature ranking algorithm called CAFÉ-Map. CAFÉ-Map is a locally linear feature ranking framework that allows recognition of important features in any given region of the feature space or for any individual example. This allows for simultaneous classification and feature ranking in an interpretable manner. We have benchmarked CAFÉ-Map on a number of toy and real world biomedical data sets. Our comparative study with a number of published methods shows that CAFÉ-Map achieves better accuracies on these data sets. The top ranking features obtained through CAFÉ-Map in a gene profiling study correlate very well with the importance of different genes reported in the literature. Furthermore, CAFÉ-Map provides a more in-depth analysis of feature ranking at the level of individual examples. CAFÉ-Map Python code is available at: http://faculty.pieas.edu.pk/fayyaz/software.html#cafemap . The CAFÉ-Map package supports parallelization and sparse data and provides example scripts for classification. This code can be used to reconstruct the results given in this paper. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hox cluster polarity in early transcriptional availability: a high order regulatory level of clustered Hox genes in the mouse.

PubMed

Roelen, Bernard A J; de Graaff, Wim; Forlani, Sylvie; Deschamps, Jacqueline

2002-11-01

The molecular mechanism underlying the 3' to 5' polarity of induction of mouse Hox genes is still elusive. While relief from a cluster-encompassing repression was shown to lead to all Hoxd genes being expressed like the 3'most of them, Hoxd1 (Kondo and Duboule, 1999), the molecular basis of initial activation of this 3'most gene, is not understood yet. We show that, already before primitive streak formation, prior to initial expression of the first Hox gene, a dramatic transcriptional stimulation of the 3'most genes, Hoxb1 and Hoxb2, is observed upon a short pulse of exogenous retinoic acid (RA), whereas it is not in the case for more 5', cluster-internal, RA-responsive Hoxb genes. In contrast, the RA-responding Hoxb1lacZ transgene that faithfully mimics the endogenous gene (Marshall et al., 1994) did not exhibit the sensitivity of Hoxb1 to precocious activation. We conclude that polarity in initial activation of Hoxb genes reflects a greater availability of 3'Hox genes for transcription, suggesting a pre-existing (susceptibility to) opening of the chromatin structure at the 3' extremity of the cluster. We discuss the data in the context of prevailing models involving differential chromatin opening in the directionality of clustered Hox gene transcription, and regarding the importance of the cluster context for correct timing of initial Hox gene expression.Interestingly, Cdx1 manifested the same early transcriptional availability as Hoxb1. Copyright 2002 Elsevier Science Ireland Ltd.

Insights into rubber biosynthesis from transcriptome analysis of Hevea brasiliensis latex.

PubMed

Chow, Keng-See; Wan, Kiew-Lian; Isa, Mohd Noor Mat; Bahari, Azlina; Tan, Siang-Hee; Harikrishna, K; Yeang, Hoong-Yeet

2007-01-01

Hevea brasiliensis is the most widely cultivated species for commercial production of natural rubber (cis-polyisoprene). In this study, 10,040 expressed sequence tags (ESTs) were generated from the latex of the rubber tree, which represents the cytoplasmic content of a single cell type, in order to analyse the latex transcription profile with emphasis on rubber biosynthesis-related genes. A total of 3,441 unique transcripts (UTs) were obtained after quality editing and assembly of EST sequences. Functional classification of UTs according to the Gene Ontology convention showed that 73.8% were related to genes of unknown function. Among highly expressed ESTs, a significant proportion encoded proteins related to rubber biosynthesis and stress or defence responses. Sequences encoding rubber particle membrane proteins (RPMPs) belonging to three protein families accounted for 12% of the ESTs. Characterization of these ESTs revealed nine RPMP variants (7.9-27 kDa) including the 14 kDa REF (rubber elongation factor) and 22 kDa SRPP (small rubber particle protein). The expression of multiple RPMP isoforms in latex was shown using antibodies against REF and SRPP. Both EST and quantitative reverse transcription-PCR (QRT-PCR) analyses demonstrated REF and SRPP to be the most abundant transcripts in latex. Besides rubber biosynthesis, comparative sequence analysis showed that the RPMPs are highly similar to sequences in the plant kingdom having stress-related functions. Implications of the RPMP function in cis-polyisoprene biosynthesis in the context of transcript abundance and differential gene expression are discussed.

ABCA4 midigenes reveal the full splice spectrum of all reported noncanonical splice site variants in Stargardt disease.

