The EbpA-RpoN Regulatory Pathway of the Pathogen Leptospira interrogans Is Essential for Survival in the Environment

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Hu, Wei-Lin; Pappas, Christopher J.; Zhang, Jun-Jie; Yang, You-Yun; Yan, Jie

2016-01-01

ABSTRACT Leptospira interrogans is the agent of leptospirosis, a reemerging zoonotic disease. It is transmitted to humans through environmental surface waters contaminated by the urine of mammals chronically infected by pathogenic strains able to survive in water for long periods. Little is known about the regulatory pathways underlying environmental sensing and host adaptation of L. interrogans during its enzootic cycle. This study identifies the EbpA-RpoN regulatory pathway in L. interrogans. In this pathway, EbpA, a σ54 activator and putative prokaryotic enhancer-binding protein (EBP), and the alternative sigma factor RpoN (σ54) control expression of at least three genes, encoding AmtB (an ammonium transport protein) and two proteins of unknown function. Electrophoresis mobility shift assay demonstrated that recombinant RpoN and EbpA bind to the promoter region and upstream of these three identified genes, respectively. Genetic disruption of ebpA in L. interrogans serovar Manilae virtually abolished expression of the three genes, including amtB in two independent ebpA mutants. Complementation of the ebpA mutant restored expression of these genes. Intraperitoneal inoculation of gerbils with the ebpA mutant did not affect mortality. However, the ebpA mutant had decreased cell length in vitro and had a significantly lowered cell density at stationary phase when grown with l-alanine as the sole nitrogen source. Furthermore, the ebpA mutant has dramatically reduced long-term survival ability in water. Together, these studies identify a regulatory pathway, the EbpA-RpoN pathway, that plays an important role in the zoonotic cycle of L. interrogans. IMPORTANCE Leptospirosis is a reemerging disease with global importance. However, our understanding of gene regulation of the spirochetal pathogen Leptospira interrogans is still in its infancy, largely due to the lack of robust tools for genetic manipulation of this spirochete. Little is known about how the pathogen

The EbpA-RpoN Regulatory Pathway of the Pathogen Leptospira interrogans Is Essential for Survival in the Environment.

Science.gov (United States)

Hu, Wei-Lin; Pappas, Christopher J; Zhang, Jun-Jie; Yang, You-Yun; Yan, Jie; Picardeau, Mathieu; Yang, X Frank

2017-02-01

Leptospira interrogans is the agent of leptospirosis, a reemerging zoonotic disease. It is transmitted to humans through environmental surface waters contaminated by the urine of mammals chronically infected by pathogenic strains able to survive in water for long periods. Little is known about the regulatory pathways underlying environmental sensing and host adaptation of L. interrogans during its enzootic cycle. This study identifies the EbpA-RpoN regulatory pathway in L. interrogans In this pathway, EbpA, a σ 54 activator and putative prokaryotic enhancer-binding protein (EBP), and the alternative sigma factor RpoN (σ 54 ) control expression of at least three genes, encoding AmtB (an ammonium transport protein) and two proteins of unknown function. Electrophoresis mobility shift assay demonstrated that recombinant RpoN and EbpA bind to the promoter region and upstream of these three identified genes, respectively. Genetic disruption of ebpA in L. interrogans serovar Manilae virtually abolished expression of the three genes, including amtB in two independent ebpA mutants. Complementation of the ebpA mutant restored expression of these genes. Intraperitoneal inoculation of gerbils with the ebpA mutant did not affect mortality. However, the ebpA mutant had decreased cell length in vitro and had a significantly lowered cell density at stationary phase when grown with l-alanine as the sole nitrogen source. Furthermore, the ebpA mutant has dramatically reduced long-term survival ability in water. Together, these studies identify a regulatory pathway, the EbpA-RpoN pathway, that plays an important role in the zoonotic cycle of L. interrogans IMPORTANCE: Leptospirosis is a reemerging disease with global importance. However, our understanding of gene regulation of the spirochetal pathogen Leptospira interrogans is still in its infancy, largely due to the lack of robust tools for genetic manipulation of this spirochete. Little is known about how the pathogen achieves its

DMPD: Type I interferon [corrected] gene induction by the interferon regulatory factorfamily of transcription factors. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available 16979567 Type I interferon [corrected] gene induction by the interferon regulatory factorfamily...ng) (.svg) (.html) (.csml) Show Type I interferon [corrected] gene induction by the interferon regulatory factorfamily...orrected] gene induction by the interferon regulatory factorfamily of transcription factors. Authors Honda K

Fanconi anemia core complex gene promoters harbor conserved transcription regulatory elements.

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Meier, Daniel; Schindler, Detlev

2011-01-01

The Fanconi anemia (FA) gene family is a recent addition to the complex network of proteins that respond to and repair certain types of DNA damage in the human genome. Since little is known about the regulation of this novel group of genes at the DNA level, we characterized the promoters of the eight genes (FANCA, B, C, E, F, G, L and M) that compose the FA core complex. The promoters of these genes show the characteristic attributes of housekeeping genes, such as a high GC content and CpG islands, a lack of TATA boxes and a low conservation. The promoters functioned in a monodirectional way and were, in their most active regions, comparable in strength to the SV40 promoter in our reporter plasmids. They were also marked by a distinctive transcriptional start site (TSS). In the 5' region of each promoter, we identified a region that was able to negatively regulate the promoter activity in HeLa and HEK 293 cells in isolation. The central and 3' regions of the promoter sequences harbor binding sites for several common and rare transcription factors, including STAT, SMAD, E2F, AP1 and YY1, which indicates that there may be cross-connections to several established regulatory pathways. Electrophoretic mobility shift assays and siRNA experiments confirmed the shared regulatory responses between the prominent members of the TGF-β and JAK/STAT pathways and members of the FA core complex. Although the promoters are not well conserved, they share region and sequence specific regulatory motifs and transcription factor binding sites (TBFs), and we identified a bi-partite nature to these promoters. These results support a hypothesis based on the co-evolution of the FA core complex genes that was expanded to include their promoters.

Fanconi anemia core complex gene promoters harbor conserved transcription regulatory elements.

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Daniel Meier

Full Text Available The Fanconi anemia (FA gene family is a recent addition to the complex network of proteins that respond to and repair certain types of DNA damage in the human genome. Since little is known about the regulation of this novel group of genes at the DNA level, we characterized the promoters of the eight genes (FANCA, B, C, E, F, G, L and M that compose the FA core complex. The promoters of these genes show the characteristic attributes of housekeeping genes, such as a high GC content and CpG islands, a lack of TATA boxes and a low conservation. The promoters functioned in a monodirectional way and were, in their most active regions, comparable in strength to the SV40 promoter in our reporter plasmids. They were also marked by a distinctive transcriptional start site (TSS. In the 5' region of each promoter, we identified a region that was able to negatively regulate the promoter activity in HeLa and HEK 293 cells in isolation. The central and 3' regions of the promoter sequences harbor binding sites for several common and rare transcription factors, including STAT, SMAD, E2F, AP1 and YY1, which indicates that there may be cross-connections to several established regulatory pathways. Electrophoretic mobility shift assays and siRNA experiments confirmed the shared regulatory responses between the prominent members of the TGF-β and JAK/STAT pathways and members of the FA core complex. Although the promoters are not well conserved, they share region and sequence specific regulatory motifs and transcription factor binding sites (TBFs, and we identified a bi-partite nature to these promoters. These results support a hypothesis based on the co-evolution of the FA core complex genes that was expanded to include their promoters.

Gene Expression Dynamics in Major Endocrine Regulatory Pathways along the Transition from Solitary to Social Life in a Bumblebee, Bombus terrestris

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Pavel Jedlička

2016-11-01

Full Text Available Understanding the social evolution leading to insect eusociality requires, among other, a detailed insight into endocrine regulatory mechanisms that have been co-opted from solitary ancestors to play new roles in the complex life histories of eusocial species. Bumblebees represent well-suited models of a relatively primitive social organization standing on the mid-way to highly advanced eusociality and their queens undergo both, a solitary and a social phase, separated by winter diapause.In the present paper, we characterize the gene expression levels of major endocrine regulatory pathways across tissues, sexes, and life-stages of the buff-tailed bumblebee, Bombus terrestris, with special emphasis on critical stages of the queen’s transition from solitary to social life. We focused on fundamental genes of three pathways: (1 Forkhead box protein O and insulin/insulin-like signaling, (2 Juvenile hormone signaling, and (3 Adipokinetic hormone signaling. Virgin queens were distinguished by higher expression of forkhead box protein O and downregulated insulin-like peptides and juvenile hormone (JH signaling, indicated by low expression of methyl farnesoate epoxidase (MFE and transcription factor Krüppel homolog 1 (Kr-h1. Diapausing queens showed the expected downregulation of JH signaling in terms of low MFE and vitellogenin (Vg expressions, but an unexpectedly high expression of Kr-h1. By contrast, reproducing queens revealed an upregulation of MFE and Vg together with insulin signaling. Surprisingly, the insulin growth factor 1 (IGF-1 turned out to be a queen-specific hormone. Workers exhibited an expression pattern of MFE and Vg similar to that of reproducing queens. Males were characterized by high Kr-h1 expression and low Vg level. The tissue comparison unveiled an unexpected resemblance between the fat body and hypopharyngeal glands across all investigated genes, sexes, and life stages.

Evolution of Cis-Regulatory Elements and Regulatory Networks in Duplicated Genes of Arabidopsis.

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Arsovski, Andrej A; Pradinuk, Julian; Guo, Xu Qiu; Wang, Sishuo; Adams, Keith L

2015-12-01

Plant genomes contain large numbers of duplicated genes that contribute to the evolution of new functions. Following duplication, genes can exhibit divergence in their coding sequence and their expression patterns. Changes in the cis-regulatory element landscape can result in changes in gene expression patterns. High-throughput methods developed recently can identify potential cis-regulatory elements on a genome-wide scale. Here, we use a recent comprehensive data set of DNase I sequencing-identified cis-regulatory binding sites (footprints) at single-base-pair resolution to compare binding sites and network connectivity in duplicated gene pairs in Arabidopsis (Arabidopsis thaliana). We found that duplicated gene pairs vary greatly in their cis-regulatory element architecture, resulting in changes in regulatory network connectivity. Whole-genome duplicates (WGDs) have approximately twice as many footprints in their promoters left by potential regulatory proteins than do tandem duplicates (TDs). The WGDs have a greater average number of footprint differences between paralogs than TDs. The footprints, in turn, result in more regulatory network connections between WGDs and other genes, forming denser, more complex regulatory networks than shown by TDs. When comparing regulatory connections between duplicates, WGDs had more pairs in which the two genes are either partially or fully diverged in their network connections, but fewer genes with no network connections than the TDs. There is evidence of younger TDs and WGDs having fewer unique connections compared with older duplicates. This study provides insights into cis-regulatory element evolution and network divergence in duplicated genes. © 2015 American Society of Plant Biologists. All Rights Reserved.

Discriminating response groups in metabolic and regulatory pathway networks.

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Van Hemert, John L; Dickerson, Julie A

2012-04-01

Analysis of omics experiments generates lists of entities (genes, metabolites, etc.) selected based on specific behavior, such as changes in response to stress or other signals. Functional interpretation of these lists often uses category enrichment tests using functional annotations like Gene Ontology terms and pathway membership. This approach does not consider the connected structure of biochemical pathways or the causal directionality of events. The Omics Response Group (ORG) method, described in this work, interprets omics lists in the context of metabolic pathway and regulatory networks using a statistical model for flow within the networks. Statistical results for all response groups are visualized in a novel Pathway Flow plot. The statistical tests are based on the Erlang distribution model under the assumption of independent and identically Exponential-distributed random walk flows through pathways. As a proof of concept, we applied our method to an Escherichia coli transcriptomics dataset where we confirmed common knowledge of the E.coli transcriptional response to Lipid A deprivation. The main response is related to osmotic stress, and we were also able to detect novel responses that are supported by the literature. We also applied our method to an Arabidopsis thaliana expression dataset from an abscisic acid study. In both cases, conventional pathway enrichment tests detected nothing, while our approach discovered biological processes beyond the original studies. We created a prototype for an interactive ORG web tool at http://ecoserver.vrac.iastate.edu/pathwayflow (source code is available from https://subversion.vrac.iastate.edu/Subversion/jlv/public/jlv/pathwayflow). The prototype is described along with additional figures and tables in Supplementary Material. julied@iastate.edu Supplementary data are available at Bioinformatics online.

The major cellular sterol regulatory pathway is required for Andes virus infection.

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Josiah Petersen

2014-02-01

Full Text Available The Bunyaviridae comprise a large family of RNA viruses with worldwide distribution and includes the pathogenic New World hantavirus, Andes virus (ANDV. Host factors needed for hantavirus entry remain largely enigmatic and therapeutics are unavailable. To identify cellular requirements for ANDV infection, we performed two parallel genetic screens. Analysis of a large library of insertionally mutagenized human haploid cells and a siRNA genomic screen converged on components (SREBP-2, SCAP, S1P and S2P of the sterol regulatory pathway as critically important for infection by ANDV. The significance of this pathway was confirmed using functionally deficient cells, TALEN-mediated gene disruption, RNA interference and pharmacologic inhibition. Disruption of sterol regulatory complex function impaired ANDV internalization without affecting virus binding. Pharmacologic manipulation of cholesterol levels demonstrated that ANDV entry is sensitive to changes in cellular cholesterol and raises the possibility that clinically approved regulators of sterol synthesis may prove useful for combating ANDV infection.

Single nucleotide polymorphism in transcriptional regulatory regions and expression of environmentally responsive genes

International Nuclear Information System (INIS)

Wang, Xuting; Tomso, Daniel J.; Liu Xuemei; Bell, Douglas A.

2005-01-01

Single nucleotide polymorphisms (SNPs) in the human genome are DNA sequence variations that can alter an individual's response to environmental exposure. SNPs in gene coding regions can lead to changes in the biological properties of the encoded protein. In contrast, SNPs in non-coding gene regulatory regions may affect gene expression levels in an allele-specific manner, and these functional polymorphisms represent an important but relatively unexplored class of genetic variation. The main challenge in analyzing these SNPs is a lack of robust computational and experimental methods. Here, we first outline mechanisms by which genetic variation can impact gene regulation, and review recent findings in this area; then, we describe a methodology for bioinformatic discovery and functional analysis of regulatory SNPs in cis-regulatory regions using the assembled human genome sequence and databases on sequence polymorphism and gene expression. Our method integrates SNP and gene databases and uses a set of computer programs that allow us to: (1) select SNPs, from among the >9 million human SNPs in the NCBI dbSNP database, that are similar to cis-regulatory element (RE) consensus sequences; (2) map the selected dbSNP entries to the human genome assembly in order to identify polymorphic REs near gene start sites; (3) prioritize the candidate polymorphic RE containing genes by searching the existing genotype and gene expression data sets. The applicability of this system has been demonstrated through studies on p53 responsive elements and is being extended to additional pathways and environmentally responsive genes

Logical knowledge representation of regulatory relations in biomedical pathways

DEFF Research Database (Denmark)

Zambach, Sine; Hansen, Jens Ulrik

2010-01-01

Knowledge on regulatory relations, in for example regulatory pathways in biology, is used widely in experiment design by biomedical researchers and in systems biology. The knowledge has typically either been represented through simple graphs or through very expressive differential equation...... simulations of smaller parts of a pathway. In this work we suggest a knowledge representation of the most basic relations in regulatory processes regulates, positively regulates and negatively regulates in logics based on a semantic analysis. We discuss the usage of these relations in biology and in articial...... intelligence for hypothesis development in drug discovery....

A comparative study of covariance selection models for the inference of gene regulatory networks.

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Stifanelli, Patrizia F; Creanza, Teresa M; Anglani, Roberto; Liuzzi, Vania C; Mukherjee, Sayan; Schena, Francesco P; Ancona, Nicola

2013-10-01

The inference, or 'reverse-engineering', of gene regulatory networks from expression data and the description of the complex dependency structures among genes are open issues in modern molecular biology. In this paper we compared three regularized methods of covariance selection for the inference of gene regulatory networks, developed to circumvent the problems raising when the number of observations n is smaller than the number of genes p. The examined approaches provided three alternative estimates of the inverse covariance matrix: (a) the 'PINV' method is based on the Moore-Penrose pseudoinverse, (b) the 'RCM' method performs correlation between regression residuals and (c) 'ℓ(2C)' method maximizes a properly regularized log-likelihood function. Our extensive simulation studies showed that ℓ(2C) outperformed the other two methods having the most predictive partial correlation estimates and the highest values of sensitivity to infer conditional dependencies between genes even when a few number of observations was available. The application of this method for inferring gene networks of the isoprenoid biosynthesis pathways in Arabidopsis thaliana allowed to enlighten a negative partial correlation coefficient between the two hubs in the two isoprenoid pathways and, more importantly, provided an evidence of cross-talk between genes in the plastidial and the cytosolic pathways. When applied to gene expression data relative to a signature of HRAS oncogene in human cell cultures, the method revealed 9 genes (p-value<0.0005) directly interacting with HRAS, sharing the same Ras-responsive binding site for the transcription factor RREB1. This result suggests that the transcriptional activation of these genes is mediated by a common transcription factor downstream of Ras signaling. Software implementing the methods in the form of Matlab scripts are available at: http://users.ba.cnr.it/issia/iesina18/CovSelModelsCodes.zip. Copyright © 2013 The Authors. Published by

Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression.

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Fairfax, Benjamin P; Humburg, Peter; Makino, Seiko; Naranbhai, Vivek; Wong, Daniel; Lau, Evelyn; Jostins, Luke; Plant, Katharine; Andrews, Robert; McGee, Chris; Knight, Julian C

2014-03-07

To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor-modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.

Integrated systems approach identifies risk regulatory pathways and key regulators in coronary artery disease.

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Zhang, Yan; Liu, Dianming; Wang, Lihong; Wang, Shuyuan; Yu, Xuexin; Dai, Enyu; Liu, Xinyi; Luo, Shanshun; Jiang, Wei

2015-12-01

Coronary artery disease (CAD) is the most common type of heart disease. However, the molecular mechanisms of CAD remain elusive. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, inferring risk regulatory pathways is an important step toward elucidating the mechanisms underlying CAD. With advances in high-throughput data, we developed an integrated systems approach to identify CAD risk regulatory pathways and key regulators. Firstly, a CAD-related core subnetwork was identified from a curated transcription factor (TF) and microRNA (miRNA) regulatory network based on a random walk algorithm. Secondly, candidate risk regulatory pathways were extracted from the subnetwork by applying a breadth-first search (BFS) algorithm. Then, risk regulatory pathways were prioritized based on multiple CAD-associated data sources. Finally, we also proposed a new measure to prioritize upstream regulators. We inferred that phosphatase and tensin homolog (PTEN) may be a key regulator in the dysregulation of risk regulatory pathways. This study takes a closer step than the identification of disease subnetworks or modules. From the risk regulatory pathways, we could understand the flow of regulatory information in the initiation and progression of the disease. Our approach helps to uncover its potential etiology. We developed an integrated systems approach to identify risk regulatory pathways. We proposed a new measure to prioritize the key regulators in CAD. PTEN may be a key regulator in dysregulation of the risk regulatory pathways.

EWS and FUS bind a subset of transcribed genes encoding proteins enriched in RNA regulatory functions

DEFF Research Database (Denmark)

Luo, Yonglun; Friis, Jenny Blechingberg; Fernandes, Ana Miguel

2015-01-01

at different levels. Gene Ontology analyses showed that FUS and EWS target genes preferentially encode proteins involved in regulatory processes at the RNA level. Conclusions The presented results yield new insights into gene interactions of EWS and FUS and have identified a set of FUS and EWS target genes...... involved in pathways at the RNA regulatory level with potential to mediate normal and disease-associated functions of the FUS and EWS proteins.......Background FUS (TLS) and EWS (EWSR1) belong to the FET-protein family of RNA and DNA binding proteins. FUS and EWS are structurally and functionally related and participate in transcriptional regulation and RNA processing. FUS and EWS are identified in translocation generated cancer fusion proteins...

Small regulatory RNAs of the RNA interference (RNAi) pathway as a prophylactic treatment against fish pathogenic viruses

DEFF Research Database (Denmark)

Schyth, Brian Dall; Hajiabadi, Seyed Amir Hossein Jalali; Kristensen, Lasse Bøgelund Juel

2011-01-01

Small RNAs acting in the recently discovered gene regulatory mechanism called RNA interference has a potential as diagnostic signatures of disease and immunological state and when produced synthetically as prophylactic treatment of such diseases. In the RNAi mechanism the cell produces different....... The mechanism can be programmed with several types of small double stranded RNAs - the type of which defines the destiny of the target. One such class of regulatory RNAs called microRNAs are upregulated due to various physiological responses of the cell and they suppress many genes simultaneously believed...... small RNAs which inhibit gene expression through more or less specific interaction with messenger RNAs resulting in repression of translation to protein. In this way cells can turn of genes of specific pathways thereby leading to altered physiological stages of tissues and possibly of whole organisms...

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks.

Science.gov (United States)

Guo, Liyuan; Wang, Jing

2018-01-04

Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element-target gene pairs (E-G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Simultaneous genome-wide inference of physical, genetic, regulatory, and functional pathway components.

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Christopher Y Park

2010-11-01

Full Text Available Biomolecular pathways are built from diverse types of pairwise interactions, ranging from physical protein-protein interactions and modifications to indirect regulatory relationships. One goal of systems biology is to bridge three aspects of this complexity: the growing body of high-throughput data assaying these interactions; the specific interactions in which individual genes participate; and the genome-wide patterns of interactions in a system of interest. Here, we describe methodology for simultaneously predicting specific types of biomolecular interactions using high-throughput genomic data. This results in a comprehensive compendium of whole-genome networks for yeast, derived from ∼3,500 experimental conditions and describing 30 interaction types, which range from general (e.g. physical or regulatory to specific (e.g. phosphorylation or transcriptional regulation. We used these networks to investigate molecular pathways in carbon metabolism and cellular transport, proposing a novel connection between glycogen breakdown and glucose utilization supported by recent publications. Additionally, 14 specific predicted interactions in DNA topological change and protein biosynthesis were experimentally validated. We analyzed the systems-level network features within all interactomes, verifying the presence of small-world properties and enrichment for recurring network motifs. This compendium of physical, synthetic, regulatory, and functional interaction networks has been made publicly available through an interactive web interface for investigators to utilize in future research at http://function.princeton.edu/bioweaver/.

Transcriptional regulatory programs underlying barley germination and regulatory functions of Gibberellin and abscisic acid

Science.gov (United States)

2011-01-01

Background Seed germination is a complex multi-stage developmental process, and mainly accomplished through concerted activities of many gene products and biological pathways that are often subjected to strict developmental regulation. Gibberellins (GA) and abscisic acid (ABA) are two key phytohormones regulating seed germination and seedling growth. However, transcriptional regulatory networks underlying seed germination and its associated biological pathways are largely unknown. Results The studies examined transcriptomes of barley representing six distinct and well characterized germination stages and revealed that the transcriptional regulatory program underlying barley germination was composed of early, late, and post-germination phases. Each phase was accompanied with transcriptional up-regulation of distinct biological pathways. Cell wall synthesis and regulatory components including transcription factors, signaling and post-translational modification components were specifically and transiently up-regulated in early germination phase while histone families and many metabolic pathways were up-regulated in late germination phase. Photosynthesis and seed reserve mobilization pathways were up-regulated in post-germination phase. However, stress related pathways and seed storage proteins were suppressed through the entire course of germination. A set of genes were transiently up-regulated within three hours of imbibition, and might play roles in initiating biological pathways involved in seed germination. However, highly abundant transcripts in dry barley and Arabidopsis seeds were significantly conserved. Comparison with transcriptomes of barley aleurone in response to GA and ABA identified three sets of germination responsive genes that were regulated coordinately by GA, antagonistically by ABA, and coordinately by GA but antagonistically by ABA. Major CHO metabolism, cell wall degradation and protein degradation pathways were up-regulated by both GA and seed

Transcriptional regulatory programs underlying barley germination and regulatory functions of Gibberellin and abscisic acid

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Lin Li

2011-06-01

Full Text Available Abstract Background Seed germination is a complex multi-stage developmental process, and mainly accomplished through concerted activities of many gene products and biological pathways that are often subjected to strict developmental regulation. Gibberellins (GA and abscisic acid (ABA are two key phytohormones regulating seed germination and seedling growth. However, transcriptional regulatory networks underlying seed germination and its associated biological pathways are largely unknown. Results The studies examined transcriptomes of barley representing six distinct and well characterized germination stages and revealed that the transcriptional regulatory program underlying barley germination was composed of early, late, and post-germination phases. Each phase was accompanied with transcriptional up-regulation of distinct biological pathways. Cell wall synthesis and regulatory components including transcription factors, signaling and post-translational modification components were specifically and transiently up-regulated in early germination phase while histone families and many metabolic pathways were up-regulated in late germination phase. Photosynthesis and seed reserve mobilization pathways were up-regulated in post-germination phase. However, stress related pathways and seed storage proteins were suppressed through the entire course of germination. A set of genes were transiently up-regulated within three hours of imbibition, and might play roles in initiating biological pathways involved in seed germination. However, highly abundant transcripts in dry barley and Arabidopsis seeds were significantly conserved. Comparison with transcriptomes of barley aleurone in response to GA and ABA identified three sets of germination responsive genes that were regulated coordinately by GA, antagonistically by ABA, and coordinately by GA but antagonistically by ABA. Major CHO metabolism, cell wall degradation and protein degradation pathways were up

Application of R to investigate common gene regulatory network pathway among bipolar disorder and associate diseases

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Nahida Habib

2016-12-01

Full Text Available Depression, Major Depression or mental disorder creates severe diseases. Mental illness such as Unipolar Major Depression, Bipolar Disorder, Dysthymia, Schizophrenia, Cardiovascular Diseases (Hypertension, Coronary Heart Disease, Stroke etc., are known as Major Depression. Several studies have revealed the possibilities about the association among Bipolar Disorder, Schizophrenia, Coronary Heart Diseases and Stroke with each other. The current study aimed to investigate the relationships between genetic variants in the above four diseases and to create a common pathway or PPI network. The associated genes of each disease are collected from different gene database with verification using R. After performing some preprocessing, mining and operations using R on collected genes, seven (7 common associated genes are discovered on selected four diseases (SZ, BD, CHD and Stroke. In each of the iteration, the numbers of collected genes are reduced up to 51%, 36%, 10%, 2% and finally less than 1% respectively. Moreover, common pathway on selected diseases has been investigated in this research.

Layered signaling regulatory networks analysis of gene expression involved in malignant tumorigenesis of non-resolving ulcerative colitis via integration of cross-study microarray profiles.

Science.gov (United States)

Fan, Shengjun; Pan, Zhenyu; Geng, Qiang; Li, Xin; Wang, Yefan; An, Yu; Xu, Yan; Tie, Lu; Pan, Yan; Li, Xuejun

2013-01-01

Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups. In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks. Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one. The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis sketched a directive insight into colorectal carcinogenesis

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

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Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

Science.gov (United States)

Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

2014-01-01

Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

A flood-based information flow analysis and network minimization method for gene regulatory networks.

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Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

2013-04-24

Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.

EWS and FUS bind a subset of transcribed genes encoding proteins enriched in RNA regulatory functions.

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Luo, Yonglun; Blechingberg, Jenny; Fernandes, Ana Miguel; Li, Shengting; Fryland, Tue; Børglum, Anders D; Bolund, Lars; Nielsen, Anders Lade

2015-11-14

FUS (TLS) and EWS (EWSR1) belong to the FET-protein family of RNA and DNA binding proteins. FUS and EWS are structurally and functionally related and participate in transcriptional regulation and RNA processing. FUS and EWS are identified in translocation generated cancer fusion proteins and involved in the human neurological diseases amyotrophic lateral sclerosis and fronto-temporal lobar degeneration. To determine the gene regulatory functions of FUS and EWS at the level of chromatin, we have performed chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq). Our results show that FUS and EWS bind to a subset of actively transcribed genes, that binding often is downstream the poly(A)-signal, and that binding overlaps with RNA polymerase II. Functional examinations of selected target genes identified that FUS and EWS can regulate gene expression at different levels. Gene Ontology analyses showed that FUS and EWS target genes preferentially encode proteins involved in regulatory processes at the RNA level. The presented results yield new insights into gene interactions of EWS and FUS and have identified a set of FUS and EWS target genes involved in pathways at the RNA regulatory level with potential to mediate normal and disease-associated functions of the FUS and EWS proteins.

Sequence-based model of gap gene regulatory network.

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Kozlov, Konstantin; Gursky, Vitaly; Kulakovskiy, Ivan; Samsonova, Maria

2014-01-01

The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. We developed a new model that provides a dynamical description of gap gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces gap gene expression patterns in wild type embryos and is able to predict gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the gap gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded. The reconstructed topology of the gap gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3

Inference of cancer-specific gene regulatory networks using soft computing rules.

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Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Regulatory Mechanisms of the Ihh/PTHrP Signaling Pathway in Fibrochondrocytes in Entheses of Pig Achilles Tendon

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Xuesong Han

2016-01-01

Full Text Available This study is aimed at exploring the effect of stress stimulation on the proliferation and differentiation of fibrochondrocytes in entheses mediated via the Indian hedgehog (Ihh/parathyroid hormone-related protein (PTHrP signaling pathway. Differential stress stimulation on fibrochondrocytes in entheses was imposed. Gene expression and protein levels of signaling molecules including collagen type I (Col I, Col II, Col X, Ihh, and PTHrP in the cytoplasm of fibrochondrocytes were detected. Ihh signal blocking group was set up using Ihh signaling pathway-specific blocking agent cyclopamine. PTHrP enhancement group was set up using PTHrP reagent. Ihh/PTHrP double intervention group, as well as control group, was included to study the regulatory mechanisms of the Ihh/PTHrP signaling pathway in fibrochondrocytes. Under low cyclic stress tensile (CTS, PTHrP, Col I, and Col II gene expression and protein synthesis increased. Under high CTS, Ihh and Col X gene expression and protein synthesis increased. Blocking Ihh signaling with cyclopamine resulted in reduced PTHrP gene expression and protein synthesis and increased Col X gene expression and protein synthesis. Ihh and PTHrP coregulate fibrochondrocyte proliferation and differentiation in entheses through negative feedback regulation. Fibrochondrocyte is affected by the CTS. This phenomenon is regulated by stress stimulation through the Ihh/PTHrP signaling pathway.

Regulatory Mechanisms of the Ihh/PTHrP Signaling Pathway in Fibrochondrocytes in Entheses of Pig Achilles Tendon.

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Han, Xuesong; Zhuang, Yanfeng; Zhang, Zhihong; Guo, Lin; Wang, Wanming

2016-01-01

This study is aimed at exploring the effect of stress stimulation on the proliferation and differentiation of fibrochondrocytes in entheses mediated via the Indian hedgehog (Ihh)/parathyroid hormone-related protein (PTHrP) signaling pathway. Differential stress stimulation on fibrochondrocytes in entheses was imposed. Gene expression and protein levels of signaling molecules including collagen type I (Col I), Col II, Col X, Ihh, and PTHrP in the cytoplasm of fibrochondrocytes were detected. Ihh signal blocking group was set up using Ihh signaling pathway-specific blocking agent cyclopamine. PTHrP enhancement group was set up using PTHrP reagent. Ihh/PTHrP double intervention group, as well as control group, was included to study the regulatory mechanisms of the Ihh/PTHrP signaling pathway in fibrochondrocytes. Under low cyclic stress tensile (CTS), PTHrP, Col I, and Col II gene expression and protein synthesis increased. Under high CTS, Ihh and Col X gene expression and protein synthesis increased. Blocking Ihh signaling with cyclopamine resulted in reduced PTHrP gene expression and protein synthesis and increased Col X gene expression and protein synthesis. Ihh and PTHrP coregulate fibrochondrocyte proliferation and differentiation in entheses through negative feedback regulation. Fibrochondrocyte is affected by the CTS. This phenomenon is regulated by stress stimulation through the Ihh/PTHrP signaling pathway.

Identification of a cis-regulatory element by transient analysis of co-ordinately regulated genes

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Allan Andrew C

2008-07-01

Full Text Available Abstract Background Transcription factors (TFs co-ordinately regulate target genes that are dispersed throughout the genome. This co-ordinate regulation is achieved, in part, through the interaction of transcription factors with conserved cis-regulatory motifs that are in close proximity to the target genes. While much is known about the families of transcription factors that regulate gene expression in plants, there are few well characterised cis-regulatory motifs. In Arabidopsis, over-expression of the MYB transcription factor PAP1 (PRODUCTION OF ANTHOCYANIN PIGMENT 1 leads to transgenic plants with elevated anthocyanin levels due to the co-ordinated up-regulation of genes in the anthocyanin biosynthetic pathway. In addition to the anthocyanin biosynthetic genes, there are a number of un-associated genes that also change in expression level. This may be a direct or indirect consequence of the over-expression of PAP1. Results Oligo array analysis of PAP1 over-expression Arabidopsis plants identified genes co-ordinately up-regulated in response to the elevated expression of this transcription factor. Transient assays on the promoter regions of 33 of these up-regulated genes identified eight promoter fragments that were transactivated by PAP1. Bioinformatic analysis on these promoters revealed a common cis-regulatory motif that we showed is required for PAP1 dependent transactivation. Conclusion Co-ordinated gene regulation by individual transcription factors is a complex collection of both direct and indirect effects. Transient transactivation assays provide a rapid method to identify direct target genes from indirect target genes. Bioinformatic analysis of the promoters of these direct target genes is able to locate motifs that are common to this sub-set of promoters, which is impossible to identify with the larger set of direct and indirect target genes. While this type of analysis does not prove a direct interaction between protein and DNA

Genome-wide characterization of differentially expressed genes provides insights into regulatory network of heat stress response in radish (Raphanus sativus L.).

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Wang, Ronghua; Mei, Yi; Xu, Liang; Zhu, Xianwen; Wang, Yan; Guo, Jun; Liu, Liwang

2018-03-01

Heat stress (HS) causes detrimental effects on plant morphology, physiology, and biochemistry that lead to drastic reduction in plant biomass production and economic yield worldwide. To date, little is known about HS-responsive genes involved in thermotolerance mechanism in radish. In this study, a total of 6600 differentially expressed genes (DEGs) from the control and Heat24 cDNA libraries of radish were isolated by high-throughput sequencing. With Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, some genes including MAPK, DREB, ERF, AP2, GST, Hsf, and Hsp were predominantly assigned in signal transductions, metabolic pathways, and biosynthesis and abiotic stress-responsive pathways. These pathways played significant roles in reducing stress-induced damages and enhancing heat tolerance in radish. Expression patterns of 24 candidate genes were validated by reverse-transcription quantitative PCR (RT-qPCR). Based mainly on the analysis of DEGs combining with the previous miRNAs analysis, the schematic model of HS-responsive regulatory network was proposed. To counter the effects of HS, a rapid response of the plasma membrane leads to the opening of specific calcium channels and cytoskeletal reorganization, after which HS-responsive genes are activated to repair damaged proteins and ultimately facilitate further enhancement of thermotolerance in radish. These results could provide fundamental insight into the regulatory network underlying heat tolerance in radish and facilitate further genetic manipulation of thermotolerance in root vegetable crops.

Identification of mechanosensitive genes during skeletal development: alteration of genes associated with cytoskeletal rearrangement and cell signalling pathways.

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Rolfe, Rebecca A; Nowlan, Niamh C; Kenny, Elaine M; Cormican, Paul; Morris, Derek W; Prendergast, Patrick J; Kelly, Daniel; Murphy, Paula

2014-01-20

into a transcriptional response. This work identifies key developmental regulatory genes impacted by altered mechanical stimulation, sheds light on the molecular mechanisms that interpret mechanical stimulation during skeletal development and provides valuable resources for further investigation of the mechanistic basis of mechanoregulation. In particular it highlights the Wnt signalling pathway as a potential point of integration of mechanical and molecular signalling and cytoskeletal components as mediators of the response.

Inference of Cancer-specific Gene Regulatory Networks Using Soft Computing Rules

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Xiaosheng Wang

2010-03-01

Full Text Available Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Current approaches to gene regulatory network modelling

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Brazma Alvis

2007-09-01

Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

Regulatory pathway analysis by high-throughput in situ hybridization.

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Axel Visel

2007-10-01

Full Text Available Automated in situ hybridization enables the construction of comprehensive atlases of gene expression patterns in mammals. Such atlases can become Web-searchable digital expression maps of individual genes and thus offer an entryway to elucidate genetic interactions and signaling pathways. Towards this end, an atlas housing approximately 1,000 spatial gene expression patterns of the midgestation mouse embryo was generated. Patterns were textually annotated using a controlled vocabulary comprising >90 anatomical features. Hierarchical clustering of annotations was carried out using distance scores calculated from the similarity between pairs of patterns across all anatomical structures. This process ordered hundreds of complex expression patterns into a matrix that reflects the embryonic architecture and the relatedness of patterns of expression. Clustering yielded 12 distinct groups of expression patterns. Because of the similarity of expression patterns within a group, members of each group may be components of regulatory cascades. We focused on the group containing Pax6, an evolutionary conserved transcriptional master mediator of development. Seventeen of the 82 genes in this group showed a change of expression in the developing neocortex of Pax6-deficient embryos. Electromobility shift assays were used to test for the presence of Pax6-paired domain binding sites. This led to the identification of 12 genes not previously known as potential targets of Pax6 regulation. These findings suggest that cluster analysis of annotated gene expression patterns obtained by automated in situ hybridization is a novel approach for identifying components of signaling cascades.

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

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Koumakis, Lefteris; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Vassou, Despoina; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-01-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the

Coexpression landscape in ATTED-II: usage of gene list and gene network for various types of pathways.

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Obayashi, Takeshi; Kinoshita, Kengo

2010-05-01

Gene coexpression analyses are a powerful method to predict the function of genes and/or to identify genes that are functionally related to query genes. The basic idea of gene coexpression analyses is that genes with similar functions should have similar expression patterns under many different conditions. This approach is now widely used by many experimental researchers, especially in the field of plant biology. In this review, we will summarize recent successful examples obtained by using our gene coexpression database, ATTED-II. Specifically, the examples will describe the identification of new genes, such as the subunits of a complex protein, the enzymes in a metabolic pathway and transporters. In addition, we will discuss the discovery of a new intercellular signaling factor and new regulatory relationships between transcription factors and their target genes. In ATTED-II, we provide two basic views of gene coexpression, a gene list view and a gene network view, which can be used as guide gene approach and narrow-down approach, respectively. In addition, we will discuss the coexpression effectiveness for various types of gene sets.

Regulatory pathways for vaccines for developing countries.

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Milstien, Julie; Belgharbi, Lahouari

2004-01-01

Vaccines that are designed for use only in developing countries face regulatory hurdles that may restrict their use. There are two primary reasons for this: most regulatory authorities are set up to address regulation of products for use only within their jurisdictions and regulatory authorities in developing countries traditionally have been considered weak. Some options for regulatory pathways for such products have been identified: licensing in the country of manufacture, file review by the European Medicines Evaluation Agency on behalf of WHO, export to a country with a competent national regulatory authority (NRA) that could handle all regulatory functions for the developing country market, shared manufacturing and licensing in a developing country with competent manufacturing and regulatory capacity, and use of a contracted independent entity for global regulatory approval. These options have been evaluated on the basis of five criteria: assurance of all regulatory functions for the life of the product, appropriateness of epidemiological assessment, applicability to products no longer used in the domestic market of the manufacturing country, reduction of regulatory risk for the manufacturer, and existing rules and regulations for implementation. No one option satisfies all criteria. For all options, national infrastructures (including the underlying regulatory legislative framework, particularly to formulate and implement local evidence-based vaccine policy) must be developed. WHO has led work to develop this capacity with some success. The paper outlines additional areas of action required by the international community to assure development and use of vaccines needed for the developing world. PMID:15042235

Transcription factor trapping by RNA in gene regulatory elements.

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Sigova, Alla A; Abraham, Brian J; Ji, Xiong; Molinie, Benoit; Hannett, Nancy M; Guo, Yang Eric; Jangi, Mohini; Giallourakis, Cosmas C; Sharp, Phillip A; Young, Richard A

2015-11-20

Transcription factors (TFs) bind specific sequences in promoter-proximal and -distal DNA elements to regulate gene transcription. RNA is transcribed from both of these DNA elements, and some DNA binding TFs bind RNA. Hence, RNA transcribed from regulatory elements may contribute to stable TF occupancy at these sites. We show that the ubiquitously expressed TF Yin-Yang 1 (YY1) binds to both gene regulatory elements and their associated RNA species across the entire genome. Reduced transcription of regulatory elements diminishes YY1 occupancy, whereas artificial tethering of RNA enhances YY1 occupancy at these elements. We propose that RNA makes a modest but important contribution to the maintenance of certain TFs at gene regulatory elements and suggest that transcription of regulatory elements produces a positive-feedback loop that contributes to the stability of gene expression programs. Copyright © 2015, American Association for the Advancement of Science.

Evolutionary rate patterns of the Gibberellin pathway genes

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Zhang Fu-min

2009-08-01

Full Text Available Abstract Background Analysis of molecular evolutionary patterns of different genes within metabolic pathways allows us to determine whether these genes are subject to equivalent evolutionary forces and how natural selection shapes the evolution of proteins in an interacting system. Although previous studies found that upstream genes in the pathway evolved more slowly than downstream genes, the correlation between evolutionary rate and position of the genes in metabolic pathways as well as its implications in molecular evolution are still less understood. Results We sequenced and characterized 7 core structural genes of the gibberellin biosynthetic pathway from 8 representative species of the rice tribe (Oryzeae to address alternative hypotheses regarding evolutionary rates and patterns of metabolic pathway genes. We have detected significant rate heterogeneity among 7 GA pathway genes for both synonymous and nonsynonymous sites. Such rate variation is mostly likely attributed to differences of selection intensity rather than differential mutation pressures on the genes. Unlike previous argument that downstream genes in metabolic pathways would evolve more slowly than upstream genes, the downstream genes in the GA pathway did not exhibited the elevated substitution rate and instead, the genes that encode either the enzyme at the branch point (GA20ox or enzymes catalyzing multiple steps (KO, KAO and GA3ox in the pathway had the lowest evolutionary rates due to strong purifying selection. Our branch and codon models failed to detect signature of positive selection for any lineage and codon of the GA pathway genes. Conclusion This study suggests that significant heterogeneity of evolutionary rate of the GA pathway genes is mainly ascribed to differential constraint relaxation rather than the positive selection and supports the pathway flux theory that predicts that natural selection primarily targets enzymes that have the greatest control on fluxes.

