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

Directory of Open Access Journals (Sweden)

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.

Overproduction of lactimidomycin by cross-overexpression of genes encoding Streptomyces antibiotic regulatory proteins.

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Zhang, Bo; Yang, Dong; Yan, Yijun; Pan, Guohui; Xiang, Wensheng; Shen, Ben

2016-03-01

The glutarimide-containing polyketides represent a fascinating class of natural products that exhibit a multitude of biological activities. We have recently cloned and sequenced the biosynthetic gene clusters for three members of the glutarimide-containing polyketides-iso-migrastatin (iso-MGS) from Streptomyces platensis NRRL 18993, lactimidomycin (LTM) from Streptomyces amphibiosporus ATCC 53964, and cycloheximide (CHX) from Streptomyces sp. YIM56141. Comparative analysis of the three clusters identified mgsA and chxA, from the mgs and chx gene clusters, respectively, that were predicted to encode the PimR-like Streptomyces antibiotic regulatory proteins (SARPs) but failed to reveal any regulatory gene from the ltm gene cluster. Overexpression of mgsA or chxA in S. platensis NRRL 18993, Streptomyces sp. YIM56141 or SB11024, and a recombinant strain of Streptomyces coelicolor M145 carrying the intact mgs gene cluster has no significant effect on iso-MGS or CHX production, suggesting that MgsA or ChxA regulation may not be rate-limiting for iso-MGS and CHX production in these producers. In contrast, overexpression of mgsA or chxA in S. amphibiosporus ATCC 53964 resulted in a significant increase in LTM production, with LTM titer reaching 106 mg/L, which is five-fold higher than that of the wild-type strain. These results support MgsA and ChxA as members of the SARP family of positive regulators for the iso-MGS and CHX biosynthetic machinery and demonstrate the feasibility to improve glutarimide-containing polyketide production in Streptomyces strains by exploiting common regulators.

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.

Mutational robustness of gene regulatory networks.

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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.

A Regulatory Network Analysis of Orphan Genes in Arabidopsis Thaliana

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Singh, Pramesh; Chen, Tianlong; Arendsee, Zebulun; Wurtele, Eve S.; Bassler, Kevin E.

Orphan genes, which are genes unique to each particular species, have recently drawn significant attention for their potential usefulness for organismal robustness. Their origin and regulatory interaction patterns remain largely undiscovered. Recently, methods that use the context likelihood of relatedness to infer a network followed by modularity maximizing community detection algorithms on the inferred network to find the functional structure of regulatory networks were shown to be effective. We apply improved versions of these methods to gene expression data from Arabidopsis thaliana, identify groups (clusters) of interacting genes with related patterns of expression and analyze the structure within those groups. Focusing on clusters that contain orphan genes, we compare the identified clusters to gene ontology (GO) terms, regulons, and pathway designations and analyze their hierarchical structure. We predict new regulatory interactions and unravel the structure of the regulatory interaction patterns of orphan genes. Work supported by the NSF through Grants DMR-1507371 and IOS-1546858.

Learning gene regulatory networks from only positive and unlabeled data

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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)

Robustness and accuracy in sea urchin developmental gene regulatory networks

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Smadar eBen-Tabou De-Leon

2016-02-01

Full Text Available Developmental gene regulatory networks robustly control the timely activation of regulatory and differentiation genes. The structure of these networks underlies their capacity to buffer intrinsic and extrinsic noise and maintain embryonic morphology. Here I illustrate how the use of specific architectures by the sea urchin developmental regulatory networks enables the robust control of cell fate decisions. The Wnt-βcatenin signaling pathway patterns the primary embryonic axis while the BMP signaling pathway patterns the secondary embryonic axis in the sea urchin embryo and across bilateria. Interestingly, in the sea urchin in both cases, the signaling pathway that defines the axis controls directly the expression of a set of downstream regulatory genes. I propose that this direct activation of a set of regulatory genes enables a uniform regulatory response and a clear cut cell fate decision in the endoderm and in the dorsal ectoderm. The specification of the mesodermal pigment cell lineage is activated by Delta signaling that initiates a triple positive feedback loop that locks down the pigment specification state. I propose that the use of compound positive feedback circuitry provides the endodermal cells enough time to turn off mesodermal genes and ensures correct mesoderm vs. endoderm fate decision. Thus, I argue that understanding the control properties of repeatedly used regulatory architectures illuminates their role in embryogenesis and provides possible explanations to their resistance to evolutionary change.

Inferring the conservative causal core of gene regulatory networks

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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.

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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.

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.

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.

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.

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,

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.

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.

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

Cis-regulatory somatic mutations and gene-expression alteration in B-cell lymphomas.

Science.gov (United States)

Mathelier, Anthony; Lefebvre, Calvin; Zhang, Allen W; Arenillas, David J; Ding, Jiarui; Wasserman, Wyeth W; Shah, Sohrab P

2015-04-23

With the rapid increase of whole-genome sequencing of human cancers, an important opportunity to analyze and characterize somatic mutations lying within cis-regulatory regions has emerged. A focus on protein-coding regions to identify nonsense or missense mutations disruptive to protein structure and/or function has led to important insights; however, the impact on gene expression of mutations lying within cis-regulatory regions remains under-explored. We analyzed somatic mutations from 84 matched tumor-normal whole genomes from B-cell lymphomas with accompanying gene expression measurements to elucidate the extent to which these cancers are disrupted by cis-regulatory mutations. We characterize mutations overlapping a high quality set of well-annotated transcription factor binding sites (TFBSs), covering a similar portion of the genome as protein-coding exons. Our results indicate that cis-regulatory mutations overlapping predicted TFBSs are enriched in promoter regions of genes involved in apoptosis or growth/proliferation. By integrating gene expression data with mutation data, our computational approach culminates with identification of cis-regulatory mutations most likely to participate in dysregulation of the gene expression program. The impact can be measured along with protein-coding mutations to highlight key mutations disrupting gene expression and pathways in cancer. Our study yields specific genes with disrupted expression triggered by genomic mutations in either the coding or the regulatory space. It implies that mutated regulatory components of the genome contribute substantially to cancer pathways. Our analyses demonstrate that identifying genomically altered cis-regulatory elements coupled with analysis of gene expression data will augment biological interpretation of mutational landscapes of cancers.

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

Science.gov (United States)

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.

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.

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

Science.gov (United States)

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.

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

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

2012-01-01

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

DNA-binding site of major regulatory protein alpha 4 specifically associated with promoter-regulatory domains of alpha genes of herpes simplex virus type 1.

OpenAIRE

Kristie, T M; Roizman, B

1986-01-01

Herpes simplex virus type 1 genes form at least five groups (alpha, beta 1, beta 2, gamma 1, and gamma 2) whose expression is coordinately regulated and sequentially ordered in a cascade fashion. Previous studies have shown that functional alpha 4 gene product is essential for the transition from alpha to beta protein synthesis and have suggested that alpha 4 gene expression is autoregulatory. We have previously reported that labeled DNA fragments containing promoter-regulatory domains of thr...

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

Directory of Open Access Journals (Sweden)

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

Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

Science.gov (United States)

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

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.

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.

Gene Therapy With Regulatory T Cells: A Beneficial Alliance

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Moanaro Biswas

2018-03-01

Full Text Available Gene therapy aims to replace a defective or a deficient protein at therapeutic or curative levels. Improved vector designs have enhanced safety, efficacy, and delivery, with potential for lasting treatment. However, innate and adaptive immune responses to the viral vector and transgene product remain obstacles to the establishment of therapeutic efficacy. It is widely accepted that endogenous regulatory T cells (Tregs are critical for tolerance induction to the transgene product and in some cases the viral vector. There are two basic strategies to harness the suppressive ability of Tregs: in vivo induction of adaptive Tregs specific to the introduced gene product and concurrent administration of autologous, ex vivo expanded Tregs. The latter may be polyclonal or engineered to direct specificity to the therapeutic antigen. Recent clinical trials have advanced adoptive immunotherapy with Tregs for the treatment of autoimmune disease and in patients receiving cell transplants. Here, we highlight the potential benefit of combining gene therapy with Treg adoptive transfer to achieve a sustained transgene expression. Furthermore, techniques to engineer antigen-specific Treg cell populations, either through reprogramming conventional CD4+ T cells or transferring T cell receptors with known specificity into polyclonal Tregs, are promising in preclinical studies. Thus, based upon these observations and the successful use of chimeric (IgG-based antigen receptors (CARs in antigen-specific effector T cells, different types of CAR-Tregs could be added to the repertoire of inhibitory modalities to suppress immune responses to therapeutic cargos of gene therapy vectors. The diverse approaches to harness the ability of Tregs to suppress unwanted immune responses to gene therapy and their perspectives are reviewed in this article.

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.

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.

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...

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

Heterologous expression of the Aspergillus nidulans regulatory gene nirA in Fusarium oxysporum.

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Daboussi, M J; Langin, T; Deschamps, F; Brygoo, Y; Scazzocchio, C; Burger, G

1991-12-20

We have isolated strains of Fusarium oxysporum carrying mutations conferring a phenotype characteristic of a loss of function in the regulatory gene of nitrate assimilation (nirA in Aspergillus nidulans, nit-4 in Neurospora crassa). One of these nir- mutants was successfully transformed with a plasmid containing the nirA gene of A. nidulans. The nitrate reductase of the transformants is still inducible, although the maximum activity is lower than in the wild type. Single and multiple integration events were found, as well as a strict correlation between the presence of the nirA gene and the Nir+ phenotype of the F. oxysporum transformants. We also investigated how the A. nidulans structural gene (niaD) is regulated in F. oxysporum. Enzyme assays and Northern experiments show that the niaD gene is subject to nitrate induction and that it responds to nitrogen metabolite repression in a F. oxysporum genetic background. This indicates that both the mechanisms of specific induction, mediated by a gene product isofunctional to nirA, and nitrogen metabolite repression, presumably mediated by a gene product isofunctional to the homologous gene of A. nidulans, are operative in F. oxysporum.

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.

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

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

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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.

Heart morphogenesis gene regulatory networks revealed by temporal expression analysis.

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Hill, Jonathon T; Demarest, Bradley; Gorsi, Bushra; Smith, Megan; Yost, H Joseph

2017-10-01

During embryogenesis the heart forms as a linear tube that then undergoes multiple simultaneous morphogenetic events to obtain its mature shape. To understand the gene regulatory networks (GRNs) driving this phase of heart development, during which many congenital heart disease malformations likely arise, we conducted an RNA-seq timecourse in zebrafish from 30 hpf to 72 hpf and identified 5861 genes with altered expression. We clustered the genes by temporal expression pattern, identified transcription factor binding motifs enriched in each cluster, and generated a model GRN for the major gene batteries in heart morphogenesis. This approach predicted hundreds of regulatory interactions and found batteries enriched in specific cell and tissue types, indicating that the approach can be used to narrow the search for novel genetic markers and regulatory interactions. Subsequent analyses confirmed the GRN using two mutants, Tbx5 and nkx2-5 , and identified sets of duplicated zebrafish genes that do not show temporal subfunctionalization. This dataset provides an essential resource for future studies on the genetic/epigenetic pathways implicated in congenital heart defects and the mechanisms of cardiac transcriptional regulation. © 2017. Published by The Company of Biologists Ltd.

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.

SACE_5599, a putative regulatory protein, is involved in morphological differentiation and erythromycin production in Saccharopolyspora erythraea.

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Kirm, Benjamin; Magdevska, Vasilka; Tome, Miha; Horvat, Marinka; Karničar, Katarina; Petek, Marko; Vidmar, Robert; Baebler, Spela; Jamnik, Polona; Fujs, Štefan; Horvat, Jaka; Fonovič, Marko; Turk, Boris; Gruden, Kristina; Petković, Hrvoje; Kosec, Gregor

2013-12-17

D, SACE_5599 is involved in morphological development of S. erythraea, suggesting a very close relationship between secondary metabolite biosynthesis and morphological differentiation in this organism. While the mode of action of SACE_5599 remains to be elucidated, the manipulation of this gene clearly shows potential for improvement of erythromycin production in S. erythraea in industrial setting. We have also demonstrated the applicability of the comparative proteomics approach for identifying new regulatory elements involved in biosynthesis of secondary metabolites in industrial conditions.

The Reconstruction and Analysis of Gene Regulatory Networks.

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Zheng, Guangyong; Huang, Tao

2018-01-01

In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.

Engineering nucleases for gene targeting: safety and regulatory considerations.

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Pauwels, Katia; Podevin, Nancy; Breyer, Didier; Carroll, Dana; Herman, Philippe

2014-01-25

Nuclease-based gene targeting (NBGT) represents a significant breakthrough in targeted genome editing since it is applicable from single-celled protozoa to human, including several species of economic importance. Along with the fast progress in NBGT and the increasing availability of customized nucleases, more data are available about off-target effects associated with the use of this approach. We discuss how NBGT may offer a new perspective for genetic modification, we address some aspects crucial for a safety improvement of the corresponding techniques and we also briefly relate the use of NBGT applications and products to the regulatory oversight. Copyright © 2013 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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.

Cracking the regulatory code of biosynthetic gene clusters as a strategy for natural product discovery.

Science.gov (United States)

Rigali, Sébastien; Anderssen, Sinaeda; Naômé, Aymeric; van Wezel, Gilles P

2018-01-05

The World Health Organization (WHO) describes antibiotic resistance as "one of the biggest threats to global health, food security, and development today", as the number of multi- and pan-resistant bacteria is rising dangerously. Acquired resistance phenomena also impair antifungals, antivirals, anti-cancer drug therapy, while herbicide resistance in weeds threatens the crop industry. On the positive side, it is likely that the chemical space of natural products goes far beyond what has currently been discovered. This idea is fueled by genome sequencing of microorganisms which unveiled numerous so-called cryptic biosynthetic gene clusters (BGCs), many of which are transcriptionally silent under laboratory culture conditions, and by the fact that most bacteria cannot yet be cultivated in the laboratory. However, brute force antibiotic discovery does not yield the same results as it did in the past, and researchers have had to develop creative strategies in order to unravel the hidden potential of microorganisms such as Streptomyces and other antibiotic-producing microorganisms. Identifying the cis elements and their corresponding transcription factors(s) involved in the control of BGCs through bioinformatic approaches is a promising strategy. Theoretically, we are a few 'clicks' away from unveiling the culturing conditions or genetic changes needed to activate the production of cryptic metabolites or increase the production yield of known compounds to make them economically viable. In this opinion article, we describe and illustrate the idea beyond 'cracking' the regulatory code for natural product discovery, by presenting a series of proofs of concept, and discuss what still should be achieved to increase the rate of success of this strategy. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

Gene expression profiles of immune-regulatory genes in whole blood of cattle with a subclinical infection of Mycobacterium avium subsp. paratuberculosis.

Directory of Open Access Journals (Sweden)

Hyun-Eui Park

Full Text Available Johne's disease is a chronic wasting disease of ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP, resulting in inflammation of intestines and persistent diarrhea. The initial host response against MAP infections is mainly regulated by the Th1 response, which is characterized by the production of IFN-γ. With the progression of disease, MAP can survive in the host through the evasion of the host's immune response by manipulating the host immune response. However, the host response during subclinical phases has not been fully understood. Immune regulatory genes, including Th17-derived cytokines, interferon regulatory factors, and calcium signaling-associated genes, are hypothesized to play an important role during subclinical phases of Johne's disease. Therefore, the present study was conducted to analyze the expression profiles of immune regulatory genes during MAP infection in whole blood. Different expression patterns of genes were identified depending on the infection stages. Downregulation of IL-17A, IL-17F, IL-22, IL-26, HMGB1, and IRF4 and upregulation of PIP5K1C indicate suppression of the Th1 response due to MAP infection and loss of granuloma integrity. In addition, increased expression of IRF5 and IRF7 suggest activation of IFN-α/β signaling during subclinical stages, which induced indoleamine 2,3-dioxygenase mediated depletion of tryptophan metabolism. Increased expression of CORO1A indicate modulation of calcium signaling, which enhanced the survival of MAP. Taken together, distinct host gene expression induced by MAP infection indicates enhanced survival of MAP during subclinical stages.

Gene regulatory and signaling networks exhibit distinct topological distributions of motifs

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Ferreira, Gustavo Rodrigues; Nakaya, Helder Imoto; Costa, Luciano da Fontoura

2018-04-01

The biological processes of cellular decision making and differentiation involve a plethora of signaling pathways and gene regulatory circuits. These networks in turn exhibit a multitude of motifs playing crucial parts in regulating network activity. Here we compare the topological placement of motifs in gene regulatory and signaling networks and observe that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.

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.

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

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.

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

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

The Aspergillus flavus Homeobox Gene, hbx1, Is Required for Development and Aflatoxin Production

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Jeffrey W. Cary

2017-10-01

Full Text Available Homeobox proteins, a class of well conserved transcription factors, regulate the expression of targeted genes, especially those involved in development. In filamentous fungi, homeobox genes are required for normal conidiogenesis and fruiting body formation. In the present study, we identified eight homeobox (hbx genes in the aflatoxin-producing ascomycete, Aspergillus flavus, and determined their respective role in growth, conidiation and sclerotial production. Disruption of seven of the eight genes had little to no effect on fungal growth and development. However, disruption of the homeobox gene AFLA_069100, designated as hbx1, in two morphologically different A. flavus strains, CA14 and AF70, resulted in complete loss of production of conidia and sclerotia as well as aflatoxins B1 and B2, cyclopiazonic acid and aflatrem. Microscopic examination showed that the Δhbx1 mutants did not produce conidiophores. The inability of Δhbx1 mutants to produce conidia was related to downregulation of brlA (bristle and abaA (abacus, regulatory genes for conidiophore development. These mutants also had significant downregulation of the aflatoxin pathway biosynthetic genes aflC, aflD, aflM and the cluster-specific regulatory gene, aflR. Our results demonstrate that hbx1 not only plays a significant role in controlling A. flavus development but is also critical for the production of secondary metabolites, such as aflatoxins.

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.

Current status of herbal product: Regulatory overview

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Sharma, Sanjay

2015-01-01

A review of the regulatory status of herbal drugs/products was done for few countries forming part of Asia, Africa, America, Europe, and Australia, to understand various categories under which the trade of herbal products is permitted and their premarketing requirements. A critical assessment was done, to know the hindrances in the process of harmonization of herbal products. It has been found that there is a lack of harmonization in the regulatory requirements of herbal products internationally, besides the issues of availability of herbs and their conservation. These are hindering the international trade and growth of the herbal products segment. PMID:26681886

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.

State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference

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Tuqyah Abdullah Al Qazlan

2015-01-01

Full Text Available To address one of the most challenging issues at the cellular level, this paper surveys the fuzzy methods used in gene regulatory networks (GRNs inference. GRNs represent causal relationships between genes that have a direct influence, trough protein production, on the life and the development of living organisms and provide a useful contribution to the understanding of the cellular functions as well as the mechanisms of diseases. Fuzzy systems are based on handling imprecise knowledge, such as biological information. They provide viable computational tools for inferring GRNs from gene expression data, thus contributing to the discovery of gene interactions responsible for specific diseases and/or ad hoc correcting therapies. Increasing computational power and high throughput technologies have provided powerful means to manage these challenging digital ecosystems at different levels from cell to society globally. The main aim of this paper is to report, present, and discuss the main contributions of this multidisciplinary field in a coherent and structured framework.

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.

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

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.

RNA-Seq of Bacillus licheniformis: active regulatory RNA features expressed within a productive fermentation

Science.gov (United States)

2013-01-01

Background The production of enzymes by an industrial strain requires a complex adaption of the bacterial metabolism to the conditions within the fermenter. Regulatory events within the process result in a dynamic change of the transcriptional activity of the genome. This complex network of genes is orchestrated by proteins as well as regulatory RNA elements. Here we present an RNA-Seq based study considering selected phases of an industry-oriented fermentation of Bacillus licheniformis. Results A detailed analysis of 20 strand-specific RNA-Seq datasets revealed a multitude of transcriptionally active genomic regions. 3314 RNA features encoded by such active loci have been identified and sorted into ten functional classes. The identified sequences include the expected RNA features like housekeeping sRNAs, metabolic riboswitches and RNA switches well known from studies on Bacillus subtilis as well as a multitude of completely new candidates for regulatory RNAs. An unexpectedly high number of 855 RNA features are encoded antisense to annotated protein and RNA genes, in addition to 461 independently transcribed small RNAs. These antisense transcripts contain molecules with a remarkable size range variation from 38 to 6348 base pairs in length. The genome of the type strain B. licheniformis DSM13 was completely reannotated using data obtained from RNA-Seq analyses and from public databases. Conclusion The hereby generated data-sets represent a solid amount of knowledge on the dynamic transcriptional activities during the investigated fermentation stages. The identified regulatory elements enable research on the understanding and the optimization of crucial metabolic activities during a productive fermentation of Bacillus licheniformis strains. PMID:24079885

RNA-Seq of Bacillus licheniformis: active regulatory RNA features expressed within a productive fermentation.

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Wiegand, Sandra; Dietrich, Sascha; Hertel, Robert; Bongaerts, Johannes; Evers, Stefan; Volland, Sonja; Daniel, Rolf; Liesegang, Heiko

2013-10-01

The production of enzymes by an industrial strain requires a complex adaption of the bacterial metabolism to the conditions within the fermenter. Regulatory events within the process result in a dynamic change of the transcriptional activity of the genome. This complex network of genes is orchestrated by proteins as well as regulatory RNA elements. Here we present an RNA-Seq based study considering selected phases of an industry-oriented fermentation of Bacillus licheniformis. A detailed analysis of 20 strand-specific RNA-Seq datasets revealed a multitude of transcriptionally active genomic regions. 3314 RNA features encoded by such active loci have been identified and sorted into ten functional classes. The identified sequences include the expected RNA features like housekeeping sRNAs, metabolic riboswitches and RNA switches well known from studies on Bacillus subtilis as well as a multitude of completely new candidates for regulatory RNAs. An unexpectedly high number of 855 RNA features are encoded antisense to annotated protein and RNA genes, in addition to 461 independently transcribed small RNAs. These antisense transcripts contain molecules with a remarkable size range variation from 38 to 6348 base pairs in length. The genome of the type strain B. licheniformis DSM13 was completely reannotated using data obtained from RNA-Seq analyses and from public databases. The hereby generated data-sets represent a solid amount of knowledge on the dynamic transcriptional activities during the investigated fermentation stages. The identified regulatory elements enable research on the understanding and the optimization of crucial metabolic activities during a productive fermentation of Bacillus licheniformis strains.

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

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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.

Portrait of Candida Species Biofilm Regulatory Network Genes.

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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.

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

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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.

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.

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...

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...

redD and actII-ORF4, Pathway-Specific Regulatory Genes for Antibiotic Production in Streptomyces coelicolor A3(2), Are Transcribed In Vitro by an RNA Polymerase Holoenzyme Containing σhrdD

NARCIS (Netherlands)

Fujii, T.; Gramajo, H.C.; Takano, E.; Bibb, M.J.

1996-01-01

redD and actII-ORF4, regulatory genes required for synthesis of the antibiotics undecylprodigiosin and actinorhodin by Streptomyces coelicolor A3(2), were transcribed in vitro by an RNA polymerase holoenzyme containing σhrdD. Disruption of hrdD had no effect on antibiotic production, indicating that

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…

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.

Science.gov (United States)

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.

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.

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.

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

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

Science.gov (United States)

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.

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

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.

A discrete transition zone organizes the topological and regulatory autonomy of the adjacent tfap2c and bmp7 genes.

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Taro Tsujimura

2015-01-01

Full Text Available Despite the well-documented role of remote enhancers in controlling developmental gene expression, the mechanisms that allocate enhancers to genes are poorly characterized. Here, we investigate the cis-regulatory organization of the locus containing the Tfap2c and Bmp7 genes in vivo, using a series of engineered chromosomal rearrangements. While these genes lie adjacent to one another, we demonstrate that they are independently regulated by distinct sets of enhancers, which in turn define non-overlapping regulatory domains. Chromosome conformation capture experiments reveal a corresponding partition of the locus in two distinct structural entities, demarcated by a discrete transition zone. The impact of engineered chromosomal rearrangements on the topology of the locus and the resultant gene expression changes indicate that this transition zone functionally organizes the structural partition of the locus, thereby defining enhancer-target gene allocation. This partition is, however, not absolute: we show that it allows competing interactions across it that may be non-productive for the competing gene, but modulate expression of the competed one. Altogether, these data highlight the prime role of the topological organization of the genome in long-distance regulation of gene expression.

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.

Modernizing the Regulatory System for Biotechnology Products

Science.gov (United States)

This Web page describes the continuing effort to modernize the federal regulatory system for biotechnology products as well as clarify various roles of EPA, FDA and USDA in evaluating new biotechnology products.

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

Directory of Open Access Journals (Sweden)

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

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...

Gene Editing of Microalgae: Scientific Progress and Regulatory Challenges in Europe.

Science.gov (United States)

Spicer, Andrew; Molnar, Attila

2018-03-06

It is abundantly clear that the development of gene editing technologies, represents a potentially powerful force for good with regard to human and animal health and addressing the challenges we continue to face in a growing global population. This now includes the development of approaches to modify microalgal strains for potential improvements in productivity, robustness, harvestability, processability, nutritional composition, and application. The rapid emergence and ongoing developments in this area demand a timely review and revision of the current definitions and regulations around genetically modified organisms (GMOs), particularly within Europe. Current practices within the EU provide exemptions from the GMO directives for organisms, including crop plants and micro-organisms that are produced through chemical or UV/radiation mutagenesis. However, organisms generated through gene editing, including microalgae, where only genetic changes in native genes are made, remain currently under the GMO umbrella; they are, as such, excluded from practical and commercial opportunities in the EU. In this review, we will review the advances that are being made in the area of gene editing in microalgae and the impact of regulation on commercial advances in this area with consideration to the current regulatory framework as it relates to GMOs including GM microalgae in Europe.

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

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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.

National Strategy for Modernizing the Regulatory System for Biotechnology Products

Science.gov (United States)

This National Strategy for Modernizing the Regulatory System for Biotechnology Products sets forth a vision for ensuring that the federal regulatory system is prepared to efficiently assess the risks, if any, of the future products of biotechnology.

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...

Characterization of a putative cis-regulatory element that controls transcriptional activity of the pig uroplakin II gene promoter

International Nuclear Information System (INIS)

Kwon, Deug-Nam; Park, Mi-Ryung; Park, Jong-Yi; Cho, Ssang-Goo; Park, Chankyu; Oh, Jae-Wook; Song, Hyuk; Kim, Jae-Hwan; Kim, Jin-Hoi

2011-01-01

Highlights: → The sequences of -604 to -84 bp of the pUPII promoter contained the region of a putative negative cis-regulatory element. → The core promoter was located in the 5F-1. → Transcription factor HNF4 can directly bind in the pUPII core promoter region, which plays a critical role in controlling promoter activity. → These features of the pUPII promoter are fundamental to development of a target-specific vector. -- Abstract: Uroplakin II (UPII) is a one of the integral membrane proteins synthesized as a major differentiation product of mammalian urothelium. UPII gene expression is bladder specific and differentiation dependent, but little is known about its transcription response elements and molecular mechanism. To identify the cis-regulatory elements in the pig UPII (pUPII) gene promoter region, we constructed pUPII 5' upstream region deletion mutants and demonstrated that each of the deletion mutants participates in controlling the expression of the pUPII gene in human bladder carcinoma RT4 cells. We also identified a new core promoter region and putative negative cis-regulatory element within a minimal promoter region. In addition, we showed that hepatocyte nuclear factor 4 (HNF4) can directly bind in the pUPII core promoter (5F-1) region, which plays a critical role in controlling promoter activity. Transient cotransfection experiments showed that HNF4 positively regulates pUPII gene promoter activity. Thus, the binding element and its binding protein, HNF4 transcription factor, may be involved in the mechanism that specifically regulates pUPII gene transcription.

SNPs in the 5'-regulatory region of the tyrosinase gene do not affect plumage color in ducks (Anas platyrhynchos).

Science.gov (United States)

Zhang, N N; Hu, J W; Liu, H H; Xu, H Y; He, H; Li, L

2015-12-29

Tyrosinase, encoded by the TYR gene, is the rate-limiting enzyme in the production of melanin pigment. In this study, plumage color separation was observed in Cherry Valley duck line D and F1 and F2 hybrid generations of Liancheng white ducks. Gene sequencing and bioinformatic analysis were applied to the 5'-regulatory region of TYR, to explore the connection between TYR sequence variation and duck plumage color. Four SNPs were found in the 5'-regulatory region. The SNPs were in tight linkage and formed three haplotypes. However, the genotype distribution in groups with different plumage color was not significantly different, and there were no changes in the transcription factor binding sites between the different genotypes. In conclusion, these SNP variations may not cause the differences in feather color observed in this test group.

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).

Production of recombinant AAV vectors encoding insulin-like growth factor I is enhanced by interaction among AAV rep regulatory sequences

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Dilley Robert

2009-01-01

Full Text Available Abstract Background Adeno-associated virus (AAV vectors are promising tools for gene therapy. Currently, their potential is limited by difficulties in producing high vector yields with which to generate transgene protein product. AAV vector production depends in part upon the replication (Rep proteins required for viral replication. We tested the hypothesis that mutations in the start codon and upstream regulatory elements of Rep78/68 in AAV helper plasmids can regulate recombinant AAV (rAAV vector production. We further tested whether the resulting rAAV vector preparation augments the production of the potentially therapeutic transgene, insulin-like growth factor I (IGF-I. Results We constructed a series of AAV helper plasmids containing different Rep78/68 start codon in combination with different gene regulatory sequences. rAAV vectors carrying the human IGF-I gene were prepared with these vectors and the vector preparations used to transduce HT1080 target cells. We found that the substitution of ATG by ACG in the Rep78/68 start codon in an AAV helper plasmid (pAAV-RC eliminated Rep78/68 translation, rAAV and IGF-I production. Replacement of the heterologous sequence upstream of Rep78/68 in pAAV-RC with the AAV2 endogenous p5 promoter restored translational activity to the ACG mutant, and restored rAAV and IGF-I production. Insertion of the AAV2 p19 promoter sequence into pAAV-RC in front of the heterologous sequence also enabled ACG to function as a start codon for Rep78/68 translation. The data further indicate that the function of the AAV helper construct (pAAV-RC, that is in current widespread use for rAAV production, may be improved by replacement of its AAV2 unrelated heterologous sequence with the native AAV2 p5 promoter. Conclusion Taken together, the data demonstrate an interplay between the start codon and upstream regulatory sequences in the regulation of Rep78/68 and indicate that selective mutations in Rep78/68 regulatory elements

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

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

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

Science.gov (United States)

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.

Directory of Open Access Journals (Sweden)

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.

Isoeugenol monooxygenase and its putative regulatory gene are located in the eugenol metabolic gene cluster in Pseudomonas nitroreducens Jin1.