PubMed

Sangermano, Riccardo; Khan, Mubeen; Cornelis, Stéphanie S; Richelle, Valerie; Albert, Silvia; Garanto, Alejandro; Elmelik, Duaa; Qamar, Raheel; Lugtenberg, Dorien; van den Born, L Ingeborgh; Collin, Rob W J; Cremers, Frans P M

2018-01-01

Stargardt disease is caused by variants in the ABCA4 gene, a significant part of which are noncanonical splice site (NCSS) variants. In case a gene of interest is not expressed in available somatic cells, small genomic fragments carrying potential disease-associated variants are tested for splice abnormalities using in vitro splice assays. We recently discovered that when using small minigenes lacking the proper genomic context, in vitro results do not correlate with splice defects observed in patient cells. We therefore devised a novel strategy in which a bacterial artificial chromosome was employed to generate midigenes, splice vectors of varying lengths (up to 11.7 kb) covering almost the entire ABCA4 gene. These midigenes were used to analyze the effect of all 44 reported and three novel NCSS variants on ABCA4 pre-mRNA splicing. Intriguingly, multi-exon skipping events were observed, as well as exon elongation and intron retention. The analysis of all reported NCSS variants in ABCA4 allowed us to reveal the nature of aberrant splicing events and to classify the severity of these mutations based on the residual fraction of wild-type mRNA. Our strategy to generate large overlapping splice vectors carrying multiple exons, creating a toolbox for robust and high-throughput analysis of splice variants, can be applied to all human genes. © 2018 Sangermano et al.; Published by Cold Spring Harbor Laboratory Press.

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci.

PubMed

Larson, Nicholas B; McDonnell, Shannon K; Fogarty, Zach; Larson, Melissa C; Cheville, John; Riska, Shaun; Baheti, Saurabh; Weber, Alexandra M; Nair, Asha A; Wang, Liang; O'Brien, Daniel; Davila, Jaime; Schaid, Daniel J; Thibodeau, Stephen N

2017-10-17

Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis -acting associations due to study limitations. While trans -eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans -eQTL associations are mediated by cis -regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis -mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans -eQTL associations that were significantly mediated by cis -regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B , and target trans -genes with known HNF response elements ( MIA2 , SRC , SEMA6A , KIF12 ). We additionally identified evidence of cis -acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1 . The majority of these cis -mediator relationships demonstrated trans -eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Quinolone Resistance Determinants of Clinical Salmonella Enteritidis in Thailand.

PubMed

Utrarachkij, Fuangfa; Nakajima, Chie; Changkwanyeun, Ruchirada; Siripanichgon, Kanokrat; Kongsoi, Siriporn; Pornruangwong, Srirat; Changkaew, Kanjana; Tsunoda, Risa; Tamura, Yutaka; Suthienkul, Orasa; Suzuki, Yasuhiko

2017-10-01

Salmonella Enteritidis has emerged as a global concern regarding quinolone resistance and invasive potential. Although quinolone-resistant S. Enteritidis has been observed with high frequency in Thailand, information on the mechanism of resistance acquisition is limited. To elucidate the mechanism, a total of 158 clinical isolates of nalidixic acid (NAL)-resistant S. Enteritidis were collected throughout Thailand, and the quinolone resistance determinants were investigated in the context of resistance levels to NAL, norfloxacin (NOR), and ciprofloxacin (CIP). The analysis of point mutations in type II topoisomerase genes and the detection of plasmid-mediated quinolone resistance genes showed that all but two harbored a gyrA mutation, the qnrS1 gene, or both. The most commonly affected codon in mutant gyrA was 87, followed by 83. Double codon mutation in gyrA was found in an isolate with high-level resistance to NAL, NOR, and CIP. A new mutation causing serine to isoleucine substitution at codon 83 was identified in eight isolates. In addition to eighteen qnrS1-carrying isolates showing nontypical quinolone resistance, one carrying both the qnrS1 gene and a gyrA mutation also showed a high level of resistance. Genotyping by multilocus variable number of tandem repeat analysis suggested a possible clonal expansion of NAL-resistant strains nationwide. Our data suggested that NAL-resistant isolates with single quinolone resistance determinant may potentially become fluoroquinolone resistant by acquiring secondary determinants. Restricted therapeutic and farming usage of quinolones is strongly recommended to prevent the emergence of fluoroquinolone-resistant isolates.

Evidence of cardiac involvement in the fetal inflammatory response syndrome: disruption of gene networks programming cardiac development in nonhuman primates.