LncRNAs in Secondary Hair Follicle of Cashmere Goat: Identification, Expression, and Their Regulatory Network in Wnt Signaling Pathway.

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Bai, Wen L; Zhao, Su J; Wang, Ze Y; Zhu, Yu B; Dang, Yun L; Cong, Yu Y; Xue, Hui L; Wang, Wei; Deng, Liang; Guo, Dan; Wang, Shi Q; Zhu, Yan X; Yin, Rong H

2018-07-03

Long noncoding RNAs (lncRNAs) are a novel class of eukaryotic transcripts. They are thought to act as a critical regulator of protein-coding gene expression. Herein, we identified and characterized 13 putative lncRNAs from the expressed sequence tags from secondary hair follicle of Cashmere goat. Furthermore, we investigated their transcriptional pattern in secondary hair follicle of Liaoning Cashmere goat during telogen and anagen phases. Also, we generated intracellular regulatory networks of upregulated lncRNAs at anagen in Wnt signaling pathway based on bioinformatics analysis. The relative expression of six putative lncRNAs (lncRNA-599618, -599556, -599554, -599547, -599531, and -599509) at the anagen phase is significantly higher than that at telogen. Compared with anagen, the relative expression of four putative lncRNAs (lncRNA-599528, -599518, -599511, and -599497) was found to be significantly upregulated at telogen phase. The network generated showed that a rich and complex regulatory relationship of the putative lncRNAs and related miRNAs with their target genes in Wnt signaling pathway. Our results from the present study provided a foundation for further elucidating the functional and regulatory mechanisms of these putative lncRNAs in the development of secondary hair follicle and cashmere fiber growth of Cashmere goat.

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato; Kuwahara, Hiroyuki; Yu, Ge; Guo, Lili; Gao, Xin

2016-01-01

An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato

2016-08-25

An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

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

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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

Inferring Gene Regulatory Networks Using Conditional Regulation Pattern to Guide Candidate Genes.

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Fei Xiao

Full Text Available Combining path consistency (PC algorithms with conditional mutual information (CMI are widely used in reconstruction of gene regulatory networks. CMI has many advantages over Pearson correlation coefficient in measuring non-linear dependence to infer gene regulatory networks. It can also discriminate the direct regulations from indirect ones. However, it is still a challenge to select the conditional genes in an optimal way, which affects the performance and computation complexity of the PC algorithm. In this study, we develop a novel conditional mutual information-based algorithm, namely RPNI (Regulation Pattern based Network Inference, to infer gene regulatory networks. For conditional gene selection, we define the co-regulation pattern, indirect-regulation pattern and mixture-regulation pattern as three candidate patterns to guide the selection of candidate genes. To demonstrate the potential of our algorithm, we apply it to gene expression data from DREAM challenge. Experimental results show that RPNI outperforms existing conditional mutual information-based methods in both accuracy and time complexity for different sizes of gene samples. Furthermore, the robustness of our algorithm is demonstrated by noisy interference analysis using different types of noise.

Integrated bioinformatic analysis unveils significant genes and pathways in the pathogenesis of supratentorial primitive neuroectodermal tumor

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Wang G

2018-04-01

Full Text Available Guang-Yu Wang,1,* Ling Li,2,* Bo Liu,1 Xiao Han,1 Chun-Hua Wang,1 Ji-Wen Wang3 1Department of Neurosurgery, 2Department of Pediatrics, Qilu Children’s Hospital of Shandong University, Jinan, Shandong, 3Department of Neurology, Shanghai Children’s Medical Center, Shanghai Jiaotong University School of Medicine, Pudong New District, Shanghai, People’s Republic of China *These authors contributed equally to this work Purpose: This study aimed to explore significant genes and pathways involved in the pathogenesis of supratentorial primitive neuroectodermal tumor (sPNET. Materials and methods: Gene expression profile of GSE14295 was downloaded from publicly available Gene Expression Omnibus (GEO database. Differentially expressed genes (DEGs were screened out in primary sPNET samples compared with normal fetal and adult brain reference samples (sPNET vs fetal brain and sPNET vs adult brain. Pathway enrichment analysis of these DEGs was conducted, followed by protein–protein interaction (PPI network construction and significant module selection. Additionally, transcription factors (TFs regulating the common DEGs in the two comparison groups were identified, and the regulatory network was constructed. Results: In total, 526 DEGs (99 up- and 427 downregulated in sPNET vs fetal brain and 815 DEGs (200 up- and 615 downregulated in sPNET vs adult brain were identified. DEGs in sPNET vs fetal brain and sPNET vs adult brain were associated with calcium signaling pathway, cell cycle, and p53 signaling pathway. CDK1, CDC20, BUB1B, and BUB1 were hub nodes in the PPI networks of DEGs in sPNET vs fetal brain and sPNET vs adult brain. Significant modules were extracted from the PPI networks. In addition, 64 upregulated and 200 downregulated overlapping DEGs were identified in both sPNET vs fetal brain and sPNET vs adult brain. The genes involved in the regulatory network upon overlapping DEGs and the TFs were correlated with calcium signaling pathway

Integrative analysis of RUNX1 downstream pathways and target genes

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Liu Marjorie

2008-07-01

Full Text Available Abstract Background The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML. The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. Results Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1 cell lines with RUNX1 mutations from FPD-AML patients, 2 over-expression of RUNX1 and CBFβ, and 3 Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFβ. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. Conclusion This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease

Mutational robustness of gene regulatory networks.

Directory of Open Access Journals (Sweden)

Aalt D J van Dijk

Full Text Available Mutational robustness of gene regulatory networks refers to their ability to generate constant biological output upon mutations that change network structure. Such networks contain regulatory interactions (transcription factor-target gene interactions but often also protein-protein interactions between transcription factors. Using computational modeling, we study factors that influence robustness and we infer several network properties governing it. These include the type of mutation, i.e. whether a regulatory interaction or a protein-protein interaction is mutated, and in the case of mutation of a regulatory interaction, the sign of the interaction (activating vs. repressive. In addition, we analyze the effect of combinations of mutations and we compare networks containing monomeric with those containing dimeric transcription factors. Our results are consistent with available data on biological networks, for example based on evolutionary conservation of network features. As a novel and remarkable property, we predict that networks are more robust against mutations in monomer than in dimer transcription factors, a prediction for which analysis of conservation of DNA binding residues in monomeric vs. dimeric transcription factors provides indirect evidence.

Transcriptome Analysis of Three Sheep Intestinal Regions reveals Key Pathways and Hub Regulatory Genes of Large Intestinal Lipid Metabolism.

Science.gov (United States)

Chao, Tianle; Wang, Guizhi; Ji, Zhibin; Liu, Zhaohua; Hou, Lei; Wang, Jin; Wang, Jianmin

2017-07-13

The large intestine, also known as the hindgut, is an important part of the animal digestive system. Recent studies on digestive system development in ruminants have focused on the rumen and the small intestine, but the molecular mechanisms underlying sheep large intestine metabolism remain poorly understood. To identify genes related to intestinal metabolism and to reveal molecular regulation mechanisms, we sequenced and compared the transcriptomes of mucosal epithelial tissues among the cecum, proximal colon and duodenum. A total of 4,221 transcripts from 3,254 genes were identified as differentially expressed transcripts. Between the large intestine and duodenum, differentially expressed transcripts were found to be significantly enriched in 6 metabolism-related pathways, among which PPAR signaling was identified as a key pathway. Three genes, CPT1A, LPL and PCK1, were identified as higher expression hub genes in the large intestine. Between the cecum and colon, differentially expressed transcripts were significantly enriched in 5 lipid metabolism related pathways, and CEPT1 and MBOAT1 were identified as hub genes. This study provides important information regarding the molecular mechanisms of intestinal metabolism in sheep and may provide a basis for further study.

Learning gene regulatory networks from only positive and unlabeled data

Directory of Open Access Journals (Sweden)

Elkan Charles

2010-05-01

Full Text Available Abstract Background Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled as a binary classification problem for each pair of genes. A statistical classifier is trained to recognize the relationships between the activation profiles of gene pairs. This approach has been proven to outperform previous unsupervised methods. However, the supervised approach raises open questions. In particular, although known regulatory connections can safely be assumed to be positive training examples, obtaining negative examples is not straightforward, because definite knowledge is typically not available that a given pair of genes do not interact. Results A recent advance in research on data mining is a method capable of learning a classifier from only positive and unlabeled examples, that does not need labeled negative examples. Applied to the reconstruction of gene regulatory networks, we show that this method significantly outperforms the current state of the art of machine learning methods. We assess the new method using both simulated and experimental data, and obtain major performance improvement. Conclusions Compared to unsupervised methods for gene network inference, supervised methods are potentially more accurate, but for training they need a complete set of known regulatory connections. A supervised method that can be trained using only positive and unlabeled data, as presented in this paper, is especially beneficial for the task of inferring gene regulatory networks, because only an incomplete set of known regulatory connections is available in public databases such as RegulonDB, TRRD, KEGG, Transfac, and IPA.

Sparsity in Model Gene Regulatory Networks

International Nuclear Information System (INIS)

Zagorski, M.

2011-01-01

We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)

Regulatory Oversight of Cell and Gene Therapy Products in Canada.

Science.gov (United States)

Ridgway, Anthony; Agbanyo, Francisca; Wang, Jian; Rosu-Myles, Michael

2015-01-01

Health Canada regulates gene therapy products and many cell therapy products as biological drugs under the Canadian Food and Drugs Act and its attendant regulations. Cellular products that meet certain criteria, including minimal manipulation and homologous use, may be subjected to a standards-based approach under the Safety of Human Cells, Tissues and Organs for Transplantation Regulations. The manufacture and clinical testing of cell and gene therapy products (CGTPs) presents many challenges beyond those for protein biologics. Cells cannot be subjected to pathogen removal or inactivation procedures and must frequently be administered shortly after final formulation. Viral vector design and manufacturing control are critically important to overall product quality and linked to safety and efficacy in patients through concerns such as replication competence, vector integration, and vector shedding. In addition, for many CGTPs, the value of nonclinical studies is largely limited to providing proof of concept, and the first meaningful data relating to appropriate dosing, safety parameters, and validity of surrogate or true determinants of efficacy must come from carefully designed clinical trials in patients. Addressing these numerous challenges requires application of various risk mitigation strategies and meeting regulatory expectations specifically adapted to the product types. Regulatory cooperation and harmonisation at an international level are essential for progress in the development and commercialisation of these products. However, particularly in the area of cell therapy, new regulatory paradigms may be needed to harness the benefits of clinical progress in situations where the resources and motivation to pursue a typical drug product approval pathway may be lacking.

Genetic variation in mitotic regulatory pathway genes is associated with breast tumor grade

Science.gov (United States)

Purrington, Kristen S.; Slettedahl, Seth; Bolla, Manjeet K.; Michailidou, Kyriaki; Czene, Kamila; Nevanlinna, Heli; Bojesen, Stig E.; Andrulis, Irene L.; Cox, Angela; Hall, Per; Carpenter, Jane; Yannoukakos, Drakoulis; Haiman, Christopher A.; Fasching, Peter A.; Mannermaa, Arto; Winqvist, Robert; Brenner, Hermann; Lindblom, Annika; Chenevix-Trench, Georgia; Benitez, Javier; Swerdlow, Anthony; Kristensen, Vessela; Guénel, Pascal; Meindl, Alfons; Darabi, Hatef; Eriksson, Mikael; Fagerholm, Rainer; Aittomäki, Kristiina; Blomqvist, Carl; Nordestgaard, Børge G.; Nielsen, Sune F.; Flyger, Henrik; Wang, Xianshu; Olswold, Curtis; Olson, Janet E.; Mulligan, Anna Marie; Knight, Julia A.; Tchatchou, Sandrine; Reed, Malcolm W.R.; Cross, Simon S.; Liu, Jianjun; Li, Jingmei; Humphreys, Keith; Clarke, Christine; Scott, Rodney; Fostira, Florentia; Fountzilas, George; Konstantopoulou, Irene; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Ekici, Arif B.; Hartmann, Arndt; Beckmann, Matthias W.; Hartikainen, Jaana M.; Kosma, Veli-Matti; Kataja, Vesa; Jukkola-Vuorinen, Arja; Pylkäs, Katri; Kauppila, Saila; Dieffenbach, Aida Karina; Stegmaier, Christa; Arndt, Volker; Margolin, Sara; Balleine, Rosemary; Arias Perez, Jose Ignacio; Pilar Zamora, M.; Menéndez, Primitiva; Ashworth, Alan; Jones, Michael; Orr, Nick; Arveux, Patrick; Kerbrat, Pierre; Truong, Thérèse; Bugert, Peter; Toland, Amanda E.; Ambrosone, Christine B.; Labrèche, France; Goldberg, Mark S.; Dumont, Martine; Ziogas, Argyrios; Lee, Eunjung; Dite, Gillian S.; Apicella, Carmel; Southey, Melissa C.; Long, Jirong; Shrubsole, Martha; Deming-Halverson, Sandra; Ficarazzi, Filomena; Barile, Monica; Peterlongo, Paolo; Durda, Katarzyna; Jaworska-Bieniek, Katarzyna; Tollenaar, Robert A.E.M.; Seynaeve, Caroline; Brüning, Thomas; Ko, Yon-Dschun; Van Deurzen, Carolien H.M.; Martens, John W.M.; Kriege, Mieke; Figueroa, Jonine D.; Chanock, Stephen J.; Lissowska, Jolanta; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Schneeweiss, Andreas; Tapper, William J.; Gerty, Susan M.; Durcan, Lorraine; Mclean, Catriona; Milne, Roger L.; Baglietto, Laura; dos Santos Silva, Isabel; Fletcher, Olivia; Johnson, Nichola; Van'T Veer, Laura J.; Cornelissen, Sten; Försti, Asta; Torres, Diana; Rüdiger, Thomas; Rudolph, Anja; Flesch-Janys, Dieter; Nickels, Stefan; Weltens, Caroline; Floris, Giuseppe; Moisse, Matthieu; Dennis, Joe; Wang, Qin; Dunning, Alison M.; Shah, Mitul; Brown, Judith; Simard, Jacques; Anton-Culver, Hoda; Neuhausen, Susan L.; Hopper, John L.; Bogdanova, Natalia; Dörk, Thilo; Zheng, Wei; Radice, Paolo; Jakubowska, Anna; Lubinski, Jan; Devillee, Peter; Brauch, Hiltrud; Hooning, Maartje; García-Closas, Montserrat; Sawyer, Elinor; Burwinkel, Barbara; Marmee, Frederick; Eccles, Diana M.; Giles, Graham G.; Peto, Julian; Schmidt, Marjanka; Broeks, Annegien; Hamann, Ute; Chang-Claude, Jenny; Lambrechts, Diether; Pharoah, Paul D.P.; Easton, Douglas; Pankratz, V. Shane; Slager, Susan; Vachon, Celine M.; Couch, Fergus J.

2014-01-01

Mitotic index is an important component of histologic grade and has an etiologic role in breast tumorigenesis. Several small candidate gene studies have reported associations between variation in mitotic genes and breast cancer risk. We measured associations between 2156 single nucleotide polymorphisms (SNPs) from 194 mitotic genes and breast cancer risk, overall and by histologic grade, in the Breast Cancer Association Consortium (BCAC) iCOGS study (n = 39 067 cases; n = 42 106 controls). SNPs in TACC2 [rs17550038: odds ratio (OR) = 1.24, 95% confidence interval (CI) 1.16–1.33, P = 4.2 × 10−10) and EIF3H (rs799890: OR = 1.07, 95% CI 1.04–1.11, P = 8.7 × 10−6) were significantly associated with risk of low-grade breast cancer. The TACC2 signal was retained (rs17550038: OR = 1.15, 95% CI 1.07–1.23, P = 7.9 × 10−5) after adjustment for breast cancer risk SNPs in the nearby FGFR2 gene, suggesting that TACC2 is a novel, independent genome-wide significant genetic risk locus for low-grade breast cancer. While no SNPs were individually associated with high-grade disease, a pathway-level gene set analysis showed that variation across the 194 mitotic genes was associated with high-grade breast cancer risk (P = 2.1 × 10−3). These observations will provide insight into the contribution of mitotic defects to histological grade and the etiology of breast cancer. PMID:24927736

Learning Gene Regulatory Networks Computationally from Gene Expression Data Using Weighted Consensus

KAUST Repository

Fujii, Chisato

2015-04-16

Gene regulatory networks analyze the relationships between genes allowing us to un- derstand the gene regulatory interactions in systems biology. Gene expression data from the microarray experiments is used to obtain the gene regulatory networks. How- ever, the microarray data is discrete, noisy and non-linear which makes learning the networks a challenging problem and existing gene network inference methods do not give consistent results. Current state-of-the-art study uses the average-ranking-based consensus method to combine and average the ranked predictions from individual methods. However each individual method has an equal contribution to the consen- sus prediction. We have developed a linear programming-based consensus approach which uses learned weights from linear programming among individual methods such that the methods have di↵erent weights depending on their performance. Our result reveals that assigning di↵erent weights to individual methods rather than giving them equal weights improves the performance of the consensus. The linear programming- based consensus method is evaluated and it had the best performance on in silico and Saccharomyces cerevisiae networks, and the second best on the Escherichia coli network outperformed by Inferelator Pipeline method which gives inconsistent results across a wide range of microarray data sets.

Genes and (Common) Pathways Underlying Drug Addiction

Science.gov (United States)

Li, Chuan-Yun; Mao, Xizeng; Wei, Liping

2008-01-01

Drug addiction is a serious worldwide problem with strong genetic and environmental influences. Different technologies have revealed a variety of genes and pathways underlying addiction; however, each individual technology can be biased and incomplete. We integrated 2,343 items of evidence from peer-reviewed publications between 1976 and 2006 linking genes and chromosome regions to addiction by single-gene strategies, microrray, proteomics, or genetic studies. We identified 1,500 human addiction-related genes and developed KARG (http://karg.cbi.pku.edu.cn), the first molecular database for addiction-related genes with extensive annotations and a friendly Web interface. We then performed a meta-analysis of 396 genes that were supported by two or more independent items of evidence to identify 18 molecular pathways that were statistically significantly enriched, covering both upstream signaling events and downstream effects. Five molecular pathways significantly enriched for all four different types of addictive drugs were identified as common pathways which may underlie shared rewarding and addictive actions, including two new ones, GnRH signaling pathway and gap junction. We connected the common pathways into a hypothetical common molecular network for addiction. We observed that fast and slow positive feedback loops were interlinked through CAMKII, which may provide clues to explain some of the irreversible features of addiction. PMID:18179280

Genes and (common pathways underlying drug addiction.

Directory of Open Access Journals (Sweden)

Chuan-Yun Li

2008-01-01

Full Text Available Drug addiction is a serious worldwide problem with strong genetic and environmental influences. Different technologies have revealed a variety of genes and pathways underlying addiction; however, each individual technology can be biased and incomplete. We integrated 2,343 items of evidence from peer-reviewed publications between 1976 and 2006 linking genes and chromosome regions to addiction by single-gene strategies, microrray, proteomics, or genetic studies. We identified 1,500 human addiction-related genes and developed KARG (http://karg.cbi.pku.edu.cn, the first molecular database for addiction-related genes with extensive annotations and a friendly Web interface. We then performed a meta-analysis of 396 genes that were supported by two or more independent items of evidence to identify 18 molecular pathways that were statistically significantly enriched, covering both upstream signaling events and downstream effects. Five molecular pathways significantly enriched for all four different types of addictive drugs were identified as common pathways which may underlie shared rewarding and addictive actions, including two new ones, GnRH signaling pathway and gap junction. We connected the common pathways into a hypothetical common molecular network for addiction. We observed that fast and slow positive feedback loops were interlinked through CAMKII, which may provide clues to explain some of the irreversible features of addiction.

Creating and validating cis-regulatory maps of tissue-specific gene expression regulation

Science.gov (United States)

O'Connor, Timothy R.; Bailey, Timothy L.

2014-01-01

Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules–CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for ‘other’ tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a ‘nearest neighbor’ heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps. PMID:25200088

Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.

Science.gov (United States)

Rubiolo, Mariano; Milone, Diego H; Stegmayer, Georgina

2015-01-01

Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel method based on a pool of neural networks for obtaining a gene regulatory network from a gene expression dataset. They are used for modeling each possible interaction between pairs of genes in the dataset, and a set of mining rules is applied to accurately detect the subjacent relations among genes. The results obtained on artificial and real datasets confirm the method effectiveness for discovering regulatory networks from a proper modeling of the temporal dynamics of gene expression profiles.

Ancestral regulatory circuits governing ectoderm patterning downstream of Nodal and BMP2/4 revealed by gene regulatory network analysis in an echinoderm.

Directory of Open Access Journals (Sweden)

Alexandra Saudemont

2010-12-01

Full Text Available Echinoderms, which are phylogenetically related to vertebrates and produce large numbers of transparent embryos that can be experimentally manipulated, offer many advantages for the analysis of the gene regulatory networks (GRN regulating germ layer formation. During development of the sea urchin embryo, the ectoderm is the source of signals that pattern all three germ layers along the dorsal-ventral axis. How this signaling center controls patterning and morphogenesis of the embryo is not understood. Here, we report a large-scale analysis of the GRN deployed in response to the activity of this signaling center in the embryos of the Mediterranean sea urchin Paracentrotus lividus, in which studies with high spatial resolution are possible. By using a combination of in situ hybridization screening, overexpression of mRNA, recombinant ligand treatments, and morpholino-based loss-of-function studies, we identified a cohort of transcription factors and signaling molecules expressed in the ventral ectoderm, dorsal ectoderm, and interposed neurogenic ("ciliary band" region in response to the known key signaling molecules Nodal and BMP2/4 and defined the epistatic relationships between the most important genes. The resultant GRN showed a number of striking features. First, Nodal was found to be essential for the expression of all ventral and dorsal marker genes, and BMP2/4 for all dorsal genes. Second, goosecoid was identified as a central player in a regulatory sub-circuit controlling mouth formation, while tbx2/3 emerged as a critical factor for differentiation of the dorsal ectoderm. Finally, and unexpectedly, a neurogenic ectoderm regulatory circuit characterized by expression of "ciliary band" genes was triggered in the absence of TGF beta signaling. We propose a novel model for ectoderm regionalization, in which neural ectoderm is the default fate in the absence of TGF beta signaling, and suggest that the stomodeal and neural subcircuits that we

Gene dosage compensation calibrates four regulatory RNAs to control Vibrio cholerae quorum sensing

DEFF Research Database (Denmark)

Svenningsen, Sine L; Tu, Kimberly C; Bassler, Bonnie L

2009-01-01

the quorum regulatory RNAs 1-4 (Qrr1-4). The four Qrr sRNAs are functionally redundant. That is, expression of any one of them is sufficient for wild-type quorum-sensing behaviour. Here, we show that the combined action of two feedback loops, one involving the sRNA-activator LuxO and one involving the sRNA......Quorum sensing is a mechanism of cell-to-cell communication that allows bacteria to coordinately regulate gene expression in response to changes in cell-population density. At the core of the Vibrio cholerae quorum-sensing signal transduction pathway reside four homologous small RNAs (sRNAs), named......-target HapR, promotes gene dosage compensation between the four qrr genes. Gene dosage compensation adjusts the total Qrr1-4 sRNA pool and provides the molecular mechanism underlying sRNA redundancy. The dosage compensation mechanism is exquisitely sensitive to small perturbations in Qrr levels. Precisely...

Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

Science.gov (United States)

Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

2017-11-20

Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Interactive visualization of gene regulatory networks with associated gene expression time series data

NARCIS (Netherlands)

Westenberg, M.A.; Hijum, van S.A.F.T.; Lulko, A.T.; Kuipers, O.P.; Roerdink, J.B.T.M.; Linsen, L.; Hagen, H.; Hamann, B.

2008-01-01

We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes,

Identification of a new gene regulatory circuit involving B cell receptor activated signaling using a combined analysis of experimental, clinical and global gene expression data

Science.gov (United States)

Schrader, Alexandra; Meyer, Katharina; Walther, Neele; Stolz, Ailine; Feist, Maren; Hand, Elisabeth; von Bonin, Frederike; Evers, Maurits; Kohler, Christian; Shirneshan, Katayoon; Vockerodt, Martina; Klapper, Wolfram; Szczepanowski, Monika; Murray, Paul G.; Bastians, Holger; Trümper, Lorenz; Spang, Rainer; Kube, Dieter

2016-01-01

To discover new regulatory pathways in B lymphoma cells, we performed a combined analysis of experimental, clinical and global gene expression data. We identified a specific cluster of genes that was coherently expressed in primary lymphoma samples and suppressed by activation of the B cell receptor (BCR) through αIgM treatment of lymphoma cells in vitro. This gene cluster, which we called BCR.1, includes numerous cell cycle regulators. A reduced expression of BCR.1 genes after BCR activation was observed in different cell lines and also in CD10+ germinal center B cells. We found that BCR activation led to a delayed entry to and progression of mitosis and defects in metaphase. Cytogenetic changes were detected upon long-term αIgM treatment. Furthermore, an inverse correlation of BCR.1 genes with c-Myc co-regulated genes in distinct groups of lymphoma patients was observed. Finally, we showed that the BCR.1 index discriminates activated B cell-like and germinal centre B cell-like diffuse large B cell lymphoma supporting the functional relevance of this new regulatory circuit and the power of guided clustering for biomarker discovery. PMID:27166259

A Model of an Integrated Immune System Pathway in Homo sapiens and Its Interaction with Superantigen Producing Expression Regulatory Pathway in Staphylococcus aureus: Comparing Behavior of Pathogen Perturbed and Unperturbed Pathway

Science.gov (United States)

Tomar, Namrata; De, Rajat K.

2013-01-01

Response of an immune system to a pathogen attack depends on the balance between the host immune defense and the virulence of the pathogen. Investigation of molecular interactions between the proteins of a host and a pathogen helps in identifying the pathogenic proteins. It is necessary to understand the dynamics of a normally behaved host system to evaluate the capacity of its immune system upon pathogen attack. In this study, we have compared the behavior of an unperturbed and pathogen perturbed host system. Moreover, we have developed a formalism under Flux Balance Analysis (FBA) for the optimization of conflicting objective functions. We have constructed an integrated pathway system, which includes Staphylococcal Superantigen (SAg) expression regulatory pathway and TCR signaling pathway of Homo sapiens. We have implemented the method on this pathway system and observed the behavior of host signaling molecules upon pathogen attack. The entire study has been divided into six different cases, based on the perturbed/unperturbed conditions. In other words, we have investigated unperturbed and pathogen perturbed human TCR signaling pathway, with different combinations of optimization of concentrations of regulatory and signaling molecules. One of these cases has aimed at finding out whether minimization of the toxin production in a pathogen leads to the change in the concentration levels of the proteins coded by TCR signaling pathway genes in the infected host. Based on the computed results, we have hypothesized that the balance between TCR signaling inhibitory and stimulatory molecules can keep TCR signaling system into resting/stimulating state, depending upon the perturbation. The proposed integrated host-pathogen interaction pathway model has accurately reflected the experimental evidences, which we have used for validation purpose. The significance of this kind of investigation lies in revealing the susceptible interaction points that can take back the

Deconstructing the pluripotency gene regulatory network

KAUST Repository

Li, Mo

2018-04-04

Pluripotent stem cells can be isolated from embryos or derived by reprogramming. Pluripotency is stabilized by an interconnected network of pluripotency genes that cooperatively regulate gene expression. Here we describe the molecular principles of pluripotency gene function and highlight post-transcriptional controls, particularly those induced by RNA-binding proteins and alternative splicing, as an important regulatory layer of pluripotency. We also discuss heterogeneity in pluripotency regulation, alternative pluripotency states and future directions of pluripotent stem cell research.

Deconstructing the pluripotency gene regulatory network

KAUST Repository

Li, Mo; Belmonte, Juan Carlos Izpisua

2018-01-01

Pluripotent stem cells can be isolated from embryos or derived by reprogramming. Pluripotency is stabilized by an interconnected network of pluripotency genes that cooperatively regulate gene expression. Here we describe the molecular principles of pluripotency gene function and highlight post-transcriptional controls, particularly those induced by RNA-binding proteins and alternative splicing, as an important regulatory layer of pluripotency. We also discuss heterogeneity in pluripotency regulation, alternative pluripotency states and future directions of pluripotent stem cell research.

Characterization of WRKY co-regulatory networks in rice and Arabidopsis

Directory of Open Access Journals (Sweden)

Kikuchi Shoshi

2009-09-01

Full Text Available Abstract Background The WRKY transcription factor gene family has a very ancient origin and has undergone extensive duplications in the plant kingdom. Several studies have pointed out their involvement in a range of biological processes, revealing that a large number of WRKY genes are transcriptionally regulated under conditions of biotic and/or abiotic stress. To investigate the existence of WRKY co-regulatory networks in plants, a whole gene family WRKYs expression study was carried out in rice (Oryza sativa. This analysis was extended to Arabidopsis thaliana taking advantage of an extensive repository of gene expression data. Results The presented results suggested that 24 members of the rice WRKY gene family (22% of the total were differentially-regulated in response to at least one of the stress conditions tested. We defined the existence of nine OsWRKY gene clusters comprising both phylogenetically related and unrelated genes that were significantly co-expressed, suggesting that specific sets of WRKY genes might act in co-regulatory networks. This hypothesis was tested by Pearson Correlation Coefficient analysis of the Arabidopsis WRKY gene family in a large set of Affymetrix microarray experiments. AtWRKYs were found to belong to two main co-regulatory networks (COR-A, COR-B and two smaller ones (COR-C and COR-D, all including genes belonging to distinct phylogenetic groups. The COR-A network contained several AtWRKY genes known to be involved mostly in response to pathogens, whose physical and/or genetic interaction was experimentally proven. We also showed that specific co-regulatory networks were conserved between the two model species by identifying Arabidopsis orthologs of the co-expressed OsWRKY genes. Conclusion In this work we identified sets of co-expressed WRKY genes in both rice and Arabidopsis that are functionally likely to cooperate in the same signal transduction pathways. We propose that, making use of data from co-regulatory

The impact of gene expression variation on the robustness and evolvability of a developmental gene regulatory network.

Directory of Open Access Journals (Sweden)

David A Garfield

2013-10-01

Full Text Available Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear, allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.

Examination of tetrahydrobiopterin pathway genes in autism.

Science.gov (United States)

Schnetz-Boutaud, N C; Anderson, B M; Brown, K D; Wright, H H; Abramson, R K; Cuccaro, M L; Gilbert, J R; Pericak-Vance, M A; Haines, J L

2009-11-01

Autism is a complex disorder with a high degree of heritability and significant phenotypic and genotypic heterogeneity. Although candidate gene studies and genome-wide screens have failed to identify major causal loci associated with autism, numerous studies have proposed association with several variations in genes in the dopaminergic and serotonergic pathways. Because tetrahydrobiopterin (BH4) is the essential cofactor in the synthesis of these two neurotransmitters, we genotyped 25 SNPs in nine genes of the BH4 pathway in a total of 403 families. Significant nominal association was detected in the gene for 6-pyruvoyl-tetrahydropterin synthase, PTS (chromosome 11), with P = 0.009; this result was not restricted to an affected male-only subset. Multilocus interaction was detected in the BH4 pathway alone, but not across the serotonin, dopamine and BH4 pathways.

The Rose (Rosa hybrida) NAC Transcription Factor 3 Gene, RhNAC3, Involved in ABA Signaling Pathway Both in Rose and Arabidopsis

OpenAIRE

Jiang, Guimei; Jiang, Xinqiang; Lü, Peitao; Liu, Jitao; Gao, Junping; Zhang, Changqing

2014-01-01

Plant transcription factors involved in stress responses are generally classified by their involvement in either the abscisic acid (ABA)-dependent or the ABA-independent regulatory pathways. A stress-associated NAC gene from rose (Rosa hybrida), RhNAC3, was previously found to increase dehydration tolerance in both rose and Arabidopsis. However, the regulatory mechanism involved in RhNAC3 action is still not fully understood. In this study, we isolated and analyzed the upstream regulatory seq...

Evolutionary conservation of regulatory elements in vertebrate HOX gene clusters

Energy Technology Data Exchange (ETDEWEB)

Santini, Simona; Boore, Jeffrey L.; Meyer, Axel

2003-12-31

Due to their high degree of conservation, comparisons of DNA sequences among evolutionarily distantly-related genomes permit to identify functional regions in noncoding DNA. Hox genes are optimal candidate sequences for comparative genome analyses, because they are extremely conserved in vertebrates and occur in clusters. We aligned (Pipmaker) the nucleotide sequences of HoxA clusters of tilapia, pufferfish, striped bass, zebrafish, horn shark, human and mouse (over 500 million years of evolutionary distance). We identified several highly conserved intergenic sequences, likely to be important in gene regulation. Only a few of these putative regulatory elements have been previously described as being involved in the regulation of Hox genes, while several others are new elements that might have regulatory functions. The majority of these newly identified putative regulatory elements contain short fragments that are almost completely conserved and are identical to known binding sites for regulatory proteins (Transfac). The conserved intergenic regions located between the most rostrally expressed genes in the developing embryo are longer and better retained through evolution. We document that presumed regulatory sequences are retained differentially in either A or A clusters resulting from a genome duplication in the fish lineage. This observation supports both the hypothesis that the conserved elements are involved in gene regulation and the Duplication-Deletion-Complementation model.

A gene regulatory network armature for T-lymphocyte specification

Energy Technology Data Exchange (ETDEWEB)

Fung, Elizabeth-sharon [Los Alamos National Laboratory

2008-01-01

Choice of a T-lymphoid fate by hematopoietic progenitor cells depends on sustained Notch-Delta signaling combined with tightly-regulated activities of multiple transcription factors. To dissect the regulatory network connections that mediate this process, we have used high-resolution analysis of regulatory gene expression trajectories from the beginning to the end of specification; tests of the short-term Notchdependence of these gene expression changes; and perturbation analyses of the effects of overexpression of two essential transcription factors, namely PU.l and GATA-3. Quantitative expression measurements of >50 transcription factor and marker genes have been used to derive the principal components of regulatory change through which T-cell precursors progress from primitive multipotency to T-lineage commitment. Distinct parts of the path reveal separate contributions of Notch signaling, GATA-3 activity, and downregulation of PU.l. Using BioTapestry, the results have been assembled into a draft gene regulatory network for the specification of T-cell precursors and the choice of T as opposed to myeloid dendritic or mast-cell fates. This network also accommodates effects of E proteins and mutual repression circuits of Gfil against Egr-2 and of TCF-l against PU.l as proposed elsewhere, but requires additional functions that remain unidentified. Distinctive features of this network structure include the intense dose-dependence of GATA-3 effects; the gene-specific modulation of PU.l activity based on Notch activity; the lack of direct opposition between PU.l and GATA-3; and the need for a distinct, late-acting repressive function or functions to extinguish stem and progenitor-derived regulatory gene expression.

Dose response relationship in anti-stress gene regulatory networks.

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Zhang, Qiang; Andersen, Melvin E

2007-03-02

To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products) in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear) depends on changes in the specific values of local response coefficients (gains) distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear, and depending on

Dose response relationship in anti-stress gene regulatory networks.

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Qiang Zhang

2007-03-01

Full Text Available To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear depends on changes in the specific values of local response coefficients (gains distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear

Agrobacterium mediated transient gene silencing (AMTS in Stevia rebaudiana: insights into steviol glycoside biosynthesis pathway.

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Praveen Guleria

Full Text Available Steviol glycoside biosynthesis pathway has emerged as bifurcation from ent-kaurenoic acid, substrate of methyl erythritol phosphate pathway that also leads to gibberellin biosynthesis. However, the genetic regulation of steviol glycoside biosynthesis has not been studied. So, in present study RNA interference (RNAi based Agrobacterium mediated transient gene silencing (AMTS approach was followed. SrKA13H and three SrUGTs (SrUGT85C2, SrUGT74G1 and SrUGT76G1 genes encoding ent-kaurenoic acid-13 hydroxylase and three UDP glycosyltransferases of steviol glycoside biosynthesis pathway were silenced in Stevia rebaudiana to understand its molecular mechanism and association with gibberellins.RNAi mediated AMTS of SrKA13H and three SrUGTs has significantly reduced the expression of targeted endogenous genes as well as total steviol glycoside accumulation. While gibberellins (GA3 content was significantly enhanced on AMTS of SrUGT85C2 and SrKA13H. Silencing of SrKA13H and SrUGT85C2 was found to block the metabolite flux of steviol glycoside pathway and shifted it towards GA3 biosynthesis. Further, molecular docking of three SrUGT proteins has documented highest affinity of SrUGT76G1 for the substrates of alternate pathways synthesizing steviol glycosides. This could be a plausible reason for maximum reduction in steviol glycoside content on silencing of SrUGT76G1 than other genes.SrKA13H and SrUGT85C2 were identified as regulatory genes influencing carbon flux between steviol glycoside and gibberellin biosynthesis. This study has also documented the existence of alternate steviol glycoside biosynthesis route.

SLAM-seq defines direct gene-regulatory functions of the BRD4-MYC axis.

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Muhar, Matthias; Ebert, Anja; Neumann, Tobias; Umkehrer, Christian; Jude, Julian; Wieshofer, Corinna; Rescheneder, Philipp; Lipp, Jesse J; Herzog, Veronika A; Reichholf, Brian; Cisneros, David A; Hoffmann, Thomas; Schlapansky, Moritz F; Bhat, Pooja; von Haeseler, Arndt; Köcher, Thomas; Obenauf, Anna C; Popow, Johannes; Ameres, Stefan L; Zuber, Johannes

2018-05-18

Defining direct targets of transcription factors and regulatory pathways is key to understanding their roles in physiology and disease. We combined SLAM-seq [thiol(SH)-linked alkylation for the metabolic sequencing of RNA], a method for direct quantification of newly synthesized messenger RNAs (mRNAs), with pharmacological and chemical-genetic perturbation in order to define regulatory functions of two transcriptional hubs in cancer, BRD4 and MYC, and to interrogate direct responses to BET bromodomain inhibitors (BETis). We found that BRD4 acts as general coactivator of RNA polymerase II-dependent transcription, which is broadly repressed upon high-dose BETi treatment. At doses triggering selective effects in leukemia, BETis deregulate a small set of hypersensitive targets including MYC. In contrast to BRD4, MYC primarily acts as a selective transcriptional activator controlling metabolic processes such as ribosome biogenesis and de novo purine synthesis. Our study establishes a simple and scalable strategy to identify direct transcriptional targets of any gene or pathway. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Altered expression of hypoxia-inducible factor-1α (HIF-1α and its regulatory genes in gastric cancer tissues.

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Jihan Wang

Full Text Available Tissue hypoxia induces reprogramming of cell metabolism and may result in normal cell transformation and cancer progression. Hypoxia-inducible factor 1-alpha (HIF-1α, the key transcription factor, plays an important role in gastric cancer development and progression. This study aimed to investigate the underlying regulatory signaling pathway in gastric cancer using gastric cancer tissue specimens. The integration of gene expression profile and transcriptional regulatory element database (TRED was pursued to identify HIF-1α ↔ NFκB1 → BRCA1 → STAT3 ← STAT1 gene pathways and their regulated genes. The data showed that there were 82 differentially expressed genes that could be regulated by these five transcription factors in gastric cancer tissues and these genes formed 95 regulation modes, among which seven genes (MMP1, TIMP1, TLR2, FCGR3A, IRF1, FAS, and TFF3 were hub molecules that are regulated at least by two of these five transcription factors simultaneously and were associated with hypoxia, inflammation, and immune disorder. Real-Time PCR and western blot showed increasing of HIF-1α in mRNA and protein levels as well as TIMP1, TFF3 in mRNA levels in gastric cancer tissues. The data are the first study to demonstrate HIF-1α-regulated transcription factors and their corresponding network genes in gastric cancer. Further study with a larger sample size and more functional experiments is needed to confirm these data and then translate into clinical biomarker discovery and treatment strategy for gastric cancer.

Comparison of Current Regulatory Status for Gene-Based Vaccines in the U.S., Europe and Japan

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Yoshikazu Nakayama

2015-03-01

Full Text Available Gene-based vaccines as typified by plasmid DNA vaccines and recombinant viral-vectored vaccines are expected as promising solutions against infectious diseases for which no effective prophylactic vaccines exist such as HIV, dengue virus, Ebola virus and malaria, and for which more improved vaccines are needed such as tuberculosis and influenza virus. Although many preclinical and clinical trials have been conducted to date, no DNA vaccines or recombinant viral-vectored vaccines expressing heterologous antigens for human use have yet been licensed in the U.S., Europe or Japan. In this research, we describe the current regulatory context for gene-based prophylactic vaccines against infectious disease in the U.S., Europe, and Japan. We identify the important considerations, in particular, on the preclinical assessments that would allow these vaccines to proceed to clinical trials, and the differences on the regulatory pathway for the marketing authorization in each region.

Integration of steady-state and temporal gene expression data for the inference of gene regulatory networks.

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Wang, Yi Kan; Hurley, Daniel G; Schnell, Santiago; Print, Cristin G; Crampin, Edmund J

2013-01-01

We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and time-series data sets can successfully be combined to identify gene regulatory interactions using the new algorithm. Inferring gene networks from combined data sets was found to be advantageous when using noisy measurements collected with either lower sampling rates or a limited number of experimental replicates. We illustrate our method by applying it to a microarray gene expression dataset from human umbilical vein endothelial cells (HUVECs) which combines time series data from treatment with growth factor TNF and steady state data from siRNA knockdown treatments. Our results suggest that the combination of steady-state and time-series datasets may provide better prediction of RNA-to-RNA interactions, and may also reveal biological features that cannot be identified from dynamic or steady state information alone. Finally, we consider the experimental design of genomics experiments for gene regulatory network inference and show that network inference can be improved by incorporating steady-state measurements with time-series data.

Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice

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Shuchi eSmita

2015-12-01

Full Text Available MYB transcription factor (TF is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by top down and guide gene approaches. More than 50% of OsMYBs were strongly correlated under fifty experimental conditions with 51 hub genes via top down approach. Further, clusters were identified using Markov Clustering (MCL. To maximize the clustering performance, parameter evaluation of the MCL inflation score (I was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by guide gene approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought

Penalized differential pathway analysis of integrative oncogenomics studies.

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

2014-04-01

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

The transcriptional and gene regulatory network of Lactococcus lactis MG1363 during growth in milk.

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Anne de Jong

Full Text Available In the present study we examine the changes in the expression of genes of Lactococcus lactis subspecies cremoris MG1363 during growth in milk. To reveal which specific classes of genes (pathways, operons, regulons, COGs are important, we performed a transcriptome time series experiment. Global analysis of gene expression over time showed that L. lactis adapted quickly to the environmental changes. Using upstream sequences of genes with correlated gene expression profiles, we uncovered a substantial number of putative DNA binding motifs that may be relevant for L. lactis fermentative growth in milk. All available novel and literature-derived data were integrated into network reconstruction building blocks, which were used to reconstruct and visualize the L. lactis gene regulatory network. This network enables easy mining in the chrono-transcriptomics data. A freely available website at http://milkts.molgenrug.nl gives full access to all transcriptome data, to the reconstructed network and to the individual network building blocks.

Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

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Cicin-Sain, Damjan; Ashyraliyev, Maksat; Jaeger, Johannes

2012-01-01

Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to

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

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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

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

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

2014-12-10

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

The Alternative NF-κB Pathway in Regulatory T Cell Homeostasis and Suppressive Function.

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Grinberg-Bleyer, Yenkel; Caron, Rachel; Seeley, John J; De Silva, Nilushi S; Schindler, Christian W; Hayden, Matthew S; Klein, Ulf; Ghosh, Sankar

2018-04-01

CD4 + Foxp3 + regulatory T cells (Tregs) are essential regulators of immune responses. Perturbation of Treg homeostasis or function can lead to uncontrolled inflammation and autoimmunity. Therefore, understanding the molecular mechanisms involved in Treg biology remains an active area of investigation. It has been shown previously that the NF-κB family of transcription factors, in particular, the canonical pathway subunits, c-Rel and p65, are crucial for the development, maintenance, and function of Tregs. However, the role of the alternative NF-κB pathway components, p100 and RelB, in Treg biology remains unclear. In this article, we show that conditional deletion of the p100 gene, nfkb2 , in Tregs, resulted in massive inflammation because of impaired suppressive function of nfkb2 -deficient Tregs. Surprisingly, mice lacking RelB in Tregs did not exhibit the same phenotype. Instead, deletion of both relb and nfkb2 rescued the inflammatory phenotype, demonstrating an essential role for p100 as an inhibitor of RelB in Tregs. Our data therefore illustrate a new role for the alternative NF-κB signaling pathway in Tregs that has implications for the understanding of molecular pathways driving tolerance and immunity. Copyright © 2018 by The American Association of Immunologists, Inc.

Agrobacterium Mediated Transient Gene Silencing (AMTS) in Stevia rebaudiana: Insights into Steviol Glycoside Biosynthesis Pathway

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Guleria, Praveen; Yadav, Sudesh Kumar

2013-01-01

Background Steviol glycoside biosynthesis pathway has emerged as bifurcation from ent-kaurenoic acid, substrate of methyl erythritol phosphate pathway that also leads to gibberellin biosynthesis. However, the genetic regulation of steviol glycoside biosynthesis has not been studied. So, in present study RNA interference (RNAi) based Agrobacterium mediated transient gene silencing (AMTS) approach was followed. SrKA13H and three SrUGTs (SrUGT85C2, SrUGT74G1 and SrUGT76G1) genes encoding ent-kaurenoic acid-13 hydroxylase and three UDP glycosyltransferases of steviol glycoside biosynthesis pathway were silenced in Stevia rebaudiana to understand its molecular mechanism and association with gibberellins. Methodology/Principal Findings RNAi mediated AMTS of SrKA13H and three SrUGTs has significantly reduced the expression of targeted endogenous genes as well as total steviol glycoside accumulation. While gibberellins (GA3) content was significantly enhanced on AMTS of SrUGT85C2 and SrKA13H. Silencing of SrKA13H and SrUGT85C2 was found to block the metabolite flux of steviol glycoside pathway and shifted it towards GA3 biosynthesis. Further, molecular docking of three SrUGT proteins has documented highest affinity of SrUGT76G1 for the substrates of alternate pathways synthesizing steviol glycosides. This could be a plausible reason for maximum reduction in steviol glycoside content on silencing of SrUGT76G1 than other genes. Conclusions SrKA13H and SrUGT85C2 were identified as regulatory genes influencing carbon flux between steviol glycoside and gibberellin biosynthesis. This study has also documented the existence of alternate steviol glycoside biosynthesis route. PMID:24023961

Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data.

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Lee, Hyeonjeong; Shin, Miyoung

2017-01-01

The problem of discovering genetic markers as disease signatures is of great significance for the successful diagnosis, treatment, and prognosis of complex diseases. Even if many earlier studies worked on identifying disease markers from a variety of biological resources, they mostly focused on the markers of genes or gene-sets (i.e., pathways). However, these markers may not be enough to explain biological interactions between genetic variables that are related to diseases. Thus, in this study, our aim is to investigate distinctive associations among active pathways (i.e., pathway-sets) shown each in case and control samples which can be observed from gene expression and/or methylation data. The pathway-sets are obtained by identifying a set of associated pathways that are often active together over a significant number of class samples. For this purpose, gene expression or methylation profiles are first analyzed to identify significant (active) pathways via gene-set enrichment analysis. Then, regarding these active pathways, an association rule mining approach is applied to examine interesting pathway-sets in each class of samples (case or control). By doing so, the sets of associated pathways often working together in activity profiles are finally chosen as our distinctive signature of each class. The identified pathway-sets are aggregated into a pathway activity network (PAN), which facilitates the visualization of differential pathway associations between case and control samples. From our experiments with two publicly available datasets, we could find interesting PAN structures as the distinctive signatures of breast cancer and uterine leiomyoma cancer, respectively. Our pathway-set markers were shown to be superior or very comparable to other genetic markers (such as genes or gene-sets) in disease classification. Furthermore, the PAN structure, which can be constructed from the identified markers of pathway-sets, could provide deeper insights into

Overlapping positive and negative regulatory domains of the human β-interferon gene

International Nuclear Information System (INIS)

Goodbourn, S.; Maniatis, T.

1988-01-01

Virus of poly(I) x poly(C) induction of human β-interferon gene expression requires a 40-base-pair DNA sequence designated the interferon gene regulatory element (IRE). Previous studies have shown that the IRE contains both positive and negative regulatory DNA sequences. To localize these sequences and study their interactions, the authors have examined the effects of a large number of single-base mutations within the IRE on β-interferon gene regulation. They find that the IRE consists of two genetically separable positive regulatory domains and an overlapping negative control sequence. They propose that the β-interferon gene is switched off in uninduced cells by a repressor that blocks the interaction between one of the two positive regulatory sequences and a specific transcription factor. Induction would then lead to inactivation or displacement of the repressor and binding of transcription factors to both positive regulatory domains

Modeling stochasticity and robustness in gene regulatory networks.

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Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis

2009-06-15

Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).

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Huan, Jinliang; Wang, Lishan; Xing, Li; Qin, Xianju; Feng, Lingbin; Pan, Xiaofeng; Zhu, Ling

2014-01-01

Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628 (12h), 852 (24h) and 880 (48 h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathway enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time point. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, and chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction and calcium signaling pathway. At 48 h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway (TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its

Pharmacodynamic/Pharmacogenomic Modeling of Insulin Resistance Genes in Rat Muscle After Methylprednisolone Treatment: Exploring Regulatory Signaling Cascades

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Zhenling Yao

2008-01-01

Full Text Available Corticosteroids (CS effects on insulin resistance related genes in rat skeletal muscle were studied. In our acute study, adrenalectomized (ADX rats were given single doses of 50 mg/kg methylprednisolone (MPL intravenously. In our chronic study, ADX rats were implanted with Alzet mini-pumps giving zero-order release rates of 0.3 mg/kg/h MPL and sacrificed at various times up to 7 days. Total RNA was extracted from gastrocnemius muscles and hybridized to Affymetrix GeneChips. Data mining and literature searches identified 6 insulin resistance related genes which exhibited complex regulatory pathways. Insulin receptor substrate-1 (IRS-1, uncoupling protein 3 (UCP3, pyruvate dehydrogenase kinase isoenzyme 4 (PDK4, fatty acid translocase (FAT and glycerol-3-phosphate acyltransferase (GPAT dynamic profiles were modeled with mutual effects by calculated nuclear drug-receptor complex (DR(N and transcription factors. The oscillatory feature of endothelin-1 (ET-1 expression was depicted by a negative feedback loop. These integrated models provide test- able quantitative hypotheses for these regulatory cascades.

Study on the regulatory mechanism of the lipid metabolism pathways during chicken male germ cell differentiation based on RNA-seq.

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Zuo, Qisheng; Li, Dong; Zhang, Lei; Elsayed, Ahmed Kamel; Lian, Chao; Shi, Qingqing; Zhang, Zhentao; Zhu, Rui; Wang, Yinjie; Jin, Kai; Zhang, Yani; Li, Bichun

2015-01-01

Here, we explore the regulatory mechanism of lipid metabolic signaling pathways and related genes during differentiation of male germ cells in chickens, with the hope that better understanding of these pathways may improve in vitro induction. Fluorescence-activated cell sorting was used to obtain highly purified cultures of embryonic stem cells (ESCs), primitive germ cells (PGCs), and spermatogonial stem cells (SSCs). The total RNA was then extracted from each type of cell. High-throughput analysis methods (RNA-seq) were used to sequence the transcriptome of these cells. Gene Ontology (GO) analysis and the KEGG database were used to identify lipid metabolism pathways and related genes. Retinoic acid (RA), the end-product of the retinol metabolism pathway, induced in vitro differentiation of ESC into male germ cells. Quantitative real-time PCR (qRT-PCR) was used to detect changes in the expression of the genes involved in the retinol metabolic pathways. From the results of RNA-seq and the database analyses, we concluded that there are 328 genes in 27 lipid metabolic pathways continuously involved in lipid metabolism during the differentiation of ESC into SSC in vivo, including retinol metabolism. Alcohol dehydrogenase 5 (ADH5) and aldehyde dehydrogenase 1 family member A1 (ALDH1A1) are involved in RA synthesis in the cell. ADH5 was specifically expressed in PGC in our experiments and aldehyde dehydrogenase 1 family member A1 (ALDH1A1) persistently increased throughout development. CYP26b1, a member of the cytochrome P450 superfamily, is involved in the degradation of RA. Expression of CYP26b1, in contrast, decreased throughout development. Exogenous RA in the culture medium induced differentiation of ESC to SSC-like cells. The expression patterns of ADH5, ALDH1A1, and CYP26b1 were consistent with RNA-seq results. We conclude that the retinol metabolism pathway plays an important role in the process of chicken male germ cell differentiation.

Coordinated transcriptional regulation of two key genes in the lignin branch pathway--CAD and CCR--is mediated through MYB- binding sites.

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Rahantamalala, Anjanirina; Rech, Philippe; Martinez, Yves; Chaubet-Gigot, Nicole; Grima-Pettenati, Jacqueline; Pacquit, Valérie

2010-06-28

Cinnamoyl CoA reductase (CCR) and cinnamyl alcohol dehydrogenase (CAD) catalyze the final steps in the biosynthesis of monolignols, the monomeric units of the phenolic lignin polymers which confer rigidity, imperviousness and resistance to biodegradation to cell walls. We have previously shown that the Eucalyptus gunnii CCR and CAD2 promoters direct similar expression patterns in vascular tissues suggesting that monolignol production is controlled, at least in part, by the coordinated transcriptional regulation of these two genes. Although consensus motifs for MYB transcription factors occur in most gene promoters of the whole phenylpropanoid pathway, functional evidence for their contribution to promoter activity has only been demonstrated for a few of them. Here, in the lignin-specific branch, we studied the functional role of MYB elements as well as other cis-elements identified in the regulatory regions of EgCAD2 and EgCCR promoters, in the transcriptional activity of these gene promoters. By using promoter deletion analysis and in vivo footprinting, we identified an 80 bp regulatory region in the Eucalyptus gunnii EgCAD2 promoter that contains two MYB elements, each arranged in a distinct module with newly identified cis-elements. A directed mutagenesis approach was used to introduce block mutations in all putative cis-elements of the EgCAD2 promoter and in those of the 50 bp regulatory region previously delineated in the EgCCR promoter. We showed that the conserved MYB elements in EgCAD2 and EgCCR promoters are crucial both for the formation of DNA-protein complexes in EMSA experiments and for the transcriptional activation of EgCAD2 and EgCCR promoters in vascular tissues in planta. In addition, a new regulatory cis-element that modulates the balance between two DNA-protein complexes in vitro was found to be important for EgCAD2 expression in the cambial zone. Our assignment of functional roles to the identified cis-elements clearly demonstrates the

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

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Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

2013-09-22

High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

The Crc global regulator inhibits the Pseudomonas putida pWW0 toluene/xylene assimilation pathway by repressing the translation of regulatory and structural genes.

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Moreno, Renata; Fonseca, Pilar; Rojo, Fernando

2010-08-06

In Pseudomonas putida, the expression of the pWW0 plasmid genes for the toluene/xylene assimilation pathway (the TOL pathway) is subject to complex regulation in response to environmental and physiological signals. This includes strong inhibition via catabolite repression, elicited by the carbon sources that the cells prefer to hydrocarbons. The Crc protein, a global regulator that controls carbon flow in pseudomonads, has an important role in this inhibition. Crc is a translational repressor that regulates the TOL genes, but how it does this has remained unknown. This study reports that Crc binds to sites located at the translation initiation regions of the mRNAs coding for XylR and XylS, two specific transcription activators of the TOL genes. Unexpectedly, eight additional Crc binding sites were found overlapping the translation initiation sites of genes coding for several enzymes of the pathway, all encoded within two polycistronic mRNAs. Evidence is provided supporting the idea that these sites are functional. This implies that Crc can differentially modulate the expression of particular genes within polycistronic mRNAs. It is proposed that Crc controls TOL genes in two ways. First, Crc inhibits the translation of the XylR and XylS regulators, thereby reducing the transcription of all TOL pathway genes. Second, Crc inhibits the translation of specific structural genes of the pathway, acting mainly on proteins involved in the first steps of toluene assimilation. This ensures a rapid inhibitory response that reduces the expression of the toluene/xylene degradation proteins when preferred carbon sources become available.

DMPD: TLR pathways and IFN-regulatory factors: to each its own. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available Immunol. 2007 Feb;37(2):306-9. (.png) (.svg) (.html) (.csml) Show TLR pathways and IFN-regulatory factors: ...ng) SVG File (.svg) HTML File (.html) CSML File (.csml) Open .csml file with CIOPlayer Open .csml file with

Recurrent neural network based hybrid model for reconstructing gene regulatory network.

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Raza, Khalid; Alam, Mansaf

2016-10-01

One of the exciting problems in systems biology research is to decipher how genome controls the development of complex biological system. The gene regulatory networks (GRNs) help in the identification of regulatory interactions between genes and offer fruitful information related to functional role of individual gene in a cellular system. Discovering GRNs lead to a wide range of applications, including identification of disease related pathways providing novel tentative drug targets, helps to predict disease response, and also assists in diagnosing various diseases including cancer. Reconstruction of GRNs from available biological data is still an open problem. This paper proposes a recurrent neural network (RNN) based model of GRN, hybridized with generalized extended Kalman filter for weight update in backpropagation through time training algorithm. The RNN is a complex neural network that gives a better settlement between biological closeness and mathematical flexibility to model GRN; and is also able to capture complex, non-linear and dynamic relationships among variables. Gene expression data are inherently noisy and Kalman filter performs well for estimation problem even in noisy data. Hence, we applied non-linear version of Kalman filter, known as generalized extended Kalman filter, for weight update during RNN training. The developed model has been tested on four benchmark networks such as DNA SOS repair network, IRMA network, and two synthetic networks from DREAM Challenge. We performed a comparison of our results with other state-of-the-art techniques which shows superiority of our proposed model. Further, 5% Gaussian noise has been induced in the dataset and result of the proposed model shows negligible effect of noise on results, demonstrating the noise tolerance capability of the model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Semi-supervised prediction of gene regulatory networks using ...

Indian Academy of Sciences (India)

2015-09-28

Sep 28, 2015 ... Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging ... two types of methods differ primarily based on whether ..... negligible, allowing us to draw the qualitative conclusions .... research will be conducted to develop additional biologically.

Conserved Transcriptional Regulatory Programs Underlying Rice and Barley Germination

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Lin, Li; Tian, Shulan; Kaeppler, Shawn; Liu, Zongrang; An, Yong-Qiang (Charles)

2014-01-01

Germination is a biological process important to plant development and agricultural production. Barley and rice diverged 50 million years ago, but share a similar germination process. To gain insight into the conservation of their underlying gene regulatory programs, we compared transcriptomes of barley and rice at start, middle and end points of germination, and revealed that germination regulated barley and rice genes (BRs) diverged significantly in expression patterns and/or protein sequences. However, BRs with higher protein sequence similarity tended to have more conserved expression patterns. We identified and characterized 316 sets of conserved barley and rice genes (cBRs) with high similarity in both protein sequences and expression patterns, and provided a comprehensive depiction of the transcriptional regulatory program conserved in barley and rice germination at gene, pathway and systems levels. The cBRs encoded proteins involved in a variety of biological pathways and had a wide range of expression patterns. The cBRs encoding key regulatory components in signaling pathways often had diverse expression patterns. Early germination up-regulation of cell wall metabolic pathway and peroxidases, and late germination up-regulation of chromatin structure and remodeling pathways were conserved in both barley and rice. Protein sequence and expression pattern of a gene change quickly if it is not subjected to a functional constraint. Preserving germination-regulated expression patterns and protein sequences of those cBRs for 50 million years strongly suggests that the cBRs are functionally significant and equivalent in germination, and contribute to the ancient characteristics of germination preserved in barley and rice. The functional significance and equivalence of the cBR genes predicted here can serve as a foundation to further characterize their biological functions and facilitate bridging rice and barley germination research with greater confidence. PMID

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

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

2014-03-06

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

Identification and Functional Analysis of Gene Regulatory Sequences Interacting with Colorectal Tumor Suppressors

DEFF Research Database (Denmark)

Dahlgaard, Katja; Troelsen, Jesper

2018-01-01

Several tumor suppressors possess gene regulatory activity. Here, we describe how promoter and promoter/enhancer reporter assays can be used to characterize a colorectal tumor suppressor proteins’ gene regulatory activity of possible target genes. In the first part, a bioinformatic approach...... of the quick and efficient In-Fusion cloning method, and how to carry out transient transfections of Caco-2 colon cancer cells with the produced luciferase reporter plasmids using polyethyleneimine (PEI). A plan describing how to set up and carry out the luciferase expression assay is presented. The luciferase...... to identify relevant gene regulatory regions of potential target genes is presented. In the second part, it is demonstrated how to prepare and carry out the functional assay. We explain how to clone the bioinformatically identified gene regulatory regions into luciferase reporter plasmids by the use...

Identifying Tmem59 related gene regulatory network of mouse neural stem cell from a compendium of expression profiles

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Guo Xiuyun

2011-09-01

Full Text Available Abstract Background Neural stem cells offer potential treatment for neurodegenerative disorders, such like Alzheimer's disease (AD. While much progress has been made in understanding neural stem cell function, a precise description of the molecular mechanisms regulating neural stem cells is not yet established. This lack of knowledge is a major barrier holding back the discovery of therapeutic uses of neural stem cells. In this paper, the regulatory mechanism of mouse neural stem cell (NSC differentiation by tmem59 is explored on the genome-level. Results We identified regulators of tmem59 during the differentiation of mouse NSCs from a compendium of expression profiles. Based on the microarray experiment, we developed the parallelized SWNI algorithm to reconstruct gene regulatory networks of mouse neural stem cells. From the inferred tmem59 related gene network including 36 genes, pou6f1 was identified to regulate tmem59 significantly and might play an important role in the differentiation of NSCs in mouse brain. There are four pathways shown in the gene network, indicating that tmem59 locates in the downstream of the signalling pathway. The real-time RT-PCR results shown that the over-expression of pou6f1 could significantly up-regulate tmem59 expression in C17.2 NSC line. 16 out of 36 predicted genes in our constructed network have been reported to be AD-related, including Ace, aqp1, arrdc3, cd14, cd59a, cds1, cldn1, cox8b, defb11, folr1, gdi2, mmp3, mgp, myrip, Ripk4, rnd3, and sncg. The localization of tmem59 related genes and functional-related gene groups based on the Gene Ontology (GO annotation was also identified. Conclusions Our findings suggest that the expression of tmem59 is an important factor contributing to AD. The parallelized SWNI algorithm increased the efficiency of network reconstruction significantly. This study enables us to highlight novel genes that may be involved in NSC differentiation and provides a shortcut to

Pathway-based analysis of genome-wide siRNA screens reveals the regulatory landscape of APP processing.

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Luiz Miguel Camargo

Full Text Available The progressive aggregation of Amyloid-β (Aβ in the brain is a major trait of Alzheimer's Disease (AD. Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP. Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPPα. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A recently implicated with AD through genome wide association studies (GWAS and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the "regulatory landscape" of APP.

Pathways-driven sparse regression identifies pathways and genes associated with high-density lipoprotein cholesterol in two Asian cohorts.

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Matt Silver

2013-11-01

Full Text Available Standard approaches to data analysis in genome-wide association studies (GWAS ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK

Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

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Silver, Matt; Chen, Peng; Li, Ruoying; Cheng, Ching-Yu; Wong, Tien-Yin; Tai, E-Shyong; Teo, Yik-Ying; Montana, Giovanni

2013-01-01

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune

Genome-wide identification of regulatory elements and reconstruction of gene regulatory networks of the green alga Chlamydomonas reinhardtii under carbon deprivation.

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Flavia Vischi Winck

Full Text Available The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO2], a carbon concentrating mechanism (CCM is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1 gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF and transcription regulator (TR genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO 2 response regulator 1 and Lcr2 (Low-CO2 response regulator 2, may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome

A guide to approaching regulatory considerations for lentiviral-mediated gene therapies.

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White, Michael; Whittaker, Roger; Stoll, Elizabeth Ann

2017-06-12

Lentiviral vectors are increasingly the gene transfer tool of choice for gene or cell therapies, with multiple clinical investigations showing promise for this viral vector in terms of both safety and efficacy. The third-generation vector system is well-characterized, effectively delivers genetic material and maintains long-term stable expression in target cells, delivers larger amounts of genetic material than other methods, is non-pathogenic and does not cause an inflammatory response in the recipient. This report aims to help academic scientists and regulatory managers negotiate the governance framework to achieve successful translation of a lentiviral vector-based gene therapy. The focus is on European regulations, and how they are administered in the United Kingdom, although many of the principles will be similar for other regions including the United States. The report justifies the rationale for using third-generation lentiviral vectors to achieve gene delivery for in vivo and ex vivo applications; briefly summarises the extant regulatory guidance for gene therapies, categorised as advanced therapeutic medicinal products (ATMPs); provides guidance on specific regulatory issues regarding gene therapies; presents an overview of the key stakeholders to be approached when pursuing clinical trials authorization for an ATMP; and includes a brief catalogue of the documentation required to submit an application for regulatory approval of a new gene therapy.

Cloning and bioinformatic analysis of lovastatin biosynthesis regulatory gene lovE.

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Huang, Xin; Li, Hao-ming

2009-08-05

Lovastatin is an effective drug for treatment of hyperlipidemia. This study aimed to clone lovastatin biosynthesis regulatory gene lovE and analyze the structure and function of its encoding protein. According to the lovastatin synthase gene sequence from genebank, primers were designed to amplify and clone the lovastatin biosynthesis regulatory gene lovE from Aspergillus terrus genomic DNA. Bioinformatic analysis of lovE and its encoding animo acid sequence was performed through internet resources and software like DNAMAN. Target fragment lovE, almost 1500 bp in length, was amplified from Aspergillus terrus genomic DNA and the secondary and three-dimensional structures of LovE protein were predicted. In the lovastatin biosynthesis process lovE is a regulatory gene and LovE protein is a GAL4-like transcriptional factor.

In silico analysis of cis-acting regulatory elements in 5' regulatory regions of sucrose transporter gene families in rice (Oryza sativa Japonica) and Arabidopsis thaliana.

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Ibraheem, Omodele; Botha, Christiaan E J; Bradley, Graeme

2010-12-01

The regulation of gene expression involves a multifarious regulatory system. Each gene contains a unique combination of cis-acting regulatory sequence elements in the 5' regulatory region that determines its temporal and spatial expression. Cis-acting regulatory elements are essential transcriptional gene regulatory units; they control many biological processes and stress responses. Thus a full understanding of the transcriptional gene regulation system will depend on successful functional analyses of cis-acting elements. Cis-acting regulatory elements present within the 5' regulatory region of the sucrose transporter gene families in rice (Oryza sativa Japonica cultivar-group) and Arabidopsis thaliana, were identified using a bioinformatics approach. The possible cis-acting regulatory elements were predicted by scanning 1.5kbp of 5' regulatory regions of the sucrose transporter genes translational start sites, using Plant CARE, PLACE and Genomatix Matinspector professional databases. Several cis-acting regulatory elements that are associated with plant development, plant hormonal regulation and stress response were identified, and were present in varying frequencies within the 1.5kbp of 5' regulatory region, among which are; A-box, RY, CAT, Pyrimidine-box, Sucrose-box, ABRE, ARF, ERE, GARE, Me-JA, ARE, DRE, GA-motif, GATA, GT-1, MYC, MYB, W-box, and I-box. This result reveals the probable cis-acting regulatory elements that possibly are involved in the expression and regulation of sucrose transporter gene families in rice and Arabidopsis thaliana during cellular development or environmental stress conditions. Copyright © 2010 Elsevier Ltd. All rights reserved.

Shared molecular pathways and gene networks for cardiovascular disease and type 2 diabetes mellitus in women across diverse ethnicities.

Science.gov (United States)

Chan, Kei Hang K; Huang, Yen-Tsung; Meng, Qingying; Wu, Chunyuan; Reiner, Alexander; Sobel, Eric M; Tinker, Lesley; Lusis, Aldons J; Yang, Xia; Liu, Simin

2014-12-01

Although cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) share many common risk factors, potential molecular mechanisms that may also be shared for these 2 disorders remain unknown. Using an integrative pathway and network analysis, we performed genome-wide association studies in 8155 blacks, 3494 Hispanic American, and 3697 Caucasian American women who participated in the national Women's Health Initiative single-nucleotide polymorphism (SNP) Health Association Resource and the Genomics and Randomized Trials Network. Eight top pathways and gene networks related to cardiomyopathy, calcium signaling, axon guidance, cell adhesion, and extracellular matrix seemed to be commonly shared between CVD and T2D across all 3 ethnic groups. We also identified ethnicity-specific pathways, such as cell cycle (specific for Hispanic American and Caucasian American) and tight junction (CVD and combined CVD and T2D in Hispanic American). In network analysis of gene-gene or protein-protein interactions, we identified key drivers that included COL1A1, COL3A1, and ELN in the shared pathways for both CVD and T2D. These key driver genes were cross-validated in multiple mouse models of diabetes mellitus and atherosclerosis. Our integrative analysis of American women of 3 ethnicities identified multiple shared biological pathways and key regulatory genes for the development of CVD and T2D. These prospective findings also support the notion that ethnicity-specific susceptibility genes and process are involved in the pathogenesis of CVD and T2D. © 2014 American Heart Association, Inc.

Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

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Guo Zheng

2006-01-01

Full Text Available Abstract Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network to address the underlying regulations of genes that can span any unit(s of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex

Prioritization of gene regulatory interactions from large-scale modules in yeast

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Bringas Ricardo

2008-01-01

Full Text Available Abstract Background The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological systems. While methods have been developed to derive numerous modules from genome-wide data, individual links between regulatory proteins and target genes still need experimental verification. In this work, we aim to prioritize regulator-target links within transcriptional modules based on three types of large-scale data sources. Results Starting with putative transcriptional modules from ChIP-chip data, we first derive modules in which target genes show both expression and function coherence. The most reliable regulatory links between transcription factors and target genes are established by identifying intersection of target genes in coherent modules for each enriched functional category. Using a combination of genome-wide yeast data in normal growth conditions and two different reference datasets, we show that our method predicts regulatory interactions with significantly higher predictive power than ChIP-chip binding data alone. A comparison with results from other studies highlights that our approach provides a reliable and complementary set of regulatory interactions. Based on our results, we can also identify functionally interacting target genes, for instance, a group of co-regulated proteins related to cell wall synthesis. Furthermore, we report novel conserved binding sites of a glycoprotein-encoding gene, CIS3, regulated by Swi6-Swi4 and Ndd1-Fkh2-Mcm1 complexes. Conclusion We provide a simple method to prioritize individual TF-gene interactions from large-scale transcriptional modules. In comparison with other published works, we predict a complementary set of regulatory interactions which yields a similar or higher prediction accuracy at the expense of sensitivity. Therefore, our method can serve as an alternative approach to prioritization for

The Integration of Epistasis Network and Functional Interactions in a GWAS Implicates RXR Pathway Genes in the Immune Response to Smallpox Vaccine.

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Brett A McKinney

Full Text Available Although many diseases and traits show large heritability, few genetic variants have been found to strongly separate phenotype groups by genotype. Complex regulatory networks of variants and expression of multiple genes lead to small individual-variant effects and difficulty replicating the effect of any single variant in an affected pathway. Interaction network modeling of GWAS identifies effects ignored by univariate models, but population differences may still cause specific genes to not replicate. Integrative network models may help detect indirect effects of variants in the underlying biological pathway. In this study, we used gene-level functional interaction information from the Integrative Multi-species Prediction (IMP tool to reveal important genes associated with a complex phenotype through evidence from epistasis networks and pathway enrichment. We test this method for augmenting variant-based network analyses with functional interactions by applying it to a smallpox vaccine immune response GWAS. The integrative analysis spotlights the role of genes related to retinoid X receptor alpha (RXRA, which has been implicated in a previous epistasis network analysis of smallpox vaccine.

Isolation of the phe-operon from G. stearothermophilus comprising the phenol degradative meta-pathway genes and a novel transcriptional regulator

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Reiss Monika

2008-11-01

Full Text Available Abstract Background Geobacillus stearothermophilus is able to utilize phenol as a sole carbon source. A DNA fragment encoding a phenol hydroxylase catalyzing the first step in the meta-pathway has been isolated previously. Based on these findings a PCR-based DNA walk was performed initially to isolate a catechol 2,3-dioxygenase for biosensoric applications but was continued to elucidate the organisation of the genes encoding the proteins for the metabolization of phenol. Results A 20.2 kb DNA fragment was isolated as a result of the DNA walk. Fifteen open reading frames residing on a low-copy megaplasmid were identified. Eleven genes are co-transcribed in one polycistronic mRNA as shown by reverse transcription-PCR. Ten genes encode proteins, that are directly linked with the meta-cleavage pathway. The deduced amino acid sequences display similarities to a two-component phenol hydroxylase, a catechol 2,3-dioxygenase, a 4-oxalocrotonate tautomerase, a 2-oxopent-4-dienoate hydratase, a 4-oxalocrotonate decarboxylase, a 4-hydroxy-2-oxovalerate aldolase, an acetaldehyde dehydrogenase, a plant-type ferredoxin involved in the reactivation of extradiol dioxygenases and a novel regulatory protein. The only enzymes missing for the complete mineralization of phenol are a 2-hydroxymuconic acid-6-semialdehyde hydrolase and/or 2-hydroxymuconic acid-6-semialdehyde dehydrogenase. Conclusion Research on the bacterial degradation of aromatic compounds on a sub-cellular level has been more intensively studied in gram-negative organisms than in gram-positive bacteria. Especially regulatory mechanisms in gram-positive (thermophilic prokaryotes remain mostly unknown. We isolated the first complete sequence of an operon from a thermophilic bacterium encoding the meta-pathway genes and analyzed the genetic organization. Moreover, the first transcriptional regulator of the phenol metabolism in gram-positive bacteria was identified. This is a first step to elucidate

Global Regulatory Differences for Gene- and Cell-Based Therapies

DEFF Research Database (Denmark)

Coppens, Delphi G M; De Bruin, Marie L; Leufkens, Hubert G M

2017-01-01

Gene- and cell-based therapies (GCTs) offer potential new treatment options for unmet medical needs. However, the use of conventional regulatory requirements for medicinal products to approve GCTs may impede patient access and therapeutic innovation. Furthermore, requirements differ between...... jurisdictions, complicating the global regulatory landscape. We provide a comparative overview of regulatory requirements for GCT approval in five jurisdictions and hypothesize on the consequences of the observed global differences on patient access and therapeutic innovation....

SELANSI: a toolbox for simulation of stochastic gene regulatory networks.

Science.gov (United States)

Pájaro, Manuel; Otero-Muras, Irene; Vázquez, Carlos; Alonso, Antonio A

2018-03-01

Gene regulation is inherently stochastic. In many applications concerning Systems and Synthetic Biology such as the reverse engineering and the de novo design of genetic circuits, stochastic effects (yet potentially crucial) are often neglected due to the high computational cost of stochastic simulations. With advances in these fields there is an increasing need of tools providing accurate approximations of the stochastic dynamics of gene regulatory networks (GRNs) with reduced computational effort. This work presents SELANSI (SEmi-LAgrangian SImulation of GRNs), a software toolbox for the simulation of stochastic multidimensional gene regulatory networks. SELANSI exploits intrinsic structural properties of gene regulatory networks to accurately approximate the corresponding Chemical Master Equation with a partial integral differential equation that is solved by a semi-lagrangian method with high efficiency. Networks under consideration might involve multiple genes with self and cross regulations, in which genes can be regulated by different transcription factors. Moreover, the validity of the method is not restricted to a particular type of kinetics. The tool offers total flexibility regarding network topology, kinetics and parameterization, as well as simulation options. SELANSI runs under the MATLAB environment, and is available under GPLv3 license at https://sites.google.com/view/selansi. antonio@iim.csic.es. © The Author(s) 2017. Published by Oxford University Press.

Placental gene-expression profiles of intrahepatic cholestasis of pregnancy reveal involvement of multiple molecular pathways in blood vessel formation and inflammation.

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Du, QiaoLing; Pan, YouDong; Zhang, YouHua; Zhang, HaiLong; Zheng, YaJuan; Lu, Ling; Wang, JunLei; Duan, Tao; Chen, JianFeng

2014-07-07

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-associated liver disease with potentially deleterious consequences for the fetus, particularly when maternal serum bile-acid concentration >40 μM. However, the etiology and pathogenesis of ICP remain elusive. To reveal the underlying molecular mechanisms for the association of maternal serum bile-acid level and fetal outcome in ICP patients, DNA microarray was applied to characterize the whole-genome expression profiles of placentas from healthy women and women diagnosed with ICP. Thirty pregnant women recruited in this study were categorized evenly into three groups: healthy group; mild ICP, with serum bile-acid concentration ranging from 10-40 μM; and severe ICP, with bile-acid concentration >40 μM. Gene Ontology analysis in combination with construction of gene-interaction and gene co-expression networks were applied to identify the core regulatory genes associated with ICP pathogenesis, which were further validated by quantitative real-time PCR and histological staining. The core regulatory genes were mainly involved in immune response, VEGF signaling pathway and G-protein-coupled receptor signaling, implying essential roles of immune response, vasculogenesis and angiogenesis in ICP pathogenesis. This implication was supported by the observed aggregated immune-cell infiltration and deficient blood vessel formation in ICP placentas. Our study provides a system-level insight into the placental gene-expression profiles of women with mild or severe ICP, and reveals multiple molecular pathways in immune response and blood vessel formation that might contribute to ICP pathogenesis.

Synchronous versus asynchronous modeling of gene regulatory networks.

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Garg, Abhishek; Di Cara, Alessandro; Xenarios, Ioannis; Mendoza, Luis; De Micheli, Giovanni

2008-09-01

In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Identifying noncoding risk variants using disease-relevant gene regulatory networks.

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Gao, Long; Uzun, Yasin; Gao, Peng; He, Bing; Ma, Xiaoke; Wang, Jiahui; Han, Shizhong; Tan, Kai

2018-02-16

Identifying noncoding risk variants remains a challenging task. Because noncoding variants exert their effects in the context of a gene regulatory network (GRN), we hypothesize that explicit use of disease-relevant GRNs can significantly improve the inference accuracy of noncoding risk variants. We describe Annotation of Regulatory Variants using Integrated Networks (ARVIN), a general computational framework for predicting causal noncoding variants. It employs a set of novel regulatory network-based features, combined with sequence-based features to infer noncoding risk variants. Using known causal variants in gene promoters and enhancers in a number of diseases, we show ARVIN outperforms state-of-the-art methods that use sequence-based features alone. Additional experimental validation using reporter assay further demonstrates the accuracy of ARVIN. Application of ARVIN to seven autoimmune diseases provides a holistic view of the gene subnetwork perturbed by the combinatorial action of the entire set of risk noncoding mutations.

Feather development genes and associated regulatory innovation predate the origin of Dinosauria.

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Lowe, Craig B; Clarke, Julia A; Baker, Allan J; Haussler, David; Edwards, Scott V

2015-01-01

The evolution of avian feathers has recently been illuminated by fossils and the identification of genes involved in feather patterning and morphogenesis. However, molecular studies have focused mainly on protein-coding genes. Using comparative genomics and more than 600,000 conserved regulatory elements, we show that patterns of genome evolution in the vicinity of feather genes are consistent with a major role for regulatory innovation in the evolution of feathers. Rates of innovation at feather regulatory elements exhibit an extended period of innovation with peaks in the ancestors of amniotes and archosaurs. We estimate that 86% of such regulatory elements and 100% of the nonkeratin feather gene set were present prior to the origin of Dinosauria. On the branch leading to modern birds, we detect a strong signal of regulatory innovation near insulin-like growth factor binding protein (IGFBP) 2 and IGFBP5, which have roles in body size reduction, and may represent a genomic signature for the miniaturization of dinosaurian body size preceding the origin of flight. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Differential Gene Expression and Aging

Directory of Open Access Journals (Sweden)

Laurent Seroude

2002-01-01

Full Text Available It has been established that an intricate program of gene expression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential gene expression. At least two genetic pathways regulating organism longevity act by modifying gene expression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related gene expression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.

Pleiotropic regulatory genes bldA, adpA and absB are implicated in production of phosphoglycolipid antibiotic moenomycin.

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Makitrynskyy, Roman; Ostash, Bohdan; Tsypik, Olga; Rebets, Yuriy; Doud, Emma; Meredith, Timothy; Luzhetskyy, Andriy; Bechthold, Andreas; Walker, Suzanne; Fedorenko, Victor

2013-10-23

Unlike the majority of actinomycete secondary metabolic pathways, the biosynthesis of peptidoglycan glycosyltransferase inhibitor moenomycin in Streptomyces ghanaensis does not involve any cluster-situated regulators (CSRs). This raises questions about the regulatory signals that initiate and sustain moenomycin production. We now show that three pleiotropic regulatory genes for Streptomyces morphogenesis and antibiotic production-bldA, adpA and absB-exert multi-layered control over moenomycin biosynthesis in native and heterologous producers. The bldA gene for tRNA(Leu)UAA is required for the translation of rare UUA codons within two key moenomycin biosynthetic genes (moe), moeO5 and moeE5. It also indirectly influences moenomycin production by controlling the translation of the UUA-containing adpA and, probably, other as-yet-unknown repressor gene(s). AdpA binds key moe promoters and activates them. Furthermore, AdpA interacts with the bldA promoter, thus impacting translation of bldA-dependent mRNAs-that of adpA and several moe genes. Both adpA expression and moenomycin production are increased in an absB-deficient background, most probably because AbsB normally limits adpA mRNA abundance through ribonucleolytic cleavage. Our work highlights an underappreciated strategy for secondary metabolism regulation, in which the interaction between structural genes and pleiotropic regulators is not mediated by CSRs. This strategy might be relevant for a growing number of CSR-free gene clusters unearthed during actinomycete genome mining.

DMPD: Signalling pathways mediating type I interferon gene expression. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available 17904888 Signalling pathways mediating type I interferon gene expression. Edwards M...hways mediating type I interferon gene expression. PubmedID 17904888 Title Signalling pathways...R, Slater L, Johnston SL. Microbes Infect. 2007 Sep;9(11):1245-51. Epub 2007 Jul 1. (.png) (.svg) (.html) (.csml) Show Signalling pat

Harnessing diversity towards the reconstructing of large scale gene regulatory networks.

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Takeshi Hase

Full Text Available Elucidating gene regulatory network (GRN from large scale experimental data remains a central challenge in systems biology. Recently, numerous techniques, particularly consensus driven approaches combining different algorithms, have become a potentially promising strategy to infer accurate GRNs. Here, we develop a novel consensus inference algorithm, TopkNet that can integrate multiple algorithms to infer GRNs. Comprehensive performance benchmarking on a cloud computing framework demonstrated that (i a simple strategy to combine many algorithms does not always lead to performance improvement compared to the cost of consensus and (ii TopkNet integrating only high-performance algorithms provide significant performance improvement compared to the best individual algorithms and community prediction. These results suggest that a priori determination of high-performance algorithms is a key to reconstruct an unknown regulatory network. Similarity among gene-expression datasets can be useful to determine potential optimal algorithms for reconstruction of unknown regulatory networks, i.e., if expression-data associated with known regulatory network is similar to that with unknown regulatory network, optimal algorithms determined for the known regulatory network can be repurposed to infer the unknown regulatory network. Based on this observation, we developed a quantitative measure of similarity among gene-expression datasets and demonstrated that, if similarity between the two expression datasets is high, TopkNet integrating algorithms that are optimal for known dataset perform well on the unknown dataset. The consensus framework, TopkNet, together with the similarity measure proposed in this study provides a powerful strategy towards harnessing the wisdom of the crowds in reconstruction of unknown regulatory networks.