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Ryu, Ji-Young; Seo, Jiyoung; Unno, Tatsuya; Ahn, Joong-Hoon; Yan, Tao; Sadowsky, Michael J; Hur, Hor-Gil

2010-03-01

The plant-derived phenylpropanoids eugenol and isoeugenol have been proposed as useful precursors for the production of natural vanillin. Genes involved in the metabolism of eugenol and isoeugenol were clustered in region of about a 30 kb of Pseudomonas nitroreducens Jin1. Two of the 23 ORFs in this region, ORFs 26 (iemR) and 27 (iem), were predicted to be involved in the conversion of isoeugenol to vanillin. The deduced amino acid sequence of isoeugenol monooxygenase (Iem) of strain Jin1 had 81.4% identity to isoeugenol monooxygenase from Pseudomonas putida IE27, which also transforms isoeugenol to vanillin. Iem was expressed in E. coli BL21(DE3) and was found to lead to isoeugenol to vanillin transformation. Deletion and cloning analyses indicated that the gene iemR, located upstream of iem, is required for expression of iem in the presence of isoeugenol, suggesting it to be the iem regulatory gene. Reverse transcription, real-time PCR analyses indicated that the genes involved in the metabolism of eugenol and isoeugenol were differently induced by isoeugenol, eugenol, and vanillin.

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

Disruption of the nitrogen regulatory gene AcareA in Acremonium chrysogenum leads to reduction of cephalosporin production and repression of nitrogen metabolism.

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Li, Jinyang; Pan, Yuanyuan; Liu, Gang

2013-12-01

AcareA, encoding a homologue of the fungal nitrogen regulatory GATA zinc-finger proteins, was cloned from Acremonium chrysogenum. Gene disruption and genetic complementation revealed that AcareA was required for nitrogen metabolism and cephalosporin production. Disruption of AcareA resulted in growth defect in the medium using nitrate, uric acid and low concentration of ammonium, glutamine or urea as sole nitrogen source. Transcriptional analysis showed that the transcription of niaD/niiA was increased drastically when induced with nitrate in the wild-type and AcareA complemented strains but not in AcareA disruption mutant. Consistent with the reduction of cephalosporin production, the transcription of pcbAB, cefD2, cefEF and cefG encoding the enzymes for cephalosporin production was reduced in AcareA disruption mutant. Band shift assays showed that AcAREA bound to the promoter regions of niaD, niiA and the bidirectional promoter region of pcbAB-pcbC. Sequence analysis showed that all the AcAREA binding sites contain the consensus GATA elements. These results indicated that AcAREA plays an important role both in the regulation of nitrogen metabolism and cephalosporin production in A. chrysogenum. Copyright © 2013 Elsevier Inc. All rights reserved.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

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Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information

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

Regulatory network controlling extracellular proteins in Erwinia carotovora subsp. carotovora: FlhDC, the master regulator of flagellar genes, activates rsmB regulatory RNA production by affecting gacA and hexA (lrhA) expression.

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Cui, Yaya; Chatterjee, Asita; Yang, Hailian; Chatterjee, Arun K

2008-07-01

Erwinia carotovora subsp. carotovora produces an array of extracellular proteins (i.e., exoproteins), including plant cell wall-degrading enzymes and Harpin, an effector responsible for eliciting hypersensitive reaction. Exoprotein genes are coregulated by the quorum-sensing signal, N-acyl homoserine lactone, plant signals, an assortment of transcriptional factors/regulators (GacS/A, ExpR1, ExpR2, KdgR, RpoS, HexA, and RsmC) and posttranscriptional regulators (RsmA, rsmB RNA). rsmB RNA production is positively regulated by GacS/A, a two-component system, and negatively regulated by HexA (PecT in Erwinia chrysanthemi; LrhA [LysR homolog A] in Escherichia coli) and RsmC, a putative transcriptional adaptor. While free RsmA, an RNA-binding protein, promotes decay of mRNAs of exoprotein genes, binding of RsmA with rsmB RNA neutralizes the RsmA effect. In the course of studies of GacA regulation, we discovered that a locus bearing strong homology to the flhDC operon of E. coli also controls extracellular enzyme production. A transposon insertion FlhDC(-) mutant produces very low levels of pectate lyase, polygalacturonase, cellulase, protease, and E. carotovora subsp. carotovora Harpin (Harpin(Ecc)) and is severely attenuated in its plant virulence. The production of these exoproteins is restored in the mutant carrying an FlhDC(+) plasmid. Sequence analysis and transcript assays disclosed that the flhD operon of E. carotovora subsp. carotovora, like those of other enterobacteria, consists of flhD and flhC. Complementation analysis revealed that the regulatory effect requires functions of both flhD and flhC products. The data presented here show that FlhDC positively regulates gacA, rsmC, and fliA and negatively regulates hexA (lrhA). Evidence shows that FlhDC controls extracellular protein production through cumulative effects on hexA and gacA. Reduced levels of GacA and elevated levels of HexA in the FlhDC(-) mutant are responsible for the inhibition of rsmB RNA

Regulatory Network Controlling Extracellular Proteins in Erwinia carotovora subsp. carotovora: FlhDC, the Master Regulator of Flagellar Genes, Activates rsmB Regulatory RNA Production by Affecting gacA and hexA (lrhA) Expression▿

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Cui, Yaya; Chatterjee, Asita; Yang, Hailian; Chatterjee, Arun K.

2008-01-01

Erwinia carotovora subsp. carotovora produces an array of extracellular proteins (i.e., exoproteins), including plant cell wall-degrading enzymes and Harpin, an effector responsible for eliciting hypersensitive reaction. Exoprotein genes are coregulated by the quorum-sensing signal, N-acyl homoserine lactone, plant signals, an assortment of transcriptional factors/regulators (GacS/A, ExpR1, ExpR2, KdgR, RpoS, HexA, and RsmC) and posttranscriptional regulators (RsmA, rsmB RNA). rsmB RNA production is positively regulated by GacS/A, a two-component system, and negatively regulated by HexA (PecT in Erwinia chrysanthemi; LrhA [LysR homolog A] in Escherichia coli) and RsmC, a putative transcriptional adaptor. While free RsmA, an RNA-binding protein, promotes decay of mRNAs of exoprotein genes, binding of RsmA with rsmB RNA neutralizes the RsmA effect. In the course of studies of GacA regulation, we discovered that a locus bearing strong homology to the flhDC operon of E. coli also controls extracellular enzyme production. A transposon insertion FlhDC− mutant produces very low levels of pectate lyase, polygalacturonase, cellulase, protease, and E. carotovora subsp. carotovora Harpin (HarpinEcc) and is severely attenuated in its plant virulence. The production of these exoproteins is restored in the mutant carrying an FlhDC+ plasmid. Sequence analysis and transcript assays disclosed that the flhD operon of E. carotovora subsp. carotovora, like those of other enterobacteria, consists of flhD and flhC. Complementation analysis revealed that the regulatory effect requires functions of both flhD and flhC products. The data presented here show that FlhDC positively regulates gacA, rsmC, and fliA and negatively regulates hexA (lrhA). Evidence shows that FlhDC controls extracellular protein production through cumulative effects on hexA and gacA. Reduced levels of GacA and elevated levels of HexA in the FlhDC− mutant are responsible for the inhibition of rsmB RNA production

What's the Regulatory Value of a Target Product Profile?

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Breder, Christopher D; Du, Wenny; Tyndall, Adria

2017-07-01

Target product profiles (TPPs) are used as a regulatory tool for dialog on clinical development or manufacturing plans. Drugs and biologics approved by the FDA that mention TPPs are associated with more efficient regulatory review times, perhaps as a result of increased planning or because the TPP promotes well-organized regulatory dialog. Published by Elsevier Ltd.

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

Conservation of lipid metabolic gene transcriptional regulatory networks in fish and mammals.

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Carmona-Antoñanzas, Greta; Tocher, Douglas R; Martinez-Rubio, Laura; Leaver, Michael J

2014-01-15

Lipid content and composition in aquafeeds have changed rapidly as a result of the recent drive to replace ecologically limited marine ingredients, fishmeal and fish oil (FO). Terrestrial plant products are the most economic and sustainable alternative; however, plant meals and oils are devoid of physiologically important cholesterol and long-chain polyunsaturated fatty acids (LC-PUFA), eicosapentaenoic (EPA), docosahexaenoic (DHA) and arachidonic (ARA) acids. Although replacement of dietary FO with vegetable oil (VO) has little effect on growth in Atlantic salmon (Salmo salar), several studies have shown major effects on the activity and expression of genes involved in lipid homeostasis. In vertebrates, sterols and LC-PUFA play crucial roles in lipid metabolism by direct interaction with lipid-sensing transcription factors (TFs) and consequent regulation of target genes. The primary aim of the present study was to elucidate the role of key TFs in the transcriptional regulation of lipid metabolism in fish by transfection and overexpression of TFs. The results show that the expression of genes of LC-PUFA biosynthesis (elovl and fads2) and cholesterol metabolism (abca1) are regulated by Lxr and Srebp TFs in salmon, indicating highly conserved regulatory mechanism across vertebrates. In addition, srebp1 and srebp2 mRNA respond to replacement of dietary FO with VO. Thus, Atlantic salmon adjust lipid metabolism in response to dietary lipid composition through the transcriptional regulation of gene expression. It may be possible to further increase efficient and effective use of sustainable alternatives to marine products in aquaculture by considering these important molecular interactions when formulating diets. © 2013.

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.

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.

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.

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

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 ...

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.

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

International Nuclear Information System (INIS)

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.

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.

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

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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

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

Directory of Open Access Journals (Sweden)

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.

Transcriptional regulation of genes related to progesterone production.

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Mizutani, Tetsuya; Ishikane, Shin; Kawabe, Shinya; Umezawa, Akihiro; Miyamoto, Kaoru

2015-01-01

Steroid hormones are synthesized from cholesterol in various tissues, mainly in the adrenal glands and gonads. Because these lipid-soluble steroid hormones immediately diffuse through the cells in which they are produced, their secretion directly reflects the activity of the genes related to their production. Progesterone is important not only for luteinization and maintenance of pregnancy, but also as a substrate for most other steroids. Steroidogenic acute regulatory protein (STAR), cytochrome P450 cholesterol side-chain cleavage enzyme (P450scc), and 3β-hydroxysteroid dehydrogenase/Δ(5)-Δ(4) isomerase (3β-HSD) are well-known proteins essential for progesterone production. In addition to them, glutathione S-transferase A1-1 and A3-3 are shown to exert Δ(5)-Δ(4) isomerization activity to produce progesterone in a cooperative fashion with 3β-HSD. 5-Aminolevulinic acid synthase 1, ferredoxin 1, and ferredoxin reductase also play a role in steroidogenesis as accessory factors. Members of the nuclear receptor 5A (NR5A) family (steroidogenic factor 1 and liver receptor homolog 1) play a crucial role in the transcriptional regulation of these genes. The NR5A family activates these genes by binding to NR5A responsive elements present within their promoter regions, as well as to the elements far from their promoters. In addition, various NR5A-interacting proteins including peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α), nuclear receptor subfamily 0, group B, member 1 (DAX-1), and CCAAT/enhancer-binding proteins (C/EBP) are involved in the transcription of NR5A target genes and regulate the transcription either positively or negatively under both basal and tropic hormone-stimulated conditions. In this review, we describe the transcriptional regulation of genes related to progesterone production.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks

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Lepoivre Cyrille

2012-01-01

Full Text Available Abstract Background Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. Results We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices, (ii potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii regulatory interactions curated from the literature, (iv predicted post-transcriptional regulation by micro-RNA, (v protein kinase-substrate interactions and (vi physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration

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.

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

Characterization of regulatory pathways in Xylella fastidiosa: genes and phenotypes controlled by algU.

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Shi, Xiang Yang; Dumenyo, C Korsi; Hernandez-Martinez, Rufina; Azad, Hamid; Cooksey, Donald A

2007-11-01

Many virulence genes in plant bacterial pathogens are coordinately regulated by "global" regulatory genes. Conducting DNA microarray analysis of bacterial mutants of such genes, compared with the wild type, can help to refine the list of genes that may contribute to virulence in bacterial pathogens. The regulatory gene algU, with roles in stress response and regulation of the biosynthesis of the exopolysaccharide alginate in Pseudomonas aeruginosa and many other bacteria, has been extensively studied. The role of algU in Xylella fastidiosa, the cause of Pierce's disease of grapevines, was analyzed by mutation and whole-genome microarray analysis to define its involvement in aggregation, biofilm formation, and virulence. In this study, an algU::nptII mutant had reduced cell-cell aggregation, attachment, and biofilm formation and lower virulence in grapevines. Microarray analysis showed that 42 genes had significantly lower expression in the algU::nptII mutant than in the wild type. Among these are several genes that could contribute to cell aggregation and biofilm formation, as well as other physiological processes such as virulence, competition, and survival.

Drug-device combination products: regulatory landscape and market growth.

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Bayarri, L

2015-08-01

Combination products are therapeutic and diagnostic products that combine drugs, devices and/or biological products, leading to safer and more effective treatments thanks to careful and precise drug targeting, local administration and individualized therapy. These technologies can especially benefit patients suffering from serious diseases and conditions such as cancer, heart disease, multiple sclerosis and diabetes, among others. On the other hand, drug-device combination products have also introduced a new dynamic in medical product development, regulatory approval and corporate interaction. Due to the increasing integration of drugs and devices observed in the latest generation of combination products, regulatory agencies have developed specific competences and regulations over the last decade. Manufacturers are required to fully understand the specific requirements in each country in order to ensure timely and accurate market access of new combination products, and the development of combination products involves a very specific pattern of interactions between manufacturers and regulatory agencies. The increased sophistication of the products brought to market over the last couple of decades has accentuated the need to develop drugs and devices collaboratively using resources from both industries, fostering the need of business partnering and technology licensing. This review will provide a global overview of the market trends, as well as (in the last section) an analysis of the drug-device combination products approved by the FDA during the latest 5 years. Copyright 2015 Prous Science, S.A.U. or its licensors. All rights reserved.

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.

A PTEN-COL17A1 fusion gene and its novel regulatory role in Collagen XVII expression and GBM malignance.

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Yan, Xiaoyan; Zhang, Chuanbao; Liang, Tingyu; Yang, Fan; Wang, Haoyuan; Wu, Fan; Wang, Wen; Wang, Zheng; Cheng, Wen; Xu, Jiangnan; Jiang, Tao; Chen, Jing; Ding, Yaozhong

2017-10-17

Collagen XVII expression has recently been demonstrated to be correlated with the tumor malignance. While Collagen XVII is known to be widely distributed in neurons of the human brain, its precise role in pathogenesis of glioblastoma multiforme (GBM) is unknown. In this study, we identified and characterized a new PTEN-COL17A1 fusion gene in GMB using transcriptome sequencing. Although fusion gene did not result in measurable fusion protein production, its presence is accompanied with high levels of COL17A1 expression, revealed a novel regulatory mechanism of Collagen XVII expression by PTEN-COL17A1 gene fusion. Knocked down Collagen XVII expression in glioma cell lines resulted in decreased tumor invasiveness, along with significant reduction of MMP9 expression, while increased Collagen XVII expression promotes invasive activities of glioma cells and associated with GBM recurrences. Together, our results uncovered a new PTEN-COL17A1 fusion gene and its novel regulatory role in Collagen XVII expression and GBM malignance, and demonstrated that COL17A1 could serve as a useful prognostic biomarker and therapeutic targets for GBM.

Potent Nematicidal Activity and New Hybrid Metabolite Production by Disruption of a Cytochrome P450 Gene Involved in the Biosynthesis of Morphological Regulatory Arthrosporols in Nematode-Trapping Fungus Arthrobotrys oligospora.

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Song, Tian-Yang; Xu, Zi-Fei; Chen, Yong-Hong; Ding, Qiu-Yan; Sun, Yu-Rong; Miao, Yang; Zhang, Ke-Qin; Niu, Xue-Mei

2017-05-24

Types of polyketide synthase-terpenoid synthase (PKS-TPS) hybrid metabolites, including arthrosporols with significant morphological regulatory activity, have been elucidated from nematode-trapping fungus Arthrobotrys oligospora. A previous study suggested that the gene cluster AOL_s00215 in A. oligospora was involved in the production of arthrosporols. Here, we report that disruption of one cytochrome P450 monooxygenase gene AOL_s00215g280 in the cluster resulted in significant phenotypic difference and much aerial hyphae. A further bioassay indicated that the mutant showed a dramatic decrease in the conidial formation but developed numerous traps and killed 85% nematodes within 6 h in contact with prey, in sharp contrast to the wild-type strain with no obvious response. Chemical investigation revealed huge accumulation of three new PKS-TPS epoxycyclohexone derivatives with different oxygenated patterns around the epoxycyclohexone moiety and the absence of arthrosporols in the cultural broth of the mutant ΔAOL_s00215g280. These findings suggested that a study on the biosynthetic pathway for morphological regulatory metabolites in nematode-trapping fungus would provide an efficient way to develop new fungal biocontrol agents.

A critical assessment of regulatory triggers for products of biotechnology: Product vs. process

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McHughen, Alan

2016-01-01

ABSTRACT Regulatory policies governing the safety of genetic engineering (rDNA) and the resulting products (GMOs) have been contentious and divisive, especially in agricultural applications of the technologies. These tensions led to vastly different approaches to safety regulation in different jurisdictions, even though the intent of regulations—to assure public and environmental safety—are common worldwide, and even though the international scientific communities agree on the basic principles of risk assessment and risk management. So great are the political divisions that jurisdictions cannot even agree on the appropriate triggers for regulatory capture, whether product or process. This paper reviews the historical policy and scientific implications of agricultural biotechnology regulatory approaches taken by the European Union, USA and Canada, using their respective statutes and regulations, and then critically assesses the scientific underpinnings of each. PMID:27813691

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.

Mapping of cis-regulatory sites in the promoter of testis-specific stellate genes of Drosophila melanogaster.

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Olenkina, O M; Egorova, K S; Aravin, A A; Naumova, N M; Gvozdev, V A; Olenina, L V

2012-11-01

Tandem Stellate genes organized into two clusters in heterochromatin and euchromatin of the X-chromosome are part of the Ste-Su(Ste) genetic system required for maintenance of male fertility and reproduction of Drosophila melanogaster. Stellate genes encode a regulatory subunit of protein kinase CK2 and are the main targets of germline-specific piRNA-silencing; their derepression leads to appearance of protein crystals in spermatocytes, meiotic disturbances, and male sterility. A short promoter region of 134 bp appears to be sufficient for testis-specific transcription of Stellate, and it contains three closely located cis-regulatory elements called E-boxes. By using reporter analysis, we confirmed a strong functionality of the E-boxes in the Stellate promoter for in vivo transcription. Using selective mutagenesis, we have shown that the presence of the central E-box 2 is preferable to maintain a high-level testis-specific transcription of the reporter gene under the Stellate promoter. The Stellate promoter provides transcription even in heterochromatin, and corresponding mRNAs are translated with the generation of full-size protein products in case of disturbances in the piRNA-silencing process. We have also shown for the first time that the activity of the Stellate promoter is determined by chromatin context of the X-chromosome in male germinal cells, and it increases at about twofold when relocating in autosomes.

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

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.

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.

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.

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.

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.

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...

Marketing Regulatory Oversight of Advanced Therapy Medicinal Products (ATMPs) in Europe: The EMA/CAT Perspective.

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Salmikangas, Paula; Schuessler-Lenz, Martina; Ruiz, Sol; Celis, Patrick; Reischl, Ilona; Menezes-Ferreira, Margarida; Flory, Egbert; Renner, Matthias; Ferry, Nicolas

2015-01-01

With the release of Regulation 1394/2007, a new framework for gene and cell therapy medicinal products and tissue-engineered products was established in the European Union. For all three product classes, called advanced therapy medicinal products, a centralised marketing authorisation became mandatory. The European Medicines Agency (EMA) together with its Committee for Advanced Therapies, Committee for Human Medicinal Products and the network of national agencies is responsible for scientific evaluation of the marketing authorisation applications. For a new application, data and information relating to manufacturing processes and quality control of the active substance and the final product have to be submitted for evaluation together with data from non-clinical and clinical safety and efficacy studies. Technical requirements for ATMPs are defined in the legislation, and guidance for different products is available through several EMA/CAT guidelines. Due to the diversity of ATMPs, a tailored approach for regulating these products is considered necessary. Thus, a risk-based approach has been introduced for ATMPs allowing flexibility for the regulatory requirements. Since the regulatory framework for ATMPs was established, five products have been licenced in the European Union. However, the pipeline of new ATMPs is much bigger, as seen from the significant numbers of different products discussed by the CAT in scientific advice and classification procedures. In 2013, a public consultation on the ATMP Regulation was conducted by the European Commission, and the results were published in 2014. The report proposes several improvements for the current framework and established procedures for the regulation of ATMPs.

Integrated analysis of microRNA and gene expression profiles reveals a functional regulatory module associated with liver fibrosis.

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Chen, Wei; Zhao, Wenshan; Yang, Aiting; Xu, Anjian; Wang, Huan; Cong, Min; Liu, Tianhui; Wang, Ping; You, Hong

2017-12-15

Liver fibrosis, characterized with the excessive accumulation of extracellular matrix (ECM) proteins, represents the final common pathway of chronic liver inflammation. Ever-increasing evidence indicates microRNAs (miRNAs) dysregulation has important implications in the different stages of liver fibrosis. However, our knowledge of miRNA-gene regulation details pertaining to such disease remains unclear. The publicly available Gene Expression Omnibus (GEO) datasets of patients suffered from cirrhosis were extracted for integrated analysis. Differentially expressed miRNAs (DEMs) and genes (DEGs) were identified using GEO2R web tool. Putative target gene prediction of DEMs was carried out using the intersection of five major algorithms: DIANA-microT, TargetScan, miRanda, PICTAR5 and miRWalk. Functional miRNA-gene regulatory network (FMGRN) was constructed based on the computational target predictions at the sequence level and the inverse expression relationships between DEMs and DEGs. DAVID web server was selected to perform KEGG pathway enrichment analysis. Functional miRNA-gene regulatory module was generated based on the biological interpretation. Internal connections among genes in liver fibrosis-related module were determined using String database. MiRNA-gene regulatory modules related to liver fibrosis were experimentally verified in recombinant human TGFβ1 stimulated and specific miRNA inhibitor treated LX-2 cells. We totally identified 85 and 923 dysregulated miRNAs and genes in liver cirrhosis biopsy samples compared to their normal controls. All evident miRNA-gene pairs were identified and assembled into FMGRN which consisted of 990 regulations between 51 miRNAs and 275 genes, forming two big sub-networks that were defined as down-network and up-network, respectively. KEGG pathway enrichment analysis revealed that up-network was prominently involved in several KEGG pathways, in which "Focal adhesion", "PI3K-Akt signaling pathway" and "ECM

FK506 biosynthesis is regulated by two positive regulatory elements in Streptomyces tsukubaensis

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Goranovič Dušan

2012-10-01

Full Text Available Abstract Background FK506 (Tacrolimus is an important immunosuppressant, produced by industrial biosynthetic processes using various Streptomyces species. Considering the complex structure of FK506, it is reasonable to expect complex regulatory networks controlling its biosynthesis. Regulatory elements, present in gene clusters can have a profound influence on the final yield of target product and can play an important role in development of industrial bioprocesses. Results Three putative regulatory elements, namely fkbR, belonging to the LysR-type family, fkbN, a large ATP-binding regulator of the LuxR family (LAL-type and allN, a homologue of AsnC family regulatory proteins, were identified in the FK506 gene cluster from Streptomyces tsukubaensis NRRL 18488, a progenitor of industrial strains used for production of FK506. Inactivation of fkbN caused a complete disruption of FK506 biosynthesis, while inactivation of fkbR resulted in about 80% reduction of FK506 yield. No functional role in the regulation of the FK506 gene cluster has been observed for the allN gene. Using RT-PCR and a reporter system based on a chalcone synthase rppA, we demonstrated, that in the wild type as well as in fkbN- and fkbR-inactivated strains, fkbR is transcribed in all stages of cultivation, even before the onset of FK506 production, whereas fkbN expression is initiated approximately with the initiation of FK506 production. Surprisingly, inactivation of fkbN (or fkbR does not abolish the transcription of the genes in the FK506 gene cluster in general, but may reduce expression of some of the tested biosynthetic genes. Finally, introduction of a second copy of the fkbR or fkbN genes under the control of the strong ermE* promoter into the wild type strain resulted in 30% and 55% of yield improvement, respectively. Conclusions Our results clearly demonstrate the positive regulatory role of fkbR and fkbN genes in FK506 biosynthesis in S. tsukubaensis NRRL 18488. We

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

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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

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

Neurogenic gene regulatory pathways in the sea urchin embryo.

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Wei, Zheng; Angerer, Lynne M; Angerer, Robert C

2016-01-15

During embryogenesis the sea urchin early pluteus larva differentiates 40-50 neurons marked by expression of the pan-neural marker synaptotagmin B (SynB) that are distributed along the ciliary band, in the apical plate and pharyngeal endoderm, and 4-6 serotonergic neurons that are confined to the apical plate. Development of all neurons has been shown to depend on the function of Six3. Using a combination of molecular screens and tests of gene function by morpholino-mediated knockdown, we identified SoxC and Brn1/2/4, which function sequentially in the neurogenic regulatory pathway and are also required for the differentiation of all neurons. Misexpression of Brn1/2/4 at low dose caused an increase in the number of serotonin-expressing cells and at higher dose converted most of the embryo to a neurogenic epithelial sphere expressing the Hnf6 ciliary band marker. A third factor, Z167, was shown to work downstream of the Six3 and SoxC core factors and to define a branch specific for the differentiation of serotonergic neurons. These results provide a framework for building a gene regulatory network for neurogenesis in the sea urchin embryo. © 2016. Published by The Company of Biologists Ltd.

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

Regulatory role of melatonin and BMP-4 in prolactin production by rat pituitary lactotrope GH3 cells.

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Ogura-Ochi, Kanako; Fujisawa, Satoshi; Iwata, Nahoko; Komatsubara, Motoshi; Nishiyama, Yuki; Tsukamoto-Yamauchi, Naoko; Inagaki, Kenichi; Wada, Jun; Otsuka, Fumio

2017-08-01

The effects of melatonin on prolactin production and its regulatory mechanism remain uncertain. We investigated the regulatory role of melatonin in prolactin production using rat pituitary lactotrope GH3 cells by focusing on the bone morphogenetic protein (BMP) system. Melatonin receptor activation, induced by melatonin and its receptor agonist ramelteon, significantly suppressed basal and forskolin-induced prolactin secretion and prolactin mRNA expression in GH3 cells. The melatonin MT2 receptor was predominantly expressed in GH3 cells, and the inhibitory effects of melatonin on prolactin production were reversed by treatment with the receptor antagonist luzindole, suggesting functional involvement of MT2 action in the suppression of prolactin release. Melatonin receptor activation also suppressed BMP-4-induced prolactin expression by inhibiting phosphorylation of Smad and transcription of the BMP-target gene Id-1, while BMP-4 treatment upregulated MT2 expression. Melatonin receptor activation suppressed basal, BMP-4-induced and forskolin-induced cAMP synthesis; however, BtcAMP-induced prolactin mRNA expression was not affected by melatonin or ramelteon, suggesting that MT2 activation leads to inhibition of prolactin production through the suppression of Smad signaling and cAMP synthesis. Experiments using intracellular signal inhibitors revealed that the ERK pathway is, at least in part, involved in prolactin induction by GH3 cells. Thus, a new regulatory role of melatonin involving BMP-4 in prolactin secretion was uncovered in lactotrope GH3 cells. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Mutation analysis of the human CYP3A4 gene 5' regulatory region: population screening using non-radioactive SSCP.

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Hamzeiy, Hossein; Vahdati-Mashhadian, Nasser; Edwards, Helen J; Goldfarb, Peter S

2002-03-20

Human CYP3A4 is the major cytochrome P450 isoenzyme in adult human liver and is known to metabolise many xenobiotic and endogenous compounds. There is substantial inter-individual variation in the hepatic levels of CYP3A4. Although, polymorphic mutations have been reported in the 5' regulatory region of the CYP3A4 gene, those that have been investigated so far do not appear to have any effect on gene expression. To determine whether other mutations exist in this region of the gene, we have performed a new population screen on a panel of 101 human DNA samples. A 1140 bp section of the 5' proximal regulatory region of the CYP3A4 gene, containing numerous regulatory motifs, was amplified from genomic DNA as three overlapping segments. The 300 bp distal enhancer region at -7.9kb containing additional regulatory motifs was also amplified. Mutation analysis of the resulting PCR products was carried out using non-radioactive single strand conformation polymorphism (SSCP) and confirmatory sequencing of both DNA strands in those samples showing extra SSCP bands. In addition to detection of the previously reported CYP3A4*1B allele in nine subjects, three novel alleles were found: CYP3A4*1E (having a T-->A transversion at -369 in one subject), CYP3A4*1F (having a C-->G tranversion at -747 in 17 subjects) and CYP3A4*15B containing a nine-nucleotide insertion between -845 and -844 linked to an A-->G transition at -392 and a G-->A transition in exon 6 (position 485 in the cDNA) in one subject. All the novel alleles were heterozygous. No mutations were found in the upstream distal enhancer region. Our results clearly indicate that this rapid and simple SSCP approach can reveal mutant alleles in drug metabolising enzyme genes. Detection and determination of the frequency of novel alleles in CYP3A4 will assist investigation of the relationship between genotype, xenobiotic metabolism and toxicity in the CYP3A family of isoenzymes.

Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks

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Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...

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.

Cis-regulatory element based targeted gene finding: genome-wide identification of abscisic acid- and abiotic stress-responsive genes in Arabidopsis thaliana.

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Zhang, Weixiong; Ruan, Jianhua; Ho, Tuan-Hua David; You, Youngsook; Yu, Taotao; Quatrano, Ralph S

2005-07-15

A fundamental problem of computational genomics is identifying the genes that respond to certain endogenous cues and environmental stimuli. This problem can be referred to as targeted gene finding. Since gene regulation is mainly determined by the binding of transcription factors and cis-regulatory DNA sequences, most existing gene annotation methods, which exploit the conservation of open reading frames, are not effective in finding target genes. A viable approach to targeted gene finding is to exploit the cis-regulatory elements that are known to be responsible for the transcription of target genes. Given such cis-elements, putative target genes whose promoters contain the elements can be identified. As a case study, we apply the above approach to predict the genes in model plant Arabidopsis thaliana which are inducible by a phytohormone, abscisic acid (ABA), and abiotic stress, such as drought, cold and salinity. We first construct and analyze two ABA specific cis-elements, ABA-responsive element (ABRE) and its coupling element (CE), in A.thaliana, based on their conservation in rice and other cereal plants. We then use the ABRE-CE module to identify putative ABA-responsive genes in A.thaliana. Based on RT-PCR verification and the results from literature, this method has an accuracy rate of 67.5% for the top 40 predictions. The cis-element based targeted gene finding approach is expected to be widely applicable since a large number of cis-elements in many species are available.

Both positive and negative regulatory elements mediate expression of a photoregulated CAB gene from Nicotiana plumbaginifolia.

