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 ...

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.

A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

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Haitao Guo

2017-01-01

Full Text Available The discovery of cis-regulatory modules (CRMs is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them.

A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

Science.gov (United States)

2017-01-01

The discovery of cis-regulatory modules (CRMs) is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them. PMID:28497059

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

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

2015-12-01

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

Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach

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Buer Jan

2004-12-01

Full Text Available Abstract Background Cellular functions are coordinately carried out by groups of genes forming functional modules. Identifying such modules in the transcriptional regulatory network (TRN of organisms is important for understanding the structure and function of these fundamental cellular networks and essential for the emerging modular biology. So far, the global connectivity structure of TRN has not been well studied and consequently not applied for the identification of functional modules. Moreover, network motifs such as feed forward loop are recently proposed to be basic building blocks of TRN. However, their relationship to functional modules is not clear. Results In this work we proposed a top-down approach to identify modules in the TRN of E. coli. By studying the global connectivity structure of the regulatory network, we first revealed a five-layer hierarchical structure in which all the regulatory relationships are downward. Based on this regulatory hierarchy, we developed a new method to decompose the regulatory network into functional modules and to identify global regulators governing multiple modules. As a result, 10 global regulators and 39 modules were identified and shown to have well defined functions. We then investigated the distribution and composition of the two basic network motifs (feed forward loop and bi-fan motif in the hierarchical structure of TRN. We found that most of these network motifs include global regulators, indicating that these motifs are not basic building blocks of modules since modules should not contain global regulators. Conclusion The transcriptional regulatory network of E. coli possesses a multi-layer hierarchical modular structure without feedback regulation at transcription level. This hierarchical structure builds the basis for a new and simple decomposition method which is suitable for the identification of functional modules and global regulators in the transcriptional regulatory network of E

Modulation of dynamic modes by interplay between positive and negative feedback loops in gene regulatory networks

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Wang, Liu-Suo; Li, Ning-Xi; Chen, Jing-Jia; Zhang, Xiao-Peng; Liu, Feng; Wang, Wei

2018-04-01

A positive and a negative feedback loop can induce bistability and oscillation, respectively, in biological networks. Nevertheless, they are frequently interlinked to perform more elaborate functions in many gene regulatory networks. Coupled positive and negative feedback loops may exhibit either oscillation or bistability depending on the intensity of the stimulus in some particular networks. It is less understood how the transition between the two dynamic modes is modulated by the positive and negative feedback loops. We developed an abstract model of such systems, largely based on the core p53 pathway, to explore the mechanism for the transformation of dynamic behaviors. Our results show that enhancing the positive feedback may promote or suppress oscillations depending on the strength of both feedback loops. We found that the system oscillates with low amplitudes in response to a moderate stimulus and switches to the on state upon a strong stimulus. When the positive feedback is activated much later than the negative one in response to a strong stimulus, the system exhibits long-term oscillations before switching to the on state. We explain this intriguing phenomenon using quasistatic approximation. Moreover, early switching to the on state may occur when the system starts from a steady state in the absence of stimuli. The interplay between the positive and negative feedback plays a key role in the transitions between oscillation and bistability. Of note, our conclusions should be applicable only to some specific gene regulatory networks, especially the p53 network, in which both oscillation and bistability exist in response to a certain type of stimulus. Our work also underscores the significance of transient dynamics in determining cellular outcome.

KIRMES: kernel-based identification of regulatory modules in euchromatic sequences.

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Schultheiss, Sebastian J; Busch, Wolfgang; Lohmann, Jan U; Kohlbacher, Oliver; Rätsch, Gunnar

2009-08-15

Understanding transcriptional regulation is one of the main challenges in computational biology. An important problem is the identification of transcription factor (TF) binding sites in promoter regions of potential TF target genes. It is typically approached by position weight matrix-based motif identification algorithms using Gibbs sampling, or heuristics to extend seed oligos. Such algorithms succeed in identifying single, relatively well-conserved binding sites, but tend to fail when it comes to the identification of combinations of several degenerate binding sites, as those often found in cis-regulatory modules. We propose a new algorithm that combines the benefits of existing motif finding with the ones of support vector machines (SVMs) to find degenerate motifs in order to improve the modeling of regulatory modules. In experiments on microarray data from Arabidopsis thaliana, we were able to show that the newly developed strategy significantly improves the recognition of TF targets. The python source code (open source-licensed under GPL), the data for the experiments and a Galaxy-based web service are available at http://www.fml.mpg.de/raetsch/suppl/kirmes/.

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.

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.

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...

Predicting tissue specific cis-regulatory modules in the human genome using pairs of co-occurring motifs

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Girgis Hani Z

2012-02-01

Full Text Available Abstract Background Researchers seeking to unlock the genetic basis of human physiology and diseases have been studying gene transcription regulation. The temporal and spatial patterns of gene expression are controlled by mainly non-coding elements known as cis-regulatory modules (CRMs and epigenetic factors. CRMs modulating related genes share the regulatory signature which consists of transcription factor (TF binding sites (TFBSs. Identifying such CRMs is a challenging problem due to the prohibitive number of sequence sets that need to be analyzed. Results We formulated the challenge as a supervised classification problem even though experimentally validated CRMs were not required. Our efforts resulted in a software system named CrmMiner. The system mines for CRMs in the vicinity of related genes. CrmMiner requires two sets of sequences: a mixed set and a control set. Sequences in the vicinity of the related genes comprise the mixed set, whereas the control set includes random genomic sequences. CrmMiner assumes that a large percentage of the mixed set is made of background sequences that do not include CRMs. The system identifies pairs of closely located motifs representing vertebrate TFBSs that are enriched in the training mixed set consisting of 50% of the gene loci. In addition, CrmMiner selects a group of the enriched pairs to represent the tissue-specific regulatory signature. The mixed and the control sets are searched for candidate sequences that include any of the selected pairs. Next, an optimal Bayesian classifier is used to distinguish candidates found in the mixed set from their control counterparts. Our study proposes 62 tissue-specific regulatory signatures and putative CRMs for different human tissues and cell types. These signatures consist of assortments of ubiquitously expressed TFs and tissue-specific TFs. Under controlled settings, CrmMiner identified known CRMs in noisy sets up to 1:25 signal-to-noise ratio. CrmMiner was

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

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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.

cisMEP: an integrated repository of genomic epigenetic profiles and cis-regulatory modules in Drosophila.

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Yang, Tzu-Hsien; Wang, Chung-Ching; Hung, Po-Cheng; Wu, Wei-Sheng

2014-01-01

Cis-regulatory modules (CRMs), or the DNA sequences required for regulating gene expression, play the central role in biological researches on transcriptional regulation in metazoan species. Nowadays, the systematic understanding of CRMs still mainly resorts to computational methods due to the time-consuming and small-scale nature of experimental methods. But the accuracy and reliability of different CRM prediction tools are still unclear. Without comparative cross-analysis of the results and combinatorial consideration with extra experimental information, there is no easy way to assess the confidence of the predicted CRMs. This limits the genome-wide understanding of CRMs. It is known that transcription factor binding and epigenetic profiles tend to determine functions of CRMs in gene transcriptional regulation. Thus integration of the genome-wide epigenetic profiles with systematically predicted CRMs can greatly help researchers evaluate and decipher the prediction confidence and possible transcriptional regulatory functions of these potential CRMs. However, these data are still fragmentary in the literatures. Here we performed the computational genome-wide screening for potential CRMs using different prediction tools and constructed the pioneer database, cisMEP (cis-regulatory module epigenetic profile database), to integrate these computationally identified CRMs with genomic epigenetic profile data. cisMEP collects the literature-curated TFBS location data and nine genres of epigenetic data for assessing the confidence of these potential CRMs and deciphering the possible CRM functionality. cisMEP aims to provide a user-friendly interface for researchers to assess the confidence of different potential CRMs and to understand the functions of CRMs through experimentally-identified epigenetic profiles. The deposited potential CRMs and experimental epigenetic profiles for confidence assessment provide experimentally testable hypotheses for the molecular mechanisms

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

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

2014-01-01

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

Functional modules by relating protein interaction networks and gene expression.

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Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Lmx1b-targeted cis-regulatory modules involved in limb dorsalization.

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Haro, Endika; Watson, Billy A; Feenstra, Jennifer M; Tegeler, Luke; Pira, Charmaine U; Mohan, Subburaman; Oberg, Kerby C

2017-06-01

Lmx1b is a homeodomain transcription factor responsible for limb dorsalization. Despite striking double-ventral (loss-of-function) and double-dorsal (gain-of-function) limb phenotypes, no direct gene targets in the limb have been confirmed. To determine direct targets, we performed a chromatin immunoprecipitation against Lmx1b in mouse limbs at embryonic day 12.5 followed by next-generation sequencing (ChIP-seq). Nearly 84% ( n =617) of the Lmx1b-bound genomic intervals (LBIs) identified overlap with chromatin regulatory marks indicative of potential cis -regulatory modules (PCRMs). In addition, 73 LBIs mapped to CRMs that are known to be active during limb development. We compared Lmx1b-bound PCRMs with genes regulated by Lmx1b and found 292 PCRMs within 1 Mb of 254 Lmx1b-regulated genes. Gene ontological analysis suggests that Lmx1b targets extracellular matrix production, bone/joint formation, axonal guidance, vascular development, cell proliferation and cell movement. We validated the functional activity of a PCRM associated with joint-related Gdf5 that provides a mechanism for Lmx1b-mediated joint modification and a PCRM associated with Lmx1b that suggests a role in autoregulation. This is the first report to describe genome-wide Lmx1b binding during limb development, directly linking Lmx1b to targets that accomplish limb dorsalization. © 2017. Published by The Company of Biologists Ltd.

Sequence-based model of gap gene regulatory network.

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

2014-01-01

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

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

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Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

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

Network perturbation by recurrent regulatory variants in cancer.

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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.

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

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Xiaosheng Wang

2010-03-01

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

Modulation of gene expression made easy

DEFF Research Database (Denmark)

Solem, Christian; Jensen, Peter Ruhdal

2002-01-01

A new approach for modulating gene expression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...... that the method can be applied to modulating the expression of native genes on the chromosome. We constructed a series of strains in which the expression of the las operon, containing the genes pfk, pyk, and ldh, was modulated by integrating a truncated copy of the pfk gene. Importantly, the modulation affected...

Identification of miRNA-mRNA regulatory modules by exploring collective group relationships.

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Masud Karim, S M; Liu, Lin; Le, Thuc Duy; Li, Jiuyong

2016-01-11

microRNAs (miRNAs) play an essential role in the post-transcriptional gene regulation in plants and animals. They regulate a wide range of biological processes by targeting messenger RNAs (mRNAs). Evidence suggests that miRNAs and mRNAs interact collectively in gene regulatory networks. The collective relationships between groups of miRNAs and groups of mRNAs may be more readily interpreted than those between individual miRNAs and mRNAs, and thus are useful for gaining insight into gene regulation and cell functions. Several computational approaches have been developed to discover miRNA-mRNA regulatory modules (MMRMs) with a common aim to elucidate miRNA-mRNA regulatory relationships. However, most existing methods do not consider the collective relationships between a group of miRNAs and the group of targeted mRNAs in the process of discovering MMRMs. Our aim is to develop a framework to discover MMRMs and reveal miRNA-mRNA regulatory relationships from the heterogeneous expression data based on the collective relationships. We propose DIscovering COllective group RElationships (DICORE), an effective computational framework for revealing miRNA-mRNA regulatory relationships. We utilize the notation of collective group relationships to build the computational framework. The method computes the collaboration scores of the miRNAs and mRNAs on the basis of their interactions with mRNAs and miRNAs, respectively. Then it determines the groups of miRNAs and groups of mRNAs separately based on their respective collaboration scores. Next, it calculates the strength of the collective relationship between each pair of miRNA group and mRNA group using canonical correlation analysis, and the group pairs with significant canonical correlations are considered as the MMRMs. We applied this method to three gene expression datasets, and validated the computational discoveries. Analysis of the results demonstrates that a large portion of the regulatory relationships discovered by

Current approaches to gene regulatory network modelling

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Brazma Alvis

2007-09-01

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

Sub-cellular mRNA localization modulates the regulation of gene expression by small RNAs in bacteria

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Teimouri, Hamid; Korkmazhan, Elgin; Stavans, Joel; Levine, Erel

2017-10-01

Small non-coding RNAs can exert significant regulatory activity on gene expression in bacteria. In recent years, substantial progress has been made in understanding bacterial gene expression by sRNAs. However, recent findings that demonstrate that families of mRNAs show non-trivial sub-cellular distributions raise the question of how localization may affect the regulatory activity of sRNAs. Here we address this question within a simple mathematical model. We show that the non-uniform spatial distributions of mRNA can alter the threshold-linear response that characterizes sRNAs that act stoichiometrically, and modulate the hierarchy among targets co-regulated by the same sRNA. We also identify conditions where the sub-cellular organization of cofactors in the sRNA pathway can induce spatial heterogeneity on sRNA targets. Our results suggest that under certain conditions, interpretation and modeling of natural and synthetic gene regulatory circuits need to take into account the spatial organization of the transcripts of participating genes.

PReMod: a database of genome-wide mammalian cis-regulatory module predictions.

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Ferretti, Vincent; Poitras, Christian; Bergeron, Dominique; Coulombe, Benoit; Robert, François; Blanchette, Mathieu

2007-01-01

We describe PReMod, a new database of genome-wide cis-regulatory module (CRM) predictions for both the human and the mouse genomes. The prediction algorithm, described previously in Blanchette et al. (2006) Genome Res., 16, 656-668, exploits the fact that many known CRMs are made of clusters of phylogenetically conserved and repeated transcription factors (TF) binding sites. Contrary to other existing databases, PReMod is not restricted to modules located proximal to genes, but in fact mostly contains distal predicted CRMs (pCRMs). Through its web interface, PReMod allows users to (i) identify pCRMs around a gene of interest; (ii) identify pCRMs that have binding sites for a given TF (or a set of TFs) or (iii) download the entire dataset for local analyses. Queries can also be refined by filtering for specific chromosomal regions, for specific regions relative to genes or for the presence of CpG islands. The output includes information about the binding sites predicted within the selected pCRMs, and a graphical display of their distribution within the pCRMs. It also provides a visual depiction of the chromosomal context of the selected pCRMs in terms of neighboring pCRMs and genes, all of which are linked to the UCSC Genome Browser and the NCBI. PReMod: http://genomequebec.mcgill.ca/PReMod.

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.

Transcription factor trapping by RNA in gene regulatory elements.

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

2015-11-20

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

Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks

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He Weiming

2010-07-01

Full Text Available Abstract Background Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions. Results Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways. Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods. Conclusions Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

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

2016-01-01

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

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato

2016-08-25

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

Detection of deregulated modules using deregulatory linked path.

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Yuxuan Hu

Full Text Available The identification of deregulated modules (such as induced by oncogenes is a crucial step for exploring the pathogenic process of complex diseases. Most of the existing methods focus on deregulation of genes rather than the links of the path among them. In this study, we emphasize on the detection of deregulated links, and develop a novel and effective regulatory path-based approach in finding deregulated modules. Observing that a regulatory pathway between two genes might involve in multiple rather than a single path, we identify condition-specific core regulatory path (CCRP to detect the significant deregulation of regulatory links. Using time-series gene expression, we define the regulatory strength within each gene pair based on statistical dependence analysis. The CCRPs in regulatory networks can then be identified using the shortest path algorithm. Finally, we derive the deregulated modules by integrating the differential edges (as deregulated links of the CCRPs between the case and the control group. To demonstrate the effectiveness of our approach, we apply the method to expression data associated with different states of Human Epidermal Growth Factor Receptor 2 (HER2. The experimental results show that the genes as well as the links in the deregulated modules are significantly enriched in multiple KEGG pathways and GO biological processes, most of which can be validated to suffer from impact of this oncogene based on previous studies. Additionally, we find the regulatory mechanism associated with the crucial gene SNAI1 significantly deregulated resulting from the activation of HER2. Hence, our method provides not only a strategy for detecting the deregulated links in regulatory networks, but also a way to identify concerning deregulated modules, thus contributing to the target selection of edgetic drugs.

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

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Fei Xiao

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

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.

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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.

On the Concept of Cis-regulatory Information: From Sequence Motifs to Logic Functions

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Tarpine, Ryan; Istrail, Sorin

The regulatory genome is about the “system level organization of the core genomic regulatory apparatus, and how this is the locus of causality underlying the twin phenomena of animal development and animal evolution” (E.H. Davidson. The Regulatory Genome: Gene Regulatory Networks in Development and Evolution, Academic Press, 2006). Information processing in the regulatory genome is done through regulatory states, defined as sets of transcription factors (sequence-specific DNA binding proteins which determine gene expression) that are expressed and active at the same time. The core information processing machinery consists of modular DNA sequence elements, called cis-modules, that interact with transcription factors. The cis-modules “read” the information contained in the regulatory state of the cell through transcription factor binding, “process” it, and directly or indirectly communicate with the basal transcription apparatus to determine gene expression. This endowment of each gene with the information-receiving capacity through their cis-regulatory modules is essential for the response to every possible regulatory state to which it might be exposed during all phases of the life cycle and in all cell types. We present here a set of challenges addressed by our CYRENE research project aimed at studying the cis-regulatory code of the regulatory genome. The CYRENE Project is devoted to (1) the construction of a database, the cis-Lexicon, containing comprehensive information across species about experimentally validated cis-regulatory modules; and (2) the software development of a next-generation genome browser, the cis-Browser, specialized for the regulatory genome. The presentation is anchored on three main computational challenges: the Gene Naming Problem, the Consensus Sequence Bottleneck Problem, and the Logic Function Inference Problem.

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

The phenotypic and molecular assessment of the non-conserved Arabidopsis MICRORNA163/S-ADENOSYL-METHYLTRANSFERASE regulatory module during biotic stress.

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Litholdo, Celso Gaspar; Eamens, Andrew Leigh; Waterhouse, Peter Michael

2018-04-01

In plants, microRNAs (miRNAs) have evolved in parallel to the protein-coding genes that they target for expression regulation, and miRNA-directed gene expression regulation is central to almost every cellular process. MicroRNA, miR163, is unique to the Arabidopsis genus and is processed into a 24-nucleotide (nt) mature small regulatory RNA (sRNA) from a single precursor transcript transcribed from a single locus, the MIR163 gene. The MIR163 locus is a result of a recent inverted duplication event of one of the five closely related S-ADENOSYL-METHYLTRANSFERASE genes that the mature miR163 sRNA targets for expression regulation. Currently, however, little is known about the role of the miR163/S-ADENOSYL-METHYLTRANSFERASE regulatory module in response to biotic stress. Here, we document the expression domains of MIR163 and the S-ADENOSYL-METHYLTRANSFERASE target genes following fusion of their putative promoter sequences to the β-glucuronidase (GUS) reporter gene and subsequent in planta expression. Further, we report on our phenotypic and molecular assessment of Arabidopsis thaliana plants with altered miR163 accumulation, namely the mir163-1 and mir163-2 insertion knockout mutants and the miR163 overexpression line, the MIR163-OE plant. Finally, we reveal miR163 accumulation and S-ADENOSYL-METHYLTRANSFERASE target gene expression post treatment with the defence elicitors, salicylic acid and jasmonic acid, and following Fusarium oxysporum infection, wounding, and herbivory attack. Together, the work presented here provides a comprehensive new biological insight into the role played by the Arabidopsis genus-specific miR163/S-ADENOSYL-METHYLTRANSFERASE regulatory module in normal A. thaliana development and during the exposure of A. thaliana plants to biotic stress.

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.

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.

Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

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Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

2017-10-03

With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

Conserved gene regulatory module specifies lateral neural borders across bilaterians.

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Li, Yongbin; Zhao, Di; Horie, Takeo; Chen, Geng; Bao, Hongcun; Chen, Siyu; Liu, Weihong; Horie, Ryoko; Liang, Tao; Dong, Biyu; Feng, Qianqian; Tao, Qinghua; Liu, Xiao

2017-08-01

The lateral neural plate border (NPB), the neural part of the vertebrate neural border, is composed of central nervous system (CNS) progenitors and peripheral nervous system (PNS) progenitors. In invertebrates, PNS progenitors are also juxtaposed to the lateral boundary of the CNS. Whether there are conserved molecular mechanisms determining vertebrate and invertebrate lateral neural borders remains unclear. Using single-cell-resolution gene-expression profiling and genetic analysis, we present evidence that orthologs of the NPB specification module specify the invertebrate lateral neural border, which is composed of CNS and PNS progenitors. First, like in vertebrates, the conserved neuroectoderm lateral border specifier Msx/vab-15 specifies lateral neuroblasts in Caenorhabditis elegans Second, orthologs of the vertebrate NPB specification module ( Msx/vab-15 , Pax3/7/pax-3 , and Zic/ref-2 ) are significantly enriched in worm lateral neuroblasts. In addition, like in other bilaterians, the expression domain of Msx/vab-15 is more lateral than those of Pax3/7/pax-3 and Zic/ref- 2 in C. elegans Third, we show that Msx/vab-15 regulates the development of mechanosensory neurons derived from lateral neural progenitors in multiple invertebrate species, including C. elegans , Drosophila melanogaster , and Ciona intestinalis We also identify a novel lateral neural border specifier, ZNF703/tlp-1 , which functions synergistically with Msx/vab- 15 in both C. elegans and Xenopus laevis These data suggest a common origin of the molecular mechanism specifying lateral neural borders across bilaterians.

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.

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

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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.

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,

Pathogenic adaptation of intracellular bacteria by rewiring a cis-regulatory input function.

Science.gov (United States)

Osborne, Suzanne E; Walthers, Don; Tomljenovic, Ana M; Mulder, David T; Silphaduang, Uma; Duong, Nancy; Lowden, Michael J; Wickham, Mark E; Waller, Ross F; Kenney, Linda J; Coombes, Brian K

2009-03-10

The acquisition of DNA by horizontal gene transfer enables bacteria to adapt to previously unexploited ecological niches. Although horizontal gene transfer and mutation of protein-coding sequences are well-recognized forms of pathogen evolution, the evolutionary significance of cis-regulatory mutations in creating phenotypic diversity through altered transcriptional outputs is not known. We show the significance of regulatory mutation for pathogen evolution by mapping and then rewiring a cis-regulatory module controlling a gene required for murine typhoid. Acquisition of a binding site for the Salmonella pathogenicity island-2 regulator, SsrB, enabled the srfN gene, ancestral to the Salmonella genus, to play a role in pathoadaptation of S. typhimurium to a host animal. We identified the evolved cis-regulatory module and quantified the fitness gain that this regulatory output accrues for the bacterium using competitive infections of host animals. Our findings highlight a mechanism of pathogen evolution involving regulatory mutation that is selected because of the fitness advantage the new regulatory output provides the incipient clones.