Transcript Profile of Flowering Regulatory Genes in VcFT-Overexpressing Blueberry Plants.

Science.gov (United States)

Walworth, Aaron E; Chai, Benli; Song, Guo-Qing

2016-01-01

In order to identify genetic components in flowering pathways of highbush blueberry (Vaccinium corymbosum L.), a transcriptome reference composed of 254,396 transcripts and 179,853 gene contigs was developed by assembly of 72.7 million reads using Trinity. Using this transcriptome reference and a query of flowering pathway genes of herbaceous plants, we identified potential flowering pathway genes/transcripts of blueberry. Transcriptome analysis of flowering pathway genes was then conducted on leaf tissue samples of transgenic blueberry cv. Aurora ('VcFT-Aurora'), which overexpresses a blueberry FLOWERING LOCUS T-like gene (VcFT). Sixty-one blueberry transcripts of 40 genes showed high similarities to 33 known flowering-related genes of herbaceous plants, of which 17 down-regulated and 16 up-regulated genes were identified in 'VcFT-Aurora'. All down-regulated genes encoded transcription factors/enzymes upstream in the signaling pathway containing VcFT. A blueberry CONSTANS-LIKE 5-like (VcCOL5) gene was down-regulated and associated with five other differentially expressed (DE) genes in the photoperiod-mediated flowering pathway. Three down-regulated genes, i.e., a MADS-AFFECTING FLOWERING 2-like gene (VcMAF2), a MADS-AFFECTING FLOWERING 5-like gene (VcMAF5), and a VERNALIZATION1-like gene (VcVRN1), may function as integrators in place of FLOWERING LOCUS C (FLC) in the vernalization pathway. Because no CONSTAN1-like or FLOWERING LOCUS C-like genes were found in blueberry, VcCOL5 and VcMAF2/VcMAF5 or VRN1 might be the major integrator(s) in the photoperiod- and vernalization-mediated flowering pathway, respectively. The major down-stream genes of VcFT, i.e., SUPPRESSOR of Overexpression of Constans 1-like (VcSOC1), LEAFY-like (VcLFY), APETALA1-like (VcAP1), CAULIFLOWER 1-like (VcCAL1), and FRUITFULL-like (VcFUL) genes were present and showed high similarity to their orthologues in herbaceous plants. Moreover, overexpression of VcFT promoted expression of all of these

Transcript Profile of Flowering Regulatory Genes in VcFT-Overexpressing Blueberry Plants.

Directory of Open Access Journals (Sweden)

Aaron E Walworth

Full Text Available In order to identify genetic components in flowering pathways of highbush blueberry (Vaccinium corymbosum L., a transcriptome reference composed of 254,396 transcripts and 179,853 gene contigs was developed by assembly of 72.7 million reads using Trinity. Using this transcriptome reference and a query of flowering pathway genes of herbaceous plants, we identified potential flowering pathway genes/transcripts of blueberry. Transcriptome analysis of flowering pathway genes was then conducted on leaf tissue samples of transgenic blueberry cv. Aurora ('VcFT-Aurora', which overexpresses a blueberry FLOWERING LOCUS T-like gene (VcFT. Sixty-one blueberry transcripts of 40 genes showed high similarities to 33 known flowering-related genes of herbaceous plants, of which 17 down-regulated and 16 up-regulated genes were identified in 'VcFT-Aurora'. All down-regulated genes encoded transcription factors/enzymes upstream in the signaling pathway containing VcFT. A blueberry CONSTANS-LIKE 5-like (VcCOL5 gene was down-regulated and associated with five other differentially expressed (DE genes in the photoperiod-mediated flowering pathway. Three down-regulated genes, i.e., a MADS-AFFECTING FLOWERING 2-like gene (VcMAF2, a MADS-AFFECTING FLOWERING 5-like gene (VcMAF5, and a VERNALIZATION1-like gene (VcVRN1, may function as integrators in place of FLOWERING LOCUS C (FLC in the vernalization pathway. Because no CONSTAN1-like or FLOWERING LOCUS C-like genes were found in blueberry, VcCOL5 and VcMAF2/VcMAF5 or VRN1 might be the major integrator(s in the photoperiod- and vernalization-mediated flowering pathway, respectively. The major down-stream genes of VcFT, i.e., SUPPRESSOR of Overexpression of Constans 1-like (VcSOC1, LEAFY-like (VcLFY, APETALA1-like (VcAP1, CAULIFLOWER 1-like (VcCAL1, and FRUITFULL-like (VcFUL genes were present and showed high similarity to their orthologues in herbaceous plants. Moreover, overexpression of VcFT promoted expression of all of

Transcript Profile of Flowering Regulatory Genes in VcFT-Overexpressing Blueberry Plants

Science.gov (United States)

Walworth, Aaron E.; Chai, Benli; Song, Guo-qing

2016-01-01

In order to identify genetic components in flowering pathways of highbush blueberry (Vaccinium corymbosum L.), a transcriptome reference composed of 254,396 transcripts and 179,853 gene contigs was developed by assembly of 72.7 million reads using Trinity. Using this transcriptome reference and a query of flowering pathway genes of herbaceous plants, we identified potential flowering pathway genes/transcripts of blueberry. Transcriptome analysis of flowering pathway genes was then conducted on leaf tissue samples of transgenic blueberry cv. Aurora (‘VcFT-Aurora’), which overexpresses a blueberry FLOWERING LOCUS T-like gene (VcFT). Sixty-one blueberry transcripts of 40 genes showed high similarities to 33 known flowering-related genes of herbaceous plants, of which 17 down-regulated and 16 up-regulated genes were identified in ‘VcFT-Aurora’. All down-regulated genes encoded transcription factors/enzymes upstream in the signaling pathway containing VcFT. A blueberry CONSTANS-LIKE 5-like (VcCOL5) gene was down-regulated and associated with five other differentially expressed (DE) genes in the photoperiod-mediated flowering pathway. Three down-regulated genes, i.e., a MADS-AFFECTING FLOWERING 2-like gene (VcMAF2), a MADS-AFFECTING FLOWERING 5-like gene (VcMAF5), and a VERNALIZATION1-like gene (VcVRN1), may function as integrators in place of FLOWERING LOCUS C (FLC) in the vernalization pathway. Because no CONSTAN1-like or FLOWERING LOCUS C-like genes were found in blueberry, VcCOL5 and VcMAF2/VcMAF5 or VRN1 might be the major integrator(s) in the photoperiod- and vernalization-mediated flowering pathway, respectively. The major down-stream genes of VcFT, i.e., SUPPRESSOR of Overexpression of Constans 1-like (VcSOC1), LEAFY-like (VcLFY), APETALA1-like (VcAP1), CAULIFLOWER 1-like (VcCAL1), and FRUITFULL-like (VcFUL) genes were present and showed high similarity to their orthologues in herbaceous plants. Moreover, overexpression of VcFT promoted expression of all

Association genetics and transcriptome analysis reveal a gibberellin-responsive pathway involved in regulating photosynthesis.

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Xie, Jianbo; Tian, Jiaxing; Du, Qingzhang; Chen, Jinhui; Li, Ying; Yang, Xiaohui; Li, Bailian; Zhang, Deqiang

2016-05-01

Gibberellins (GAs) regulate a wide range of important processes in plant growth and development, including photosynthesis. However, the mechanism by which GAs regulate photosynthesis remains to be understood. Here, we used multi-gene association to investigate the effect of genes in the GA-responsive pathway, as constructed by RNA sequencing, on photosynthesis, growth, and wood property traits, in a population of 435 Populus tomentosa By analyzing changes in the transcriptome following GA treatment, we identified many key photosynthetic genes, in agreement with the observed increase in measurements of photosynthesis. Regulatory motif enrichment analysis revealed that 37 differentially expressed genes related to photosynthesis shared two essential GA-related cis-regulatory elements, the GA response element and the pyrimidine box. Thus, we constructed a GA-responsive pathway consisting of 47 genes involved in regulating photosynthesis, including GID1, RGA, GID2, MYBGa, and 37 photosynthetic differentially expressed genes. Single nucleotide polymorphism (SNP)-based association analysis showed that 142 SNPs, representing 40 candidate genes in this pathway, were significantly associated with photosynthesis, growth, and wood property traits. Epistasis analysis uncovered interactions between 310 SNP-SNP pairs from 37 genes in this pathway, revealing possible genetic interactions. Moreover, a structural gene-gene matrix based on a time-course of transcript abundances provided a better understanding of the multi-gene pathway affecting photosynthesis. The results imply a functional role for these genes in mediating photosynthesis, growth, and wood properties, demonstrating the potential of combining transcriptome-based regulatory pathway construction and genetic association approaches to detect the complex genetic networks underlying quantitative traits. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights

Establishing neural crest identity: a gene regulatory recipe

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Simões-Costa, Marcos; Bronner, Marianne E.

2015-01-01

The neural crest is a stem/progenitor cell population that contributes to a wide variety of derivatives, including sensory and autonomic ganglia, cartilage and bone of the face and pigment cells of the skin. Unique to vertebrate embryos, it has served as an excellent model system for the study of cell behavior and identity owing to its multipotency, motility and ability to form a broad array of cell types. Neural crest development is thought to be controlled by a suite of transcriptional and epigenetic inputs arranged hierarchically in a gene regulatory network. Here, we examine neural crest development from a gene regulatory perspective and discuss how the underlying genetic circuitry results in the features that define this unique cell population. PMID:25564621

Exploring Regulatory Mechanisms of Atrial Myocyte Hypertrophy of Mitral Regurgitation through Gene Expression Profiling Analysis: Role of NFAT in Cardiac Hypertrophy.

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Tzu-Hao Chang

Full Text Available Left atrial enlargement in mitral regurgitation (MR predicts a poor prognosis. The regulatory mechanisms of atrial myocyte hypertrophy of MR patients remain unknown.This study comprised 14 patients with MR, 7 patients with aortic valve disease (AVD, and 6 purchased samples from normal subjects (NC. We used microarrays, enrichment analysis and quantitative RT-PCR to study the gene expression profiles in the left atria. Microarray results showed that 112 genes were differentially up-regulated and 132 genes were differentially down-regulated in the left atria between MR patients and NC. Enrichment analysis of differentially expressed genes demonstrated that "NFAT in cardiac hypertrophy" pathway was not only one of the significant associated canonical pathways, but also the only one predicted with a non-zero score of 1.34 (i.e. activated through Ingenuity Pathway Analysis molecule activity predictor. Ingenuity Pathway Analysis Global Molecular Network analysis exhibited that the highest score network also showed high association with cardiac related pathways and functions. Therefore, 5 NFAT associated genes (PPP3R1, PPP3CB, CAMK1, MEF2C, PLCE1 were studies for validation. The mRNA expressions of PPP3CB and MEF2C were significantly up-regulated, and CAMK1 and PPP3R1 were significantly down-regulated in MR patients compared to NC. Moreover, MR patients had significantly increased mRNA levels of PPP3CB, MEF2C and PLCE1 compared to AVD patients. The atrial myocyte size of MR patients significantly exceeded that of the AVD patients and NC.Differentially expressed genes in the "NFAT in cardiac hypertrophy" pathway may play a critical role in the atrial myocyte hypertrophy of MR patients.

Digest: Ant workers might use ancient regulatory pathways to divide labor

Czech Academy of Sciences Publication Activity Database

Ernst, Ulrich R.

2017-01-01

Roč. 71, č. 1 (2017), s. 193-194 ISSN 0014-3820 Institutional support: RVO:61388963 Keywords : regulatory pathways * social insect * ants Subject RIV: EH - Ecology, Behaviour OBOR OECD: Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology Impact factor: 4.201, year: 2016

Text mining in cancer gene and pathway prioritization.

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Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

2014-01-01

Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes.

Exploring the key genes and pathways in enchondromas using a gene expression microarray.

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Shi, Zhongju; Zhou, Hengxing; Pan, Bin; Lu, Lu; Kang, Yi; Liu, Lu; Wei, Zhijian; Feng, Shiqing

2017-07-04

Enchondromas are the most common primary benign osseous neoplasms that occur in the medullary bone; they can undergo malignant transformation into chondrosarcoma. However, enchondromas are always undetected in patients, and the molecular mechanism is unclear. To identify key genes and pathways associated with the occurrence and development of enchondromas, we downloaded the gene expression dataset GSE22855 and obtained the differentially expressed genes (DEGs) by analyzing high-throughput gene expression in enchondromas. In total, 635 genes were identified as DEGs. Of these, 225 genes (35.43%) were up-regulated, and the remaining 410 genes (64.57%) were down-regulated. We identified the predominant gene ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were significantly over-represented in the enchondromas samples compared with the control samples. Subsequently the top 10 core genes were identified from the protein-protein interaction (PPI) network. The enrichment analyses of the genes mainly involved in two significant modules showed that the DEGs were principally related to ribosomes, protein digestion and absorption, ECM-receptor interaction, focal adhesion, amoebiasis and the PI3K-Akt signaling pathway.Together, these data elucidate the molecular mechanisms underlying the occurrence and development of enchondromas and provide promising candidates for therapeutic intervention and prognostic evaluation. However, further experimental studies are needed to confirm these results.

Challenges for modeling global gene regulatory networks during development: insights from Drosophila.

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Wilczynski, Bartek; Furlong, Eileen E M

2010-04-15

Development is regulated by dynamic patterns of gene expression, which are orchestrated through the action of complex gene regulatory networks (GRNs). Substantial progress has been made in modeling transcriptional regulation in recent years, including qualitative "coarse-grain" models operating at the gene level to very "fine-grain" quantitative models operating at the biophysical "transcription factor-DNA level". Recent advances in genome-wide studies have revealed an enormous increase in the size and complexity or GRNs. Even relatively simple developmental processes can involve hundreds of regulatory molecules, with extensive interconnectivity and cooperative regulation. This leads to an explosion in the number of regulatory functions, effectively impeding Boolean-based qualitative modeling approaches. At the same time, the lack of information on the biophysical properties for the majority of transcription factors within a global network restricts quantitative approaches. In this review, we explore the current challenges in moving from modeling medium scale well-characterized networks to more poorly characterized global networks. We suggest to integrate coarse- and find-grain approaches to model gene regulatory networks in cis. We focus on two very well-studied examples from Drosophila, which likely represent typical developmental regulatory modules across metazoans. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Large-scale modeling of condition-specific gene regulatory networks by information integration and inference.

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Ellwanger, Daniel Christian; Leonhardt, Jörn Florian; Mewes, Hans-Werner

2014-12-01

Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

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Baumbach Jan

2007-11-01

Full Text Available Abstract 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

Safety assessment considerations for food and feed derived from plants with genetic modifications that modulate endogenous gene expression and pathways.

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Kier, Larry D; Petrick, Jay S

2008-08-01

The current globally recognized comparative food and feed safety assessment paradigm for biotechnology-derived crops is a robust and comprehensive approach for evaluating the safety of both the inserted gene product and the resulting crop. Incorporating many basic concepts from food safety, toxicology, nutrition, molecular biology, and plant breeding, this approach has been used effectively by scientists and regulatory agencies for 10-15 years. Current and future challenges in agriculture include the need for improved yields, tolerance to biotic and abiotic stresses, and improved nutrition. The next generation of biotechnology-derived crops may utilize regulatory proteins, such as transcription factors that modulate gene expression and/or endogenous plant pathways. In this review, we discuss the applicability of the current safety assessment paradigm to biotechnology-derived crops developed using modifications involving regulatory proteins. The growing literature describing the molecular biology underlying plant domestication and conventional breeding demonstrates the naturally occurring genetic variation found in plants, including significant variation in the classes, expression, and activity of regulatory proteins. Specific examples of plant modifications involving insertion or altered expression of regulatory proteins are discussed as illustrative case studies supporting the conclusion that the current comparative safety assessment process is appropriate for these types of biotechnology-developed crops.

Developmental gene regulatory networks in sea urchins and what we can learn from them [version 1; referees: 3 approved

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Megan L. Martik

2016-02-01

Full Text Available Sea urchin embryos begin zygotic transcription shortly after the egg is fertilized.  Throughout the cleavage stages a series of transcription factors are activated and, along with signaling through a number of pathways, at least 15 different cell types are specified by the beginning of gastrulation.  Experimentally, perturbation of contributing transcription factors, signals and receptors and their molecular consequences enabled the assembly of an extensive gene regulatory network model.  That effort, pioneered and led by Eric Davidson and his laboratory, with many additional insights provided by other laboratories, provided the sea urchin community with a valuable resource.  Here we describe the approaches used to enable the assembly of an advanced gene regulatory network model describing molecular diversification during early development.  We then provide examples to show how a relatively advanced authenticated network can be used as a tool for discovery of how diverse developmental mechanisms are controlled and work.

On the Interplay between Entropy and Robustness of Gene Regulatory Networks

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Bor-Sen Chen

2010-05-01

Full Text Available The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.

Signal Transduction Pathways that Regulate CAB Gene Expression

Energy Technology Data Exchange (ETDEWEB)

Chory, Joanne

2004-12-31

The process of chloroplast differentiation, involves the coordinate regulation of many nuclear and chloroplast genes. The cues for the initiation of this developmental program are both extrinsic (e.g., light) and intrinsic (cell-type and plastid signals). During this project period, we utilized a molecular genetic approach to select for Arabidopsis mutants that did not respond properly to environmental light conditions, as well as mutants that were unable to perceive plastid damage. These latter mutants, called gun mutants, define two retrograde signaling pathways that regulate nuclear gene expression in response to chloroplasts. A major finding was to identify a signal from chloroplasts that regulates nuclear gene transcription. This signal is the build-up of Mg-Protoporphyrin IX, a key intermediate of the chlorophyll biosynthetic pathway. The signaling pathways downstream of this signal are currently being studied. Completion of this project has provided an increased understanding of the input signals and retrograde signaling pathways that control nuclear gene expression in response to the functional state of chloroplasts. These studies should ultimately influence our abilities to manipulate plant growth and development, and will aid in the understanding of the developmental control of photosynthesis.

Signal Transduction Pathways that Regulate CAB Gene Expression

Energy Technology Data Exchange (ETDEWEB)

Chory, Joanne

2006-01-16

The process of chloroplast differentiation, involves the coordinate regulation of many nuclear and chloroplast genes. The cues for the initiation of this developmental program are both extrinsic (e.g., light) and intrinsic (cell-type and plastid signals). During this project period, we utilized a molecular genetic approach to select for Arabidopsis mutants that did not respond properly to environmental light conditions, as well as mutants that were unable to perceive plastid damage. These latter mutants, called gun mutants, define two retrograde signaling pathways that regulate nuclear gene expression in response to chloroplasts. A major finding was to identify a signal from chloroplasts that regulates nuclear gene transcription. This signal is the build-up of Mg-Protoporphyrin IX, a key intermediate of the chlorophyll biosynthetic pathway. The signaling pathways downstream of this signal are currently being studied. Completion of this project has provided an increased understanding of the input signals and retrograde signaling pathways that control nuclear gene expression in response to the functional state of chloroplasts. These studies should ultimately influence our abilities to manipulate plant growth and development, and will aid in the understanding of the developmental control of photosynthesis.

New regulatory pathways and incentives for sustainable antibiotics: Recent European & US Initiatives

DEFF Research Database (Denmark)

Minssen, Timo

2014-01-01

) and the COMBACTE and TRANSLOCATION projects under NewDrugs4BadBugs program, involving the EU Commission and the pharma industry. But also national initiatives, such as the successful Danish ban and regulations on antibiotic use in animal production, as well as educational efforts (the European Antibiotic Awareness......New regulatory pathways and incentives for sustainable antibiotics: Recent European & US Initiatives Posted on March 19, 2014 by Timo Minssen Please find attached a ppt presentation on “New regulatory pathways and incentives for sustainable antibiotics: Recent European & US Initiatives” given...... on March 7, 2014 at the Broad Institute of MIT and Harvard. The presentation was followed by a discussion moderated by US patent attorney Melissa Hunter-Ensor, Partner at Saul Ewing, Boston I started out by emphasizing increasing problems of antimicrobial resistance (AMR) on a global level, providing new...

Interrogating the topological robustness of gene regulatory circuits by randomization.

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Bin Huang

2017-03-01

Full Text Available One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE, for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT, from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression.

The rose (Rosa hybrida) NAC transcription factor 3 gene, RhNAC3, involved in ABA signaling pathway both in rose and Arabidopsis.

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Jiang, Guimei; Jiang, Xinqiang; Lü, Peitao; Liu, Jitao; Gao, Junping; Zhang, Changqing

2014-01-01

Plant transcription factors involved in stress responses are generally classified by their involvement in either the abscisic acid (ABA)-dependent or the ABA-independent regulatory pathways. A stress-associated NAC gene from rose (Rosa hybrida), RhNAC3, was previously found to increase dehydration tolerance in both rose and Arabidopsis. However, the regulatory mechanism involved in RhNAC3 action is still not fully understood. In this study, we isolated and analyzed the upstream regulatory sequence of RhNAC3 and found many stress-related cis-elements to be present in the promoter, with five ABA-responsive element (ABRE) motifs being of particular interest. Characterization of Arabidopsis thaliana plants transformed with the putative RhNAC3 promoter sequence fused to the β-glucuronidase (GUS) reporter gene revealed that RhNAC3 is expressed at high basal levels in leaf guard cells and in vascular tissues. Moreover, the ABRE motifs in the RhNAC3 promoter were observed to have a cumulative effect on the transcriptional activity of this gene both in the presence and absence of exogenous ABA. Overexpression of RhNAC3 in A. thaliana resulted in ABA hypersensitivity during seed germination and promoted leaf closure after ABA or drought treatments. Additionally, the expression of 11 ABA-responsive genes was induced to a greater degree by dehydration in the transgenic plants overexpressing RhNAC3 than control lines transformed with the vector alone. Further analysis revealed that all these genes contain NAC binding cis-elements in their promoter regions, and RhNAC3 was found to partially bind to these putative NAC recognition sites. We further found that of 219 A. thaliana genes previously shown by microarray analysis to be regulated by heterologous overexpression RhNAC3, 85 are responsive to ABA. In rose, the expression of genes downstream of the ABA-signaling pathways was also repressed in RhNAC3-silenced petals. Taken together, we propose that the rose RhNAC3 protein

The rose (Rosa hybrida NAC transcription factor 3 gene, RhNAC3, involved in ABA signaling pathway both in rose and Arabidopsis.

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Guimei Jiang

Full Text Available Plant transcription factors involved in stress responses are generally classified by their involvement in either the abscisic acid (ABA-dependent or the ABA-independent regulatory pathways. A stress-associated NAC gene from rose (Rosa hybrida, RhNAC3, was previously found to increase dehydration tolerance in both rose and Arabidopsis. However, the regulatory mechanism involved in RhNAC3 action is still not fully understood. In this study, we isolated and analyzed the upstream regulatory sequence of RhNAC3 and found many stress-related cis-elements to be present in the promoter, with five ABA-responsive element (ABRE motifs being of particular interest. Characterization of Arabidopsis thaliana plants transformed with the putative RhNAC3 promoter sequence fused to the β-glucuronidase (GUS reporter gene revealed that RhNAC3 is expressed at high basal levels in leaf guard cells and in vascular tissues. Moreover, the ABRE motifs in the RhNAC3 promoter were observed to have a cumulative effect on the transcriptional activity of this gene both in the presence and absence of exogenous ABA. Overexpression of RhNAC3 in A. thaliana resulted in ABA hypersensitivity during seed germination and promoted leaf closure after ABA or drought treatments. Additionally, the expression of 11 ABA-responsive genes was induced to a greater degree by dehydration in the transgenic plants overexpressing RhNAC3 than control lines transformed with the vector alone. Further analysis revealed that all these genes contain NAC binding cis-elements in their promoter regions, and RhNAC3 was found to partially bind to these putative NAC recognition sites. We further found that of 219 A. thaliana genes previously shown by microarray analysis to be regulated by heterologous overexpression RhNAC3, 85 are responsive to ABA. In rose, the expression of genes downstream of the ABA-signaling pathways was also repressed in RhNAC3-silenced petals. Taken together, we propose that the rose Rh

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

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Pollard Katherine S

2007-11-01

Full Text Available Abstract Background The molecular events underlying mammary development during pregnancy, lactation, and involution are incompletely understood. Results 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. Conclusion 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.

An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series.

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Wang, Zidong; Liu, Xiaohui; Liu, Yurong; Liang, Jinling; Vinciotti, Veronica

2009-01-01

In this paper, the extended Kalman filter (EKF) algorithm is applied to model the gene regulatory network from gene time series data. The gene regulatory network is considered as a nonlinear dynamic stochastic model that consists of the gene measurement equation and the gene regulation equation. After specifying the model structure, we apply the EKF algorithm for identifying both the model parameters and the actual value of gene expression levels. It is shown that the EKF algorithm is an online estimation algorithm that can identify a large number of parameters (including parameters of nonlinear functions) through iterative procedure by using a small number of observations. Four real-world gene expression data sets are employed to demonstrate the effectiveness of the EKF algorithm, and the obtained models are evaluated from the viewpoint of bioinformatics.

Fused Regression for Multi-source Gene Regulatory Network Inference.

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Kari Y Lam

2016-12-01

Full Text Available Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. This approach improves network inference performance even when orthology mapping and conservation are incomplete. We refine this method by presenting an algorithm that extracts the true conserved subnetwork from a larger set of potentially conserved interactions and demonstrate the utility of our method in cross species network inference. Last, we demonstrate our method's utility in learning from data collected on different experimental platforms.

Predictive minimum description length principle approach to inferring gene regulatory networks.

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Chaitankar, Vijender; Zhang, Chaoyang; Ghosh, Preetam; Gong, Ping; Perkins, Edward J; Deng, Youping

2011-01-01

Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold that defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we propose a new inference algorithm that incorporates mutual information (MI), conditional mutual information (CMI), and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm is evaluated using both synthetic time series data sets and a biological time series data set (Saccharomyces cerevisiae). The results show that the proposed algorithm produced fewer false edges and significantly improved the precision when compared to existing MDL algorithm.

LmSmdB: an integrated database for metabolic and gene regulatory network in Leishmania major and Schistosoma mansoni

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Priyanka Patel

2016-03-01

Full Text Available A database that integrates all the information required for biological processing is essential to be stored in one platform. We have attempted to create one such integrated database that can be a one stop shop for the essential features required to fetch valuable result. LmSmdB (L. major and S. mansoni database is an integrated database that accounts for the biological networks and regulatory pathways computationally determined by integrating the knowledge of the genome sequences of the mentioned organisms. It is the first database of its kind that has together with the network designing showed the simulation pattern of the product. This database intends to create a comprehensive canopy for the regulation of lipid metabolism reaction in the parasite by integrating the transcription factors, regulatory genes and the protein products controlled by the transcription factors and hence operating the metabolism at genetic level. Keywords: L.major, S.mansoni, Regulatory networks, Transcription factors, Database

Phylogenetic origin and diversification of RNAi pathway genes in insects

DEFF Research Database (Denmark)

Dowling, Daniel; Pauli, Thomas; Donath, Alexander

2016-01-01

RNAinterference (RNAi) refers tothe set ofmolecular processes foundin eukaryotic organisms in which smallRNAmolecules mediate the silencing or down-regulation of target genes. In insects, RNAi serves a number of functions, including regulation of endogenous genes, anti-viral defense, and defense...... against transposable elements. Despite being well studied in model organisms, such as Drosophila, the distribution of core RNAi pathway genes and their evolution in insects is not well understood. Here we present the most comprehensive overview of the distribution and diversity of core RNAi pathway genes...... across 100 insect species, encompassing all currently recognized insect orders. We inferred the phylogenetic origin of insect-specific RNAi pathway genes and also identified several hitherto unrecorded gene expansions using whole-body transcriptome data from the international 1KITE (1000 Insect...

Mutual information and the fidelity of response of gene regulatory models

International Nuclear Information System (INIS)

Tabbaa, Omar P; Jayaprakash, C

2014-01-01

We investigate cellular response to extracellular signals by using information theory techniques motivated by recent experiments. We present results for the steady state of the following gene regulatory models found in both prokaryotic and eukaryotic cells: a linear transcription-translation model and a positive or negative auto-regulatory model. We calculate both the information capacity and the mutual information exactly for simple models and approximately for the full model. We find that (1) small changes in mutual information can lead to potentially important changes in cellular response and (2) there are diminishing returns in the fidelity of response as the mutual information increases. We calculate the information capacity using Gillespie simulations of a model for the TNF-α-NF-κ B network and find good agreement with the measured value for an experimental realization of this network. Our results provide a quantitative understanding of the differences in cellular response when comparing experimentally measured mutual information values of different gene regulatory models. Our calculations demonstrate that Gillespie simulations can be used to compute the mutual information of more complex gene regulatory models, providing a potentially useful tool in synthetic biology. (paper)

Computational challenges in modeling gene regulatory events.

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Pataskar, Abhijeet; Tiwari, Vijay K

2016-10-19

Cellular transcriptional programs driven by genetic and epigenetic mechanisms could be better understood by integrating "omics" data and subsequently modeling the gene-regulatory events. Toward this end, computational biology should keep pace with evolving experimental procedures and data availability. This article gives an exemplified account of the current computational challenges in molecular biology.

A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer

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Mary Qu Yang

Full Text Available Clear cell renal cell carcinoma (ccRCC is the most common and most aggressive form of renal cell cancer (RCC. The incidence of RCC has increased steadily in recent years. The pathogenesis of renal cell cancer remains poorly understood. Many of the tumor suppressor genes, oncogenes, and dysregulated pathways in ccRCC need to be revealed for improvement of the overall clinical outlook of the disease. Here, we developed a systems biology approach to prioritize the somatic mutated genes that lead to dysregulation of pathways in ccRCC. The method integrated multi-layer information to infer causative mutations and disease genes. First, we identified differential gene modules in ccRCC by coupling transcriptome and protein-protein interactions. Each of these modules consisted of interacting genes that were involved in similar biological processes and their combined expression alterations were significantly associated with disease type. Then, subsequent gene module-based eQTL analysis revealed somatic mutated genes that had driven the expression alterations of differential gene modules. Our study yielded a list of candidate disease genes, including several known ccRCC causative genes such as BAP1 and PBRM1, as well as novel genes such as NOD2, RRM1, CSRNP1, SLC4A2, TTLL1 and CNTN1. The differential gene modules and their driver genes revealed by our study provided a new perspective for understanding the molecular mechanisms underlying the disease. Moreover, we validated the results in independent ccRCC patient datasets. Our study provided a new method for prioritizing disease genes and pathways. Keywords: ccRCC, Causative mutation, Pathways, Protein-protein interaction, Gene module, eQTL

RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle

DEFF Research Database (Denmark)

Salleh, M. S.; Mazzoni, G.; Höglund, J. K.

2017-01-01

-throughput RNA sequencing data of liver biopsies from 19 dairy cows were used to identify differentially expressed genes (DEGs) between high- and low-FE groups of cows (based on Residual Feed Intake or RFI). Subsequently, a profile of the pathways connecting the DEGs to FE was generated, and a list of candidate...... genes and biomarkers was derived for their potential inclusion in breeding programmes to improve FE. The bovine RNA-Seq gene expression data from the liver was analysed to identify DEGs and, subsequently, identify the molecular mechanisms, pathways and possible candidate biomarkers of feed efficiency....... On average, 57 million reads (short reads or short mRNA sequences ...

Altered Levels of Aroma and Volatiles by Metabolic Engineering of Shikimate Pathway Genes in Tomato Fruits

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Vered Tzin

2015-06-01

Full Text Available The tomato (Solanum lycopersicum fruit is an excellent source of antioxidants, dietary fibers, minerals and vitamins and therefore has been referred to as a “functional food”. Ripe tomato fruits produce a large number of specialized metabolites including volatile organic compounds. These volatiles serve as key components of the tomato fruit flavor, participate in plant pathogen and herbivore defense, and are used to attract seed dispersers. A major class of specialized metabolites is derived from the shikimate pathway followed by aromatic amino acid biosynthesis of phenylalanine, tyrosine and tryptophan. We attempted to modify tomato fruit flavor by overexpressing key regulatory genes in the shikimate pathway. Bacterial genes encoding feedback-insensitive variants of 3-Deoxy-D-Arabino-Heptulosonate 7-Phosphate Synthase (DAHPS; AroG209-9 and bi-functional Chorismate Mutase/Prephenate Dehydratase (CM/PDT; PheA12 were expressed under the control of a fruit-specific promoter. We crossed these transgenes to generate tomato plants expressing both the AroG209 and PheA12 genes. Overexpression of the AroG209-9 gene had a dramatic effect on the overall metabolic profile of the fruit, including enhanced levels of multiple volatile and non-volatile metabolites. In contrast, the PheA12 overexpression line exhibited minor metabolic effects compared to the wild type fruit. Co-expression of both the AroG209-9 and PheA12 genes in tomato resulted overall in a similar metabolic effect to that of expressing only the AroG209-9 gene. However, the aroma ranking attributes of the tomato fruits from PheA12//AroG209-9 were unique and different from those of the lines expressing a single gene, suggesting a contribution of the PheA12 gene to the overall metabolic profile. We suggest that expression of bacterial genes encoding feedback-insensitive enzymes of the shikimate pathway in tomato fruits provides a useful metabolic engineering tool for the modification of

Genes encoding enzymes of the lignin biosynthesis pathway in Eucalyptus

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Ricardo Harakava

2005-01-01

Full Text Available Eucalyptus ESTs libraries were screened for genes involved in lignin biosynthesis. This search was performed under the perspective of recent revisions on the monolignols biosynthetic pathway. Eucalyptus orthologues of all genes of the phenylpropanoid pathway leading to lignin biosynthesis reported in other plant species were identified. A library made with mRNAs extracted from wood was enriched for genes involved in lignin biosynthesis and allowed to infer the isoforms of each gene family that play a major role in wood lignin formation. Analysis of the wood library suggests that, besides the enzymes of the phenylpropanoids pathway, chitinases, laccases, and dirigent proteins are also important for lignification. Colocalization of several enzymes on the endoplasmic reticulum membrane, as predicted by amino acid sequence analysis, supports the existence of metabolic channeling in the phenylpropanoid pathway. This study establishes a framework for future investigations on gene expression level, protein expression and enzymatic assays, sequence polymorphisms, and genetic engineering.

Gene networks and toxicity pathways induced by acute cadmium exposure in adult largemouth bass (Micropterus salmoides).

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Mehinto, Alvine C; Prucha, Melinda S; Colli-Dula, Reyna C; Kroll, Kevin J; Lavelle, Candice M; Barber, David S; Vulpe, Christopher D; Denslow, Nancy D

2014-07-01

Cadmium is a heavy metal that can accumulate to toxic levels in the environment leading to detrimental effects in animals and humans including kidney, liver and lung injuries. Using a transcriptomics approach, genes and cellular pathways affected by a low dose of cadmium were investigated. Adult largemouth bass were intraperitoneally injected with 20μg/kg of cadmium chloride (mean exposure level - 2.6μg of cadmium per fish) and microarray analyses were conducted in the liver and testis 48h after injection. Transcriptomic profiles identified in response to cadmium exposure were tissue-specific with the most differential expression changes found in the liver tissues, which also contained much higher levels of cadmium than the testis. Acute exposure to a low dose of cadmium induced oxidative stress response and oxidative damage pathways in the liver. The mRNA levels of antioxidants such as catalase increased and numerous transcripts related to DNA damage and DNA repair were significantly altered. Hepatic mRNA levels of metallothionein, a molecular marker of metal exposure, did not increase significantly after 48h exposure. Carbohydrate metabolic pathways were also disrupted with hepatic transcripts such as UDP-glucose, pyrophosphorylase 2, and sorbitol dehydrogenase highly induced. Both tissues exhibited a disruption of steroid signaling pathways. In the testis, estrogen receptor beta and transcripts linked to cholesterol metabolism were suppressed. On the contrary, genes involved in cholesterol metabolism were highly increased in the liver including genes encoding for the rate limiting steroidogenic acute regulatory protein and the catalytic enzyme 7-dehydrocholesterol reductase. Integration of the transcriptomic data using functional enrichment analyses revealed a number of enriched gene networks associated with previously reported adverse outcomes of cadmium exposure such as liver toxicity and impaired reproduction. Copyright © 2014 Elsevier B.V. All rights

Assembly of inflammation-related genes for pathway-focused genetic analysis.

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Matthew J Loza

2007-10-01

Full Text Available Recent identifications of associations between novel variants in inflammation-related genes and several common diseases emphasize the need for systematic evaluations of these genes in disease susceptibility. Considering that many genes are involved in the complex inflammation responses and many genetic variants in these genes have the potential to alter the functions and expression of these genes, we assembled a list of key inflammation-related genes to facilitate the identification of genetic associations of diseases with an inflammation-related etiology. We first reviewed various phases of inflammation responses, including the development of immune cells, sensing of danger, influx of cells to sites of insult, activation and functional responses of immune and non-immune cells, and resolution of the immune response. Assisted by the Ingenuity Pathway Analysis, we then identified 17 functional sub-pathways that are involved in one or multiple phases. This organization would greatly increase the chance of detecting gene-gene interactions by hierarchical clustering of genes with their functional closeness in a pathway. Finally, as an example application, we have developed tagging single nucleotide polymorphism (tSNP arrays for populations of European and African descent to capture all the common variants of these key inflammation-related genes. Assays of these tSNPs have been designed and assembled into two Affymetrix ParAllele customized chips, one each for European (12,011 SNPs and African (21,542 SNPs populations. These tSNPs have greater coverage for these inflammation-related genes compared to the existing genome-wide arrays, particularly in the African population. These tSNP arrays can facilitate systematic evaluation of inflammation pathways in disease susceptibility. For additional applications, other genotyping platforms could also be employed. For existing genome-wide association data, this list of key inflammation-related genes and

Regulatory elements of the floral homeotic gene AGAMOUS identified by phylogenetic footprinting and shadowing.

Energy Technology Data Exchange (ETDEWEB)

Hong, R. L., Hamaguchi, L., Busch, M. A., and Weigel, D.

2003-06-01

OAK-B135 In Arabidopsis thaliana, cis-regulatory sequences of the floral homeotic gene AGAMOUS (AG) are located in the second intron. This 3 kb intron contains binding sites for two direct activators of AG, LEAFY (LFY) and WUSCHEL (WUS), along with other putative regulatory elements. We have used phylogenetic footprinting and the related technique of phylogenetic shadowing to identify putative cis-regulatory elements in this intron. Among 29 Brassicaceae, several other motifs, but not the LFY and WUS binding sites previously identified, are largely invariant. Using reporter gene analyses, we tested six of these motifs and found that they are all functionally important for activity of AG regulatory sequences in A. thaliana. Although there is little obvious sequence similarity outside the Brassicaceae, the intron from cucumber AG has at least partial activity in A. thaliana. Our studies underscore the value of the comparative approach as a tool that complements gene-by-gene promoter dissection, but also highlight that sequence-based studies alone are insufficient for a complete identification of cis-regulatory sites.

Comparative analysis of chromatin landscape in regulatory regions of human housekeeping and tissue specific genes

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Dasgupta Dipayan

2005-05-01

Full Text Available Abstract Background Global regulatory mechanisms involving chromatin assembly and remodelling in the promoter regions of genes is implicated in eukaryotic transcription control especially for genes subjected to spatial and temporal regulation. The potential to utilise global regulatory mechanisms for controlling gene expression might depend upon the architecture of the chromatin in and around the gene. In-silico analysis can yield important insights into this aspect, facilitating comparison of two or more classes of genes comprising of a large number of genes within each group. Results In the present study, we carried out a comparative analysis of chromatin characteristics in terms of the scaffold/matrix attachment regions, nucleosome formation potential and the occurrence of repetitive sequences, in the upstream regulatory regions of housekeeping and tissue specific genes. Our data show that putative scaffold/matrix attachment regions are more abundant and nucleosome formation potential is higher in the 5' regions of tissue specific genes as compared to the housekeeping genes. Conclusion The differences in the chromatin features between the two groups of genes indicate the involvement of chromatin organisation in the control of gene expression. The presence of global regulatory mechanisms mediated through chromatin organisation can decrease the burden of invoking gene specific regulators for maintenance of the active/silenced state of gene expression. This could partially explain the lower number of genes estimated in the human genome.

Exploring genes and pathways involved in migraine

NARCIS (Netherlands)

Eising, E.

2017-01-01

The research in this thesis was aimed at identifying genes and molecular pathways involved in migraine. To this end, two gene expression analyses were performed in brain tissue obtained from transgenic mouse models for familial hemiplegic migraine (FHM), a monogenic subtype of migraine with aura.

Portrait of Candida Species Biofilm Regulatory Network Genes.

Science.gov (United States)

Araújo, Daniela; Henriques, Mariana; Silva, Sónia

2017-01-01

Most cases of candidiasis have been attributed to Candida albicans, but Candida glabrata, Candida parapsilosis and Candida tropicalis, designated as non-C. albicans Candida (NCAC), have been identified as frequent human pathogens. Moreover, Candida biofilms are an escalating clinical problem associated with significant rates of mortality. Biofilms have distinct developmental phases, including adhesion/colonisation, maturation and dispersal, controlled by complex regulatory networks. This review discusses recent advances regarding Candida species biofilm regulatory network genes, which are key components for candidiasis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Transcription Profiles Reveal Sugar and Hormone Signaling Pathways Mediating Flower Induction in Apple (Malus domestica Borkh.).