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Castresana, C; Garcia-Luque, I; Alonso, E; Malik, V S; Cashmore, A R

1988-01-01

We have analyzed promoter regulatory elements from a photoregulated CAB gene (Cab-E) isolated from Nicotiana plumbaginifolia. These studies have been performed by introducing chimeric gene constructs into tobacco cells via Agrobacterium tumefaciens-mediated transformation. Expression studies on the regenerated transgenic plants have allowed us to characterize three positive and one negative cis-acting elements that influence photoregulated expression of the Cab-E gene. Within the upstream sequences we have identified two positive regulatory elements (PRE1 and PRE2) which confer maximum levels of photoregulated expression. These sequences contain multiple repeated elements related to the sequence-ACCGGCCCACTT-. We have also identified within the upstream region a negative regulatory element (NRE) extremely rich in AT sequences, which reduces the level of gene expression in the light. We have defined a light regulatory element (LRE) within the promoter region extending from -396 to -186 bp which confers photoregulated expression when fused to a constitutive nopaline synthase ('nos') promoter. Within this region there is a 132-bp element, extending from -368 to -234 bp, which on deletion from the Cab-E promoter reduces gene expression from high levels to undetectable levels. Finally, we have demonstrated for a full length Cab-E promoter conferring high levels of photoregulated expression, that sequences proximal to the Cab-E TATA box are not replaceable by corresponding sequences from a 'nos' promoter. This contrasts with the apparent equivalence of these Cab-E and 'nos' TATA box-proximal sequences in truncated promoters conferring low levels of photoregulated expression. Images PMID:2901343

Sheep skeletal muscle transcriptome analysis reveals muscle growth regulatory lncRNAs.

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Chao, Tianle; Ji, Zhibin; Hou, Lei; Wang, Jin; Zhang, Chunlan; Wang, Guizhi; Wang, Jianmin

2018-01-01

As widely distributed domestic animals, sheep are an important species and the source of mutton. In this study, we aimed to evaluate the regulatory lncRNAs associated with muscle growth and development between high production mutton sheep (Dorper sheep and Qianhua Mutton Merino sheep) and low production mutton sheep (Small-tailed Han sheep). In total, 39 lncRNAs were found to be differentially expressed. Using co-expression analysis and functional annotation, 1,206 co-expression interactions were found between 32 lncRNAs and 369 genes, and 29 of these lncRNAs were found to be associated with muscle development, metabolism, cell proliferation and apoptosis. lncRNA-mRNA interactions revealed 6 lncRNAs as hub lncRNAs. Moreover, three lncRNAs and their associated co-expressed genes were demonstrated by cis-regulatory gene analyses, and we also found a potential regulatory relationship between the pseudogene lncRNA LOC101121401 and its parent gene FTH1. This study provides a genome-wide resolution of lncRNA and mRNA regulation in muscles from mutton sheep.

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

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Gerstein, Mark

2016-01-01

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks.

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Daifeng Wang

2016-10-01

Full Text Available Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs, cellular growth factors and microRNAs. A subsystem's gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally-e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the "state" and "control" in the model refer to its own (internal and another subsystem's (external gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model's parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs, seeing the degree to which these can be accounted for by orthologous (internal versus species-specific (external TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with

Analysis of a Gene Regulatory Cascade Mediating Circadian Rhythm in Zebrafish

Science.gov (United States)

Wang, Haifang; Du, Jiulin; Yan, Jun

2013-01-01

In the study of circadian rhythms, it has been a puzzle how a limited number of circadian clock genes can control diverse aspects of physiology. Here we investigate circadian gene expression genome-wide using larval zebrafish as a model system. We made use of a spatial gene expression atlas to investigate the expression of circadian genes in various tissues and cell types. Comparison of genome-wide circadian gene expression data between zebrafish and mouse revealed a nearly anti-phase relationship and allowed us to detect novel evolutionarily conserved circadian genes in vertebrates. We identified three groups of zebrafish genes with distinct responses to light entrainment: fast light-induced genes, slow light-induced genes, and dark-induced genes. Our computational analysis of the circadian gene regulatory network revealed several transcription factors (TFs) involved in diverse aspects of circadian physiology through transcriptional cascade. Of these, microphthalmia-associated transcription factor a (mitfa), a dark-induced TF, mediates a circadian rhythm of melanin synthesis, which may be involved in zebrafish's adaptation to daily light cycling. Our study describes a systematic method to discover previously unidentified TFs involved in circadian physiology in complex organisms. PMID:23468616

Radioactivity in consumer products : radiation safety and regulatory appraisal

International Nuclear Information System (INIS)

Murthy, B.K.S.; Venkataraman, G.; Subrahmanym, P.

1993-01-01

Use of radioactive materials in consumer products is in vogue almost since the discovery of radioactivity. There has been a rapid growth in the use of radioactive material in various consumer products such as Ionization Chamber Smoke Detectors (ICSD), Static eliminators, etc. In addition, there are certain manufacturing processes wherein the Naturally Occurring Radioactive Material (NORM) get incorporated in the consumer products. Certain phosphatic fertilizers, titanium dioxide pigments, phospho gypsum plaster boards are some examples in this category. The manufacture and use of these products result in radiation dose to the public apart from radiation exposure to the personnel involved in the manufacturing process. Appropriate radiation control measures have to be taken in the design, manufacture and use of consumer products to ensure that the radiation doses to the public and the population at large do not exceed the relevant limits. While appropriate regulatory controls and surveillance are established for manufacture and use of certain products, these are still to be recognised and established in respect of certain other processes and products. The current status of radiation safety and regulatory control and the lack of these in respect of some products are discussed in this paper. (author). 5 refs

Regulatory reforms and productivity: An empirical analysis of the Japanese electricity industry

International Nuclear Information System (INIS)

Nakano, Makiko; Managi, Shunsuke

2008-01-01

The Japanese electricity industry has experienced regulatory reforms since the mid-1990s. This article measures productivity in Japan's steam power-generation sector and examines the effect of reforms on the productivity of this industry over the period 1978-2003. We estimate the Luenberger productivity indicator, which is a generalization of the commonly used Malmquist productivity index, using a data envelopment analysis approach. Factors associated with productivity change are investigated through dynamic generalized method of moments (GMM) estimation of panel data. Our empirical analysis shows that the regulatory reforms have contributed to productivity growth in the steam power-generation sector in Japan

A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

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Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

2016-06-01

Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs. Copyright © 2016 Elsevier Inc. All rights reserved.

Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

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Liang Jinghang

2012-08-01

Full Text Available Abstract Background Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs. As a logical model, probabilistic Boolean networks (PBNs consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n or O(nN2n for a sparse matrix. Results This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN. An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n, where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a

Characterization of Putative cis-Regulatory Elements in Genes Preferentially Expressed in Arabidopsis Male Meiocytes

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Junhua Li

2014-01-01

Full Text Available Meiosis is essential for plant reproduction because it is the process during which homologous chromosome pairing, synapsis, and meiotic recombination occur. The meiotic transcriptome is difficult to investigate because of the size of meiocytes and the confines of anther lobes. The recent development of isolation techniques has enabled the characterization of transcriptional profiles in male meiocytes of Arabidopsis. Gene expression in male meiocytes shows unique features. The direct interaction of transcription factors (TFs with DNA regulatory sequences forms the basis for the specificity of transcriptional regulation. Here, we identified putative cis-regulatory elements (CREs associated with male meiocyte-expressed genes using in silico tools. The upstream regions (1 kb of the top 50 genes preferentially expressed in Arabidopsis meiocytes possessed conserved motifs. These motifs are putative binding sites of TFs, some of which share common functions, such as roles in cell division. In combination with cell-type-specific analysis, our findings could be a substantial aid for the identification and experimental verification of the protein-DNA interactions for the specific TFs that drive gene expression in meiocytes.

Distinct gene regulatory programs define the inhibitory effects of liver X receptors and PPARG on cancer cell proliferation.

Science.gov (United States)

Savic, Daniel; Ramaker, Ryne C; Roberts, Brian S; Dean, Emma C; Burwell, Todd C; Meadows, Sarah K; Cooper, Sara J; Garabedian, Michael J; Gertz, Jason; Myers, Richard M

2016-07-11

The liver X receptors (LXRs, NR1H2 and NR1H3) and peroxisome proliferator-activated receptor gamma (PPARG, NR1C3) nuclear receptor transcription factors (TFs) are master regulators of energy homeostasis. Intriguingly, recent studies suggest that these metabolic regulators also impact tumor cell proliferation. However, a comprehensive temporal molecular characterization of the LXR and PPARG gene regulatory responses in tumor cells is still lacking. To better define the underlying molecular processes governing the genetic control of cellular growth in response to extracellular metabolic signals, we performed a comprehensive, genome-wide characterization of the temporal regulatory cascades mediated by LXR and PPARG signaling in HT29 colorectal cancer cells. For this analysis, we applied a multi-tiered approach that incorporated cellular phenotypic assays, gene expression profiles, chromatin state dynamics, and nuclear receptor binding patterns. Our results illustrate that the activation of both nuclear receptors inhibited cell proliferation and further decreased glutathione levels, consistent with increased cellular oxidative stress. Despite a common metabolic reprogramming, the gene regulatory network programs initiated by these nuclear receptors were widely distinct. PPARG generated a rapid and short-term response while maintaining a gene activator role. By contrast, LXR signaling was prolonged, with initial, predominantly activating functions that transitioned to repressive gene regulatory activities at late time points. Through the use of a multi-tiered strategy that integrated various genomic datasets, our data illustrate that distinct gene regulatory programs elicit common phenotypic effects, highlighting the complexity of the genome. These results further provide a detailed molecular map of metabolic reprogramming in cancer cells through LXR and PPARG activation. As ligand-inducible TFs, these nuclear receptors can potentially serve as attractive therapeutic

Overexpression of maize anthocyanin regulatory gene Lc affects rice fertility.

Science.gov (United States)

Li, Yuan; Zhang, Tao; Shen, Zhong-Wei; Xu, Yu; Li, Jian-Yue

2013-01-01

Seventeen independent transgenic rice plants with the maize anthocyanin regulatory gene Lc under control of the CaMV 35S promoter were obtained and verified by molecular identification. Ten plants showed red spikelets during early development of florets, and the degenerate florets were still red after heading. Additionally, these plants exhibited intense pigmentation on the surface of the anther and the bottom of the ovary. They were unable to properly bloom and were completely sterile. Following pollination with normal pollen, these plants yielded red caryopses but did not mature normally. QRT-PCR analysis indicated that mRNA accumulation of the CHS-like gene encoding a chalcone synthase-related protein was increased significantly in the sterile plant. This is the first report to suggest that upregulation of the CHS gene expression may result in rice sterility and affect the normal development of rice seeds.

Positional bias of general and tissue-specific regulatory motifs in mouse gene promoters

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Farré Domènec

2007-12-01

Full Text Available Abstract Background The arrangement of regulatory motifs in gene promoters, or promoter architecture, is the result of mutation and selection processes that have operated over many millions of years. In mammals, tissue-specific transcriptional regulation is related to the presence of specific protein-interacting DNA motifs in gene promoters. However, little is known about the relative location and spacing of these motifs. To fill this gap, we have performed a systematic search for motifs that show significant bias at specific promoter locations in a large collection of housekeeping and tissue-specific genes. Results We observe that promoters driving housekeeping gene expression are enriched in particular motifs with strong positional bias, such as YY1, which are of little relevance in promoters driving tissue-specific expression. We also identify a large number of motifs that show positional bias in genes expressed in a highly tissue-specific manner. They include well-known tissue-specific motifs, such as HNF1 and HNF4 motifs in liver, kidney and small intestine, or RFX motifs in testis, as well as many potentially novel regulatory motifs. Based on this analysis, we provide predictions for 559 tissue-specific motifs in mouse gene promoters. Conclusion The study shows that motif positional bias is an important feature of mammalian proximal promoters and that it affects both general and tissue-specific motifs. Motif positional constraints define very distinct promoter architectures depending on breadth of expression and type of tissue.

Neural model of gene regulatory network: a survey on supportive meta-heuristics.

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Biswas, Surama; Acharyya, Sriyankar

2016-06-01

Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through various mathematical and computational schemes and reported in survey articles. Neural and neuro-fuzzy models have been the focus of attraction in bioinformatics. Predominant use of meta-heuristic algorithms in training neural models has proved its excellence. Considering these facts, this paper is organized to survey neural modelling schemes of GRN and the efficacy of meta-heuristic algorithms towards parameter learning (i.e. weighting connections) within the model. This survey paper renders two different structure-related approaches to infer GRN which are global structure approach and substructure approach. It also describes two neural modelling schemes, such as artificial neural network/recurrent neural network based modelling and neuro-fuzzy modelling. The meta-heuristic algorithms applied so far to learn the structure and parameters of neutrally modelled GRN have been reviewed here.

Sterol regulatory element binding protein-1 (SREBP1) gene expression is similarly increased in polycystic ovary syndrome and endometrial cancer.

Science.gov (United States)

Shafiee, Mohamad N; Mongan, Nigel; Seedhouse, Claire; Chapman, Caroline; Deen, Suha; Abu, Jafaru; Atiomo, William

2017-05-01

Women with polycystic ovary syndrome have a three-fold higher risk of endometrial cancer. Insulin resistance and hyperlipidemia may be pertinent factors in the pathogenesis of both conditions. The aim of this study was to investigate endometrial sterol regulatory element binding protein-1 gene expression in polycystic ovary syndrome and endometrial cancer endometrium, and to correlate endometrial sterol regulatory element binding protein-1 gene expression with serum lipid profiles. A cross-sectional study was performed at Nottingham University Hospital, UK. A total of 102 women (polycystic ovary syndrome, endometrial cancer and controls; 34 participants in each group) were recruited. Clinical and biochemical assessments were performed before endometrial biopsies were obtained from all participants. Taqman real-time polymerase chain reaction for endometrial sterol regulatory element binding protein-1 gene and its systemic protein expression were analyzed. The body mass indices of women with polycystic ovary syndrome (29.28 ± 2.91 kg/m 2 ) and controls (28.58 ± 2.62 kg/m 2 ) were not significantly different. Women with endometrial cancer had a higher mean body mass index (32.22 ± 5.70 kg/m 2 ). Sterol regulatory element binding protein-1 gene expression was significantly increased in polycystic ovary syndrome and endometrial cancer endometrium compared with controls (p ovary syndrome, but this was not statistically significant. Similarly, statistically insignificant positive correlations were found between endometrial sterol regulatory element binding protein-1 gene expression and body mass index in endometrial cancer (r = 0.643, p = 0.06) and waist-hip ratio (r = 0.096, p = 0.073). Sterol regulatory element binding protein-1 gene expression was significantly positively correlated with triglyceride in both polycystic ovary syndrome and endometrial cancer (p = 0.028 and p = 0.027, respectively). Quantitative serum sterol regulatory element

Regulatory RNAs in Bacillus subtilis : a Gram-Positive Perspective on Bacterial RNA-Mediated Regulation of Gene Expression

NARCIS (Netherlands)

Mars, Ruben A. T.; Nicolas, Pierre; Denham, Emma L.; van Dijl, Jan Maarten

2016-01-01

Bacteria can employ widely diverse RNA molecules to regulate their gene expression. Such molecules include trans-acting small regulatory RNAs, antisense RNAs, and a variety of transcriptional attenuation mechanisms in the 5= untranslated region. Thus far, most regulatory RNA research has focused on

Plasticity of the cis-regulatory input function of a gene.

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Avraham E Mayo

2006-04-01

Full Text Available The transcription rate of a gene is often controlled by several regulators that bind specific sites in the gene's cis-regulatory region. The combined effect of these regulators is described by a cis-regulatory input function. What determines the form of an input function, and how variable is it with respect to mutations? To address this, we employ the well-characterized lac operon of Escherichia coli, which has an elaborate input function, intermediate between Boolean AND-gate and OR-gate logic. We mapped in detail the input function of 12 variants of the lac promoter, each with different point mutations in the regulator binding sites, by means of accurate expression measurements from living cells. We find that even a few mutations can significantly change the input function, resulting in functions that resemble Pure AND gates, OR gates, or single-input switches. Other types of gates were not found. The variant input functions can be described in a unified manner by a mathematical model. The model also lets us predict which functions cannot be reached by point mutations. The input function that we studied thus appears to be plastic, in the sense that many of the mutations do not ruin the regulation completely but rather result in new ways to integrate the inputs.

Common market but divergent regulatory practices: exploring European regulation and the effect on regulatory uncertainty in the marketing authorization of medical products

NARCIS (Netherlands)

Chowdhury, Nupur

2013-01-01

The medical product sector is characterised by a regulatory patchwork of European and national laws and guidelines operating concurrently with each other. Each of these sectors are characterised by different levels of regulatory uncertainty that may undermine the effectiveness of the regulatory

IFN regulatory factor 1 restricts hepatitis E virus replication by activating STAT1 to induce antiviral IFN-stimulated genes.

Science.gov (United States)

Xu, Lei; Zhou, Xinying; Wang, Wenshi; Wang, Yijin; Yin, Yuebang; Laan, Luc J W van der; Sprengers, Dave; Metselaar, Herold J; Peppelenbosch, Maikel P; Pan, Qiuwei

2016-10-01

IFN regulatory factor 1 (IRF1) is one of the most important IFN-stimulated genes (ISGs) in cellular antiviral immunity. Although hepatitis E virus (HEV) is a leading cause of acute hepatitis worldwide, how ISGs counteract HEV infection is largely unknown. This study was conducted to investigate the effect of IRF1 on HEV replication. Multiple cell lines were used in 2 models that harbor HEV. In different HEV cell culture systems, IRF1 effectively inhibited HEV replication. IRF1 did not trigger IFN production, and chromatin immunoprecipitation sequencing data analysis revealed that IRF1 bound to the promoter region of signal transducers and activators of transcription 1 (STAT1). Functional assay confirmed that IRF1 could drive the transcription of STAT1, resulting in elevation of total and phosphorylated STAT1 proteins and further activating the transcription of a panel of downstream antiviral ISGs. By pharmacological inhibitors and RNAi-mediated gene-silencing approaches, we revealed that antiviral function of IRF1 is dependent on the JAK-STAT cascade. Furthermore, induction of ISGs and the anti-HEV effect of IRF1 overlapped that of IFNα, but was potentiated by ribavirin. We demonstrated that IRF1 effectively inhibits HEV replication through the activation of the JAK-STAT pathway, and the subsequent transcription of antiviral ISGs, but independent of IFN production.-Xu, L., Zhou, X., Wang, W., Wang, Y., Yin, Y., van der Laan, L. J. W., Sprengers, D., Metselaar, H. J., Peppelenbosch, M. P., Pan, Q. IFN regulatory factor 1 restricts hepatitis E virus replication by activating STAT1 to induce antiviral IFN-stimulated genes. © FASEB.

Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks.

Science.gov (United States)

Fischer, Martin; Grossmann, Patrick; Padi, Megha; DeCaprio, James A

2016-07-27

Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the limitation of individual studies, we developed a meta-analysis approach to identify high confidence target genes that reflect their frequency of identification in independent datasets. Gene regulatory networks were generated by comparing differential expression of TP53 and CC-regulated genes with chromatin immunoprecipitation studies for TP53, RB1, E2F, DREAM, B-MYB, FOXM1 and MuvB. RNA-seq data from p21-null cells revealed that gene downregulation by TP53 generally requires p21 (CDKN1A). Genes downregulated by TP53 were also identified as CC genes bound by the DREAM complex. The transcription factors RB, E2F1 and E2F7 bind to a subset of DREAM target genes that function in G1/S of the CC while B-MYB, FOXM1 and MuvB control G2/M gene expression. Our approach yields high confidence ranked target gene maps for TP53, DREAM, MMB-FOXM1 and RB-E2F and enables prediction and distinction of CC regulation. A web-based atlas at www.targetgenereg.org enables assessing the regulation of any human gene of interest. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Extensive evolutionary changes in regulatory element activity during human origins are associated with altered gene expression and positive selection.

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Yoichiro Shibata

2012-06-01

Full Text Available Understanding the molecular basis for phenotypic differences between humans and other primates remains an outstanding challenge. Mutations in non-coding regulatory DNA that alter gene expression have been hypothesized as a key driver of these phenotypic differences. This has been supported by differential gene expression analyses in general, but not by the identification of specific regulatory elements responsible for changes in transcription and phenotype. To identify the genetic source of regulatory differences, we mapped DNaseI hypersensitive (DHS sites, which mark all types of active gene regulatory elements, genome-wide in the same cell type isolated from human, chimpanzee, and macaque. Most DHS sites were conserved among all three species, as expected based on their central role in regulating transcription. However, we found evidence that several hundred DHS sites were gained or lost on the lineages leading to modern human and chimpanzee. Species-specific DHS site gains are enriched near differentially expressed genes, are positively correlated with increased transcription, show evidence of branch-specific positive selection, and overlap with active chromatin marks. Species-specific sequence differences in transcription factor motifs found within these DHS sites are linked with species-specific changes in chromatin accessibility. Together, these indicate that the regulatory elements identified here are genetic contributors to transcriptional and phenotypic differences among primate species.

Cis-regulatory timers for developmental gene expression.

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Lionel Christiaen

2013-10-01

Full Text Available How does a fertilized egg decode its own genome to eventually develop into a mature animal? Each developing cell must activate a battery of genes in a timely manner and according to the function it will ultimately perform, but how? During development of the notochord--a structure akin to the vertebrate spine--in a simple marine invertebrate, an essential protein called Brachyury binds to specific sites in its target genes. A study just published in PLOS Biology reports that if the target gene contains multiple Brachyury-binding sites it will be activated early in development but if it contains only one site it will be activated later. Genes that contain no binding site can still be activated by Brachyury, but only indirectly by an earlier Brachyury-dependent gene product, so later than the directly activated genes. Thus, this study shows how several genes can interpret the presence of a single factor differently to become active at distinct times in development.

Increasing Avermectin Production in Streptomyces avermitilis by Manipulating the Expression of a Novel TetR-Family Regulator and Its Target Gene Product.

Science.gov (United States)

Liu, Wenshuai; Zhang, Qinling; Guo, Jia; Chen, Zhi; Li, Jilun; Wen, Ying

2015-08-01

Avermectins produced by Streptomyces avermitilis are commercially important anthelmintic agents. The detailed regulatory mechanisms of avermectin biosynthesis remain unclear. Here, we identified SAV3619, a TetR-family transcriptional regulator designated AveT, to be an activator for both avermectin production and morphological differentiation in S. avermitilis. AveT was shown to indirectly stimulate avermectin production by affecting transcription of the cluster-situated activator gene aveR. AveT directly repressed transcription of its own gene (aveT), adjacent gene pepD2 (sav_3620), sav_7490 (designated aveM), and sav_7491 by binding to an 18-bp perfect palindromic sequence (CGAAACGKTKYCGTTTCG, where K is T or G and Y is T or C and where the underlining indicates inverted repeats) within their promoter regions. aveM (which encodes a putative transmembrane efflux protein belonging to the major facilitator superfamily [MFS]), the important target gene of AveT, had a striking negative effect on avermectin production and morphological differentiation. Overexpression of aveT and deletion of aveM in wild-type and industrial strains of S. avermitilis led to clear increases in the levels of avermectin production. In vitro gel-shift assays suggested that C-5-O-B1, the late pathway precursor of avermectin B1, acts as an AveT ligand. Taken together, our findings indicate positive-feedback regulation of aveT expression and avermectin production by a late pathway intermediate and provide the basis for an efficient strategy to increase avermectin production in S. avermitilis by manipulation of AveT and its target gene product, AveM. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Ground rules of the pluripotency gene regulatory network.

KAUST Repository

Li, Mo

2017-01-03

Pluripotency is a state that exists transiently in the early embryo and, remarkably, can be recapitulated in vitro by deriving embryonic stem cells or by reprogramming somatic cells to become induced pluripotent stem cells. The state of pluripotency, which is stabilized by an interconnected network of pluripotency-associated genes, integrates external signals and exerts control over the decision between self-renewal and differentiation at the transcriptional, post-transcriptional and epigenetic levels. Recent evidence of alternative pluripotency states indicates the regulatory flexibility of this network. Insights into the underlying principles of the pluripotency network may provide unprecedented opportunities for studying development and for regenerative medicine.

Ground rules of the pluripotency gene regulatory network.

KAUST Repository

Li, Mo; Belmonte, Juan Carlos Izpisua

2017-01-01

Pluripotency is a state that exists transiently in the early embryo and, remarkably, can be recapitulated in vitro by deriving embryonic stem cells or by reprogramming somatic cells to become induced pluripotent stem cells. The state of pluripotency, which is stabilized by an interconnected network of pluripotency-associated genes, integrates external signals and exerts control over the decision between self-renewal and differentiation at the transcriptional, post-transcriptional and epigenetic levels. Recent evidence of alternative pluripotency states indicates the regulatory flexibility of this network. Insights into the underlying principles of the pluripotency network may provide unprecedented opportunities for studying development and for regenerative medicine.

Sustainability, natural and organic cosmetics: consumer, products, efficacy, toxicological and regulatory considerations

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Bruno Fonseca-Santos

2015-03-01

Full Text Available The interest in sustainable products has increased along the years, since the choice of products, packaging and production processes have a great impact on the environment. These products are classified by regulatory agencies in different categories, aggregating advantages to the product and increasing the demand by consumers. However, there is no harmonization in guidelines of these certifying agencies and each cosmetic industry formulates their product and packaging in a more rational way, which causes less damage to the environment. Many cosmetic products have in their formulation natural products that perform a specific biological function, but these products should be evaluated on efficacy and toxicological aspects. The aim of this article is to approach sustainability, natural and organic cosmetics, considering the consumer and the efficacy, toxicological and regulatory aspects.

Intervention in gene regulatory networks with maximal phenotype alteration.

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Yousefi, Mohammadmahdi R; Dougherty, Edward R

2013-07-15

A basic issue for translational genomics is to model gene interaction via gene regulatory networks (GRNs) and thereby provide an informatics environment to study the effects of intervention (say, via drugs) and to derive effective intervention strategies. Taking the view that the phenotype is characterized by the long-run behavior (steady-state distribution) of the network, we desire interventions to optimally move the probability mass from undesirable to desirable states Heretofore, two external control approaches have been taken to shift the steady-state mass of a GRN: (i) use a user-defined cost function for which desirable shift of the steady-state mass is a by-product and (ii) use heuristics to design a greedy algorithm. Neither approach provides an optimal control policy relative to long-run behavior. We use a linear programming approach to optimally shift the steady-state mass from undesirable to desirable states, i.e. optimization is directly based on the amount of shift and therefore must outperform previously proposed methods. Moreover, the same basic linear programming structure is used for both unconstrained and constrained optimization, where in the latter case, constraints on the optimization limit the amount of mass that may be shifted to 'ambiguous' states, these being states that are not directly undesirable relative to the pathology of interest but which bear some perceived risk. We apply the method to probabilistic Boolean networks, but the theory applies to any Markovian GRN. Supplementary materials, including the simulation results, MATLAB source code and description of suboptimal methods are available at http://gsp.tamu.edu/Publications/supplementary/yousefi13b. edward@ece.tamu.edu Supplementary data are available at Bioinformatics online.

Inflammatory gene regulatory networks in amnion cells following cytokine stimulation: translational systems approach to modeling human parturition.

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Ruth Li

Full Text Available A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals.

Global regulatory framework for production and marketing of crops biofortified with vitamins and minerals.

Science.gov (United States)

Mejia, Luis A; Dary, Omar; Boukerdenna, Hala

2017-02-01

Biofortification of crops is being introduced in several countries as a strategy to reduce micronutrient deficiencies. Biofortified products, with increased contents of micronutrients, are currently produced by conventional plant breeding, genetic modification, or nutrient-enhanced fertilization. Corn, rice, wheat, beans, pearl millet, sweet potato, and cassava have been biofortified with increased contents of provitamin A carotenoids, iron, or zinc. However, regulatory considerations are rare or nonexistent. The objective of this paper is to review the regulatory framework for production and marketing of biofortified crops in countries that have adopted this strategy. The information was identified using Internet search engines and websites of health and nutrition organizations and nongovernmental organizations and by consulting scientists and government authorities. Thus far, biofortified products introduced in Latin America, Africa, and Asia have been produced only by conventional breeding. Cultivars using other techniques are still under testing. The production and marketing of these products have been conducted without regulatory framework and under limited government control or regulatory guidance. Nevertheless, some countries have integrated biofortified crops into their nutrition agendas. Although improvements by conventional breeding have not been subject to regulations, when biofortification becomes expanded by including other techniques, an appropriate regulatory framework will be necessary. © 2016 New York Academy of Sciences.

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

Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors.

Science.gov (United States)

Sun, Mengyang; Cheng, Xianrui; Socolar, Joshua E S

2013-06-01

A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.

Isotope production technologies from a regulatory perspective

Energy Technology Data Exchange (ETDEWEB)

Murthy, K. [Canadian Nuclear Safety Committee, Ottawa, Ontario (Canada)

2012-07-01

This paper discusses isotope production technologies from a regulatory perspective. The regulator is the CNSC which has the mandate to protect the health, safety and security of persons and the environment and to implement Canada's international commitments on the peaceful use of nuclear energy. Nuclear facilities regulated by CNSC include linear accelerator (medical), pool irradiator (industrial) and Pelletron (research) as well as cyclotrons.

Inherited variants in regulatory T cell genes and outcome of ovarian cancer.

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Ellen L Goode

Full Text Available Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs has a role in outcome of this disease, and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci (eQTL and sequence-based tagging single nucleotide polymorphisms (tagSNPs for 54 genes associated with Tregs in 3,662 invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202, p=2.7×10(-5, LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p=4.5×10(-4, and rs3753348, p=9.0×10(-4, respectively, and CD80 (endometrioid, rs13071247, p=8.0×10(-4. Fo0r the latter, correlative data support a CD80 rs13071247 genotype association with CD80 tumor RNA expression (p=0.006. An additional eQTL SNP in CD80 was associated with shorter survival (rs7804190, p=8.1×10(-4 among all cases combined. As the products of these genes are known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up phenotypic studies.

Inherited variants in regulatory T cell genes and outcome of ovarian cancer.

Science.gov (United States)

Goode, Ellen L; DeRycke, Melissa; Kalli, Kimberly R; Oberg, Ann L; Cunningham, Julie M; Maurer, Matthew J; Fridley, Brooke L; Armasu, Sebastian M; Serie, Daniel J; Ramar, Priya; Goergen, Krista; Vierkant, Robert A; Rider, David N; Sicotte, Hugues; Wang, Chen; Winterhoff, Boris; Phelan, Catherine M; Schildkraut, Joellen M; Weber, Rachel P; Iversen, Ed; Berchuck, Andrew; Sutphen, Rebecca; Birrer, Michael J; Hampras, Shalaka; Preus, Leah; Gayther, Simon A; Ramus, Susan J; Wentzensen, Nicolas; Yang, Hannah P; Garcia-Closas, Montserrat; Song, Honglin; Tyrer, Jonathan; Pharoah, Paul P D; Konecny, Gottfried; Sellers, Thomas A; Ness, Roberta B; Sucheston, Lara E; Odunsi, Kunle; Hartmann, Lynn C; Moysich, Kirsten B; Knutson, Keith L

2013-01-01

Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs) has a role in outcome of this disease, and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci (eQTL) and sequence-based tagging single nucleotide polymorphisms (tagSNPs) for 54 genes associated with Tregs in 3,662 invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202, p=2.7×10(-5)), LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p=4.5×10(-4), and rs3753348, p=9.0×10(-4), respectively), and CD80 (endometrioid, rs13071247, p=8.0×10(-4)). Fo0r the latter, correlative data support a CD80 rs13071247 genotype association with CD80 tumor RNA expression (p=0.006). An additional eQTL SNP in CD80 was associated with shorter survival (rs7804190, p=8.1×10(-4)) among all cases combined. As the products of these genes are known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up phenotypic studies.