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.

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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.

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

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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.

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

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

2013-01-01

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

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

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Shuchi eSmita

2015-12-01

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

Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

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

2012-01-01

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

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.

An integrative approach to inferring biologically meaningful gene modules

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Wang Kai

2011-07-01

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

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

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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.

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.

Science.gov (United States)

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.

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.

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.

Computational and molecular dissection of an X-box cis-Regulatory module

OpenAIRE

Warrington, Timothy Burton

2015-01-01

Ciliopathies are a class of human diseases marked by dysfunction of the cellular organelle, cilia. While many of the molecular components that make up cilia have been identified and studied, comparatively little is understood about the transcriptional regulation of genes encoding these components. The conserved transcription factor Regulatory Factor X (RFX)/DAF-19, which acts through binding to the cis-regulatory motif known as X-box, has been shown to regulate ciliary genes in many animals f...

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

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/.

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

Science.gov (United States)

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

2017-06-12

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

Cloning and bioinformatic analysis of lovastatin biosynthesis regulatory gene lovE.

Science.gov (United States)

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.

Science.gov (United States)

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.

H-ferritin-regulated microRNAs modulate gene expression in K562 cells.

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Flavia Biamonte

Full Text Available In a previous study, we showed that the silencing of the heavy subunit (FHC offerritin, the central iron storage molecule in the cell, is accompanied by a modification in global gene expression. In this work, we explored whether different FHC amounts might modulate miRNA expression levels in K562 cells and studied the impact of miRNAs in gene expression profile modifications. To this aim, we performed a miRNA-mRNA integrative analysis in K562 silenced for FHC (K562shFHC comparing it with K562 transduced with scrambled RNA (K562shRNA. Four miRNAs, namely hsa-let-7g, hsa-let-7f, hsa-let-7i and hsa-miR-125b, were significantly up-regulated in silenced cells. The remarkable down-regulation of these miRNAs, following FHC expression rescue, supports a specific relation between FHC silencing and miRNA-modulation. The integration of target predictions with miRNA and gene expression profiles led to the identification of a regulatory network which includes the miRNAs up-regulated by FHC silencing, as well as91 down-regulated putative target genes. These genes were further classified in 9 networks; the highest scoring network, "Cell Death and Survival, Hematological System Development and Function, Hematopoiesis", is composed by 18 focus molecules including RAF1 and ERK1/2. We confirmed that, following FHC silencing, ERK1/2 phosphorylation is severely impaired and that RAF1 mRNA is significantly down-regulated. Taken all together, our data indicate that, in our experimental model, FHC silencing may affect RAF1/pERK1/2 levels through the modulation of a specific set of miRNAs and add new insights in to the relationship among iron homeostasis and miRNAs.

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

Kynurenine 3-Monooxygenase Gene Associated With Nicotine Initiation and Addiction: Analysis of Novel Regulatory Features at 5′ and 3′-Regions

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Hassan A. Aziz

2018-06-01

Full Text Available Tobacco smoking is widespread behavior in Qatar and worldwide and is considered one of the major preventable causes of ill health and death. Nicotine is part of tobacco smoke that causes numerous health risks and is incredibly addictive; it binds to the α7 nicotinic acetylcholine receptor (α7nAChR in the brain. Recent studies showed α7nAChR involvement in the initiation and addiction of smoking. Kynurenic acid (KA, a significant tryptophan metabolite, is an antagonist of α7nAChR. Inhibition of kynurenine 3-monooxygenase enzyme encoded by KMO enhances the KA levels. Modulating KMO gene expression could be a useful tactic for the treatment of tobacco initiation and dependence. Since KMO regulation is still poorly understood, we aimed to investigate the 5′ and 3′-regulatory factors of KMO gene to advance our knowledge to modulate KMO gene expression. In this study, bioinformatics methods were used to identify the regulatory sequences associated with expression of KMO. The displayed differential expression of KMO mRNA in the same tissue and different tissues suggested the specific usage of the KMO multiple alternative promoters. Eleven KMO alternative promoters identified at 5′-regulatory region contain TATA-Box, lack CpG Island (CGI and showed dinucleotide base-stacking energy values specific to transcription factor binding sites (TFBSs. The structural features of regulatory sequences can influence the transcription process and cell type-specific expression. The uncharacterized LOC105373233 locus coding for non-coding RNA (ncRNA located on the reverse strand in a convergent manner at the 3′-side of KMO locus. The two genes likely expressed by a promoter that lacks TATA-Box harbor CGI and two TFBSs linked to the bidirectional transcription, the NRF1, and ZNF14 motifs. We identified two types of microRNA (miR in the uncharacterized LOC105373233 ncRNA, which are like hsa-miR-5096 and hsa-miR-1285-3p and can target the miR recognition

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

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Kwon, Andrew T.; Chou, Alice Yi; Arenillas, David J.; Wasserman, Wyeth W.

2011-01-01

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. PMID:22144875

Validation of skeletal muscle cis-regulatory module predictions reveals nucleotide composition bias in functional enhancers.

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Andrew T Kwon

2011-12-01

Full Text Available We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions.

Modular arrangement of regulatory RNA elements.

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Roßmanith, Johanna; Narberhaus, Franz

2017-03-04

Due to their simple architecture and control mechanism, regulatory RNA modules are attractive building blocks in synthetic biology. This is especially true for riboswitches, which are natural ligand-binding regulators of gene expression. The discovery of various tandem riboswitches inspired the design of combined RNA modules with activities not yet found in nature. Riboswitches were placed in tandem or in combination with a ribozyme or temperature-responsive RNA thermometer resulting in new functionalities. Here, we compare natural examples of tandem riboswitches with recently designed artificial RNA regulators suggesting substantial modularity of regulatory RNA elements. Challenges associated with modular RNA design are discussed.

Global Regulatory Differences for Gene- and Cell-Based Therapies

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

2017-01-01

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

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

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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.

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.

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.

Plasticity and innovation of regulatory mechanisms underlying seed oil content mediated by duplicated genes in the palaeopolyploid soybean.

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Zhang, Dajian; Zhao, Meixia; Li, Shuai; Sun, Lianjun; Wang, Weidong; Cai, Chunmei; Dierking, Emily C; Ma, Jianxin

2017-06-01

Many plants have undergone whole genome duplication (WGD). However, how regulatory networks underlying a particular trait are reshaped in polyploids has not been experimentally investigated. Here we show that the regulatory pathways modulating seed oil content, which involve WRINKLED1 (WRI1), LEAFY COTYLEDON1 (LEC1), and LEC2 in Arabidopsis, have been modified in the palaeopolyploid soybean. Such modifications include functional reduction of GmWRI1b of the GmWRI1a/GmWRI1b homoeologous pair relevant to WRI1, complementary non-allelic dosage effects of the GmLEC1a/GmLEC1b homoeologous pair relevant to LEC1, pseudogenization of the singleton GmLEC2 relevant to LEC2, and the rise of the LEC2-like function of GmABI3b, contrasting to its homoeolog GmABI3a, which maintains the ABSCISIC ACID INSENSITIVE 3 (ABI3)-like function in modulating seed maturation and dormancy. The function of GmABI3b in modulating seed oil biosynthesis was fulfilled by direct binding to a RY (CATGCA) cis-regulatory element in the GmWRI1a promoter, which was absent in the GmWRI1b promoter, resulting in reduction of the GmWRI1b expression. Nevertheless, the three regulators each exhibited similar intensities of purifying selection to their respective duplicates since these pairs were formed by a WGD event that is proposed to have occurred approximately 13 million years ago (mya), suggesting that the differentiation in spatiotemporal expression between the duplicated genes is more likely to be the outcome of neutral variation in regulatory sequences. This study thus exemplifies the plasticity, dynamics, and novelty of regulatory networks mediated by WGD. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Dissection of regulatory networks that are altered in disease via differential co-expression.

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David Amar

Full Text Available Comparing the gene-expression profiles of sick and healthy individuals can help in understanding disease. Such differential expression analysis is a well-established way to find gene sets whose expression is altered in the disease. Recent approaches to gene-expression analysis go a step further and seek differential co-expression patterns, wherein the level of co-expression of a set of genes differs markedly between disease and control samples. Such patterns can arise from a disease-related change in the regulatory mechanism governing that set of genes, and pinpoint dysfunctional regulatory networks. Here we present DICER, a new method for detecting differentially co-expressed gene sets using a novel probabilistic score for differential correlation. DICER goes beyond standard differential co-expression and detects pairs of modules showing differential co-expression. The expression profiles of genes within each module of the pair are correlated across all samples. The correlation between the two modules, however, differs markedly between the disease and normal samples. We show that DICER outperforms the state of the art in terms of significance and interpretability of the detected gene sets. Moreover, the gene sets discovered by DICER manifest regulation by disease-specific microRNA families. In a case study on Alzheimer's disease, DICER dissected biological processes and protein complexes into functional subunits that are differentially co-expressed, thereby revealing inner structures in disease regulatory networks.

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.

Finding trans-regulatory genes and protein complexes modulating meiotic recombination hotspots of human, mouse and yeast.

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Wu, Min; Kwoh, Chee-Keong; Li, Xiaoli; Zheng, Jie

2014-09-11

The regulatory mechanism of recombination is one of the most fundamental problems in genomics, with wide applications in genome wide association studies (GWAS), birth-defect diseases, molecular evolution, cancer research, etc. Recombination events cluster into short genomic regions called "recombination hotspots". Recently, a zinc finger protein PRDM9 was reported to regulate recombination hotspots in human and mouse genomes. In addition, a 13-mer motif contained in the binding sites of PRDM9 is found to be enriched in human hotspots. However, this 13-mer motif only covers a fraction of hotspots, indicating that PRDM9 is not the only regulator of recombination hotspots. Therefore, the challenge of discovering other regulators of recombination hotspots becomes significant. Furthermore, recombination is a complex process. Hence, multiple proteins acting as machinery, rather than individual proteins, are more likely to carry out this process in a precise and stable manner. Therefore, the extension of the prediction of individual trans-regulators to protein complexes is also highly desired. In this paper, we introduce a pipeline to identify genes and protein complexes associated with recombination hotspots. First, we prioritize proteins associated with hotspots based on their preference of binding to hotspots and coldspots. Second, using the above identified genes as seeds, we apply the Random Walk with Restart algorithm (RWR) to propagate their influences to other proteins in protein-protein interaction (PPI) networks. Hence, many proteins without DNA-binding information will also be assigned a score to implicate their roles in recombination hotspots. Third, we construct sub-PPI networks induced by top genes ranked by RWR for various species (e.g., yeast, human and mouse) and detect protein complexes in those sub-PPI networks. The GO term analysis show that our prioritizing methods and the RWR algorithm are capable of identifying novel genes associated with

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.

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

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

2018-02-16

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

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

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

2015-01-01

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

Alignment and prediction of cis-regulatory modules based on a probabilistic model of evolution.

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Xin He

2009-03-01

Full Text Available Cross-species comparison has emerged as a powerful paradigm for predicting cis-regulatory modules (CRMs and understanding their evolution. The comparison requires reliable sequence alignment, which remains a challenging task for less conserved noncoding sequences. Furthermore, the existing models of DNA sequence evolution generally do not explicitly treat the special properties of CRM sequences. To address these limitations, we propose a model of CRM evolution that captures different modes of evolution of functional transcription factor binding sites (TFBSs and the background sequences. A particularly novel aspect of our work is a probabilistic model of gains and losses of TFBSs, a process being recognized as an important part of regulatory sequence evolution. We present a computational framework that uses this model to solve the problems of CRM alignment and prediction. Our alignment method is similar to existing methods of statistical alignment but uses the conserved binding sites to improve alignment. Our CRM prediction method deals with the inherent uncertainties of binding site annotations and sequence alignment in a probabilistic framework. In simulated as well as real data, we demonstrate that our program is able to improve both alignment and prediction of CRM sequences over several state-of-the-art methods. Finally, we used alignments produced by our program to study binding site conservation in genome-wide binding data of key transcription factors in the Drosophila blastoderm, with two intriguing results: (i the factor-bound sequences are under strong evolutionary constraints even if their neighboring genes are not expressed in the blastoderm and (ii binding sites in distal bound sequences (relative to transcription start sites tend to be more conserved than those in proximal regions. Our approach is implemented as software, EMMA (Evolutionary Model-based cis-regulatory Module Analysis, ready to be applied in a broad biological context.

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.

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

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Mary Qu Yang

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

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

POEM: Identifying joint additive effects on regulatory circuits

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Maya eBotzman

2016-04-01

Full Text Available Motivation: Expression Quantitative Trait Locus (eQTL mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress towards a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such ‘modularization’ approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic effects.Results: Here we present POEM (Pairwise effect On Expression Modules, a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.Availability: The software described in this article is available at csgi.tau.ac.il/POEM/.

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

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.

Cell Type-Specific Chromatin Signatures Underline Regulatory DNA Elements in Human Induced Pluripotent Stem Cells and Somatic Cells.

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Zhao, Ming-Tao; Shao, Ning-Yi; Hu, Shijun; Ma, Ning; Srinivasan, Rajini; Jahanbani, Fereshteh; Lee, Jaecheol; Zhang, Sophia L; Snyder, Michael P; Wu, Joseph C

2017-11-10

Regulatory DNA elements in the human genome play important roles in determining the transcriptional abundance and spatiotemporal gene expression during embryonic heart development and somatic cell reprogramming. It is not well known how chromatin marks in regulatory DNA elements are modulated to establish cell type-specific gene expression in the human heart. We aimed to decipher the cell type-specific epigenetic signatures in regulatory DNA elements and how they modulate heart-specific gene expression. We profiled genome-wide transcriptional activity and a variety of epigenetic marks in the regulatory DNA elements using massive RNA-seq (n=12) and ChIP-seq (chromatin immunoprecipitation combined with high-throughput sequencing; n=84) in human endothelial cells (CD31 + CD144 + ), cardiac progenitor cells (Sca-1 + ), fibroblasts (DDR2 + ), and their respective induced pluripotent stem cells. We uncovered 2 classes of regulatory DNA elements: class I was identified with ubiquitous enhancer (H3K4me1) and promoter (H3K4me3) marks in all cell types, whereas class II was enriched with H3K4me1 and H3K4me3 in a cell type-specific manner. Both class I and class II regulatory elements exhibited stimulatory roles in nearby gene expression in a given cell type. However, class I promoters displayed more dominant regulatory effects on transcriptional abundance regardless of distal enhancers. Transcription factor network analysis indicated that human induced pluripotent stem cells and somatic cells from the heart selected their preferential regulatory elements to maintain cell type-specific gene expression. In addition, we validated the function of these enhancer elements in transgenic mouse embryos and human cells and identified a few enhancers that could possibly regulate the cardiac-specific gene expression. Given that a large number of genetic variants associated with human diseases are located in regulatory DNA elements, our study provides valuable resources for deciphering

Reprogramming of gene expression during compression wood formation in pine: Coordinated modulation of S-adenosylmethionine, lignin and lignan related genes

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2012-01-01

Background Transcript profiling of differentiating secondary xylem has allowed us to draw a general picture of the genes involved in wood formation. However, our knowledge is still limited about the regulatory mechanisms that coordinate and modulate the different pathways providing substrates during xylogenesis. The development of compression wood in conifers constitutes an exceptional model for these studies. Although differential expression of a few genes in differentiating compression wood compared to normal or opposite wood has been reported, the broad range of features that distinguish this reaction wood suggest that the expression of a larger set of genes would be modified. Results By combining the construction of different cDNA libraries with microarray analyses we have identified a total of 496 genes in maritime pine (Pinus pinaster, Ait.) that change in expression during differentiation of compression wood (331 up-regulated and 165 down-regulated compared to opposite wood). Samples from different provenances collected in different years and geographic locations were integrated into the analyses to mitigate the effects of multiple sources of variability. This strategy allowed us to define a group of genes that are consistently associated with compression wood formation. Correlating with the deposition of a thicker secondary cell wall that characterizes compression wood development, the expression of a number of genes involved in synthesis of cellulose, hemicellulose, lignin and lignans was up-regulated. Further analysis of a set of these genes involved in S-adenosylmethionine metabolism, ammonium recycling, and lignin and lignans biosynthesis showed changes in expression levels in parallel to the levels of lignin accumulation in cells undergoing xylogenesis in vivo and in vitro. Conclusions The comparative transcriptomic analysis reported here have revealed a broad spectrum of coordinated transcriptional modulation of genes involved in biosynthesis of

Reprogramming of gene expression during compression wood formation in pine: Coordinated modulation of S-adenosylmethionine, lignin and lignan related genes

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Villalobos David P

2012-06-01

Full Text Available Abstract Background Transcript profiling of differentiating secondary xylem has allowed us to draw a general picture of the genes involved in wood formation. However, our knowledge is still limited about the regulatory mechanisms that coordinate and modulate the different pathways providing substrates during xylogenesis. The development of compression wood in conifers constitutes an exceptional model for these studies. Although differential expression of a few genes in differentiating compression wood compared to normal or opposite wood has been reported, the broad range of features that distinguish this reaction wood suggest that the expression of a larger set of genes would be modified. Results By combining the construction of different cDNA libraries with microarray analyses we have identified a total of 496 genes in maritime pine (Pinus pinaster, Ait. that change in expression during differentiation of compression wood (331 up-regulated and 165 down-regulated compared to opposite wood. Samples from different provenances collected in different years and geographic locations were integrated into the analyses to mitigate the effects of multiple sources of variability. This strategy allowed us to define a group of genes that are consistently associated with compression wood formation. Correlating with the deposition of a thicker secondary cell wall that characterizes compression wood development, the expression of a number of genes involved in synthesis of cellulose, hemicellulose, lignin and lignans was up-regulated. Further analysis of a set of these genes involved in S-adenosylmethionine metabolism, ammonium recycling, and lignin and lignans biosynthesis showed changes in expression levels in parallel to the levels of lignin accumulation in cells undergoing xylogenesis in vivo and in vitro. Conclusions The comparative transcriptomic analysis reported here have revealed a broad spectrum of coordinated transcriptional modulation of genes

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.

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

-CM transitions. We report a novel method to systematically integrate multi-dimensional -omics data and reconstruct the gene regulatory networks. This method will allow one to rapidly determine the cis-modules that regulate key genes during cardiac differentiation.

Understanding gene sequence variation in the context of transcription regulation in yeast.

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Irit Gat-Viks

2010-01-01

Full Text Available DNA sequence polymorphism in a regulatory protein can have a widespread transcriptional effect. Here we present a computational approach for analyzing modules of genes with a common regulation that are affected by specific DNA polymorphisms. We identify such regulatory-linkage modules by integrating genotypic and expression data for individuals in a segregating population with complementary expression data of strains mutated in a variety of regulatory proteins. Our procedure searches simultaneously for groups of co-expressed genes, for their common underlying linkage interval, and for their shared regulatory proteins. We applied the method to a cross between laboratory and wild strains of S. cerevisiae, demonstrating its ability to correctly suggest modules and to outperform extant approaches. Our results suggest that middle sporulation genes are under the control of polymorphism in the sporulation-specific tertiary complex Sum1p/Rfm1p/Hst1p. In another example, our analysis reveals novel inter-relations between Swi3 and two mitochondrial inner membrane proteins underlying variation in a module of aerobic cellular respiration genes. Overall, our findings demonstrate that this approach provides a useful framework for the systematic mapping of quantitative trait loci and their role in gene expression variation.

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.

Systematic identification of regulatory variants associated with cancer risk.

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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.

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.

Mode of delivery shapes gut colonization pattern and modulates regulatory immunity in mice

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Hansen, Camilla Hartmann Friis; Andersen, Line Sidsel Fisker; Krych, Lukasz

2014-01-01

diabetes. In this study, we demonstrate that both C-section and cross-fostering with a genetically distinct strain influence the gut microbiota composition and immune key markers in mice. Gut microbiota profiling by denaturing gradient gel electrophoresis and 454/FLX-based 16S rRNA gene amplicon sequencing...... electrophoresis profiles was evident in adult mice. However, the adult C-section-born mice had lower proportions of Foxp3(+) regulatory T cells, tolerogenic CD103(+) dendritic cells, and less Il10 gene expression in mesenteric lymph nodes and spleens. This demonstrates long-term systemic effect on the regulatory...... and priming of regulatory immune system in mice, and mode of delivery strongly influences this....

Histone methylation mediates plasticity of human FOXP3(+) regulatory T cells by modulating signature gene expressions.

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He, Haiqi; Ni, Bing; Tian, Yi; Tian, Zhiqiang; Chen, Yanke; Liu, Zhengwen; Yang, Xiaomei; Lv, Yi; Zhang, Yong

2014-03-01

CD4(+) FOXP3(+) regulatory T (Treg) cells constitute a heterogeneous and plastic T-cell lineage that plays a pivotal role in maintaining immune homeostasis and immune tolerance. However, the fate of human Treg cells after loss of FOXP3 expression and the epigenetic mechanisms contributing to such a phenotype switch remain to be fully elucidated. In the current study, we demonstrate that human CD4(+) CD25(high) CD127(low/-) Treg cells convert to two subpopulations with distinctive FOXP3(+) and FOXP3(-) phenotypes following in vitro culture with anti-CD3/CD28 and interleukin-2. Digital gene expression analysis showed that upon in vitro expansion, human Treg cells down-regulated Treg cell signature genes, such as FOXP3, CTLA4, ICOS, IKZF2 and LRRC32, but up-regulated a set of T helper lineage-associated genes, especially T helper type 2 (Th2)-associated, such as GATA3, GFI1 and IL13. Subsequent chromatin immunoprecipitation-sequencing of these subpopulations yielded genome-wide maps of their H3K4me3 and H3K27me3 profiles. Surprisingly, reprogramming of Treg cells was associated with differential histone modifications, as evidenced by decreased abundance of permissive H3K4me3 within the down-regulated Treg cell signature genes, such as FOXP3, CTLA4 and LRRC32 loci, and increased abundance of H3K4me3 within the Th2-associated genes, such as IL4 and IL5; however, the H3K27me3 modification profile was not significantly different between the two subpopulations. In conclusion, this study revealed that loss of FOXP3 expression from human Treg cells during in vitro expansion can induce reprogramming to a T helper cell phenotype with a gene expression signature dominated by Th2 lineage-associated genes, and that this cell type conversion may be mediated by histone methylation events. © 2013 John Wiley & Sons Ltd.