PubMed

Mitchell, Timothy; MacDonald, James W; Srinouanpranchanh, Sengkeo; Bammler, Theodor K; Merillat, Sean; Boldenow, Erica; Coleman, Michelle; Agnew, Kathy; Baldessari, Audrey; Stencel-Baerenwald, Jennifer E; Tisoncik-Go, Jennifer; Green, Richard R; Gale, Michael J; Rajagopal, Lakshmi; Adams Waldorf, Kristina M

2018-04-01

Most early preterm births are associated with intraamniotic infection and inflammation, which can lead to systemic inflammation in the fetus. The fetal inflammatory response syndrome describes elevations in the fetal interleukin-6 level, which is a marker for inflammation and fetal organ injury. An understanding of the effects of inflammation on fetal cardiac development may lead to insight into the fetal origins of adult cardiovascular disease. The purpose of this study was to determine whether the fetal inflammatory response syndrome is associated with disruptions in gene networks that program fetal cardiac development. We obtained fetal cardiac tissue after necropsy from a well-described pregnant nonhuman primate model (pigtail macaque, Macaca nemestrina) of intrauterine infection (n=5) and controls (n=5). Cases with the fetal inflammatory response syndrome (fetal plasma interleukin-6 >11 pg/mL) were induced by either choriodecidual inoculation of a hypervirulent group B streptococcus strain (n=4) or intraamniotic inoculation of Escherichia coli (n=1). RNA and protein were extracted from fetal hearts and profiled by microarray and Luminex (Millipore, Billerica, MA) for cytokine analysis, respectively. Results were validated by quantitative reverse transcriptase polymerase chain reaction. Statistical and bioinformatics analyses included single gene analysis, gene set analysis, Ingenuity Pathway Analysis (Qiagen, Valencia, CA), and Wilcoxon rank sum. Severe fetal inflammation developed in the context of intraamniotic infection and a disseminated bacterial infection in the fetus. Interleukin-6 and -8 in fetal cardiac tissues were elevated significantly in fetal inflammatory response syndrome cases vs controls (P<.05). A total of 609 probe sets were expressed differentially (>1.5-fold change, P<.05) in the fetal heart (analysis of variance). Altered expression of select genes was validated by quantitative reverse transcriptase polymerase chain reaction that included several with known functions in cardiac injury, morphogenesis, angiogenesis, and tissue remodeling (eg, angiotensin I converting enzyme 2, STEAP family member 4, natriuretic peptide A, and secreted frizzled-related protein 4; all P<.05). Multiple gene sets and pathways that are involved in cardiac morphogenesis and vasculogenesis were downregulated significantly by gene set and Ingenuity Pathway Analysis (hallmark transforming growth factor beta signaling, cellular morphogenesis during differentiation, morphology of cardiovascular system; all P<.05). Disruption of gene networks for cardiac morphogenesis and vasculogenesis occurred in the preterm fetal heart of nonhuman primates with preterm labor, intraamniotic infection, and severe fetal inflammation. Inflammatory injury to the fetal heart in utero may contribute to the development of heart disease later in life. Development of preterm labor therapeutics must also target fetal inflammation to lessen organ injury and potential long-term effects on cardiac function. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed

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

2016-08-01

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

Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization

PubMed Central

Hiraishi, Kunihiko

2014-01-01

One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs. PMID:24587766

Of extracellular matrix, scaffolds, and signaling: Tissuearchitectureregulates development, homeostasis, and cancer

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

Nelson, Celeste M.; Bissell, Mina J.

2006-03-09

The microenvironment surrounding cells influences gene expression, such that a cell's behavior is largely determined by its interactions with the extracellular matrix, neighboring cells, and soluble cues released locally or by distant tissues. We describe the essential role of context and organ structure in directing mammary gland development and differentiated function, and in determining response to oncogenic insults including mutations. We expand on the concept of 'dynamic reciprocity' to present an integrated view of development, cancer, and aging, and posit that genes are like piano keys: while essential, it is the context that makes the music.

Multiple Testing in the Context of Gene Discovery in Sickle Cell Disease Using Genome-Wide Association Studies.

PubMed

Kuo, Kevin H M

2017-01-01

The issue of multiple testing, also termed multiplicity, is ubiquitous in studies where multiple hypotheses are tested simultaneously. Genome-wide association study (GWAS), a type of genetic association study that has gained popularity in the past decade, is most susceptible to the issue of multiple testing. Different methodologies have been employed to address the issue of multiple testing in GWAS. The purpose of the review is to examine the methodologies employed in dealing with multiple testing in the context of gene discovery using GWAS in sickle cell disease complications.

Gene expression allelic imbalance in ovine brown adipose tissue impacts energy homeostasis

PubMed Central

Ghazanfar, Shila; Vuocolo, Tony; Morrison, Janna L.; Nicholas, Lisa M.; McMillen, Isabella C.; Yang, Jean Y. H.; Buckley, Michael J.