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

Science.gov (United States)

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.

Regulatory RNAs in Bacillus subtilis: a Gram-Positive Perspective on Bacterial RNA-Mediated Regulation of Gene Expression

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Mars, Ruben A. T.; Nicolas, Pierre; Denham, Emma L.

2016-01-01

SUMMARY Bacteria can employ widely diverse RNA molecules to regulate their gene expression. Such molecules include trans-acting small regulatory RNAs, antisense RNAs, and a variety of transcriptional attenuation mechanisms in the 5′ untranslated region. Thus far, most regulatory RNA research has focused on Gram-negative bacteria, such as Escherichia coli and Salmonella. Hence, there is uncertainty about whether the resulting insights can be extrapolated directly to other bacteria, such as the Gram-positive soil bacterium Bacillus subtilis. A recent study identified 1,583 putative regulatory RNAs in B. subtilis, whose expression was assessed across 104 conditions. Here, we review the current understanding of RNA-based regulation in B. subtilis, and we categorize the newly identified putative regulatory RNAs on the basis of their conservation in other bacilli and the stability of their predicted secondary structures. Our present evaluation of the publicly available data indicates that RNA-mediated gene regulation in B. subtilis mostly involves elements at the 5′ ends of mRNA molecules. These can include 5′ secondary structure elements and metabolite-, tRNA-, or protein-binding sites. Importantly, sense-independent segments are identified as the most conserved and structured potential regulatory RNAs in B. subtilis. Altogether, the present survey provides many leads for the identification of new regulatory RNA functions in B. subtilis. PMID:27784798

Regulatory RNAs in Bacillus subtilis: a Gram-Positive Perspective on Bacterial RNA-Mediated Regulation of Gene Expression.

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Mars, Ruben A T; Nicolas, Pierre; Denham, Emma L; van Dijl, Jan Maarten

2016-12-01

Bacteria can employ widely diverse RNA molecules to regulate their gene expression. Such molecules include trans-acting small regulatory RNAs, antisense RNAs, and a variety of transcriptional attenuation mechanisms in the 5' untranslated region. Thus far, most regulatory RNA research has focused on Gram-negative bacteria, such as Escherichia coli and Salmonella. Hence, there is uncertainty about whether the resulting insights can be extrapolated directly to other bacteria, such as the Gram-positive soil bacterium Bacillus subtilis. A recent study identified 1,583 putative regulatory RNAs in B. subtilis, whose expression was assessed across 104 conditions. Here, we review the current understanding of RNA-based regulation in B. subtilis, and we categorize the newly identified putative regulatory RNAs on the basis of their conservation in other bacilli and the stability of their predicted secondary structures. Our present evaluation of the publicly available data indicates that RNA-mediated gene regulation in B. subtilis mostly involves elements at the 5' ends of mRNA molecules. These can include 5' secondary structure elements and metabolite-, tRNA-, or protein-binding sites. Importantly, sense-independent segments are identified as the most conserved and structured potential regulatory RNAs in B. subtilis. Altogether, the present survey provides many leads for the identification of new regulatory RNA functions in B. subtilis. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Clinical Development and Commercialization of Advanced Therapy Medicinal Products in the European Union: How Are the Product Pipeline and Regulatory Framework Evolving?

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Boráň, Tomáš; Menezes-Ferreira, Margarida; Reischl, Ilona; Celis, Patrick; Ferry, Nicolas; Gänsbacher, Bernd; Krafft, Hartmut; Lipucci di Paola, Michele; Sladowski, Dariusz; Salmikangas, Paula

2017-09-01

The research and development of advanced therapy medicinal products (ATMPs) has been active in Europe and worldwide during recent years. Yet, the number of licensed products remains low. The main expected legal change in the near future in the European Union (EU) concerns the regulation on clinical trials (536/2014), which will come into force in 2018. With this new framework, a more harmonized and swift process for approval of clinical trials is anticipated, which is expected to support the entry of new innovations into the EU market. A survey on ATMPs in clinical trials during 2010-2015 in the EU was conducted in order to study the trends of ATMP development since the earlier survey published in 2012. According to the results, the number of clinical trials using ATMPs is slowly increasing in the EU. Yet, the focus is still in early development, and the projects are mainly carried out by small and medium-sized enterprises, academia, and hospitals. Oncology is the main area of clinical development. Yet, the balance between cell-based products and gene therapy medicinal products in this area may be changing in the future due to the new T-cell technologies. Many limitations and challenges are identified for ATMP development, requiring proportionate regulatory requirements. On the other hand, for such a novel field, the developers should be active in considering possible constraints and actively engage with authorities to look for solutions. This article provides up to-date information on forthcoming regulatory improvements and discusses the main challenges hampering the commercialization of ATMPs in the EU.

A robust approach to identifying tissue-specific gene expression regulatory variants using personalized human induced pluripotent stem cells.

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Je-Hyuk Lee

2009-11-01

Full Text Available Normal variation in gene expression due to regulatory polymorphisms is often masked by biological and experimental noise. In addition, some regulatory polymorphisms may become apparent only in specific tissues. We derived human induced pluripotent stem (iPS cells from adult skin primary fibroblasts and attempted to detect tissue-specific cis-regulatory variants using in vitro cell differentiation. We used padlock probes and high-throughput sequencing for digital RNA allelotyping and measured allele-specific gene expression in primary fibroblasts, lymphoblastoid cells, iPS cells, and their differentiated derivatives. We show that allele-specific expression is both cell type and genotype-dependent, but the majority of detectable allele-specific expression loci remains consistent despite large changes in the cell type or the experimental condition following iPS reprogramming, except on the X-chromosome. We show that our approach to mapping cis-regulatory variants reduces in vitro experimental noise and reveals additional tissue-specific variants using skin-derived human iPS cells.

Defective distal regulatory element at the 5' upstream of rat prolactin gene of steroid-nonresponsive GH-subclone.

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Kumar, V; Wong, D T; Pasion, S G; Biswas, D K

1987-12-08

The prolactin-nonproducing (PRL-) GH cell strains (rat pituitary tumor cells in culture). GH12C1 and F1BGH12C1, do not respond to steroid hormones estradiol or hydrocortisone (HC). However, the stimulatory effect of estradiol and the inhibitory effect of hydrocortisone on prolactin synthesis can be demonstrated in the prolactin-producing GH cell strain, GH4C1. In this investigation we have examined the 5' end flanking region of rat prolactin (rat PRL) gene of steroid-responsive, GH4C1 cells to identify the positive and negative regulatory elements and to verify the status of these elements in steroid-nonresponsive F1BGH12C1 cells. Results presented in this report demonstrate that the basel level expression of the co-transferred Neo gene (neomycin phosphoribosyl transferase) is modulated by the distal upstream regulatory elements of rat PRL gene in response to steroid hormones. The expression of adjacent Neo gene is inhibited by dexamethasone and is stimulated by estradiol in transfectants carrying distal regulatory elements (SRE) of steroid-responsive cells. These responses are not observed in transfectants with the rat PRL upstream sequences derived from steroid-nonresponsive cells. The basal level expression of the host cell alpha-2 tubulin gene is not affected by dexamethasone. We report here the identification of the distal steroid regulatory element (SRE) located between 3.8 and 7.8 kb upstream of the transcription initiation site of rat PRL gene. Both the positive and the negative effects of steroid hormones can be identified within this upstream sequence. This distal SRE appears to be nonfunctional in steroid-nonresponsive cells. Though the proximal SRE is functional, the defect in the distal SRE makes the GH substrain nonresponsive to steroid hormones. These results suggest that both the proximal and the distal SREs are essential for the mediation of action of steroid hormones in GH cells.

PlantPAN: Plant promoter analysis navigator, for identifying combinatorial cis-regulatory elements with distance constraint in plant gene groups

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Huang Hsien-Da

2008-11-01

Full Text Available Abstract Background The elucidation of transcriptional regulation in plant genes is important area of research for plant scientists, following the mapping of various plant genomes, such as A. thaliana, O. sativa and Z. mays. A variety of bioinformatic servers or databases of plant promoters have been established, although most have been focused only on annotating transcription factor binding sites in a single gene and have neglected some important regulatory elements (tandem repeats and CpG/CpNpG islands in promoter regions. Additionally, the combinatorial interaction of transcription factors (TFs is important in regulating the gene group that is associated with the same expression pattern. Therefore, a tool for detecting the co-regulation of transcription factors in a group of gene promoters is required. Results This study develops a database-assisted system, PlantPAN (Plant Promoter Analysis Navigator, for recognizing combinatorial cis-regulatory elements with a distance constraint in sets of plant genes. The system collects the plant transcription factor binding profiles from PLACE, TRANSFAC (public release 7.0, AGRIS, and JASPER databases and allows users to input a group of gene IDs or promoter sequences, enabling the co-occurrence of combinatorial transcription factor binding sites (TFBSs within a defined distance (20 bp to 200 bp to be identified. Furthermore, the new resource enables other regulatory features in a plant promoter, such as CpG/CpNpG islands and tandem repeats, to be displayed. The regulatory elements in the conserved regions of the promoters across homologous genes are detected and presented. Conclusion In addition to providing a user-friendly input/output interface, PlantPAN has numerous advantages in the analysis of a plant promoter. Several case studies have established the effectiveness of PlantPAN. This novel analytical resource is now freely available at http://PlantPAN.mbc.nctu.edu.tw.

Regulatory analysis on the medical use of ephedrine-related products in Taiwan

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Wan-Nan Yu

2018-04-01

Full Text Available To prevent ephedrine-related products from being misused to produce amphetamine and/or its analogs, there's a need for more effective and achievable regulatory mechanisms for the health, police, investigational, prosecution and judiciary authorities in Taiwan. This review was conducted to evaluate the international and Taiwan's regulatory policies and management of medical ephedrine-related products through the corresponding information collected from international and Taiwan government agency authorities. The combat of illegal drugs should involve both supply and demand sides to be successful. Health authorities in Taiwan do not have the investigational power to manage the forbidden transformation, abusing and manufacture of the illegal drugs from ephedrine-related products. Take the judicial interventions in the United States and in Japan as the examples, the organizational cooperation in Taiwan can be one of the main key strategies to combat against illegal drugs from ephedrine-related products. It is necessary to integrate the judicial, police and health agencies to prevent the production of illegal drugs from the ephedrine-related products in Taiwan. The efforts and regulatory control measures should be integrated to speed up the collaboration between different government authorities. It might be achieved through reorganization involving Taiwan Food and Drug Administration. Keywords: Ephedrine-related products, Taiwan Food and Drug Administration (TFDA, Controlled Drugs Act, Pharmaceutical Affairs Act, Pharmacists Act

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

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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

The vertebrate Hox gene regulatory network for hindbrain segmentation: Evolution and diversification: Coupling of a Hox gene regulatory network to hindbrain segmentation is an ancient trait originating at the base of vertebrates.

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Parker, Hugo J; Bronner, Marianne E; Krumlauf, Robb

2016-06-01

Hindbrain development is orchestrated by a vertebrate gene regulatory network that generates segmental patterning along the anterior-posterior axis via Hox genes. Here, we review analyses of vertebrate and invertebrate chordate models that inform upon the evolutionary origin and diversification of this network. Evidence from the sea lamprey reveals that the hindbrain regulatory network generates rhombomeric compartments with segmental Hox expression and an underlying Hox code. We infer that this basal feature was present in ancestral vertebrates and, as an evolutionarily constrained developmental state, is fundamentally important for patterning of the vertebrate hindbrain across diverse lineages. Despite the common ground plan, vertebrates exhibit neuroanatomical diversity in lineage-specific patterns, with different vertebrates revealing variations of Hox expression in the hindbrain that could underlie this diversification. Invertebrate chordates lack hindbrain segmentation but exhibit some conserved aspects of this network, with retinoic acid signaling playing a role in establishing nested domains of Hox expression. © 2016 WILEY Periodicals, Inc.

Identification of putative regulatory motifs in the upstream regions of co-expressed functional groups of genes in Plasmodium falciparum

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Joshi NV

2009-01-01

Full Text Available Abstract Background Regulation of gene expression in Plasmodium falciparum (Pf remains poorly understood. While over half the genes are estimated to be regulated at the transcriptional level, few regulatory motifs and transcription regulators have been found. Results The study seeks to identify putative regulatory motifs in the upstream regions of 13 functional groups of genes expressed in the intraerythrocytic developmental cycle of Pf. Three motif-discovery programs were used for the purpose, and motifs were searched for only on the gene coding strand. Four motifs – the 'G-rich', the 'C-rich', the 'TGTG' and the 'CACA' motifs – were identified, and zero to all four of these occur in the 13 sets of upstream regions. The 'CACA motif' was absent in functional groups expressed during the ring to early trophozoite transition. For functional groups expressed in each transition, the motifs tended to be similar. Upstream motifs in some functional groups showed 'positional conservation' by occurring at similar positions relative to the translational start site (TLS; this increases their significance as regulatory motifs. In the ribonucleotide synthesis, mitochondrial, proteasome and organellar translation machinery genes, G-rich, C-rich, CACA and TGTG motifs, respectively, occur with striking positional conservation. In the organellar translation machinery group, G-rich motifs occur close to the TLS. The same motifs were sometimes identified for multiple functional groups; differences in location and abundance of the motifs appear to ensure different modes of action. Conclusion The identification of positionally conserved over-represented upstream motifs throws light on putative regulatory elements for transcription in Pf.

Quantitative inference of dynamic regulatory pathways via microarray data

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Chen Bor-Sen

2005-03-01

Full Text Available Abstract Background The cellular signaling pathway (network is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway are considered as the foundation of functional genomics. Thus, what genes and how much they influence each other through transcriptional binding or physical interactions are essential problems. Under the synchronous measures of gene expression via a microarray chip, an amount of dynamic information is embedded and remains to be discovered. Using a systematically dynamic modeling approach, we explore the causal relationship among genes in cellular signaling pathways from the system biology approach. Results In this study, a second-order dynamic model is developed to describe the regulatory mechanism of a target gene from the upstream causality point of view. From the expression profile and dynamic model of a target gene, we can estimate its upstream regulatory function. According to this upstream regulatory function, we would deduce the upstream regulatory genes with their regulatory abilities and activation delays, and then link up a regulatory pathway. Iteratively, these regulatory genes are considered as target genes to trace back their upstream regulatory genes. Then we could construct the regulatory pathway (or network to the genome wide. In short, we can infer the genetic regulatory pathways from gene-expression profiles quantitatively, which can confirm some doubted paths or seek some unknown paths in a regulatory pathway (network. Finally, the proposed approach is validated by randomly reshuffling the time order of microarray data. Conclusion We focus our algorithm on the inference of regulatory abilities of the identified causal genes, and how much delay before they regulate the downstream genes. With this information, a regulatory pathway would be built up using microarray data. In the present study, two signaling pathways, i.e. circadian regulatory

Memory functions reveal structural properties of gene regulatory networks

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Perez-Carrasco, Ruben

2018-01-01

Gene regulatory networks (GRNs) control cellular function and decision making during tissue development and homeostasis. Mathematical tools based on dynamical systems theory are often used to model these networks, but the size and complexity of these models mean that their behaviour is not always intuitive and the underlying mechanisms can be difficult to decipher. For this reason, methods that simplify and aid exploration of complex networks are necessary. To this end we develop a broadly applicable form of the Zwanzig-Mori projection. By first converting a thermodynamic state ensemble model of gene regulation into mass action reactions we derive a general method that produces a set of time evolution equations for a subset of components of a network. The influence of the rest of the network, the bulk, is captured by memory functions that describe how the subnetwork reacts to its own past state via components in the bulk. These memory functions provide probes of near-steady state dynamics, revealing information not easily accessible otherwise. We illustrate the method on a simple cross-repressive transcriptional motif to show that memory functions not only simplify the analysis of the subnetwork but also have a natural interpretation. We then apply the approach to a GRN from the vertebrate neural tube, a well characterised developmental transcriptional network composed of four interacting transcription factors. The memory functions reveal the function of specific links within the neural tube network and identify features of the regulatory structure that specifically increase the robustness of the network to initial conditions. Taken together, the study provides evidence that Zwanzig-Mori projections offer powerful and effective tools for simplifying and exploring the behaviour of GRNs. PMID:29470492

Generic Properties of Random Gene Regulatory Networks.

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Li, Zhiyuan; Bianco, Simone; Zhang, Zhaoyang; Tang, Chao

2013-12-01

Modeling gene regulatory networks (GRNs) is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits: steady state, periodic and chaotic, and how the dynamical properties change with network's topological characteristics. In this work, we first investigated these questions in random GRNs with different network sizes, connectivity, fraction of inhibitory links and transcription regulation rules. Then we searched for the core motifs that govern the dynamic behavior of large GRNs. We show that the stability of a random GRN is typically governed by a few embedding motifs of small sizes, and therefore can in general be understood in the context of these short motifs. Our results provide insights for the study and design of genetic networks.

Characterization of the bovine pregnancy-associated glycoprotein gene family – analysis of gene sequences, regulatory regions within the promoter and expression of selected genes

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Walker Angela M

2009-04-01

Full Text Available Abstract Background The Pregnancy-associated glycoproteins (PAGs belong to a large family of aspartic peptidases expressed exclusively in the placenta of species in the Artiodactyla order. In cattle, the PAG gene family is comprised of at least 22 transcribed genes, as well as some variants. Phylogenetic analyses have shown that the PAG family segregates into 'ancient' and 'modern' groupings. Along with sequence differences between family members, there are clear distinctions in their spatio-temporal distribution and in their relative level of expression. In this report, 1 we performed an in silico analysis of the bovine genome to further characterize the PAG gene family, 2 we scrutinized proximal promoter sequences of the PAG genes to evaluate the evolution pressures operating on them and to identify putative regulatory regions, 3 we determined relative transcript abundance of selected PAGs during pregnancy and, 4 we performed preliminary characterization of the putative regulatory elements for one of the candidate PAGs, bovine (bo PAG-2. Results From our analysis of the bovine genome, we identified 18 distinct PAG genes and 14 pseudogenes. We observed that the first 500 base pairs upstream of the translational start site contained multiple regions that are conserved among all boPAGs. However, a preponderance of conserved regions, that harbor recognition sites for putative transcriptional factors (TFs, were found to be unique to the modern boPAG grouping, but not the ancient boPAGs. We gathered evidence by means of Q-PCR and screening of EST databases to show that boPAG-2 is the most abundant of all boPAG transcripts. Finally, we provided preliminary evidence for the role of ETS- and DDVL-related TFs in the regulation of the boPAG-2 gene. Conclusion PAGs represent a relatively large gene family in the bovine genome. The proximal promoter regions of these genes display differences in putative TF binding sites, likely contributing to observed

An Intelligent Method of Product Scheme Design Based on Product Gene

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Qing Song Ai

2013-01-01

Full Text Available Nowadays, in order to have some featured products, many customers tend to buy customized products instead of buying common ones in supermarket. The manufacturing enterprises, with the purpose of improving their competitiveness, are focusing on providing customized products with high quality and low cost as well. At present, how to produce customized products rapidly and cheaply has been the key challenge to manufacturing enterprises. In this paper, an intelligent modeling approach applied to supporting the modeling of customized products is proposed, which may improve the efficiency during the product design process. Specifically, the product gene (PG method, which is an analogy of biological evolution in engineering area, is employed to model products in a new way. Based on product gene, we focus on the intelligent modeling method to generate product schemes rapidly and automatically. The process of our research includes three steps: (1 develop a product gene model for customized products; (2 find the obtainment and storage method for product gene; and (3 propose a specific genetic algorithm used for calculating the solution of customized product and generating new product schemes. Finally, a case study is applied to test the usefulness of our study.

Genetic characterization of the oxytocin-neurophysin I gene (OXT) and its regulatory regions analysis in domestic Old and New World camelids.

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Pauciullo, Alfredo; Ogah, Danlami Moses; Iannaccone, Marco; Erhardt, Georg; Di Stasio, Liliana; Cosenza, Gianfranco

2018-01-01

Oxytocin is a neurohypophysial peptide linked to a wide range of biological functions, including milk ejection, temperament and reproduction. Aims of the present study were a) the characterization of the OXT (Oxytocin-neurophysin I) gene and its regulatory regions in Old and New world camelids; b) the investigation of the genetic diversity and the discovery of markers potentially affecting the gene regulation. On average, the gene extends over 814 bp, ranging between 825 bp in dromedary, 811 bp in Bactrian and 810 bp in llama and alpaca. Such difference in size is due to a duplication event of 21 bp in dromedary. The main regulatory elements, including the composite hormone response elements (CHREs), were identified in the promoter, whereas the presence of mature microRNAs binding sequences in the 3'UTR improves the knowledge on the factors putatively involved in the OXT gene regulation, although their specific biological effect needs to be still elucidated. The sequencing of genomic DNA allowed the identification of 17 intraspecific polymorphisms and 69 nucleotide differences among the four species. One of these (MF464535:g.622C>G) is responsible, in alpaca, for the loss of a consensus sequence for the transcription factor SP1. Furthermore, the same SNP falls within a CpG island and it creates a new methylation site, thus opening future possibilities of investigation to verify the influence of the novel allelic variant in the OXT gene regulation. A PCR-RFLP method was setup for the genotyping and the frequency of the allele C was 0.93 in a population of 71 alpacas. The obtained data clarify the structure of OXT gene in domestic camelids and add knowledge to the genetic variability of a genomic region, which has received little investigation so far. These findings open the opportunity for new investigations, including association studies with productive and reproductive traits.

Cis-regulatory control of the nuclear receptor Coup-TF gene in the sea urchin Paracentrotus lividus embryo.

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Lamprini G Kalampoki

Full Text Available Coup-TF, an orphan member of the nuclear receptor super family, has a fundamental role in the development of metazoan embryos. The study of the gene's regulatory circuit in the sea urchin embryo will facilitate the placement of this transcription factor in the well-studied embryonic Gene Regulatory Network (GRN. The Paracentrotus lividus Coup-TF gene (PlCoup-TF is expressed throughout embryonic development preferentially in the oral ectoderm of the gastrula and the ciliary band of the pluteus stage. Two overlapping λ genomic clones, containing three exons and upstream sequences of PlCoup-TF, were isolated from a genomic library. The transcription initiation site was determined and 5' deletions and individual segments of a 1930 bp upstream region were placed ahead of a GFP reporter cassette and injected into fertilized P.lividus eggs. Module a (-532 to -232, was necessary and sufficient to confer ciliary band expression to the reporter. Comparison of P.lividus and Strongylocentrotus purpuratus upstream Coup-TF sequences, revealed considerable conservation, but none within module a. 5' and internal deletions into module a, defined a smaller region that confers ciliary band specific expression. Putative regulatory cis-acting elements (RE1, RE2 and RE3 within module a, were specifically bound by proteins in sea urchin embryonic nuclear extracts. Site-specific mutagenesis of these elements resulted in loss of reporter activity (RE1 or ectopic expression (RE2, RE3. It is proposed that sea urchin transcription factors, which bind these three regulatory sites, are necessary for spatial and quantitative regulation of the PlCoup-TF gene at pluteus stage sea urchin embryos. These findings lead to the future identification of these factors and to the hierarchical positioning of PlCoup-TF within the embryonic GRN.

Directed partial correlation: inferring large-scale gene regulatory network through induced topology disruptions.

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Yinyin Yuan

Full Text Available Inferring regulatory relationships among many genes based on their temporal variation in transcript abundance has been a popular research topic. Due to the nature of microarray experiments, classical tools for time series analysis lose power since the number of variables far exceeds the number of the samples. In this paper, we describe some of the existing multivariate inference techniques that are applicable to hundreds of variables and show the potential challenges for small-sample, large-scale data. We propose a directed partial correlation (DPC method as an efficient and effective solution to regulatory network inference using these data. Specifically for genomic data, the proposed method is designed to deal with large-scale datasets. It combines the efficiency of partial correlation for setting up network topology by testing conditional independence, and the concept of Granger causality to assess topology change with induced interruptions. The idea is that when a transcription factor is induced artificially within a gene network, the disruption of the network by the induction signifies a genes role in transcriptional regulation. The benchmarking results using GeneNetWeaver, the simulator for the DREAM challenges, provide strong evidence of the outstanding performance of the proposed DPC method. When applied to real biological data, the inferred starch metabolism network in Arabidopsis reveals many biologically meaningful network modules worthy of further investigation. These results collectively suggest DPC is a versatile tool for genomics research. The R package DPC is available for download (http://code.google.com/p/dpcnet/.

Correlation of gene expression and protein production rate - a system wide study

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Arvas Mikko

2011-12-01

Full Text Available Abstract Background Growth rate is a major determinant of intracellular function. However its effects can only be properly dissected with technically demanding chemostat cultivations in which it can be controlled. Recent work on Saccharomyces cerevisiae chemostat cultivations provided the first analysis on genome wide effects of growth rate. In this work we study the filamentous fungus Trichoderma reesei (Hypocrea jecorina that is an industrial protein production host known for its exceptional protein secretion capability. Interestingly, it exhibits a low growth rate protein production phenotype. Results We have used transcriptomics and proteomics to study the effect of growth rate and cell density on protein production in chemostat cultivations of T. reesei. Use of chemostat allowed control of growth rate and exact estimation of the extracellular specific protein production rate (SPPR. We find that major biosynthetic activities are all negatively correlated with SPPR. We also find that expression of many genes of secreted proteins and secondary metabolism, as well as various lineage specific, mostly unknown genes are positively correlated with SPPR. Finally, we enumerate possible regulators and regulatory mechanisms, arising from the data, for this response. Conclusions Based on these results it appears that in low growth rate protein production energy is very efficiently used primarly for protein production. Also, we propose that flux through early glycolysis or the TCA cycle is a more fundamental determining factor than growth rate for low growth rate protein production and we propose a novel eukaryotic response to this i.e. the lineage specific response (LSR.

Gene analogue finder: a GRID solution for finding functionally analogous gene products

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Licciulli Flavio

2007-09-01

Full Text Available Abstract Background To date more than 2,1 million gene products from more than 100000 different species have been described specifying their function, the processes they are involved in and their cellular localization using a very well defined and structured vocabulary, the gene ontology (GO. Such vast, well defined knowledge opens the possibility of compare gene products at the level of functionality, finding gene products which have a similar function or are involved in similar biological processes without relying on the conventional sequence similarity approach. Comparisons within such a large space of knowledge are highly data and computing intensive. For this reason this project was based upon the use of the computational GRID, a technology offering large computing and storage resources. Results We have developed a tool, GENe AnaloGue FINdEr (ENGINE that parallelizes the search process and distributes the calculation and data over the computational GRID, splitting the process into many sub-processes and joining the calculation and the data on the same machine and therefore completing the whole search in about 3 days instead of occupying one single machine for more than 5 CPU years. The results of the functional comparison contain potential functional analogues for more than 79000 gene products from the most important species. 46% of the analyzed gene products are well enough described for such an analysis to individuate functional analogues, such as well-known members of the same gene family, or gene products with similar functions which would never have been associated by standard methods. Conclusion ENGINE has produced a list of potential functionally analogous relations between gene products within and between species using, in place of the sequence, the gene description of the GO, thus demonstrating the potential of the GO. However, the current limiting factor is the quality of the associations of many gene products from non

Integration of Genome-Wide TF Binding and Gene Expression Data to Characterize Gene Regulatory Networks in Plant Development.

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Chen, Dijun; Kaufmann, Kerstin

2017-01-01

Key transcription factors (TFs) controlling the morphogenesis of flowers and leaves have been identified in the model plant Arabidopsis thaliana. Recent genome-wide approaches based on chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) enable systematic identification of genome-wide TF binding sites (TFBSs) of these regulators. Here, we describe a computational pipeline for analyzing ChIP-seq data to identify TFBSs and to characterize gene regulatory networks (GRNs) with applications to the regulatory studies of flower development. In particular, we provide step-by-step instructions on how to download, analyze, visualize, and integrate genome-wide data in order to construct GRNs for beginners of bioinformatics. The practical guide presented here is ready to apply to other similar ChIP-seq datasets to characterize GRNs of interest.

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

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

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Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier

An algebra-based method for inferring gene regulatory networks.

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Vera-Licona, Paola; Jarrah, Abdul; Garcia-Puente, Luis David; McGee, John; Laubenbacher, Reinhard

2014-03-26

The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the

As Gene Giants, os Agrotóxicos e as Sementes Transgênicas: o Papel Regulatório Brasileiro sob a perspectiva do Desenvolvimento Sustentável / The Gene Giants, Pesticides and Genetically Modified Seeds: The Brazilian Regulatory Role from the perspective of Sustainable Development

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Marcus Tullius Fernandes dos Santos

2016-10-01

Full Text Available Purpose – The purpose of this study is to analyze the market performance of the gene giants with respect to the production and marketing of pesticides and genetically modified seeds in Brazil, checking the regulatory role regarding control and supervision by the federal government, on par with the discussion on the implementation of sustainable development. Methodology/approach/design – Research of the literature associated with data collection and documents in the period 2005-2015 was implemented at the institutions responsible for the registration, release, control and inspection of GM seeds and pesticides in Brazil, using the institutional theory of law. The main idea is that laws and institutions have not crystallized culture of sustainability, since in their application on cases involving the gene giants economic interests have overshadowed weak regulatory modeling. Findings – There is need to establish a smart regulatory model so that regulation can be implemented by abandoning the one-sided view of the preponderance of economic interest. Only with strong regulatory, social and economic pressures can address the transnational nature of sustainable development in face of the power of big business corporations. Practical implications – Regulatory criteria were developed by avoiding the preponderance of economic interests at the expense of sensitive environmental, social, cultural, and political values.

The carboxy-terminal domain of Dictyostelium C-module-binding factor is an independent gene regulatory entity.

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Jörg Lucas

Full Text Available The C-module-binding factor (CbfA is a multidomain protein that belongs to the family of jumonji-type (JmjC transcription regulators. In the social amoeba Dictyostelium discoideum, CbfA regulates gene expression during the unicellular growth phase and multicellular development. CbfA and a related D. discoideum CbfA-like protein, CbfB, share a paralogous domain arrangement that includes the JmjC domain, presumably a chromatin-remodeling activity, and two zinc finger-like (ZF motifs. On the other hand, the CbfA and CbfB proteins have completely different carboxy-terminal domains, suggesting that the plasticity of such domains may have contributed to the adaptation of the CbfA-like transcription factors to the rapid genome evolution in the dictyostelid clade. To support this hypothesis we performed DNA microarray and real-time RT-PCR measurements and found that CbfA regulates at least 160 genes during the vegetative growth of D. discoideum cells. Functional annotation of these genes revealed that CbfA predominantly controls the expression of gene products involved in housekeeping functions, such as carbohydrate, purine nucleoside/nucleotide, and amino acid metabolism. The CbfA protein displays two different mechanisms of gene regulation. The expression of one set of CbfA-dependent genes requires at least the JmjC/ZF domain of the CbfA protein and thus may depend on chromatin modulation. Regulation of the larger group of genes, however, does not depend on the entire CbfA protein and requires only the carboxy-terminal domain of CbfA (CbfA-CTD. An AT-hook motif located in CbfA-CTD, which is known to mediate DNA binding to A+T-rich sequences in vitro, contributed to CbfA-CTD-dependent gene regulatory functions in vivo.