Histone methylation mediates plasticity of human FOXP3+ regulatory T cells by modulating signature gene expressions

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He, Haiqi; Ni, Bing; Tian, Yi; Tian, Zhiqiang; Chen, Yanke; Liu, Zhengwen; Yang, Xiaomei; Lv, Yi; Zhang, Yong

2014-01-01

CD4+ FOXP3+ regulatory T (Treg) cells constitute a heterogeneous and plastic T-cell lineage that plays a pivotal role in maintaining immune homeostasis and immune tolerance. However, the fate of human Treg cells after loss of FOXP3 expression and the epigenetic mechanisms contributing to such a phenotype switch remain to be fully elucidated. In the current study, we demonstrate that human CD4+ CD25high CD127low/− Treg cells convert to two subpopulations with distinctive FOXP3+ and FOXP3− phenotypes following in vitro culture with anti-CD3/CD28 and interleukin-2. Digital gene expression analysis showed that upon in vitro expansion, human Treg cells down-regulated Treg cell signature genes, such as FOXP3, CTLA4, ICOS, IKZF2 and LRRC32, but up-regulated a set of T helper lineage-associated genes, especially T helper type 2 (Th2)-associated, such as GATA3, GFI1 and IL13. Subsequent chromatin immunoprecipitation-sequencing of these subpopulations yielded genome-wide maps of their H3K4me3 and H3K27me3 profiles. Surprisingly, reprogramming of Treg cells was associated with differential histone modifications, as evidenced by decreased abundance of permissive H3K4me3 within the down-regulated Treg cell signature genes, such as FOXP3, CTLA4 and LRRC32 loci, and increased abundance of H3K4me3 within the Th2-associated genes, such as IL4 and IL5; however, the H3K27me3 modification profile was not significantly different between the two subpopulations. In conclusion, this study revealed that loss of FOXP3 expression from human Treg cells during in vitro expansion can induce reprogramming to a T helper cell phenotype with a gene expression signature dominated by Th2 lineage-associated genes, and that this cell type conversion may be mediated by histone methylation events. PMID:24152290

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

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Kier, Larry D; Petrick, Jay S

2008-08-01

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

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.

Transcriptional regulation by competing transcription factor modules.

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Rutger Hermsen

2006-12-01

Full Text Available Gene regulatory networks lie at the heart of cellular computation. In these networks, intracellular and extracellular signals are integrated by transcription factors, which control the expression of transcription units by binding to cis-regulatory regions on the DNA. The designs of both eukaryotic and prokaryotic cis-regulatory regions are usually highly complex. They frequently consist of both repetitive and overlapping transcription factor binding sites. To unravel the design principles of these promoter architectures, we have designed in silico prokaryotic transcriptional logic gates with predefined input-output relations using an evolutionary algorithm. The resulting cis-regulatory designs are often composed of modules that consist of tandem arrays of binding sites to which the transcription factors bind cooperatively. Moreover, these modules often overlap with each other, leading to competition between them. Our analysis thus identifies a new signal integration motif that is based upon the interplay between intramodular cooperativity and intermodular competition. We show that this signal integration mechanism drastically enhances the capacity of cis-regulatory domains to integrate signals. Our results provide a possible explanation for the complexity of promoter architectures and could be used for the rational design of synthetic gene circuits.

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

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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...

Characterization of chemically induced liver injuries using gene co-expression modules.

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Gregory J Tawa

Full Text Available Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1 known biochemical pathways associated with liver injuries and 2 clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20% genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.

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...

Network statistics of genetically-driven gene co-expression modules in mouse crosses

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Marie-Pier eScott-Boyer

2013-12-01

Full Text Available In biology, networks are used in different contexts as ways to represent relationships between entities, such as for instance interactions between genes, proteins or metabolites. Despite progress in the analysis of such networks and their potential to better understand the collective impact of genes on complex traits, one remaining challenge is to establish the biologic validity of gene co-expression networks and to determine what governs their organization. We used WGCNA to construct and analyze seven gene expression datasets from several tissues of mouse recombinant inbred strains (RIS. For six out of the 7 networks, we found that linkage to module QTLs (mQTLs could be established for 29.3% of gene co-expression modules detected in the several mouse RIS. For about 74.6% of such genetically-linked modules, the mQTL was on the same chromosome as the one contributing most genes to the module, with genes originating from that chromosome showing higher connectivity than other genes in the modules. Such modules (that we considered as genetically-driven had network statistic properties (density, centralization and heterogeneity that set them apart from other modules in the network. Altogether, a sizeable portion of gene co-expression modules detected in mouse RIS panels had genetic determinants as their main organizing principle. In addition to providing a biologic interpretation validation for these modules, these genetic determinants imparted on them particular properties that set them apart from other modules in the network, to the point that they can be predicted to a large extent on the basis of their network statistics.

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

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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

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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

Oct4 targets regulatory nodes to modulate stem cell function.

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Pearl A Campbell

2007-06-01

Full Text Available Stem cells are characterized by two defining features, the ability to self-renew and to differentiate into highly specialized cell types. The POU homeodomain transcription factor Oct4 (Pou5f1 is an essential mediator of the embryonic stem cell state and has been implicated in lineage specific differentiation, adult stem cell identity, and cancer. Recent description of the regulatory networks which maintain 'ES' have highlighted a dual role for Oct4 in the transcriptional activation of genes required to maintain self-renewal and pluripotency while concomitantly repressing genes which facilitate lineage specific differentiation. However, the molecular mechanism by which Oct4 mediates differential activation or repression at these loci to either maintain stem cell identity or facilitate the emergence of alternate transcriptional programs required for the realization of lineage remains to be elucidated. To further investigate Oct4 function, we employed gene expression profiling together with a robust statistical analysis to identify genes highly correlated to Oct4. Gene Ontology analysis to categorize overrepresented genes has led to the identification of themes which may prove essential to stem cell identity, including chromatin structure, nuclear architecture, cell cycle control, DNA repair, and apoptosis. Our experiments have identified previously unappreciated roles for Oct4 for firstly, regulating chromatin structure in a state consistent with self-renewal and pluripotency, and secondly, facilitating the expression of genes that keeps the cell poised to respond to cues that lead to differentiation. Together, these data define the mechanism by which Oct4 orchestrates cellular regulatory pathways to enforce the stem cell state and provides important insight into stem cell function and cancer.

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

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

2007-08-01

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

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

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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.

Identifying modules of coexpressed transcript units and their organization of Saccharopolyspora erythraea from time series gene expression profiles.

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Xiao Chang

Full Text Available BACKGROUND: The Saccharopolyspora erythraea genome sequence was released in 2007. In order to look at the gene regulations at whole transcriptome level, an expression microarray was specifically designed on the S. erythraea strain NRRL 2338 genome sequence. Based on these data, we set out to investigate the potential transcriptional regulatory networks and their organization. METHODOLOGY/PRINCIPAL FINDINGS: In view of the hierarchical structure of bacterial transcriptional regulation, we constructed a hierarchical coexpression network at whole transcriptome level. A total of 27 modules were identified from 1255 differentially expressed transcript units (TUs across time course, which were further classified in to four groups. Functional enrichment analysis indicated the biological significance of our hierarchical network. It was indicated that primary metabolism is activated in the first rapid growth phase (phase A, and secondary metabolism is induced when the growth is slowed down (phase B. Among the 27 modules, two are highly correlated to erythromycin production. One contains all genes in the erythromycin-biosynthetic (ery gene cluster and the other seems to be associated with erythromycin production by sharing common intermediate metabolites. Non-concomitant correlation between production and expression regulation was observed. Especially, by calculating the partial correlation coefficients and building the network based on Gaussian graphical model, intrinsic associations between modules were found, and the association between those two erythromycin production-correlated modules was included as expected. CONCLUSIONS: This work created a hierarchical model clustering transcriptome data into coordinated modules, and modules into groups across the time course, giving insight into the concerted transcriptional regulations especially the regulation corresponding to erythromycin production of S. erythraea. This strategy may be extendable to studies

Identifying modules of coexpressed transcript units and their organization of Saccharopolyspora erythraea from time series gene expression profiles.

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Chang, Xiao; Liu, Shuai; Yu, Yong-Tao; Li, Yi-Xue; Li, Yuan-Yuan

2010-08-12

The Saccharopolyspora erythraea genome sequence was released in 2007. In order to look at the gene regulations at whole transcriptome level, an expression microarray was specifically designed on the S. erythraea strain NRRL 2338 genome sequence. Based on these data, we set out to investigate the potential transcriptional regulatory networks and their organization. In view of the hierarchical structure of bacterial transcriptional regulation, we constructed a hierarchical coexpression network at whole transcriptome level. A total of 27 modules were identified from 1255 differentially expressed transcript units (TUs) across time course, which were further classified in to four groups. Functional enrichment analysis indicated the biological significance of our hierarchical network. It was indicated that primary metabolism is activated in the first rapid growth phase (phase A), and secondary metabolism is induced when the growth is slowed down (phase B). Among the 27 modules, two are highly correlated to erythromycin production. One contains all genes in the erythromycin-biosynthetic (ery) gene cluster and the other seems to be associated with erythromycin production by sharing common intermediate metabolites. Non-concomitant correlation between production and expression regulation was observed. Especially, by calculating the partial correlation coefficients and building the network based on Gaussian graphical model, intrinsic associations between modules were found, and the association between those two erythromycin production-correlated modules was included as expected. This work created a hierarchical model clustering transcriptome data into coordinated modules, and modules into groups across the time course, giving insight into the concerted transcriptional regulations especially the regulation corresponding to erythromycin production of S. erythraea. This strategy may be extendable to studies on other prokaryotic microorganisms.

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.

Combinatorial binding leads to diverse regulatory responses: Lmd is a tissue-specific modulator of Mef2 activity.

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Paulo M F Cunha

2010-07-01

Full Text Available Understanding how complex patterns of temporal and spatial expression are regulated is central to deciphering genetic programs that drive development. Gene expression is initiated through the action of transcription factors and their cofactors converging on enhancer elements leading to a defined activity. Specific constellations of combinatorial occupancy are therefore often conceptualized as rigid binding codes that give rise to a common output of spatio-temporal expression. Here, we assessed this assumption using the regulatory input of two essential transcription factors within the Drosophila myogenic network. Mutations in either Myocyte enhancing factor 2 (Mef2 or the zinc-finger transcription factor lame duck (lmd lead to very similar defects in myoblast fusion, yet the underlying molecular mechanism for this shared phenotype is not understood. Using a combination of ChIP-on-chip analysis and expression profiling of loss-of-function mutants, we obtained a global view of the regulatory input of both factors during development. The majority of Lmd-bound enhancers are co-bound by Mef2, representing a subset of Mef2's transcriptional input during these stages of development. Systematic analyses of the regulatory contribution of both factors demonstrate diverse regulatory roles, despite their co-occupancy of shared enhancer elements. These results indicate that Lmd is a tissue-specific modulator of Mef2 activity, acting as both a transcriptional activator and repressor, which has important implications for myogenesis. More generally, this study demonstrates considerable flexibility in the regulatory output of two factors, leading to additive, cooperative, and repressive modes of co-regulation.

Singular Perturbation Analysis and Gene Regulatory Networks with Delay

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Shlykova, Irina; Ponosov, Arcady

2009-09-01

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

The capacity for multistability in small gene regulatory networks

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Grotewold Erich

2009-09-01

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

Gene Module Identification from Microarray Data Using Nonnegative Independent Component Analysis

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Ting Gong

2007-01-01

Full Text Available Genes mostly interact with each other to form transcriptional modules for performing single or multiple functions. It is important to unravel such transcriptional modules and to determine how disturbances in them may lead to disease. Here, we propose a non-negative independent component analysis (nICA approach for transcriptional module discovery. nICA method utilizes the non-negativity constraint to enforce the independence of biological processes within the participated genes. In such, nICA decomposes the observed gene expression into positive independent components, which fi ts better to the reality of corresponding putative biological processes. In conjunction with nICA modeling, visual statistical data analyzer (VISDA is applied to group genes into modules in latent variable space. We demonstrate the usefulness of the approach through the identification of composite modules from yeast data and the discovery of pathway modules in muscle regeneration.

Tissue-specific expression of aryl hydrocarbon receptor and putative developmental regulatory modules in Baltic salmon yolk-sac fry

Energy Technology Data Exchange (ETDEWEB)

Vuori, Kristiina A. [Centre of Excellence in Evolutionary Genetics and Physiology, Department of Biology, University of Turku, FI-20014 Turku (Finland)], E-mail: kristiina.vuori@utu.fi; Nordlund, Eija [Department of Information Technology, University of Turku, and Turku Centre for Computer Science (TUCS), FI-20014 Turku (Finland); Kallio, Jenny [Centre of Excellence in Evolutionary Genetics and Physiology, Department of Biology, University of Turku, FI-20014 Turku (Finland); Salakoski, Tapio [Department of Information Technology, University of Turku, and Turku Centre for Computer Science (TUCS), FI-20014 Turku (Finland); Nikinmaa, Mikko [Centre of Excellence in Evolutionary Genetics and Physiology, Department of Biology, University of Turku, FI-20014 Turku (Finland)

2008-04-08

The aryl hydrocarbon receptor (AhR) is an ancient protein that is conserved in vertebrates and invertebrates, indicating its important function throughout evolution. AhR has been studied largely because of its role in toxicology-gene expression via AhR is induced by many aromatic hydrocarbons in mammals. Recently, however, it has become clear that AhR is involved in various aspects of development such as cell proliferation and differentiation, and cell motility and migration. The mechanisms by which AhR regulates these various functions remain poorly understood. Across-species comparative studies of AhR in invertebrates, non-mammalian vertebrates and mammals may help to reveal the multiple functions of AhR. Here, we have studied AhR during larval development of Baltic salmon (Salmon salar). Our results indicate that AhR protein is expressed in nervous system, liver and muscle tissues. We also present putative regulatory modules and module-matching genes, produced by chromatin immunoprecipitation (ChIP) cloning and in silico analysis, which may be associated with evolutionarily conserved functions of AhR during development. For example, the module NFKB-AHRR-CREB found from salmon ChIP sequences is present in human ULK3 (regulating formation of granule cell axons in mouse and axon outgrowth in Caernohabditis elegans) and SRGAP1 (GTPase-activating protein involved in the Slit/Robo pathway) promoters. We suggest that AhR may have an evolutionarily conserved role in neuronal development and nerve cell targeting, and in Wnt signaling pathway.

Tissue-specific expression of aryl hydrocarbon receptor and putative developmental regulatory modules in Baltic salmon yolk-sac fry

International Nuclear Information System (INIS)

Vuori, Kristiina A.; Nordlund, Eija; Kallio, Jenny; Salakoski, Tapio; Nikinmaa, Mikko

2008-01-01

The aryl hydrocarbon receptor (AhR) is an ancient protein that is conserved in vertebrates and invertebrates, indicating its important function throughout evolution. AhR has been studied largely because of its role in toxicology-gene expression via AhR is induced by many aromatic hydrocarbons in mammals. Recently, however, it has become clear that AhR is involved in various aspects of development such as cell proliferation and differentiation, and cell motility and migration. The mechanisms by which AhR regulates these various functions remain poorly understood. Across-species comparative studies of AhR in invertebrates, non-mammalian vertebrates and mammals may help to reveal the multiple functions of AhR. Here, we have studied AhR during larval development of Baltic salmon (Salmon salar). Our results indicate that AhR protein is expressed in nervous system, liver and muscle tissues. We also present putative regulatory modules and module-matching genes, produced by chromatin immunoprecipitation (ChIP) cloning and in silico analysis, which may be associated with evolutionarily conserved functions of AhR during development. For example, the module NFKB-AHRR-CREB found from salmon ChIP sequences is present in human ULK3 (regulating formation of granule cell axons in mouse and axon outgrowth in Caernohabditis elegans) and SRGAP1 (GTPase-activating protein involved in the Slit/Robo pathway) promoters. We suggest that AhR may have an evolutionarily conserved role in neuronal development and nerve cell targeting, and in Wnt signaling pathway

Computational exploration of cis-regulatory modules in rhythmic expression data using the "Exploration of Distinctive CREs and CRMs" (EDCC) and "CRM Network Generator" (CNG) programs.

Science.gov (United States)

Bekiaris, Pavlos Stephanos; Tekath, Tobias; Staiger, Dorothee; Danisman, Selahattin

2018-01-01

Understanding the effect of cis-regulatory elements (CRE) and clusters of CREs, which are called cis-regulatory modules (CRM), in eukaryotic gene expression is a challenge of computational biology. We developed two programs that allow simple, fast and reliable analysis of candidate CREs and CRMs that may affect specific gene expression and that determine positional features between individual CREs within a CRM. The first program, "Exploration of Distinctive CREs and CRMs" (EDCC), correlates candidate CREs and CRMs with specific gene expression patterns. For pairs of CREs, EDCC also determines positional preferences of the single CREs in relation to each other and to the transcriptional start site. The second program, "CRM Network Generator" (CNG), prioritizes these positional preferences using a neural network and thus allows unbiased rating of the positional preferences that were determined by EDCC. We tested these programs with data from a microarray study of circadian gene expression in Arabidopsis thaliana. Analyzing more than 1.5 million pairwise CRE combinations, we found 22 candidate combinations, of which several contained known clock promoter elements together with elements that had not been identified as relevant to circadian gene expression before. CNG analysis further identified positional preferences of these CRE pairs, hinting at positional information that may be relevant for circadian gene expression. Future wet lab experiments will have to determine which of these combinations confer daytime specific circadian gene expression.

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

Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules

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Ettore Mosca

2017-09-01

Full Text Available Autism spectrum disorder (ASD is marked by a strong genetic heterogeneity, which is underlined by the low overlap between ASD risk gene lists proposed in different studies. In this context, molecular networks can be used to analyze the results of several genome-wide studies in order to underline those network regions harboring genetic variations associated with ASD, the so-called “disease modules.” In this work, we used a recent network diffusion-based approach to jointly analyze multiple ASD risk gene lists. We defined genome-scale prioritizations of human genes in relation to ASD genes from multiple studies, found significantly connected gene modules associated with ASD and predicted genes functionally related to ASD risk genes. Most of them play a role in synapsis and neuronal development and function; many are related to syndromes that can be in comorbidity with ASD and the remaining are involved in epigenetics, cell cycle, cell adhesion and cancer.

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

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Nadiatul Akmal Mohd-Radzman

2013-10-01

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

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

Science.gov (United States)

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

2013-10-01

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

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

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Xiaobo Guo

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

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

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Frank Emmert-Streib

2013-02-01

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

Modeling genome-wide dynamic regulatory network in mouse lungs with influenza infection using high-dimensional ordinary differential equations.

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Wu, Shuang; Liu, Zhi-Ping; Qiu, Xing; Wu, Hulin

2014-01-01

The immune response to viral infection is regulated by an intricate network of many genes and their products. The reverse engineering of gene regulatory networks (GRNs) using mathematical models from time course gene expression data collected after influenza infection is key to our understanding of the mechanisms involved in controlling influenza infection within a host. A five-step pipeline: detection of temporally differentially expressed genes, clustering genes into co-expressed modules, identification of network structure, parameter estimate refinement, and functional enrichment analysis, is developed for reconstructing high-dimensional dynamic GRNs from genome-wide time course gene expression data. Applying the pipeline to the time course gene expression data from influenza-infected mouse lungs, we have identified 20 distinct temporal expression patterns in the differentially expressed genes and constructed a module-based dynamic network using a linear ODE model. Both intra-module and inter-module annotations and regulatory relationships of our inferred network show some interesting findings and are highly consistent with existing knowledge about the immune response in mice after influenza infection. The proposed method is a computationally efficient, data-driven pipeline bridging experimental data, mathematical modeling, and statistical analysis. The application to the influenza infection data elucidates the potentials of our pipeline in providing valuable insights into systematic modeling of complicated biological processes.

Novel sequence variations in LAMA2 and SGCG genes modulating cis-acting regulatory elements and RNA secondary structure

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Olfa Siala

2010-01-01

Full Text Available In this study, we detected new sequence variations in LAMA2 and SGCG genes in 5 ethnic populations, and analysed their effect on enhancer composition and mRNA structure. PCR amplification and DNA sequencing were performed and followed by bioinformatics analyses using ESEfinder as well as MFOLD software. We found 3 novel sequence variations in the LAMA2 (c.3174+22_23insAT and c.6085 +12delA and SGCG (c.*102A/C genes. These variations were present in 210 tested healthy controls from Tunisian, Moroccan, Algerian, Lebanese and French populations suggesting that they represent novel polymorphisms within LAMA2 and SGCG genes sequences. ESEfinder showed that the c.*102A/C substitution created a new exon splicing enhancer in the 3'UTR of SGCG genes, whereas the c.6085 +12delA deletion was situated in the base pairing region between LAMA2 mRNA and the U1snRNA spliceosomal components. The RNA structure analyses showed that both variations modulated RNA secondary structure. Our results are suggestive of correlations between mRNA folding and the recruitment of spliceosomal components mediating splicing, including SR proteins. The contribution of common sequence variations to mRNA structural and functional diversity will contribute to a better study of gene expression.

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...

DREAM (Downstream Regulatory Element Antagonist Modulator contributes to synaptic depression and contextual fear memory

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Wu Long-Jun

2010-01-01

Full Text Available Abstract The downstream regulatory element antagonist modulator (DREAM, a multifunctional Ca2+-binding protein, binds specifically to DNA and several nucleoproteins regulating gene expression and with proteins outside the nucleus to regulate membrane excitability or calcium homeostasis. DREAM is highly expressed in the central nervous system including the hippocampus and cortex; however, the roles of DREAM in hippocampal synaptic transmission and plasticity have not been investigated. Taking advantage of transgenic mice overexpressing a Ca2+-insensitive DREAM mutant (TgDREAM, we used integrative methods including electrophysiology, biochemistry, immunostaining, and behavior tests to study the function of DREAM in synaptic transmission, long-term plasticity and fear memory in hippocampal CA1 region. We found that NMDA receptor but not AMPA receptor-mediated current was decreased in TgDREAM mice. Moreover, synaptic plasticity, such as long-term depression (LTD but not long-term potentiation (LTP, was impaired in TgDREAM mice. Biochemical experiments found that DREAM interacts with PSD-95 and may inhibit NMDA receptor function through this interaction. Contextual fear memory was significantly impaired in TgDREAM mice. By contrast, sensory responses to noxious stimuli were not affected. Our results demonstrate that DREAM plays a novel role in postsynaptic modulation of the NMDA receptor, and contributes to synaptic plasticity and behavioral memory.

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.

Science.gov (United States)

Altay, Gökmen; Emmert-Streib, Frank

2010-09-28

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

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

A novel proapoptotic gene PANO encodes a post-translational modulator of the tumor suppressor p14ARF

Energy Technology Data Exchange (ETDEWEB)

Watari, Akihiro; Li, Yang; Higashiyama, Shinji; Yutsudo, Masuo, E-mail: yutsudo@biken.osaka-u.ac.jp

2012-02-01

The protein p14ARF is a known tumor suppressor protein controlling cell proliferation and survival, which mainly localizes in nucleoli. However, the regulatory mechanisms that govern its activity or expression remain unclear. Here, we report that a novel proapoptotic nucleolar protein, PANO, modulates the expression and activity of p14ARF in HeLa cells. Overexpression of PANO enhances the stability of p14ARF protein by protecting it from degradation, resulting in an increase in p14ARF expression levels. Overexpression of PANO also induces apoptosis under low serum conditions. This effect is dependent on the nucleolar localization of PANO and inhibited by knocking-down p14ARF. Alternatively, PANO siRNA treated cells exhibit a reduction in p14ARF protein levels. In addition, ectopic expression of PANO suppresses the tumorigenicity of HeLa cells in nude mice. These results indicate that PANO is a new apoptosis-inducing gene by modulating the tumor suppressor protein, p14ARF, and may itself be a new candidate tumor suppressor gene.