2017-01-01

Heritable trait variation within a population of organisms is largely governed by DNA variations that impact gene transcription and protein function. Identifying genetic variants that affect complex functional traits is a primary aim of population genetics studies, especially in the context of human disease and agricultural production traits. The identification of alleles directly altering mRNA expression and thereby biological function is challenging due to difficulty in isolating direct effects of cis-acting genetic variations from indirect trans-acting genetic effects. Allele specific gene expression or allelic imbalance in gene expression (AI) occurring at heterozygous loci provides an opportunity to identify genes directly impacted by cis-acting genetic variants as indirect trans-acting effects equally impact the expression of both alleles. However, the identification of genes showing AI in the context of the expression of all genes remains a challenge due to a variety of technical and statistical issues. The current study focuses on the discovery of genes showing AI using single nucleotide polymorphisms as allelic reporters. By developing a computational and statistical process that addressed multiple analytical challenges, we ranked 5,809 genes for evidence of AI using RNA-Seq data derived from brown adipose tissue samples from a cohort of late gestation fetal lambs and then identified a conservative subgroup of 1,293 genes. Thus, AI was extensive, representing approximately 25% of the tested genes. Genes associated with AI were enriched for multiple Gene Ontology (GO) terms relating to lipid metabolism, mitochondrial function and the extracellular matrix. These functions suggest that cis-acting genetic variations causing AI in the population are preferentially impacting genes involved in energy homeostasis and tissue remodelling. These functions may contribute to production traits likely to be under genetic selection in the population. PMID:28665992

Combining Zebrafish and Mouse Models to Test the Function of Deubiquitinating Enzyme (Dubs) Genes in Development: Role of USP45 in the Retina.

PubMed

Toulis, Vasileios; Garanto, Alejandro; Marfany, Gemma

2016-01-01

Ubiquitination is a dynamic and reversible posttranslational modification. Much effort has been devoted to characterize the function of ubiquitin pathway genes in the cell context, but much less is known on their functional role in the development and maintenance of organs and tissues in the organism. In fact, several ubiquitin ligases and deubiquitinating enzymes (DUBs) are implicated in human pathological disorders, from cancer to neurodegeneration. The aim of our work is to explore the relevance of DUBs in retinal function in health and disease, particularly since some genes related to the ubiquitin or SUMO pathways cause retinal dystrophies, a group of rare diseases that affect 1:3000 individuals worldwide. We propose zebrafish as an extremely useful and informative genetic model to characterize the function of any particular gene in the retina, and thus complement the expression data from mouse. A preliminary characterization of gene expression in mouse retinas (RT-PCR and in situ hybridization) was performed to select particularly interesting genes, and we later replicated the experiments in zebrafish. As a proof of concept, we selected ups45 to be knocked down by morpholino injection in zebrafish embryos. Morphant phenotypic analysis showed moderate to severe eye morphological defects, with a defective formation of the retinal structures, therefore supporting the relevance of DUBs in the formation and differentiation of the vertebrate retina, and suggesting that genes encoding ubiquitin pathway enzymes are good candidates for causing hereditary retinal dystrophies.

Genetic determinants of prepubertal and pubertal growth and development.

PubMed

Thomis, Martine A; Towne, Bradford

2006-12-01

This article surveys the current general understanding of genetic influences on within- and between-population variation in growth and development in the context of establishing an International Growth Standard for Preadolescent and Adolescent Children. Traditional genetic epidemiologic analysis methods are reviewed, and evidence from family studies for genetic effects on different measures of growth and development is then presented. Findings from linkage and association studies seeking to identify specific genomic locations and allelic variants of genes influencing variation in growth and maturation are then summarized. Special mention is made of the need to study the interactions between genes and environments. At present, specific genes and polymorphisms contributing to variation in growth and maturation are only beginning to be identified. Larger genetic epidemiologic studies are needed in different parts of the world to better explore population differences in gene frequencies and gene-environment interactions. As advances continue to be made in molecular and statistical genetic methods, the genetic architecture of complex processes, including those of growth and development, will become better elucidated. For now, it can only be concluded that although the fundamental genetic underpinnings of the growth and development of children worldwide are likely to be essentially the same, there are also likely to be differences between populations in the frequencies of allelic gene variants that influence growth and maturation and in the nature of gene-environment interactions. This does not necessarily preclude an international growth reference, but it does have important implications for the form that such a reference might ultimately take.

The complete mitochondrial genome of Koerneria sudhausi (Diplogasteromorpha: Nematoda) supports monophyly of Diplogasteromorpha within Rhabditomorpha.