Functional and topological characteristics of mammalian regulatory domains

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Symmons, Orsolya; Uslu, Veli Vural; Tsujimura, Taro; Ruf, Sandra; Nassari, Sonya; Schwarzer, Wibke; Ettwiller, Laurence; Spitz, François

2014-01-01

Long-range regulatory interactions play an important role in shaping gene-expression programs. However, the genomic features that organize these activities are still poorly characterized. We conducted a large operational analysis to chart the distribution of gene regulatory activities along the mouse genome, using hundreds of insertions of a regulatory sensor. We found that enhancers distribute their activities along broad regions and not in a gene-centric manner, defining large regulatory domains. Remarkably, these domains correlate strongly with the recently described TADs, which partition the genome into distinct self-interacting blocks. Different features, including specific repeats and CTCF-binding sites, correlate with the transition zones separating regulatory domains, and may help to further organize promiscuously distributed regulatory influences within large domains. These findings support a model of genomic organization where TADs confine regulatory activities to specific but large regulatory domains, contributing to the establishment of specific gene expression profiles. PMID:24398455

Correlating Information Contents of Gene Ontology Terms to Infer Semantic Similarity of Gene Products

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Mingxin Gan

2014-01-01

Full Text Available Successful applications of the gene ontology to the inference of functional relationships between gene products in recent years have raised the need for computational methods to automatically calculate semantic similarity between gene products based on semantic similarity of gene ontology terms. Nevertheless, existing methods, though having been widely used in a variety of applications, may significantly overestimate semantic similarity between genes that are actually not functionally related, thereby yielding misleading results in applications. To overcome this limitation, we propose to represent a gene product as a vector that is composed of information contents of gene ontology terms annotated for the gene product, and we suggest calculating similarity between two gene products as the relatedness of their corresponding vectors using three measures: Pearson’s correlation coefficient, cosine similarity, and the Jaccard index. We focus on the biological process domain of the gene ontology and annotations of yeast proteins to study the effectiveness of the proposed measures. Results show that semantic similarity scores calculated using the proposed measures are more consistent with known biological knowledge than those derived using a list of existing methods, suggesting the effectiveness of our method in characterizing functional relationships between gene products.

Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

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Alina Sîrbu

2015-05-01

Full Text Available Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions. Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks.

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Sîrbu, Alina; Crane, Martin; Ruskin, Heather J

2015-05-14

Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions). Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

GRN2SBML: automated encoding and annotation of inferred gene regulatory networks complying with SBML.

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Vlaic, Sebastian; Hoffmann, Bianca; Kupfer, Peter; Weber, Michael; Dräger, Andreas

2013-09-01

GRN2SBML automatically encodes gene regulatory networks derived from several inference tools in systems biology markup language. Providing a graphical user interface, the networks can be annotated via the simple object access protocol (SOAP)-based application programming interface of BioMart Central Portal and minimum information required in the annotation of models registry. Additionally, we provide an R-package, which processes the output of supported inference algorithms and automatically passes all required parameters to GRN2SBML. Therefore, GRN2SBML closes a gap in the processing pipeline between the inference of gene regulatory networks and their subsequent analysis, visualization and storage. GRN2SBML is freely available under the GNU Public License version 3 and can be downloaded from http://www.hki-jena.de/index.php/0/2/490. General information on GRN2SBML, examples and tutorials are available at the tool's web page.

Bringing a probiotic-containing functional food to the market: microbiological, product, regulatory and labeling issues.

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Sanders, M E; Huis in't Veld, J

1999-01-01

Properly formulated probiotic-containing foods offer consumers a low risk, low cost dietary component that has the potential to promote health in a variety of ways. Several such products are available commercially, although markets in Japan and Europe are more developed than in the USA. Once healthful attributes of a probiotic product have been identified, there remain microbiological, product, regulatory and labeling issues to be addressed prior to marketing. Microbiological and product issues include safety, effective scale-up for manufacturing, definition of probiotic activity, probiotic stability in the product over the course of product manufacture, shelf-life and consumption, definition of effective dose and target population(s), and development of quality assurance approaches. Examples of probiotic-containing foods are given. Regulatory and labeling issues are complicated because they differ for each country, but are likewise critical because they provide the means for communication of the product benefits to the consumer. The regulatory climate worldwide appears to be one of caution about overstating the benefits of such products but at the same time not preventing corporate commitment to marketing.

Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method.

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Grassi, Angela; Di Camillo, Barbara; Ciccarese, Francesco; Agnusdei, Valentina; Zanovello, Paola; Amadori, Alberto; Finesso, Lorenzo; Indraccolo, Stefano; Toffolo, Gianna Maria

2016-03-12

Inference of gene regulation from expression data may help to unravel regulatory mechanisms involved in complex diseases or in the action of specific drugs. A challenging task for many researchers working in the field of systems biology is to build up an experiment with a limited budget and produce a dataset suitable to reconstruct putative regulatory modules worth of biological validation. Here, we focus on small-scale gene expression screens and we introduce a novel experimental set-up and a customized method of analysis to make inference on regulatory modules starting from genetic perturbation data, e.g. knockdown and overexpression data. To illustrate the utility of our strategy, it was applied to produce and analyze a dataset of quantitative real-time RT-PCR data, in which interferon-α (IFN-α) transcriptional response in endothelial cells is investigated by RNA silencing of two candidate IFN-α modulators, STAT1 and IFIH1. A putative regulatory module was reconstructed by our method, revealing an intriguing feed-forward loop, in which STAT1 regulates IFIH1 and they both negatively regulate IFNAR1. STAT1 regulation on IFNAR1 was object of experimental validation at the protein level. Detailed description of the experimental set-up and of the analysis procedure is reported, with the intent to be of inspiration for other scientists who want to realize similar experiments to reconstruct gene regulatory modules starting from perturbations of possible regulators. Application of our approach to the study of IFN-α transcriptional response modulators in endothelial cells has led to many interesting novel findings and new biological hypotheses worth of validation.

Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.

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Gong, Wuming; Koyano-Nakagawa, Naoko; Li, Tongbin; Garry, Daniel J

2015-03-07

Decoding the temporal control of gene expression patterns is key to the understanding of the complex mechanisms that govern developmental decisions during heart development. High-throughput methods have been employed to systematically study the dynamic and coordinated nature of cardiac differentiation at the global level with multiple dimensions. Therefore, there is a pressing need to develop a systems approach to integrate these data from individual studies and infer the dynamic regulatory networks in an unbiased fashion. We developed a two-step strategy to integrate data from (1) temporal RNA-seq, (2) temporal histone modification ChIP-seq, (3) transcription factor (TF) ChIP-seq and (4) gene perturbation experiments to reconstruct the dynamic network during heart development. First, we trained a logistic regression model to predict the probability (LR score) of any base being bound by 543 TFs with known positional weight matrices. Second, four dimensions of data were combined using a time-varying dynamic Bayesian network model to infer the dynamic networks at four developmental stages in the mouse [mouse embryonic stem cells (ESCs), mesoderm (MES), cardiac progenitors (CP) and cardiomyocytes (CM)]. Our method not only infers the time-varying networks between different stages of heart development, but it also identifies the TF binding sites associated with promoter or enhancers of downstream genes. The LR scores of experimentally verified ESCs and heart enhancers were significantly higher than random regions (p network inference model identified a region with an elevated LR score approximately -9400 bp upstream of the transcriptional start site of Nkx2-5, which overlapped with a previously reported enhancer region (-9435 to -8922 bp). TFs such as Tead1, Gata4, Msx2, and Tgif1 were predicted to bind to this region and participate in the regulation of Nkx2-5 gene expression. Our model also predicted the key regulatory networks for the ESC-MES, MES-CP and CP

Nucleotide sequences of the Erwinia chrysanthemi ogl and pelE genes negatively regulated by the kdgR gene product.

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Reverchon, S; Huang, Y; Bourson, C; Robert-Baudouy, J

1989-12-21

The nucleotide sequences of the coding and regulatory regions of the genes encoding oligoglacturonate lyase (OGL) and pectate lyase e isoenzyme (PLe) from Erwinia chrysanthemi 3937 were determined. The ogl sequence contains an open reading frame (ORF) of 1164 bp coding for a 388-amino acid (aa) polypeptide with a predicted Mr of 44,124. A possible transcriptional start signal showing homology with the Escherichia coli promoter consensus sequence was detected. In addition, a sequence 3' to the coding region was found to be able to form a secondary structure which may function as an Rho-independent transcriptional termination signal. For the pelE sequence, a long ORF of 1212 bp coding for a 404-aa polypeptide was detected. PLe is secreted into the external medium by E. chrysanthemi, and a potential signal peptide sequence was identified in the pelE gene. In the 5' upstream pelE coding region, a putative promoter resembling E. coli promoter consensus sequences was detected. Furthermore, the region immediately 3' to the pelE translational stop codon may function as an Rho-independent translational termination signal. In strain 3937, the synthesis of OGL and PLe, as well as the other enzymes involved in the pectin-degradative pathway (particularly the kdgT product), are known to be regulated by the KdgR repressor, which mediates galacturonate and polygalacturonate induction. Synthesis of these enzymes is also regulated by the CRP-cAMP complex which mediates catabolite repression. Analysis of the regulatory regions of ogl and pelE allowed us to identify possible CRP-binding sites for these two genes.(ABSTRACT TRUNCATED AT 250 WORDS)

Cooperative adaptive responses in gene regulatory networks with many degrees of freedom.

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Inoue, Masayo; Kaneko, Kunihiko

2013-04-01

Cells generally adapt to environmental changes by first exhibiting an immediate response and then gradually returning to their original state to achieve homeostasis. Although simple network motifs consisting of a few genes have been shown to exhibit such adaptive dynamics, they do not reflect the complexity of real cells, where the expression of a large number of genes activates or represses other genes, permitting adaptive behaviors. Here, we investigated the responses of gene regulatory networks containing many genes that have undergone numerical evolution to achieve high fitness due to the adaptive response of only a single target gene; this single target gene responds to changes in external inputs and later returns to basal levels. Despite setting a single target, most genes showed adaptive responses after evolution. Such adaptive dynamics were not due to common motifs within a few genes; even without such motifs, almost all genes showed adaptation, albeit sometimes partial adaptation, in the sense that expression levels did not always return to original levels. The genes split into two groups: genes in the first group exhibited an initial increase in expression and then returned to basal levels, while genes in the second group exhibited the opposite changes in expression. From this model, genes in the first group received positive input from other genes within the first group, but negative input from genes in the second group, and vice versa. Thus, the adaptation dynamics of genes from both groups were consolidated. This cooperative adaptive behavior was commonly observed if the number of genes involved was larger than the order of ten. These results have implications in the collective responses of gene expression networks in microarray measurements of yeast Saccharomyces cerevisiae and the significance to the biological homeostasis of systems with many components.

A relative variation-based method to unraveling gene regulatory networks.

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Yali Wang

Full Text Available Gene regulatory network (GRN reconstruction is essential in understanding the functioning and pathology of a biological system. Extensive models and algorithms have been developed to unravel a GRN. The DREAM project aims to clarify both advantages and disadvantages of these methods from an application viewpoint. An interesting yet surprising observation is that compared with complicated methods like those based on nonlinear differential equations, etc., methods based on a simple statistics, such as the so-called Z-score, usually perform better. A fundamental problem with the Z-score, however, is that direct and indirect regulations can not be easily distinguished. To overcome this drawback, a relative expression level variation (RELV based GRN inference algorithm is suggested in this paper, which consists of three major steps. Firstly, on the basis of wild type and single gene knockout/knockdown experimental data, the magnitude of RELV of a gene is estimated. Secondly, probability for the existence of a direct regulation from a perturbed gene to a measured gene is estimated, which is further utilized to estimate whether a gene can be regulated by other genes. Finally, the normalized RELVs are modified to make genes with an estimated zero in-degree have smaller RELVs in magnitude than the other genes, which is used afterwards in queuing possibilities of the existence of direct regulations among genes and therefore leads to an estimate on the GRN topology. This method can in principle avoid the so-called cascade errors under certain situations. Computational results with the Size 100 sub-challenges of DREAM3 and DREAM4 show that, compared with the Z-score based method, prediction performances can be substantially improved, especially the AUPR specification. Moreover, it can even outperform the best team of both DREAM3 and DREAM4. Furthermore, the high precision of the obtained most reliable predictions shows that the suggested algorithm may be

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...

Spatiotemporal network motif reveals the biological traits of developmental gene regulatory networks in Drosophila melanogaster

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Kim Man-Sun

2012-05-01

Full Text Available Abstract Background Network motifs provided a “conceptual tool” for understanding the functional principles of biological networks, but such motifs have primarily been used to consider static network structures. Static networks, however, cannot be used to reveal time- and region-specific traits of biological systems. To overcome this limitation, we proposed the concept of a “spatiotemporal network motif,” a spatiotemporal sequence of network motifs of sub-networks which are active only at specific time points and body parts. Results On the basis of this concept, we analyzed the developmental gene regulatory network of the Drosophila melanogaster embryo. We identified spatiotemporal network motifs and investigated their distribution pattern in time and space. As a result, we found how key developmental processes are temporally and spatially regulated by the gene network. In particular, we found that nested feedback loops appeared frequently throughout the entire developmental process. From mathematical simulations, we found that mutual inhibition in the nested feedback loops contributes to the formation of spatial expression patterns. Conclusions Taken together, the proposed concept and the simulations can be used to unravel the design principle of developmental gene regulatory networks.

Evolutionary changes of Hox genes and relevant regulatory factors provide novel insights into mammalian morphological modifications.

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Li, Kui; Sun, Xiaohui; Chen, Meixiu; Sun, Yingying; Tian, Ran; Wang, Zhengfei; Xu, Shixia; Yang, Guang

2018-01-01

The diversity of body plans of mammals accelerates the innovation of lifestyles and the extensive adaptation to different habitats, including terrestrial, aerial and aquatic habitats. However, the genetic basis of those phenotypic modifications, which have occurred during mammalian evolution, remains poorly explored. In the present study, we synthetically surveyed the evolutionary pattern of Hox clusters that played a powerful role in the morphogenesis along the head-tail axis of animal embryos and the main regulatory factors (Mll, Bmi1 and E2f6) that control the expression of Hox genes. A deflected density of repetitive elements and lineage-specific radical mutations of Mll have been determined in marine mammals with morphological changes, suggesting that evolutionary changes may alter Hox gene expression in these lineages, leading to the morphological modification of these lineages. Although no positive selection was detected at certain ancestor nodes of lineages, the increased ω values of Hox genes implied the relaxation of functional constraints of these genes during the mammalian evolutionary process. More importantly, 49 positively-selected sites were identified in mammalian lineages with phenotypic modifications, indicating adaptive evolution acting on Hox genes and regulatory factors. In addition, 3 parallel amino acid substitutions in some Hox genes were examined in marine mammals, which might be responsible for their streamlined body. © 2017 The Authors. Integrative Zoology published by International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Feast/famine regulatory proteins (FFRPs): Escherichia coli Lrp, AsnC and related archaeal transcription factors.

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Yokoyama, Katsushi; Ishijima, Sanae A; Clowney, Lester; Koike, Hideaki; Aramaki, Hironori; Tanaka, Chikako; Makino, Kozo; Suzuki, Masashi

2006-01-01

Feast/famine regulatory proteins comprise a diverse family of transcription factors, which have been referred to in various individual identifications, including Escherichia coli leucine-responsive regulatory protein and asparagine synthase C gene product. A full length feast/famine regulatory protein consists of the N-terminal DNA-binding domain and the C-domain, which is involved in dimerization and further assembly, thereby producing, for example, a disc or a chromatin-like cylinder. Various ligands of the size of amino acids bind at the interface between feast/famine regulatory protein dimers, thereby altering their assembly forms. Also, the combination of feast/famine regulatory protein subunits forming the same assembly is altered. In this way, a small number of feast/famine regulatory proteins are able to regulate a large number of genes in response to various environmental changes. Because feast/famine regulatory proteins are shared by archaea and eubacteria, the genome-wide regulation by feast/famine regulatory proteins is traceable back to their common ancestor, being the prototype of highly differentiated transcription regulatory mechanisms found in organisms nowadays.

Retinal Expression of the Drosophila eyes absent Gene Is Controlled by Several Cooperatively Acting Cis-regulatory Elements

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Neuman, Sarah D.; Bashirullah, Arash; Kumar, Justin P.

2016-01-01

The eyes absent (eya) gene of the fruit fly, Drosophila melanogaster, is a member of an evolutionarily conserved gene regulatory network that controls eye formation in all seeing animals. The loss of eya leads to the complete elimination of the compound eye while forced expression of eya in non-retinal tissues is sufficient to induce ectopic eye formation. Within the developing retina eya is expressed in a dynamic pattern and is involved in tissue specification/determination, cell proliferation, apoptosis, and cell fate choice. In this report we explore the mechanisms by which eya expression is spatially and temporally governed in the developing eye. We demonstrate that multiple cis-regulatory elements function cooperatively to control eya transcription and that spacing between a pair of enhancer elements is important for maintaining correct gene expression. Lastly, we show that the loss of eya expression in sine oculis (so) mutants is the result of massive cell death and a progressive homeotic transformation of retinal progenitor cells into head epidermis. PMID:27930646

Manufacturing, regulatory and commercial challenges of biopharmaceuticals production: a Finnish perspective.

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Närhi, Marko; Nordström, Katrina

2005-04-01

Biopharmaceuticals product development is a broad and multidisciplinary field. Science and technology are combined with new manufacturing, regulatory and commercial challenges. However, although there is ample literature on the molecular biology and biochemistry of products, the implementation of processes from test tube to commercial scale has not received similar attention. Consequently, the present study aims to highlight, from practical point of view, some of the key issues involved with manufacturing technologies of biopharmaceuticals at a commercial scale. Regulatory requirements and investments are also addressed based on the practical experiences of start-up and small companies. Finland is used as a case-example of such companies as this is a EU-member state with strong technological growth and rapidly increasing number of biotech companies.

Transcriptional analysis of the jamaicamide gene cluster from the marine cyanobacterium Lyngbya majuscula and identification of possible regulatory proteins

Directory of Open Access Journals (Sweden)

Dorrestein Pieter C

2009-12-01

Full Text Available Abstract Background The marine cyanobacterium Lyngbya majuscula is a prolific producer of bioactive secondary metabolites. Although biosynthetic gene clusters encoding several of these compounds have been identified, little is known about how these clusters of genes are transcribed or regulated, and techniques targeting genetic manipulation in Lyngbya strains have not yet been developed. We conducted transcriptional analyses of the jamaicamide gene cluster from a Jamaican strain of Lyngbya majuscula, and isolated proteins that could be involved in jamaicamide regulation. Results An unusually long untranslated leader region of approximately 840 bp is located between the jamaicamide transcription start site (TSS and gene cluster start codon. All of the intergenic regions between the pathway ORFs were transcribed into RNA in RT-PCR experiments; however, a promoter prediction program indicated the possible presence of promoters in multiple intergenic regions. Because the functionality of these promoters could not be verified in vivo, we used a reporter gene assay in E. coli to show that several of these intergenic regions, as well as the primary promoter preceding the TSS, are capable of driving β-galactosidase production. A protein pulldown assay was also used to isolate proteins that may regulate the jamaicamide pathway. Pulldown experiments using the intergenic region upstream of jamA as a DNA probe isolated two proteins that were identified by LC-MS/MS. By BLAST analysis, one of these had close sequence identity to a regulatory protein in another cyanobacterial species. Protein comparisons suggest a possible correlation between secondary metabolism regulation and light dependent complementary chromatic adaptation. Electromobility shift assays were used to evaluate binding of the recombinant proteins to the jamaicamide promoter region. Conclusion Insights into natural product regulation in cyanobacteria are of significant value to drug discovery

Algebraic model checking for Boolean gene regulatory networks.

Science.gov (United States)

Tran, Quoc-Nam

2011-01-01

We present a computational method in which modular and Groebner bases (GB) computation in Boolean rings are used for solving problems in Boolean gene regulatory networks (BN). In contrast to other known algebraic approaches, the degree of intermediate polynomials during the calculation of Groebner bases using our method will never grow resulting in a significant improvement in running time and memory space consumption. We also show how calculation in temporal logic for model checking can be done by means of our direct and efficient Groebner basis computation in Boolean rings. We present our experimental results in finding attractors and control strategies of Boolean networks to illustrate our theoretical arguments. The results are promising. Our algebraic approach is more efficient than the state-of-the-art model checker NuSMV on BNs. More importantly, our approach finds all solutions for the BN problems.

Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

Science.gov (United States)

Patel, Nihir; Wang, Jason T L

2015-10-01

Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.

Regulatory requirements for the use of consumer products containing radioactive substances

International Nuclear Information System (INIS)

Mason, G.C.; Paynter, R.A.; Schmitt-Hannig, A.; Sztanyik, L.B.

1996-01-01

In almost 100 years since the discovery of radioactivity, the properties of radioactive materials have been exploited in products such as clocks and watches incorporating luminous paint which are freely available to members of the public. Over time, regulatory authorities have felt it necessary to apply some degree of control to the supply and use of such products in order to protect public health. In many areas of radiation protection, national authorities take note of international recommendations when developing national standards, but the existing detailed guidance of the International Atomic Energy Agency (IAEA) for consumer products is incomplete and out of date. Recently, a thorough revision of the International Basic Safety Standards (BSS) has occurred, which has prompted a review and revision of the related guidance published by the IAEA. A draft Guide on Regulatory Requirements for the Use of Consumer Products Containing Radioactive Substances has now been completed and is currently under review within the IAEA's system for development of documents in its Safety Series of publications. (author)

Evolutionary dynamics of DNA-binding sites and direct target genes of a floral master regulatory transcription factor [RNA-Seq

NARCIS (Netherlands)

Muiño, J.M.; Bruijn, de S.A.; Vingron, Martin; Angenent, G.C.; Kaufmann, Kerstin

2015-01-01

Plant development is controlled by transcription factors (TFs) which form complex gene-regulatory networks. Genome-wide TF DNA-binding studies revealed that these TFs have several thousands of binding sites in the Arabidopsis genome, and may regulate the expression of many genes directly. Given the

A canonical correlation analysis-based dynamic bayesian network prior to infer gene regulatory networks from multiple types of biological data.

Science.gov (United States)

Baur, Brittany; Bozdag, Serdar

2015-04-01

One of the challenging and important computational problems in systems biology is to infer gene regulatory networks (GRNs) of biological systems. Several methods that exploit gene expression data have been developed to tackle this problem. In this study, we propose the use of copy number and DNA methylation data to infer GRNs. We developed an algorithm that scores regulatory interactions between genes based on canonical correlation analysis. In this algorithm, copy number or DNA methylation variables are treated as potential regulator variables, and expression variables are treated as potential target variables. We first validated that the canonical correlation analysis method is able to infer true interactions in high accuracy. We showed that the use of DNA methylation or copy number datasets leads to improved inference over steady-state expression. Our results also showed that epigenetic and structural information could be used to infer directionality of regulatory interactions. Additional improvements in GRN inference can be gleaned from incorporating the result in an informative prior in a dynamic Bayesian algorithm. This is the first study that incorporates copy number and DNA methylation into an informative prior in dynamic Bayesian framework. By closely examining top-scoring interactions with different sources of epigenetic or structural information, we also identified potential novel regulatory interactions.

Enhanced regulatory gene expressions in the blood and articular cartilage of patients with rheumatoid arthritis

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Elena Vasilyevna Chetina

2012-01-01

Full Text Available Objective: to study the expression ratio of the non-tissue specific regulatory genes mTOR, р21, ATG1, caspase 3, tumor necrosis factor-а (TNF-а, and interleukin-6 (IL-6, as well as matrix metalloproteinase 13 (MMP-13 and X type collagen (COL10A1, cartilage resorption-associated MMP13 and COL10A1 in the blood and knee articular cartilage in patients with rheumatoid arthritis (RA. Subjects and methods. Twenty-five specimens of the distal femoral articular cartilage condyles were studied in 15 RA patients (mean age 52.4+9.1 years after endoprosthetic knee joint replacement and in 10 healthy individuals (mean age 36.0+9.1 years included into the control group. Twenty-eight blood samples taken from 28 RA patients (aged 52+7.6 years prior to endoprosthetic knee joint replacement and 27 blood samples from healthy individuals (mean age 53.6+8.3 years; a control group were also analyzed. Real-time quantitative polymerase chain reaction was applied to estimate the expression of the mTOR, p21, ATG1, caspase 3, TNF-а, IL- 6, COL0A1, and MMP-13 genes. The levels of a protein equivalent in the p70-S6K(activated by mTOR, p21, and caspase 3 genes concerned was measured in the isolated lymphocyte lysates, by applying the commercially available ELISA kits. Total protein in the cell extracts was determined using the Bradford assay procedure. Results. The cartilage samples from patients with end-stage RA exhibited a significantly higher mTOR, ATG1, p21, TNFа, MMP-13, and COL10A1 gene expressions than did those from the healthy individuals. At the same time, IL6 gene expression was much lower than that in the control group. The expressions of the mTOR, ATG1, p21, TNFа, and IL 6 genes in the blood of RA patients were much greater than those in the donors. Caspase 3 expression did not differ essentially in the bloods of the patients with RA and healthy individuals. The bloods failed to show MMP-13 and COL10A1 expressions. High mTOR and p21 gene expressions were

Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

Science.gov (United States)

Watson, Emma; MacNeil, Lesley T; Arda, H Efsun; Zhu, Lihua Julie; Walhout, Albertha J M

2013-03-28

Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus. Copyright © 2013 Elsevier Inc. All rights reserved.

Co-ordinate regulation of Salmonella typhimurium invasion genes by environmental and regulatory factors is mediated by control of hilA expression.

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Bajaj, V; Lucas, R L; Hwang, C; Lee, C A

1996-11-01

During infection of their hosts, salmonellae enter intestinal epithelial cells. It has been proposed that when Salmonella typhimurium is present in the intestinal lumen, several environmental and regulatory conditions modulate the expression of invasion factors required for bacterial entry into host cells. We report here that the expression of six different S. typhimurium invasion genes encoded on SPI1 (Salmonella pathogenicity island 1) is co-ordinately regulated by oxygen, osmolarity, pH, PhoPQ, and HilA. HilA is a transcriptional activator of the OmpR/ToxR family that is also encoded on SPI1. We have found that HilA plays a central role in the co-ordinated regulation of invasion genes by environmental and regulatory conditions. HilA can activate the expression of two invasion gene-lacZY fusions on reporter plasmids in Escherichia coll, suggesting that HilA acts directly at invasion-gene promoters in S. typhimurium. We have found that the regulation of invasion genes by oxygen, osmolarity, pH, and PhoPQ is indirect and is mediated by regulation of hilA expression by these environmental and regulatory factors. We hypothesize that the complex and co-ordinate regulation of Invasion genes by HilA is an important feature of salmonella pathogenesis and allows salmonellae to enter intestinal epithelial cells.

Prediction of regulatory elements

DEFF Research Database (Denmark)

Sandelin, Albin

2008-01-01

Finding the regulatory mechanisms responsible for gene expression remains one of the most important challenges for biomedical research. A major focus in cellular biology is to find functional transcription factor binding sites (TFBS) responsible for the regulation of a downstream gene. As wet......-lab methods are time consuming and expensive, it is not realistic to identify TFBS for all uncharacterized genes in the genome by purely experimental means. Computational methods aimed at predicting potential regulatory regions can increase the efficiency of wet-lab experiments significantly. Here, methods...

5' Region of the human interleukin 4 gene: structure and potential regulatory elements

Energy Technology Data Exchange (ETDEWEB)

Eder, A; Krafft-Czepa, H; Krammer, P H

1988-01-25

The lymphokine Interleukin 4 (IL-4) is secreted by antigen or mitogen activated T lymphocytes. IL-4 stimulates activation and differentiation of B lymphocytes and growth of T lymphocytes and mast cells. The authors isolated the human IL-4 gene from a lambda EMBL3 genomic library. As a probe they used a synthetic oligonucleotide spanning position 40 to 79 of the published IL-4 cDNA sequence. The 5' promoter region contains several sequence elements which may have a cis-acting regulatory function for IL-4 gene expression. These elements include a TATA-box, three CCAAT-elements (two are on the non-coding strand) and an octamer motif. A comparison of the 5' flanking region of the human murine IL-4 gene (4) shows that the region between position -306 and +44 is highly conserved (83% homology).

Inhibition effect of B7-H1 gene-modified regulatory dendritic cells on thyroid-associated ophthalmopathy in mice

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Hua-Xin Chen

2014-10-01

Full Text Available AIM:To construct adenovirus vector expressing mice B7-H1 gene, transfect dendritic cells(DCs, and to study the therapeutic effect of modified DC on thyroid-associated ophthalmopathy(TAOin mice.METHODS: We designed and constructed B7-H1 gene adenovirus expression vector, and transfected DCs from mouse bone marrow, tested the phenotype and function of modified DCs, identificated its negative regulation to immune responses. The modified DCs were infected the sicked mice. And then the immunotherapeutic effect of modified DCs to TAO were tested. RESULTS: B7-H1 gene adenovirus vector was constructed and transfected DCs from bone marrow. The titer of the recombinant adenovirus was 1.8×109PFU/mL. B7-H1 gene modified DCs characteristics of regulatory DCs, could inhibit positive immune responses. The inhibition proceeding of TAO into mice infected modified DCs, was obviously prior to the control mice. The gene modified DCs, maybe become the new immunotherapy biological agent to thy TAO.CONCLUSION: We constructed the expression of mouse B7-H1 gene adenovirus expressed vector successfully, transfected DCs,by vector have properties of regulatory DCs, inhibiting positive immune response and the occurrence and development of thyroid eye disease. Gene modified DCs, reveal potent to the treatment of thyroid eye disease.