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.

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...

Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.

Science.gov (United States)

Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P

2013-03-21

Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group

Meta-analysis of peripheral blood gene expression modules for COPD phenotypes.

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Dominik Reinhold

Full Text Available Chronic obstructive pulmonary disease (COPD occurs typically in current or former smokers, but only a minority of people with smoking history develops the disease. Besides environmental factors, genetics is an important risk factor for COPD. However, the relationship between genetics, environment and phenotypes is not well understood. Sample sizes for genome-wide expression studies based on lung tissue have been small due to the invasive nature of sample collection. Increasing evidence for the systemic nature of the disease makes blood a good alternative source to study the disease, but there have also been few large-scale blood genomic studies in COPD. Due to the complexity and heterogeneity of COPD, examining groups of interacting genes may have more relevance than identifying individual genes. Therefore, we used Weighted Gene Co-expression Network Analysis to find groups of genes (modules that are highly connected. However, module definitions may vary between individual data sets. To alleviate this problem, we used a consensus module definition based on two cohorts, COPDGene and ECLIPSE. We studied the relationship between the consensus modules and COPD phenotypes airflow obstruction and emphysema. We also used these consensus module definitions on an independent cohort (TESRA and performed a meta analysis involving all data sets. We found several modules that are associated with COPD phenotypes, are enriched in functional categories and are overrepresented for cell-type specific genes. Of the 14 consensus modules, three were strongly associated with airflow obstruction (meta p ≤ 0.0002, and two had some association with emphysema (meta p ≤ 0.06; some associations were stronger in the case-control cohorts, and others in the cases-only subcohorts. Gene Ontology terms that were overrepresented included "immune response" and "defense response." The cell types whose type-specific genes were overrepresented in modules (p < 0.05 included

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

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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).

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

REDfly: a Regulatory Element Database for Drosophila.

Science.gov (United States)

Gallo, Steven M; Li, Long; Hu, Zihua; Halfon, Marc S

2006-02-01

Bioinformatics studies of transcriptional regulation in the metazoa are significantly hindered by the absence of readily available data on large numbers of transcriptional cis-regulatory modules (CRMs). Even the richly annotated Drosophila melanogaster genome lacks extensive CRM information. We therefore present here a database of Drosophila CRMs curated from the literature complete with both DNA sequence and a searchable description of the gene expression pattern regulated by each CRM. This resource should greatly facilitate the development of computational approaches to CRM discovery as well as bioinformatics analyses of regulatory sequence properties and evolution.

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

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Meier, Daniel; Schindler, Detlev

2011-01-01

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

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

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.

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

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

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

Genes and Social Behavior

OpenAIRE

Robinson, Gene E.; Fernald, Russell D.; Clayton, David F.

2008-01-01

What specific genes and regulatory sequences contribute to the organization and functioning of brain circuits that support social behavior? How does social experience interact with information in the genome to modulate these brain circuits? Here we address these questions by highlighting progress that has been made in identifying and understanding two key “vectors of influence” that link genes, brain, and social behavior: 1) social information alters gene readout in the brain to influence beh...

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

Using hexamers to predict cis-regulatory motifs in Drosophila

Directory of Open Access Journals (Sweden)

Kibler Dennis

2005-10-01

Full Text Available Abstract Background Cis-regulatory modules (CRMs are short stretches of DNA that help regulate gene expression in higher eukaryotes. They have been found up to 1 megabase away from the genes they regulate and can be located upstream, downstream, and even within their target genes. Due to the difficulty of finding CRMs using biological and computational techniques, even well-studied regulatory systems may contain CRMs that have not yet been discovered. Results We present a simple, efficient method (HexDiff based only on hexamer frequencies of known CRMs and non-CRM sequence to predict novel CRMs in regulatory systems. On a data set of 16 gap and pair-rule genes containing 52 known CRMs, predictions made by HexDiff had a higher correlation with the known CRMs than several existing CRM prediction algorithms: Ahab, Cluster Buster, MSCAN, MCAST, and LWF. After combining the results of the different algorithms, 10 putative CRMs were identified and are strong candidates for future study. The hexamers used by HexDiff to distinguish between CRMs and non-CRM sequence were also analyzed and were shown to be enriched in regulatory elements. Conclusion HexDiff provides an efficient and effective means for finding new CRMs based on known CRMs, rather than known binding sites.

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

Directory of Open Access Journals (Sweden)

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.

Science.gov (United States)

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.

Science.gov (United States)

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.

Science.gov (United States)

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.

Functional Module Analysis for Gene Coexpression Networks with Network Integration.

Science.gov (United States)

Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

2015-01-01

Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

Dynamic and modular gene regulatory networks drive the development of gametogenesis.

Science.gov (United States)

Che, Dongxue; Wang, Yang; Bai, Weiyang; Li, Leijie; Liu, Guiyou; Zhang, Liangcai; Zuo, Yongchun; Tao, Shiheng; Hua, Jinlian; Liao, Mingzhi

2017-07-01

Gametogenesis is a complex process, which includes mitosis and meiosis and results in the production of ovum and sperm. The development of gametogenesis is dynamic and needs many different genes to work synergistically, but it is lack of global perspective research about this process. In this study, we detected the dynamic process of gametogenesis from the perspective of systems biology based on protein-protein interaction networks (PPINs) and functional analysis. Results showed that gametogenesis genes have strong synergistic effects in PPINs within and between different phases during the development. Addition to the synergistic effects on molecular networks, gametogenesis genes showed functional consistency within and between different phases, which provides the further evidence about the dynamic process during the development of gametogenesis. At last, we detected and provided the core molecular modules of different phases about gametogenesis. The gametogenesis genes and related modules can be obtained from our Web site Gametogenesis Molecule Online (GMO, http://gametsonline.nwsuaflmz.com/index.php), which is freely accessible. GMO may be helpful for the reference and application of these genes and modules in the future identification of key genes about gametogenesis. Summary, this work provided a computational perspective and frame to the analysis of the gametogenesis dynamics and modularity in both human and mouse. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

Science.gov (United States)

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

Genomewide analyses of pathogenic and regulatory T cells of NOD ...

Indian Academy of Sciences (India)

Reestablishing a well-balanced population of regulatory T cells (Tregs) and pathogenic T cells (Tpaths) is necessary for diabetic patients to regain glucose control. However, the molecular mechanisms modulating functional differentiation of Tpaths and Tregs remain unclear. In this study, we anal- ysed the gene expression ...

Differential Gene Expression and Aging

Directory of Open Access Journals (Sweden)

Laurent Seroude

2002-01-01

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

CHIR99021 promotes self-renewal of mouse embryonic stem cells by modulation of protein-encoding gene and long intergenic non-coding RNA expression

Energy Technology Data Exchange (ETDEWEB)

Wu, Yongyan [College of Veterinary Medicine, Northwest A and F University, Yangling 712100, Shaanxi (China); Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); Ai, Zhiying [Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); College of Life Sciences, Northwest A and F University, Yangling 712100, Shaanxi (China); Yao, Kezhen [College of Veterinary Medicine, Northwest A and F University, Yangling 712100, Shaanxi (China); Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); Cao, Lixia; Du, Juan; Shi, Xiaoyan [Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); College of Life Sciences, Northwest A and F University, Yangling 712100, Shaanxi (China); Guo, Zekun, E-mail: gzk@nwsuaf.edu.cn [College of Veterinary Medicine, Northwest A and F University, Yangling 712100, Shaanxi (China); Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); Zhang, Yong, E-mail: zhylab@hotmail.com [College of Veterinary Medicine, Northwest A and F University, Yangling 712100, Shaanxi (China); Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China)

2013-10-15

Embryonic stem cells (ESCs) can proliferate indefinitely in vitro and differentiate into cells of all three germ layers. These unique properties make them exceptionally valuable for drug discovery and regenerative medicine. However, the practical application of ESCs is limited because it is difficult to derive and culture ESCs. It has been demonstrated that CHIR99021 (CHIR) promotes self-renewal and enhances the derivation efficiency of mouse (m)ESCs. However, the downstream targets of CHIR are not fully understood. In this study, we identified CHIR-regulated genes in mESCs using microarray analysis. Our microarray data demonstrated that CHIR not only influenced the Wnt/β-catenin pathway by stabilizing β-catenin, but also modulated several other pluripotency-related signaling pathways such as TGF-β, Notch and MAPK signaling pathways. More detailed analysis demonstrated that CHIR inhibited Nodal signaling, while activating bone morphogenetic protein signaling in mESCs. In addition, we found that pluripotency-maintaining transcription factors were up-regulated by CHIR, while several developmental-related genes were down-regulated. Furthermore, we found that CHIR altered the expression of epigenetic regulatory genes and long intergenic non-coding RNAs. Quantitative real-time PCR results were consistent with microarray data, suggesting that CHIR alters the expression pattern of protein-encoding genes (especially transcription factors), epigenetic regulatory genes and non-coding RNAs to establish a relatively stable pluripotency-maintaining network. - Highlights: • Combined use of CHIR with LIF promotes self-renewal of J1 mESCs. • CHIR-regulated genes are involved in multiple pathways. • CHIR inhibits Nodal signaling and promotes Bmp4 expression to activate BMP signaling. • Expression of epigenetic regulatory genes and lincRNAs is altered by CHIR.

CHIR99021 promotes self-renewal of mouse embryonic stem cells by modulation of protein-encoding gene and long intergenic non-coding RNA expression

International Nuclear Information System (INIS)

Wu, Yongyan; Ai, Zhiying; Yao, Kezhen; Cao, Lixia; Du, Juan; Shi, Xiaoyan; Guo, Zekun; Zhang, Yong

2013-01-01

Embryonic stem cells (ESCs) can proliferate indefinitely in vitro and differentiate into cells of all three germ layers. These unique properties make them exceptionally valuable for drug discovery and regenerative medicine. However, the practical application of ESCs is limited because it is difficult to derive and culture ESCs. It has been demonstrated that CHIR99021 (CHIR) promotes self-renewal and enhances the derivation efficiency of mouse (m)ESCs. However, the downstream targets of CHIR are not fully understood. In this study, we identified CHIR-regulated genes in mESCs using microarray analysis. Our microarray data demonstrated that CHIR not only influenced the Wnt/β-catenin pathway by stabilizing β-catenin, but also modulated several other pluripotency-related signaling pathways such as TGF-β, Notch and MAPK signaling pathways. More detailed analysis demonstrated that CHIR inhibited Nodal signaling, while activating bone morphogenetic protein signaling in mESCs. In addition, we found that pluripotency-maintaining transcription factors were up-regulated by CHIR, while several developmental-related genes were down-regulated. Furthermore, we found that CHIR altered the expression of epigenetic regulatory genes and long intergenic non-coding RNAs. Quantitative real-time PCR results were consistent with microarray data, suggesting that CHIR alters the expression pattern of protein-encoding genes (especially transcription factors), epigenetic regulatory genes and non-coding RNAs to establish a relatively stable pluripotency-maintaining network. - Highlights: • Combined use of CHIR with LIF promotes self-renewal of J1 mESCs. • CHIR-regulated genes are involved in multiple pathways. • CHIR inhibits Nodal signaling and promotes Bmp4 expression to activate BMP signaling. • Expression of epigenetic regulatory genes and lincRNAs is altered by CHIR

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

Science.gov (United States)

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 ...

THD-Module Extractor: An Application for CEN Module Extraction and Interesting Gene Identification for Alzheimer's Disease.

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Kakati, Tulika; Kashyap, Hirak; Bhattacharyya, Dhruba K

2016-11-30

There exist many tools and methods for construction of co-expression network from gene expression data and for extraction of densely connected gene modules. In this paper, a method is introduced to construct co-expression network and to extract co-expressed modules having high biological significance. The proposed method has been validated on several well known microarray datasets extracted from a diverse set of species, using statistical measures, such as p and q values. The modules obtained in these studies are found to be biologically significant based on Gene Ontology enrichment analysis, pathway analysis, and KEGG enrichment analysis. Further, the method was applied on an Alzheimer's disease dataset and some interesting genes are found, which have high semantic similarity among them, but are not significantly correlated in terms of expression similarity. Some of these interesting genes, such as MAPT, CASP2, and PSEN2, are linked with important aspects of Alzheimer's disease, such as dementia, increase cell death, and deposition of amyloid-beta proteins in Alzheimer's disease brains. The biological pathways associated with Alzheimer's disease, such as, Wnt signaling, Apoptosis, p53 signaling, and Notch signaling, incorporate these interesting genes. The proposed method is evaluated in regard to existing literature.

The Evolution of the Secreted Regulatory Protein Progranulin.

Science.gov (United States)

Palfree, Roger G E; Bennett, Hugh P J; Bateman, Andrew

2015-01-01

Progranulin is a secreted growth factor that is active in tumorigenesis, wound repair, and inflammation. Haploinsufficiency of the human progranulin gene, GRN, causes frontotemporal dementia. Progranulins are composed of chains of cysteine-rich granulin modules. Modules may be released from progranulin by proteolysis as 6kDa granulin polypeptides. Both intact progranulin and some of the granulin polypeptides are biologically active. The granulin module occurs in certain plant proteases and progranulins are present in early diverging metazoan clades such as the sponges, indicating their ancient evolutionary origin. There is only one Grn gene in mammalian genomes. More gene-rich Grn families occur in teleost fish with between 3 and 6 members per species including short-form Grns that have no tetrapod counterparts. Our goals are to elucidate progranulin and granulin module evolution by investigating (i): the origins of metazoan progranulins (ii): the evolutionary relationships between the single Grn of tetrapods and the multiple Grn genes of fish (iii): the evolution of granulin module architectures of vertebrate progranulins (iv): the conservation of mammalian granulin polypeptide sequences and how the conserved granulin amino acid sequences map to the known three dimensional structures of granulin modules. We report that progranulin-like proteins are present in unicellular eukaryotes that are closely related to metazoa suggesting that progranulin is among the earliest extracellular regulatory proteins still employed by multicellular animals. From the genomes of the elephant shark and coelacanth we identified contemporary representatives of a precursor for short-from Grn genes of ray-finned fish that is lost in tetrapods. In vertebrate Grns pathways of exon duplication resulted in a conserved module architecture at the amino-terminus that is frequently accompanied by an unusual pattern of tandem nearly identical module repeats near the carboxyl-terminus. Polypeptide

Resistin enhances the expansion of regulatory T cells through modulation of dendritic cells

Directory of Open Access Journals (Sweden)

Han Seung

2010-06-01

Full Text Available Abstract Background Resistin, a member of adipokine family, is known to be involved in the modulation of immune responses including inflammatory activity. Interestingly, resistin is secreted by adipocytes in mice and rats whereas it is secreted by leukocytes in humans. However, the mechanism behind the effect of resistin on the expansion of regulatory T cells (Tregs remains poorly understood. Therefore, we examined regulatory effect of resistin on the induction and cellular modification of Tregs. Results Both protein and mRNA expression of FoxP3, a representative marker of Tregs, increased in a dose-dependent manner when peripheral blood mononuclear cells were treated with resistin. At the same time, resistin had no direct effect on the induction of FoxP3 in CD4+ T cells, suggesting an indirect role through other cells type(s. Since DCs are an important player in the differentiation of T cells, we focused on the role of DCs in the modulation of Tregs by resistin. Resistin suppressed the expression of interferon regulatory factor (IRF-1 and its target cytokines, IL-6, IL-23p19 and IL-12p40, in DCs. Furthermore, FoxP3 expression is increased in CD4+ T cells when co-cultured with DCs and concomitantly treated with resistin. Conclusion Our results suggest that resistin induces expansion of functional Tregs only when co-cultured with DCs.

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.

Science.gov (United States)

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.

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

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

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

2012-01-01

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

The dynamic landscape of gene regulation during Bombyx mori oogenesis.

Science.gov (United States)

Zhang, Qiang; Sun, Wei; Sun, Bang-Yong; Xiao, Yang; Zhang, Ze

2017-09-11

Oogenesis in the domestic silkworm (Bombyx mori) is a complex process involving previtellogenesis, vitellogenesis and choriogenesis. During this process, follicles show drastic morphological and physiological changes. However, the genome-wide regulatory profiles of gene expression during oogenesis remain to be determined. In this study, we obtained time-series transcriptome data and used these data to reveal the dynamic landscape of gene regulation during oogenesis. A total of 1932 genes were identified to be differentially expressed among different stages, most of which occurred during the transition from late vitellogenesis to early choriogenesis. Using weighted gene co-expression network analysis, we identified six stage-specific gene modules that correspond to multiple regulatory pathways. Strikingly, the biosynthesis pathway of the molting hormone 20-hydroxyecdysone (20E) was enriched in one of the modules. Further analysis showed that the ecdysteroid 20-hydroxylase gene (CYP314A1) of steroidgenesis genes was mainly expressed in previtellogenesis and early vitellogenesis. However, the 20E-inactivated genes, particularly the ecdysteroid 26-hydroxylase encoding gene (Cyp18a1), were highly expressed in late vitellogenesis. These distinct expression patterns between 20E synthesis and catabolism-related genes might ensure the rapid decline of the hormone titer at the transition point from vitellogenesis to choriogenesis. In addition, we compared landscapes of gene regulation between silkworm (Lepidoptera) and fruit fly (Diptera) oogeneses. Our results show that there is some consensus in the modules of gene co-expression during oogenesis in these insects. The data presented in this study provide new insights into the regulatory mechanisms underlying oogenesis in insects with polytrophic meroistic ovaries. The results also provide clues for further investigating the roles of epigenetic reconfiguration and circadian rhythm in insect oogenesis.

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

Science.gov (United States)

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.

Shared regulatory sites are abundant in the human genome and shed light on genome evolution and disease pleiotropy.

Science.gov (United States)

Tong, Pin; Monahan, Jack; Prendergast, James G D

2017-03-01

Large-scale gene expression datasets are providing an increasing understanding of the location of cis-eQTLs in the human genome and their role in disease. However, little is currently known regarding the extent of regulatory site-sharing between genes. This is despite it having potentially wide-ranging implications, from the determination of the way in which genetic variants may shape multiple phenotypes to the understanding of the evolution of human gene order. By first identifying the location of non-redundant cis-eQTLs, we show that regulatory site-sharing is a relatively common phenomenon in the human genome, with over 10% of non-redundant regulatory variants linked to the expression of multiple nearby genes. We show that these shared, local regulatory sites are linked to high levels of chromatin looping between the regulatory sites and their associated genes. In addition, these co-regulated gene modules are found to be strongly conserved across mammalian species, suggesting that shared regulatory sites have played an important role in shaping human gene order. The association of these shared cis-eQTLs with multiple genes means they also appear to be unusually important in understanding the genetics of human phenotypes and pleiotropy, with shared regulatory sites more often linked to multiple human phenotypes than other regulatory variants. This study shows that regulatory site-sharing is likely an underappreciated aspect of gene regulation and has important implications for the understanding of various biological phenomena, including how the two and three dimensional structures of the genome have been shaped and the potential causes of disease pleiotropy outside coding regions.

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.

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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

Human Intellectual Disability Genes Form Conserved Functional Modules in Drosophila

Science.gov (United States)

Oortveld, Merel A. W.; Keerthikumar, Shivakumar; Oti, Martin; Nijhof, Bonnie; Fernandes, Ana Clara; Kochinke, Korinna; Castells-Nobau, Anna; van Engelen, Eva; Ellenkamp, Thijs; Eshuis, Lilian; Galy, Anne; van Bokhoven, Hans; Habermann, Bianca; Brunner, Han G.; Zweier, Christiane; Verstreken, Patrik; Huynen, Martijn A.; Schenck, Annette

2013-01-01

Intellectual Disability (ID) disorders, defined by an IQ below 70, are genetically and phenotypically highly heterogeneous. Identification of common molecular pathways underlying these disorders is crucial for understanding the molecular basis of cognition and for the development of therapeutic intervention strategies. To systematically establish their functional connectivity, we used transgenic RNAi to target 270 ID gene orthologs in the Drosophila eye. Assessment of neuronal function in behavioral and electrophysiological assays and multiparametric morphological analysis identified phenotypes associated with knockdown of 180 ID gene orthologs. Most of these genotype-phenotype associations were novel. For example, we uncovered 16 genes that are required for basal neurotransmission and have not previously been implicated in this process in any system or organism. ID gene orthologs with morphological eye phenotypes, in contrast to genes without phenotypes, are relatively highly expressed in the human nervous system and are enriched for neuronal functions, suggesting that eye phenotyping can distinguish different classes of ID genes. Indeed, grouping genes by Drosophila phenotype uncovered 26 connected functional modules. Novel links between ID genes successfully predicted that MYCN, PIGV and UPF3B regulate synapse development. Drosophila phenotype groups show, in addition to ID, significant phenotypic similarity also in humans, indicating that functional modules are conserved. The combined data indicate that ID disorders, despite their extreme genetic diversity, are caused by disruption of a limited number of highly connected functional modules. PMID:24204314

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

Science.gov (United States)

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.

Computational integration of homolog and pathway gene module expression reveals general stemness signatures.

Directory of Open Access Journals (Sweden)

Martina Koeva

Full Text Available The stemness hypothesis states that all stem cells use common mechanisms to regulate self-renewal and multi-lineage potential. However, gene expression meta-analyses at the single gene level have failed to identify a significant number of genes selectively expressed by a broad range of stem cell types. We hypothesized that stemness may be regulated by modules of homologs. While the expression of any single gene within a module may vary from one stem cell type to the next, it is possible that the expression of the module as a whole is required so that the expression of different, yet functionally-synonymous, homologs is needed in different stem cells. Thus, we developed a computational method to test for stem cell-specific gene expression patterns from a comprehensive collection of 49 murine datasets covering 12 different stem cell types. We identified 40 individual genes and 224 stemness modules with reproducible and specific up-regulation across multiple stem cell types. The stemness modules included families regulating chromatin remodeling, DNA repair, and Wnt signaling. Strikingly, the majority of modules represent evolutionarily related homologs. Moreover, a score based on the discovered modules could accurately distinguish stem cell-like populations from other cell types in both normal and cancer tissues. This scoring system revealed that both mouse and human metastatic populations exhibit higher stemness indices than non-metastatic populations, providing further evidence for a stem cell-driven component underlying the transformation to metastatic disease.