PubMed

Kim, Taeho; Kim, Jiyeon; Nadler, Steven A; Park, Joong-Ki

2016-05-01

Testing hypotheses of monophyly for different nematode groups in the context of broad representation of nematode diversity is central to understanding the patterns and processes of nematode evolution. Herein sequence information from mitochondrial genomes is used to test the monophyly of diplogasterids, which includes an important nematode model organism. The complete mitochondrial genome sequence of Koerneria sudhausi, a representative of Diplogasteromorpha, was determined and used for phylogenetic analyses along with 60 other nematode species. The mtDNA of K. sudhausi is comprised of 16,005 bp that includes 36 genes (12 protein-coding genes, 2 ribosomal RNA genes and 22 transfer RNA genes) encoded in the same direction. Phylogenetic trees inferred from amino acid and nucleotide sequence data for the 12 protein-coding genes strongly supported the sister relationship of K. sudhausi with Pristionchus pacificus, supporting Diplogasteromorpha. The gene order of K. sudhausi is identical to that most commonly found in members of the Rhabditomorpha + Ascaridomorpha + Diplogasteromorpha clade, with an exception of some tRNA translocations. Both the gene order pattern and sequence-based phylogenetic analyses support a close relationship between the diplogasterid species and Rhabditomorpha. The nesting of the two diplogasteromorph species within Rhabditomorpha is consistent with most molecular phylogenies for the group, but inconsistent with certain morphology-based hypotheses that asserted phylogenetic affinity between diplogasteromorphs and tylenchomorphs. Phylogenetic analysis of mitochondrial genome sequences strongly supports monophyly of the diplogasteromorpha.

Prioritizing Therapeutics for Lung Cancer: An Integrative Meta-analysis of Cancer Gene Signatures and Chemogenomic Data

PubMed Central

Fortney, Kristen; Griesman, Joshua; Kotlyar, Max; Pastrello, Chiara; Angeli, Marc; Sound-Tsao, Ming; Jurisica, Igor

2015-01-01

Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context; it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain. PMID:25786242

Competitive PCR-High Resolution Melting Analysis (C-PCR-HRMA) for large genomic rearrangements (LGRs) detection: A new approach to assess quantitative status of BRCA1 gene in a reference laboratory.

PubMed

Minucci, Angelo; De Paolis, Elisa; Concolino, Paola; De Bonis, Maria; Rizza, Roberta; Canu, Giulia; Scaglione, Giovanni Luca; Mignone, Flavio; Scambia, Giovanni; Zuppi, Cecilia; Capoluongo, Ettore

2017-07-01

Evaluation of copy number variation (CNV) in BRCA1/2 genes, due to large genomic rearrangements (LGRs), is a mandatory analysis in hereditary breast and ovarian cancers families, if no pathogenic variants are found by sequencing. LGRs cannot be detected by conventional methods and several alternative methods have been developed. Since these approaches are expensive and time consuming, identification of alternative screening methods for LGRs detection is needed in order to reduce and optimize the diagnostic procedure. The aim of this study was to investigate a Competitive PCR-High Resolution Melting Analysis (C-PCR-HRMA) as molecular tool to detect recurrent BRCA1 LGRs. C-PCR-HRMA was performed on exons 3, 14, 18, 19, 20 and 21 of the BRCA1 gene; exons 4, 6 and 7 of the ALB gene were used as reference fragments. This study showed that it is possible to identify recurrent BRCA1 LGRs, by melting peak height ratio between target (BRCA1) and reference (ALB) fragments. Furthermore, we underline that a peculiar amplicon-melting profile is associated to a specific BRCA1 LGR. All C-PCR-HRMA results were confirmed by Multiplex ligation-dependent probe amplification. C-PCR-HRMA has proved to be an innovative, efficient and fast method for BRCA1 LGRs detection. Given the sensitivity, specificity and ease of use, c-PCR-HRMA can be considered an attractive and powerful alternative to other methods for BRCA1 CNVs screening, improving molecular strategies for BRCA testing in the context of Massive Parallel Sequencing. Copyright © 2017 Elsevier B.V. All rights reserved.

Choline kinase-alpha by regulating cell aggressiveness and drug sensitivity is a potential druggable target for ovarian cancer.

PubMed

Granata, A; Nicoletti, R; Tinaglia, V; De Cecco, L; Pisanu, M E; Ricci, A; Podo, F; Canevari, S; Iorio, E; Bagnoli, M; Mezzanzanica, D

2014-01-21

Aberrant choline metabolism has been proposed as a novel cancer hallmark. We recently showed that epithelial ovarian cancer (EOC) possesses an altered MRS-choline profile, characterised by increased phosphocholine (PCho) content to which mainly contribute over-expression and activation of choline kinase-alpha (ChoK-alpha). To assess its biological relevance, ChoK-alpha expression was downmodulated by transient RNA interference in EOC in vitro models. Gene expression profiling by microarray analysis and functional analysis was performed to identify the pathway/functions perturbed in ChoK-alpha-silenced cells, then validated by in vitro experiments. In silenced cells, compared with control, we observed: (I) a significant reduction of both CHKA transcript and ChoK-alpha protein expression; (II) a dramatic, proportional drop in PCho content ranging from 60 to 71%, as revealed by (1)H-magnetic spectroscopy analysis; (III) a 35-36% of cell growth inhibition, with no evidences of apoptosis or modification of the main cellular survival signalling pathways; (IV) 476 differentially expressed genes, including genes related to lipid metabolism. Ingenuity pathway analysis identified cellular functions related to cell death and cellular proliferation and movement as the most perturbed. Accordingly, CHKA-silenced cells displayed a significant delay in wound repair, a reduced migration and invasion capability were also observed. Furthermore, although CHKA silencing did not directly induce cell death, a significant increase of sensitivity to platinum, paclitaxel and doxorubicin was observed even in a drug-resistant context. We showed for the first time in EOC that CHKA downregulation significantly decreased the aggressive EOC cell behaviour also affecting cells' sensitivity to drug treatment. These observations open the way to further analysis for ChoK-alpha validation as a new EOC therapeutic target to be used alone or in combination with conventional drugs.