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Xing, Li-Bo; Zhang, Dong; Li, You-Mei; Shen, Ya-Wen; Zhao, Cai-Ping; Ma, Juan-Juan; An, Na; Han, Ming-Yu

2015-10-01

Flower induction in apple (Malus domestica Borkh.) is regulated by complex gene networks that involve multiple signal pathways to ensure flower bud formation in the next year, but the molecular determinants of apple flower induction are still unknown. In this research, transcriptomic profiles from differentiating buds allowed us to identify genes potentially involved in signaling pathways that mediate the regulatory mechanisms of flower induction. A hypothetical model for this regulatory mechanism was obtained by analysis of the available transcriptomic data, suggesting that sugar-, hormone- and flowering-related genes, as well as those involved in cell-cycle induction, participated in the apple flower induction process. Sugar levels and metabolism-related gene expression profiles revealed that sucrose is the initiation signal in flower induction. Complex hormone regulatory networks involved in cytokinin (CK), abscisic acid (ABA) and gibberellic acid pathways also induce apple flower formation. CK plays a key role in the regulation of cell formation and differentiation, and in affecting flowering-related gene expression levels during these processes. Meanwhile, ABA levels and ABA-related gene expression levels gradually increased, as did those of sugar metabolism-related genes, in developing buds, indicating that ABA signals regulate apple flower induction by participating in the sugar-mediated flowering pathway. Furthermore, changes in sugar and starch deposition levels in buds can be affected by ABA content and the expression of the genes involved in the ABA signaling pathway. Thus, multiple pathways, which are mainly mediated by crosstalk between sugar and hormone signals, regulate the molecular network involved in bud growth and flower induction in apple trees. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

Inference of gene regulatory networks with sparse structural equation models exploiting genetic perturbations.

Directory of Open Access Journals (Sweden)

Xiaodong Cai

Full Text Available Integrating genetic perturbations with gene expression data not only improves accuracy of regulatory network topology inference, but also enables learning of causal regulatory relations between genes. Although a number of methods have been developed to integrate both types of data, the desiderata of efficient and powerful algorithms still remains. In this paper, sparse structural equation models (SEMs are employed to integrate both gene expression data and cis-expression quantitative trait loci (cis-eQTL, for modeling gene regulatory networks in accordance with biological evidence about genes regulating or being regulated by a small number of genes. A systematic inference method named sparsity-aware maximum likelihood (SML is developed for SEM estimation. Using simulated directed acyclic or cyclic networks, the SML performance is compared with that of two state-of-the-art algorithms: the adaptive Lasso (AL based scheme, and the QTL-directed dependency graph (QDG method. Computer simulations demonstrate that the novel SML algorithm offers significantly better performance than the AL-based and QDG algorithms across all sample sizes from 100 to 1,000, in terms of detection power and false discovery rate, in all the cases tested that include acyclic or cyclic networks of 10, 30 and 300 genes. The SML method is further applied to infer a network of 39 human genes that are related to the immune function and are chosen to have a reliable eQTL per gene. The resulting network consists of 9 genes and 13 edges. Most of the edges represent interactions reasonably expected from experimental evidence, while the remaining may just indicate the emergence of new interactions. The sparse SEM and efficient SML algorithm provide an effective means of exploiting both gene expression and perturbation data to infer gene regulatory networks. An open-source computer program implementing the SML algorithm is freely available upon request.

The R2R3-MYB-like regulatory factor EOBI, acting downstream of EOBII, regulates scent production by activating ODO1 and structural scent-related genes in petunia.

Science.gov (United States)

Spitzer-Rimon, Ben; Farhi, Moran; Albo, Boaz; Cna'ani, Alon; Ben Zvi, Michal Moyal; Masci, Tania; Edelbaum, Orit; Yu, Yixun; Shklarman, Elena; Ovadis, Marianna; Vainstein, Alexander

2012-12-01

Flower scent is a highly dynamic trait, under developmental, spatial, and diurnal regulation. The mechanism governing scent production is only beginning to be unraveled. In petunia (Petunia hybrida), EMISSION OF BENZENOIDS II (EOBII) controls transcription of both the shikimate pathway-regulating MYB factor ODORANT1 (ODO1) and phenylpropanoid scent-related structural genes. A promoter-activation screen identified an R2R3-MYB-like regulatory factor of phenylpropanoid volatile biosynthesis acting downstream of EOBII, designated EOBI. EOBI silencing led to downregulation of ODO1 and numerous structural scent-related genes from both the shikimate and phenylpropanoid pathways. The ability of EOBI to directly activate ODO1, as revealed by electrophoretic mobility shift assay and yeast one-hybrid analysis, place EOBI upstream of ODO1 in regulating substrate availability for volatile biosynthesis. Interestingly, ODO1-silenced transgenic petunia flowers accumulated higher EOBI transcript levels than controls, suggesting a complex feedback loop between these regulatory factors. The accumulation pattern of EOBI transcript relative to EOBII and ODO1, and the effect of up/downregulation of EOBII on transcript levels of EOBI and ODO1, further support these factors' hierarchical relationships. The dependence of scent production on EOBI expression and its direct interaction with both regulatory and structural genes provide evidence for EOBI's wide-ranging involvement in the production of floral volatiles.

Inferring the functional effect of gene expression changes in signaling pathways

Science.gov (United States)

Sebastián-León, Patricia; Carbonell, José; Salavert, Francisco; Sanchez, Rubén; Medina, Ignacio; Dopazo, Joaquín

2013-01-01

Signaling pathways constitute a valuable source of information that allows interpreting the way in which alterations in gene activities affect to particular cell functionalities. There are web tools available that allow viewing and editing pathways, as well as representing experimental data on them. However, few methods aimed to identify the signaling circuits, within a pathway, associated to the biological problem studied exist and none of them provide a convenient graphical web interface. We present PATHiWAYS, a web-based signaling pathway visualization system that infers changes in signaling that affect cell functionality from the measurements of gene expression values in typical expression microarray case–control experiments. A simple probabilistic model of the pathway is used to estimate the probabilities for signal transmission from any receptor to any final effector molecule (taking into account the pathway topology) using for this the individual probabilities of gene product presence/absence inferred from gene expression values. Significant changes in these probabilities allow linking different cell functionalities triggered by the pathway to the biological problem studied. PATHiWAYS is available at: http://pathiways.babelomics.org/. PMID:23748960

Causality analysis detects the regulatory role of maternal effect genes in the early Drosophila embryo

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Zara Ghodsi

2017-03-01

Full Text Available In developmental studies, inferring regulatory interactions of segmentation genetic network play a vital role in unveiling the mechanism of pattern formation. As such, there exists an opportune demand for theoretical developments and new mathematical models which can result in a more accurate illustration of this genetic network. Accordingly, this paper seeks to extract the meaningful regulatory role of the maternal effect genes using a variety of causality detection techniques and to explore whether these methods can suggest a new analytical view to the gene regulatory networks. We evaluate the use of three different powerful and widely-used models representing time and frequency domain Granger causality and convergent cross mapping technique with the results being thoroughly evaluated for statistical significance. Our findings show that the regulatory role of maternal effect genes is detectable in different time classes and thereby the method is applicable to infer the possible regulatory interactions present among the other genes of this network.

Nutritional control of gene expression in Drosophila larvae via TOR, Myc and a novel cis-regulatory element

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Grewal Savraj S

2010-01-01

Full Text Available Abstract Background Nutrient availability is a key determinant of eukaryotic cell growth. In unicellular organisms many signaling and transcriptional networks link nutrient availability to the expression of metabolic genes required for growth. However, less is known about the corresponding mechanisms that operate in metazoans. We used gene expression profiling to explore this issue in developing Drosophila larvae. Results We found that starvation for dietary amino acids (AA's leads to dynamic changes in transcript levels of many metabolic genes. The conserved insulin/PI3K and TOR signaling pathways mediate nutrition-dependent growth in Drosophila and other animals. We found that many AA starvation-responsive transcripts were also altered in TOR mutants. In contrast, although PI3K overexpression induced robust changes in the expression of many metabolic genes, these changes showed limited overlap with the AA starvation expression profile. We did however identify a strong overlap between genes regulated by the transcription factor, Myc, and AA starvation-responsive genes, particularly those involved in ribosome biogenesis, protein synthesis and mitochondrial function. The consensus Myc DNA binding site is enriched in promoters of these AA starvation genes, and we found that Myc overexpression could bypass dietary AA to induce expression of these genes. We also identified another sequence motif (Motif 1 enriched in the promoters of AA starvation-responsive genes. We showed that Motif 1 was both necessary and sufficient to mediate transcriptional responses to dietary AA in larvae. Conclusions Our data suggest that many of the transcriptional effects of amino acids are mediated via signaling through the TOR pathway in Drosophila larvae. We also find that these transcriptional effects are mediated through at least two mechanisms: via the transcription factor Myc, and via the Motif 1 cis-regulatory element. These studies begin to elucidate a nutrient

A saturation screen for cis-acting regulatory DNA in the Hox genes of Ciona intestinalis

Energy Technology Data Exchange (ETDEWEB)

Keys, David N.; Lee, Byung-in; Di Gregorio, Anna; Harafuji, Naoe; Detter, Chris; Wang, Mei; Kahsai, Orsalem; Ahn, Sylvia; Arellano, Andre; Zhang, Quin; Trong, Stephan; Doyle, Sharon A.; Satoh, Noriyuki; Satou, Yutaka; Saiga, Hidetoshi; Christian, Allen; Rokhsar, Dan; Hawkins, Trevor L.; Levine, Mike; Richardson, Paul

2005-01-05

A screen for the systematic identification of cis-regulatory elements within large (>100 kb) genomic domains containing Hox genes was performed by using the basal chordate Ciona intestinalis. Randomly generated DNA fragments from bacterial artificial chromosomes containing two clusters of Hox genes were inserted into a vector upstream of a minimal promoter and lacZ reporter gene. A total of 222 resultant fusion genes were separately electroporated into fertilized eggs, and their regulatory activities were monitored in larvae. In sum, 21 separable cis-regulatory elements were found. These include eight Hox linked domains that drive expression in nested anterior-posterior domains of ectodermally derived tissues. In addition to vertebrate-like CNS regulation, the discovery of cis-regulatory domains that drive epidermal transcription suggests that C. intestinalis has arthropod-like Hox patterning in the epidermis.

Simple mathematical models of gene regulatory dynamics

CERN Document Server

Mackey, Michael C; Tyran-Kamińska, Marta; Zeron, Eduardo S

2016-01-01

This is a short and self-contained introduction to the field of mathematical modeling of gene-networks in bacteria. As an entry point to the field, we focus on the analysis of simple gene-network dynamics. The notes commence with an introduction to the deterministic modeling of gene-networks, with extensive reference to applicable results coming from dynamical systems theory. The second part of the notes treats extensively several approaches to the study of gene-network dynamics in the presence of noise—either arising from low numbers of molecules involved, or due to noise external to the regulatory process. The third and final part of the notes gives a detailed treatment of three well studied and concrete examples of gene-network dynamics by considering the lactose operon, the tryptophan operon, and the lysis-lysogeny switch. The notes contain an index for easy location of particular topics as well as an extensive bibliography of the current literature. The target audience of these notes are mainly graduat...

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

Science.gov (United States)

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

2015-05-09

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

Fractal gene regulatory networks for robust locomotion control of modular robots

DEFF Research Database (Denmark)

Zahadat, Payam; Christensen, David Johan; Schultz, Ulrik Pagh

2010-01-01

Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed and the ......Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed...

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

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Gaora Peadar Ó

2010-10-01

Full Text Available Abstract Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of

Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network.

Science.gov (United States)

Kordmahalleh, Mina Moradi; Sefidmazgi, Mohammad Gorji; Harrison, Scott H; Homaifar, Abdollah

2017-01-01

The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design. Interactions in gene regulatory networks (GRNs) include effects of transcription factors, repressors, small metabolites, and microRNA species. In addition, the effects of regulatory interactions are not always simultaneous, but can occur after a finite time delay, or as a combined outcome of simultaneous and time delayed interactions. Powerful biotechnologies have been rapidly and successfully measuring levels of genetic expression to illuminate different states of biological systems. This has led to an ensuing challenge to improve the identification of specific regulatory mechanisms through regulatory network reconstructions. Solutions to this challenge will ultimately help to spur forward efforts based on the usage of regulatory network reconstructions in systems biology applications. We have developed a hierarchical recurrent neural network (HRNN) that identifies time-delayed gene interactions using time-course data. A customized genetic algorithm (GA) was used to optimize hierarchical connectivity of regulatory genes and a target gene. The proposed design provides a non-fully connected network with the flexibility of using recurrent connections inside the network. These features and the non-linearity of the HRNN facilitate the process of identifying temporal patterns of a GRN. Our HRNN method was implemented with the Python language. It was first evaluated on simulated data representing linear and nonlinear time-delayed gene-gene interaction models across a range of network sizes and variances of noise. We then further demonstrated the capability of our method in reconstructing GRNs of the Saccharomyces cerevisiae synthetic network for in vivo benchmarking of reverse-engineering and modeling approaches (IRMA). We compared the performance of our method to TD-ARACNE, HCC-CLINDE, TSNI and ebdbNet across different network

The Association between Infants' Self-Regulatory Behavior and MAOA Gene Polymorphism

Science.gov (United States)

Zhang, Minghao; Chen, Xinyin; Way, Niobe; Yoshikawa, Hirokazu; Deng, Huihua; Ke, Xiaoyan; Yu, Weiwei; Chen, Ping; He, Chuan; Chi, Xia; Lu, Zuhong

2011-01-01

Self-regulatory behavior in early childhood is an important characteristic that has considerable implications for the development of adaptive and maladaptive functioning. The present study investigated the relations between a functional polymorphism in the upstream region of monoamine oxidase A gene (MAOA) and self-regulatory behavior in a sample…

A search engine to identify pathway genes from expression data on multiple organisms

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Zambon Alexander C

2007-05-01

Full Text Available Abstract Background The completion of several genome projects showed that most genes have not yet been characterized, especially in multicellular organisms. Although most genes have unknown functions, a large collection of data is available describing their transcriptional activities under many different experimental conditions. In many cases, the coregulatation of a set of genes across a set of conditions can be used to infer roles for genes of unknown function. Results We developed a search engine, the Multiple-Species Gene Recommender (MSGR, which scans gene expression datasets from multiple organisms to identify genes that participate in a genetic pathway. The MSGR takes a query consisting of a list of genes that function together in a genetic pathway from one of six organisms: Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Arabidopsis thaliana, and Helicobacter pylori. Using a probabilistic method to merge searches, the MSGR identifies genes that are significantly coregulated with the query genes in one or more of those organisms. The MSGR achieves its highest accuracy for many human pathways when searches are combined across species. We describe specific examples in which new genes were identified to be involved in a neuromuscular signaling pathway and a cell-adhesion pathway. Conclusion The search engine can scan large collections of gene expression data for new genes that are significantly coregulated with a pathway of interest. By integrating searches across organisms, the MSGR can identify pathway members whose coregulation is either ancient or newly evolved.

Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer

International Nuclear Information System (INIS)

Yu, Jack X; Sieuwerts, Anieta M; Zhang, Yi; Martens, John WM; Smid, Marcel; Klijn, Jan GM; Wang, Yixin; Foekens, John A

2007-01-01

Published prognostic gene signatures in breast cancer have few genes in common. Here we provide a rationale for this observation by studying the prognostic power and the underlying biological pathways of different gene signatures. Gene signatures to predict the development of metastases in estrogen receptor-positive and estrogen receptor-negative tumors were identified using 500 re-sampled training sets and mapping to Gene Ontology Biological Process to identify over-represented pathways. The Global Test program confirmed that gene expression profilings in the common pathways were associated with the metastasis of the patients. The apoptotic pathway and cell division, or cell growth regulation and G-protein coupled receptor signal transduction, were most significantly associated with the metastatic capability of estrogen receptor-positive or estrogen-negative tumors, respectively. A gene signature derived of the common pathways predicted metastasis in an independent cohort. Mapping of the pathways represented by different published prognostic signatures showed that they share 53% of the identified pathways. We show that divergent gene sets classifying patients for the same clinical endpoint represent similar biological processes and that pathway-derived signatures can be used to predict prognosis. Furthermore, our study reveals that the underlying biology related to aggressiveness of estrogen receptor subgroups of breast cancer is quite different

Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

KAUST Repository

Othoum, Ghofran K

2013-05-01

Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

KAUST Repository

Othoum, Ghofran K

2013-01-01

Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

Using reporter gene assays to identify cis regulatory differences between humans and chimpanzees.

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Chabot, Adrien; Shrit, Ralla A; Blekhman, Ran; Gilad, Yoav

2007-08-01

Most phenotypic differences between human and chimpanzee are likely to result from differences in gene regulation, rather than changes to protein-coding regions. To date, however, only a handful of human-chimpanzee nucleotide differences leading to changes in gene regulation have been identified. To hone in on differences in regulatory elements between human and chimpanzee, we focused on 10 genes that were previously found to be differentially expressed between the two species. We then designed reporter gene assays for the putative human and chimpanzee promoters of the 10 genes. Of seven promoters that we found to be active in human liver cell lines, human and chimpanzee promoters had significantly different activity in four cases, three of which recapitulated the gene expression difference seen in the microarray experiment. For these three genes, we were therefore able to demonstrate that a change in cis influences expression differences between humans and chimpanzees. Moreover, using site-directed mutagenesis on one construct, the promoter for the DDA3 gene, we were able to identify three nucleotides that together lead to a cis regulatory difference between the species. High-throughput application of this approach can provide a map of regulatory element differences between humans and our close evolutionary relatives.

Anthocyanin biosynthesis in fruit tree crops: Genes and their regulation

African Journals Online (AJOL)

The anthocyanin biosynthesis pathway is a little complex with branches responsible for the synthesis of a variety of metabolites. In fruit tree crops, during the past decade, many structural genes encoding enzymes in the anthocyanin biosynthetic pathway and various regulatory genes encoding transcription factors that ...

Gene regulatory network inference by point-based Gaussian approximation filters incorporating the prior information.

Science.gov (United States)

Jia, Bin; Wang, Xiaodong

2013-12-17

: The extended Kalman filter (EKF) has been applied to inferring gene regulatory networks. However, it is well known that the EKF becomes less accurate when the system exhibits high nonlinearity. In addition, certain prior information about the gene regulatory network exists in practice, and no systematic approach has been developed to incorporate such prior information into the Kalman-type filter for inferring the structure of the gene regulatory network. In this paper, an inference framework based on point-based Gaussian approximation filters that can exploit the prior information is developed to solve the gene regulatory network inference problem. Different point-based Gaussian approximation filters, including the unscented Kalman filter (UKF), the third-degree cubature Kalman filter (CKF3), and the fifth-degree cubature Kalman filter (CKF5) are employed. Several types of network prior information, including the existing network structure information, sparsity assumption, and the range constraint of parameters, are considered, and the corresponding filters incorporating the prior information are developed. Experiments on a synthetic network of eight genes and the yeast protein synthesis network of five genes are carried out to demonstrate the performance of the proposed framework. The results show that the proposed methods provide more accurate inference results than existing methods, such as the EKF and the traditional UKF.

Differential hexosamine biosynthetic pathway gene expression with type 2 diabetes

Directory of Open Access Journals (Sweden)

Megan Coomer

2014-01-01

Full Text Available The hexosamine biosynthetic pathway (HBP culminates in the attachment of O-linked β-N-acetylglucosamine (O-GlcNAc onto serine/threonine residues of target proteins. The HBP is regulated by several modulators, i.e. O-linked β-N-acetylglucosaminyl transferase (OGT and β-N-acetylglucosaminidase (OGA catalyze the addition and removal of O-GlcNAc moieties, respectively; while flux is controlled by the rate-limiting enzyme glutamine:fructose-6-phosphate amidotransferase (GFPT, transcribed by two genes, GFPT1 and GFPT2. Since increased HBP flux is glucose-responsive and linked to insulin resistance/type 2 diabetes onset, we hypothesized that diabetic individuals exhibit differential expression of HBP regulatory genes. Volunteers (n = 60; n = 20 Mixed Ancestry, n = 40 Caucasian were recruited from Stellenbosch and Paarl (Western Cape, South Africa and classified as control, pre- or diabetic according to fasting plasma glucose and HbA1c levels, respectively. RNA was purified from leukocytes isolated from collected blood samples and OGT, OGA, GFPT1 and GFPT2 expressions determined by quantitative real-time PCR. The data reveal lower OGA expression in diabetic individuals (P < 0.01, while pre- and diabetic subjects displayed attenuated OGT expression vs. controls (P < 0.01 and P < 0.001, respectively. Moreover, GFPT2 expression decreased in pre- and diabetic Caucasians vs. controls (P < 0.05 and P < 0.01, respectively. We also found ethnic differences, i.e. Mixed Ancestry individuals exhibited a 2.4-fold increase in GFPT2 expression vs. Caucasians, despite diagnosis (P < 0.01. Gene expression of HBP regulators differs between diabetic and non-diabetic individuals, together with distinct ethnic-specific gene profiles. Thus differential HBP gene regulation may offer diagnostic utility and provide candidate susceptibility genes for different ethnic groupings.

HPRT deficiency coordinately dysregulates canonical Wnt and presenilin-1 signaling: a neuro-developmental regulatory role for a housekeeping gene?

Directory of Open Access Journals (Sweden)

Tae Hyuk Kang

2011-01-01

Full Text Available We have used microarray-based methods of global gene expression together with quantitative PCR and Western blot analysis to identify dysregulation of genes and aberrant cellular processes in human fibroblasts and in SH-SY5Y neuroblastoma cells made HPRT-deficient by transduction with a retrovirus stably expressing an shRNA targeted against HPRT. Analysis of the microarray expression data by Gene ontology (GO and Gene Set Enrichment Analysis (GSEA as well as significant pathway analysis by GeneSpring GX10 and Panther Classification System reveal that HPRT deficiency is accompanied by aberrations in a variety of pathways known to regulate neurogenesis or to be implicated in neurodegenerative disease, including the canonical Wnt/β-catenin and the Alzheimer's disease/presenilin signaling pathways. Dysregulation of the Wnt/β-catenin pathway is confirmed by Western blot demonstration of cytosolic sequestration of β-catenin during in vitro differentiation of the SH-SY5Y cells toward the neuronal phenotype. We also demonstrate that two key transcription factor genes known to be regulated by Wnt signaling and to be vital for the generation and function of dopaminergic neurons; i.e., Lmx1a and Engrailed 1, are down-regulated in the HPRT knockdown SH-SY5Y cells. In addition to the Wnt signaling aberration, we found that expression of presenilin-1 shows severely aberrant expression in HPRT-deficient SH-SY5Y cells, reflected by marked deficiency of the 23 kDa C-terminal fragment of presenilin-1 in knockdown cells. Western blot analysis of primary fibroblast cultures from two LND patients also shows dysregulated presenilin-1 expression, including aberrant proteolytic processing of presenilin-1. These demonstrations of dysregulated Wnt signaling and presenilin-1 expression together with impaired expression of dopaminergic transcription factors reveal broad pleitropic neuro-regulatory defects played by HPRT expression and suggest new directions for

Transcriptome Analysis of an Insecticide Resistant Housefly Strain: Insights about SNPs and Regulatory Elements in Cytochrome P450 Genes.

Science.gov (United States)

Mahmood, Khalid; Højland, Dorte H; Asp, Torben; Kristensen, Michael

2016-01-01

Insecticide resistance in the housefly, Musca domestica, has been investigated for more than 60 years. It will enter a new era after the recent publication of the housefly genome and the development of multiple next generation sequencing technologies. The genetic background of the xenobiotic response can now be investigated in greater detail. Here, we investigate the 454-pyrosequencing transcriptome of the spinosad-resistant 791spin strain in relation to the housefly genome with focus on P450 genes. The de novo assembly of clean reads gave 35,834 contigs consisting of 21,780 sequences of the spinosad resistant strain. The 3,648 sequences were annotated with an enzyme code EC number and were mapped to 124 KEGG pathways with metabolic processes as most highly represented pathway. One hundred and twenty contigs were annotated as P450s covering 44 different P450 genes of housefly. Eight differentially expressed P450s genes were identified and investigated for SNPs, CpG islands and common regulatory motifs in promoter and coding regions. Functional annotation clustering of metabolic related genes and motif analysis of P450s revealed their association with epigenetic, transcription and gene expression related functions. The sequence variation analysis resulted in 12 SNPs and eight of them found in cyp6d1. There is variation in location, size and frequency of CpG islands and specific motifs were also identified in these P450s. Moreover, identified motifs were associated to GO terms and transcription factors using bioinformatic tools. Transcriptome data of a spinosad resistant strain provide together with genome data fundamental support for future research to understand evolution of resistance in houseflies. Here, we report for the first time the SNPs, CpG islands and common regulatory motifs in differentially expressed P450s. Taken together our findings will serve as a stepping stone to advance understanding of the mechanism and role of P450s in xenobiotic detoxification.

Comparison of evolutionary algorithms in gene regulatory network model inference.

LENUS (Irish Health Repository)

2010-01-01

ABSTRACT: BACKGROUND: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very difficult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insufficient. RESULTS: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and offer a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. CONCLUSIONS: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identified and a platform for development of appropriate model formalisms is established.

Singular Perturbation Analysis and Gene Regulatory Networks with Delay

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Shlykova, Irina; Ponosov, Arcady

2009-09-01

There are different ways of how to model gene regulatory networks. Differential equations allow for a detailed description of the network's dynamics and provide an explicit model of the gene concentration changes over time. Production and relative degradation rate functions used in such models depend on the vector of steeply sloped threshold functions which characterize the activity of genes. The most popular example of the threshold functions comes from the Boolean network approach, where the threshold functions are given by step functions. The system of differential equations becomes then piecewise linear. The dynamics of this system can be described very easily between the thresholds, but not in the switching domains. For instance this approach fails to analyze stationary points of the system and to define continuous solutions in the switching domains. These problems were studied in [2], [3], but the proposed model did not take into account a time delay in cellular systems. However, analysis of real gene expression data shows a considerable number of time-delayed interactions suggesting that time delay is essential in gene regulation. Therefore, delays may have a great effect on the dynamics of the system presenting one of the critical factors that should be considered in reconstruction of gene regulatory networks. The goal of this work is to apply the singular perturbation analysis to certain systems with delay and to obtain an analog of Tikhonov's theorem, which provides sufficient conditions for constracting the limit system in the delay case.

The capacity for multistability in small gene regulatory networks

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Grotewold Erich

2009-09-01

Full Text Available Abstract Background Recent years have seen a dramatic increase in the use of mathematical modeling to gain insight into gene regulatory network behavior across many different organisms. In particular, there has been considerable interest in using mathematical tools to understand how multistable regulatory networks may contribute to developmental processes such as cell fate determination. Indeed, such a network may subserve the formation of unicellular leaf hairs (trichomes in the model plant Arabidopsis thaliana. Results In order to investigate the capacity of small gene regulatory networks to generate multiple equilibria, we present a chemical reaction network (CRN-based modeling formalism and describe a number of methods for CRN analysis in a parameter-free context. These methods are compared and applied to a full set of one-component subnetworks, as well as a large random sample from 40,680 similarly constructed two-component subnetworks. We find that positive feedback and cooperativity mediated by transcription factor (TF dimerization is a requirement for one-component subnetwork bistability. For subnetworks with two components, the presence of these processes increases the probability that a randomly sampled subnetwork will exhibit multiple equilibria, although we find several examples of bistable two-component subnetworks that do not involve cooperative TF-promoter binding. In the specific case of epidermal differentiation in Arabidopsis, dimerization of the GL3-GL1 complex and cooperative sequential binding of GL3-GL1 to the CPC promoter are each independently sufficient for bistability. Conclusion Computational methods utilizing CRN-specific theorems to rule out bistability in small gene regulatory networks are far superior to techniques generally applicable to deterministic ODE systems. Using these methods to conduct an unbiased survey of parameter-free deterministic models of small networks, and the Arabidopsis epidermal cell

IntPath--an integrated pathway gene relationship database for model organisms and important pathogens.

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Zhou, Hufeng; Jin, Jingjing; Zhang, Haojun; Yi, Bo; Wozniak, Michal; Wong, Limsoon

2012-01-01

Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. In this paper, we overcome these issues through extraction, normalization and integration of pathway data from several major public databases (KEGG, WikiPathways, BioCyc, etc). We build a database that not only hosts our integrated pathway gene relationship data for public access but also maintains the necessary updates in the long run. This public repository is named IntPath (Integrated Pathway gene relationship database for model organisms and important pathogens). Four organisms--S. cerevisiae, M. tuberculosis H37Rv, H. Sapiens and M. musculus--are included in this version (V2.0) of IntPath. IntPath uses the "full unification" approach to ensure no deletion and no introduced noise in this process. Therefore, IntPath contains much richer pathway-gene and pathway-gene pair relationships and much larger number of non-redundant genes and gene pairs than any of the single-source databases. The gene relationships of each gene (measured by average node degree) per pathway are significantly richer. The gene relationships in each pathway (measured by average number of gene pairs per pathway) are also considerably richer in the integrated pathways. Moderate manual curation are involved to get rid of errors and noises from source data (e.g., the gene ID errors in WikiPathways and

In silico comparison of genomic regions containing genes coding for enzymes and transcription factors for the phenylpropanoid pathway in Phaseolus vulgaris L. and Glycine max L. Merr

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Yarmilla eReinprecht

2013-09-01

Full Text Available Legumes contain a variety of phytochemicals derived from the phenylpropanoid pathway that have important effects on human health as well as seed coat color, plant disease resistance and nodulation. However, the information about the genes involved in this important pathway is fragmentary in common bean (Phaseolus vulgaris L.. The objectives of this research were to isolate genes that function in and control the phenylpropanoid pathway in common bean, determine their genomic locations in silico in common bean and soybean, and analyze sequences of the 4CL gene family in two common bean genotypes. Sequences of phenylpropanoid pathway genes available for common bean or other plant species were aligned, and the conserved regions were used to design sequence-specific primers. The PCR products were cloned and sequenced and the gene sequences along with common bean gene-based (g markers were BLASTed against the Glycine max v.1.0 genome and the P. vulgaris v.1.0 (Andean early release genome. In addition, gene sequences were BLASTed against the OAC Rex (Mesoamerican genome sequence assembly. In total, fragments of 46 structural and regulatory phenylpropanoid pathway genes were characterized in this way and placed in silico on common bean and soybean sequence maps. The maps contain over 250 common bean g and SSR (simple sequence repeat markers and identify the positions of more than 60 additional phenylpropanoid pathway gene sequences, plus the putative locations of seed coat color genes. The majority of cloned phenylpropanoid pathway gene sequences were mapped to one location in the common bean genome but had two positions in soybean. The comparison of the genomic maps confirmed previous studies, which show that common bean and soybean share genomic regions, including those containing phenylpropanoid pathway gene sequences, with conserved synteny. Indels identified in the comparison of Andean and Mesoamerican common bean sequences might be used to develop

About miRNAs, miRNA seeds, target genes and target pathways.

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Kehl, Tim; Backes, Christina; Kern, Fabian; Fehlmann, Tobias; Ludwig, Nicole; Meese, Eckart; Lenhof, Hans-Peter; Keller, Andreas

2017-12-05

miRNAs are typically repressing gene expression by binding to the 3' UTR, leading to degradation of the mRNA. This process is dominated by the eight-base seed region of the miRNA. Further, miRNAs are known not only to target genes but also to target significant parts of pathways. A logical line of thoughts is: miRNAs with similar (seed) sequence target similar sets of genes and thus similar sets of pathways. By calculating similarity scores for all 3.25 million pairs of 2,550 human miRNAs, we found that this pattern frequently holds, while we also observed exceptions. Respective results were obtained for both, predicted target genes as well as experimentally validated targets. We note that miRNAs target gene set similarity follows a bimodal distribution, pointing at a set of 282 miRNAs that seems to target genes with very high specificity. Further, we discuss miRNAs with different (seed) sequences that nonetheless regulate similar gene sets or pathways. Most intriguingly, we found miRNA pairs that regulate different gene sets but similar pathways such as miR-6886-5p and miR-3529-5p. These are jointly targeting different parts of the MAPK signaling cascade. The main goal of this study is to provide a general overview on the results, to highlight a selection of relevant results on miRNAs, miRNA seeds, target genes and target pathways and to raise awareness for artifacts in respective comparisons. The full set of information that allows to infer detailed results on each miRNA has been included in miRPathDB, the miRNA target pathway database (https://mpd.bioinf.uni-sb.de).

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

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Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A

2018-02-22

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be

On the role of sparseness in the evolution of modularity in gene regulatory networks.

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Espinosa-Soto, Carlos

2018-05-01

Modularity is a widespread property in biological systems. It implies that interactions occur mainly within groups of system elements. A modular arrangement facilitates adjustment of one module without perturbing the rest of the system. Therefore, modularity of developmental mechanisms is a major factor for evolvability, the potential to produce beneficial variation from random genetic change. Understanding how modularity evolves in gene regulatory networks, that create the distinct gene activity patterns that characterize different parts of an organism, is key to developmental and evolutionary biology. One hypothesis for the evolution of modules suggests that interactions between some sets of genes become maladaptive when selection favours additional gene activity patterns. The removal of such interactions by selection would result in the formation of modules. A second hypothesis suggests that modularity evolves in response to sparseness, the scarcity of interactions within a system. Here I simulate the evolution of gene regulatory networks and analyse diverse experimentally sustained networks to study the relationship between sparseness and modularity. My results suggest that sparseness alone is neither sufficient nor necessary to explain modularity in gene regulatory networks. However, sparseness amplifies the effects of forms of selection that, like selection for additional gene activity patterns, already produce an increase in modularity. That evolution of new gene activity patterns is frequent across evolution also supports that it is a major factor in the evolution of modularity. That sparseness is widespread across gene regulatory networks indicates that it may have facilitated the evolution of modules in a wide variety of cases.

The gene regulatory network for breast cancer: Integrated regulatory landscape of cancer hallmarks

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Frank eEmmert-Streib

2014-02-01

Full Text Available In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of $351$ patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome $21$ is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.

Halobenzoquinone-Induced Alteration of Gene Expression Associated with Oxidative Stress Signaling Pathways.

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Li, Jinhua; Moe, Birget; Liu, Yanming; Li, Xing-Fang

2018-06-05

Halobenzoquinones (HBQs) are emerging disinfection byproducts (DBPs) that effectively induce reactive oxygen species and oxidative damage in vitro. However, the impacts of HBQs on oxidative-stress-related gene expression have not been investigated. In this study, we examined alterations in the expression of 44 genes related to oxidative-stress-induced signaling pathways in human uroepithelial cells (SV-HUC-1) upon exposure to six HBQs. The results show the structure-dependent effects of HBQs on the studied gene expression. After 2 h of exposure, the expression levels of 9 to 28 genes were altered, while after 8 h of exposure, the expression levels of 29 to 31 genes were altered. Four genes ( HMOX1, NQO1, PTGS2, and TXNRD1) were significantly upregulated by all six HBQs at both exposure time points. Ingenuity pathway analysis revealed that the Nrf2 pathway was significantly responsive to HBQ exposure. Other canonical pathways responsive to HBQ exposure included GSH redox reductions, superoxide radical degradation, and xenobiotic metabolism signaling. This study has demonstrated that HBQs significantly alter the gene expression of oxidative-stress-related signaling pathways and contributes to the understanding of HBQ-DBP-associated toxicity.

The R2R3-MYB–Like Regulatory Factor EOBI, Acting Downstream of EOBII, Regulates Scent Production by Activating ODO1 and Structural Scent-Related Genes in Petunia[C][W

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Spitzer-Rimon, Ben; Farhi, Moran; Albo, Boaz; Cna’ani, Alon; Ben Zvi, Michal Moyal; Masci, Tania; Edelbaum, Orit; Yu, Yixun; Shklarman, Elena; Ovadis, Marianna; Vainstein, Alexander

2012-01-01

Flower scent is a highly dynamic trait, under developmental, spatial, and diurnal regulation. The mechanism governing scent production is only beginning to be unraveled. In petunia (Petunia hybrida), EMISSION OF BENZENOIDS II (EOBII) controls transcription of both the shikimate pathway-regulating MYB factor ODORANT1 (ODO1) and phenylpropanoid scent-related structural genes. A promoter-activation screen identified an R2R3-MYB–like regulatory factor of phenylpropanoid volatile biosynthesis acting downstream of EOBII, designated EOBI. EOBI silencing led to downregulation of ODO1 and numerous structural scent-related genes from both the shikimate and phenylpropanoid pathways. The ability of EOBI to directly activate ODO1, as revealed by electrophoretic mobility shift assay and yeast one-hybrid analysis, place EOBI upstream of ODO1 in regulating substrate availability for volatile biosynthesis. Interestingly, ODO1-silenced transgenic petunia flowers accumulated higher EOBI transcript levels than controls, suggesting a complex feedback loop between these regulatory factors. The accumulation pattern of EOBI transcript relative to EOBII and ODO1, and the effect of up/downregulation of EOBII on transcript levels of EOBI and ODO1, further support these factors' hierarchical relationships. The dependence of scent production on EOBI expression and its direct interaction with both regulatory and structural genes provide evidence for EOBI’s wide-ranging involvement in the production of floral volatiles. PMID:23275577

An integer optimization algorithm for robust identification of non-linear gene regulatory networks

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Chemmangattuvalappil Nishanth

2012-09-01

Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters

A cross-study gene set enrichment analysis identifies critical pathways in endometriosis

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Bai Chunyan

2009-09-01

Full Text Available Abstract Background Endometriosis is an enigmatic disease. Gene expression profiling of endometriosis has been used in several studies, but few studies went further to classify subtypes of endometriosis based on expression patterns and to identify possible pathways involved in endometriosis. Some of the observed pathways are more inconsistent between the studies, and these candidate pathways presumably only represent a fraction of the pathways involved in endometriosis. Methods We applied a standardised microarray preprocessing and gene set enrichment analysis to six independent studies, and demonstrated increased concordance between these gene datasets. Results We find 16 up-regulated and 19 down-regulated pathways common in ovarian endometriosis data sets, 22 up-regulated and one down-regulated pathway common in peritoneal endometriosis data sets. Among them, 12 up-regulated and 1 down-regulated were found consistent between ovarian and peritoneal endometriosis. The main canonical pathways identified are related to immunological and inflammatory disease. Early secretory phase has the most over-represented pathways in the three uterine cycle phases. There are no overlapping significant pathways between the dataset from human endometrial endothelial cells and the datasets from ovarian endometriosis which used whole tissues. Conclusion The study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. By standardised microarray preprocessing and GSEA, we have increased the concordance in identifying many biological mechanisms involved in endometriosis. The identified gene pathways will shed light on the understanding of endometriosis and promote the development of novel therapies.

Inferring nonlinear gene regulatory networks from gene expression data based on distance correlation.

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Xiaobo Guo

Full Text Available Nonlinear dependence is general in regulation mechanism of gene regulatory networks (GRNs. It is vital to properly measure or test nonlinear dependence from real data for reconstructing GRNs and understanding the complex regulatory mechanisms within the cellular system. A recently developed measurement called the distance correlation (DC has been shown powerful and computationally effective in nonlinear dependence for many situations. In this work, we incorporate the DC into inferring GRNs from the gene expression data without any underling distribution assumptions. We propose three DC-based GRNs inference algorithms: CLR-DC, MRNET-DC and REL-DC, and then compare them with the mutual information (MI-based algorithms by analyzing two simulated data: benchmark GRNs from the DREAM challenge and GRNs generated by SynTReN network generator, and an experimentally determined SOS DNA repair network in Escherichia coli. According to both the receiver operator characteristic (ROC curve and the precision-recall (PR curve, our proposed algorithms significantly outperform the MI-based algorithms in GRNs inference.

Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

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Frank Emmert-Streib

2013-02-01

Full Text Available The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I observational gene expression data: normal environmental condition, (II interventional gene expression data: growth in rich media, (III interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.

Multiple independent regulatory pathways control UBI4 expression after heat shock in Saccharomyces cerevisiae.

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Simon, J R; Treger, J M; McEntee, K

1999-02-01

Transcription of the polyubiquitin gene UBI4 of Saccharomyces cerevisiae is strongly induced by a variety of environmental stresses, such as heat shock, nutrient depletion and exposure to DNA-damaging agents. This transcriptional response of UBI4 is likely to be the primary mechanism for increasing the pool of ubiquitin for degradation of stress-damaged proteins. Deletion and promoter fusion studies of the 5' regulatory sequences indicated that two different elements, heat shock elements (HSEs) and stress response element (STREs), contributed independently to heat shock regulation of the UBI4 gene. In the absence of HSEs, STRE sequences localized to the intervals -264 to -238 and -215 to -183 were needed for stress control of transcription after heat shock. Site-directed mutagenesis of the STRE (AG4) at -252 to -248 abolished heat shock induction of UBI4 transcription. Northern analysis demonstrated that cells containing either a temperature-sensitive HSF or non-functional Msn2p/Msn4p transcription factors induced high levels of UBI4 transcripts after heat shock. In cells deficient in both heat stress pathways, heat-induced UBI4 transcript levels were considerably lower but not abolished, suggesting a role for another factor(s) in stress control of its expression.

Optimal structural inference of signaling pathways from unordered and overlapping gene sets.