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.

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.

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.

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

Selective constraints in experimentally defined primate regulatory regions.

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Daniel J Gaffney

2008-08-01

Full Text Available Changes in gene regulation may be important in evolution. However, the evolutionary properties of regulatory mutations are currently poorly understood. This is partly the result of an incomplete annotation of functional regulatory DNA in many species. For example, transcription factor binding sites (TFBSs, a major component of eukaryotic regulatory architecture, are typically short, degenerate, and therefore difficult to differentiate from randomly occurring, nonfunctional sequences. Furthermore, although sites such as TFBSs can be computationally predicted using evolutionary conservation as a criterion, estimates of the true level of selective constraint (defined as the fraction of strongly deleterious mutations occurring at a locus in regulatory regions will, by definition, be upwardly biased in datasets that are a priori evolutionarily conserved. Here we investigate the fitness effects of regulatory mutations using two complementary datasets of human TFBSs that are likely to be relatively free of ascertainment bias with respect to evolutionary conservation but, importantly, are supported by experimental data. The first is a collection of almost >2,100 human TFBSs drawn from the literature in the TRANSFAC database, and the second is derived from several recent high-throughput chromatin immunoprecipitation coupled with genomic microarray (ChIP-chip analyses. We also define a set of putative cis-regulatory modules (pCRMs by spatially clustering multiple TFBSs that regulate the same gene. We find that a relatively high proportion ( approximately 37% of mutations at TFBSs are strongly deleterious, similar to that at a 2-fold degenerate protein-coding site. However, constraint is significantly reduced in human and chimpanzee pCRMS and ChIP-chip sequences, relative to macaques. We estimate that the fraction of regulatory mutations that have been driven to fixation by positive selection in humans is not significantly different from zero. We also find

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.

Macrogenomic engineering via modulation of the scaling of chromatin packing density.

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Almassalha, Luay M; Bauer, Greta M; Wu, Wenli; Cherkezyan, Lusik; Zhang, Di; Kendra, Alexis; Gladstein, Scott; Chandler, John E; VanDerway, David; Seagle, Brandon-Luke L; Ugolkov, Andrey; Billadeau, Daniel D; O'Halloran, Thomas V; Mazar, Andrew P; Roy, Hemant K; Szleifer, Igal; Shahabi, Shohreh; Backman, Vadim

2017-11-01

Many human diseases result from the dysregulation of the complex interactions between tens to thousands of genes. However, approaches for the transcriptional modulation of many genes simultaneously in a predictive manner are lacking. Here, through the combination of simulations, systems modelling and in vitro experiments, we provide a physical regulatory framework based on chromatin packing-density heterogeneity for modulating the genomic information space. Because transcriptional interactions are essentially chemical reactions, they depend largely on the local physical nanoenvironment. We show that the regulation of the chromatin nanoenvironment allows for the predictable modulation of global patterns in gene expression. In particular, we show that the rational modulation of chromatin density fluctuations can lead to a decrease in global transcriptional activity and intercellular transcriptional heterogeneity in cancer cells during chemotherapeutic responses to achieve near-complete cancer cell killing in vitro. Our findings represent a 'macrogenomic engineering' approach to modulating the physical structure of chromatin for whole-scale transcriptional modulation.

Sterol regulatory element-binding proteins are regulators of the rat thyroid peroxidase gene in thyroid cells.

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Christine Rauer

Full Text Available Sterol regulatory element-binding proteins (SREBPs-1c and -2, which were initially discovered as master transcriptional regulators of lipid biosynthesis and uptake, were recently identified as novel transcriptional regulators of the sodium-iodide symporter gene in the thyroid, which is essential for thyroid hormone synthesis. Based on this observation that SREBPs play a role for thyroid hormone synthesis, we hypothesized that another gene involved in thyroid hormone synthesis, the thyroid peroxidase (TPO gene, is also a target of SREBP-1c and -2. Thyroid epithelial cells treated with 25-hydroxycholesterol, which is known to inhibit SREBP activation, had about 50% decreased mRNA levels of TPO. Similarly, the mRNA level of TPO was reduced by about 50% in response to siRNA mediated knockdown of both, SREBP-1 and SREBP-2. Reporter gene assays revealed that overexpression of active SREBP-1c and -2 causes a strong transcriptional activation of the rat TPO gene, which was localized to an approximately 80 bp region in the intron 1 of the rat TPO gene. In vitro- and in vivo-binding of both, SREBP-1c and SREBP-2, to this region in the rat TPO gene could be demonstrated using gel-shift assays and chromatin immunoprecipitation. Mutation analysis of the 80 bp region of rat TPO intron 1 revealed two isolated and two overlapping SREBP-binding elements from which one, the overlapping SRE+609/InvSRE+614, was shown to be functional in reporter gene assays. In connection with recent findings that the rat NIS gene is also a SREBP target gene in the thyroid, the present findings suggest that SREBPs may be possible novel targets for pharmacological modulation of thyroid hormone synthesis.

ChIPBase v2.0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data.

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Zhou, Ke-Ren; Liu, Shun; Sun, Wen-Ju; Zheng, Ling-Ling; Zhou, Hui; Yang, Jian-Hua; Qu, Liang-Hu

2017-01-04

The abnormal transcriptional regulation of non-coding RNAs (ncRNAs) and protein-coding genes (PCGs) is contributed to various biological processes and linked with human diseases, but the underlying mechanisms remain elusive. In this study, we developed ChIPBase v2.0 (http://rna.sysu.edu.cn/chipbase/) to explore the transcriptional regulatory networks of ncRNAs and PCGs. ChIPBase v2.0 has been expanded with ∼10 200 curated ChIP-seq datasets, which represent about 20 times expansion when comparing to the previous released version. We identified thousands of binding motif matrices and their binding sites from ChIP-seq data of DNA-binding proteins and predicted millions of transcriptional regulatory relationships between transcription factors (TFs) and genes. We constructed 'Regulator' module to predict hundreds of TFs and histone modifications that were involved in or affected transcription of ncRNAs and PCGs. Moreover, we built a web-based tool, Co-Expression, to explore the co-expression patterns between DNA-binding proteins and various types of genes by integrating the gene expression profiles of ∼10 000 tumor samples and ∼9100 normal tissues and cell lines. ChIPBase also provides a ChIP-Function tool and a genome browser to predict functions of diverse genes and visualize various ChIP-seq data. This study will greatly expand our understanding of the transcriptional regulations of ncRNAs and PCGs. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

The response of early neural genes to FGF signaling or inhibition of BMP indicate the absence of a conserved neural induction module

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Rogers Crystal D

2011-12-01

Full Text Available Abstract Background The molecular mechanism that initiates the formation of the vertebrate central nervous system has long been debated. Studies in Xenopus and mouse demonstrate that inhibition of BMP signaling is sufficient to induce neural tissue in explants or ES cells respectively, whereas studies in chick argue that instructive FGF signaling is also required for the expression of neural genes. Although additional signals may be involved in neural induction and patterning, here we focus on the roles of BMP inhibition and FGF8a. Results To address the question of necessity and sufficiency of BMP inhibition and FGF signaling, we compared the temporal expression of the five earliest genes expressed in the neuroectoderm and determined their requirements for induction at the onset of neural plate formation in Xenopus. Our results demonstrate that the onset and peak of expression of the genes vary and that they have different regulatory requirements and are therefore unlikely to share a conserved neural induction regulatory module. Even though all require inhibition of BMP for expression, some also require FGF signaling; expression of the early-onset pan-neural genes sox2 and foxd5α requires FGF signaling while other early genes, sox3, geminin and zicr1 are induced by BMP inhibition alone. Conclusions We demonstrate that BMP inhibition and FGF signaling induce neural genes independently of each other. Together our data indicate that although the spatiotemporal expression patterns of early neural genes are similar, the mechanisms involved in their expression are distinct and there are different signaling requirements for the expression of each gene.

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

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

2017-12-01

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

Improving functional modules discovery by enriching interaction networks with gene profiles

KAUST Repository

Salem, Saeed

2013-05-01

Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.

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...

The Evolution of the Secreted Regulatory Protein Progranulin.

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Roger G E Palfree

Full Text Available Progranulin is a secreted growth factor that is active in tumorigenesis, wound repair, and inflammation. Haploinsufficiency of the human progranulin gene, GRN, causes frontotemporal dementia. Progranulins are composed of chains of cysteine-rich granulin modules. Modules may be released from progranulin by proteolysis as 6kDa granulin polypeptides. Both intact progranulin and some of the granulin polypeptides are biologically active. The granulin module occurs in certain plant proteases and progranulins are present in early diverging metazoan clades such as the sponges, indicating their ancient evolutionary origin. There is only one Grn gene in mammalian genomes. More gene-rich Grn families occur in teleost fish with between 3 and 6 members per species including short-form Grns that have no tetrapod counterparts. Our goals are to elucidate progranulin and granulin module evolution by investigating (i: the origins of metazoan progranulins (ii: the evolutionary relationships between the single Grn of tetrapods and the multiple Grn genes of fish (iii: the evolution of granulin module architectures of vertebrate progranulins (iv: the conservation of mammalian granulin polypeptide sequences and how the conserved granulin amino acid sequences map to the known three dimensional structures of granulin modules. We report that progranulin-like proteins are present in unicellular eukaryotes that are closely related to metazoa suggesting that progranulin is among the earliest extracellular regulatory proteins still employed by multicellular animals. From the genomes of the elephant shark and coelacanth we identified contemporary representatives of a precursor for short-from Grn genes of ray-finned fish that is lost in tetrapods. In vertebrate Grns pathways of exon duplication resulted in a conserved module architecture at the amino-terminus that is frequently accompanied by an unusual pattern of tandem nearly identical module repeats near the carboxyl

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 contribution to the study of plant development evolution based on gene co-expression networks

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Francisco J. Romero-Campero

2013-08-01

Full Text Available Phototrophic eukaryotes are among the most successful organisms on Earth due to their unparalleled efficiency at capturing light energy and fixing carbon dioxide to produce organic molecules. A conserved and efficient network of light-dependent regulatory modules could be at the bases of this success. This regulatory system conferred early advantages to phototrophic eukaryotes that allowed for specialization, complex developmental processes and modern plant characteristics. We have studied light-dependent gene regulatory modules from algae to plants employing integrative-omics approaches based on gene co-expression networks. Our study reveals some remarkably conserved ways in which eukaryotic phototrophs deal with day length and light signaling. Here we describe how a family of Arabidopsis transcription factors involved in photoperiod response has evolved from a single algal gene according to the innovation, amplification and divergence theory of gene evolution by duplication. These modifications of the gene co-expression networks from the ancient unicellular green algae Chlamydomonas reinhardtii to the modern brassica Arabidopsis thaliana may hint on the evolution and specialization of plants and other organisms.

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.

Science.gov (United States)

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

Symbiont modulates expression of specific gene categories in Angomonas deanei

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Luciana Loureiro Penha

Full Text Available Trypanosomatids are parasites that cause disease in humans, animals, and plants. Most are non-pathogenic and some harbor a symbiotic bacterium. Endosymbiosis is part of the evolutionary process of vital cell functions such as respiration and photosynthesis. Angomonas deanei is an example of a symbiont-containing trypanosomatid. In this paper, we sought to investigate how symbionts influence host cells by characterising and comparing the transcriptomes of the symbiont-containing A. deanei (wild type and the symbiont-free aposymbiotic strains. The comparison revealed that the presence of the symbiont modulates several differentially expressed genes. Empirical analysis of differential gene expression showed that 216 of the 7625 modulated genes were significantly changed. Finally, gene set enrichment analysis revealed that the largest categories of genes that downregulated in the absence of the symbiont were those involved in oxidation-reduction process, ATP hydrolysis coupled proton transport and glycolysis. In contrast, among the upregulated gene categories were those involved in proteolysis, microtubule-based movement, and cellular metabolic process. Our results provide valuable information for dissecting the mechanism of endosymbiosis in A. deanei.

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.

Directory of Open Access Journals (Sweden)

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

A Yin-Yang 1/miR-30a regulatory circuit modulates autophagy in pancreatic cancer cells.

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Yang, Chuang; Zhang, Jing-Jing; Peng, Yun-Peng; Zhu, Yi; Yin, Ling-Di; Wei, Ji-Shu; Gao, Wen-Tao; Jiang, Kui-Rong; Miao, Yi

2017-10-19

Autophagy is a highly regulated biological process that mediates the degradation of intracellular components. It is required for tumor cell metabolism and homeostasis. Yin-Yang 1 (YY1) has been reported to be involved in autophagy in several carcinomas. However, its role in autophagy in pancreatic cancer, one of the deadliest human malignancies, is unknown. Here, we investigated the function of YY1 in pancreatic cancer cells autophagy and its mechanisms of action. The activity of cells undergoing autophagy was assessed using transmission electron microscopy, immunofluorescence, and Western blotting. A luciferase activity assay, real-time quantitative polymerase chain reaction (RT-qPCR), and chromatin immunoprecipitation (ChIP) were also used to identify putative downstream targets of YY1. YY1 was confirmed to regulate autophagy in pancreatic cancer cells. It was found to directly regulate the expression of miR-30a, a known modulator of autophagy-associated genes. Furthermore, overexpression of miR-30a attenuated the pro-autophagic effects of YY1. Cumulatively, our data suggest that miR-30a acts in a feedback loop to modulate the pro-autophagic activities of YY1. Thus, autophagy in pancreatic cancer cells may be regulated, in part, by a tightly coordinated YY1/miR-30a regulatory circuit. These findings provide a potential druggable target for the development of treatments for pancreatic cancer.

Bifidobacterium breve - HT-29 cell line interaction: modulation of TNF-α induced gene expression.

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Boesten, R J; Schuren, F H J; Willemsen, L E M; Vriesema, A; Knol, J; De Vos, W M

2011-06-01

To provide insight in the molecular basis for intestinal host-microbe interactions, we determined the genome-wide transcriptional response of human intestinal epithelial cells following exposure to cells of Bifidobacterium breve. To select an appropriate test system reflecting inflammatory conditions, the responsiveness to TNF-α was compared in T84, Caco-2 and HT-29 cells. The highest TNF-α response was observed in HT-29 cells and this cell line was selected for exposure to the B. breve strains M-16V, NR246 and UCC2003. After one hour of bacterial pre-incubation followed by two hours of additional TNF-α stimulation, B. breve M-16V (86%), but to a much lesser extent strains NR246 (50%) or UCC2003 (32%), showed a strain-specific reduction of the HT-29 transcriptional response to the inflammatory treatment. The most important functional groups of genes that were transcriptionally suppressed by the presence of B. breve M-16V, were found to be involved in immune regulation and apoptotic processes. About 54% of the TNF-α induced genes were solely suppressed by the presence of B. breve M-16V. These included apoptosis-related cysteine protease caspase 7 (CASP7), interferon regulatory factor 3 (IRF3), amyloid beta (A4) precursor proteinbinding family A member 1 (APBA1), NADPH oxidase (NOX5), and leukemia inhibitory factor receptor (LIFR). The extracellular IL-8 concentration was determined by an immunological assay but did not change significantly, indicating that B. breve M-16V only partially modulates the TNF-α pathway. In conclusion, this study shows that B. breve strains modulate gene expression in HT-29 cells under inflammatory conditions in a strain-specific way.

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.

Hydrogen-Deuterium Exchange Mass Spectrometry Reveals Calcium Binding Properties and Allosteric Regulation of Downstream Regulatory Element Antagonist Modulator (DREAM).

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Zhang, Jun; Li, Jing; Craig, Theodore A; Kumar, Rajiv; Gross, Michael L

2017-07-18

Downstream regulatory element antagonist modulator (DREAM) is an EF-hand Ca 2+ -binding protein that also binds to a specific DNA sequence, downstream regulatory elements (DRE), and thereby regulates transcription in a calcium-dependent fashion. DREAM binds to DRE in the absence of Ca 2+ but detaches from DRE under Ca 2+ stimulation, allowing gene expression. The Ca 2+ binding properties of DREAM and the consequences of the binding on protein structure are key to understanding the function of DREAM. Here we describe the application of hydrogen-deuterium exchange mass spectrometry (HDX-MS) and site-directed mutagenesis to investigate the Ca 2+ binding properties and the subsequent conformational changes of full-length DREAM. We demonstrate that all EF-hands undergo large conformation changes upon calcium binding even though the EF-1 hand is not capable of binding to Ca 2+ . Moreover, EF-2 is a lower-affinity site compared to EF-3 and -4 hands. Comparison of HDX profiles between wild-type DREAM and two EF-1 mutated constructs illustrates that the conformational changes in the EF-1 hand are induced by long-range structural interactions. HDX analyses also reveal a conformational change in an N-terminal leucine-charged residue-rich domain (LCD) remote from Ca 2+ -binding EF-hands. This LCD domain is responsible for the direct interaction between DREAM and cAMP response element-binding protein (CREB) and regulates the recruitment of the co-activator, CREB-binding protein. These long-range interactions strongly suggest how conformational changes transmit the Ca 2+ signal to CREB-mediated gene transcription.

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

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

2017-11-13

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

Systems Genetics Analysis to Identify the Genetic Modulation of a Glaucoma-Associated Gene.

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Chintalapudi, Sumana R; Jablonski, Monica M

2017-01-01

Loss of retinal ganglion cells (RGCs) is one of the hallmarks of retinal neurodegenerative diseases, glaucoma being one of the most common. Recently, γ-synuclein (SNCG) was shown to be highly expressed in the somas and axons of RGCs. In various mouse models of glaucoma, downregulation of Sncg gene expression correlates with RGC loss. To investigate the regulation of Sncg in RGCs, we used a systems genetics approach to identify a gene that modulates the expression of Sncg, followed by confirmatory studies in both healthy and diseased retinas. We found that chromosome 1 harbors an eQTL that modulates the expression of Sncg in the mouse retina and identified Pfdn2 as the candidate upstream modulator of Sncg expression. Downregulation of Pfdn2 in enriched RGCs causes a concomitant reduction in Sncg. In this chapter, we describe our strategy and methods for identifying and confirming a genetic modulation of a glaucoma-associated gene. A similar method can be applied to other genes expressed in other tissues.

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...

Direct activation of a notochord cis-regulatory module by Brachyury and FoxA in the ascidian Ciona intestinalis.

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Passamaneck, Yale J; Katikala, Lavanya; Perrone, Lorena; Dunn, Matthew P; Oda-Ishii, Izumi; Di Gregorio, Anna

2009-11-01

The notochord is a defining feature of the chordate body plan. Experiments in ascidian, frog and mouse embryos have shown that co-expression of Brachyury and FoxA class transcription factors is required for notochord development. However, studies on the cis-regulatory sequences mediating the synergistic effects of these transcription factors are complicated by the limited knowledge of notochord genes and cis-regulatory modules (CRMs) that are directly targeted by both. We have identified an easily testable model for such investigations in a 155-bp notochord-specific CRM from the ascidian Ciona intestinalis. This CRM contains functional binding sites for both Ciona Brachyury (Ci-Bra) and FoxA (Ci-FoxA-a). By combining point mutation analysis and misexpression experiments, we demonstrate that binding of both transcription factors to this CRM is necessary and sufficient to activate transcription. To gain insights into the cis-regulatory criteria controlling its activity, we investigated the organization of the transcription factor binding sites within the 155-bp CRM. The 155-bp sequence contains two Ci-Bra binding sites with identical core sequences but opposite orientations, only one of which is required for enhancer activity. Changes in both orientation and spacing of these sites substantially affect the activity of the CRM, as clusters of identical sites found in the Ciona genome with different arrangements are unable to activate transcription in notochord cells. This work presents the first evidence of a synergistic interaction between Brachyury and FoxA in the activation of an individual notochord CRM, and highlights the importance of transcription factor binding site arrangement for its function.

Control of Metastatic Progression by microRNA Regulatory Networks

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Pencheva, Nora; Tavazoie, Sohail F.

2015-01-01

Aberrant microRNA (miRNA) expression is a defining feature of human malignancy. Specific miRNAs have been identified as promoters or suppressors of metastatic progression. These miRNAs control metastasis through divergent or convergent regulation of metastatic gene pathways. Some miRNA regulatory networks govern cell-autonomous cancer phenotypes, while others modulate the cell-extrinsic composition of the metastatic microenvironment. The use of small RNAs as probes into the molecular and cellular underpinnings of metastasis holds promise for the identification of candidate genes for potential therapeutic intervention. PMID:23728460

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

DNA methylation affects the lifespan of honey bee (Apis mellifera L.) workers - Evidence for a regulatory module that involves vitellogenin expression but is independent of juvenile hormone function.

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Cardoso-Júnior, Carlos A M; Guidugli-Lazzarini, Karina R; Hartfelder, Klaus

2018-01-01

The canonic regulatory module for lifespan of honey bee (Apis mellifera) workers involves a mutual repressor relationship between juvenile hormone (JH) and vitellogenin (Vg). Compared to vertebrates, however, little is known about a possible role of epigenetic factors. The full genomic repertoire of DNA methyltransferases (DNMTs) makes the honey bee an attractive emergent model for studying the role of epigenetics in the aging process of invertebrates, and especially so in social insects. We first quantified the transcript levels of the four DNMTs encoding genes in the head thorax and abdomens of workers of different age, showing that dnmt1a and dnmt3 expression is up-regulated in abdomens of old workers, whereas dnmt1b and dnmt2 are down-regulated in heads of old workers. Pharmacological genome demethylation by RG108 treatment caused an increase in worker lifespan. Next, we showed that the genomic DNA methylation status indirectly affects vitellogenin gene expression both in vitro and in vivo in young workers, and that this occurs independent of caloric restriction or JH levels, suggesting that a non-canonical circuitry may be acting in parallel with the JH/Vg module to regulate the adult life cycle of honey bee workers. Our data provide evidence that epigenetic factors play a role in regulatory networks associated with complex life history traits of a social insect. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modulation of human multidrug-resistance MDR-1 gene by natural curcuminoids

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Buddhasukh Duang

2004-04-01

Full Text Available Abstract Background Multidrug resistance (MDR is a phenomenon that is often associated with decreased intracellular drug accumulation in patient's tumor cells resulting from enhanced drug efflux. It is related to the overexpression of a membrane protein, P-glycoprotein (Pgp-170, thereby reducing drug cytotoxicity. A variety of studies have tried to find MDR modulators which increase drug accumulation in cancer cells. Methods In this study, natural curcuminoids, pure curcumin, demethoxycurcumin and bisdemethoxycurcumin, isolated from turmeric (Curcuma longa Linn, were compared for their potential ability to modulate the human MDR-1 gene expression in multidrug resistant human cervical carcinoma cell line, KB-V1 by Western blot analysis and RT-PCR. Results Western blot analysis and RT-PCR showed that all the three curcuminoids inhibited MDR-1 gene expression, and bisdemethoxycurcumin produced maximum effect. In additional studies we found that commercial grade curcuminoid (approximately 77% curcumin, 17% demethoxycurcumin and 3% bisdemthoxycurcumin decreased MDR-1 gene expression in a dose dependent manner and had about the same potent inhibitory effect on MDR-1 gene expression as our natural curcuminoid mixtures. Conclusion These results indicate that bisdemethoxycurcumin is the most active of the curcuminoids present in turmeric for modulation of MDR-1 gene. Treatment of drug resistant KB-V1 cells with curcumin increased their sensitivity to vinblastine, which was consistent with a decreased MDR-1 gene product, a P-glycoprotein, on the cell plasma membrane. Although many drugs that prevent the P-glycoprotein function have been reported, this report describes the inhibition of MDR-1 expression by a phytochemical. The modulation of MDR-1 expression may be an attractive target for new chemosensitizing agents.