Adaptations to High Salt in a Halophilic Protist: Differential Expression and Gene Acquisitions through Duplications and Gene Transfers

PubMed Central

Harding, Tommy; Roger, Andrew J.; Simpson, Alastair G. B.

2017-01-01

The capacity of halophiles to thrive in extreme hypersaline habitats derives partly from the tight regulation of ion homeostasis, the salt-dependent adjustment of plasma membrane fluidity, and the increased capability to manage oxidative stress. Halophilic bacteria, and archaea have been intensively studied, and substantial research has been conducted on halophilic fungi, and the green alga Dunaliella. By contrast, there have been very few investigations of halophiles that are phagotrophic protists, i.e., protozoa. To gather fundamental knowledge about salt adaptation in these organisms, we studied the transcriptome-level response of Halocafeteria seosinensis (Stramenopiles) grown under contrasting salinities. We provided further evolutionary context to our analysis by identifying genes that underwent recent duplications. Genes that were highly responsive to salinity variations were involved in stress response (e.g., chaperones), ion homeostasis (e.g., Na+/H+ transporter), metabolism and transport of lipids (e.g., sterol biosynthetic genes), carbohydrate metabolism (e.g., glycosidases), and signal transduction pathways (e.g., transcription factors). A significantly high proportion (43%) of duplicated genes were also differentially expressed, accentuating the importance of gene expansion in adaptation by H. seosinensis to high salt environments. Furthermore, we found two genes that were lateral acquisitions from bacteria, and were also highly up-regulated and highly expressed at high salt, suggesting that this evolutionary mechanism could also have facilitated adaptation to high salt. We propose that a transition toward high-salt adaptation in the ancestors of H. seosinensis required the acquisition of new genes via duplication, and some lateral gene transfers (LGTs), as well as the alteration of transcriptional programs, leading to increased stress resistance, proper establishment of ion gradients, and modification of cell structure properties like membrane fluidity. PMID:28611746

Comparative Sequence Analysis of the Plasmid-Encoded Regulator of Enteropathogenic Escherichia coli Strains

PubMed Central

Okeke, Iruka N.; Borneman, Jade A.; Shin, Sooan; Mellies, Jay L.; Quinn, Laura E.; Kaper, James B.

2001-01-01

Enteropathogenic Escherichia coli (EPEC) strains that carry the EPEC adherence factor (EAF) plasmid were screened for the presence of different EAF sequences, including those of the plasmid-encoded regulator (per). Considerable variation in gene content of EAF plasmids from different strains was seen. However, bfpA, the gene encoding the structural subunit for the bundle-forming pilus, bundlin, and per genes were found in 96.8% of strains. Sequence analysis of the per operon and its promoter region from 15 representative strains revealed that it is highly conserved. Most of the variation occurs in the 5′ two-thirds of the perA gene. In contrast, the C-terminal portion of the predicted PerA protein that contains the DNA-binding helix-turn-helix motif is 100% conserved in all strains that possess a full-length gene. In a minority of strains including the O119:H2 and canine isolates and in a subset of O128:H2 and O142:H6 strains, frameshift mutations in perA leading to premature truncation and consequent inactivation of the gene were identified. Cloned perA, -B, and -C genes from these strains, unlike those from strains with a functional operon, failed to activate the LEE1 operon and bfpA transcriptional fusions or to complement a per mutant in reference strain E2348/69. Furthermore, O119, O128, and canine strains that carry inactive per operons were deficient in virulence protein expression. The context in which the perABC operon occurs on the EAF plasmid varies. The sequence upstream of the per promoter region in EPEC reference strains E2348/69 and B171-8 was present in strains belonging to most serogroups. In a subset of O119:H2, O128:H2, and O142:H6 strains and in the canine isolate, this sequence was replaced by an IS1294-homologous sequence. PMID:11500429

Quantitative genome-wide methylation analysis of high-grade non-muscle invasive bladder cancer

PubMed Central

Kitchen, Mark O.; Bryan, Richard T.; Emes, Richard D.; Glossop, John R.; Luscombe, Christopher; Cheng, K. K.; Zeegers, Maurice P.; James, Nicholas D.; Devall, Adam J.; Mein, Charles A.; Gommersall, Lyndon; Fryer, Anthony A.; Farrell, William E.