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Acharya, Lipi R; Judeh, Thair; Wang, Guangdi; Zhu, Dongxiao

2012-02-15

A plethora of bioinformatics analysis has led to the discovery of numerous gene sets, which can be interpreted as discrete measurements emitted from latent signaling pathways. Their potential to infer signaling pathway structures, however, has not been sufficiently exploited. Existing methods accommodating discrete data do not explicitly consider signal cascading mechanisms that characterize a signaling pathway. Novel computational methods are thus needed to fully utilize gene sets and broaden the scope from focusing only on pairwise interactions to the more general cascading events in the inference of signaling pathway structures. We propose a gene set based simulated annealing (SA) algorithm for the reconstruction of signaling pathway structures. A signaling pathway structure is a directed graph containing up to a few hundred nodes and many overlapping signal cascades, where each cascade represents a chain of molecular interactions from the cell surface to the nucleus. Gene sets in our context refer to discrete sets of genes participating in signal cascades, the basic building blocks of a signaling pathway, with no prior information about gene orderings in the cascades. From a compendium of gene sets related to a pathway, SA aims to search for signal cascades that characterize the optimal signaling pathway structure. In the search process, the extent of overlap among signal cascades is used to measure the optimality of a structure. Throughout, we treat gene sets as random samples from a first-order Markov chain model. We evaluated the performance of SA in three case studies. In the first study conducted on 83 KEGG pathways, SA demonstrated a significantly better performance than Bayesian network methods. Since both SA and Bayesian network methods accommodate discrete data, use a 'search and score' network learning strategy and output a directed network, they can be compared in terms of performance and computational time. In the second study, we compared SA and

Human T lymphotropic virus type-1 p30II alters cellular gene expression to selectively enhance signaling pathways that activate T lymphocytes

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Feuer Gerold

2004-11-01

Full Text Available Abstract Background Human T-lymphotropic virus type-1 (HTLV-1 is a deltaretrovirus that causes adult T-cell leukemia/lymphoma and is implicated in a variety of lymphocyte-mediated disorders. HTLV-1 contains both regulatory and accessory genes in four pX open reading frames. pX ORF-II encodes two proteins, p13II and p30II, which are incompletely defined in the virus life cycle or HTLV-1 pathogenesis. Proviral clones of the virus with pX ORF-II mutations diminish the ability of the virus to maintain viral loads in vivo. Exogenous expression of p30II differentially modulates CREB and Tax-responsive element-mediated transcription through its interaction with CREB-binding protein/p300 and represses tax/rex RNA nuclear export. Results Herein, we further characterized the role of p30II in regulation of cellular gene expression, using stable p30II expression system employing lentiviral vectors to test cellular gene expression with Affymetrix U133A arrays, representing ~33,000 human genes. Reporter assays in Jurkat T cells and RT-PCR in Jurkat and primary CD4+ T-lymphocytes were used to confirm selected gene expression patterns. Our data reveals alterations of interrelated pathways of cell proliferation, T-cell signaling, apoptosis and cell cycle in p30II expressing Jurkat T cells. In all categories, p30II appeared to be an overall repressor of cellular gene expression, while selectively increasing the expression of certain key regulatory genes. Conclusions We are the first to demonstrate that p30II, while repressing the expression of many genes, selectively activates key gene pathways involved in T-cell signaling/activation. Collectively, our data suggests that this complex retrovirus, associated with lymphoproliferative diseases, relies upon accessory gene products to modify cellular environment to promote clonal expansion of the virus genome and thus maintain proviral loads in vivo.

Comparative metabolomics in primates reveals the effects of diet and gene regulatory variation on metabolic divergence.

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Blekhman, Ran; Perry, George H; Shahbaz, Sevini; Fiehn, Oliver; Clark, Andrew G; Gilad, Yoav

2014-07-28

Human diets differ from those of non-human primates. Among few obvious differences, humans consume more meat than most non-human primates and regularly cook their food. It is hypothesized that a dietary shift during human evolution has been accompanied by molecular adaptations in metabolic pathways. Consistent with this notion, comparative studies of gene expression levels in primates have found that the regulation of genes with metabolic functions tend to evolve rapidly in the human lineage. The metabolic consequences of these regulatory differences, however, remained unknown. To address this gap, we performed a comparative study using a combination of gene expression and metabolomic profiling in livers from humans, chimpanzees, and rhesus macaques. We show that dietary differences between species have a strong effect on metabolic concentrations. In addition, we found that differences in metabolic concentration across species are correlated with inter-species differences in the expression of the corresponding enzymes, which control the same metabolic reaction. We identified a number of metabolic compounds with lineage-specific profiles, including examples of human-species metabolic differences that may be directly related to dietary differences.

Integrated bioinformatics analysis reveals key candidate genes and pathways in breast cancer.

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Wang, Yuzhi; Zhang, Yi; Huang, Qian; Li, Chengwen

2018-04-19

Breast cancer (BC) is the leading malignancy in women worldwide, yet relatively little is known about the genes and signaling pathways involved in BC tumorigenesis and progression. The present study aimed to elucidate potential key candidate genes and pathways in BC. Five gene expression profile data sets (GSE22035, GSE3744, GSE5764, GSE21422 and GSE26910) were downloaded from the Gene Expression Omnibus (GEO) database, which included data from 113 tumorous and 38 adjacent non‑tumorous tissue samples. Differentially expressed genes (DEGs) were identified using t‑tests in the limma R package. These DEGs were subsequently investigated by pathway enrichment analysis and a protein‑protein interaction (PPI) network was constructed. The most significant module from the PPI network was selected for pathway enrichment analysis. In total, 227 DEGs were identified, of which 82 were upregulated and 145 were downregulated. Pathway enrichment analysis results revealed that the upregulated DEGs were mainly enriched in 'cell division', the 'proteinaceous extracellular matrix (ECM)', 'ECM structural constituents' and 'ECM‑receptor interaction', whereas downregulated genes were mainly enriched in 'response to drugs', 'extracellular space', 'transcriptional activator activity' and the 'peroxisome proliferator‑activated receptor signaling pathway'. The PPI network contained 174 nodes and 1,257 edges. DNA topoisomerase 2‑a, baculoviral inhibitor of apoptosis repeat‑containing protein 5, cyclin‑dependent kinase 1, G2/mitotic‑specific cyclin‑B1 and kinetochore protein NDC80 homolog were identified as the top 5 hub genes. Furthermore, the genes in the most significant module were predominantly involved in 'mitotic nuclear division', 'mid‑body', 'protein binding' and 'cell cycle'. In conclusion, the DEGs, relative pathways and hub genes identified in the present study may aid in understanding of the molecular mechanisms underlying BC progression and provide

The nude mutant gene Foxn1 is a HOXC13 regulatory target during hair follicle and nail differentiation.

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Potter, Christopher S; Pruett, Nathanael D; Kern, Michael J; Baybo, Mary Ann; Godwin, Alan R; Potter, Kathleen A; Peterson, Ron L; Sundberg, John P; Awgulewitsch, Alexander

2011-04-01

Among the Hox genes, homeobox C13 (Hoxc13) has been shown to be essential for proper hair shaft differentiation, as Hoxc13 gene-targeted (Hoxc13(tm1Mrc)) mice completely lack external hair. Because of the remarkable overt phenotypic parallels to the Foxn1(nu) (nude) mutant mice, we sought to determine whether Hoxc13 and forkhead box N1 (Foxn1) might act in a common pathway of hair follicle (HF) differentiation. We show that the alopecia exhibited by both the Hoxc13(tm1Mrc) and Foxn1(nu) mice is because of strikingly similar defects in hair shaft differentiation and that both mutants suffer from a severe nail dystrophy. These phenotypic similarities are consistent with the extensive overlap between Hoxc13 and Foxn1 expression patterns in the HF and the nail matrix. Furthermore, DNA microarray analysis of skin from Hoxc13(tm1Mrc) mice identified Foxn1 as significantly downregulated along with numerous hair keratin genes. This Foxn1 downregulation apparently reflects the loss of direct transcriptional control by HOXC13 as indicated by our results obtained through co-transfection and chromatin immunoprecipitation (ChIP) assays. As presented in the discussion, these data support a regulatory model of keratinocyte differentiation in which HOXC13-dependent activation of Foxn1 is part of a regulatory cascade controlling the expression of terminal differentiation markers.

Trichomes: different regulatory networks lead to convergent structures.

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Serna, Laura; Martin, Cathie

2006-06-01

Sometimes, proteins, biological structures or even organisms have similar functions and appearances but have evolved through widely divergent pathways. There is experimental evidence to suggest that different developmental pathways have converged to produce similar outgrowths of the aerial plant epidermis, referred to as trichomes. The emerging picture suggests that trichomes in Arabidopsis thaliana and, perhaps, in cotton develop through a transcriptional regulatory network that differs from those regulating trichome formation in Antirrhinum and Solanaceous species. Several lines of evidence suggest that the duplication of a gene controlling anthocyanin production and subsequent divergence might be the major force driving trichome formation in Arabidopsis, whereas the multicellular trichomes of Antirrhinum and Solanaceous species appear to have a different regulatory origin.

Identification of key pathways and genes influencing prognosis in bladder urothelial carcinoma

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Ning X

2017-03-01

Full Text Available Xin Ning, Yaoliang Deng Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province, People’s Republic of China Background: Genomic profiling can be used to identify the predictive effect of genomic subsets for determining prognosis in bladder urothelial carcinoma (BUC after radical cystectomy. This study aimed to investigate potential gene and pathway markers associated with prognosis in BUC.Methods: A microarray dataset of BUC was obtained from The Cancer Genome Atlas database. Differentially expressed genes (DEGs were identified by DESeq of the R platform. Kaplan–Meier analysis was applied for prognostic markers. Key pathways and genes were identified using bioinformatics tools, such as gene set enrichment analysis, gene ontology, the Kyoto Encyclopedia of Genes and Genomes, gene multiple association network integration algorithm (GeneMANIA, Search Tool for the Retrieval of Interacting Genes/Proteins, and Molecular Complex Detection.Results: A comparative gene set enrichment analysis of tumor and adjacent normal tissues suggested BUC tumorigenesis resulted mainly from enrichment of cell cycle and DNA damage and repair-related biological processes and pathways, including TP53 and mitotic recombination. Two hundred and fifty-six genes were identified as potential prognosis-related DEGs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the potential prognosis-related DEGs were enriched in angiogenesis, including the cyclic adenosine monophosphate biosynthetic process, cyclic guanosine monophosphate-protein kinase G, mitogen-activated protein kinase, Rap1, and phosphoinositide-3-kinase-AKT signaling pathway. Nine hub genes, TAGLN, ACTA2, MYH11, CALD1, MYLK, GEM, PRELP, TPM2, and OGN, were identified from the intersection of protein–protein interaction and GeneMANIA networks. Module analysis of protein–protein interaction and GeneMANIA networks mainly showed

Identification of sparsely distributed clusters of cis-regulatory elements in sets of co-expressed genes

OpenAIRE

Kreiman, Gabriel

2004-01-01

Sequence information and high‐throughput methods to measure gene expression levels open the door to explore transcriptional regulation using computational tools. Combinatorial regulation and sparseness of regulatory elements throughout the genome allow organisms to control the spatial and temporal patterns of gene expression. Here we study the organization of cis‐regulatory elements in sets of co‐regulated genes. We build an algorithm to search for combinations of transcription factor binding...

Inferring the conservative causal core of gene regulatory networks

Directory of Open Access Journals (Sweden)

Emmert-Streib Frank

2010-09-01

Full Text Available Abstract Background Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. Results In this paper, we introduce a novel gene regulatory network inference (GRNI algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. Conclusions For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

Inferring the conservative causal core of gene regulatory networks.

Science.gov (United States)

Altay, Gökmen; Emmert-Streib, Frank

2010-09-28

Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

Polymorphisms in inflammation pathway genes and endometrial cancer risk

Science.gov (United States)

Delahanty, Ryan J.; Xiang, Yong-Bing; Spurdle, Amanda; Beeghly-Fadiel, Alicia; Long, Jirong; Thompson, Deborah; Tomlinson, Ian; Yu, Herbert; Lambrechts, Diether; Dörk, Thilo; Goodman, Marc T.; Zheng, Ying; Salvesen, Helga B.; Bao, Ping-Ping; Amant, Frederic; Beckmann, Matthias W.; Coenegrachts, Lieve; Coosemans, An; Dubrowinskaja, Natalia; Dunning, Alison; Runnebaum, Ingo B.; Easton, Douglas; Ekici, Arif B.; Fasching, Peter A.; Halle, Mari K.; Hein, Alexander; Howarth, Kimberly; Gorman, Maggie; Kaydarova, Dylyara; Krakstad, Camilla; Lose, Felicity; Lu, Lingeng; Lurie, Galina; O’Mara, Tracy; Matsuno, Rayna K.; Pharoah, Paul; Risch, Harvey; Corssen, Madeleine; Trovik, Jone; Turmanov, Nurzhan; Wen, Wanqing; Lu, Wei; Cai, Qiuyin; Zheng, Wei; Shu, Xiao-Ou

2013-01-01

Background Experimental and epidemiological evidence have suggested that chronic inflammation may play a critical role in endometrial carcinogenesis. Methods To investigate this hypothesis, a two-stage study was carried out to evaluate single nucleotide polymorphisms (SNPs) in inflammatory pathway genes in association with endometrial cancer risk. In stage 1, 64 candidate pathway genes were identified and 4,542 directly genotyped or imputed SNPs were analyzed among 832 endometrial cancer cases and 2,049 controls, using data from the Shanghai Endometrial Cancer Genetics Study. Linkage disequilibrium of stage 1 SNPs significantly associated with endometrial cancer (PAsian- and European-ancestry samples. Conclusions These findings lend support to the hypothesis that genetic polymorphisms in genes involved in the inflammatory pathway may contribute to genetic susceptibility to endometrial cancer. Impact Statement This study adds to the growing evidence that inflammation plays an important role in endometrial carcinogenesis. PMID:23221126

Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

Science.gov (United States)

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

2017-01-01

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

Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

International Nuclear Information System (INIS)

Thomassen, Mads; Tan, Qihua; Kruse, Torben A

2008-01-01

Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may

Screening key candidate genes and pathways involved in insulinoma by microarray analysis.

Science.gov (United States)

Zhou, Wuhua; Gong, Li; Li, Xuefeng; Wan, Yunyan; Wang, Xiangfei; Li, Huili; Jiang, Bin

2018-06-01

Insulinoma is a rare type tumor and its genetic features remain largely unknown. This study aimed to search for potential key genes and relevant enriched pathways of insulinoma.The gene expression data from GSE73338 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified between insulinoma tissues and normal pancreas tissues, followed by pathway enrichment analysis, protein-protein interaction (PPI) network construction, and module analysis. The expressions of candidate key genes were validated by quantitative real-time polymerase chain reaction (RT-PCR) in insulinoma tissues.A total of 1632 DEGs were obtained, including 1117 upregulated genes and 514 downregulated genes. Pathway enrichment results showed that upregulated DEGs were significantly implicated in insulin secretion, and downregulated DEGs were mainly enriched in pancreatic secretion. PPI network analysis revealed 7 hub genes with degrees more than 10, including GCG (glucagon), GCGR (glucagon receptor), PLCB1 (phospholipase C, beta 1), CASR (calcium sensing receptor), F2R (coagulation factor II thrombin receptor), GRM1 (glutamate metabotropic receptor 1), and GRM5 (glutamate metabotropic receptor 5). DEGs involved in the significant modules were enriched in calcium signaling pathway, protein ubiquitination, and platelet degranulation. Quantitative RT-PCR data confirmed that the expression trends of these hub genes were similar to the results of bioinformatic analysis.The present study demonstrated that candidate DEGs and enriched pathways were the potential critical molecule events involved in the development of insulinoma, and these findings were useful for better understanding of insulinoma genesis.

Identification of differentially expressed genes and biological pathways in bladder cancer

Science.gov (United States)

Tang, Fucai; He, Zhaohui; Lei, Hanqi; Chen, Yuehan; Lu, Zechao; Zeng, Guohua; Wang, Hangtao

2018-01-01

The purpose of the present study was to identify key genes and investigate the related molecular mechanisms of bladder cancer (BC) progression. From the Gene Expression Omnibus database, the gene expression dataset GSE7476 was downloaded, which contained 43 BC samples and 12 normal bladder tissues. GSE7476 was analyzed to screen the differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for the DEGs using the DAVID database, and a protein-protein interaction (PPI) network was then constructed using Cytoscape software. The results of the GO analysis showed that the upregulated DEGs were significantly enriched in cell division, nucleoplasm and protein binding, while the downregulated DEGs were significantly enriched in ‘extracellular matrix organization’, ‘proteinaceous extracellular matrix’ and ‘heparin binding’. The results of the KEGG pathway analysis showed that the upregulated DEGs were significantly enriched in the ‘cell cycle’, whereas the downregulated DEGs were significantly enriched in ‘complement and coagulation cascades’. JUN, cyclin-dependent kinase 1, FOS, PCNA, TOP2A, CCND1 and CDH1 were found to be hub genes in the PPI network. Sub-networks revealed that these gene were enriched in significant pathways, including the ‘cell cycle’ signaling pathway and ‘PI3K-Akt signaling pathway’. In summary, the present study identified DEGs and key target genes in the progression of BC, providing potential molecular targets and diagnostic biomarkers for the treatment of BC. PMID:29532898

Gene networks and toxicity pathways induced by acute cadmium exposure in adult largemouth bass (Micropterus salmoides)

International Nuclear Information System (INIS)

Mehinto, Alvine C.; Prucha, Melinda S.; Colli-Dula, Reyna C.; Kroll, Kevin J.; Lavelle, Candice M.; Barber, David S.; Vulpe, Christopher D.; Denslow, Nancy D.

2014-01-01

Highlights: • Low-level acute cadmium exposure elicited tissue-specific gene expression changes. • Molecular initiating events included oxidative stress and disruption of DNA repair. • Metallothionein, a marker of metal exposure, was not significantly affected. • We report effects of cadmium on cholesterol metabolism and steroid synthesis. • Diabetic complications and impaired reproduction are potential adverse outcomes. - Abstract: Cadmium is a heavy metal that can accumulate to toxic levels in the environment leading to detrimental effects in animals and humans including kidney, liver and lung injuries. Using a transcriptomics approach, genes and cellular pathways affected by a low dose of cadmium were investigated. Adult largemouth bass were intraperitoneally injected with 20 μg/kg of cadmium chloride (mean exposure level – 2.6 μg of cadmium per fish) and microarray analyses were conducted in the liver and testis 48 h after injection. Transcriptomic profiles identified in response to cadmium exposure were tissue-specific with the most differential expression changes found in the liver tissues, which also contained much higher levels of cadmium than the testis. Acute exposure to a low dose of cadmium induced oxidative stress response and oxidative damage pathways in the liver. The mRNA levels of antioxidants such as catalase increased and numerous transcripts related to DNA damage and DNA repair were significantly altered. Hepatic mRNA levels of metallothionein, a molecular marker of metal exposure, did not increase significantly after 48 h exposure. Carbohydrate metabolic pathways were also disrupted with hepatic transcripts such as UDP-glucose, pyrophosphorylase 2, and sorbitol dehydrogenase highly induced. Both tissues exhibited a disruption of steroid signaling pathways. In the testis, estrogen receptor beta and transcripts linked to cholesterol metabolism were suppressed. On the contrary, genes involved in cholesterol metabolism were highly

Gene networks and toxicity pathways induced by acute cadmium exposure in adult largemouth bass (Micropterus salmoides)

Energy Technology Data Exchange (ETDEWEB)

Mehinto, Alvine C., E-mail: alvinam@sccwrp.org [Southern California Coastal Water Research Project, Costa Mesa, CA 92626 (United States); Department of Physiological Sciences and Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL 32611 (United States); Prucha, Melinda S. [Department of Human Genetics, Yerkes National Primate Research Center, Emory University, Atlanta, GA 30322 (United States); Department of Physiological Sciences and Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL 32611 (United States); Colli-Dula, Reyna C.; Kroll, Kevin J.; Lavelle, Candice M.; Barber, David S. [Department of Physiological Sciences and Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL 32611 (United States); Vulpe, Christopher D. [Department of Nutritional Sciences and Toxicology, University of California, Berkeley, CA 94720 (United States); Denslow, Nancy D. [Department of Physiological Sciences and Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL 32611 (United States)

2014-07-01

Highlights: • Low-level acute cadmium exposure elicited tissue-specific gene expression changes. • Molecular initiating events included oxidative stress and disruption of DNA repair. • Metallothionein, a marker of metal exposure, was not significantly affected. • We report effects of cadmium on cholesterol metabolism and steroid synthesis. • Diabetic complications and impaired reproduction are potential adverse outcomes. - Abstract: Cadmium is a heavy metal that can accumulate to toxic levels in the environment leading to detrimental effects in animals and humans including kidney, liver and lung injuries. Using a transcriptomics approach, genes and cellular pathways affected by a low dose of cadmium were investigated. Adult largemouth bass were intraperitoneally injected with 20 μg/kg of cadmium chloride (mean exposure level – 2.6 μg of cadmium per fish) and microarray analyses were conducted in the liver and testis 48 h after injection. Transcriptomic profiles identified in response to cadmium exposure were tissue-specific with the most differential expression changes found in the liver tissues, which also contained much higher levels of cadmium than the testis. Acute exposure to a low dose of cadmium induced oxidative stress response and oxidative damage pathways in the liver. The mRNA levels of antioxidants such as catalase increased and numerous transcripts related to DNA damage and DNA repair were significantly altered. Hepatic mRNA levels of metallothionein, a molecular marker of metal exposure, did not increase significantly after 48 h exposure. Carbohydrate metabolic pathways were also disrupted with hepatic transcripts such as UDP-glucose, pyrophosphorylase 2, and sorbitol dehydrogenase highly induced. Both tissues exhibited a disruption of steroid signaling pathways. In the testis, estrogen receptor beta and transcripts linked to cholesterol metabolism were suppressed. On the contrary, genes involved in cholesterol metabolism were highly

Rapid male-specific regulatory divergence and down regulation of spermatogenesis genes in Drosophila species hybrids.

Directory of Open Access Journals (Sweden)

Jennifer Ferguson

Full Text Available In most crosses between closely related species of Drosophila, the male hybrids are sterile and show postmeiotic abnormalities. A series of gene expression studies using genomic approaches have found significant down regulation of postmeiotic spermatogenesis genes in sterile male hybrids. These results have led some to suggest a direct relationship between down regulation in gene expression and hybrid sterility. An alternative explanation to a cause-and-effect relationship between misregulation of gene expression and male sterility is rapid divergence of male sex regulatory elements leading to incompatible interactions in an interspecies hybrid genome. To test the effect of regulatory divergence in spermatogenesis gene expression, we isolated 35 fertile D. simulans strains with D. mauritiana introgressions in either the X, second or third chromosome. We analyzed gene expression in these fertile hybrid strains for a subset of spermatogenesis genes previously reported as significantly under expressed in sterile hybrids relative to D. simulans. We found that fertile autosomal introgressions can cause levels of gene down regulation similar to that of sterile hybrids. We also found that X chromosome heterospecific introgressions cause significantly less gene down regulation than autosomal introgressions. Our results provide evidence that rapid male sex gene regulatory divergence can explain misexpression of spermatogenesis genes in hybrids.

Small RNA-Controlled Gene Regulatory Networks in Pseudomonas putida

DEFF Research Database (Denmark)

Bojanovic, Klara

evolved numerous mechanisms to controlgene expression in response to specific environmental signals. In addition to two-component systems, small regulatory RNAs (sRNAs) have emerged as major regulators of gene expression. The majority of sRNAs bind to mRNA and regulate their expression. They often have...... multiple targets and are incorporated into large regulatory networks and the RNA chaper one Hfq in many cases facilitates interactions between sRNAs and their targets. Some sRNAs also act by binding to protein targets and sequestering their function. In this PhD thesis we investigated the transcriptional....... Detailed insights into the mechanisms through which P. putida responds to different stress conditions and increased understanding of bacterial adaptation in natural and industrial settings were gained. Additionally, we identified genome-wide transcription start sites, andmany regulatory RNA elements...

Inference of Transcription Regulatory Network in Low Phytic Acid Soybean Seeds

Directory of Open Access Journals (Sweden)

Neelam Redekar

2017-11-01

Full Text Available A dominant loss of function mutation in myo-inositol phosphate synthase (MIPS gene and recessive loss of function mutations in two multidrug resistant protein type-ABC transporter genes not only reduce the seed phytic acid levels in soybean, but also affect the pathways associated with seed development, ultimately resulting in low emergence. To understand the regulatory mechanisms and identify key genes that intervene in the seed development process in low phytic acid crops, we performed computational inference of gene regulatory networks in low and normal phytic acid soybeans using a time course transcriptomic data and multiple network inference algorithms. We identified a set of putative candidate transcription factors and their regulatory interactions with genes that have functions in myo-inositol biosynthesis, auxin-ABA signaling, and seed dormancy. We evaluated the performance of our unsupervised network inference method by comparing the predicted regulatory network with published regulatory interactions in Arabidopsis. Some contrasting regulatory interactions were observed in low phytic acid mutants compared to non-mutant lines. These findings provide important hypotheses on expression regulation of myo-inositol metabolism and phytohormone signaling in developing low phytic acid soybeans. The computational pipeline used for unsupervised network learning in this study is provided as open source software and is freely available at https://lilabatvt.github.io/LPANetwork/.

Regulation of FA and TAG biosynthesis pathway genes in endosperms and embryos of high and low oil content genotypes of Jatropha curcas L.

Science.gov (United States)

Sood, Archit; Chauhan, Rajinder Singh

2015-09-01

The rising demand for biofuels has raised concerns about selecting alternate and promising renewable energy crops which do not compete with food supply. Jatropha (Jatropha curcas L.), a non-edible energy crop of the family euphorbiaceae, has the potential of providing biodiesel feedstock due to the presence of high proportion of unsaturated fatty acids (75%) in seed oil which is mainly accumulated in endosperm and embryo. The molecular basis of seed oil biosynthesis machinery has been studied in J. curcas, however, what genetic differences contribute to differential oil biosynthesis and accumulation in genotypes varying for oil content is poorly understood. We investigated expression profile of 18 FA and TAG biosynthetic pathway genes in different developmental stages of embryo and endosperm from high (42%) and low (30%) oil content genotypes grown at two geographical locations. Most of the genes showed relatively higher expression in endosperms of high oil content genotype, whereas no significant difference was observed in endosperms versus embryos of low oil content genotype. The promoter regions of key genes from FA and TAG biosynthetic pathways as well as other genes implicated in oil accumulation were analyzed for regulatory elements and transcription factors specific to oil or lipid accumulation in plants such as Dof, CBF (LEC1), SORLIP, GATA and Skn-1_motif etc. Identification of key genes from oil biosynthesis and regulatory elements specific to oil deposition will be useful not only in dissecting the molecular basis of high oil content but also improving seed oil content through transgenic or molecular breeding approaches. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer's Disease Diagnosis.

Science.gov (United States)

Voyle, Nicola; Keohane, Aoife; Newhouse, Stephen; Lunnon, Katie; Johnston, Caroline; Soininen, Hilkka; Kloszewska, Iwona; Mecocci, Patrizia; Tsolaki, Magda; Vellas, Bruno; Lovestone, Simon; Hodges, Angela; Kiddle, Steven; Dobson, Richard Jb

2016-01-01

Recent studies indicate that gene expression levels in blood may be able to differentiate subjects with Alzheimer's disease (AD) from normal elderly controls and mild cognitively impaired (MCI) subjects. However, there is limited replicability at the single marker level. A pathway-based interpretation of gene expression may prove more robust. This study aimed to investigate whether a case/control classification model built on pathway level data was more robust than a gene level model and may consequently perform better in test data. The study used two batches of gene expression data from the AddNeuroMed (ANM) and Dementia Case Registry (DCR) cohorts. Our study used Illumina Human HT-12 Expression BeadChips to collect gene expression from blood samples. Random forest modeling with recursive feature elimination was used to predict case/control status. Age and APOE ɛ4 status were used as covariates for all analysis. Gene and pathway level models performed similarly to each other and to a model based on demographic information only. Any potential increase in concordance from the novel pathway level approach used here has not lead to a greater predictive ability in these datasets. However, we have only tested one method for creating pathway level scores. Further, we have been able to benchmark pathways against genes in datasets that had been extensively harmonized. Further work should focus on the use of alternative methods for creating pathway level scores, in particular those that incorporate pathway topology, and the use of an endophenotype based approach.

An ensemble method to predict target genes and pathways in uveal melanoma

Directory of Open Access Journals (Sweden)

Wei Chao

2018-04-01

Full Text Available This work proposes to predict target genes and pathways for uveal melanoma (UM based on an ensemble method and pathway analyses. Methods: The ensemble method integrated a correlation method (Pearson correlation coefficient, PCC, a causal inference method (IDA and a regression method (Lasso utilizing the Borda count election method. Subsequently, to validate the performance of PIL method, comparisons between confirmed database and predicted miRNA targets were performed. Ultimately, pathway enrichment analysis was conducted on target genes in top 1000 miRNA-mRNA interactions to identify target pathways for UM patients. Results: Thirty eight of the predicted interactions were matched with the confirmed interactions, indicating that the ensemble method was a suitable and feasible approach to predict miRNA targets. We obtained 50 seed miRNA-mRNA interactions of UM patients and extracted target genes from these interactions, such as ASPG, BSDC1 and C4BP. The 601 target genes in top 1,000 miRNA-mRNA interactions were enriched in 12 target pathways, of which Phototransduction was the most significant one. Conclusion: The target genes and pathways might provide a new way to reveal the molecular mechanism of UM and give hand for target treatments and preventions of this malignant tumor.

Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

Science.gov (United States)

Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

2014-12-01

Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

Two potential hookworm DAF-16 target genes, SNR-3 and LPP-1: gene structure, expression profile, and implications of a cis-regulatory element in the regulation of gene expression.

Science.gov (United States)

Gao, Xin; Goggin, Kevin; Dowling, Camille; Qian, Jason; Hawdon, John M

2015-01-08

Hookworms infect nearly 700 million people, causing anemia and developmental stunting in heavy infections. Little is known about the genomic structure or gene regulation in hookworms, although recent publication of draft genome assemblies has allowed the first investigations of these topics to be undertaken. The transcription factor DAF-16 mediates multiple developmental pathways in the free living nematode Caenorhabditis elegans, and is involved in the recovery from the developmentally arrested L3 in hookworms. Identification of downstream targets of DAF-16 will provide a better understanding of the molecular mechanism of hookworm infection. Genomic Fragment 2.23 containing a DAF-16 binding element (DBE) was used to identify overlapping complementary expressed sequence tags (ESTs). These sequences were used to search a draft assembly of the Ancylostoma caninum genome, and identified two neighboring genes, snr-3 and lpp-1, in a tail-to-tail orientation. Expression patterns of both genes during parasitic development were determined by qRT-PCR. DAF-16 dependent cis-regulatory activity of fragment 2.23 was investigated using an in vitro reporter system. The snr-3 gene spans approximately 5.6 kb in the genome and contains 3 exons and 2 introns, and contains the DBE in its 3' untranslated region. Downstream from snr-3 in a tail-to-tail arrangement is the gene lpp-1. The lpp-1 gene spans more than 6 kb and contains 10 exons and 9 introns. The A. caninum genome contains 2 apparent splice variants, but there are 7 splice variants in the A. ceylanicum genome. While the gene order is similar, the gene structures of the hookworm genes differ from their C. elegans orthologs. Both genes show peak expression in the late L4 stage. Using a cell culture based expression system, fragment 2.23 was found to have both DAF-16-dependent promoter and enhancer activity that required an intact DBE. Two putative DAF-16 targets were identified by genome wide screening for DAF-16 binding

Gene mdpC plays a regulatory role in the methyl-tert-butyl ether degradation pathway of Methylibium petroleiphilum strain PM1.

Science.gov (United States)

Joshi, Geetika; Schmidt, Radomir; Scow, Kate M; Denison, Michael S; Hristova, Krassimira R

2015-04-01

Among the few bacteria known to utilize methyl tert-butyl ether (MTBE) as a sole carbon source, Methylibium petroleiphilum PM1 is a well-characterized organism with a sequenced genome; however, knowledge of the genetic regulation of its MTBE degradation pathway is limited. We investigated the role of a putative transcriptional activator gene, mdpC, in the induction of MTBE-degradation genes mdpA (encoding MTBE monooxygenase) and mdpJ (encoding tert-butyl alcohol hydroxylase) of strain PM1 in a gene-knockout mutant mdpC(-). We also utilized quantitative reverse transcriptase PCR assays targeting genes mdpA, mdpJ and mdpC to determine the effects of the mutation on transcription of these genes. Our results indicate that gene mdpC is involved in the induction of both mdpA and mdpJ in response to MTBE and tert-butyl alcohol (TBA) exposure in PM1. An additional independent mechanism may be involved in the induction of mdpJ in the presence of TBA. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evolutionary Rate Heterogeneity of Primary and Secondary Metabolic Pathway Genes in Arabidopsis thaliana.

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Mukherjee, Dola; Mukherjee, Ashutosh; Ghosh, Tapash Chandra

2015-11-10

Primary metabolism is essential to plants for growth and development, and secondary metabolism helps plants to interact with the environment. Many plant metabolites are industrially important. These metabolites are produced by plants through complex metabolic pathways. Lack of knowledge about these pathways is hindering the successful breeding practices for these metabolites. For a better knowledge of the metabolism in plants as a whole, evolutionary rate variation of primary and secondary metabolic pathway genes is a prerequisite. In this study, evolutionary rate variation of primary and secondary metabolic pathway genes has been analyzed in the model plant Arabidopsis thaliana. Primary metabolic pathway genes were found to be more conserved than secondary metabolic pathway genes. Several factors such as gene structure, expression level, tissue specificity, multifunctionality, and domain number are the key factors behind this evolutionary rate variation. This study will help to better understand the evolutionary dynamics of plant metabolism. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies

Science.gov (United States)

2014-01-01

Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods. PMID:24708878

Transcriptome profiling reveals regulatory mechanisms underlying Corolla Senescence in Petunia

Science.gov (United States)

Genetic regulatory mechanisms that govern petal natural senescence in petunia is complicated and unclear. To identify key genes and pathways that regulate the process, we initiated a transcriptome analysis in petunia petals at four developmental time points, including petal opening without anthesis ...

Cloning and Expression Analysis of MEP Pathway Enzyme-encoding Genes in Osmanthus fragrans

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Chen Xu

2016-09-01

Full Text Available The 2-C-methyl-d-erythritol 4-phosphate (MEP pathway is responsible for the biosynthesis of many crucial secondary metabolites, such as carotenoids, monoterpenes, plastoquinone, and tocopherols. In this study, we isolated and identified 10 MEP pathway genes in the important aromatic plant sweet osmanthus (Osmanthus fragrans. Multiple sequence alignments revealed that 10 MEP pathway genes shared high identities with other reported proteins. The genes showed distinctive expression profiles in various tissues, or at different flower stages and diel time points. The qRT-PCR results demonstrated that these genes were highly expressed in inflorescences, which suggested a tissue-specific transcript pattern. Our results also showed that OfDXS1, OfDXS2, and OfHDR1 had a clear diurnal oscillation pattern. The isolation and expression analysis provides a strong foundation for further research on the MEP pathway involved in gene function and molecular evolution, and improves our understanding of the molecular mechanism underlying this pathway in plants.

The nomenclature of MHC class I gene regulatory regions - the case of two different downstream regulatory elements

Czech Academy of Sciences Publication Activity Database

Hatina, J.; Jansa, Petr; Forejt, Jiří

2001-01-01

Roč. 37, 12-13 (2001), s. 799-800 ISSN 0161-5890 Institutional research plan: CEZ:AV0Z5052915 Keywords : MHC I gene regulatory elements Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.973, year: 2001

miRTrail - a comprehensive webserver for analyzing gene and miRNA patterns to enhance the understanding of regulatory mechanisms in diseases

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Laczny Cedric

2012-02-01

Full Text Available Abstract Background Expression profiling provides new insights into regulatory and metabolic processes and in particular into pathogenic mechanisms associated with diseases. Besides genes, non-coding transcripts as microRNAs (miRNAs gained increasing relevance in the last decade. To understand the regulatory processes of miRNAs on genes, integrative computer-aided approaches are essential, especially in the light of complex human diseases as cancer. Results Here, we present miRTrail, an integrative tool that allows for performing comprehensive analyses of interactions of genes and miRNAs based on expression profiles. The integrated analysis of mRNA and miRNA data should generate more robust and reliable results on deregulated pathogenic processes and may also offer novel insights into the regulatory interactions between miRNAs and genes. Our web-server excels in carrying out gene sets analysis, analysis of miRNA sets as well as the combination of both in a systems biology approach. To this end, miRTrail integrates information on 20.000 genes, almost 1.000 miRNAs, and roughly 280.000 putative interactions, for Homo sapiens and accordingly for Mus musculus and Danio rerio. The well-established, classical Chi-squared test is one of the central techniques of our tool for the joint consideration of miRNAs and their targets. For interactively visualizing obtained results, it relies on the network analyzers and viewers BiNA or Cytoscape-web, also enabling direct access to relevant literature. We demonstrated the potential of miRTrail by applying our tool to mRNA and miRNA data of malignant melanoma. MiRTrail identified several deregulated miRNAs that target deregulated mRNAs including miRNAs hsa-miR-23b and hsa-miR-223, which target the highest numbers of deregulated mRNAs and regulate the pathway "basal cell carcinoma". In addition, both miRNAs target genes like PTCH1 and RASA1 that are involved in many oncogenic processes. Conclusions The application

RNA interference screen to identify pathways that enhance or reduce nonviral gene transfer during lipofection.

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Barker, Gregory A; Diamond, Scott L

2008-09-01

Some barriers to DNA lipofection are well characterized; however, there is as yet no method of finding unknown pathways that impact the process. A druggable genome small-interfering RNA (siRNA) screen against 5,520 genes was tested for its effect on lipofection of human aortic endothelial cells (HAECs). We found 130 gene targets which, when silenced by pooled siRNAs (three siRNAs per gene), resulted in enhanced luminescence after lipofection (86 gene targets showed reduced expression). In confirmation tests with single siRNAs, 18 of the 130 hits showed enhanced lipofection with two or more individual siRNAs in the absence of cytotoxicity. Of these confirmed gene targets, we identified five leading candidates, two of which are isoforms of the regulatory subunit of protein phosphatase 2A (PP2A). The best candidate siRNA targeted the PPP2R2C gene and produced a 65% increase in luminescence from lipofection, with a quantitative PCR-validated knockdown of approximately 76%. Flow cytometric analysis confirmed that the silencing of the PPP2R2C gene resulted in an improvement of 10% in transfection efficiency, thereby demonstrating an increase in the number of transfected cells. These results show that an RNA interference (RNAi) high-throughput screen (HTS) can be applied to nonviral gene transfer. We have also demonstrated that siRNAs can be co-delivered with lipofected DNA to increase the transfection efficiency in vitro.

Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes.

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Biankin, Andrew V; Waddell, Nicola; Kassahn, Karin S; Gingras, Marie-Claude; Muthuswamy, Lakshmi B; Johns, Amber L; Miller, David K; Wilson, Peter J; Patch, Ann-Marie; Wu, Jianmin; Chang, David K; Cowley, Mark J; Gardiner, Brooke B; Song, Sarah; Harliwong, Ivon; Idrisoglu, Senel; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Wani, Shivangi; Gongora, Milena; Pajic, Marina; Scarlett, Christopher J; Gill, Anthony J; Pinho, Andreia V; Rooman, Ilse; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Nones, Katia; Fink, J Lynn; Christ, Angelika; Bruxner, Tim; Cloonan, Nicole; Kolle, Gabriel; Newell, Felicity; Pinese, Mark; Mead, R Scott; Humphris, Jeremy L; Kaplan, Warren; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chou, Angela; Chin, Venessa T; Chantrill, Lorraine A; Mawson, Amanda; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Daly, Roger J; Merrett, Neil D; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Kakkar, Nipun; Zhao, Fengmei; Wu, Yuan Qing; Wang, Min; Muzny, Donna M; Fisher, William E; Brunicardi, F Charles; Hodges, Sally E; Reid, Jeffrey G; Drummond, Jennifer; Chang, Kyle; Han, Yi; Lewis, Lora R; Dinh, Huyen; Buhay, Christian J; Beck, Timothy; Timms, Lee; Sam, Michelle; Begley, Kimberly; Brown, Andrew; Pai, Deepa; Panchal, Ami; Buchner, Nicholas; De Borja, Richard; Denroche, Robert E; Yung, Christina K; Serra, Stefano; Onetto, Nicole; Mukhopadhyay, Debabrata; Tsao, Ming-Sound; Shaw, Patricia A; Petersen, Gloria M; Gallinger, Steven; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Schulick, Richard D; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Capelli, Paola; Corbo, Vincenzo; Scardoni, Maria; Tortora, Giampaolo; Tempero, Margaret A; Mann, Karen M; Jenkins, Nancy A; Perez-Mancera, Pedro A; Adams, David J; Largaespada, David A; Wessels, Lodewyk F A; Rust, Alistair G; Stein, Lincoln D; Tuveson, David A; Copeland, Neal G; Musgrove, Elizabeth A; Scarpa, Aldo; Eshleman, James R; Hudson, Thomas J; Sutherland, Robert L; Wheeler, David A; Pearson, John V; McPherson, John D; Gibbs, Richard A; Grimmond, Sean M

2012-11-15

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

A Meta-Analysis of Multiple Matched Copy Number and Transcriptomics Data Sets for Inferring Gene Regulatory Relationships

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Newton, Richard; Wernisch, Lorenz

2014-01-01

Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments. PMID:25148247

Induction of cytoprotective pathways is central to the extension of lifespan conferred by multiple longevity pathways.

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David E Shore

Full Text Available Many genetic and physiological treatments that extend lifespan also confer resistance to a variety of stressors, suggesting that cytoprotective mechanisms underpin the regulation of longevity. It has not been established, however, whether the induction of cytoprotective pathways is essential for lifespan extension or merely correlated. Using a panel of GFP-fused stress response genes, we identified the suites of cytoprotective pathways upregulated by 160 gene inactivations known to increase Caenorhabditis elegans longevity, including the mitochondrial UPR (hsp-6, hsp-60, the ER UPR (hsp-4, ROS response (sod-3, gst-4, and xenobiotic detoxification (gst-4. We then screened for other gene inactivations that disrupt the induction of these responses by xenobiotic or genetic triggers, identifying 29 gene inactivations required for cytoprotective gene expression. If cytoprotective responses contribute directly to lifespan extension, inactivation of these genes would be expected to compromise the extension of lifespan conferred by decreased insulin/IGF-1 signaling, caloric restriction, or the inhibition of mitochondrial function. We find that inactivation of 25 of 29 cytoprotection-regulatory genes shortens the extension of longevity normally induced by decreased insulin/IGF-1 signaling, disruption of mitochondrial function, or caloric restriction, without disrupting normal longevity nearly as dramatically. These data demonstrate that induction of cytoprotective pathways is central to longevity extension and identify a large set of new genetic components of the pathways that detect cellular damage and couple that detection to downstream cytoprotective effectors.

Whole-genome transcription and DNA methylation analysis of peripheral blood mononuclear cells identified aberrant gene regulation pathways in systemic lupus erythematosus.