Modulation of human multidrug-resistance MDR-1 gene by natural curcuminoids

International Nuclear Information System (INIS)

Limtrakul, Pornngarm; Anuchapreeda, Songyot; Buddhasukh, Duang

2004-01-01

Multidrug resistance (MDR) is a phenomenon that is often associated with decreased intracellular drug accumulation in patient's tumor cells resulting from enhanced drug efflux. It is related to the overexpression of a membrane protein, P-glycoprotein (Pgp-170), thereby reducing drug cytotoxicity. A variety of studies have tried to find MDR modulators which increase drug accumulation in cancer cells. In this study, natural curcuminoids, pure curcumin, demethoxycurcumin and bisdemethoxycurcumin, isolated from turmeric (Curcuma longa Linn), were compared for their potential ability to modulate the human MDR-1 gene expression in multidrug resistant human cervical carcinoma cell line, KB-V1 by Western blot analysis and RT-PCR. Western blot analysis and RT-PCR showed that all the three curcuminoids inhibited MDR-1 gene expression, and bisdemethoxycurcumin produced maximum effect. In additional studies we found that commercial grade curcuminoid (approximately 77% curcumin, 17% demethoxycurcumin and 3% bisdemthoxycurcumin) decreased MDR-1 gene expression in a dose dependent manner and had about the same potent inhibitory effect on MDR-1 gene expression as our natural curcuminoid mixtures. These results indicate that bisdemethoxycurcumin is the most active of the curcuminoids present in turmeric for modulation of MDR-1 gene. Treatment of drug resistant KB-V1 cells with curcumin increased their sensitivity to vinblastine, which was consistent with a decreased MDR-1 gene product, a P-glycoprotein, on the cell plasma membrane. Although many drugs that prevent the P-glycoprotein function have been reported, this report describes the inhibition of MDR-1 expression by a phytochemical. The modulation of MDR-1 expression may be an attractive target for new chemosensitizing agents

Safety assessment of immunomodulatory biologics: the promise and challenges of regulatory T-cell modulation.

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Ponce, Rafael A

2011-01-01

Regulatory T-cell (T(reg)) modulation is developing as an important therapeutic opportunity for the treatment of a number of important diseases, including cancer, autoimmunity, infection, and organ transplant rejection. However, as demonstrated with IL-2 and TGN-1412, our understanding of the complex immunological interactions that occur with T(reg) modulation in both non-clinical models and in patients remains limited and appears highly contextual. This lack of understanding will challenge our ability to identify the patient population who might derive the highest benefit from T(reg) modulation and creates special challenges as we transition these therapeutics from non-clinical models into humans. Thus, in vivo testing in the most representative animal model systems, with careful progress in the clinic, will remain critical in developing therapeutics targeting T(reg) and understanding their clinical utility. Moreover, toxicology models can inform some of the potential liabilities associated with T(reg) modulation, but not all, suggesting a continued need to explore and validate predictive models.

Expression profiles of variation integration genes in bladder urothelial carcinoma.

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Wang, J M; Wang, Y Q; Gao, Z L; Wu, J T; Shi, B K; Yu, C C

2014-04-30

Bladder cancer is a common cancer worldwide and its incidence continues to increase. There are approximately 261,000 cases of bladder cancer resulting in 115,000 deaths annually. This study aimed to integrate bladder cancer genome copy number variation information and bladder cancer gene transcription level expression data to construct a causal-target module network of the range of bladder cancer-related genomes. Here, we explored the control mechanism underlying bladder cancer phenotype expression regulation by the major bladder cancer genes. We selected 22 modules as the initial module network to expand the search to screen more networks. After bootstrapping 100 times, we obtained 16 key regulators. These 16 key candidate regulatory genes were further expanded to identify the expression changes of 11,676 genes in 275 modules, which may all have the same regulation. In conclusion, a series of modules associated with the terms 'cancer' or 'bladder' were considered to constitute a potential network.

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.

Directory of Open Access Journals (Sweden)

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

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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

Regulatory Oversight of Cell and Gene Therapy Products in Canada.

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

2015-01-01

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

Vitamin A and feeding statuses modulate the insulin-regulated gene expression in Zucker lean and fatty primary rat hepatocytes.

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Wei Chen

Full Text Available Unattended hepatic insulin resistance predisposes individuals to dyslipidemia, type 2 diabetes and many other metabolic complications. The mechanism of hepatic insulin resistance at the gene expression level remains unrevealed. To examine the effects of vitamin A (VA, total energy intake and feeding conditions on the insulin-regulated gene expression in primary hepatocytes of Zucker lean (ZL and fatty (ZF rats, we analyze the expression levels of hepatic model genes in response to the treatments of insulin and retinoic acid (RA. We report that the insulin- and RA-regulated glucokinase, sterol regulatory element-binding protein-1c and cytosolic form of phosphoenolpyruvate carboxykinase expressions are impaired in hepatocytes of ZF rats fed chow or a VA sufficient (VAS diet ad libitum. The impairments are partially corrected when ZF rats are fed a VA deficient (VAD diet ad libitum or pair-fed a VAS diet to the intake of their VAD counterparts in non-fasting conditions. Interestingly in the pair-fed ZL and ZF rats, transient overeating on the last day of pair-feeding regimen changes the expression levels of some VA catabolic genes, and impairs the insulin- and RA-regulated gene expression in hepatocytes. These results demonstrate that VA and feeding statuses modulate the hepatic insulin sensitivity at the gene expression level.

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.

CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation.

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Nikulova, Anna A; Favorov, Alexander V; Sutormin, Roman A; Makeev, Vsevolod J; Mironov, Andrey A

2012-07-01

Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory 'grammar', or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila.

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

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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.

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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.

Gene Network for Identifying the Entropy Changes of Different Modules in Pediatric Sepsis

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Jing Yang

2016-12-01

Full Text Available Background/Aims: Pediatric sepsis is a disease that threatens life of children. The incidence of pediatric sepsis is higher in developing countries due to various reasons, such as insufficient immunization and nutrition, water and air pollution, etc. Exploring the potential genes via different methods is of significance for the prevention and treatment of pediatric sepsis. This study aimed to identify potential genes associated with pediatric sepsis utilizing analysis of gene network and entropy. Methods: The mRNA expression in the blood samples collected from 20 septic children and 30 healthy controls was quantified by using Affymetrix HG-U133A microarray. Two condition-specific protein-protein interaction networks (PINs, one for the healthy control and the other one for the children with sepsis, were deduced by combining the fundamental human PINs with gene expression profiles in the two phenotypes. Subsequently, distinct modules from the two conditional networks were extracted by adopting a maximal clique-merging approach. Delta entropy (ΔS was calculated between sepsis and control modules. Results: Then, key genes displaying changes in gene composition were identified by matching the control and sepsis modules. Two objective modules were obtained, in which ribosomal protein RPL4 and RPL9 as well as TOP2A were probably considered as the key genes differentiating sepsis from healthy controls. Conclusion: According to previous reports and this work, TOP2A is the potential gene therapy target for pediatric sepsis. The relationship between pediatric sepsis and RPL4 and RPL9 needs further investigation.

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.

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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

CD4+CD25+ regulatory T cells control CD8+ T-cell effector differentiation by modulating IL-2 homeostasis

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McNally, Alice; Hill, Geoffrey R.; Sparwasser, Tim; Thomas, Ranjeny; Steptoe, Raymond J.

2011-01-01

CD4+CD25+ regulatory T cells (Treg) play a crucial role in the regulation of immune responses. Although many mechanisms of Treg suppression in vitro have been described, the mechanisms by which Treg modulate CD8+ T cell differentiation and effector function in vivo are more poorly defined. It has been proposed, in many instances, that modulation of cytokine homeostasis could be an important mechanism by which Treg regulate adaptive immunity; however, direct experimental evidence is sparse. Here we demonstrate that CD4+CD25+ Treg, by critically regulating IL-2 homeostasis, modulate CD8+ T-cell effector differentiation. Expansion and effector differentiation of CD8+ T cells is promoted by autocrine IL-2 but, by competing for IL-2, Treg limit CD8+ effector differentiation. Furthermore, a regulatory loop exists between Treg and CD8+ effector T cells, where IL-2 produced during CD8+ T-cell effector differentiation promotes Treg expansion. PMID:21502514

Highly preserved consensus gene modules in human papilloma virus 16 positive cervical cancer and head and neck cancers.

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Zhang, Xianglan; Cha, In-Ho; Kim, Ki-Yeol

2017-12-26

In this study, we investigated the consensus gene modules in head and neck cancer (HNC) and cervical cancer (CC). We used a publicly available gene expression dataset, GSE6791, which included 42 HNC, 14 normal head and neck, 20 CC and 8 normal cervical tissue samples. To exclude bias because of different human papilloma virus (HPV) types, we analyzed HPV16-positive samples only. We identified 3824 genes common to HNC and CC samples. Among these, 977 genes showed high connectivity and were used to construct consensus modules. We demonstrated eight consensus gene modules for HNC and CC using the dissimilarity measure and average linkage hierarchical clustering methods. These consensus modules included genes with significant biological functions, including ATP binding and extracellular exosome. Eigengen network analysis revealed the consensus modules were highly preserved with high connectivity. These findings demonstrate that HPV16-positive head and neck and cervical cancers share highly preserved consensus gene modules with common potentially therapeutic targets.

Regulatory RNA-assisted genome engineering in microorganisms.

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Si, Tong; HamediRad, Mohammad; Zhao, Huimin

2015-12-01

Regulatory RNAs are increasingly recognized and utilized as key modulators of gene expression in diverse organisms. Thanks to their modular and programmable nature, trans-acting regulatory RNAs are especially attractive in genome-scale applications. Here we discuss the recent examples in microbial genome engineering implementing various trans-acting RNA platforms, including sRNA, RNAi, asRNA and CRISRP-Cas. In particular, we focus on how the scalable and multiplex nature of trans-acting RNAs has been used to tackle the challenges in creating genome-wide and combinatorial diversity for functional genomics and metabolic engineering applications. Advances in computational design and context-dependent regulation are also discussed for their contribution in improving fine-tuning capabilities of trans-acting RNAs. Copyright © 2015 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.; 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

MRF Family Genes Are Involved in Translation Control, Especially under Energy-Deficient Conditions, and Their Expression and Functions Are Modulated by the TOR Signaling Pathway[OPEN

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Lee, Du-Hwa; Park, Seung Jun; Ahn, Chang Sook

2017-01-01

Dynamic control of protein translation in response to the environment is essential for the survival of plant cells. Target of rapamycin (TOR) coordinates protein synthesis with cellular energy/nutrient availability through transcriptional modulation and phosphorylation of the translation machinery. However, mechanisms of TOR-mediated translation control are poorly understood in plants. Here, we report that Arabidopsis thaliana MRF (MA3 DOMAIN-CONTAINING TRANSLATION REGULATORY FACTOR) family genes encode translation regulatory factors under TOR control, and their functions are particularly important in energy-deficient conditions. Four MRF family genes (MRF1-MRF4) are transcriptionally induced by dark and starvation (DS). Silencing of multiple MRFs increases susceptibility to DS and treatment with a TOR inhibitor, while MRF1 overexpression decreases susceptibility. MRF proteins interact with eIF4A and cofractionate with ribosomes. MRF silencing decreases translation activity, while MRF1 overexpression increases it, accompanied by altered ribosome patterns, particularly in DS. Furthermore, MRF deficiency in DS causes altered distribution of mRNAs in sucrose gradient fractions and accelerates rRNA degradation. MRF1 is phosphorylated in vivo and phosphorylated by S6 kinases in vitro. MRF expression and MRF1 ribosome association and phosphorylation are modulated by cellular energy status and TOR activity. We discuss possible mechanisms of the function of MRF family proteins under normal and energy-deficient conditions and their functional link with the TOR pathway. PMID:29084871

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.

A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes.

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Simone de Jong

Full Text Available Despite large-scale genome-wide association studies (GWAS, the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1, is located in, and regulated by the major histocompatibility (MHC complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network.

Limb development: a paradigm of gene regulation.

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Petit, Florence; Sears, Karen E; Ahituv, Nadav

2017-04-01

The limb is a commonly used model system for developmental biology. Given the need for precise control of complex signalling pathways to achieve proper patterning, the limb is also becoming a model system for gene regulation studies. Recent developments in genomic technologies have enabled the genome-wide identification of regulatory elements that control limb development, yielding insights into the determination of limb morphology and forelimb versus hindlimb identity. The modulation of regulatory interactions - for example, through the modification of regulatory sequences or chromatin architecture - can lead to morphological evolution, acquired regeneration capacity or limb malformations in diverse species, including humans.

Evolution of hepatic glucose metabolism: liver-specific glucokinase deficiency explained by parallel loss of the gene for glucokinase regulatory protein (GCKR.

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Zhao Yang Wang

Full Text Available Glucokinase (GCK plays an important role in the regulation of carbohydrate metabolism. In the liver, phosphorylation of glucose to glucose-6-phosphate by GCK is the first step for both glycolysis and glycogen synthesis. However, some vertebrate species are deficient in GCK activity in the liver, despite containing GCK genes that appear to be compatible with function in their genomes. Glucokinase regulatory protein (GCKR is the most important post-transcriptional regulator of GCK in the liver; it participates in the modulation of GCK activity and location depending upon changes in glucose levels. In experimental models, loss of GCKR has been shown to associate with reduced hepatic GCK protein levels and activity.GCKR genes and GCKR-like sequences were identified in the genomes of all vertebrate species with available genome sequences. The coding sequences of GCKR and GCKR-like genes were identified and aligned; base changes likely to disrupt coding potential or splicing were also identified.GCKR genes could not be found in the genomes of 9 vertebrate species, including all birds. In addition, in multiple mammalian genomes, whereas GCKR-like gene sequences could be identified, these genes could not predict a functional protein. Vertebrate species that were previously reported to be deficient in hepatic GCK activity were found to have deleted (birds and lizard or mutated (mammals GCKR genes. Our results suggest that mutation of the GCKR gene leads to hepatic GCK deficiency due to the loss of the stabilizing effect of GCKR.

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

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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.

Genes co-regulated with LBD16 in nematode feeding sites inferred from in silico analysis show similarities to regulatory circuits mediated by the auxin/cytokinin balance in Arabidopsis.

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Cabrera, Javier; Fenoll, Carmen; Escobar, Carolina

2015-01-01

Plant endoparasitic nematodes, root-knot and cyst nematodes (RKNs and CNs) induce within the root vascular cylinder transfer cells used for nourishing, termed giant cells (GCs) and syncytia. Understanding the molecular mechanisms behind this process is essential to develop tools for nematode control. Based on the crucial role in gall development of LBD16, also a key component of the auxin pathway leading to the divisions in the xylem pole pericycle during lateral root (LR) formation, we investigated genes co-regulated with LBD16 in different transcriptomes and analyzed their similarities and differences with those of RKNs and CNs feeding sites (FS). This analysis confirmed LBD16 and its co-regulated genes, integrated in signaling cascades mediated by auxins during LR and callus formation, as a particular feature of RKN-FS distinct to CNs. However, LBD16, and its positively co-regulated genes, were repressed in syncytia, suggesting a selective down- regulation of the LBD16 auxin mediated pathways in CNs-FS. Interestingly, cytokinin-induced genes are enriched in syncytia and we encountered similarities between the transcriptome of shoot regeneration from callus, modulated by cytokinins, and that of syncytia. These findings establish differences in the regulatory networks leading to both FS formation, probably modulated by the auxin/cytokinin balance.

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.

Assessment of citalopram and escitalopram on neuroblastoma cell lines: Cell toxicity and gene modulation

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Sakka, Laurent; Delétage, Nathalie; Chalus, Maryse; Aissouni, Youssef; Sylvain-Vidal, Valérie; Gobron, Stéphane; Coll, Guillaume

2017-01-01

Selective serotonin reuptake inhibitors (SSRI) are common antidepressants which cytotoxicity has been assessed in cancers notably colorectal carcinomas and glioma cell lines. We assessed and compared the cytotoxicity of 2 SSRI, citalopram and escitalopram, on neuroblastoma cell lines. The study was performed on 2 non-MYCN amplified cell lines (rat B104 and human SH-SY5Y) and 2 human MYCN amplified cell lines (IMR32 and Kelly). Citalopram and escitalopram showed concentration-dependent cytotoxicity on all cell lines. Citalopram was more cytotoxic than escitalopram. IMR32 was the most sensitive cell line. The absence of toxicity on human primary Schwann cells demonstrated the safety of both molecules for myelin. The mechanisms of cytotoxicity were explored using gene-expression profiles and quantitative real-time PCR (qPCR). Citalopram modulated 1 502 genes and escitalopram 1 164 genes with a fold change ≥ 2. 1 021 genes were modulated by both citalopram and escitalopram; 481 genes were regulated only by citalopram while 143 genes were regulated only by escitalopram. Citalopram modulated 69 pathways (KEGG) and escitalopram 42. Ten pathways were differently modulated by citalopram and escitalopram. Citalopram drastically decreased the expression of MYBL2, BIRC5 and BARD1 poor prognosis factors of neuroblastoma with fold-changes of -107 (pescitalopram. PMID:28467792

Assessment of citalopram and escitalopram on neuroblastoma cell lines. Cell toxicity and gene modulation.

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Sakka, Laurent; Delétage, Nathalie; Chalus, Maryse; Aissouni, Youssef; Sylvain-Vidal, Valérie; Gobron, Stéphane; Coll, Guillaume

2017-06-27

Selective serotonin reuptake inhibitors (SSRI) are common antidepressants which cytotoxicity has been assessed in cancers notably colorectal carcinomas and glioma cell lines. We assessed and compared the cytotoxicity of 2 SSRI, citalopram and escitalopram, on neuroblastoma cell lines. The study was performed on 2 non-MYCN amplified cell lines (rat B104 and human SH-SY5Y) and 2 human MYCN amplified cell lines (IMR32 and Kelly). Citalopram and escitalopram showed concentration-dependent cytotoxicity on all cell lines. Citalopram was more cytotoxic than escitalopram. IMR32 was the most sensitive cell line. The absence of toxicity on human primary Schwann cells demonstrated the safety of both molecules for myelin. The mechanisms of cytotoxicity were explored using gene-expression profiles and quantitative real-time PCR (qPCR). Citalopram modulated 1 502 genes and escitalopram 1 164 genes with a fold change ≥ 2. 1 021 genes were modulated by both citalopram and escitalopram; 481 genes were regulated only by citalopram while 143 genes were regulated only by escitalopram. Citalopram modulated 69 pathways (KEGG) and escitalopram 42. Ten pathways were differently modulated by citalopram and escitalopram. Citalopram drastically decreased the expression of MYBL2, BIRC5 and BARD1 poor prognosis factors of neuroblastoma with fold-changes of -107 (pescitalopram.

Direct activation of EXPANSIN14 by LBD18 in the gene regulatory network of lateral root formation in Arabidopsis.

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Kim, Jungmook; Lee, Han Woo

2013-02-01

Root system architecture is important for plants to adapt to a changing environment. The major determinant of the root system is lateral roots originating from the primary root. The developmental process of lateral root formation can be divided into priming, initiation, primordium development and the emergence of lateral roots, and is well characterized in Arabidopsis. The hormone auxin plays a critical role in lateral root development, and several auxin response modules involving AUXIN RESPONSE FACTORS (ARFs), transcriptional regulators of auxin-regulated genes and Aux/IAA, negative regulators of ARFs, regulate lateral root formation. The LATERAL ORGAN BOUNDARIES DOMAIN/ASYMMETRIC LEAVES2-LIKE (LBD/ASL) gene family encodes a unique class of transcription factors harbouring a conserved plant-specific lateral organ boundary domain and plays a role in lateral organ development of plants including lateral root formation. In our previous study, we showed that LBD18 stimulates lateral root formation in combination with LBD16 downstream of ARF7 and ARF19 during the auxin response. We have recently demonstrated that LBD18 activates expression of EXP14, a gene encoding the cell-wall loosening factor, by directly binding to the EXP14 promoter to promote lateral root emergence. Here we present the molecular function of LBD18 and its gene regulatory network during lateral root formation.

Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data.

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Farber, Charles R

2010-11-01

Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD. © 2010 American Society for Bone and Mineral Research.

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.

Mediator kinase module and human tumorigenesis.

Science.gov (United States)

Clark, Alison D; Oldenbroek, Marieke; Boyer, Thomas G

2015-01-01

Mediator is a conserved multi-subunit signal processor through which regulatory informatiosn conveyed by gene-specific transcription factors is transduced to RNA Polymerase II (Pol II). In humans, MED13, MED12, CDK8 and Cyclin C (CycC) comprise a four-subunit "kinase" module that exists in variable association with a 26-subunit Mediator core. Genetic and biochemical studies have established the Mediator kinase module as a major ingress of developmental and oncogenic signaling through Mediator, and much of its function in signal-dependent gene regulation derives from its resident CDK8 kinase activity. For example, CDK8-targeted substrate phosphorylation impacts transcription factor half-life, Pol II activity and chromatin chemistry and functional status. Recent structural and biochemical studies have revealed a precise network of physical and functional subunit interactions required for proper kinase module activity. Accordingly, pathologic change in this activity through altered expression or mutation of constituent kinase module subunits can have profound consequences for altered signaling and tumor formation. Herein, we review the structural organization, biological function and oncogenic potential of the Mediator kinase module. We focus principally on tumor-associated alterations in kinase module subunits for which mechanistic relationships as opposed to strictly correlative associations are established. These considerations point to an emerging picture of the Mediator kinase module as an oncogenic unit, one in which pathogenic activation/deactivation through component change drives tumor formation through perturbation of signal-dependent gene regulation. It follows that therapeutic strategies to combat CDK8-driven tumors will involve targeted modulation of CDK8 activity or pharmacologic manipulation of dysregulated CDK8-dependent signaling pathways.