2016-01-01

ABSTRACT High-grade non-muscle invasive bladder cancer (HG-NMIBC) is a clinically unpredictable disease with greater risks of recurrence and progression relative to their low-intermediate-grade counterparts. The molecular events, including those affecting the epigenome, that characterize this disease entity in the context of tumor development, recurrence, and progression, are incompletely understood. We therefore interrogated genome-wide DNA methylation using HumanMethylation450 BeadChip arrays in 21 primary HG-NMIBC tumors relative to normal bladder controls. Using strict inclusion-exclusion criteria we identified 1,057 hypermethylated CpGs within gene promoter-associated CpG islands, representing 256 genes. We validated the array data by bisulphite pyrosequencing and examined 25 array-identified candidate genes in an independent cohort of 30 HG-NMIBC and 18 low-intermediate-grade NMIBC. These analyses revealed significantly higher methylation frequencies in high-grade tumors relative to low-intermediate-grade tumors for the ATP5G2, IRX1 and VAX2 genes (P<0.05), and similarly significant increases in mean levels of methylation in high-grade tumors for the ATP5G2, VAX2, INSRR, PRDM14, VSX1, TFAP2b, PRRX1, and HIST1H4F genes (P<0.05). Although inappropriate promoter methylation was not invariantly associated with reduced transcript expression, a significant association was apparent for the ARHGEF4, PON3, STAT5a, and VAX2 gene transcripts (P<0.05). Herein, we present the first genome-wide DNA methylation analysis in a unique HG-NMIBC cohort, showing extensive and discrete methylation changes relative to normal bladder and low-intermediate-grade tumors. The genes we identified hold significant potential as targets for novel therapeutic intervention either alone, or in combination, with more conventional therapeutic options in the treatment of this clinically unpredictable disease. PMID:26929985

The human genome and sport, including epigenetics, gene doping, and athleticogenomics.

PubMed

Sharp, N C Craig

2010-03-01

Hugh Montgomery's discovery of the first of more than 239 fitness genes together with rapid advances in human gene therapy have created a prospect of using genes, genetic elements, and cells that have the capacity to enhance athletic performance (to paraphrase the World Anti-Doping Agency's definition of gene doping). This brief overview covers the main areas of interface between genetics and sport, attempts to provide a context against which gene doping may be viewed, and predicts a futuristic legitimate use of genomic (and possibly epigenetic) information in sport. Copyright 2010 Elsevier Inc. All rights reserved.

Abundant Gene-by-Environment Interactions in Gene Expression Reaction Norms to Copper within Saccharomyces cerevisiae

PubMed Central

Hodgins-Davis, Andrea; Adomas, Aleksandra B.; Warringer, Jonas; Townsend, Jeffrey P.

2012-01-01

Genetic variation for plastic phenotypes potentially contributes phenotypic variation to populations that can be selected during adaptation to novel ecological contexts. However, the basis and extent of plastic variation that manifests in diverse environments remains elusive. Here, we characterize copper reaction norms for mRNA abundance among five Saccharomyces cerevisiae strains to 1) describe population variation across the full range of ecologically relevant copper concentrations, from starvation to toxicity, and 2) to test the hypothesis that plastic networks exhibit increased population variation for gene expression. We find that although the vast majority of the variation is small in magnitude (considerably <2-fold), not just some, but most genes demonstrate variable expression across environments, across genetic backgrounds, or both. Plastically expressed genes included both genes regulated directly by copper-binding transcription factors Mac1 and Ace1 and genes indirectly responding to the downstream metabolic consequences of the copper gradient, particularly genes involved in copper, iron, and sulfur homeostasis. Copper-regulated gene networks exhibited more similar behavior within the population in environments where those networks have a large impact on fitness. Nevertheless, expression variation in genes like Cup1, important to surviving copper stress, was linked with variation in mitotic fitness and in the breadth of differential expression across the genome. By revealing a broader and deeper range of population variation, our results provide further evidence for the interconnectedness of genome-wide mRNA levels, their dependence on environmental context and genetic background, and the abundance of variation in gene expression that can contribute to future evolution. PMID:23019066

Applying gene flow science to environmental policy needs: a boundary work perspective.