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Zhu, Honglin; Mi, Wentao; Luo, Hui; Chen, Tao; Liu, Shengxi; Raman, Indu; Zuo, Xiaoxia; Li, Quan-Zhen

2016-07-13

Recent achievement in genetics and epigenetics has led to the exploration of the pathogenesis of systemic lupus erythematosus (SLE). Identification of differentially expressed genes and their regulatory mechanism(s) at whole-genome level will provide a comprehensive understanding of the development of SLE and its devastating complications, lupus nephritis (LN). We performed whole-genome transcription and DNA methylation analysis in PBMC of 30 SLE patients, including 15 with LN (SLE LN(+)) and 15 without LN (SLE LN(-)), and 25 normal controls (NC) using HumanHT-12 Beadchips and Illumina Human Methy450 chips. The serum proinflammatory cytokines were quantified using Bio-plex Human Cytokine 27-plex assay. Differentially expressed genes and differentially methylated CpG were analyzed with GenomeStudio, R, and SAM software. The association between DNA methylation and gene expression were tested. Gene interaction pathways of the differentially expressed genes were analyzed by IPA software. We identified 552 upregulated genes and 550 downregulated genes in PBMC of SLE. Integration of DNA methylation and gene expression profiling showed that 334 upregulated genes were hypomethylated, and 479 downregulated genes were hypermethylated. Pathway analysis on the differential genes in SLE revealed significant enrichment in interferon (IFN) signaling and toll-like receptor (TLR) signaling pathways. Nine IFN- and seven TLR-related genes were identified and displayed step-wise increase in SLE LN(-) and SLE LN(+). Hypomethylated CpG sites were detected on these genes. The gene expressions for MX1, GPR84, and E2F2 were increased in SLE LN(+) as compared to SLE LN(-) patients. The serum levels of inflammatory cytokines, including IL17A, IP-10, bFGF, TNF-α, IL-6, IL-15, GM-CSF, IL-1RA, IL-5, and IL-12p70, were significantly elevated in SLE compared with NC. The levels of IL-15 and IL1RA correlated with their mRNA expression. The upregulation of IL-15 may be regulated by hypomethylated

Construction of an integrated gene regulatory network link to stress-related immune system in cattle.

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Behdani, Elham; Bakhtiarizadeh, Mohammad Reza

2017-10-01

The immune system is an important biological system that is negatively impacted by stress. This study constructed an integrated regulatory network to enhance our understanding of the regulatory gene network used in the stress-related immune system. Module inference was used to construct modules of co-expressed genes with bovine leukocyte RNA-Seq data. Transcription factors (TFs) were then assigned to these modules using Lemon-Tree algorithms. In addition, the TFs assigned to each module were confirmed using the promoter analysis and protein-protein interactions data. Therefore, our integrated method identified three TFs which include one TF that is previously known to be involved in immune response (MYBL2) and two TFs (E2F8 and FOXS1) that had not been recognized previously and were identified for the first time in this study as novel regulatory candidates in immune response. This study provides valuable insights on the regulatory programs of genes involved in the stress-related immune system.

On the dynamics of a gene regulatory network

International Nuclear Information System (INIS)

Grammaticos, B; Carstea, A S; Ramani, A

2006-01-01

We examine the dynamics of a network of genes focusing on a periodic chain of genes, of arbitrary length. We show that within a given class of sigmoids representing the equilibrium probability of the binding of the RNA polymerase to the core promoter, the system possesses a single stable fixed point. By slightly modifying the sigmoid, introducing 'stiffer' forms, we show that it is possible to find network configurations exhibiting bistable behaviour. Our results do not depend crucially on the length of the chain considered: calculations with finite chains lead to similar results. However, a realistic study of regulatory genetic networks would require the consideration of more complex topologies and interactions

Nitrogen modulation of legume root architecture signalling pathways involves phytohormones and small regulatory molecules

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Nadiatul Akmal Mohd-Radzman

2013-10-01

Full Text Available Nitrogen, particularly nitrate is an important yield determinant for crops. However, current agricultural practice with excessive fertilizer usage has detrimental effects on the environment. Therefore, legumes have been suggested as a sustainable alternative for replenishing soil nitrogen. Legumes can uniquely form nitrogen-fixing nodules through symbiotic interaction with specialized soil bacteria. Legumes possess a highly plastic root system which modulates its architecture according to the nitrogen availability in the soil. Understanding how legumes regulate root development in response to nitrogen availability is an important step to improving root architecture. The nitrogen-mediated root development pathway starts with sensing soil nitrogen level followed by subsequent signal transduction pathways involving phytohormones, microRNAs and regulatory peptides that collectively modulate the growth and shape of the root system. This review focuses on the current understanding of nitrogen-mediated legume root architecture including local and systemic regulations by different N-sources and the modulations by phytohormones and small regulatory molecules.

Nitrogen modulation of legume root architecture signaling pathways involves phytohormones and small regulatory molecules.

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Mohd-Radzman, Nadiatul A; Djordjevic, Michael A; Imin, Nijat

2013-10-01

Nitrogen, particularly nitrate is an important yield determinant for crops. However, current agricultural practice with excessive fertilizer usage has detrimental effects on the environment. Therefore, legumes have been suggested as a sustainable alternative for replenishing soil nitrogen. Legumes can uniquely form nitrogen-fixing nodules through symbiotic interaction with specialized soil bacteria. Legumes possess a highly plastic root system which modulates its architecture according to the nitrogen availability in the soil. Understanding how legumes regulate root development in response to nitrogen availability is an important step to improving root architecture. The nitrogen-mediated root development pathway starts with sensing soil nitrogen level followed by subsequent signal transduction pathways involving phytohormones, microRNAs and regulatory peptides that collectively modulate the growth and shape of the root system. This review focuses on the current understanding of nitrogen-mediated legume root architecture including local and systemic regulations by different N-sources and the modulations by phytohormones and small regulatory molecules.

Statistical identification of gene association by CID in application of constructing ER regulatory network

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Lien Huang-Chun

2009-03-01

Full Text Available Abstract Background A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID, is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs (X and their downstream genes (Y based on clinical data. More specifically, we use estrogen receptor α (ERα as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A. Results The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC, Student's t-test (STT, coefficient of determination (CoD, and mutual information (MI. When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y against a discrete variable (X, it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays. Conclusion CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the

Deciphering RNA Regulatory Elements Involved in the Developmental and Environmental Gene Regulation of Trypanosoma brucei.

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Gazestani, Vahid H; Salavati, Reza

2015-01-01

Trypanosoma brucei is a vector-borne parasite with intricate life cycle that can cause serious diseases in humans and animals. This pathogen relies on fine regulation of gene expression to respond and adapt to variable environments, with implications in transmission and infectivity. However, the involved regulatory elements and their mechanisms of actions are largely unknown. Here, benefiting from a new graph-based approach for finding functional regulatory elements in RNA (GRAFFER), we have predicted 88 new RNA regulatory elements that are potentially involved in the gene regulatory network of T. brucei. We show that many of these newly predicted elements are responsive to both transcriptomic and proteomic changes during the life cycle of the parasite. Moreover, we found that 11 of predicted elements strikingly resemble previously identified regulatory elements for the parasite. Additionally, comparison with previously predicted motifs on T. brucei suggested the superior performance of our approach based on the current limited knowledge of regulatory elements in T. brucei.

Characterization of differentially expressed genes involved in pathways associated with gastric cancer.

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Hao Li

Full Text Available To explore the patterns of gene expression in gastric cancer, a total of 26 paired gastric cancer and noncancerous tissues from patients were enrolled for gene expression microarray analyses. Limma methods were applied to analyze the data, and genes were considered to be significantly differentially expressed if the False Discovery Rate (FDR value was 2. Subsequently, Gene Ontology (GO categories were used to analyze the main functions of the differentially expressed genes. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG database, we found pathways significantly associated with the differential genes. Gene-Act network and co-expression network were built respectively based on the relationships among the genes, proteins and compounds in the database. 2371 mRNAs and 350 lncRNAs considered as significantly differentially expressed genes were selected for the further analysis. The GO categories, pathway analyses and the Gene-Act network showed a consistent result that up-regulated genes were responsible for tumorigenesis, migration, angiogenesis and microenvironment formation, while down-regulated genes were involved in metabolism. These results of this study provide some novel findings on coding RNAs, lncRNAs, pathways and the co-expression network in gastric cancer which will be useful to guide further investigation and target therapy for this disease.

Syndromes associated with Homo sapiens pol II regulatory genes.

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Bina, M; Demmon, S; Pares-Matos, E I

2000-01-01

The molecular basis of human characteristics is an intriguing but an unresolved problem. Human characteristics cover a broad spectrum, from the obvious to the abstract. Obvious characteristics may include morphological features such as height, shape, and facial form. Abstract characteristics may be hidden in processes that are controlled by hormones and the human brain. In this review we examine exaggerated characteristics presented as syndromes. Specifically, we focus on human genes that encode transcription factors to examine morphological, immunological, and hormonal anomalies that result from deletion, insertion, or mutation of genes that regulate transcription by RNA polymerase II (the Pol II genes). A close analysis of abnormal phenotypes can give clues into how sequence variations in regulatory genes and changes in transcriptional control may give rise to characteristics defined as complex traits.

Examining the intersection between splicing, nuclear export and small RNA pathways.

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Nabih, Amena; Sobotka, Julia A; Wu, Monica Z; Wedeles, Christopher J; Claycomb, Julie M

2017-11-01

Nuclear Argonaute/small RNA pathways in a variety of eukaryotic species are generally known to regulate gene expression via chromatin modulation and transcription attenuation in a process known as transcriptional gene silencing (TGS). However, recent data, including genetic screens, phylogenetic profiling, and molecular mechanistic studies, also point to a novel and emerging intersection between the splicing and nuclear export machinery with nuclear Argonaute/small RNA pathways in many organisms. In this review, we summarize the field's current understanding regarding the relationship between splicing, export and small RNA pathways, and consider the biological implications for coordinated regulation of transcripts by these pathways. We also address the importance and available approaches for understanding the RNA regulatory logic generated by the intersection of these particular pathways in the context of synthetic biology. The interactions between various eukaryotic RNA regulatory pathways, particularly splicing, nuclear export and small RNA pathways provide a type of combinatorial code that informs the identity ("self" versus "non-self") and dictates the fate of each transcript in a cell. Although the molecular mechanisms for how splicing and nuclear export impact small RNA pathways are not entirely clear at this early stage, the links between these pathways are widespread across eukaryotic phyla. The link between splicing, nuclear export, and small RNA pathways is emerging and establishes a new frontier for understanding the combinatorial logic of gene regulation across species that could someday be harnessed for therapeutic, biotechnology and agricultural applications. This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue. Copyright © 2017 Elsevier B.V. All rights reserved.

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

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Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-06

Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

Regulation of signaling genes by TGFβ during entry into dauer diapause in C. elegans

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Patterson Garth I

2004-09-01

Full Text Available Abstract Background When resources are scant, C. elegans larvae arrest as long-lived dauers under the control of insulin/IGF- and TGFβ-related signaling pathways. However, critical questions remain regarding the regulation of this developmental event. How do three dozen insulin-like proteins regulate one tyrosine kinase receptor to control complex events in dauer, metabolism and aging? How are signals from the TGFβ and insulin/IGF pathways integrated? What gene expression programs do these pathways regulate, and how do they control complex downstream events? Results We have identified genes that show different levels of expression in a comparison of wild-type L2 or L3 larvae (non-dauer to TGFβ mutants at similar developmental stages undergoing dauer formation. Many insulin/IGF pathway and other known dauer regulatory genes have changes in expression that suggest strong positive feedback by the TGFβ pathway. In addition, many insulin-like ligand and novel genes with similarity to the extracellular domain of insulin/IGF receptors have altered expression. We have identified a large group of regulated genes with putative binding sites for the FOXO transcription factor, DAF-16. Genes with DAF-16 sites upstream of the transcription start site tend to be upregulated, whereas genes with DAF-16 sites downstream of the coding region tend to be downregulated. Finally, we also see strong regulation of many novel hedgehog- and patched-related genes, hormone biosynthetic genes, cell cycle genes, and other regulatory genes. Conclusions The feedback regulation of insulin/IGF pathway and other dauer genes that we observe would be predicted to amplify signals from the TGFβ pathway; this amplification may serve to ensure a decisive choice between "dauer" and "non-dauer", even if environmental cues are ambiguous. Up and down regulation of insulin-like ligands and novel genes with similarity to the extracellular domain of insulin/IGF receptors suggests opposing

An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

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Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

2018-05-14

A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives

Learning a Markov Logic network for supervised gene regulatory network inference.

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Brouard, Céline; Vrain, Christel; Dubois, Julie; Castel, David; Debily, Marie-Anne; d'Alché-Buc, Florence

2013-09-12

Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate "regulates", starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black-box model such as a

Signaling pathway-focused gene expression profiling in pressure overloaded hearts

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Marco Musumeci

2011-01-01

Full Text Available The β-blocker propranolol displays antihypertrophic and antifibrotic properties in the heart subjected to pressure overload. Yet the underlying mechanisms responsible for these important effects remain to be completely understood. The purpose of this study was to determine signaling pathway-focused gene expression profile associated with the antihypertrophic action of propranolol in pressure overloaded hearts. To address this question, a focused real-time PCR array was used to screen left ventricular RNA expression of 84 gene transcripts representative of 18 different signaling pathways in C57BL/6 mice subjected to transverse aortic constriction (TAC or sham surgery. On the surgery day, mice received either propranolol (80 mg/kg/day or vehicle for 14 days. TAC caused a 49% increase in the left ventricular weight-to-body weight (LVW/BW ratio without changing gene expression. Propranolol blunted LVW/BW ratio increase by approximately 50% while causing about a 3-fold increase in the expression of two genes, namely Brca1 and Cdkn2a, belonging to the TGF-beta and estrogen pathways, respectively. In conclusion, after 2 weeks of pressure overload, TAC hearts show a gene expression profile superimposable to that of sham hearts. Conversely, propranolol treatment is associated with an increased expression of genes which negatively regulate cell cycle progression. It remains to be established whether a mechanistic link between gene expression changes and the antihypertrophic action of propranolol occurs.

Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

OpenAIRE

Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

2009-01-01

Abstract Background Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori assumptions about the interactions, which all simulate the observed patterns. It is important to analyze the properties of the circuits. Findings We have analyzed the simulated gene expression ...

Activation of counter-regulatory mechanisms in a rat renal acute rejection model

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Salomon Daniel R

2008-02-01

Full Text Available Abstract Background Microarray analysis provides a powerful approach to identify gene expression alterations following transplantation. In patients the heterogeneity of graft specimens, co-morbidity, co-medications and the challenges in sample collection and preparation complicate conclusions regarding the underlying mechanisms of graft injury, rejection and immune regulation. Results We used a rat kidney transplantation model with strict transplant and sample preparation procedures to analyze genome wide changes in gene expression four days after syngeneic and allogeneic transplantation. Both interventions were associated with substantial changes in gene expression. After allogeneic transplantation, genes and pathways related to transport and metabolism were predominantly down-regulated consistent with rejection-mediated graft injury and dysfunction. Up-regulated genes were primarily related to the acute immune response including antigen presentation, T-cell receptor signaling, apoptosis, interferon signaling and complement cascades. We observed a cytokine and chemokine expression profile consistent with activation of a Th1-cell response. A novel finding was up-regulation of several regulatory and protective genes after allogeneic transplantation, specifically IL10, Bcl2a1, C4bpa, Ctla4, HO-1 and the SOCS family. Conclusion Our data indicate that in parallel with the predicted activation of immune response and tissue injury pathways, there is simultaneous activation of pathways for counter regulatory and protective mechanisms that would balance and limit the ongoing inflammatory/immune responses. The pathophysiological mechanisms behind and the clinical consequences of alterations in expression of these gene classes in acute rejection, injury and dysfunction vs. protection and immunoregulation, prompt further analyses and open new aspects for therapeutic approaches.

Conserved-peptide upstream open reading frames (CPuORFs are associated with regulatory genes in angiosperms

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Richard A Jorgensen

2012-08-01

Full Text Available Upstream open reading frames (uORFs are common in eukaryotic transcripts, but those that encode conserved peptides (CPuORFs occur in less than 1% of transcripts. The peptides encoded by three plant CPuORF families are known to control translation of the downstream ORF in response to a small signal molecule (sucrose, polyamines and phosphocholine. In flowering plants, transcription factors are statistically over-represented among genes that possess CPuORFs, and in general it appeared that many CPuORF genes also had other regulatory functions, though the significance of this suggestion was uncertain (Hayden and Jorgensen, 2007. Five years later the literature provides much more information on the functions of many CPuORF genes. Here we reassess the functions of 27 known CPuORF gene families and find that 22 of these families play a variety of different regulatory roles, from transcriptional control to protein turnover, and from small signal molecules to signal transduction kinases. Clearly then, there is indeed a strong association of CPuORFs with regulatory genes. In addition, 16 of these families play key roles in a variety of different biological processes. Most strikingly, the core sucrose response network includes three different CPuORFs, creating the potential for sophisticated balancing of the network in response to three different molecular inputs. We propose that the function of most CPuORFs is to modulate translation of a downstream major ORF (mORF in response to a signal molecule recognized by the conserved peptide and that because the mORFs of CPuORF genes generally encode regulatory proteins, many of them centrally important in the biology of plants, CPuORFs play key roles in balancing such regulatory networks.

minepath.org: a free interactive pathway analysis web server.

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Koumakis, Lefteris; Roussos, Panos; Potamias, George

2017-07-03

( www.minepath.org ) is a web-based platform that elaborates on, and radically extends the identification of differentially expressed sub-paths in molecular pathways. Besides the network topology, the underlying MinePath algorithmic processes exploit exact gene-gene molecular relationships (e.g. activation, inhibition) and are able to identify differentially expressed pathway parts. Each pathway is decomposed into all its constituent sub-paths, which in turn are matched with corresponding gene expression profiles. The highly ranked, and phenotype inclined sub-paths are kept. Apart from the pathway analysis algorithm, the fundamental innovation of the MinePath web-server concerns its advanced visualization and interactive capabilities. To our knowledge, this is the first pathway analysis server that introduces and offers visualization of the underlying and active pathway regulatory mechanisms instead of genes. Other features include live interaction, immediate visualization of functional sub-paths per phenotype and dynamic linked annotations for the engaged genes and molecular relations. The user can download not only the results but also the corresponding web viewer framework of the performed analysis. This feature provides the flexibility to immediately publish results without publishing source/expression data, and get all the functionality of a web based pathway analysis viewer. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

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Precious Takondwa Makondi

Full Text Available Acquired drug resistance to the chemotherapeutic drug irinotecan (the active metabolite of which is SN-38 is one of the significant obstacles in the treatment of advanced colorectal cancer (CRC. The molecular mechanism or targets mediating irinotecan resistance are still unclear. It is urgent to find the irinotecan response biomarkers to improve CRC patients' therapy.Genetic Omnibus Database GSE42387 which contained the gene expression profiles of parental and irinotecan-resistant HCT-116 cell lines was used. Differentially expressed genes (DEGs between parental and irinotecan-resistant cells, protein-protein interactions (PPIs, gene ontologies (GOs and pathway analysis were performed to identify the overall biological changes. The most common DEGs in the PPIs, GOs and pathways were identified and were validated clinically by their ability to predict overall survival and disease free survival. The gene-gene expression correlation and gene-resistance correlation was also evaluated in CRC patients using The Cancer Genomic Atlas data (TCGA.The 135 DEGs were identified of which 36 were upregulated and 99 were down regulated. After mapping the PPI networks, the GOs and the pathways, nine genes (GNAS, PRKACB, MECOM, PLA2G4C, BMP6, BDNF, DLG4, FGF2 and FGF9 were found to be commonly enriched. Signal transduction was the most significant GO and MAPK pathway was the most significant pathway. The five genes (FGF2, FGF9, PRKACB, MECOM and PLA2G4C in the MAPK pathway were all contained in the signal transduction and the levels of those genes were upregulated. The FGF2, FGF9 and MECOM expression were highly associated with CRC patients' survival rate but not PRKACB and PLA2G4C. In addition, FGF9 was also associated with irinotecan resistance and poor disease free survival. FGF2, FGF9 and PRKACB were positively correlated with each other while MECOM correlated positively with FGF9 and PLA2G4C, and correlated negatively with FGF2 and PRKACB after doing gene-gene

Differential selection on carotenoid biosynthesis genes as a function of gene position in the metabolic pathway: a study on the carrot and dicots.

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Jérémy Clotault

Full Text Available Selection of genes involved in metabolic pathways could target them differently depending on the position of genes in the pathway and on their role in controlling metabolic fluxes. This hypothesis was tested in the carotenoid biosynthesis pathway using population genetics and phylogenetics.Evolutionary rates of seven genes distributed along the carotenoid biosynthesis pathway, IPI, PDS, CRTISO, LCYB, LCYE, CHXE and ZEP, were compared in seven dicot taxa. A survey of deviations from neutrality expectations at these genes was also undertaken in cultivated carrot (Daucus carota subsp. sativus, a species that has been intensely bred for carotenoid pattern diversification in its root during its cultivation history. Parts of sequences of these genes were obtained from 46 individuals representing a wide diversity of cultivated carrots. Downstream genes exhibited higher deviations from neutral expectations than upstream genes. Comparisons of synonymous and nonsynonymous substitution rates between genes among dicots revealed greater constraints on upstream genes than on downstream genes. An excess of intermediate frequency polymorphisms, high nucleotide diversity and/or high differentiation of CRTISO, LCYB1 and LCYE in cultivated carrot suggest that balancing selection may have targeted genes acting centrally in the pathway.Our results are consistent with relaxed constraints on downstream genes and selection targeting the central enzymes of the carotenoid biosynthesis pathway during carrot breeding history.

Gene-Gene Interactions in the Folate Metabolic Pathway and the Risk of Conotruncal Heart Defects

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Philip J. Lupo

2010-01-01

Full Text Available Conotruncal and related heart defects (CTRD are common, complex malformations. Although there are few established risk factors, there is evidence that genetic variation in the folate metabolic pathway influences CTRD risk. This study was undertaken to assess the association between inherited (i.e., case and maternal gene-gene interactions in this pathway and the risk of CTRD. Case-parent triads (n=727, ascertained from the Children's Hospital of Philadelphia, were genotyped for ten functional variants of nine folate metabolic genes. Analyses of inherited genotypes were consistent with the previously reported association between MTHFR A1298C and CTRD (adjusted P=.02, but provided no evidence that CTRD was associated with inherited gene-gene interactions. Analyses of the maternal genotypes provided evidence of a MTHFR C677T/CBS 844ins68 interaction and CTRD risk (unadjusted P=.02. This association is consistent with the effects of this genotype combination on folate-homocysteine biochemistry but remains to be confirmed in independent study populations.

Sexy splicing: regulatory interplays governing sex determination from Drosophila to mammals.

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Lalli, Enzo; Ohe, Kenji; Latorre, Elisa; Bianchi, Marco E; Sassone-Corsi, Paolo

2003-02-01

A remarkable array of strategies is used to produce sexual differentiation in different species. Complex gene hierarchies govern sex determination pathways, as exemplified by the classic D. melanogaster paradigm, where an interplay of transcriptional, splicing and translational mechanisms operate. Molecular studies support the hypothesis that genetic sex determination pathways evolved in reverse order, from downstream to upstream genes, in the cascade. The recent identification of a role for the key regulatory factors SRY and WT1(+KTS) in pre-mRNA splicing indicates that important steps in the mammalian sex determination process are likely to operate at the post-transcriptional level.

Identification of Cell Wall Synthesis Regulatory Genes Controlling Biomass Characteristics and Yield in Rice (Oryza Sativa)

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Peng, Zhaohua PEng [Mississippi State University; Ronald, Palmela [UC-Davis; Wang, Guo-Liang [The Ohio State University

2013-04-26

This project aims to identify the regulatory genes of rice cell wall synthesis pathways using a cell wall removal and regeneration system. We completed the gene expression profiling studies following the time course from cell wall removal to cell wall regeneration in rice suspension cells. We also completed, total proteome, nuclear subproteome and histone modification studies following the course from cell wall removal and cell wall regeneration process. A large number of differentially expressed regulatory genes and proteins were identified. Meanwhile, we generated RNAi and over-expression transgenic rice for 45 genes with at least 10 independent transgenic lines for each gene. In addition, we ordered T-DNA and transposon insertion mutants for 60 genes from Korea, Japan, and France and characterized the mutants. Overall, we have mutants and transgenic lines for over 90 genes, exceeded our proposed goal of generating mutants for 50 genes. Interesting Discoveries a) Cell wall re-synthesis in protoplasts may involve a novel cell wall synthesis mechanism. The synthesis of the primary cell wall is initiated in late cytokinesis with further modification during cell expansion. Phragmoplast plays an essential role in cell wall synthesis. It services as a scaffold for building the cell plate and formation of a new cell wall. Only one phragmoplast and one new cell wall is produced for each dividing cell. When the cell wall was removed enzymatically, we found that cell wall re-synthesis started from multiple locations simultaneously, suggesting that a novel mechanism is involved in cell wall re-synthesis. This observation raised many interesting questions, such as how the starting sites of cell wall synthesis are determined, whether phragmoplast and cell plate like structures are involved in cell wall re-synthesis, and more importantly whether the same set of enzymes and apparatus are used in cell wall re-synthesis as during cytokinesis. Given that many known cell wall

Postinduction represssion of the β-interferon gene is mediated through two positive regulatory domains

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Whittemore, L.A.; Maniatis, T.

1990-01-01

Virus induction of the human β-interferon (β-IFN) gene results in an increase in the rate of β-IFN mRNA synthesis, followed by a rapid postinduction decrease. In this paper, the authors show that two β-IFN promoter elements, positive regulatory domains I and II (PRDI and PRDII), which are required for virus induction of the β-IFN gene are also required for the postinduction turnoff. Although protein synthesis is not necessary for activation, it is necessary for repression of these promoter elements. Examination of nuclear extracts from cells infected with virus reveals the presence of virus-inducible, cycloheximide-sensitive, DNA-binding activities that interact specifically with PRDI or PRDII. They propose that the postinduction repression of β-IFN gene transcription involves virus inducible repressors that either bind directly to the positive regulatory elements of the β-IFN promoter or inactivate the positive regulatory factors bound to PRDI and PRDII

Predictive modelling of gene expression from transcriptional regulatory elements.

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Budden, David M; Hurley, Daniel G; Crampin, Edmund J

2015-07-01

Predictive modelling of gene expression provides a powerful framework for exploring the regulatory logic underpinning transcriptional regulation. Recent studies have demonstrated the utility of such models in identifying dysregulation of gene and miRNA expression associated with abnormal patterns of transcription factor (TF) binding or nucleosomal histone modifications (HMs). Despite the growing popularity of such approaches, a comparative review of the various modelling algorithms and feature extraction methods is lacking. We define and compare three methods of quantifying pairwise gene-TF/HM interactions and discuss their suitability for integrating the heterogeneous chromatin immunoprecipitation (ChIP)-seq binding patterns exhibited by TFs and HMs. We then construct log-linear and ϵ-support vector regression models from various mouse embryonic stem cell (mESC) and human lymphoblastoid (GM12878) data sets, considering both ChIP-seq- and position weight matrix- (PWM)-derived in silico TF-binding. The two algorithms are evaluated both in terms of their modelling prediction accuracy and ability to identify the established regulatory roles of individual TFs and HMs. Our results demonstrate that TF-binding and HMs are highly predictive of gene expression as measured by mRNA transcript abundance, irrespective of algorithm or cell type selection and considering both ChIP-seq and PWM-derived TF-binding. As we encourage other researchers to explore and develop these results, our framework is implemented using open-source software and made available as a preconfigured bootable virtual environment. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

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Lockwood William W

2010-05-01

Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.

Foxf genes integrate tbx5 and hedgehog pathways in the second heart field for cardiac septation.

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Andrew D Hoffmann

2014-10-01

Full Text Available The Second Heart Field (SHF has been implicated in several forms of congenital heart disease (CHD, including atrioventricular septal defects (AVSDs. Identifying the SHF gene regulatory networks required for atrioventricular septation is therefore an essential goal for understanding the molecular basis of AVSDs. We defined a SHF Hedgehog-dependent gene regulatory network using whole genome transcriptional profiling and GLI-chromatin interaction studies. The Forkhead box transcription factors Foxf1a and Foxf2 were identified as SHF Hedgehog targets. Compound haploinsufficiency for Foxf1a and Foxf2 caused atrioventricular septal defects, demonstrating the biological relevance of this regulatory network. We identified a Foxf1a cis-regulatory element that bound the Hedgehog transcriptional regulators GLI1 and GLI3 and the T-box transcription factor TBX5 in vivo. GLI1 and TBX5 synergistically activated transcription from this cis-regulatory element in vitro. This enhancer drove reproducible expression in vivo in the posterior SHF, the only region where Gli1 and Tbx5 expression overlaps. Our findings implicate Foxf genes in atrioventricular septation, describe the molecular underpinnings of the genetic interaction between Hedgehog signaling and Tbx5, and establish a molecular model for the selection of the SHF gene regulatory network for cardiac septation.

Regulatory network of secondary metabolism in Brassica rapa : insight into the glucosinolate pathway

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Pino Del Carpio, Dunia; Basnet, Ram Kumar; Arends, Danny; Lin, Ke; De Vos, Ric C H; Muth, Dorota; Kodde, Jan; Boutilier, Kim; Bucher, Johan; Wang, Xiaowu; Jansen, Ritsert; Bonnema, Guusje

2014-01-01

Brassica rapa studies towards metabolic variation have largely been focused on the profiling of the diversity of metabolic compounds in specific crop types or regional varieties, but none aimed to identify genes with regulatory function in metabolite composition. Here we followed a genetical

Regulatory structures for gene therapy medicinal products in the European Union.

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Klug, Bettina; Celis, Patrick; Carr, Melanie; Reinhardt, Jens

2012-01-01

Taking into account the complexity and technical specificity of advanced therapy medicinal products: (gene and cell therapy medicinal products and tissue engineered products), a dedicated European regulatory framework was needed. Regulation (EC) No. 1394/2007, the "ATMP Regulation" provides tailored regulatory principles for the evaluation and authorization of these innovative medicines. The majority of gene or cell therapy product development is carried out by academia, hospitals, and small- and medium-sized enterprises (SMEs). Thus, acknowledging the particular needs of these types of sponsors, the legislation also provides incentives for product development tailored to them. The European Medicines Agency (EMA) and, in particular, its Committee for Advanced Therapies (CAT) provide a variety of opportunities for early interaction with developers of ATMPs to enable them to have early regulatory and scientific input. An important tool to promote innovation and the development of new medicinal products by micro-, small-, and medium-sized enterprises is the EMA's SME initiative launched in December 2005 to offer financial and administrative assistance to smaller companies. The European legislation also foresees the involvement of stakeholders, such as patient organizations, in the development of new medicines. Considering that gene therapy medicinal products are developed in many cases for treatment of rare diseases often of monogenic origin, the involvement of patient organizations, which focus on rare diseases and genetic and congenital disorders, is fruitful. Two such organizations are represented in the CAT. Research networks play another important role in the development of gene therapy medicinal products. The European Commission is funding such networks through the EU Sixth Framework Program. Copyright © 2012 Elsevier Inc. All rights reserved.

Pathway Distiller - multisource biological pathway consolidation.

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Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

2012-01-01

One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow

Gene expression profiling demonstrates WNT/β-catenin pathway genes alteration in Mexican patients with colorectal cancer and diabetes mellitus.

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Ivonne Wence-Chavez, Laura; Palomares-Chacon, Ulises; Pablo Flores-Gutierrez, Juan; Felipe Jave-Suarez, Luis; Del Carmen Aguilar-Lemarroy, Adriana; Barros-Nunez, Patricio; Esperanza Flores-Martinez, Silvia; Sanchez-Corona, Jose; Alejandra Rosales-Reynoso, Monica

2017-01-01

Several studies have shown a strong association between diabetes mellitus (DM) and increased risk of colorectal cancer (CRC). The fundamental mechanisms that support this association are not entirely understood; however, it is believed that hyperinsulinemia and hyperglycemia may be involved. Some proposed mechanisms include upregulation of mitogenic signaling pathways like MAPK, PI3K, mTOR, and WNT, which are involved in cell proliferation, growth, and cancer cell survival. The purpose of this study was to evaluate the gene expression profile and identify differently expressed genes involved in mitogenic pathways in CRC patients with and without DM. In this study, microarray analysis of gene expression followed by quantitative PCR (qPCR) was performed in cancer tissue from CRC patients with and without DM to identify the gene expression profiles and validate the differently expressed genes. Among the study groups, some differently expressed genes were identified. However, when bioinformatics clustering tools were used, a significant modulation of genes involved in the WNT pathway was evident. Therefore, we focused on genes participating in this pathway, such as WNT3A, LRP6, TCF7L2, and FRA-1. Validation of the expression levels of those genes by qPCR showed that CRC patients without type 2 diabetes mellitus (T2DM) expressed significantly more WNT3Ay LRP6, but less TCF7L2 and FRA-1 compared to controls, while in CRC patients with DM the expression levels of WNT3A, LRP6, TCF7L2, and FRA-1 were significantly higher compared to controls. Our results suggest that WNT/β-catenin pathway is upregulated in patients with CRC and DM, demonstrating its importance and involvement in both pathologies.

Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

NARCIS (Netherlands)

Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

2009-01-01

Background: Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori

The evolutionary capacitor HSP90 buffers the regulatory effects of mammalian endogenous retroviruses.

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Hummel, Barbara; Hansen, Erik C; Yoveva, Aneliya; Aprile-Garcia, Fernando; Hussong, Rebecca; Sawarkar, Ritwick

2017-03-01

Understanding how genotypes are linked to phenotypes is important in biomedical and evolutionary studies. The chaperone heat-shock protein 90 (HSP90) buffers genetic variation by stabilizing proteins with variant sequences, thereby uncoupling phenotypes from genotypes. Here we report an unexpected role of HSP90 in buffering cis-regulatory variation affecting gene expression. By using the tripartite-motif-containing 28 (TRIM28; also known as KAP1)-mediated epigenetic pathway, HSP90 represses the regulatory influence of endogenous retroviruses (ERVs) on neighboring genes that are critical for mouse development. Our data based on natural variations in the mouse genome show that genes respond to HSP90 inhibition in a manner dependent on their genomic location with regard to strain-specific ERV-insertion sites. The evolutionary-capacitor function of HSP90 may thus have facilitated the exaptation of ERVs as key modifiers of gene expression and morphological diversification. Our findings add a new regulatory layer through which HSP90 uncouples phenotypic outcomes from individual genotypes.

Mechanistically Distinct Pathways of Divergent Regulatory DNA Creation Contribute to Evolution of Human-Specific Genomic Regulatory Networks Driving Phenotypic Divergence of Homo sapiens.

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Glinsky, Gennadi V

2016-09-19

Thousands of candidate human-specific regulatory sequences (HSRS) have been identified, supporting the hypothesis that unique to human phenotypes result from human-specific alterations of genomic regulatory networks. Collectively, a compendium of multiple diverse families of HSRS that are functionally and structurally divergent from Great Apes could be defined as the backbone of human-specific genomic regulatory networks. Here, the conservation patterns analysis of 18,364 candidate HSRS was carried out requiring that 100% of bases must remap during the alignments of human, chimpanzee, and bonobo sequences. A total of 5,535 candidate HSRS were identified that are: (i) highly conserved in Great Apes; (ii) evolved by the exaptation of highly conserved ancestral DNA; (iii) defined by either the acceleration of mutation rates on the human lineage or the functional divergence from non-human primates. The exaptation of highly conserved ancestral DNA pathway seems mechanistically distinct from the evolution of regulatory DNA segments driven by the species-specific expansion of transposable elements. Genome-wide proximity placement analysis of HSRS revealed that a small fraction of topologically associating domains (TADs) contain more than half of HSRS from four distinct families. TADs that are enriched for HSRS and termed rapidly evolving in humans TADs (revTADs) comprise 0.8-10.3% of 3,127 TADs in the hESC genome. RevTADs manifest distinct correlation patterns between placements of human accelerated regions, human-specific transcription factor-binding sites, and recombination rates. There is a significant enrichment within revTAD boundaries of hESC-enhancers, primate-specific CTCF-binding sites, human-specific RNAPII-binding sites, hCONDELs, and H3K4me3 peaks with human-specific enrichment at TSS in prefrontal cortex neurons (P sapiens is driven by the evolution of human-specific genomic regulatory networks via at least two mechanistically distinct pathways of creation of

A systems biology approach to construct the gene regulatory network of systemic inflammation via microarray and databases mining

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Lan Chung-Yu

2008-09-01

Full Text Available Abstract Background Inflammation is a hallmark of many human diseases. Elucidating the mechanisms underlying systemic inflammation has long been an important topic in basic and clinical research. When primary pathogenetic events remains unclear due to its immense complexity, construction and analysis of the gene regulatory network of inflammation at times becomes the best way to understand the detrimental effects of disease. However, it is difficult to recognize and evaluate relevant biological processes from the huge quantities of experimental data. It is hence appealing to find an algorithm which can generate a gene regulatory network of systemic inflammation from high-throughput genomic studies of human diseases. Such network will be essential for us to extract valuable information from the complex and chaotic network under diseased conditions. Results In this study, we construct a gene regulatory network of inflammation using data extracted from the Ensembl and JASPAR databases. We also integrate and apply a number of systematic algorithms like cross correlation threshold, maximum likelihood estimation method and Akaike Information Criterion (AIC on time-lapsed microarray data to refine the genome-wide transcriptional regulatory network in response to bacterial endotoxins in the context of dynamic activated genes, which are regulated by transcription factors (TFs such as NF-κB. This systematic approach is used to investigate the stochastic interaction represented by the dynamic leukocyte gene expression profiles of human subject exposed to an inflammatory stimulus (bacterial endotoxin. Based on the kinetic parameters of the dynamic gene regulatory network, we identify important properties (such as susceptibility to infection of the immune system, which may be useful for translational research. Finally, robustness of the inflammatory gene network is also inferred by analyzing the hubs and "weak ties" structures of the gene network

Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient.

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Mohamed Salleh, Faridah Hani; Arif, Shereena Mohd; Zainudin, Suhaila; Firdaus-Raih, Mohd

2015-12-01

A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5. Copyright © 2015 Elsevier Ltd. All rights reserved.

TLR-related pathway analysis : novel gene-gene interactions in the development of asthma and atopy

NARCIS (Netherlands)

Reijmerink, N. E.; Bottema, R. W. B.; Kerkhof, M.; Gerritsen, J.; Stelma, F. F.; Thijs, C.; van Schayck, C. P.; Smit, H. A.; Brunekreef, B.; Koppelman, G. H.; Postma, D. S.

P>Background: The toll-like receptor (TLR)-related pathway is important in host defence and may be crucial in the development of asthma and atopy. Numerous studies have shown associations of TLR-related pathway genes with asthma and atopy phenotypes. So far it has not been investigated whether

A big data pipeline: Identifying dynamic gene regulatory networks from time-course Gene Expression Omnibus data with applications to influenza infection.

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Carey, Michelle; Ramírez, Juan Camilo; Wu, Shuang; Wu, Hulin

2018-07-01

A biological host response to an external stimulus or intervention such as a disease or infection is a dynamic process, which is regulated by an intricate network of many genes and their products. Understanding the dynamics of this gene regulatory network allows us to infer the mechanisms involved in a host response to an external stimulus, and hence aids the discovery of biomarkers of phenotype and biological function. In this article, we propose a modeling/analysis pipeline for dynamic gene expression data, called Pipeline4DGEData, which consists of a series of statistical modeling techniques to construct dynamic gene regulatory networks from the large volumes of high-dimensional time-course gene expression data that are freely available in the Gene Expression Omnibus repository. This pipeline has a consistent and scalable structure that allows it to simultaneously analyze a large number of time-course gene expression data sets, and then integrate the results across different studies. We apply the proposed pipeline to influenza infection data from nine studies and demonstrate that interesting biological findings can be discovered with its implementation.

Synthetic lethality between gene defects affecting a single non-essential molecular pathway with reversible steps.

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Andrei Zinovyev

2013-04-01

Full Text Available Systematic analysis of synthetic lethality (SL constitutes a critical tool for systems biology to decipher molecular pathways. The most accepted mechanistic explanation of SL is that the two genes function in parallel, mutually compensatory pathways, known as between-pathway SL. However, recent genome-wide analyses in yeast identified a significant number of within-pathway negative genetic interactions. The molecular mechanisms leading to within-pathway SL are not fully understood. Here, we propose a novel mechanism leading to within-pathway SL involving two genes functioning in a single non-essential pathway. This type of SL termed within-reversible-pathway SL involves reversible pathway steps, catalyzed by different enzymes in the forward and backward directions, and kinetic trapping of a potentially toxic intermediate. Experimental data with recombinational DNA repair genes validate the concept. Mathematical modeling recapitulates the possibility of kinetic trapping and revealed the potential contributions of synthetic, dosage-lethal interactions in such a genetic system as well as the possibility of within-pathway positive masking interactions. Analysis of yeast gene interaction and pathway data suggests broad applicability of this novel concept. These observations extend the canonical interpretation of synthetic-lethal or synthetic-sick interactions with direct implications to reconstruct molecular pathways and improve therapeutic approaches to diseases such as cancer.

Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

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Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

2006-07-01

Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

Vitamin D metabolic pathway genes and pancreatic cancer risk.