IBTK Differently Modulates Gene Expression and RNA Splicing in HeLa and K562 Cells

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Giuseppe Fiume

2016-11-01

Full Text Available The IBTK gene encodes the major protein isoform IBTKα that was recently characterized as substrate receptor of Cul3-dependent E3 ligase, regulating ubiquitination coupled to proteasomal degradation of Pdcd4, an inhibitor of translation. Due to the presence of Ankyrin-BTB-RCC1 domains that mediate several protein-protein interactions, IBTKα could exert expanded regulatory roles, including interaction with transcription regulators. To verify the effects of IBTKα on gene expression, we analyzed HeLa and K562 cell transcriptomes by RNA-Sequencing before and after IBTK knock-down by shRNA transduction. In HeLa cells, 1285 (2.03% of 63,128 mapped transcripts were differentially expressed in IBTK-shRNA-transduced cells, as compared to cells treated with control-shRNA, with 587 upregulated (45.7% and 698 downregulated (54.3% RNAs. In K562 cells, 1959 (3.1% of 63128 mapped RNAs were differentially expressed in IBTK-shRNA-transduced cells, including 1053 upregulated (53.7% and 906 downregulated (46.3%. Only 137 transcripts (0.22% were commonly deregulated by IBTK silencing in both HeLa and K562 cells, indicating that most IBTKα effects on gene expression are cell type-specific. Based on gene ontology classification, the genes responsive to IBTK are involved in different biological processes, including in particular chromatin and nucleosomal organization, gene expression regulation, and cellular traffic and migration. In addition, IBTK RNA interference affected RNA maturation in both cell lines, as shown by the evidence of alternative 3′- and 5′-splicing, mutually exclusive exons, retained introns, and skipped exons. Altogether, these results indicate that IBTK differently modulates gene expression and RNA splicing in HeLa and K562 cells, demonstrating a novel biological role of this protein.

IBTK Differently Modulates Gene Expression and RNA Splicing in HeLa and K562 Cells.

Science.gov (United States)

Fiume, Giuseppe; Scialdone, Annarita; Rizzo, Francesca; De Filippo, Maria Rosaria; Laudanna, Carmelo; Albano, Francesco; Golino, Gaetanina; Vecchio, Eleonora; Pontoriero, Marilena; Mimmi, Selena; Ceglia, Simona; Pisano, Antonio; Iaccino, Enrico; Palmieri, Camillo; Paduano, Sergio; Viglietto, Giuseppe; Weisz, Alessandro; Scala, Giuseppe; Quinto, Ileana

2016-11-07

The IBTK gene encodes the major protein isoform IBTKα that was recently characterized as substrate receptor of Cul3-dependent E3 ligase, regulating ubiquitination coupled to proteasomal degradation of Pdcd4, an inhibitor of translation. Due to the presence of Ankyrin-BTB-RCC1 domains that mediate several protein-protein interactions, IBTKα could exert expanded regulatory roles, including interaction with transcription regulators. To verify the effects of IBTKα on gene expression, we analyzed HeLa and K562 cell transcriptomes by RNA-Sequencing before and after IBTK knock-down by shRNA transduction. In HeLa cells, 1285 (2.03%) of 63,128 mapped transcripts were differentially expressed in IBTK -shRNA-transduced cells, as compared to cells treated with control-shRNA, with 587 upregulated (45.7%) and 698 downregulated (54.3%) RNAs. In K562 cells, 1959 (3.1%) of 63128 mapped RNAs were differentially expressed in IBTK -shRNA-transduced cells, including 1053 upregulated (53.7%) and 906 downregulated (46.3%). Only 137 transcripts (0.22%) were commonly deregulated by IBTK silencing in both HeLa and K562 cells, indicating that most IBTKα effects on gene expression are cell type-specific. Based on gene ontology classification, the genes responsive to IBTK are involved in different biological processes, including in particular chromatin and nucleosomal organization, gene expression regulation, and cellular traffic and migration. In addition, IBTK RNA interference affected RNA maturation in both cell lines, as shown by the evidence of alternative 3'- and 5'-splicing, mutually exclusive exons, retained introns, and skipped exons. Altogether, these results indicate that IBTK differently modulates gene expression and RNA splicing in HeLa and K562 cells, demonstrating a novel biological role of this protein.

Bladder inflammatory transcriptome in response to tachykinins: Neurokinin 1 receptor-dependent genes and transcription regulatory elements

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Dozmorov Igor

2007-05-01

Full Text Available Abstract Background Tachykinins (TK, such as substance P, and their neurokinin receptors which are ubiquitously expressed in the human urinary tract, represent an endogenous system regulating bladder inflammatory, immune responses, and visceral hypersensitivity. Increasing evidence correlates alterations in the TK system with urinary tract diseases such as neurogenic bladders, outflow obstruction, idiopathic detrusor instability, and interstitial cystitis. However, despite promising effects in animal models, there seems to be no published clinical study showing that NK-receptor antagonists are an effective treatment of pain in general or urinary tract disorders, such as detrusor overactivity. In order to search for therapeutic targets that could block the tachykinin system, we set forth to determine the regulatory network downstream of NK1 receptor activation. First, NK1R-dependent transcripts were determined and used to query known databases for their respective transcription regulatory elements (TREs. Methods An expression analysis was performed using urinary bladders isolated from sensitized wild type (WT and NK1R-/- mice that were stimulated with saline, LPS, or antigen to provoke inflammation. Based on cDNA array results, NK1R-dependent genes were selected. PAINT software was used to query TRANSFAC database and to retrieve upstream TREs that were confirmed by electrophoretic mobility shift assays. Results The regulatory network of TREs driving NK1R-dependent genes presented cRel in a central position driving 22% of all genes, followed by AP-1, NF-kappaB, v-Myb, CRE-BP1/c-Jun, USF, Pax-6, Efr-1, Egr-3, and AREB6. A comparison between NK1R-dependent and NK1R-independent genes revealed Nkx-2.5 as a unique discriminator. In the presence of NK1R, Nkx2-5 _01 was significantly correlated with 36 transcripts which included several candidates for mediating bladder development (FGF and inflammation (PAR-3, IL-1R, IL-6, α-NGF, TSP2. In the absence of

Genetics and Molecular Biology of Epstein-Barr Virus-Encoded BART MicroRNA: A Paradigm for Viral Modulation of Host Immune Response Genes and Genome Stability

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David H. Dreyfus

2017-01-01

Full Text Available Epstein-Barr virus, a ubiquitous human herpesvirus, is associated through epidemiologic evidence with common autoimmune syndromes and cancers. However, specific genetic mechanisms of pathogenesis have been difficult to identify. In this review, the author summarizes evidence that recently discovered noncoding RNAs termed microRNA encoded by Epstein-Barr virus BARF (BamHI A right frame termed BART (BamHI A right transcripts are modulators of human immune response genes and genome stability in infected and bystander cells. BART expression is apparently regulated by complex feedback loops with the host immune response regulatory NF-κB transcription factors. EBV-encoded BZLF-1 (ZEBRA protein could also regulate BART since ZEBRA contains a terminal region similar to ankyrin proteins such as IκBα that regulate host NF-κB. BALF-2 (BamHI A left frame transcript, a viral homologue of the immunoglobulin and T cell receptor gene recombinase RAG-1 (recombination-activating gene-1, may also be coregulated with BART since BALF-2 regulatory sequences are located near the BART locus. Viral-encoded microRNA and viral mRNA transferred to bystander cells through vesicles, defective viral particles, or other mechanisms suggest a new paradigm in which bystander or hit-and-run mechanisms enable the virus to transiently or chronically alter human immune response genes as well as the stability of the human genome.

bc-GenExMiner 3.0: new mining module computes breast cancer gene expression correlation analyses.

Science.gov (United States)

Jézéquel, Pascal; Frénel, Jean-Sébastien; Campion, Loïc; Guérin-Charbonnel, Catherine; Gouraud, Wilfried; Ricolleau, Gabriel; Campone, Mario

2013-01-01

We recently developed a user-friendly web-based application called bc-GenExMiner (http://bcgenex.centregauducheau.fr), which offered the possibility to evaluate prognostic informativity of genes in breast cancer by means of a 'prognostic module'. In this study, we develop a new module called 'correlation module', which includes three kinds of gene expression correlation analyses. The first one computes correlation coefficient between 2 or more (up to 10) chosen genes. The second one produces two lists of genes that are most correlated (positively and negatively) to a 'tested' gene. A gene ontology (GO) mining function is also proposed to explore GO 'biological process', 'molecular function' and 'cellular component' terms enrichment for the output lists of most correlated genes. The third one explores gene expression correlation between the 15 telomeric and 15 centromeric genes surrounding a 'tested' gene. These correlation analyses can be performed in different groups of patients: all patients (without any subtyping), in molecular subtypes (basal-like, HER2+, luminal A and luminal B) and according to oestrogen receptor status. Validation tests based on published data showed that these automatized analyses lead to results consistent with studies' conclusions. In brief, this new module has been developed to help basic researchers explore molecular mechanisms of breast cancer. DATABASE URL: http://bcgenex.centregauducheau.fr

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...

MRF Family Genes Are Involved in Translation Control, Especially under Energy-Deficient Conditions, and Their Expression and Functions Are Modulated by the TOR Signaling Pathway.

Science.gov (United States)

Lee, Du-Hwa; Park, Seung Jun; Ahn, Chang Sook; Pai, Hyun-Sook

2017-11-01

Dynamic control of protein translation in response to the environment is essential for the survival of plant cells. Target of rapamycin (TOR) coordinates protein synthesis with cellular energy/nutrient availability through transcriptional modulation and phosphorylation of the translation machinery. However, mechanisms of TOR-mediated translation control are poorly understood in plants. Here, we report that Arabidopsis thaliana MRF (MA3 DOMAIN-CONTAINING TRANSLATION REGULATORY FACTOR) family genes encode translation regulatory factors under TOR control, and their functions are particularly important in energy-deficient conditions. Four MRF family genes ( MRF1 - MRF4 ) are transcriptionally induced by dark and starvation (DS). Silencing of multiple MRFs increases susceptibility to DS and treatment with a TOR inhibitor, while MRF1 overexpression decreases susceptibility. MRF proteins interact with eIF4A and cofractionate with ribosomes. MRF silencing decreases translation activity, while MRF1 overexpression increases it, accompanied by altered ribosome patterns, particularly in DS. Furthermore, MRF deficiency in DS causes altered distribution of mRNAs in sucrose gradient fractions and accelerates rRNA degradation. MRF1 is phosphorylated in vivo and phosphorylated by S6 kinases in vitro. MRF expression and MRF1 ribosome association and phosphorylation are modulated by cellular energy status and TOR activity. We discuss possible mechanisms of the function of MRF family proteins under normal and energy-deficient conditions and their functional link with the TOR pathway. © 2017 American Society of Plant Biologists. All rights reserved.

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.

The Regulatory Small RNA MarS Supports Virulence of Streptococcus pyogenes.

Science.gov (United States)

Pappesch, Roberto; Warnke, Philipp; Mikkat, Stefan; Normann, Jana; Wisniewska-Kucper, Aleksandra; Huschka, Franziska; Wittmann, Maja; Khani, Afsaneh; Schwengers, Oliver; Oehmcke-Hecht, Sonja; Hain, Torsten; Kreikemeyer, Bernd; Patenge, Nadja

2017-09-25

Small regulatory RNAs (sRNAs) play a role in the control of bacterial virulence gene expression. In this study, we investigated an sRNA that was identified in Streptococcus pyogenes (group A Streptococcus, GAS) but is conserved throughout various streptococci. In a deletion strain, expression of mga, the gene encoding the multiple virulence gene regulator, was reduced. Accordingly, transcript and proteome analyses revealed decreased expression of several Mga-activated genes. Therefore, and because the sRNA was shown to interact with the 5' UTR of the mga transcript in a gel-shift assay, we designated it MarS for m ga-activating regulatory sRNA. Down-regulation of important virulence factors, including the antiphagocytic M-protein, led to increased susceptibility of the deletion strain to phagocytosis and reduced adherence to human keratinocytes. In a mouse infection model, the marS deletion mutant showed reduced dissemination to the liver, kidney, and spleen. Additionally, deletion of marS led to increased tolerance towards oxidative stress. Our in vitro and in vivo results indicate a modulating effect of MarS on virulence gene expression and on the pathogenic potential of GAS.

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

Science.gov (United States)

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

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

Science.gov (United States)

Gu, Zuguang; Zhang, Chenyu; Wang, Jin

2012-05-01

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

Paralogous Genes as a Tool to Study the Regulation of Gene Expression

DEFF Research Database (Denmark)

Hoffmann, Robert D

The genomes of plants are marked by reoccurring events of whole-genome duplication. These events are major contributors to speciation and provide the genetic material for organisms to evolve ever greater complexity. Duplicated genes, referred to as paralogs, may be retained because they acquired...... regions. These results suggest that a concurrent purifying selection acts on coding and non-coding sequences of paralogous genes in A. thaliana. Mutational analyses of the promoters from a paralogous gene pair were performed in transgenic A. thaliana plants. The results revealed a 170-bp long DNA sequence...... that forms a bifunctional cis-regulatory module; it represses gene expression in the sporophyte while activating it in pollen. This finding is important for many aspects of gene regulation and the transcriptional changes underlying gametophyte development. In conclusion, the presented thesis suggests that...

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.

Regulatory cross-talks and cascades in rice hormone biosynthesis pathways contribute to stress signaling

Directory of Open Access Journals (Sweden)

Arindam Deb

2016-08-01

Full Text Available Crosstalk among different hormone signaling pathways play an important role in modulating plant response to both biotic and abiotic stress. Hormone activity is controlled by its bio-availability, which is again influenced by its biosynthesis. Thus independent hormone biosynthesis pathways must be regulated and co-ordinated to mount an integrated response. One of the possibilities is to use cis-regulatory elements to orchestrate expression of hormone biosynthesis genes. Analysis of CREs, associated with differentially expressed hormone biosynthesis related genes in rice leaf under Magnaporthe oryzae attack and drought stress enabled us to obtain insights about cross-talk among hormone biosynthesis pathways at the transcriptional level. We identified some master transcription regulators that co-ordinate different hormone biosynthesis pathways under stress. We found that Abscisic acid and Brassinosteroid regulate Cytokinin conjugation; conversely Brassinosteroid biosynthesis is affected by both Abscisic acid and Cytokinin. Jasmonic acid and Ethylene biosynthesis may be modulated by Abscisic acid through DREB transcription factors. Jasmonic acid or Salicylic acid biosynthesis pathways are co-regulated but they are unlikely to influence each other’s production directly. Thus multiple hormones may modulate hormone biosynthesis pathways through a complex regulatory network, where biosynthesis of one hormone is affected by several other contributing hormones.

Brachyury, Foxa2 and the cis-Regulatory Origins of the Notochord.

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Diana S José-Edwards

2015-12-01

Full Text Available A main challenge of modern biology is to understand how specific constellations of genes are activated to differentiate cells and give rise to distinct tissues. This study focuses on elucidating how gene expression is initiated in the notochord, an axial structure that provides support and patterning signals to embryos of humans and all other chordates. Although numerous notochord genes have been identified, the regulatory DNAs that orchestrate development and propel evolution of this structure by eliciting notochord gene expression remain mostly uncharted, and the information on their configuration and recurrence is still quite fragmentary. Here we used the simple chordate Ciona for a systematic analysis of notochord cis-regulatory modules (CRMs, and investigated their composition, architectural constraints, predictive ability and evolutionary conservation. We found that most Ciona notochord CRMs relied upon variable combinations of binding sites for the transcription factors Brachyury and/or Foxa2, which can act either synergistically or independently from one another. Notably, one of these CRMs contains a Brachyury binding site juxtaposed to an (AC microsatellite, an unusual arrangement also found in Brachyury-bound regulatory regions in mouse. In contrast, different subsets of CRMs relied upon binding sites for transcription factors of widely diverse families. Surprisingly, we found that neither intra-genomic nor interspecific conservation of binding sites were reliably predictive hallmarks of notochord CRMs. We propose that rather than obeying a rigid sequence-based cis-regulatory code, most notochord CRMs are rather unique. Yet, this study uncovered essential elements recurrently used by divergent chordates as basic building blocks for notochord CRMs.

Brachyury, Foxa2 and the cis-Regulatory Origins of the Notochord.

Science.gov (United States)

José-Edwards, Diana S; Oda-Ishii, Izumi; Kugler, Jamie E; Passamaneck, Yale J; Katikala, Lavanya; Nibu, Yutaka; Di Gregorio, Anna

2015-12-01

A main challenge of modern biology is to understand how specific constellations of genes are activated to differentiate cells and give rise to distinct tissues. This study focuses on elucidating how gene expression is initiated in the notochord, an axial structure that provides support and patterning signals to embryos of humans and all other chordates. Although numerous notochord genes have been identified, the regulatory DNAs that orchestrate development and propel evolution of this structure by eliciting notochord gene expression remain mostly uncharted, and the information on their configuration and recurrence is still quite fragmentary. Here we used the simple chordate Ciona for a systematic analysis of notochord cis-regulatory modules (CRMs), and investigated their composition, architectural constraints, predictive ability and evolutionary conservation. We found that most Ciona notochord CRMs relied upon variable combinations of binding sites for the transcription factors Brachyury and/or Foxa2, which can act either synergistically or independently from one another. Notably, one of these CRMs contains a Brachyury binding site juxtaposed to an (AC) microsatellite, an unusual arrangement also found in Brachyury-bound regulatory regions in mouse. In contrast, different subsets of CRMs relied upon binding sites for transcription factors of widely diverse families. Surprisingly, we found that neither intra-genomic nor interspecific conservation of binding sites were reliably predictive hallmarks of notochord CRMs. We propose that rather than obeying a rigid sequence-based cis-regulatory code, most notochord CRMs are rather unique. Yet, this study uncovered essential elements recurrently used by divergent chordates as basic building blocks for notochord CRMs.

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.

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

Science.gov (United States)

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.

Transcriptional modulation of genes encoding nitrate reductase in ...

African Journals Online (AJOL)

The free aluminum (Al) content in soil can reach levels that are toxic to plants, and this has frequently limited increased productivity of cultures. Four genes encoding nitrate reductase (NR) were identified, named ZmNR1–4. With the aim of evaluating NR activity and the transcriptional modulation of the ZmNR1, ZmNR2, ...

Microarray meta-analysis to explore abiotic stress-specific gene expression patterns in Arabidopsis.

Science.gov (United States)

Shen, Po-Chih; Hour, Ai-Ling; Liu, Li-Yu Daisy

2017-12-01

Abiotic stresses are the major limiting factors that affect plant growth, development, yield and final quality. Deciphering the underlying mechanisms of plants' adaptations to stresses using few datasets might overlook the different aspects of stress tolerance in plants, which might be simultaneously and consequently operated in the system. Fortunately, the accumulated microarray expression data offer an opportunity to infer abiotic stress-specific gene expression patterns through meta-analysis. In this study, we propose to combine microarray gene expression data under control, cold, drought, heat, and salt conditions and determined modules (gene sets) of genes highly associated with each other according to the observed expression data. By analyzing the expression variations of the Eigen genes from different conditions, we had identified two, three, and five gene modules as cold-, heat-, and salt-specific modules, respectively. Most of the cold- or heat-specific modules were differentially expressed to a particular degree in shoot samples, while most of the salt-specific modules were differentially expressed to a particular degree in root samples. A gene ontology (GO) analysis on the stress-specific modules suggested that the gene modules exclusively enriched stress-related GO terms and that different genes under the same GO terms may be alternatively disturbed in different conditions. The gene regulatory events for two genes, DREB1A and DEAR1, in the cold-specific gene module had also been validated, as evidenced through the literature search. Our protocols study the specificity of the gene modules that were specifically activated under a particular type of abiotic stress. The biplot can also assist to visualize the stress-specific gene modules. In conclusion, our approach has the potential to further elucidate mechanisms in plants and beneficial for future experiments design under different abiotic stresses.

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.

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.

Modulation of DNA binding by gene-specific transcription factors.

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Schleif, Robert F

2013-10-01

The transcription of many genes, particularly in prokaryotes, is controlled by transcription factors whose activity can be modulated by controlling their DNA binding affinity. Understanding the molecular mechanisms by which DNA binding affinity is regulated is important, but because forming definitive conclusions usually requires detailed structural information in combination with data from extensive biophysical, biochemical, and sometimes genetic experiments, little is truly understood about this topic. This review describes the biological requirements placed upon DNA binding transcription factors and their consequent properties, particularly the ways that DNA binding affinity can be modulated and methods for its study. What is known and not known about the mechanisms modulating the DNA binding affinity of a number of prokaryotic transcription factors, including CAP and lac repressor, is provided.

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.

Liver X Receptor Genes Variants Modulate ALS Phenotype.

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Mouzat, Kevin; Molinari, Nicolas; Kantar, Jovana; Polge, Anne; Corcia, Philippe; Couratier, Philippe; Clavelou, Pierre; Juntas-Morales, Raul; Pageot, Nicolas; Lobaccaro, Jean -Marc A; Raoul, Cedric; Lumbroso, Serge; Camu, William

2018-03-01

Amyotrophic lateral sclerosis (ALS) is one of the most severe motor neuron (MN) disorders in adults. Phenotype of ALS patients is highly variable and may be influenced by modulators of energy metabolism. Recent works have implicated the liver X receptors α and β (LXRs), either in the propagation process of ALS or in the maintenance of MN survival. LXRs are nuclear receptors activated by oxysterols, modulating cholesterol levels, a suspected modulator of ALS severity. In a cohort of 438 ALS patients and 330 healthy controls, the influence of LXR genes on ALS risk and phenotype was studied using single nucleotide polymorphisms (SNPs). The two LXRα SNPs rs2279238 and rs7120118 were shown to be associated with age at onset in ALS patients. Consistently, homozygotes were twice more correlated than were heterozygotes to delayed onset. The onset was thus delayed by 3.9 years for rs2279238 C/T carriers and 7.8 years for T/T carriers. Similar results were obtained for rs7120118 (+2.1 years and +6.7 years for T/C and C/C genotypes, respectively). The LXRβ SNP rs2695121 was also shown to be associated with a 30% increase of ALS duration (p = 0.0055, FDR = 0.044). The tested genotypes were not associated with ALS risk. These findings add further evidence to the suspected implication of LXR genes in the disease process of ALS and might open new perspectives in ALS therapeutics.