Functional characterization of a three-component regulatory system involved in quorum sensing-based regulation of peptide antibiotic production in Carnobacterium maltaromaticum

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Quadri Luis EN

2006-10-01

Full Text Available Abstract Background Quorum sensing is a form of cell-to-cell communication that allows bacteria to control a wide range of physiological processes in a population density-dependent manner. Production of peptide antibiotics is one of the processes regulated by quorum sensing in several species of Gram-positive bacteria, including strains of Carnobacterium maltaromaticum. This bacterium and its peptide antibiotics are of interest due to their potential applications in food preservation. The molecular bases of the quorum sensing phenomenon controlling peptide antibiotic production in C. maltaromaticum remain poorly understood. The present study was aimed at gaining a deeper insight into the molecular mechanism involved in quorum sensing-mediated regulation of peptide antibiotic (bacteriocin production by C. maltaromaticum. We report the functional analyses of the CS (autoinducer-CbnK (histidine protein kinase-CbnR (response regulator three-component regulatory system and the three regulated promoters involved in peptide antibiotic production in C. maltaromaticum LV17B. Results CS-CbnK-CbnR system-dependent activation of carnobacterial promoters was demonstrated in both homologous and heterologous hosts using a two-plasmid system with a β-glucuronidase (GusA reporter read-out. The results of our analyses support a model in which the CbnK-CbnR two-component signal transduction system is necessary and sufficient to transduce the signal of the peptide autoinducer CS into the activation of the promoters that drive the expression of the genes required for production of the carnobacterial peptide antibiotics and the immunity proteins that protect the producer bacterium. Conclusions The CS-CbnK-CbnR triad forms a three-component regulatory system by which production of peptide antibiotics by C. maltaromaticum LV17B is controlled in a population density-dependent (or cell proximity-dependent manner. This regulatory mechanism would permit the bacterial

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.

Equivalence of complex drug products: advances in and challenges for current regulatory frameworks.

Science.gov (United States)

Hussaarts, Leonie; Mühlebach, Stefan; Shah, Vinod P; McNeil, Scott; Borchard, Gerrit; Flühmann, Beat; Weinstein, Vera; Neervannan, Sesha; Griffiths, Elwyn; Jiang, Wenlei; Wolff-Holz, Elena; Crommelin, Daan J A; de Vlieger, Jon S B

2017-11-01

Biotechnology and nanotechnology provide a growing number of innovator-driven complex drug products and their copy versions. Biologics exemplify one category of complex drugs, but there are also nonbiological complex drug products, including many nanomedicines, such as iron-carbohydrate complexes, drug-carrying liposomes or emulsions, and glatiramoids. In this white paper, which stems from a 1-day conference at the New York Academy of Sciences, we discuss regulatory frameworks in use worldwide (e.g., the U.S. Food and Drug Administration, the European Medicines Agency, the World Health Organization) to approve these complex drug products and their follow-on versions. One of the key questions remains how to assess equivalence of these complex products. We identify a number of points for which consensus was found among the stakeholders who were present: scientists from innovator and generic/follow-on companies, academia, and regulatory bodies from different parts of the world. A number of topics requiring follow-up were identified: (1) assessment of critical attributes to establish equivalence for follow-on versions, (2) the need to publish scientific findings in the public domain to further progress in the field, (3) the necessity to develop worldwide consensus regarding nomenclature and labeling of these complex products, and (4) regulatory actions when substandard complex drug products are identified. © 2017 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

DEFF Research Database (Denmark)

Kogelman, Lisette; Cirera Salicio, Susanna; Zhernakova, Daria V.

2014-01-01

interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model...... (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. Results WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P ... the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using...

Delay-independent stability of genetic regulatory networks.

Science.gov (United States)

Wu, Fang-Xiang

2011-11-01

Genetic regulatory networks can be described by nonlinear differential equations with time delays. In this paper, we study both locally and globally delay-independent stability of genetic regulatory networks, taking messenger ribonucleic acid alternative splicing into consideration. Based on nonnegative matrix theory, we first develop necessary and sufficient conditions for locally delay-independent stability of genetic regulatory networks with multiple time delays. Compared to the previous results, these conditions are easy to verify. Then we develop sufficient conditions for global delay-independent stability for genetic regulatory networks. Compared to the previous results, this sufficient condition is less conservative. To illustrate theorems developed in this paper, we analyze delay-independent stability of two genetic regulatory networks: a real-life repressilatory network with three genes and three proteins, and a synthetic gene regulatory network with five genes and seven proteins. The simulation results show that the theorems developed in this paper can effectively determine the delay-independent stability of genetic regulatory networks.

The PAZAR database of gene regulatory information coupled to the ORCA toolkit for the study of regulatory sequences

Science.gov (United States)

Portales-Casamar, Elodie; Arenillas, David; Lim, Jonathan; Swanson, Magdalena I.; Jiang, Steven; McCallum, Anthony; Kirov, Stefan; Wasserman, Wyeth W.

2009-01-01

The PAZAR database unites independently created and maintained data collections of transcription factor and regulatory sequence annotation. The flexible PAZAR schema permits the representation of diverse information derived from experiments ranging from biochemical protein–DNA binding to cellular reporter gene assays. Data collections can be made available to the public, or restricted to specific system users. The data ‘boutiques’ within the shopping-mall-inspired system facilitate the analysis of genomics data and the creation of predictive models of gene regulation. Since its initial release, PAZAR has grown in terms of data, features and through the addition of an associated package of software tools called the ORCA toolkit (ORCAtk). ORCAtk allows users to rapidly develop analyses based on the information stored in the PAZAR system. PAZAR is available at http://www.pazar.info. ORCAtk can be accessed through convenient buttons located in the PAZAR pages or via our website at http://www.cisreg.ca/ORCAtk. PMID:18971253

Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress

Directory of Open Access Journals (Sweden)

He eLiu

2014-10-01

Full Text Available Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay (EMSA demonstrated that TetR regulator bound directly to the promoter of this gene cluster. Consistently, the results of quantitative real-time PCR also showed alterations in expression of associated genes. Moreover, the proteins affected by TetR under oxidative stress were revealed by comparing proteomic profiles of wild-type and mutant strains via 1D SDS-PAGE and LC-MS/MS analyses. Taken together, our results demonstrated that tetR gene in this novel gene cluster contributed to cell survival under oxidative stress, and TetR protein played an important regulatory role in growth kinetics, biofilm-forming capability, SOD and catalase activity, and oxide detoxicating ability.

Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress.

Science.gov (United States)

Liu, He; Yang, Chun-Lan; Ge, Meng-Yu; Ibrahim, Muhammad; Li, Bin; Zhao, Wen-Jun; Chen, Gong-You; Zhu, Bo; Xie, Guan-Lin

2014-01-01

Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay demonstrated that TetR regulator bound directly to the promoter of this gene cluster. Consistently, the results of quantitative real-time PCR also showed alterations in expression of associated genes. Moreover, the proteins affected by TetR under oxidative stress were revealed by comparing proteomic profiles of wild-type and mutant strains via 1D SDS-PAGE and LC-MS/MS analyses. Taken together, our results demonstrated that tetR gene in this novel gene cluster contributed to cell survival under oxidative stress, and TetR protein played an important regulatory role in growth kinetics, biofilm-forming capability, superoxide dismutase and catalase activity, and oxide detoxicating ability.

Structural basis for regulation of rhizobial nodulation and symbiosis gene expression by the regulatory NolR

Science.gov (United States)

The symbiosis between rhizobial microbes and host plants involves the coordinated expression of multiple genes, which leads to nodule formation and nitrogen fixation. As part of the transcriptional machinery for nodulation and symbiosis across a range of Rhizobium, NolR serves as a global regulatory...

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

Directory of Open Access Journals (Sweden)

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.

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.

Evolutionary dynamics of DNA-binding sites and direct target genes of a floral master regulatory transcription factor [ChIP-Seq

NARCIS (Netherlands)

Muiño, J.M.; Bruijn, de S.A.; Vingron, Martin; Angenent, G.C.; Kaufmann, K.

2015-01-01

Plant development is controlled by transcription factors (TFs) which form complex gene-regulatory networks. Genome-wide TF DNA-binding studies revealed that these TFs have several thousands of binding sites in the Arabidopsis genome, and may regulate the expression of many genes directly. Given the

Potential energy landscape and robustness of a gene regulatory network: toggle switch.

Directory of Open Access Journals (Sweden)

Keun-Young Kim

2007-03-01

Full Text Available Finding a multidimensional potential landscape is the key for addressing important global issues, such as the robustness of cellular networks. We have uncovered the underlying potential energy landscape of a simple gene regulatory network: a toggle switch. This was realized by explicitly constructing the steady state probability of the gene switch in the protein concentration space in the presence of the intrinsic statistical fluctuations due to the small number of proteins in the cell. We explored the global phase space for the system. We found that the protein synthesis rate and the unbinding rate of proteins to the gene were small relative to the protein degradation rate; the gene switch is monostable with only one stable basin of attraction. When both the protein synthesis rate and the unbinding rate of proteins to the gene are large compared with the protein degradation rate, two global basins of attraction emerge for a toggle switch. These basins correspond to the biologically stable functional states. The potential energy barrier between the two basins determines the time scale of conversion from one to the other. We found as the protein synthesis rate and protein unbinding rate to the gene relative to the protein degradation rate became larger, the potential energy barrier became larger. This also corresponded to systems with less noise or the fluctuations on the protein numbers. It leads to the robustness of the biological basins of the gene switches. The technique used here is general and can be applied to explore the potential energy landscape of the gene networks.

An allele of an ancestral transcription factor dependent on a horizontally acquired gene product.

Science.gov (United States)

Chen, H Deborah; Jewett, Mollie W; Groisman, Eduardo A

2012-01-01

Changes in gene regulatory circuits often give rise to phenotypic differences among closely related organisms. In bacteria, these changes can result from alterations in the ancestral genome and/or be brought about by genes acquired by horizontal transfer. Here, we identify an allele of the ancestral transcription factor PmrA that requires the horizontally acquired pmrD gene product to promote gene expression. We determined that a single amino acid difference between the PmrA proteins from the human adapted Salmonella enterica serovar Paratyphi B and the broad host range S. enterica serovar Typhimurium rendered transcription of PmrA-activated genes dependent on the PmrD protein in the former but not the latter serovar. Bacteria harboring the serovar Typhimurium allele exhibited polymyxin B resistance under PmrA- or under PmrA- and PmrD-inducing conditions. By contrast, isogenic strains with the serovar Paratyphi B allele displayed PmrA-regulated polymyxin B resistance only when experiencing activating conditions for both PmrA and PmrD. We establish that the two PmrA orthologs display quantitative differences in several biochemical properties. Strains harboring the serovar Paratyphi B allele showed enhanced biofilm formation, a property that might promote serovar Paratyphi B's chronic infection of the gallbladder. Our findings illustrate how subtle differences in ancestral genes can impact the ability of horizontally acquired genes to confer new properties.

Where we stand, where we are moving: Surveying computational techniques for identifying miRNA genes and uncovering their regulatory role

KAUST Repository

Kleftogiannis, Dimitrios A.; Korfiati, Aigli; Theofilatos, Konstantinos A.; Likothanassis, Spiridon D.; Tsakalidis, Athanasios K.; Mavroudi, Seferina P.

2013-01-01

Traditional biology was forced to restate some of its principles when the microRNA (miRNA) genes and their regulatory role were firstly discovered. Typically, miRNAs are small non-coding RNA molecules which have the ability to bind to the 3'untraslated region (UTR) of their mRNA target genes for cleavage or translational repression. Existing experimental techniques for their identification and the prediction of the target genes share some important limitations such as low coverage, time consuming experiments and high cost reagents. Hence, many computational methods have been proposed for these tasks to overcome these limitations. Recently, many researchers emphasized on the development of computational approaches to predict the participation of miRNA genes in regulatory networks and to analyze their transcription mechanisms. All these approaches have certain advantages and disadvantages which are going to be described in the present survey. Our work is differentiated from existing review papers by updating the methodologies list and emphasizing on the computational issues that arise from the miRNA data analysis. Furthermore, in the present survey, the various miRNA data analysis steps are treated as an integrated procedure whose aims and scope is to uncover the regulatory role and mechanisms of the miRNA genes. This integrated view of the miRNA data analysis steps may be extremely useful for all researchers even if they work on just a single step. © 2013 Elsevier Inc.

Where we stand, where we are moving: Surveying computational techniques for identifying miRNA genes and uncovering their regulatory role

KAUST Repository

Kleftogiannis, Dimitrios A.

2013-06-01

Traditional biology was forced to restate some of its principles when the microRNA (miRNA) genes and their regulatory role were firstly discovered. Typically, miRNAs are small non-coding RNA molecules which have the ability to bind to the 3\\'untraslated region (UTR) of their mRNA target genes for cleavage or translational repression. Existing experimental techniques for their identification and the prediction of the target genes share some important limitations such as low coverage, time consuming experiments and high cost reagents. Hence, many computational methods have been proposed for these tasks to overcome these limitations. Recently, many researchers emphasized on the development of computational approaches to predict the participation of miRNA genes in regulatory networks and to analyze their transcription mechanisms. All these approaches have certain advantages and disadvantages which are going to be described in the present survey. Our work is differentiated from existing review papers by updating the methodologies list and emphasizing on the computational issues that arise from the miRNA data analysis. Furthermore, in the present survey, the various miRNA data analysis steps are treated as an integrated procedure whose aims and scope is to uncover the regulatory role and mechanisms of the miRNA genes. This integrated view of the miRNA data analysis steps may be extremely useful for all researchers even if they work on just a single step. © 2013 Elsevier Inc.

Evolution of cichlid vision via trans-regulatory divergence

Directory of Open Access Journals (Sweden)

O’Quin Kelly E

2012-12-01

Full Text Available Abstract Background Phenotypic evolution may occur through mutations that affect either the structure or expression of protein-coding genes. Although the evolution of color vision has historically been attributed to structural mutations within the opsin genes, recent research has shown that opsin regulatory mutations can also tune photoreceptor sensitivity and color vision. Visual sensitivity in African cichlid fishes varies as a result of the differential expression of seven opsin genes. We crossed cichlid species that express different opsin gene sets and scanned their genome for expression Quantitative Trait Loci (eQTL responsible for these differences. Our results shed light on the role that different structural, cis-, and trans-regulatory mutations play in the evolution of color vision. Results We identified 11 eQTL that contribute to the divergent expression of five opsin genes. On three linkage groups, several eQTL formed regulatory “hotspots” associated with the expression of multiple opsins. Importantly, however, the majority of the eQTL we identified (8/11 or 73% occur on linkage groups located trans to the opsin genes, suggesting that cichlid color vision has evolved primarily via trans-regulatory divergence. By modeling the impact of just two of these trans-regulatory eQTL, we show that opsin regulatory mutations can alter cichlid photoreceptor sensitivity and color vision at least as much as opsin structural mutations can. Conclusions Combined with previous work, we demonstrate that the evolution of cichlid color vision results from the interplay of structural, cis-, and especially trans-regulatory loci. Although there are numerous examples of structural and cis-regulatory mutations that contribute to phenotypic evolution, our results suggest that trans-regulatory mutations could contribute to phenotypic divergence more commonly than previously expected, especially in systems like color vision, where compensatory changes in the

Health claims on food products in Southeast Asia: regulatory frameworks, barriers, and opportunities.

Science.gov (United States)

Tan, Karin Y M; van der Beek, Eline M; Chan, M Y; Zhao, Xuejun; Stevenson, Leo

2015-09-01

The Association of Southeast Asian Nations aims to act as a single market and allow free movement of goods, services, and manpower. The purpose of this article is to present an overview of the current regulatory framework for health claims in Southeast Asia and to highlight the current barriers and opportunities in the regulatory frameworks in the Association of Southeast Asian Nations. To date, 5 countries in Southeast Asia, i.e., Indonesia, Malaysia, the Philippines, Singapore, and Thailand, have regulations and guidelines to permit the use of health claims on food products. There are inconsistencies in the regulations and the types of evidence required for health claim applications in these countries. A clear understanding of the regulatory frameworks in these countries may help to increase trade in this fast-growing region and to provide direction for the food industry and the regulatory community to develop and market food products with better nutritional quality tailored to the needs of Southeast Asian consumers. © The Author(s) 2015. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

[Regulatory requirements regarding cell-based medicinal products for human and veterinary use - a comparison].

Science.gov (United States)

Kuhlmann-Gottke, Johanna; Duchow, Karin

2015-11-01

At present, there is no separate regulatory framework for cell-based medicinal products (CBMP) for veterinary use at the European or German level. Current European and national regulations exclusively apply to the corresponding medicinal products for human use. An increasing number of requests for the regulatory classification of CBMP for veterinary use, such as allogeneic stem cell preparations and dendritic cell-based autologous tumour vaccines, and a rise in scientific advice for companies developing these products, illustrate the need for adequate legislation. Currently, advice is given and decisions are made on a case-by-case basis regarding the regulatory classification and authorisation requirements.Since some of the CBMP - in particular in the area of stem-cell products - are developed in parallel for human and veterinary use, there is an urgent need to create specific legal definitions, regulations, and guidelines for these complex innovative products in the veterinary sector as well. Otherwise, there is a risk that that the current legal grey area regarding veterinary medicinal products will impede therapeutic innovations in the long run. A harmonised EU-wide approach is desirable. Currently the European legislation on veterinary medicinal products is under revision. In this context, veterinary therapeutics based on allogeneic cells and tissues will be defined and regulated. Certainly, the legal framework does not have to be as comprehensive as for human CBMP; a leaner solution is conceivable, similar to the special provisions for advanced-therapy medicinal products laid down in the German Medicines Act.

A new measure for functional similarity of gene products based on Gene Ontology

Directory of Open Access Journals (Sweden)

Lengauer Thomas

2006-06-01

Full Text Available Abstract Background Gene Ontology (GO is a standard vocabulary of functional terms and allows for coherent annotation of gene products. These annotations provide a basis for new methods that compare gene products regarding their molecular function and biological role. Results We present a new method for comparing sets of GO terms and for assessing the functional similarity of gene products. The method relies on two semantic similarity measures; simRel and funSim. One measure (simRel is applied in the comparison of the biological processes found in different groups of organisms. The other measure (funSim is used to find functionally related gene products within the same or between different genomes. Results indicate that the method, in addition to being in good agreement with established sequence similarity approaches, also provides a means for the identification of functionally related proteins independent of evolutionary relationships. The method is also applied to estimating functional similarity between all proteins in Saccharomyces cerevisiae and to visualizing the molecular function space of yeast in a map of the functional space. A similar approach is used to visualize the functional relationships between protein families. Conclusion The approach enables the comparison of the underlying molecular biology of different taxonomic groups and provides a new comparative genomics tool identifying functionally related gene products independent of homology. The proposed map of the functional space provides a new global view on the functional relationships between gene products or protein families.

Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

Science.gov (United States)

Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

2017-01-01

Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

A strategy for regulatory action when new adverse effects of a licensed product emerge.

Science.gov (United States)

Aronson, Jeffrey K; Price, Deirdre; Ferner, Robin E

2009-01-01

Regulatory agencies grant product licences (marketing authorizations) for medicinal products in the light of evidence that the balance between benefit and harm in the population is favourable. Here we consider a framework for allowing regulatory agencies to make rational decisions when reviewing product licences in the light of new information about harms that change that balance. The regulator can revoke the product licence, restrict the product's availability or change the 'label' in different ways. We examine the features of the adverse effect that may be relevant in making the decision: namely, individual differences in susceptibility; the possibility of monitoring; and the availability of protective strategies. The balance of benefit and harm, and the time-course and dose relation of the adverse effect play important roles in the decision-making process. We set out how these factors can help determine the logical response to new information on the balance between benefit and harm, and provide a series of relevant examples. We believe that when regulatory agencies have to decide how to amend the product licence of a drug when new serious adverse effects cause concern, they would find it useful to adopt a framework of this kind, using different strategies for different cases. Our proposed framework could also be useful in risk management planning during drug development.

Comparative Bioinformatics Analysis of Transcription Factor Genes Indicates Conservation of Key Regulatory Domains among Babesia bovis, Babesia microti, and Theileria equi.

Science.gov (United States)

Alzan, Heba F; Knowles, Donald P; Suarez, Carlos E

2016-11-01

Apicomplexa tick-borne hemoparasites, including Babesia bovis, Babesia microti, and Theileria equi are responsible for bovine and human babesiosis and equine theileriosis, respectively. These parasites of vast medical, epidemiological, and economic impact have complex life cycles in their vertebrate and tick hosts. Large gaps in knowledge concerning the mechanisms used by these parasites for gene regulation remain. Regulatory genes coding for DNA binding proteins such as members of the Api-AP2, HMG, and Myb families are known to play crucial roles as transcription factors. Although the repertoire of Api-AP2 has been defined and a HMG gene was previously identified in the B. bovis genome, these regulatory genes have not been described in detail in B. microti and T. equi. In this study, comparative bioinformatics was used to: (i) identify and map genes encoding for these transcription factors among three parasites' genomes; (ii) identify a previously unreported HMG gene in B. microti; (iii) define a repertoire of eight conserved Myb genes; and (iv) identify AP2 correlates among B. bovis and the better-studied Plasmodium parasites. Searching the available transcriptome of B. bovis defined patterns of transcription of these three gene families in B. bovis erythrocyte stage parasites. Sequence comparisons show conservation of functional domains and general architecture in the AP2, Myb, and HMG proteins, which may be significant for the regulation of common critical parasite life cycle transitions in B. bovis, B. microti, and T. equi. A detailed understanding of the role of gene families encoding DNA binding proteins will provide new tools for unraveling regulatory mechanisms involved in B. bovis, B. microti, and T. equi life cycles and environmental adaptive responses and potentially contributes to the development of novel convergent strategies for improved control of babesiosis and equine piroplasmosis.

Comparative Bioinformatics Analysis of Transcription Factor Genes Indicates Conservation of Key Regulatory Domains among Babesia bovis, Babesia microti, and Theileria equi.

Directory of Open Access Journals (Sweden)

Heba F Alzan

2016-11-01

Full Text Available Apicomplexa tick-borne hemoparasites, including Babesia bovis, Babesia microti, and Theileria equi are responsible for bovine and human babesiosis and equine theileriosis, respectively. These parasites of vast medical, epidemiological, and economic impact have complex life cycles in their vertebrate and tick hosts. Large gaps in knowledge concerning the mechanisms used by these parasites for gene regulation remain. Regulatory genes coding for DNA binding proteins such as members of the Api-AP2, HMG, and Myb families are known to play crucial roles as transcription factors. Although the repertoire of Api-AP2 has been defined and a HMG gene was previously identified in the B. bovis genome, these regulatory genes have not been described in detail in B. microti and T. equi. In this study, comparative bioinformatics was used to: (i identify and map genes encoding for these transcription factors among three parasites' genomes; (ii identify a previously unreported HMG gene in B. microti; (iii define a repertoire of eight conserved Myb genes; and (iv identify AP2 correlates among B. bovis and the better-studied Plasmodium parasites. Searching the available transcriptome of B. bovis defined patterns of transcription of these three gene families in B. bovis erythrocyte stage parasites. Sequence comparisons show conservation of functional domains and general architecture in the AP2, Myb, and HMG proteins, which may be significant for the regulation of common critical parasite life cycle transitions in B. bovis, B. microti, and T. equi. A detailed understanding of the role of gene families encoding DNA binding proteins will provide new tools for unraveling regulatory mechanisms involved in B. bovis, B. microti, and T. equi life cycles and environmental adaptive responses and potentially contributes to the development of novel convergent strategies for improved control of babesiosis and equine piroplasmosis.

Genomic regulatory landscapes and chromosomal rearrangements

DEFF Research Database (Denmark)

Ladegaard, Elisabete L Engenheiro

2008-01-01

The main objectives of the PhD study are to identify and characterise chromosomal rearrangements within evolutionarily conserved regulatory landscapes around genes involved in the regulation of transcription and/or development (trans-dev genes). A frequent feature of trans-dev genes is that they ......The main objectives of the PhD study are to identify and characterise chromosomal rearrangements within evolutionarily conserved regulatory landscapes around genes involved in the regulation of transcription and/or development (trans-dev genes). A frequent feature of trans-dev genes...... the complex spatio-temporal expression of the associated trans-dev gene. Rare chromosomal breakpoints that disrupt the integrity of these regulatory landscapes may be used as a tool, not only to make genotype-phenotype associations, but also to link the associated phenotype with the position and tissue...... specificity of the individual CNEs. In this PhD study I have studied several chromosomal rearrangements with breakpoints in the vicinity of trans-dev genes. This included chromosomal rearrangements compatible with known phenotype-genotype associations (Rieger syndrome-PITX2, Mowat-Wilson syndrome-ZEB2...

Developmental evolution in social insects: regulatory networks from genes to societies.

Science.gov (United States)

Linksvayer, Timothy A; Fewell, Jennifer H; Gadau, Jürgen; Laubichler, Manfred D

2012-05-01

The evolution and development of complex phenotypes in social insect colonies, such as queen-worker dimorphism or division of labor, can, in our opinion, only be fully understood within an expanded mechanistic framework of Developmental Evolution. Conversely, social insects offer a fertile research area in which fundamental questions of Developmental Evolution can be addressed empirically. We review the concept of gene regulatory networks (GRNs) that aims to fully describe the battery of interacting genomic modules that are differentially expressed during the development of individual organisms. We discuss how distinct types of network models have been used to study different levels of biological organization in social insects, from GRNs to social networks. We propose that these hierarchical networks spanning different organizational levels from genes to societies should be integrated and incorporated into full GRN models to elucidate the evolutionary and developmental mechanisms underlying social insect phenotypes. Finally, we discuss prospects and approaches to achieve such an integration. © 2012 WILEY PERIODICALS, INC.

Penicillin production in industrial strain Penicillium chrysogenum P2niaD18 is not dependent on the copy number of biosynthesis genes.

Science.gov (United States)

Ziemons, Sandra; Koutsantas, Katerina; Becker, Kordula; Dahlmann, Tim; Kück, Ulrich

2017-02-16

Multi-copy gene integration into microbial genomes is a conventional tool for obtaining improved gene expression. For Penicillium chrysogenum, the fungal producer of the beta-lactam antibiotic penicillin, many production strains carry multiple copies of the penicillin biosynthesis gene cluster. This discovery led to the generally accepted view that high penicillin titers are the result of multiple copies of penicillin genes. Here we investigated strain P2niaD18, a production line that carries only two copies of the penicillin gene cluster. We performed pulsed-field gel electrophoresis (PFGE), quantitative qRT-PCR, and penicillin bioassays to investigate production, deletion and overexpression strains generated in the P. chrysogenum P2niaD18 background, in order to determine the copy number of the penicillin biosynthesis gene cluster, and study the expression of one penicillin biosynthesis gene, and the penicillin titer. Analysis of production and recombinant strain showed that the enhanced penicillin titer did not depend on the copy number of the penicillin gene cluster. Our assumption was strengthened by results with a penicillin null strain lacking pcbC encoding isopenicillin N synthase. Reintroduction of one or two copies of the cluster into the pcbC deletion strain restored transcriptional high expression of the pcbC gene, but recombinant strains showed no significantly different penicillin titer compared to parental strains. Here we present a molecular genetic analysis of production and recombinant strains in the P2niaD18 background carrying different copy numbers of the penicillin biosynthesis gene cluster. Our analysis shows that the enhanced penicillin titer does not strictly depend on the copy number of the cluster. Based on these overall findings, we hypothesize that instead, complex regulatory mechanisms are prominently implicated in increased penicillin biosynthesis in production strains.

Interplay of the modified nucleotide phosphoadenosine 5'-phosphosulfate (PAPS) with global regulatory proteins in Escherichia coli: modulation of cyclic AMP (cAMP)-dependent gene expression and interaction with the HupA regulatory protein.

Science.gov (United States)

Longo, Francesca; Motta, Sara; Mauri, Pierluigi; Landini, Paolo; Rossi, Elio

2016-11-25

In the bacterium Escherichia coli, some intermediates of the sulfate assimilation and cysteine biosynthesis pathway can act as signal molecules and modulate gene expression. In addition to sensing and utilization of sulphur sources, these signaling mechanisms also impact more global cell processes, such as resistance to antimicrobial agents and biofilm formation. In a recent work, we have shown that inactivation of the cysH gene, encoding phosphoadenosine-phosphosulfate (PAPS) reductase, and the consequent increase in intracellular PAPS concentration, strongly affect production of several cell surface-associated structures, enhancing surface adhesion and cell aggregation. In order to identify the molecular mechanism relaying intracellular PAPS concentration to regulation of cell surface-associated structures, we looked for mutations able to suppress the effects of cysH inactivation. We found that mutations in the adenylate cyclase-encoding cyaA gene abolished the effects of PAPS accumulation; consistent with this result, cyclic AMP (cAMP)-dependent gene expression appears to be increased in the cysH mutant. Experiments aimed at the direct identification of proteins interacting with either CysC or CysH, i.e. the PAPS-related proteins APS kinase and PAPS reductase, allowed us to identify several regulators, namely, CspC, CspE, HNS and HupA. Protein-protein interaction between HupA and CysH was confirmed by a bacterial two hybrid system, and inactivation of the hupA gene enhanced the effects of the cysH mutation in terms of production of cell surface-associated factors. Our results indicate that PAPS can modulate different regulatory systems, providing evidence that this molecule acts as a global signal molecule in E. coli. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Mechanisms of endogenous drug resistance acquisition by spontaneous chromosomal gene mutation].

Science.gov (United States)

Fukuda, H; Hiramatsu, K

1997-05-01

Endogenous resistance in bacteria is caused by a change or loss of function and generally genetically recessive. However, this type of resistance acquisition are now prevalent in clinical setting. Chromosomal genes that afford endogenous resistance are the genes correlated with the target of the drug, the drug inactivating enzymes, and permeability of the molecules including the antibacterial agents. Endogenous alteration of the drug target are mediated by the spontaneous mutation of their structural gene. This mutation provides much lower affinity of the drugs for the target. Gene expression of the inactivating enzymes, such as class C beta-lactamase, is generally regulated by regulatory genes. Spontaneous mutations in the regulatory genes cause constitutive enzyme production and provides the resistant to the agent which is usually stable for such enzymes. Spontaneous mutation in the structural gene gives the enzyme extra-spectrum substrate specificity, like ESBL (Extra-Spectrum-beta-Lactamase). Expression of structural genes encoding the permeability systems are also regulated by some regulatory genes. The spontaneous mutation of the regulatory genes reduce an amount of porin protein. This mutation causes much lower influx of the drug in the cell. Spontaneous mutation in promoter region of the structural gene of efflux protein was observed. This mutation raised the gene transcription and overproduced efflux protein. This protein progresses the drug efflux from the cell.

[Analysis of cis-regulatory element distribution in gene promoters of Gossypium raimondii and Arabidopsis thaliana].

Science.gov (United States)

Sun, Gao-Fei; He, Shou-Pu; Du, Xiong-Ming

2013-10-01

Cotton genomic studies have boomed since the release of Gossypium raimondii draft genome. In this study, cis-regulatory element (CRE) in 1 kb length sequence upstream 5' UTR of annotated genes were selected and scanned in the Arabidopsis thaliana (At) and Gossypium raimondii (Gr) genomes, based on the database of PLACE (Plant cis-acting Regulatory DNA Elements). According to the definition of this study, 44 (12.3%) and 57 (15.5%) CREs presented "peak-like" distribution in the 1 kb selected sequences of both genomes, respectively. Thirty-four of them were peak-like distributed in both genomes, which could be further categorized into 4 types based on their core sequences. The coincidence of TATABOX peak position and their actual position ((-) -30 bp) indicated that the position of a common CRE was conservative in different genes, which suggested that the peak position of these CREs was their possible actual position of transcription factors. The position of a common CRE was also different between the two genomes due to stronger length variation of 5' UTR in Gr than At. Furthermore, most of the peak-like CREs were located in the region of -110 bp-0 bp, which suggested that concentrated distribution might be conductive to the interaction of transcription factors, and then regulate the gene expression in downstream.