PubMed

Ridley, Caroline E; Alexander, Laurie C

2016-08-01

One application of gene flow science is the policy arena. In this article, we describe two examples in which the topic of gene flow has entered into the U.S. national environmental policymaking process: regulation of genetically engineered crops and clarification of the jurisdictional scope of the Clean Water Act. We summarize both current scientific understanding and the legal context within which gene flow science has relevance. We also discuss the process by which scientific knowledge has been synthesized and communicated to decision-makers in these two contexts utilizing the concept of 'boundary work'. Boundary organizations, the work they engage in to bridge the worlds of science, policy, and practice, and the boundary objects they produce to translate scientific knowledge existed in both examples. However, the specific activities and attributes of the objects produced varied based on the needs of the decision-makers. We close with suggestions for how scientists can contribute to or engage in boundary work with policymakers.

DNA Replication Control During Drosophila Development: Insights into the Onset of S Phase, Replication Initiation, and Fork Progression

PubMed Central

Hua, Brian L.; Orr-Weaver, Terry L.

2017-01-01

Proper control of DNA replication is critical to ensure genomic integrity during cell proliferation. In addition, differential regulation of the DNA replication program during development can change gene copy number to influence cell size and gene expression. Drosophila melanogaster serves as a powerful organism to study the developmental control of DNA replication in various cell cycle contexts in a variety of differentiated cell and tissue types. Additionally, Drosophila has provided several developmentally regulated replication models to dissect the molecular mechanisms that underlie replication-based copy number changes in the genome, which include differential underreplication and gene amplification. Here, we review key findings and our current understanding of the developmental control of DNA replication in the contexts of the archetypal replication program as well as of underreplication and differential gene amplification. We focus on the use of these latter two replication systems to delineate many of the molecular mechanisms that underlie the developmental control of replication initiation and fork elongation. PMID:28874453

Wasabi: An Integrated Platform for Evolutionary Sequence Analysis and Data Visualization.

PubMed

Veidenberg, Andres; Medlar, Alan; Löytynoja, Ari

2016-04-01

Wasabi is an open source, web-based environment for evolutionary sequence analysis. Wasabi visualizes sequence data together with a phylogenetic tree within a modern, user-friendly interface: The interface hides extraneous options, supports context sensitive menus, drag-and-drop editing, and displays additional information, such as ancestral sequences, associated with specific tree nodes. The Wasabi environment supports reproducibility by automatically storing intermediate analysis steps and includes built-in functions to share data between users and publish analysis results. For computational analysis, Wasabi supports PRANK and PAGAN for phylogeny-aware alignment and alignment extension, and it can be easily extended with other tools. Along with drag-and-drop import of local files, Wasabi can access remote data through URL and import sequence data, GeneTrees and EPO alignments directly from Ensembl. To demonstrate a typical workflow using Wasabi, we reproduce key findings from recent comparative genomics studies, including a reanalysis of the EGLN1 gene from the tiger genome study: These case studies can be browsed within Wasabi at http://wasabiapp.org:8000?id=usecases. Wasabi runs inside a web browser and does not require any installation. One can start using it at http://wasabiapp.org. All source code is licensed under the AGPLv3. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Enhancing dopaminergic signaling and histone acetylation promotes long-term rescue of deficient fear extinction

PubMed Central

Whittle, N; Maurer, V; Murphy, C; Rainer, J; Bindreither, D; Hauschild, M; Scharinger, A; Oberhauser, M; Keil, T; Brehm, C; Valovka, T; Striessnig, J; Singewald, N

2016-01-01

Extinction-based exposure therapy is used to treat anxiety- and trauma-related disorders; however, there is the need to improve its limited efficacy in individuals with impaired fear extinction learning and to promote greater protection against return-of-fear phenomena. Here, using 129S1/SvImJ mice, which display impaired fear extinction acquisition and extinction consolidation, we revealed that persistent and context-independent rescue of deficient fear extinction in these mice was associated with enhanced expression of dopamine-related genes, such as dopamine D1 (Drd1a) and -D2 (Drd2) receptor genes in the medial prefrontal cortex (mPFC) and amygdala, but not hippocampus. Moreover, enhanced histone acetylation was observed in the promoter of the extinction-regulated Drd2 gene in the mPFC, revealing a potential gene-regulatory mechanism. Although enhancing histone acetylation, via administering the histone deacetylase (HDAC) inhibitor MS-275, does not induce fear reduction during extinction training, it promoted enduring and context-independent rescue of deficient fear extinction consolidation/retrieval once extinction learning was initiated as shown following a mild conditioning protocol. This was associated with enhanced histone acetylation in neurons of the mPFC and amygdala. Finally, as a proof-of-principle, mimicking enhanced dopaminergic signaling by L-dopa treatment rescued deficient fear extinction and co-administration of MS-275 rendered this effect enduring and context-independent. In summary, current data reveal that combining dopaminergic and epigenetic mechanisms is a promising strategy to improve exposure-based behavior therapy in extinction-impaired individuals by initiating the formation of an enduring and context-independent fear-inhibitory memory. PMID:27922638