Importância de polimorfismos de genes reguladores de citocinas em transplantes de células progenitoras hematopoiéticas Importance of regulatory cytokine gene polymorphisms in hematopoietic stem cell transplantation

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Jeane Eliete Laguila Visentainer

2008-12-01

Full Text Available A compatibilidade genética HLA entre doador e receptor é um fator importante para o sucesso do transplante de células progenitoras hematopoiéticas (TCPH. No entanto, outros genes não-HLA estão sendo investigados em relação ao seu papel na incidência e gravidade da doença do enxerto contra o hospedeiro e na sobrevida, por modularem a intensidade da inflamação e os danos teciduais. Estes genes, não-HLA, incluem os genes de citocinas com polimorfismos dentro das seqüências 5' ou 3' regulatórias dos genes. Os polimorfismos ou microssatélites podem alterar a ligação dos fatores de transcrição aos sítios dentro dos genes promotores e a quantidade de citocina produzida. Este estudo revisa o papel potencial destes polimorfismos genéticos relativos às citocinas em prever o curso do TCPH.HLA genetic matching of donor and recipient is an important requirement for optimizing outcome following hematopoietic stem cell transplantation (HSCT. However, other non-HLA genes are being investigated for their role in graft-versus-host disease incidence and severity and in survival, by modulating the intensity of inflammation and tissue injury. These non-HLA-encoded genes include cytokine genes with polymorphisms within the 5' or 3' regulatory sequences of the genes. The polymorphisms or microsatellites may alter the transcription factor binding sites within the gene promoters and the amount of cytokine produced. This chapter summarizes the potential role of these genetic polymorphisms regarding the cytokines in predicting outcome of HSCT.

Fusobacterium nucleatum binding to complement regulatory protein CD46 modulates the expression and secretion of cytokines and matrix metalloproteinases by oral epithelial cells.

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Mahtout, Hayette; Chandad, Fatiha; Rojo, Jose M; Grenier, Daniel

2011-02-01

Periodontitis is a chronic inflammatory disease that results in the destruction of the supporting tissues of the teeth. Gingival epithelial cells are an important mechanical barrier and participate in the host inflammatory response to periodontopathogens. The aim of the present study is to investigate the capacity of Fusobacterium nucleatum to bind to the complement regulatory protein CD46 expressed by oral epithelial cells and to determine the impact of the binding on the gene expression and protein secretion of interleukin (IL)-6, IL-8, and matrix metalloproteinase (MMP)-9 by oral epithelial cells. Binding of recombinant human CD46 to the surface of F. nucleatum was demonstrated by immunologic assays. After stimulation of oral epithelial cells with F. nucleatum, gene expression was determined by real-time polymerase chain reaction analysis while protein secretion was monitored by enzyme-linked immunosorbent assays. Heat and protease treatments of bacterial cells reduced CD46 binding. F. nucleatum-bound CD46 mediated the cleavage of C3b in the presence of factor I. Stimulating oral epithelial cells with F. nucleatum at a multiplicity of infection of 50 resulted in a significant upregulation of the gene expression and protein secretion of IL-6, IL-8, and MMP-9 by oral epithelial cells. However, pretreating the epithelial cells with an anti-CD46 polyclonal antibody attenuated the production of IL-6, IL-8, and MMP-9 in response to F. nucleatum. Such an inhibitory effect was not observed with non-specific antibodies. The present study demonstrates that F. nucleatum can bind the complement regulatory protein CD46. The interaction of F. nucleatum with epithelial cell surface CD46 may contribute to increasing the levels of proinflammatory mediators and MMPs in periodontal sites and consequently modulate tissue destruction.

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.

E3L and F1L Gene Functions Modulate the Protective Capacity of Modified Vaccinia Virus Ankara Immunization in Murine Model of Human Smallpox

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Asisa Volz

2018-01-01

Full Text Available The highly attenuated Modified Vaccinia virus Ankara (MVA lacks most of the known vaccinia virus (VACV virulence and immune evasion genes. Today MVA can serve as a safety-tested next-generation smallpox vaccine. Yet, we still need to learn about regulatory gene functions preserved in the MVA genome, such as the apoptosis inhibitor genes F1L and E3L. Here, we tested MVA vaccine preparations on the basis of the deletion mutant viruses MVA-ΔF1L and MVA-ΔE3L for efficacy against ectromelia virus (ECTV challenge infections in mice. In non-permissive human tissue culture the MVA deletion mutant viruses produced reduced levels of the VACV envelope antigen B5. Upon mousepox challenge at three weeks after vaccination, MVA-ΔF1L and MVA-ΔE3L exhibited reduced protective capacity in comparison to wildtype MVA. Surprisingly, however, all vaccines proved equally protective against a lethal ECTV infection at two days after vaccination. Accordingly, the deletion mutant MVA vaccines induced high levels of virus-specific CD8+ T cells previously shown to be essential for rapidly protective MVA vaccination. These results suggest that inactivation of the anti-apoptotic genes F1L or E3L modulates the protective capacity of MVA vaccination most likely through the induction of distinct orthopoxvirus specific immunity in the absence of these viral regulatory proteins.

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.

The regulatory effects of low-dose ionizing radiation on Ikaros-autotaxin interaction

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Kang, Hana; Cho, Seong Jun; Kim, Sung Jin; Nam, Seon Young; Yang, Kwang Hee [KHNP Radiation Health Institute, Korea Hydro and Nuclear Power Co, Seoul (Korea, Republic of)

2016-11-15

Ikaros, a transcription factor containing zinc-finger motif, has known as a critical regulator of hematopoiesis in immune system. Ikaros protein modulates the transcription of target genes via binding to the regulatory elements of the genes promoters. However the regulatory function of Ikaros in other organelle except nuclear remains to be determined. This study explored radiation-induced modulatory function of Ikaros in cytoplasm. The results showed that Ikaros protein lost its DNA binding ability after LDIR (low-dose ionizing radiation) exposure. Cell fractionation and Western blot analysis showed that Ikaros protein was translocated into cytoplasm from nuclear by LDIR. This was confirmed by immunofluorescence assay. We identified Autotaxin as a novel protein which potentially interacts with Ikaros through in vitro protein-binding screening. Co-immunoprecipitation assay revealed that Ikaros and Autotaxin are able to bind each other. Autotaxin is a crucial enzyme generating lysophosphatidic acid (LPA), a phospholipid mediator, which has potential regulatory effects on immune cell growth and motility. Our results indicate that LDIR potentially regulates immune system via protein-protein interaction of Ikaros and Autotaxin.

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

Clock gene modulates roles of OXTR and AVPR1b genes in prosociality.

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Haipeng Ci

Full Text Available BACKGROUND: The arginine vasopressin receptor (AVPR and oxytocin receptor (OXTR genes have been demonstrated to contribute to prosocial behavior. Recent research has focused on the manner by which these simple receptor genes influence prosociality, particularly with regard to the AVP system, which is modulated by the clock gene. The clock gene is responsible for regulating the human biological clock, affecting sleep, emotion and behavior. The current study examined in detail whether the influences of the OXTR and AVPR1b genes on prosociality are dependent on the clock gene. METHODOLOGY/PRINCIPAL FINDINGS: This study assessed interactions between the clock gene (rs1801260, rs6832769 and the OXTR (rs1042778, rs237887 and AVPR1b (rs28373064 genes in association with individual differences in prosociality in healthy male Chinese subjects (n = 436. The Prosocial Tendencies Measure (PTM-R was used to assess prosociality. Participants carrying both the GG/GA variant of AVPR1b rs28373064 and the AA variant of clock rs6832769 showed the highest scores on the Emotional PTM. Carriers of both the T allele of OXTR rs1042778 and the C allele of clock rs1801260 showed the lowest total PTM scores compared with the other groups. CONCLUSIONS: The observed interaction effects provide converging evidence that the clock gene and OXT/AVP systems are intertwined and contribute to human prosociality.

Clock gene modulates roles of OXTR and AVPR1b genes in prosociality.

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Ci, Haipeng; Wu, Nan; Su, Yanjie

2014-01-01

The arginine vasopressin receptor (AVPR) and oxytocin receptor (OXTR) genes have been demonstrated to contribute to prosocial behavior. Recent research has focused on the manner by which these simple receptor genes influence prosociality, particularly with regard to the AVP system, which is modulated by the clock gene. The clock gene is responsible for regulating the human biological clock, affecting sleep, emotion and behavior. The current study examined in detail whether the influences of the OXTR and AVPR1b genes on prosociality are dependent on the clock gene. This study assessed interactions between the clock gene (rs1801260, rs6832769) and the OXTR (rs1042778, rs237887) and AVPR1b (rs28373064) genes in association with individual differences in prosociality in healthy male Chinese subjects (n = 436). The Prosocial Tendencies Measure (PTM-R) was used to assess prosociality. Participants carrying both the GG/GA variant of AVPR1b rs28373064 and the AA variant of clock rs6832769 showed the highest scores on the Emotional PTM. Carriers of both the T allele of OXTR rs1042778 and the C allele of clock rs1801260 showed the lowest total PTM scores compared with the other groups. The observed interaction effects provide converging evidence that the clock gene and OXT/AVP systems are intertwined and contribute to human prosociality.

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

Role of plant MicroRNA in cross-species regulatory networks of humans.

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Zhang, Hao; Li, Yanpu; Liu, Yuanning; Liu, Haiming; Wang, Hongyu; Jin, Wen; Zhang, Yanmei; Zhang, Chao; Xu, Dong

2016-08-08

It has been found that microRNAs (miRNAs) can function as a regulatory factor across species. For example, food-derived plant miRNAs may pass through the gastrointestinal (GI) tract, enter into the plasma and serum of mammals, and interact with endogenous RNAs to regulate their expression. Although this new type of regulatory mechanism is not well understood, it provides a fresh look at the relationship between food consumption and physiology. To investigate this new type of mechanism, we conducted a systematic computational study to analyze the potential functions of these dietary miRNAs in the human body. In this paper, we predicted human and plant target genes using RNAhybrid and set some criteria to further filter them. Then we built the cross-species regulatory network according to the filtered targets, extracted central nodes by PageRank algorithm and built core modules. We summarized the functions of these modules to three major categories: ion transport, metabolic process and stress response, and especially some target genes are highly related to ion transport, polysaccharides and the lipid metabolic process. Through functional analysis, we found that human and plants have similar functions such as ion transport and stress response, so our study also indicates the existence of a close link between exogenous plant miRNA targets and digestive/urinary organs. According to our analysis results, we suggest that the ingestion of these plant miRNAs may have a functional impact on consuming organisms in a cross-kingdom way, and the dietary habit may affect the physiological condition at a genetic level. Our findings may be useful for discovering cross-species regulatory mechanism in further study.

ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis

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Saurav Mallik

2017-12-01

Full Text Available For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures—weighted rank-based Jaccard and Cosine measures—and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm—RANWAR—was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

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Mallik, Saurav; Zhao, Zhongming

2017-12-28

For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations.

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Xin Wang

Full Text Available Combinatorial gene perturbations provide rich information for a systematic exploration of genetic interactions. Despite successful applications to bacteria and yeast, the scalability of this approach remains a major challenge for higher organisms such as humans. Here, we report a novel experimental and computational framework to efficiently address this challenge by limiting the 'search space' for important genetic interactions. We propose to integrate rich phenotypes of multiple single gene perturbations to robustly predict functional modules, which can subsequently be subjected to further experimental investigations such as combinatorial gene silencing. We present posterior association networks (PANs to predict functional interactions between genes estimated using a Bayesian mixture modelling approach. The major advantage of this approach over conventional hypothesis tests is that prior knowledge can be incorporated to enhance predictive power. We demonstrate in a simulation study and on biological data, that integrating complementary information greatly improves prediction accuracy. To search for significant modules, we perform hierarchical clustering with multiscale bootstrap resampling. We demonstrate the power of the proposed methodologies in applications to Ewing's sarcoma and human adult stem cells using publicly available and custom generated data, respectively. In the former application, we identify a gene module including many confirmed and highly promising therapeutic targets. Genes in the module are also significantly overrepresented in signalling pathways that are known to be critical for proliferation of Ewing's sarcoma cells. In the latter application, we predict a functional network of chromatin factors controlling epidermal stem cell fate. Further examinations using ChIP-seq, ChIP-qPCR and RT-qPCR reveal that the basis of their genetic interactions may arise from transcriptional cross regulation. A Bioconductor package

Mutation screening of brain-expressed X-chromosomal miRNA genes in 464 patients with nonsyndromic X-linked mental retardation.

NARCIS (Netherlands)

Chen, W.; Jensen, L.R.; Gecz, J.; Fryns, J.P.; Moraine, C.; Brouwer, A.; Chelly, J.; Moser, B.; Ropers, H.H.; Kuss, A.W.

2007-01-01

MiRNAs are small noncoding RNAs that control the expression of target genes at the post-transcriptional level and have been reported to modulate various biological processes. Their function as regulatory factors in gene expression renders them attractive candidates for harbouring genetic variants

Using scale and feather traits for module construction provides a functional approach to chicken epidermal development.

Science.gov (United States)

Bao, Weier; Greenwold, Matthew J; Sawyer, Roger H

2017-11-01

Gene co-expression network analysis has been a research method widely used in systematically exploring gene function and interaction. Using the Weighted Gene Co-expression Network Analysis (WGCNA) approach to construct a gene co-expression network using data from a customized 44K microarray transcriptome of chicken epidermal embryogenesis, we have identified two distinct modules that are highly correlated with scale or feather development traits. Signaling pathways related to feather development were enriched in the traditional KEGG pathway analysis and functional terms relating specifically to embryonic epidermal development were also enriched in the Gene Ontology analysis. Significant enrichment annotations were discovered from customized enrichment tools such as Modular Single-Set Enrichment Test (MSET) and Medical Subject Headings (MeSH). Hub genes in both trait-correlated modules showed strong specific functional enrichment toward epidermal development. Also, regulatory elements, such as transcription factors and miRNAs, were targeted in the significant enrichment result. This work highlights the advantage of this methodology for functional prediction of genes not previously associated with scale- and feather trait-related modules.

Engineering nucleases for gene targeting: safety and regulatory considerations.

Science.gov (United States)

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.

Identification of Gene Modules Associated with Low Temperatures Response in Bambara Groundnut by Network-Based Analysis.

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Venkata Suresh Bonthala

Full Text Available Bambara groundnut (Vigna subterranea (L. Verdc. is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01 under the sub-optimal (23°C and very sub-optimal (18°C temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties.

Vision from next generation sequencing: multi-dimensional genome-wide analysis for producing gene regulatory networks underlying retinal development, aging and disease.

Science.gov (United States)

Yang, Hyun-Jin; Ratnapriya, Rinki; Cogliati, Tiziana; Kim, Jung-Woong; Swaroop, Anand

2015-05-01

Genomics and genetics have invaded all aspects of biology and medicine, opening uncharted territory for scientific exploration. The definition of "gene" itself has become ambiguous, and the central dogma is continuously being revised and expanded. Computational biology and computational medicine are no longer intellectual domains of the chosen few. Next generation sequencing (NGS) technology, together with novel methods of pattern recognition and network analyses, has revolutionized the way we think about fundamental biological mechanisms and cellular pathways. In this review, we discuss NGS-based genome-wide approaches that can provide deeper insights into retinal development, aging and disease pathogenesis. We first focus on gene regulatory networks (GRNs) that govern the differentiation of retinal photoreceptors and modulate adaptive response during aging. Then, we discuss NGS technology in the context of retinal disease and develop a vision for therapies based on network biology. We should emphasize that basic strategies for network construction and analyses can be transported to any tissue or cell type. We believe that specific and uniform guidelines are required for generation of genome, transcriptome and epigenome data to facilitate comparative analysis and integration of multi-dimensional data sets, and for constructing networks underlying complex biological processes. As cellular homeostasis and organismal survival are dependent on gene-gene and gene-environment interactions, we believe that network-based biology will provide the foundation for deciphering disease mechanisms and discovering novel drug targets for retinal neurodegenerative diseases. Published by Elsevier Ltd.

Generic Properties of Random Gene Regulatory Networks.

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

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

Directory of Open Access Journals (Sweden)

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

Systematic Assessment of Regulatory Competences (SARCON) V18a

International Nuclear Information System (INIS)

Zimmermann, Moritz

2014-01-01

Why Competence Management? • Arrangements for competence management is a key factor to: • Support the implementation of article 8 of CNS (Convention on Nuclear Safety – “regulatory body with adequate competence and human resources”); • Support the implementation of Modules 3 and 4 of the IRRS and other IAEA Safety Standards (Module 3: “Responsibilities and functions of the regulatory body”, Module 4: “Management system of the regulatory body”); • Identify gaps between regulatory required competences and the existing resources; • Develop and implement tools and programmes to fill the gaps; • Review periodically the competence needs and training programmes

Regulatory elements involved in tax-mediated transactivation of the HTLV-I LTR.

Science.gov (United States)

Seeler, J S; Muchardt, C; Podar, M; Gaynor, R B

1993-10-01

HTLV-I is the etiologic agent of adult T-cell leukemia. In this study, we investigated the regulatory elements and cellular transcription factors which function in modulating HTLV-I gene expression in response to the viral transactivator protein, tax. Transfection experiments into Jurkat cells of a variety of site-directed mutants in the HTLV-1 LTR indicated that each of the three motifs A, B, and C within the 21-bp repeats, the binding sites for the Ets family of proteins, and the TATA box all influenced the degree of tax-mediated activation. Tax is also able to activate gene expression of other viral and cellular promoters. Tax activation of the IL-2 receptor and the HIV-1 LTR is mediated through NF-kappa B motifs. Interestingly, sequences in the 21-bp repeat B and C motifs contain significant homology with NF-kappa B regulatory elements. We demonstrated that an NF-kappa B binding protein, PRDII-BF1, but not the rel protein, bound to the B and C motifs in the 21-bp repeat. PRDII-BF1 was also able to stimulate activation of HTLV-I gene expression by tax. The role of the Ets proteins on modulating tax activation was also studied. Ets 1 but not Ets 2 was capable of increasing the degree of tax activation of the HTLV-I LTR. These results suggest that tax activates gene expression by either direct or indirect interaction with several cellular transcription factors that bind to the HTLV-I LTR.

Conserved regulatory modules in the Sox9 testis-specific enhancer predict roles for SOX, TCF/LEF, Forkhead, DMRT, and GATA proteins in vertebrate sex determination.

Science.gov (United States)

Bagheri-Fam, Stefan; Sinclair, Andrew H; Koopman, Peter; Harley, Vincent R

2010-03-01

While the primary sex determining switch varies between vertebrate species, a key downstream event in testicular development, namely the male-specific up-regulation of Sox9, is conserved. To date, only two sex determining switch genes have been identified, Sry in mammals and the Dmrt1-related gene Dmy (Dmrt1bY) in the medaka fish Oryzias latipes. In mice, Sox9 expression is evidently up-regulated by SRY and maintained by SOX9 both of which directly activate the core 1.3 kb testis-specific enhancer of Sox9 (TESCO). How Sox9 expression is up-regulated and maintained in species without Sry (i.e. non-mammalian species) is not understood. In this study, we have undertaken an in-depth comparative genomics approach and show that TESCO contains an evolutionarily conserved region (ECR) of 180 bp which is present in marsupials, monotremes, birds, reptiles and amphibians. The ECR contains highly conserved modules that predict regulatory roles for SOX, TCF/LEF, Forkhead, DMRT, and GATA proteins in vertebrate sex determination/differentiation. Our data suggest that tetrapods share common aspects of Sox9 regulation in the testis, despite having different sex determining switch mechanisms. They also suggest that Sox9 autoregulation is an ancient mechanism shared by all tetrapods, raising the possibility that in mammals, SRY evolved by mimicking this regulation. The validation of ECR regulatory sequences conserved from human to frogs will provide new insights into vertebrate sex determination. Copyright 2009 Elsevier Ltd. All rights reserved.

Genetic variation in glia-neuron signalling modulates ageing rate.

Science.gov (United States)

Yin, Jiang-An; Gao, Ge; Liu, Xi-Juan; Hao, Zi-Qian; Li, Kai; Kang, Xin-Lei; Li, Hong; Shan, Yuan-Hong; Hu, Wen-Li; Li, Hai-Peng; Cai, Shi-Qing

2017-11-08

The rate of behavioural decline in the ageing population is remarkably variable among individuals. Despite the considerable interest in studying natural variation in ageing rate to identify factors that control healthy ageing, no such factor has yet been found. Here we report a genetic basis for variation in ageing rates in Caenorhabditis elegans. We find that C. elegans isolates show diverse lifespan and age-related declines in virility, pharyngeal pumping, and locomotion. DNA polymorphisms in a novel peptide-coding gene, named regulatory-gene-for-behavioural-ageing-1 (rgba-1), and the neuropeptide receptor gene npr-28 influence the rate of age-related decline of worm mating behaviour; these two genes might have been subjected to recent selective sweeps. Glia-derived RGBA-1 activates NPR-28 signalling, which acts in serotonergic and dopaminergic neurons to accelerate behavioural deterioration. This signalling involves the SIR-2.1-dependent activation of the mitochondrial unfolded protein response, a pathway that modulates ageing. Thus, natural variation in neuropeptide-mediated glia-neuron signalling modulates the rate of ageing in C. elegans.

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

Science.gov (United States)

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.

Gene Therapy With Regulatory T Cells: A Beneficial Alliance

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

Mechanosensitive promoter region in the human HB-GAM gene

DEFF Research Database (Denmark)

Liedert, Astrid; Kassem, Moustapha; Claes, Lutz

2009-01-01

Mechanical loading is essential for maintaining bone mass in the adult skeleton. However, the underlying process of the transfer of the physical stimulus into a biochemical response, which is termed mechanotransduction is poorly understood. Mechanotransduction results in the modulation of gene...... cells. Analysis of the human HB-GAM gene upstream regulatory region with luciferase reporter gene assays revealed that the upregulation of HB-GAM expression occurred at the transcriptional level and was mainly dependent on the HB-GAM promoter region most upstream containing three potential AP-1 binding...

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

Science.gov (United States)

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Regulatory RNA at the root of animals: dynamic expression of developmental lincRNAs in the calcisponge Sycon ciliatum.

Science.gov (United States)

Bråte, Jon; Adamski, Marcin; Neumann, Ralf S; Shalchian-Tabrizi, Kamran; Adamska, Maja

2015-12-22

Long non-coding RNAs (lncRNAs) play important regulatory roles during animal development, and it has been hypothesized that an RNA-based gene regulation was important for the evolution of developmental complexity in animals. However, most studies of lncRNA gene regulation have been performed using model animal species, and very little is known about this type of gene regulation in non-bilaterians. We have therefore analysed RNA-Seq data derived from a comprehensive set of embryogenesis stages in the calcareous sponge Sycon ciliatum and identified hundreds of developmentally expressed intergenic lncRNAs (lincRNAs) in this species. In situ hybridization of selected lincRNAs revealed dynamic spatial and temporal expression during embryonic development. More than 600 lincRNAs constitute integral parts of differentially expressed gene modules, which also contain known developmental regulatory genes, e.g. transcription factors and signalling molecules. This study provides insights into the non-coding gene repertoire of one of the earliest evolved animal lineages, and suggests that RNA-based gene regulation was probably present in the last common ancestor of animals. © 2015 The Authors.

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

Science.gov (United States)

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.