Drought Response in Wheat: Key Genes and Regulatory Mechanisms Controlling Root System Architecture and Transpiration Efficiency

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Manoj Kulkarni

2017-12-01

Full Text Available Abiotic stresses such as, drought, heat, salinity, and flooding threaten global food security. Crop genetic improvement with increased resilience to abiotic stresses is a critical component of crop breeding strategies. Wheat is an important cereal crop and a staple food source globally. Enhanced drought tolerance in wheat is critical for sustainable food production and global food security. Recent advances in drought tolerance research have uncovered many key genes and transcription regulators governing morpho-physiological traits. Genes controlling root architecture and stomatal development play an important role in soil moisture extraction and its retention, and therefore have been targets of molecular breeding strategies for improving drought tolerance. In this systematic review, we have summarized evidence of beneficial contributions of root and stomatal traits to plant adaptation to drought stress. Specifically, we discuss a few key genes such as, DRO1 in rice and ERECTA in Arabidopsis and rice that were identified to be the enhancers of drought tolerance via regulation of root traits and transpiration efficiency. Additionally, we highlight several transcription factor families, such as, ERF (ethylene response factors, DREB (dehydration responsive element binding, ZFP (zinc finger proteins, WRKY, and MYB that were identified to be both positive and negative regulators of drought responses in wheat, rice, maize, and/or Arabidopsis. The overall aim of this review is to provide an overview of candidate genes that have been identified as regulators of drought response in plants. The lack of a reference genome sequence for wheat and non-transgenic approaches for manipulation of gene functions in wheat in the past had impeded high-resolution interrogation of functional elements, including genes and QTLs, and their application in cultivar improvement. The recent developments in wheat genomics and reverse genetics, including the availability of a

Drought response in wheat: key genes and regulatory mechanisms controlling root system architecture and transpiration efficiency

Science.gov (United States)

Kulkarni, Manoj; Soolanayakanahally, Raju; Ogawa, Satoshi; Uga, Yusaku; Selvaraj, Michael G.; Kagale, Sateesh

2017-12-01

Abiotic stresses such as drought, heat, salinity and flooding threaten global food security. Crop genetic improvement with increased resilience to abiotic stresses is a critical component of crop breeding strategies. Wheat is an important cereal crop and a staple food source globally. Enhanced drought tolerance in wheat is critical for sustainable food production and global food security. Recent advances in drought tolerance research have uncovered many key genes and transcription regulators governing morpho-physiological traits. Genes controlling root architecture and stomatal development play an important role in soil moisture extraction and its retention, and therefore have been targets of molecular breeding strategies for improving drought tolerance. In this systematic review, we have summarized evidence of beneficial contributions of root and stomatal traits to plant adaptation to drought stress. Specifically, we discuss a few key genes such as DRO1 in rice and ERECTA in Arabidopsis and rice that were identified to be the enhancers of drought tolerance via regulation of root traits and transpiration efficiency. Additionally, we highlight several transcription factor families, such as ERF (ethylene response factors), DREB (dehydration responsive element binding), ZFP (zinc finger proteins), WRKY and MYB that were identified to be both positive and negative regulators of drought responses in wheat, rice, maize and/or Arabidopsis. The overall aim of this review was to provide an overview of candidate genes that have been tested as regulators of drought response in plants. The lack of a reference genome sequence for wheat and nontransgenic approaches for manipulation of gene functions in the past had impeded high-resolution interrogation of functional elements, including genes and QTLs, and their application in cultivar improvement. The recent developments in wheat genomics and reverse genetics, including the availability of a gold-standard reference genome

Network perturbation by recurrent regulatory variants in cancer.

Directory of Open Access Journals (Sweden)

Kiwon Jang

2017-03-01

Full Text Available Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes.

Essential Oils Modulate Gene Expression and Ochratoxin A Production in Aspergillus carbonarius

International Nuclear Information System (INIS)

Atoui, A.; El Khoury, R.; Verheecke, C; Mathieu, F.; Maroun, R.; El Khoury, A.

2016-01-01

Ochratoxin A (OTA) is a mycotoxin, mainly produced on grapes by Aspergillus carbonarius, that causes massive health problems for humans. This study aims to reduce the occurrence of OTA by using the ten following essential oils (E.Os): fennel, cardamom, anise, chamomile, celery, cinnamon, thyme, taramira, oregano and rosemary at μL/mL and 5 μL/mL for each E.O. As a matter of fact, their effects on the OTA production and the growth of A. carbonarius S402 cultures were evaluated, after four days at 28 °C on a Synthetic Grape Medium (SGM). Results showed that A. carbonarius growth was reduced up to 100%, when cultured with the E.Os of cinnamon, taramira, and oregano at both concentrations and the thyme at 5 μL/mL. As for the other six E.Os, their effect on A. carbonarius growth was insignificant, but highly important on the OTA production. Interestingly, the fennel E.O at 5 _L/mL reduced the OTA production up to 88.9% compared to the control, with only 13.8% of fungal growth reduction. We further investigated the effect of these E.Os on the expression levels of the genes responsible for the OTA biosynthesis (acOTApks and acOTAnrps along with the acpks gene) as well as the two regulatory genes laeA and vea, using the quantitative Reverse Transcription-Polymerase Chain Reaction (qRT-PCR) method. The results revealed that these six E.Os reduced the expression of the five studied genes, where the ackps was downregulated by 99.2% (the highest downregulation in this study) with 5 μL/mL of fennel E.O. As for the acOTApks, acOTAnrps, veA and laeA, their reduction levels ranged between 10% and 96% depending on the nature of the E.O and its concentration in the medium. (author)

Genetic control and regulatory mechanisms of succinoglycan and curdlan biosynthesis in genus Agrobacterium.

Science.gov (United States)

Wu, Dan; Li, Ang; Ma, Fang; Yang, Jixian; Xie, Yutong

2016-07-01

Agrobacterium is a genus of gram-negative bacteria that can produce several typical exopolysaccharides with commercial uses in the food and pharmaceutical fields. In particular, succinoglycan and curdlan, due to their good quality in high yield, have been employed on an industrial scale comparatively early. Exopolysaccharide biosynthesis is a multiple-step process controlled by different functional genes, and various environmental factors cause changes in exopolysaccharide biosynthesis through regulatory mechanisms. In this mini-review, we focus on the genetic control and regulatory mechanisms of succinoglycan and curdlan produced by Agrobacterium. Some key functional genes and regulatory mechanisms for exopolysaccharide biosynthesis are described, possessing a high potential for application in metabolic engineering to modify exopolysaccharide production and physicochemical properties. This review may contribute to the understanding of exopolysaccharide biosynthesis and exopolysaccharide modification by metabolic engineering methods in Agrobacterium.

Quantitative statistical analysis of cis-regulatory sequences in ABA/VP1- and CBF/DREB1-regulated genes of Arabidopsis.

Science.gov (United States)

Suzuki, Masaharu; Ketterling, Matthew G; McCarty, Donald R

2005-09-01

We have developed a simple quantitative computational approach for objective analysis of cis-regulatory sequences in promoters of coregulated genes. The program, designated MotifFinder, identifies oligo sequences that are overrepresented in promoters of coregulated genes. We used this approach to analyze promoter sequences of Viviparous1 (VP1)/abscisic acid (ABA)-regulated genes and cold-regulated genes, respectively, of Arabidopsis (Arabidopsis thaliana). We detected significantly enriched sequences in up-regulated genes but not in down-regulated genes. This result suggests that gene activation but not repression is mediated by specific and common sequence elements in promoters. The enriched motifs include several known cis-regulatory sequences as well as previously unidentified motifs. With respect to known cis-elements, we dissected the flanking nucleotides of the core sequences of Sph element, ABA response elements (ABREs), and the C repeat/dehydration-responsive element. This analysis identified the motif variants that may correlate with qualitative and quantitative differences in gene expression. While both VP1 and cold responses are mediated in part by ABA signaling via ABREs, these responses correlate with unique ABRE variants distinguished by nucleotides flanking the ACGT core. ABRE and Sph motifs are tightly associated uniquely in the coregulated set of genes showing a strict dependence on VP1 and ABA signaling. Finally, analysis of distribution of the enriched sequences revealed a striking concentration of enriched motifs in a proximal 200-base region of VP1/ABA and cold-regulated promoters. Overall, each class of coregulated genes possesses a discrete set of the enriched motifs with unique distributions in their promoters that may account for the specificity of gene regulation.

Cell therapy medicinal product regulatory framework in Europe and its application for MSC based therapy development

Directory of Open Access Journals (Sweden)

Janis eAncans

2012-08-01

Full Text Available Advanced therapy medicinal products (ATMPs, including cell therapy products, form a new class of medicines in the European Union. Since ATMPs are at the forefront of scientific innovation in medicine, specific regulatory framework has been developed for these medicines and implemented from 2009. The Committee for Advanced Therapies (CAT has been established at European Medicines Agency (EMA for centralized classification, certification and evaluation procedures, and other ATMP related tasks. Guidance documents, initiatives and interaction platforms are available to make the new framework more accessible for small and medium-sized enterprises, academia, hospitals and foundations. Good understanding of centralised and national components of the regulatory system is required to plan product development. It is in the best interests of cell therapy developers to utilise provided resources starting with the preclinical stage. Whilst there have not been mesenchymal stem cell (MSC based medicine authorisations in the EU, three MSC products have received marketing approval in other regions since 2011. Information provided on regulatory requirements, procedures and initiatives is aimed to facilitate MSC based medicinal product development and authorisation in the EU.

Applications of pharmacogenomics in regulatory science: a product life cycle review.

Science.gov (United States)

Tan-Koi, W C; Leow, P C; Teo, Y Y

2018-05-22

With rapid developments of pharmacogenomics (PGx) and regulatory science, it is important to understand the current PGx integration in product life cycle, impact on clinical practice thus far and opportunities ahead. We conducted a cross-sectional review on PGx-related regulatory documents and implementation guidelines in the United States and Europe. Our review found that although PGx-related guidance in both markets span across the entire product life cycle, the scope of implementation guidelines varies across two continents. Approximately one-third of Food and Drug Administration (FDA)-approved drugs with PGx information in drug labels and half of the European labels posted on PharmGKB website contain recommendations on genetic testing. The drugs affected 19 and 15 World Health Organization Anatomical Therapeutic Chemical drug classes (fourth level) in the United States and Europe, respectively, with protein kinase inhibitors (13 drugs in the United States and 16 drugs in Europe) being most prevalent. Topics of emerging interest were novel technologies, adaptive design in clinical trial and sample collection.

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems.

Science.gov (United States)

Salleh, Faridah Hani Mohamed; Zainudin, Suhaila; Arif, Shereena M

2017-01-01

Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.

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

XcisClique: analysis of regulatory bicliques

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Grene Ruth

2006-04-01

Full Text Available Abstract Background Modeling of cis-elements or regulatory motifs in promoter (upstream regions of genes is a challenging computational problem. In this work, set of regulatory motifs simultaneously present in the promoters of a set of genes is modeled as a biclique in a suitably defined bipartite graph. A biologically meaningful co-occurrence of multiple cis-elements in a gene promoter is assessed by the combined analysis of genomic and gene expression data. Greater statistical significance is associated with a set of genes that shares a common set of regulatory motifs, while simultaneously exhibiting highly correlated gene expression under given experimental conditions. Methods XcisClique, the system developed in this work, is a comprehensive infrastructure that associates annotated genome and gene expression data, models known cis-elements as regular expressions, identifies maximal bicliques in a bipartite gene-motif graph; and ranks bicliques based on their computed statistical significance. Significance is a function of the probability of occurrence of those motifs in a biclique (a hypergeometric distribution, and on the new sum of absolute values statistic (SAV that uses Spearman correlations of gene expression vectors. SAV is a statistic well-suited for this purpose as described in the discussion. Results XcisClique identifies new motif and gene combinations that might indicate as yet unidentified involvement of sets of genes in biological functions and processes. It currently supports Arabidopsis thaliana and can be adapted to other organisms, assuming the existence of annotated genomic sequences, suitable gene expression data, and identified regulatory motifs. A subset of Xcis Clique functionalities, including the motif visualization component MotifSee, source code, and supplementary material are available at https://bioinformatics.cs.vt.edu/xcisclique/.

GRNsight: a web application and service for visualizing models of small- to medium-scale gene regulatory networks

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Kam D. Dahlquist

2016-09-01

Full Text Available GRNsight is a web application and service for visualizing models of gene regulatory networks (GRNs. A gene regulatory network (GRN consists of genes, transcription factors, and the regulatory connections between them which govern the level of expression of mRNA and protein from genes. The original motivation came from our efforts to perform parameter estimation and forward simulation of the dynamics of a differential equations model of a small GRN with 21 nodes and 31 edges. We wanted a quick and easy way to visualize the weight parameters from the model which represent the direction and magnitude of the influence of a transcription factor on its target gene, so we created GRNsight. GRNsight automatically lays out either an unweighted or weighted network graph based on an Excel spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows, a Simple Interaction Format (SIF text file, or a GraphML XML file. When a user uploads an input file specifying an unweighted network, GRNsight automatically lays out the graph using black lines and pointed arrowheads. For a weighted network, GRNsight uses pointed and blunt arrowheads, and colors the edges and adjusts their thicknesses based on the sign (positive for activation or negative for repression and magnitude of the weight parameter. GRNsight is written in JavaScript, with diagrams facilitated by D3.js, a data visualization library. Node.js and the Express framework handle server-side functions. GRNsight’s diagrams are based on D3.js’s force graph layout algorithm, which was then extensively customized to support the specific needs of GRNs. Nodes are rectangular and support gene labels of up to 12 characters. The edges are arcs, which become straight lines when the nodes are close together. Self-regulatory edges are indicated by a loop. When a user mouses over an edge, the numerical value of the weight parameter is displayed. Visualizations can

Strategies of bringing drug product marketing applications to meet current regulatory standards.

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Wu, Yan; Freed, Anita; Lavrich, David; Raghavachari, Ramesh; Huynh-Ba, Kim; Shah, Ketan; Alasandro, Mark

2015-08-01

In the past decade, many guidance documents have been issued through collaboration of global organizations and regulatory authorities. Most of these are applicable to new products, but there is a risk that currently marketed products will not meet the new compliance standards during audits and inspections while companies continue to make changes through the product life cycle for continuous improvement or market demands. This discussion presents different strategies to bringing drug product marketing applications to meet current and emerging standards. It also discusses stability and method designs to meet process validation and global development efforts.

Improvement of livestock breeding strategies using physiologic and functional genomic information of the muscle regulatory factors gene family for skeletal muscle development

NARCIS (Netherlands)

Pas, te M.F.W.; Soumillon, A.

2001-01-01

A defined number of skeletal muscle fibers are formed in two separate waves during prenatal development, while postnatal growth is restricted to hypertrophic muscle fiber growth. The genes of the MRF (muscle regulatory factors) gene family, consisting of 4 structurally related transcription factors

Gain, loss and divergence in primate zinc-finger genes: a rich resource for evolution of gene regulatory differences between species.

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Katja Nowick

Full Text Available The molecular changes underlying major phenotypic differences between humans and other primates are not well understood, but alterations in gene regulation are likely to play a major role. Here we performed a thorough evolutionary analysis of the largest family of primate transcription factors, the Krüppel-type zinc finger (KZNF gene family. We identified and curated gene and pseudogene models for KZNFs in three primate species, chimpanzee, orangutan and rhesus macaque, to allow for a comparison with the curated set of human KZNFs. We show that the recent evolutionary history of primate KZNFs has been complex, including many lineage-specific duplications and deletions. We found 213 species-specific KZNFs, among them 7 human-specific and 23 chimpanzee-specific genes. Two human-specific genes were validated experimentally. Ten genes have been lost in humans and 13 in chimpanzees, either through deletion or pseudogenization. We also identified 30 KZNF orthologs with human-specific and 42 with chimpanzee-specific sequence changes that are predicted to affect DNA binding properties of the proteins. Eleven of these genes show signatures of accelerated evolution, suggesting positive selection between humans and chimpanzees. During primate evolution the most extensive re-shaping of the KZNF repertoire, including most gene additions, pseudogenizations, and structural changes occurred within the subfamily homininae. Using zinc finger (ZNF binding predictions, we suggest potential impact these changes have had on human gene regulatory networks. The large species differences in this family of TFs stands in stark contrast to the overall high conservation of primate genomes and potentially represents a potent driver of primate evolution.

An Organismal Model for Gene Regulatory Networks in the Gut-Associated Immune Response

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Katherine M. Buckley

2017-10-01

Full Text Available The gut epithelium is an ancient site of complex communication between the animal immune system and the microbial world. While elements of self-non-self receptors and effector mechanisms differ greatly among animal phyla, some aspects of recognition, regulation, and response are broadly conserved. A gene regulatory network (GRN approach provides a means to investigate the nature of this conservation and divergence even as more peripheral functional details remain incompletely understood. The sea urchin embryo is an unparalleled experimental model for detangling the GRNs that govern embryonic development. By applying this theoretical framework to the free swimming, feeding larval stage of the purple sea urchin, it is possible to delineate the conserved regulatory circuitry that regulates the gut-associated immune response. This model provides a morphologically simple system in which to efficiently unravel regulatory connections that are phylogenetically relevant to immunity in vertebrates. Here, we review the organism-wide cellular and transcriptional immune response of the sea urchin larva. A large set of transcription factors and signal systems, including epithelial expression of interleukin 17 (IL17, are important mediators in the activation of the early gut-associated response. Many of these have homologs that are active in vertebrate immunity, while others are ancient in animals but absent in vertebrates or specific to echinoderms. This larval model provides a means to experimentally characterize immune function encoded in the sea urchin genome and the regulatory interconnections that control immune response and resolution across the tissues of the organism.

Model checking optimal finite-horizon control for probabilistic gene regulatory networks.

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Wei, Ou; Guo, Zonghao; Niu, Yun; Liao, Wenyuan

2017-12-14

Probabilistic Boolean networks (PBNs) have been proposed for analyzing external control in gene regulatory networks with incorporation of uncertainty. A context-sensitive PBN with perturbation (CS-PBNp), extending a PBN with context-sensitivity to reflect the inherent biological stability and random perturbations to express the impact of external stimuli, is considered to be more suitable for modeling small biological systems intervened by conditions from the outside. In this paper, we apply probabilistic model checking, a formal verification technique, to optimal control for a CS-PBNp that minimizes the expected cost over a finite control horizon. We first describe a procedure of modeling a CS-PBNp using the language provided by a widely used probabilistic model checker PRISM. We then analyze the reward-based temporal properties and the computation in probabilistic model checking; based on the analysis, we provide a method to formulate the optimal control problem as minimum reachability reward properties. Furthermore, we incorporate control and state cost information into the PRISM code of a CS-PBNp such that automated model checking a minimum reachability reward property on the code gives the solution to the optimal control problem. We conduct experiments on two examples, an apoptosis network and a WNT5A network. Preliminary experiment results show the feasibility and effectiveness of our approach. The approach based on probabilistic model checking for optimal control avoids explicit computation of large-size state transition relations associated with PBNs. It enables a natural depiction of the dynamics of gene regulatory networks, and provides a canonical form to formulate optimal control problems using temporal properties that can be automated solved by leveraging the analysis power of underlying model checking engines. This work will be helpful for further utilization of the advances in formal verification techniques in system biology.

Sieve-based relation extraction of gene regulatory networks from biological literature.

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Žitnik, Slavko; Žitnik, Marinka; Zupan, Blaž; Bajec, Marko

2015-01-01

Relation extraction is an essential procedure in literature mining. It focuses on extracting semantic relations between parts of text, called mentions. Biomedical literature includes an enormous amount of textual descriptions of biological entities, their interactions and results of related experiments. To extract them in an explicit, computer readable format, these relations were at first extracted manually from databases. Manual curation was later replaced with automatic or semi-automatic tools with natural language processing capabilities. The current challenge is the development of information extraction procedures that can directly infer more complex relational structures, such as gene regulatory networks. We develop a computational approach for extraction of gene regulatory networks from textual data. Our method is designed as a sieve-based system and uses linear-chain conditional random fields and rules for relation extraction. With this method we successfully extracted the sporulation gene regulation network in the bacterium Bacillus subtilis for the information extraction challenge at the BioNLP 2013 conference. To enable extraction of distant relations using first-order models, we transform the data into skip-mention sequences. We infer multiple models, each of which is able to extract different relationship types. Following the shared task, we conducted additional analysis using different system settings that resulted in reducing the reconstruction error of bacterial sporulation network from 0.73 to 0.68, measured as the slot error rate between the predicted and the reference network. We observe that all relation extraction sieves contribute to the predictive performance of the proposed approach. Also, features constructed by considering mention words and their prefixes and suffixes are the most important features for higher accuracy of extraction. Analysis of distances between different mention types in the text shows that our choice of transforming

An investment-production-regulatory model for firms in the offshore oil and gas industry

International Nuclear Information System (INIS)

Jin Di.

1991-01-01

This tripartite study examines the economic consequences of proposed environmental regulations on firms in the OCS oil and gas industry. The background part reviews the major issues associated with OCS oil and gas development and relevant environmental regulatory proposals. In the theoretical part, models are developed using optimal control theory and the theory of nonrenewable resources to analyze the impact of rising compliance cost on firm's behavior in terms of the investment and production rates over time. Finally, in the simulation part, an integrated investment-production-regulatory model is developed to simulate OCS development with and without the proposed environmental regulations. Effects of regulations are measured in terms of an increase in compliance costs and the associated reduction in net profits from oil and gas production. The theoretical results indicate that an increase in compliance costs will alter exploration, development and production rates. The total investments in exploration and development, and oil production will decrease as a result of rising compliance costs for exploration, development and production over the entire planning period

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

Integration analysis of microRNA and mRNA paired expression profiling identifies deregulated microRNA-transcription factor-gene regulatory networks in ovarian endometriosis.

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Zhao, Luyang; Gu, Chenglei; Ye, Mingxia; Zhang, Zhe; Li, Li'an; Fan, Wensheng; Meng, Yuanguang

2018-01-22

The etiology and pathophysiology of endometriosis remain unclear. Accumulating evidence suggests that aberrant microRNA (miRNA) and transcription factor (TF) expression may be involved in the pathogenesis and development of endometriosis. This study therefore aims to survey the key miRNAs, TFs and genes and further understand the mechanism of endometriosis. Paired expression profiling of miRNA and mRNA in ectopic endometria compared with eutopic endometria were determined by high-throughput sequencing techniques in eight patients with ovarian endometriosis. Binary interactions and circuits among the miRNAs, TFs, and corresponding genes were identified by the Pearson correlation coefficients. miRNA-TF-gene regulatory networks were constructed using bioinformatic methods. Eleven selected miRNAs and TFs were validated by quantitative reverse transcription-polymerase chain reaction in 22 patients. Overall, 107 differentially expressed miRNAs and 6112 differentially expressed mRNAs were identified by comparing the sequencing of the ectopic endometrium group and the eutopic endometrium group. The miRNA-TF-gene regulatory network consists of 22 miRNAs, 12 TFs and 430 corresponding genes. Specifically, some key regulators from the miR-449 and miR-34b/c cluster, miR-200 family, miR-106a-363 cluster, miR-182/183, FOX family, GATA family, and E2F family as well as CEBPA, SOX9 and HNF4A were suggested to play vital regulatory roles in the pathogenesis of endometriosis. Integration analysis of the miRNA and mRNA expression profiles presents a unique insight into the regulatory network of this enigmatic disorder and possibly provides clues regarding replacement therapy for endometriosis.

Adenylyl cyclase plays a regulatory role in development, stress resistance and secondary metabolism in Fusarium fujikuroi.

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Jorge García-Martínez

Full Text Available The ascomycete fungus Fusarium fujikuroi (Gibberella fujikuroi MP-C produces secondary metabolites of biotechnological interest, such as gibberellins, bikaverin, and carotenoids. Production of these metabolites is regulated by nitrogen availability and, in a specific manner, by other environmental signals, such as light in the case of the carotenoid pathway. A complex regulatory network controlling these processes is recently emerging from the alterations of metabolite production found through the mutation of different regulatory genes. Here we show the effect of the targeted mutation of the acyA gene of F. fujikuroi, coding for adenylyl cyclase. Mutants lacking the catalytic domain of the AcyA protein showed different phenotypic alterations, including reduced growth, enhanced production of unidentified red pigments, reduced production of gibberellins and partially derepressed carotenoid biosynthesis in the dark. The phenotype differs in some aspects from that of similar mutants of the close relatives F. proliferatum and F. verticillioides: contrary to what was observed in these species, ΔacyA mutants of F. fujikuroi showed enhanced sensitivity to oxidative stress (H(2O(2, but no change in heavy metal resistance or in the ability to colonize tomato tissue, indicating a high versatility in the regulatory roles played by cAMP in this fungal group.

Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviours

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Daria eMolodtsova

2014-12-01

Full Text Available It is increasingly apparent that genes and networks that influence complex behaviour are evolutionary conserved, which is paradoxical considering that behaviour is labile over evolutionary timescales. How does adaptive change in behaviour arise if behaviour is controlled by conserved, pleiotropic, and likely evolutionary constrained genes? Pleiotropy and connectedness are known to constrain the general rate of protein evolution, prompting some to suggest that the evolution of complex traits, including behaviour, is fuelled by regulatory sequence evolution. However, we seldom have data on the strength of selection on mutations in coding and regulatory sequences, and this hinders our ability to study how pleiotropy influences coding and regulatory sequence evolution. Here we use population genomics to estimate the strength of selection on coding and regulatory mutations for a transcriptional regulatory network that influences complex behaviour of honey bees. We found that replacement mutations in highly connected transcription factors and target genes experience significantly stronger negative selection relative to weakly connected transcription factors and targets. Adaptively evolving proteins were significantly more likely to reside at the periphery of the regulatory network, while proteins with signs of negative selection were near the core of the network. Interestingly, connectedness and network structure had minimal influence on the strength of selection on putative regulatory sequences for both transcription factors and their targets. Our study indicates that adaptive evolution of complex behaviour can arise because of positive selection on protein-coding mutations in peripheral genes, and on regulatory sequence mutations in both transcription factors and their targets throughout the network.

Regulatory and clinical aspects of psychotropic medicinal products bioequivalence.

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Bałkowiec-Iskra, Ewa; Cessak, Grzegorz; Kuzawińska, Olga; Sejbuk-Rozbicka, Katarzyna; Rokita, Konrad; Mirowska-Guzel, Dagmara

2015-07-01

Introduction of generic medicinal products to the market has increased access to modern therapies but also enabled significant reduction in their cost, leading to containment of public expenditures on medicinal products reimbursement. The critical assessment of bioequivalence of any reference medicinal product and its counterpart is based on comparison of their rate and extent of absorption. It is assumed that two medicinal products are bioequivalent when their rate and extent of absorption do not show significant differences when administered at the same dose under similar experimental conditions. Bioequivalent medicinal products are declared to be also therapeutically equivalent and can be used interchangeably. However, despite regulatory declaration, switching from reference to generic drugs is often associated with concerns of healthcare providers about decreased treatment effectiveness or occurrence of adverse drug reactions. The aim of this article is to provide a description of rules that guide registration of generic medicinal products in the European Union and to analyze specific examples from the scientific literature concerning therapeutic equivalence of reference and generic antidepressant and antipsychotic medicinal products. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

Nomadic enhancers: tissue-specific cis-regulatory elements of yellow have divergent genomic positions among Drosophila species.

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Gizem Kalay

2010-11-01

Full Text Available cis-regulatory DNA sequences known as enhancers control gene expression in space and time. They are central to metazoan development and are often responsible for changes in gene regulation that contribute to phenotypic evolution. Here, we examine the sequence, function, and genomic location of enhancers controlling tissue- and cell-type specific expression of the yellow gene in six Drosophila species. yellow is required for the production of dark pigment, and its expression has evolved largely in concert with divergent pigment patterns. Using Drosophila melanogaster as a transgenic host, we examined the expression of reporter genes in which either 5' intergenic or intronic sequences of yellow from each species controlled the expression of Green Fluorescent Protein. Surprisingly, we found that sequences controlling expression in the wing veins, as well as sequences controlling expression in epidermal cells of the abdomen, thorax, and wing, were located in different genomic regions in different species. By contrast, sequences controlling expression in bristle-associated cells were located in the intron of all species. Differences in the precise pattern of spatial expression within the developing epidermis of D. melanogaster transformants usually correlated with adult pigmentation in the species from which the cis-regulatory sequences were derived, which is consistent with cis-regulatory evolution affecting yellow expression playing a central role in Drosophila pigmentation divergence. Sequence comparisons among species favored a model in which sequential nucleotide substitutions were responsible for the observed changes in cis-regulatory architecture. Taken together, these data demonstrate frequent changes in yellow cis-regulatory architecture among Drosophila species. Similar analyses of other genes, combining in vivo functional tests of enhancer activity with in silico comparative genomics, are needed to determine whether the pattern of

Cell therapy medicinal product regulatory framework in Europe and its application for MSC-based therapy development

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Ancans, Janis

2012-01-01

Advanced therapy medicinal products (ATMPs), including cell therapy products, form a new class of medicines in the European Union. Since the ATMPs are at the forefront of scientific innovation in medicine, specific regulatory framework has been developed for these medicines and implemented from 2009. The Committee for Advanced Therapies (CAT) has been established at the European Medicines Agency (EMA) for centralized classification, certification and evaluation procedures, and other ATMP-related tasks. Guidance documents, initiatives, and interaction platforms are available to make the new framework more accessible for small- and medium-sized enterprises, academia, hospitals, and foundations. Good understanding of the centralized and national components of the regulatory system is required to plan product development. It is in the best interests of the cell therapy developers to utilize the resources provided starting with the pre-clinical stage. Whilst there have been no mesenchymal stem cell (MSC)-based medicine authorizations in the EU, three MSC products have received marketing approval in other regions since 2011. The information provided on the regulatory requirements, procedures, and initiatives is aimed at facilitating MSC-based medicinal product development and authorization in the EU. PMID:22912639

Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

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Lu, Tao

2016-01-01

The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.

A regulatory review for products containing glutathione

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Nur Hidayah Abd Rahim

2016-01-01

Full Text Available Glutathione is a potent antioxidant as well as has important role for DNA synthesis and repair, protein synthesis, amino acid transport, and enzyme activation. Besides this, Glutathione products are now mainly selling as whitening agent which are mainly marketing through social media (Facebook and different websites. Information is not available whether glutathione product are following the regulatory guidelines of National Pharmaceutical Control Bureau of Malaysia (NPCB for selling, advertisement and promotion. This review was carried out by extracting information about glutathione from scientific database using PubMed, Cochrane Library and Embase. Analysis of the available information, case example of glutathione products showed that a brand of glutathione (Glutacaps HQ did not show the product's registration number from NPCB, and also did not show the name, address, contact number of the advertiser, and even not found the name of the manufacture. Without providing the above mentioned information, the product is selling and promoting through social media (fb which is not allowed by the NPCB guidelines part 4.14. So far, only two clinical trials were conducted on glutathione supplementation for 4 weeks duration. There was no serious or systematic adverse effects reported in clinical trials. As the two clinic trials resulted contradictory outcomes, further studies needed for conformation of the clinic benefits of glutathione. Otherwise, random use of glutathione may be risk for the health of the people. Besides, the marketer mainly promoting glutathione as the skin whitening beauty product instead of using as health supplement, it may cause additional and serious risk to the users as the manufacturer not providing sufficient information about the product, its registration number, manufacturing company, etc.