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Hannah Arem

Full Text Available Evidence on the association between vitamin D status and pancreatic cancer risk is inconsistent. This inconsistency may be partially attributable to variation in vitamin D regulating genes. We selected 11 vitamin D-related genes (GC, DHCR7, CYP2R1, VDR, CYP27B1, CYP24A1, CYP27A1, RXRA, CRP2, CASR and CUBN totaling 213 single nucleotide polymorphisms (SNPs, and examined associations with pancreatic adenocarcinoma. Our study included 3,583 pancreatic cancer cases and 7,053 controls from the genome-wide association studies of pancreatic cancer PanScans-I-III. We used the Adaptive Joint Test and the Adaptive Rank Truncated Product statistic for pathway and gene analyses, and unconditional logistic regression for SNP analyses, adjusting for age, sex, study and population stratification. We examined effect modification by circulating vitamin D concentration (≤50, >50 nmol/L for the most significant SNPs using a subset of cohort cases (n = 713 and controls (n = 878. The vitamin D metabolic pathway was not associated with pancreatic cancer risk (p = 0.830. Of the individual genes, none were associated with pancreatic cancer risk at a significance level of p<0.05. SNPs near the VDR (rs2239186, LRP2 (rs4668123, CYP24A1 (rs2762932, GC (rs2282679, and CUBN (rs1810205 genes were the top SNPs associated with pancreatic cancer (p-values 0.008-0.037, but none were statistically significant after adjusting for multiple comparisons. Associations between these SNPs and pancreatic cancer were not modified by circulating concentrations of vitamin D. These findings do not support an association between vitamin D-related genes and pancreatic cancer risk. Future research should explore other pathways through which vitamin D status might be associated with pancreatic cancer risk.

A complex regulatory network coordinating cell cycles during C. elegans development is revealed by a genome-wide RNAi screen.

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Roy, Sarah H; Tobin, David V; Memar, Nadin; Beltz, Eleanor; Holmen, Jenna; Clayton, Joseph E; Chiu, Daniel J; Young, Laura D; Green, Travis H; Lubin, Isabella; Liu, Yuying; Conradt, Barbara; Saito, R Mako

2014-02-28

The development and homeostasis of multicellular animals requires precise coordination of cell division and differentiation. We performed a genome-wide RNA interference screen in Caenorhabditis elegans to reveal the components of a regulatory network that promotes developmentally programmed cell-cycle quiescence. The 107 identified genes are predicted to constitute regulatory networks that are conserved among higher animals because almost half of the genes are represented by clear human orthologs. Using a series of mutant backgrounds to assess their genetic activities, the RNA interference clones displaying similar properties were clustered to establish potential regulatory relationships within the network. This approach uncovered four distinct genetic pathways controlling cell-cycle entry during intestinal organogenesis. The enhanced phenotypes observed for animals carrying compound mutations attest to the collaboration between distinct mechanisms to ensure strict developmental regulation of cell cycles. Moreover, we characterized ubc-25, a gene encoding an E2 ubiquitin-conjugating enzyme whose human ortholog, UBE2Q2, is deregulated in several cancers. Our genetic analyses suggested that ubc-25 acts in a linear pathway with cul-1/Cul1, in parallel to pathways employing cki-1/p27 and lin-35/pRb to promote cell-cycle quiescence. Further investigation of the potential regulatory mechanism demonstrated that ubc-25 activity negatively regulates CYE-1/cyclin E protein abundance in vivo. Together, our results show that the ubc-25-mediated pathway acts within a complex network that integrates the actions of multiple molecular mechanisms to control cell cycles during development. Copyright © 2014 Roy et al.

Amelogenesis Imperfecta; Genes, Proteins, and Pathways

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Claire E. L. Smith

2017-06-01

Full Text Available Amelogenesis imperfecta (AI is the name given to a heterogeneous group of conditions characterized by inherited developmental enamel defects. AI enamel is abnormally thin, soft, fragile, pitted and/or badly discolored, with poor function and aesthetics, causing patients problems such as early tooth loss, severe embarrassment, eating difficulties, and pain. It was first described separately from diseases of dentine nearly 80 years ago, but the underlying genetic and mechanistic basis of the condition is only now coming to light. Mutations in the gene AMELX, encoding an extracellular matrix protein secreted by ameloblasts during enamel formation, were first identified as a cause of AI in 1991. Since then, mutations in at least eighteen genes have been shown to cause AI presenting in isolation of other health problems, with many more implicated in syndromic AI. Some of the encoded proteins have well documented roles in amelogenesis, acting as enamel matrix proteins or the proteases that degrade them, cell adhesion molecules or regulators of calcium homeostasis. However, for others, function is less clear and further research is needed to understand the pathways and processes essential for the development of healthy enamel. Here, we review the genes and mutations underlying AI presenting in isolation of other health problems, the proteins they encode and knowledge of their roles in amelogenesis, combining evidence from human phenotypes, inheritance patterns, mouse models, and in vitro studies. An LOVD resource (http://dna2.leeds.ac.uk/LOVD/ containing all published gene mutations for AI presenting in isolation of other health problems is described. We use this resource to identify trends in the genes and mutations reported to cause AI in the 270 families for which molecular diagnoses have been reported by 23rd May 2017. Finally we discuss the potential value of the translation of AI genetics to clinical care with improved patient pathways and

Amelogenesis Imperfecta; Genes, Proteins, and Pathways.

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Smith, Claire E L; Poulter, James A; Antanaviciute, Agne; Kirkham, Jennifer; Brookes, Steven J; Inglehearn, Chris F; Mighell, Alan J

2017-01-01

Amelogenesis imperfecta (AI) is the name given to a heterogeneous group of conditions characterized by inherited developmental enamel defects. AI enamel is abnormally thin, soft, fragile, pitted and/or badly discolored, with poor function and aesthetics, causing patients problems such as early tooth loss, severe embarrassment, eating difficulties, and pain. It was first described separately from diseases of dentine nearly 80 years ago, but the underlying genetic and mechanistic basis of the condition is only now coming to light. Mutations in the gene AMELX , encoding an extracellular matrix protein secreted by ameloblasts during enamel formation, were first identified as a cause of AI in 1991. Since then, mutations in at least eighteen genes have been shown to cause AI presenting in isolation of other health problems, with many more implicated in syndromic AI. Some of the encoded proteins have well documented roles in amelogenesis, acting as enamel matrix proteins or the proteases that degrade them, cell adhesion molecules or regulators of calcium homeostasis. However, for others, function is less clear and further research is needed to understand the pathways and processes essential for the development of healthy enamel. Here, we review the genes and mutations underlying AI presenting in isolation of other health problems, the proteins they encode and knowledge of their roles in amelogenesis, combining evidence from human phenotypes, inheritance patterns, mouse models, and in vitro studies. An LOVD resource (http://dna2.leeds.ac.uk/LOVD/) containing all published gene mutations for AI presenting in isolation of other health problems is described. We use this resource to identify trends in the genes and mutations reported to cause AI in the 270 families for which molecular diagnoses have been reported by 23rd May 2017. Finally we discuss the potential value of the translation of AI genetics to clinical care with improved patient pathways and speculate on the

Comparison of Five Major Trichome Regulatory Genes in Brassica villosa with Orthologues within the Brassicaceae

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Nayidu, Naghabushana K.; Kagale, Sateesh; Taheri, Ali; Withana-Gamage, Thushan S.; Parkin, Isobel A. P.; Sharpe, Andrew G.; Gruber, Margaret Y.

2014-01-01

Coding sequences for major trichome regulatory genes, including the positive regulators GLABRA 1(GL1), GLABRA 2 (GL2), ENHANCER OF GLABRA 3 (EGL3), and TRANSPARENT TESTA GLABRA 1 (TTG1) and the negative regulator TRIPTYCHON (TRY), were cloned from wild Brassica villosa, which is characterized by dense trichome coverage over most of the plant. Transcript (FPKM) levels from RNA sequencing indicated much higher expression of the GL2 and TTG1 regulatory genes in B. villosa leaves compared with expression levels of GL1 and EGL3 genes in either B. villosa or the reference genome species, glabrous B. oleracea; however, cotyledon TTG1 expression was high in both species. RNA sequencing and Q-PCR also revealed an unusual expression pattern for the negative regulators TRY and CPC, which were much more highly expressed in trichome-rich B. villosa leaves than in glabrous B. oleracea leaves and in glabrous cotyledons from both species. The B. villosa TRY expression pattern also contrasted with TRY expression patterns in two diploid Brassica species, and with the Arabidopsis model for expression of negative regulators of trichome development. Further unique sequence polymorphisms, protein characteristics, and gene evolution studies highlighted specific amino acids in GL1 and GL2 coding sequences that distinguished glabrous species from hairy species and several variants that were specific for each B. villosa gene. Positive selection was observed for GL1 between hairy and non-hairy plants, and as expected the origin of the four expressed positive trichome regulatory genes in B. villosa was predicted to be from B. oleracea. In particular the unpredicted expression patterns for TRY and CPC in B. villosa suggest additional characterization is needed to determine the function of the expanded families of trichome regulatory genes in more complex polyploid species within the Brassicaceae. PMID:24755905

The association of environmental, individual factors, and dopamine pathway gene variation with smoking cessation.

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Li, Suyun; Wang, Qiang; Pan, Lulu; Yang, Xiaorong; Li, Huijie; Jiang, Fan; Zhang, Nan; Han, Mingkui; Jia, Chongqi

2017-09-01

This study aimed to examine whether dopamine (DA) pathway gene variation were associated with smoking cessation, and compare the relative importance of infulence factors on smoking cessation. Participants were recruited from 17 villages of Shandong Province, China. Twenty-five single nucleotide polymorphisms in 8 DA pathway genes were genotyped. Weighted gene score of each gene was used to analyze the whole gene effect. Logistic regression was used to calculate odds ratios (OR) of the total gene score for smoking cessation. Dominance analysis was employed to compare the relative importance of individual, heaviness of smoking, psychological and genetic factors on smoking cessation. 415 successful spontaneous smoking quitters served as the cases, and 404 unsuccessful quitters served as the controls. A significant negative association of total DA pathway gene score and smoking cessation was observed (p smoking cessation was heaviness of smoking score (42%), following by individual (40%), genetic (10%) and psychological score (8%). In conclusion, although the DA pathway gene variation was significantly associated with successful smoking cessation, heaviness of smoking and individual factors had bigger effect than genetic factors on smoking cessation.

The pvc operon regulates the expression of the Pseudomonas aeruginosa fimbrial chaperone/usher pathway (cup genes.

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Uzma Qaisar

Full Text Available The Pseudomonas aeruginosa fimbrial structures encoded by the cup gene clusters (cupB and cupC contribute to its attachment to abiotic surfaces and biofilm formation. The P. aeruginosa pvcABCD gene cluster encodes enzymes that synthesize a novel isonitrile functionalized cumarin, paerucumarin. Paerucumarin has already been characterized chemically, but this is the first report elucidating its role in bacterial biology. We examined the relationship between the pvc operon and the cup gene clusters in the P. aeruginosa strain MPAO1. Mutations within the pvc genes compromised biofilm development and significantly reduced the expression of cupB1-6 and cupC1-3, as well as different genes of the cupB/cupC two-component regulatory systems, roc1/roc2. Adjacent to pvc is the transcriptional regulator ptxR. A ptxR mutation in MPAO1 significantly reduced the expression of the pvc genes, the cupB/cupC genes, and the roc1/roc2 genes. Overexpression of the intact chromosomally-encoded pvc operon by a ptxR plasmid significantly enhanced cupB2, cupC2, rocS1, and rocS2 expression and biofilm development. Exogenously added paerucumarin significantly increased the expression of cupB2, cupC2, rocS1 and rocS2 in the pvcA mutant. Our results suggest that pvc influences P. aeruginosa biofilm development through the cup gene clusters in a pathway that involves paerucumarin, PtxR, and different cup regulators.

A Systems’ Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

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Xin Lai

2013-01-01

Full Text Available MicroRNAs (miRNAs are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts.

Transcriptome of Atoh7 retinal progenitor cells identifies new Atoh7-dependent regulatory genes for retinal ganglion cell formation.

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Gao, Zhiguang; Mao, Chai-An; Pan, Ping; Mu, Xiuqian; Klein, William H

2014-11-01

The bHLH transcription factor ATOH7 (Math5) is essential for establishing retinal ganglion cell (RGC) fate. However, Atoh7-expressing retinal progenitor cells (RPCs) can give rise to all retinal cell types, suggesting that other factors are involved in specifying RGCs. The basis by which a subpopulation of Atoh7-expressing RPCs commits to an RGC fate remains uncertain but is of critical importance to retinal development since RGCs are the earliest cell type to differentiate. To better understand the regulatory mechanisms leading to cell-fate specification, a binary genetic system was generated to specifically label Atoh7-expressing cells with green fluorescent protein (GFP). Fluorescence-activated cell sorting (FACS)-purified GFP(+) and GFP(-) cells were profiled by RNA-seq. Here, we identify 1497 transcripts that were differentially expressed between the two RPC populations. Pathway analysis revealed diminished growth factor signaling in Atoh7-expressing RPCs, indicating that these cells had exited the cell cycle. In contrast, axon guidance signals were enriched, suggesting that axons of Atoh7-expressing RPCs were already making synaptic connections. Notably, many genes enriched in Atoh7-expressing RPCs encoded transcriptional regulators, and several were direct targets of ATOH7, including, and unexpectedly, Ebf3 and Eya2. We present evidence for a Pax6-Atoh7-Eya2 pathway that acts downstream of Atoh7 but upstream of differentiation factor Pou4f2. EYA2 is a protein phosphatase involved in protein-protein interactions and posttranslational regulation. These properties, along with Eya2 as an early target gene of ATOH7, suggest that EYA2 functions in RGC specification. Our results expand current knowledge of the regulatory networks operating in Atoh7-expressing RPCs and offer new directions for exploring the earliest aspects of retinogenesis. © 2014 Wiley Periodicals, Inc.

Gene prediction validation and functional analysis of redundant pathways

DEFF Research Database (Denmark)

Sønderkær, Mads

2011-01-01

have employed a large mRNA-seq data set to improve and validate ab initio predicted gene models. This direct experimental evidence also provides reliable determinations of UTR regions and polyadenylation sites, which are not easily predicted in plants. Furthermore, once an annotated genome sequence...... is available, gene expression by mRNA-Seq enables acquisition of a more complete overview of gene isoform usage in complex enzymatic pathways enabling the identification of key genes. Metabolism in potatoes This information is useful e.g. for crop improvement based on manipulation of agronomically important...

Regulatory Architecture of Gene Expression Variation in the Threespine Stickleback Gasterosteus aculeatus

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Victoria L. Pritchard

2017-01-01

Full Text Available Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus, an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats.

Silencing of the pentose phosphate pathway genes influences DNA replication in human fibroblasts.

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Fornalewicz, Karolina; Wieczorek, Aneta; Węgrzyn, Grzegorz; Łyżeń, Robert

2017-11-30

Previous reports and our recently published data indicated that some enzymes of glycolysis and the tricarboxylic acid cycle can affect the genome replication process by changing either the efficiency or timing of DNA synthesis in human normal cells. Both these pathways are connected with the pentose phosphate pathway (PPP pathway). The PPP pathway supports cell growth by generating energy and precursors for nucleotides and amino acids. Therefore, we asked if silencing of genes coding for enzymes involved in the pentose phosphate pathway may also affect the control of DNA replication in human fibroblasts. Particular genes coding for PPP pathway enzymes were partially silenced with specific siRNAs. Such cells remained viable. We found that silencing of the H6PD, PRPS1, RPE genes caused less efficient enterance to the S phase and decrease in efficiency of DNA synthesis. On the other hand, in cells treated with siRNA against G6PD, RBKS and TALDO genes, the fraction of cells entering the S phase was increased. However, only in the case of G6PD and TALDO, the ratio of BrdU incorporation to DNA was significantly changed. The presented results together with our previously published studies illustrate the complexity of the influence of genes coding for central carbon metabolism on the control of DNA replication in human fibroblasts, and indicate which of them are especially important in this process. Copyright © 2017 Elsevier B.V. All rights reserved.

Regulatory Considerations for Gene Therapy Products in the US, EU, and Japan.

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Halioua-Haubold, Celine-Lea; Peyer, James G; Smith, James A; Arshad, Zeeshaan; Scholz, Matthew; Brindley, David A; MacLaren, Robert E

2017-12-01

Developers of gene therapy products (GTPs) must adhere to additional regulation beyond that of traditional small-molecule therapeutics, due to the unique mechanism-of-action of GTPs and the subsequent novel risks arisen. We have provided herein a summary of the regulatory structure under which GTPs fall in the United States, the European Union, and Japan, and a comprehensive overview of the regulatory guidance applicable to the developer of GTP. Understanding the regulatory requirements for seeking GTP market approval in these major jurisdictions is crucial for an effective and expedient path to market. The novel challenges facing GTP developers is highlighted by a case study of alipogene tiparvovec (Glybera).

GeneAnalytics Pathway Analysis and Genetic Overlap among Autism Spectrum Disorder, Bipolar Disorder and Schizophrenia

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Naveen S. Khanzada

2017-02-01

Full Text Available Bipolar disorder (BPD and schizophrenia (SCH show similar neuropsychiatric behavioral disturbances, including impaired social interaction and communication, seen in autism spectrum disorder (ASD with multiple overlapping genetic and environmental influences implicated in risk and course of illness. GeneAnalytics software was used for pathway analysis and genetic profiling to characterize common susceptibility genes obtained from published lists for ASD (792 genes, BPD (290 genes and SCH (560 genes. Rank scores were derived from the number and nature of overlapping genes, gene-disease association, tissue specificity and gene functions subdivided into categories (e.g., diseases, tissues or functional pathways. Twenty-three genes were common to all three disorders and mapped to nine biological Superpathways including Circadian entrainment (10 genes, score = 37.0, Amphetamine addiction (five genes, score = 24.2, and Sudden infant death syndrome (six genes, score = 24.1. Brain tissues included the medulla oblongata (11 genes, score = 2.1, thalamus (10 genes, score = 2.0 and hypothalamus (nine genes, score = 2.0 with six common genes (BDNF, DRD2, CHRNA7, HTR2A, SLC6A3, and TPH2. Overlapping genes impacted dopamine and serotonin homeostasis and signal transduction pathways, impacting mood, behavior and physical activity level. Converging effects on pathways governing circadian rhythms support a core etiological relationship between neuropsychiatric illnesses and sleep disruption with hypoxia and central brain stem dysfunction.

Functional evolution of cis-regulatory modules at a homeotic gene in Drosophila.

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Margaret C W Ho

2009-11-01

Full Text Available It is a long-held belief in evolutionary biology that the rate of molecular evolution for a given DNA sequence is inversely related to the level of functional constraint. This belief holds true for the protein-coding homeotic (Hox genes originally discovered in Drosophila melanogaster. Expression of the Hox genes in Drosophila embryos is essential for body patterning and is controlled by an extensive array of cis-regulatory modules (CRMs. How the regulatory modules functionally evolve in different species is not clear. A comparison of the CRMs for the Abdominal-B gene from different Drosophila species reveals relatively low levels of overall sequence conservation. However, embryonic enhancer CRMs from other Drosophila species direct transgenic reporter gene expression in the same spatial and temporal patterns during development as their D. melanogaster orthologs. Bioinformatic analysis reveals the presence of short conserved sequences within defined CRMs, representing gap and pair-rule transcription factor binding sites. One predicted binding site for the gap transcription factor KRUPPEL in the IAB5 CRM was found to be altered in Superabdominal (Sab mutations. In Sab mutant flies, the third abdominal segment is transformed into a copy of the fifth abdominal segment. A model for KRUPPEL-mediated repression at this binding site is presented. These findings challenge our current understanding of the relationship between sequence evolution at the molecular level and functional activity of a CRM. While the overall sequence conservation at Drosophila CRMs is not distinctive from neighboring genomic regions, functionally critical transcription factor binding sites within embryonic enhancer CRMs are highly conserved. These results have implications for understanding mechanisms of gene expression during embryonic development, enhancer function, and the molecular evolution of eukaryotic regulatory modules.

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

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Hermsen, Sanne A.B., E-mail: Sanne.Hermsen@rivm.nl [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands); Pronk, Tessa E. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Brandhof, Evert-Jan van den [Centre for Environmental Quality, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Ven, Leo T.M. van der [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Piersma, Aldert H. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands)

2013-10-01

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

NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

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Joeri Ruyssinck

Full Text Available One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made

Partitioning of genetic variation between regulatory and coding gene segments: the predominance of software variation in genes encoding introvert proteins.

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Mitchison, A

1997-01-01

In considering genetic variation in eukaryotes, a fundamental distinction can be made between variation in regulatory (software) and coding (hardware) gene segments. For quantitative traits the bulk of variation, particularly that near the population mean, appears to reside in regulatory segments. The main exceptions to this rule concern proteins which handle extrinsic substances, here termed extrovert proteins. The immune system includes an unusually large proportion of this exceptional category, but even so its chief source of variation may well be polymorphism in regulatory gene segments. The main evidence for this view emerges from genome scanning for quantitative trait loci (QTL), which in the case of the immune system points to a major contribution of pro-inflammatory cytokine genes. Further support comes from sequencing of major histocompatibility complex (Mhc) class II promoters, where a high level of polymorphism has been detected. These Mhc promoters appear to act, in part at least, by gating the back-signal from T cells into antigen-presenting cells. Both these forms of polymorphism are likely to be sustained by the need for flexibility in the immune response. Future work on promoter polymorphism is likely to benefit from the input from genome informatics.

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

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

2018-01-01

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

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

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Precious Takondwa Makondi

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

Systematic discovery of regulatory motifs in Fusarium graminearum by comparing four Fusarium genomes

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Kistler Corby

2010-03-01

Full Text Available Abstract Background Fusarium graminearum (Fg, a major fungal pathogen of cultivated cereals, is responsible for billions of dollars in agriculture losses. There is a growing interest in understanding the transcriptional regulation of this organism, especially the regulation of genes underlying its pathogenicity. The generation of whole genome sequence assemblies for Fg and three closely related Fusarium species provides a unique opportunity for such a study. Results Applying comparative genomics approaches, we developed a computational pipeline to systematically discover evolutionarily conserved regulatory motifs in the promoter, downstream and the intronic regions of Fg genes, based on the multiple alignments of sequenced Fusarium genomes. Using this method, we discovered 73 candidate regulatory motifs in the promoter regions. Nearly 30% of these motifs are highly enriched in promoter regions of Fg genes that are associated with a specific functional category. Through comparison to Saccharomyces cerevisiae (Sc and Schizosaccharomyces pombe (Sp, we observed conservation of transcription factors (TFs, their binding sites and the target genes regulated by these TFs related to pathways known to respond to stress conditions or phosphate metabolism. In addition, this study revealed 69 and 39 conserved motifs in the downstream regions and the intronic regions, respectively, of Fg genes. The top intronic motif is the splice donor site. For the downstream regions, we noticed an intriguing absence of the mammalian and Sc poly-adenylation signals among the list of conserved motifs. Conclusion This study provides the first comprehensive list of candidate regulatory motifs in Fg, and underscores the power of comparative genomics in revealing functional elements among related genomes. The conservation of regulatory pathways among the Fusarium genomes and the two yeast species reveals their functional significance, and provides new insights in their

Medusa structure of the gene regulatory network: dominance of transcription factors in cancer subtype classification.

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Guo, Yuchun; Feng, Ying; Trivedi, Niraj S; Huang, Sui

2011-05-01

Gene expression profiles consisting of ten thousands of transcripts are used for clustering of tissue, such as tumors, into subtypes, often without considering the underlying reason that the distinct patterns of expression arise because of constraints in the realization of gene expression profiles imposed by the gene regulatory network. The topology of this network has been suggested to consist of a regulatory core of genes represented most prominently by transcription factors (TFs) and microRNAs, that influence the expression of other genes, and of a periphery of 'enslaved' effector genes that are regulated but not regulating. This 'medusa' architecture implies that the core genes are much stronger determinants of the realized gene expression profiles. To test this hypothesis, we examined the clustering of gene expression profiles into known tumor types to quantitatively demonstrate that TFs, and even more pronounced, microRNAs, are much stronger discriminators of tumor type specific gene expression patterns than a same number of randomly selected or metabolic genes. These findings lend support to the hypothesis of a medusa architecture and of the canalizing nature of regulation by microRNAs. They also reveal the degree of freedom for the expression of peripheral genes that are less stringently associated with a tissue type specific global gene expression profile.

Wound healing, calcium signaling, and other novel pathways are associated with the formation of butterfly eyespots.

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Özsu, Nesibe; Monteiro, Antónia

2017-10-16

One hypothesis surrounding the origin of novel traits is that they originate from the co-option of pre-existing genes or larger gene regulatory networks into novel developmental contexts. Insights into a trait's evolutionary origins can, thus, be gained via identification of the genes underlying trait development, and exploring whether those genes also function in other developmental contexts. Here we investigate the set of genes associated with the development of eyespot color patterns, a trait that originated once within the Nymphalid family of butterflies. Although several genes associated with eyespot development have been identified, the eyespot gene regulatory network remains largely unknown. In this study, next-generation sequencing and transcriptome analyses were used to identify a large set of genes associated with eyespot development of Bicyclus anynana butterflies, at 3-6 h after pupation, prior to the differentiation of the color rings. Eyespot-associated genes were identified by comparing the transcriptomes of homologous micro-dissected wing tissues that either develop or do not develop eyespots in wild-type and a mutant line of butterflies, Spotty, with extra eyespots. Overall, 186 genes were significantly up and down-regulated in wing tissues that develop eyespots compared to wing tissues that do not. Many of the differentially expressed genes have yet to be annotated. New signaling pathways, including the Toll, Fibroblast Growth Factor (FGF), extracellular signal-regulated kinase (ERK) and/or Jun N-terminal kinase (JNK) signaling pathways are associated for the first time with eyespot development. In addition, several genes involved in wound healing and calcium signaling were also found to be associated with eyespots. Overall, this study provides the identity of many new genes and signaling pathways associated with eyespots, and suggests that the ancient wound healing gene regulatory network may have been co-opted to cells at the center of the

Comparative gene expression analysis of Dtg, a novel target gene of Dpp signaling pathway in the early Drosophila melanogaster embryo.

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Hodar, Christian; Zuñiga, Alejandro; Pulgar, Rodrigo; Travisany, Dante; Chacon, Carlos; Pino, Michael; Maass, Alejandro; Cambiazo, Verónica

2014-02-10

In the early Drosophila melanogaster embryo, Dpp, a secreted molecule that belongs to the TGF-β superfamily of growth factors, activates a set of downstream genes to subdivide the dorsal region into amnioserosa and dorsal epidermis. Here, we examined the expression pattern and transcriptional regulation of Dtg, a new target gene of Dpp signaling pathway that is required for proper amnioserosa differentiation. We showed that the expression of Dtg was controlled by Dpp and characterized a 524-bp enhancer that mediated expression in the dorsal midline, as well as, in the differentiated amnioserosa in transgenic reporter embryos. This enhancer contained a highly conserved region of 48-bp in which bioinformatic predictions and in vitro assays identified three Mad binding motifs. Mutational analysis revealed that these three motifs were necessary for proper expression of a reporter gene in transgenic embryos, suggesting that short and highly conserved genomic sequences may be indicative of functional regulatory regions in D. melanogaster genes. Dtg orthologs were not detected in basal lineages of Dipterans, which unlike D. melanogaster develop two extra-embryonic membranes, amnion and serosa, nevertheless Dtg orthologs were identified in the transcriptome of Musca domestica, in which dorsal ectoderm patterning leads to the formation of a single extra-embryonic membrane. These results suggest that Dtg was recruited as a new component of the network that controls dorsal ectoderm patterning in the lineage leading to higher Cyclorrhaphan flies, such as D. melanogaster and M. domestica. Copyright © 2013 Elsevier B.V. All rights reserved.

Coregulation of terpenoid pathway genes and prediction of isoprene production in Bacillus subtilis using transcriptomics

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Hess, Becky M.; Xue, Junfeng; Markillie, Lye Meng; Taylor, Ronald C.; Wiley, H. S.; Ahring, Birgitte K.; Linggi, Bryan E.

2013-06-19

The isoprenoid pathway converts pyruvate to isoprene and related isoprenoid compounds in plants and some bacteria. Currently, this pathway is of great interest because of the critical role that isoprenoids play in basic cellular processes as well as the industrial value of metabolites such as isoprene. Although the regulation of several pathway genes has been described, there is a paucity of information regarding the system level regulation and control of the pathway. To address this limitation, we examined Bacillus subtilis grown under multiple conditions and then determined the relationship between altered isoprene production and the pattern of gene expression. We found that terpenoid genes appeared to fall into two distinct subsets with opposing correlations with respect to the amount of isoprene produced. The group whose expression levels positively correlated with isoprene production included dxs, the gene responsible for the commitment step in the pathway, as well as ispD, and two genes that participate in the mevalonate pathway, yhfS and pksG. The subset of terpenoid genes that inversely correlated with isoprene production included ispH, ispF, hepS, uppS, ispE, and dxr. A genome wide partial least squares regression model was created to identify other genes or pathways that contribute to isoprene production. This analysis showed that a subset of 213 regulated genes was sufficient to create a predictive model of isoprene production under different conditions and showed correlations at the transcriptional level. We conclude that gene expression levels alone are sufficiently informative about the metabolic state of a cell that produces increased isoprene and can be used to build a model which accurately predicts production of this secondary metabolite across many simulated environmental conditions.

Regulatory networks in pollen development under cold stress

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Kamal Dev Sharma

2016-03-01

Full Text Available Cold stress modifies anthers’ metabolic pathways to induce pollen sterility. Cold-tolerant plants, unlike the susceptible ones, produce high proportion of viable pollen. Anthers in susceptible plants, when exposed to cold stress, increase abscisic acid (ABA metabolism and reduce ABA catabolism. Increased ABA negatively regulates expression of tapetum cell wall bound invertase and monosaccharide transport genes resulting in distorted carbohydrate pool in anther. Cold-stress also reduces endogenous levels of the bioactive gibberellins (GAs, GA4 and GA7, in susceptible anthers by repression of the GA biosynthesis genes. Here we discuss recent findings on mechanisms of cold susceptibility in anthers which determine pollen sterility. We also discuss differences in regulatory pathways between cold-stressed anthers of susceptible and tolerant plants that decide pollen sterility or viability.

Transcriptional profiles of SHH pathway genes in keratocystic odontogenic tumor and ameloblastoma.

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Gurgel, Clarissa Araújo Silva; Buim, Marcilei Eliza Cavichiolli; Carvalho, Kátia Cândido; Sales, Caroline Brandi Schlaepfer; Reis, Mitermayer Galvão; de Souza, Renata Oliveira; de Faro Valverde, Ludmila; de Azevedo, Roberto Almeida; Dos Santos, Jean Nunes; Soares, Fernando Augusto; Ramos, Eduardo Antônio Gonçalves

2014-09-01

Sonic hedgehog (SHH) pathway activation has been identified as a key factor in the development of many types of tumors, including odontogenic tumors. Our study examined the expression of genes in the SHH pathway to characterize their roles in the pathogenesis of keratocystic odontogenic tumors (KOT) and ameloblastomas (AB). We quantified the expression of SHH, SMO, PTCH1, SUFU, GLI1, CCND1, and BCL2 genes by qPCR in a total of 23 KOT, 11 AB, and three non-neoplastic oral mucosa (NNM). We also measured the expression of proteins related to this pathway (CCND1 and BCL2) by immunohistochemistry. We observed overexpression of SMO, PTCH1, GLI1, and CCND1 genes in both KOT (23/23) and AB (11/11). However, we did not detect expression of the SHH gene in 21/23 KOT and 10/11 AB tumors. Low levels of the SUFU gene were expressed in KOT (P = 0.0199) and AB (P = 0.0127) relative to the NNM. Recurrent KOT exhibited high levels of SMO (P = 0.035), PTCH1 (P = 0.048), CCND1 (P = 0.048), and BCL2 (P = 0.045) transcripts. Using immunolabeling of CCND1, we observed no statistical difference between primary and recurrent KOT (P = 0.8815), sporadic and NBCCS-KOT (P = 0.7688), and unicystic and solid AB (P = 0.7521). Overexpression of upstream (PTCH1 and SMO) and downstream (GLI1, CCND1 and BCL2) genes in the SHH pathway leads to the constitutive activation of this pathway in KOT and AB and may suggest a mechanism for the development of these types of tumors. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Affected pathways and transcriptional regulators in gene expression response to an ultra-marathon trail: Global and independent activity approaches.

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Maria Maqueda

Full Text Available Gene expression (GE analyses on blood samples from marathon and half-marathon runners have reported significant impacts on the immune and inflammatory systems. An ultra-marathon trail (UMT represents a greater effort due to its more testing conditions. For the first time, we report the genome-wide GE profiling in a group of 16 runners participating in an 82 km UMT competition. We quantified their differential GE profile before and after the race using HuGene2.0st microarrays (Affymetrix Inc., California, US. The results obtained were decomposed by means of an independent component analysis (ICA targeting independent expression modes. We observed significant differences in the expression levels of 5,084 protein coding genes resulting in an overrepresentation of 14% of the human biological pathways from the Kyoto Encyclopedia of Genes and Genomes database. These were mainly clustered on terms related with protein synthesis repression, altered immune system and infectious diseases related mechanisms. In a second analysis, 27 out of the 196 transcriptional regulators (TRs included in the Open Regulatory Annotation database were overrepresented. Among these TRs, we identified transcription factors from the hypoxia-inducible factors (HIF family EPAS1 (p< 0.01 and HIF1A (p<0.001, and others jointly described in the gluconeogenesis program such as HNF4 (p< 0.001, EGR1 (p<0.001, CEBPA (p< 0.001 and a highly specific TR, YY1 (p<0.01. The five independent components, obtained from ICA, further revealed a down-regulation of 10 genes distributed in the complex I, III and V from the electron transport chain. This mitochondrial activity reduction is compatible with HIF-1 system activation. The vascular endothelial growth factor (VEGF pathway, known to be regulated by HIF, also emerged (p<0.05. Additionally, and related to the brain rewarding circuit, the endocannabinoid signalling pathway was overrepresented (p<0.05.

A systems level approach reveals new gene regulatory modules in the developing ear

OpenAIRE

Chen, Jingchen; Tambalo, Monica; Barembaum, Meyer; Ranganathan, Ramya; Simões-Costa, Marcos; Bronner, Marianne E.; Streit, Andrea

2017-01-01

The inner ear is a complex vertebrate sense organ, yet it arises from a simple epithelium, the otic placode. Specification towards otic fate requires diverse signals and transcriptional inputs that act sequentially and/or in parallel. Using the chick embryo, we uncover novel genes in the gene regulatory network underlying otic commitment and reveal dynamic changes in gene expression. Functional analysis of selected transcription factors reveals the genetic hierarchy underlying the transition ...

Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities

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Fang, Xin; Sastry, Anand; Mih, Nathan; Kim, Donghyuk; Tan, Justin; Lloyd, Colton J.; Gao, Ye; Yang, Laurence; Palsson, Bernhard O.

2017-01-01

Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the Escherichia coli TRN—probably the best characterized TRN—several questions remain. Here, we address three questions: (i) How complete is our knowledge of the E. coli TRN; (ii) how well can we predict gene expression using this TRN; and (iii) how robust is our understanding of the TRN? First, we reconstructed a high-confidence TRN (hiTRN) consisting of 147 transcription factors (TFs) regulating 1,538 transcription units (TUs) encoding 1,764 genes. The 3,797 high-confidence regulatory interactions were collected from published, validated chromatin immunoprecipitation (ChIP) data and RegulonDB. For 21 different TF knockouts, up to 63% of the differentially expressed genes in the hiTRN were traced to the knocked-out TF through regulatory cascades. Second, we trained supervised machine learning algorithms to predict the expression of 1,364 TUs given TF activities using 441 samples. The algorithms accurately predicted condition-specific expression for 86% (1,174 of 1,364) of the TUs, while 193 TUs (14%) were predicted better than random TRNs. Third, we identified 10 regulatory modules whose definitions were robust against changes to the TRN or expression compendium. Using surrogate variable analysis, we also identified three unmodeled factors that systematically influenced gene expression. Our computational workflow comprehensively characterizes the predictive capabilities and systems-level functions of an organism’s TRN from disparate data types. PMID:28874552

Maternal vernalization and vernalization-pathway genes influence progeny seed germination.

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Auge, Gabriela A; Blair, Logan K; Neville, Hannah; Donohue, Kathleen

2017-10-01

Different life stages frequently respond to the same environmental cue to regulate development so that each life stage is matched to its appropriate season. We investigated how independently each life stage can respond to shared environmental cues, focusing on vernalization, in Arabidopsis thaliana plants. We first tested whether effects of rosette vernalization persisted to influence seed germination. To test whether genes in the vernalization flowering pathway also influence germination, we assessed germination of functional and nonfunctional alleles of these genes and measured their level of expression at different life stages in response to rosette vernalization. Rosette vernalization increased seed germination in diverse ecotypes. Genes in the vernalization flowering pathway also influenced seed germination. In the Columbia accession, functional alleles of most of these genes opposed the germination response observed in the ecotypes. Some genes influenced germination in a manner consistent with their known effects on FLOWERING LOCUS C gene regulation during the transition to flowering. Others did not, suggesting functional divergence across life stages. Despite persistent effects of environmental conditions across life stages, and despite pleiotropy of genes that affect both flowering and germination, the function of these genes can differ across life stages, potentially mitigating pleiotropic constraints and enabling independent environmental regulation of different life stages. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Construction and analysis of the transcription factor-microRNA co-regulatory network response to Mycobacterium tuberculosis: a view from the blood.

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Lin, Yan; Duan, Zipeng; Xu, Feng; Zhang, Jiayuan; Shulgina, Marina V; Li, Fan

2017-01-01

Mycobacterium tuberculosis ( Mtb ) infection has been regional outbreak, recently. The traditional focus on the patterns of "reductionism" which was associated with single molecular changes has been unable to meet the demand of early diagnosis and clinical application when current tuberculosis infection happened. In this study, we employed a systems biology approach to collect large microarray data sets including mRNAs and microRNAs (miRNAs) to identify the differentially expressed mRNAs and miRNAs in the whole blood of TB patients. The aim was to identify key genes associated with the immune response in the pathogenic process of tuberculosis by analyzing the co-regulatory network that was consisted of transcription factors and miRNAs as well as their target genes. The network along with their co-regulatory genes was analyzed utilizing Transcriptional Regulatory Element Database (TRED) and Database for Annotation, Visualization and Integrated Discovery (DAVID). We got 21 (19 up-regulated and 2 down-regulated) differentially expressed genes that were co-regulated by transcription factors and miRNAs. KEGG pathway enrichment analysis showed that the 21 differentially expressed genes were predominantly involved in Tuberculosis signaling pathway, which may play a major role in tuberculosis biological process. Quantitative real-time PCR was performed to verify the over expression of co-regulatory genes ( FCGR1A and CEBPB ). The genetic expression was correlated with clinicopathological characteristics in TB patients and inferences drawn. Our results suggest the TF-miRNA gene co-regulatory network may help us further understand the molecular mechanism of immune response to tuberculosis and provide us a new angle of future biomarker and therapeutic targets.

Regulatory Architecture of Gene Expression Variation in the Threespine Stickleback Gasterosteus aculeatus.

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Pritchard, Victoria L; Viitaniemi, Heidi M; McCairns, R J Scott; Merilä, Juha; Nikinmaa, Mikko; Primmer, Craig R; Leder, Erica H

2017-01-05

Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats. Copyright © 2017 Pritchard et al.

Modularity of gene-regulatory networks revealed in sea-star development

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Degnan Bernard M

2011-01-01

Full Text Available Abstract Evidence that conserved developmental gene-regulatory networks can change as a unit during deutersostome evolution emerges from a study published in BMC Biology. This shows that genes consistently expressed in anterior brain patterning in hemichordates and chordates are expressed in a similar spatial pattern in another deuterostome, an asteroid echinoderm (sea star, but in a completely different developmental context (the animal-vegetal axis. This observation has implications for hypotheses on the type of development present in the deuterostome common ancestor. See research article: http://www.biomedcentral.com/1741-7007/8/143/abstract

Quantitative trait loci and metabolic pathways

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McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

1998-01-01

The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

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

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

2018-02-01

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

Regulatory divergence of X-linked genes and hybrid male sterility in mice.

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Oka, Ayako; Shiroishi, Toshihiko

2014-01-01

Postzygotic reproductive isolation is the reduction of fertility or viability in hybrids between genetically diverged populations. One example of reproductive isolation, hybrid male sterility, may be caused by genetic incompatibility between diverged genetic factors in two distinct populations. Genetic factors involved in hybrid male sterility are disproportionately located on the X chromosome. Recent studies showing the evolutionary divergence in gene regulatory networks or epigenetic effects suggest that the genetic incompatibilities occur at much broader levels than had previously been thought (e.g., incompatibility of protein-protein interactions). The latest studies suggest that evolutionary divergence of transcriptional regulation causes genetic incompatibilities in hybrid animals, and that such incompatibilities preferentially involve X-linked genes. In this review, we focus on recent progress in understanding hybrid sterility in mice, including our studies, and we discuss the evolutionary significance of regulatory divergence for speciation.

Gene expression profiles reveal key pathways and genes associated with neuropathic pain in patients with spinal cord injury.

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He, Xijing; Fan, Liying; Wu, Zhongheng; He, Jiaxuan; Cheng, Bin

2017-04-01

Previous gene expression profiling studies of neuropathic pain (NP) following spinal cord injury (SCI) have predominantly been performed in animal models. The present study aimed to investigate gene alterations in patients with spinal cord injury and to further examine the mechanisms underlying NP following SCI. The GSE69901 gene expression profile was downloaded from the public Gene Expression Omnibus database. Samples of peripheral blood mononuclear cells (PBMCs) derived from 12 patients with intractable NP and 13 control patients without pain were analyzed to identify the differentially expressed genes (DEGs), followed by functional enrichment analysis and protein‑protein interaction (PPI) network construction. In addition, a transcriptional regulation network was constructed and functional gene clustering was performed. A total of 70 upregulated and 61 downregulated DEGs were identified in the PBMC samples from patients with NP. The upregulated and downregulated genes were significantly involved in different Gene Ontology terms and pathways, including focal adhesion, T cell receptor signaling pathway and mitochondrial function. Glycogen synthase kinase 3 β (GSK3B) was identified as a hub protein in the PPI network. In addition, ornithine decarboxylase 1 (ODC1) and ornithine aminotransferase (OAT) were regulated by additional transcription factors in the regulation network. GSK3B, OAT and ODC1 were significantly enriched in two functional gene clusters, the function of mitochondrial membrane and DNA binding. Focal adhesion and the T cell receptor signaling pathway may be significantly linked with NP, and GSK3B, OAT and ODC1 may be potential targets for the treatment of NP.