Lactobacillus reuteri-specific immunoregulatory gene rsiR modulates histamine production and immunomodulation by Lactobacillus reuteri.

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Hemarajata, P; Gao, C; Pflughoeft, K J; Thomas, C M; Saulnier, D M; Spinler, J K; Versalovic, J

2013-12-01

Human microbiome-derived strains of Lactobacillus reuteri potently suppress proinflammatory cytokines like human tumor necrosis factor (TNF) by converting the amino acid l-histidine to the biogenic amine histamine. Histamine suppresses mitogen-activated protein (MAP) kinase activation and cytokine production by signaling via histamine receptor type 2 (H2) on myeloid cells. Investigations of the gene expression profiles of immunomodulatory L. reuteri ATCC PTA 6475 highlighted numerous genes that were highly expressed during the stationary phase of growth, when TNF suppression is most potent. One such gene was found to be a regulator of genes involved in histidine-histamine metabolism by this probiotic species. During the course of these studies, this gene was renamed the Lactobacillus reuteri-specific immunoregulatory (rsiR) gene. The rsiR gene is essential for human TNF suppression by L. reuteri and expression of the histidine decarboxylase (hdc) gene cluster on the L. reuteri chromosome. Inactivation of rsiR resulted in diminished TNF suppression in vitro and reduced anti-inflammatory effects in vivo in a trinitrobenzene sulfonic acid (TNBS)-induced mouse model of acute colitis. A L. reuteri strain lacking an intact rsiR gene was unable to suppress colitis and resulted in greater concentrations of serum amyloid A (SAA) in the bloodstream of affected animals. The PhdcAB promoter region targeted by rsiR was defined by reporter gene experiments. These studies support the presence of a regulatory gene, rsiR, which modulates the expression of a gene cluster known to mediate immunoregulation by probiotics at the transcriptional level. These findings may point the way toward new strategies for controlling gene expression in probiotics by dietary interventions or microbiome manipulation.

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

HAND2 Target Gene Regulatory Networks Control Atrioventricular Canal and Cardiac Valve Development.

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Laurent, Frédéric; Girdziusaite, Ausra; Gamart, Julie; Barozzi, Iros; Osterwalder, Marco; Akiyama, Jennifer A; Lincoln, Joy; Lopez-Rios, Javier; Visel, Axel; Zuniga, Aimée; Zeller, Rolf

2017-05-23

The HAND2 transcriptional regulator controls cardiac development, and we uncover additional essential functions in the endothelial to mesenchymal transition (EMT) underlying cardiac cushion development in the atrioventricular canal (AVC). In Hand2-deficient mouse embryos, the EMT underlying AVC cardiac cushion formation is disrupted, and we combined ChIP-seq of embryonic hearts with transcriptome analysis of wild-type and mutants AVCs to identify the functionally relevant HAND2 target genes. The HAND2 target gene regulatory network (GRN) includes most genes with known functions in EMT processes and AVC cardiac cushion formation. One of these is Snai1, an EMT master regulator whose expression is lost from Hand2-deficient AVCs. Re-expression of Snai1 in mutant AVC explants partially restores this EMT and mesenchymal cell migration. Furthermore, the HAND2-interacting enhancers in the Snai1 genomic landscape are active in embryonic hearts and other Snai1-expressing tissues. These results show that HAND2 directly regulates the molecular cascades initiating AVC cardiac valve development. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

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.

Misregulation of spermatogenesis genes in Drosophila hybrids is lineage-specific and driven by the combined effects of sterility and fast male regulatory divergence.

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Gomes, S; Civetta, A

2014-09-01

Hybrid male sterility is a common outcome of crosses between different species. Gene expression studies have found that a number of spermatogenesis genes are differentially expressed in sterile hybrid males, compared with parental species. Late-stage sperm development genes are particularly likely to be misexpressed, with fewer early-stage genes affected. Thus, a link has been posited between misexpression and sterility. A more recent alternative explanation for hybrid gene misexpression has been that it is independent of sterility and driven by divergent evolution of male-specific regulatory elements between species (faster male hypothesis). The faster male hypothesis predicts that misregulation of spermatogenesis genes should be independent of sterility and approximately the same in both hybrids, whereas sterility should only affect gene expression in sterile hybrids. To test the faster male hypothesis vs. the effect of sterility on gene misexpression, we analyse spermatogenesis gene expression in different species pairs of the Drosophila phylogeny, where hybrid male sterility occurs in only one direction of the interspecies cross (i.e. unidirectional sterility). We find significant differences among genes in misexpression with effects that are lineage-specific and caused by sterility or fast male regulatory divergence. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Enhancement of plasmid-mediated stable gene expression by ...

African Journals Online (AJOL)

ARL

2012-06-12

Jun 12, 2012 ... production and faithful translation and processing of proteins (Baldi et al., ..... deeper understanding of the interaction of cellular factors and regulatory DNA .... mediated transgene expression in the rat brain. Gene Ther., 7: ...

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

Directory of Open Access Journals (Sweden)

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.

The Role of Cytotoxic T-lymphocyte-associated Protein 4 (CTLA-4) Gene, Thyroid Stimulating Hormone Receptor (TSHR) Gene and Regulatory T-cells as Risk Factors for Relapse in Patients with Graves Disease.

Science.gov (United States)

Eliana, Fatimah; Suwondo, Pradana; Asmarinah, Asmarinah; Harahap, Alida; Djauzi, Samsuridjal; Prihartono, Joedo; Pemayun, Tjokorda Gde Dalem

2017-07-01

graves' disease (GD) is the most common condition of thyrotoxicosis. The management of GD is initiated with the administration of antithyroid drugs; however, it requires a long time to achieve remission. In reality more than 50% of patients who had remission may be at risk for relapse after the drug is stopped. This study aimed to evaluate the role of clinical factors such as smoking habit, degree of ophtalmopathy, degree of thyroid enlargement; genetic factors such as CTLA-4 gene on nucleotide 49 at codon 17 of exon 1, CTLA-4 gene of promotor -318, TSHR gene polymorphism rs2268458 of intron 1; and immunological factors such as regulatory T cells (Treg) and thyroid receptor antibody (TRAb); that affecting the relapse of patients with Graves' disease in Indonesia. this was a case-control study, that compared 72 subjects who had relapse and 72 subjects without relapse at 12 months after cessation of antithyroid treatment, who met the inclusion criteria. Genetic polymorphism examination was performed using PCR-RFLP. The number of regulatory T cells was counted using flow cytometry analysis and ELISA was used to measure TRAb. The logistic regression was used since the dependent variables were categorical variables. the analysis of this study demonstrated that there was a correlation between relapse of disease and family factors (p=0.008), age at diagnosis (p=0.021), 2nd degree of Graves' ophthalmopathy (p=0.001), enlarged thyroid gland, which exceeded the lateral edge of the sternocleidomastoid muscles (p=0.040), duration of remission period (p=0.029), GG genotype of CTLA-4 gene on the nucleotide 49 at codon 17 of exon 1 (p=0.016), CC genotype of TSHR gene on the rs2268458 of intron 1 (p=0.003), the number of regulatory T cells (p=0.001) and TRAb levels (p=0.002). genetic polymorphisms of CTLA-4 gene on the nucleotide 49 at codon 17 of exon 1, TSHR gene SNP rs2268458 of intron 1, number of regulatory T cells and TRAb levels play a role as risk factors for relapse in

The Role of Cytotoxic T-lymphocyte-associated Protein 4 (CTLA-4 Gene, Thyroid Stimulating Hormone Receptor (TSHR Gene and Regulatory T-cells as Risk Factors for Relapse in Patients with Graves Disease

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Fatimah Eliana

2017-11-01

Full Text Available Background: graves’ disease (GD is the most common condition of thyrotoxicosis. The management of GD is initiated with the administration of antithyroid drugs; however, it requires a long time to achieve remission. In reality more than 50% of patients who had remission may be at risk for relapse after the drug is stopped. This study aimed to evaluate the role of clinical factors such as smoking habit, degree of ophtalmopathy, degree of thyroid enlargement; genetic factors such as CTLA-4 gene on nucleotide 49 at codon 17 of exon 1, CTLA-4 gene of promotor -318, TSHR gene polymorphism rs2268458 of intron 1; and immunological factors such as regulatory T cells (Treg and thyroid receptor antibody (TRAb; that affecting the relapse of patients with Graves’ disease in Indonesia. Methods: this was a case-control study, that compared 72 subjects who had relapse and 72 subjects without relapse at 12 months after cessation of antithyroid treatment, who met the inclusion criteria. Genetic polymorphism examination was performed using PCR-RFLP. The number of regulatory T cells was counted using flow cytometry analysis and ELISA was used to measure TRAb. The logistic regression was used since the dependent variables were categorical variables. Results: the analysis of this study demonstrated that there was a correlation between relapse of disease and family factors (p=0.008, age at diagnosis (p=0.021, 2nd degree of Graves’ ophthalmopathy (p=0.001, enlarged thyroid gland, which exceeded the lateral edge of the sternocleidomastoid muscles (p=0.040, duration of remission period (p=0.029, GG genotype of CTLA-4 gene on the nucleotide 49 at codon 17 of exon 1 (p=0.016, CC genotype of TSHR gene on the rs2268458 of intron 1 (p=0.003, the number of regulatory T cells (p=0.001 and TRAb levels (p=0.002. Conclusion: genetic polymorphisms of CTLA-4 gene on the nucleotide 49 at codon 17 of exon 1, TSHR gene SNP rs2268458 of intron 1, number of regulatory T cells and

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems

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Faridah Hani Mohamed Salleh

2017-01-01

Full Text Available Gene regulatory network (GRN reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C as a direct interaction (A → C. Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.

Functional dissection of drought-responsive gene expression patterns in Cynodon dactylon L.

Science.gov (United States)

Kim, Changsoo; Lemke, Cornelia; Paterson, Andrew H

2009-05-01

Water deficit is one of the main abiotic factors that affect plant productivity in subtropical regions. To identify genes induced during the water stress response in Bermudagrass (Cynodon dactylon), cDNA macroarrays were used. The macroarray analysis identified 189 drought-responsive candidate genes from C. dactylon, of which 120 were up-regulated and 69 were down-regulated. The candidate genes were classified into seven groups by cluster analysis of expression levels across two intensities and three durations of imposed stress. Annotation using BLASTX suggested that up-regulated genes may be involved in proline biosynthesis, signal transduction pathways, protein repair systems, and removal of toxins, while down-regulated genes were mostly related to basic plant metabolism such as photosynthesis and glycolysis. The functional classification of gene ontology (GO) was consistent with the BLASTX results, also suggesting some crosstalk between abiotic and biotic stress. Comparative analysis of cis-regulatory elements from the candidate genes implicated specific elements in drought response in Bermudagrass. Although only a subset of genes was studied, Bermudagrass shared many drought-responsive genes and cis-regulatory elements with other botanical models, supporting a strategy of cross-taxon application of drought-responsive genes, regulatory cues, and physiological-genetic information.

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

Enhancing Tissue Engineering and Regenerative Medicine Product Commercialization: The Role of Science in Regulatory Decision-Making for the TE/RM Product Development.

Science.gov (United States)

Bertram, Timothy A; Johnson, Peter C; Tawil, Bill J; Van Dyke, Mark; Hellman, Kiki B

2015-10-01

TERMIS-AM Industry Committee (TERMIS-AM/IC), in collaboration with the TERMIS-Europe (EU)/IC, conducted a symposium involving the European Medicines Agency and the U.S. Food and Drug Administration (FDA) toward building an understanding of the rational basis for regulatory decision-making and providing a framework for decisions made during the evaluation of safety and efficacy of TE/RM technologies. This symposium was held in August 2012 during the TERMIS-WC in Vienna, Austria. Emerging from this international initiative by the European Union and the United States, representatives from the respective agencies demonstrated that there are ongoing interagency efforts for developing common national practices toward harmonization of regulatory requirements for the TE/RM products. To extend a broad-based understanding of the role of science in regulatory decision-making, TERMIS-AM/IC, in cooperation with the FDA, organized a symposium at the 2014 TERMIS-AM Annual Meeting, which was held in Washington, DC. This event provided insights from leaders in the FDA and TERMIS on the current status of regulatory approaches for the approved TE/RM products, the use of science in making regulatory decisions, and TE/RM technologies that are in the development pipeline to address unmet medical needs. A far-ranging discussion with FDA representatives, industrialists, physicians, regenerative medicine biologists, and tissue engineers considered the gaps in today's scientific and regulatory understanding of TE/RM technologies. The identified gaps represent significant opportunities to advance TE/RM technologies toward commercialization.

Structural and functional analysis of mouse Msx1 gene promoter: sequence conservation with human MSX1 promoter points at potential regulatory elements.

Science.gov (United States)

Gonzalez, S M; Ferland, L H; Robert, B; Abdelhay, E

1998-06-01

Vertebrate Msx genes are related to one of the most divergent homeobox genes of Drosophila, the muscle segment homeobox (msh) gene, and are expressed in a well-defined pattern at sites of tissue interactions. This pattern of expression is conserved in vertebrates as diverse as quail, zebrafish, and mouse in a range of sites including neural crest, appendages, and craniofacial structures. In the present work, we performed structural and functional analyses in order to identify potential cis-acting elements that may be regulating Msx1 gene expression. To this end, a 4.9-kb segment of the 5'-flanking region was sequenced and analyzed for transcription-factor binding sites. Four regions showing a high concentration of these sites were identified. Transfection assays with fragments of regulatory sequences driving the expression of the bacterial lacZ reporter gene showed that a region of 4 kb upstream of the transcription start site contains positive and negative elements responsible for controlling gene expression. Interestingly, a fragment of 130 bp seems to contain the minimal elements necessary for gene expression, as its removal completely abolishes gene expression in cultured cells. These results are reinforced by comparison of this region with the human Msx1 gene promoter, which shows extensive conservation, including many consensus binding sites, suggesting a regulatory role for them.

Revealing gene action for production characteristics by inbreeding ...

African Journals Online (AJOL)

Revealing gene action for production characteristics by inbreeding, based on a long-term selection ... The gene action involved in the expression of production characters was investigated, using the effect of the theoretical inbreeding ..... and predicted selection responses for growth, fat and lean traits in mice. J. Anim. Sci.

The upstream regulatory sequence of the light harvesting complex Lhcf2 gene of the marine diatom Phaeodactylum tricornutum enhances transcription in an orientation- and distance-independent fashion.

Science.gov (United States)

Russo, Monia Teresa; Annunziata, Rossella; Sanges, Remo; Ferrante, Maria Immacolata; Falciatore, Angela

2015-12-01

Diatoms are a key phytoplankton group in the contemporary ocean, showing extraordinary adaptation capacities to rapidly changing environments. The recent availability of whole genome sequences from representative species has revealed distinct features in their genomes, like novel combinations of genes encoding distinct metabolisms and a significant number of diatom-specific genes. However, the regulatory mechanisms driving diatom gene expression are still largely uncharacterized. Considering the wide variety of fields of study orbiting diatoms, ranging from ecology, evolutionary biology to biotechnology, it is thus essential to increase our understanding of fundamental gene regulatory processes such as transcriptional regulation. To this aim, we explored the functional properties of the 5'-flanking region of the Phaeodatylum tricornutum Lhcf2 gene, encoding a member of the Light Harvesting Complex superfamily and we showed that this region enhances transcription of a GUS reporter gene in an orientation- and distance-independent fashion. This represents the first example of a cis-regulatory sequence with enhancer-like features discovered in diatoms and it is instrumental for the generation of novel genetic tools and diatom exploitation in different areas of study. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of deterministic cyclic gene regulatory network models with delays

CERN Document Server

Ahsen, Mehmet Eren; Niculescu, Silviu-Iulian

2015-01-01

This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.

Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset

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Gidrol Xavier

2008-02-01

Full Text Available Abstract Background Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interactions may be modelled by a Bayesian Network (BN that represents the presence of direct interactions from regulators to regulees by conditional probability distributions. We used enhanced evolutionary algorithms to stochastically evolve a set of candidate BN structures and found the model that best fits data without prior knowledge. Results We proposed various evolutionary strategies suitable for the task and tested our choices using simulated data drawn from a given bio-realistic network of 35 nodes, the so-called insulin network, which has been used in the literature for benchmarking. We assessed the inferred models against this reference to obtain statistical performance results. We then compared performances of evolutionary algorithms using two kinds of recombination operators that operate at different scales in the graphs. We introduced a niching strategy that reinforces diversity through the population and avoided trapping of the algorithm in one local minimum in the early steps of learning. We show the limited effect of the mutation operator when niching is applied. Finally, we compared our best evolutionary approach with various well known learning algorithms (MCMC, K2, greedy search, TPDA, MMHC devoted to BN structure learning. Conclusion We studied the behaviour of an evolutionary approach enhanced by niching for the learning of gene regulatory networks with BN. We show that this approach outperforms classical structure learning methods in elucidating the original model. These results were obtained for the learning of a bio-realistic network and, more importantly, on various small datasets. This is a suitable approach for learning transcriptional regulatory networks from real datasets without prior knowledge.

Mustn1: A Developmentally Regulated Pan-Musculoskeletal Cell Marker and Regulatory Gene

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Michael Hadjiargyrou

2018-01-01

Full Text Available The Mustn1 gene encodes a small nuclear protein (~9.6 kDa that does not belong to any known family. Its genomic organization consists of three exons interspersed by two introns and it is highly homologous across vertebrate species. Promoter analyses revealed that its expression is regulated by the AP family of transcription factors, especially c-Fos, Fra-2 and JunD. Mustn1 is predominantly expressed in the major tissues of the musculoskeletal system: bone, cartilage, skeletal muscle and tendon. Its expression has been associated with normal embryonic development, postnatal growth, exercise, and regeneration of bone and skeletal muscle. Moreover, its expression has also been detected in various musculoskeletal pathologies, including arthritis, Duchenne muscular dystrophy, other skeletal muscle myopathies, clubfoot and diabetes associated muscle pathology. In vitro and in vivo functional perturbation revealed that Mustn1 is a key regulatory molecule in myogenic and chondrogenic lineages. This comprehensive review summarizes our current knowledge of Mustn1 and proposes that it is a new developmentally regulated pan-musculoskeletal marker as well as a key regulatory protein for cell differentiation and tissue growth.

Regulation – Do or Die: An Analysis of Factors Critical to New Product Development in a Regulatory Context

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Clare O'Dwyer

2017-04-01

Full Text Available This study explores new product development in a strict regulatory and historically secretive environment. Adopting a systems perspective and a mixed methods approach in our research, we examine medical device development in Ireland. Findings indicate that the possession of a regulatory strategy expedites the rate of commercialization, so too does the generation of clear product definitions and marketing claims in the earliest developmental phases. Moreover, results suggest that if the regulated industry strengthens its culture for regulation by prioritizing regulation over speed to market, by encouraging cross-functional team collaborations, and by taking a more proactive approach in post-marketing surveillance activities, it has the potential to improve customer satisfaction and enhance product innovation. This study provides unique empirical data enriched by the homogeneity of its sample. It also contributes guidance to practitioners of new product development within a regulatory context.

Identification of genes for small non-coding RNAs that belong to the regulon of the two-component regulatory system CiaRH in Streptococcus

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Hakenbeck Regine

2010-11-01

Full Text Available Abstract Background Post-transcriptional regulation by small RNAs (sRNAs in bacteria is now recognized as a wide-spread regulatory mechanism modulating a variety of physiological responses including virulence. In Streptococcus pneumoniae, an important human pathogen, the first sRNAs to be described were found in the regulon of the CiaRH two-component regulatory system. Five of these sRNAs were detected and designated csRNAs for cia-dependent small RNAs. CiaRH pleiotropically affects β-lactam resistance, autolysis, virulence, and competence development by yet to be defined molecular mechanisms. Since CiaRH is highly conserved among streptococci, it is of interest to determine if csRNAs are also included in the CiaRH regulon in this group of organisms consisting of commensal as well as pathogenic species. Knowledge on the participation of csRNAs in CiaRH-dependent regulatory events will be the key to define the physiological role of this important control system. Results Genes for csRNAs were predicted in streptococcal genomes and data base entries other than S. pneumoniae by searching for CiaR-activated promoters located in intergenic regions that are followed by a transcriptional terminator. 61 different candidate genes were obtained specifying csRNAs ranging in size from 51 to 202 nt. Comparing these genes among each other revealed 40 different csRNA types. All streptococcal genomes harbored csRNA genes, their numbers varying between two and six. To validate these predictions, S. mitis, S. oralis, and S. sanguinis were subjected to csRNA-specific northern blot analysis. In addition, a csRNA gene from S. thermophilus plasmid pST0 introduced into S. pneumoniae was also tested. Each of the csRNAs was detected on these blots and showed the anticipated sizes. Thus, the method applied here is able to predict csRNAs with high precision. Conclusions The results of this study strongly suggest that genes for small non-coding RNAs, csRNAs, are part of

Integrative analysis of miRNA and gene expression reveals regulatory networks in tamoxifen-resistant breast cancer

DEFF Research Database (Denmark)

Joshi, Tejal; Elias, Daniel; Stenvang, Jan

2016-01-01

and 14-3-3 family genes. Integrating the inferred miRNA-target relationships, we investigated the functional importance of 2 central genes, SNAI2 and FYN, which showed increased expression in TamR cells, while their corresponding regulatory miRNA were downregulated. Using specific chemical inhibitors......Tamoxifen is an effective anti-estrogen treatment for patients with estrogen receptor-positive (ER+) breast cancer, however, tamoxifen resistance is frequently observed. To elucidate the underlying molecular mechanisms of tamoxifen resistance, we performed a systematic analysis of miRNA......-mediated gene regulation in three clinically-relevant tamoxifen-resistant breast cancer cell lines (TamRs) compared to their parental tamoxifen-sensitive cell line. Alterations in the expression of 131 miRNAs in tamoxifen-resistant vs. parental cell lines were identified, 22 of which were common to all Tam...

A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

Energy Technology Data Exchange (ETDEWEB)

Santra, Tapesh, E-mail: tapesh.santra@ucd.ie [Systems Biology Ireland, University College Dublin, Dublin (Ireland)

2014-05-20

Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein–protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

International Nuclear Information System (INIS)

Santra, Tapesh

2014-01-01

Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein–protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

Barcoded DNA-tag reporters for multiplex cis-regulatory analysis.

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Jongmin Nam

Full Text Available Cis-regulatory DNA sequences causally mediate patterns of gene expression, but efficient experimental analysis of these control systems has remained challenging. Here we develop a new version of "barcoded" DNA-tag reporters, "Nanotags" that permit simultaneous quantitative analysis of up to 130 distinct cis-regulatory modules (CRMs. The activities of these reporters are measured in single experiments by the NanoString RNA counting method and other quantitative procedures. We demonstrate the efficiency of the Nanotag method by simultaneously measuring hourly temporal activities of 126 CRMs from 46 genes in the developing sea urchin embryo, otherwise a virtually impossible task. Nanotags are also used in gene perturbation experiments to reveal cis-regulatory responses of many CRMs at once. Nanotag methodology can be applied to many research areas, ranging from gene regulatory networks to functional and evolutionary genomics.

MutaNET: a tool for automated analysis of genomic mutations in gene regulatory networks.

Science.gov (United States)

Hollander, Markus; Hamed, Mohamed; Helms, Volkhard; Neininger, Kerstin

2018-03-01

Mutations in genomic key elements can influence gene expression and function in various ways, and hence greatly contribute to the phenotype. We developed MutaNET to score the impact of individual mutations on gene regulation and function of a given genome. MutaNET performs statistical analyses of mutations in different genomic regions. The tool also incorporates the mutations in a provided gene regulatory network to estimate their global impact. The integration of a next-generation sequencing pipeline enables calling mutations prior to the analyses. As application example, we used MutaNET to analyze the impact of mutations in antibiotic resistance (AR) genes and their potential effect on AR of bacterial strains. MutaNET is freely available at https://sourceforge.net/projects/mutanet/. It is implemented in Python and supported on Mac OS X, Linux and MS Windows. Step-by-step instructions are available at http://service.bioinformatik.uni-saarland.de/mutanet/. volkhard.helms@bioinformatik.uni-saarland.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The SaeR/S gene regulatory system induces a pro-inflammatory cytokine response during Staphylococcus aureus infection.

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Robert L Watkins

Full Text Available Community-associated methicillin-resistant Staphylococcus aureus accounts for a large portion of the increased staphylococcal disease incidence and can cause illness ranging from mild skin infections to rapidly fatal sepsis syndromes. Currently, we have limited understanding of S. aureus-derived mechanisms contributing to bacterial pathogenesis and host inflammation during staphylococcal disease. Herein, we characterize an influential role for the saeR/S two-component gene regulatory system in mediating cytokine induction using mouse models of S. aureus pathogenesis. Invasive S. aureus infection induced the production of localized and systemic pro-inflammatory cytokines, including tumor necrosis factor alpha (TNF-α, interferon gamma (IFN-γ, interleukin (IL-6 and IL-2. In contrast, mice infected with an isogenic saeR/S deletion mutant demonstrated significantly reduced pro-inflammatory cytokine levels. Additionally, secreted factors influenced by saeR/S elicited pro-inflammatory cytokines in human blood ex vivo. Our study further demonstrated robust saeR/S-mediated IFN-γ production during both invasive and subcutaneous skin infections. Results also indicated a critical role for saeR/S in promoting bacterial survival and enhancing host mortality during S. aureus peritonitis. Taken together, this study provides insight into specific mechanisms used by S. aureus during staphylococcal disease and characterizes a relationship between a bacterial global regulator of virulence and the production of pro-inflammatory mediators.

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

Information transmission in genetic regulatory networks: a review

International Nuclear Information System (INIS)

Tkacik, Gasper; Walczak, Aleksandra M

2011-01-01

Genetic regulatory networks enable cells to respond to changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform, and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between a network's inputs and outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary for understanding recent work. We then discuss the functional complexity of gene regulation, which arises from the molecular nature of the regulatory interactions. We end by reviewing some experiments that support the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted 'positional information'. (topical review)

A quantitative and dynamic model of the Arabidopsis flowering time gene regulatory network.

Directory of Open Access Journals (Sweden)

Felipe Leal Valentim

Full Text Available Various environmental signals integrate into a network of floral regulatory genes leading to the final decision on when to flower. Although a wealth of qualitative knowledge is available on how flowering time genes regulate each other, only a few studies incorporated this knowledge into predictive models. Such models are invaluable as they enable to investigate how various types of inputs are combined to give a quantitative readout. To investigate the effect of gene expression disturbances on flowering time, we developed a dynamic model for the regulation of flowering time in Arabidopsis thaliana. Model parameters were estimated based on expression time-courses for relevant genes, and a consistent set of flowering times for plants of various genetic backgrounds. Validation was performed by predicting changes in expression level in mutant backgrounds and comparing these predictions with independent expression data, and by comparison of predicted and experimental flowering times for several double mutants. Remarkably, the model predicts that a disturbance in a particular gene has not necessarily the largest impact on directly connected genes. For example, the model predicts that SUPPRESSOR OF OVEREXPRESSION OF CONSTANS (SOC1 mutation has a larger impact on APETALA1 (AP1, which is not directly regulated by SOC1, compared to its effect on LEAFY (LFY which is under direct control of SOC1. This was confirmed by expression data. Another model prediction involves the importance of cooperativity in the regulation of APETALA1 (AP1 by LFY, a prediction supported by experimental evidence. Concluding, our model for flowering time gene regulation enables to address how different quantitative inputs are combined into one quantitative output, flowering time.

Integrating Ontological Knowledge and Textual Evidence in Estimating Gene and Gene Product Similarity

Energy Technology Data Exchange (ETDEWEB)

Sanfilippo, Antonio P.; Posse, Christian; Gopalan, Banu; Tratz, Stephen C.; Gregory, Michelle L.

2006-06-08

With the rising influence of the Gene On-tology, new approaches have emerged where the similarity between genes or gene products is obtained by comparing Gene Ontology code annotations associ-ated with them. So far, these approaches have solely relied on the knowledge en-coded in the Gene Ontology and the gene annotations associated with the Gene On-tology database. The goal of this paper is to demonstrate that improvements to these approaches can be obtained by integrating textual evidence extracted from relevant biomedical literature.

A unified architecture of transcriptional regulatory elements

DEFF Research Database (Denmark)

Andersson, Robin; Sandelin, Albin Gustav; Danko, Charles G.

2015-01-01

Gene expression is precisely controlled in time and space through the integration of signals that act at gene promoters and gene-distal enhancers. Classically, promoters and enhancers are considered separate classes of regulatory elements, often distinguished by histone modifications. However...... and enhancers are considered a single class of functional element, with a unified architecture for transcription initiation. The context of interacting regulatory elements and the surrounding sequences determine local transcriptional output as well as the enhancer and promoter activities of individual elements....

Evolving chromosomes and gene regulatory networks

Indian Academy of Sciences (India)

Aswin

Genes under H NS control can be. (a) regulated by H NS. (b) regulated by H NS and StpA. Because backup by StpA is partial. Page 19. Gene expression level. H NS regulated xenogenes. Other genes. Page 20 ... recollect: H&NS silences highl transcribable genes. Gene expression level unilateral. Other genes epistatic ...

Systematic identification of regulatory variants associated with cancer risk.

Science.gov (United States)

Liu, Song; Liu, Yuwen; Zhang, Qin; Wu, Jiayu; Liang, Junbo; Yu, Shan; Wei, Gong-Hong; White, Kevin P; Wang, Xiaoyue

2017-10-23

Most cancer risk-associated single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) are noncoding and it is challenging to assess their functional impacts. To systematically identify the SNPs that affect gene expression by modulating activities of distal regulatory elements, we adapt the self-transcribing active regulatory region sequencing (STARR-seq) strategy, a high-throughput technique to functionally quantify enhancer activities. From 10,673 SNPs linked with 996 cancer risk-associated SNPs identified in previous GWAS studies, we identify 575 SNPs in the fragments that positively regulate gene expression, and 758 SNPs in the fragments with negative regulatory activities. Among them, 70 variants are regulatory variants for which the two alleles confer different regulatory activities. We analyze in depth two regulatory variants-breast cancer risk SNP rs11055880 and leukemia risk-associated SNP rs12142375-and demonstrate their endogenous regulatory activities on expression of ATF7IP and PDE4B genes, respectively, using a CRISPR-Cas9 approach. By identifying regulatory variants associated with cancer susceptibility and studying their molecular functions, we hope to help the interpretation of GWAS results and provide improved information for cancer risk assessment.