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Sample records for eukaryotic gene regulatory

  1. [Construction of eukaryotic expression plasmid for mouse myogenic regulatory factor MyoD gene].

    Science.gov (United States)

    Qin, R F; Gu, X M; Chen, J W

    2001-09-01

    To construct eukaryotic expression plasmid of mouse myogenic regulatory factor MyoD gene for further study on MyoD gene function in molecular regulatory mechanism in skeletal muscle repair. The plasmids PEMMBC2 beta 5 containing full cDNA length of MyoD inserted in EcoRI restriction site, were first propagated in Escherichia coli DH5a, then extracted and purified with the Wizard Plus Minipreps DNA Purification System (Promega, USA). The coding sequence of MyoD in PEMMBC2 beta 5 was confirmed by agarose gel electrophoresis and DNA sequence analysis. After plasmids PEMMBC2 beta 5 and plasmids pcDNA3-neo were prepared by digestion with EcoRI, the MyoD cDNA fragment was inserted into EcoRI site in pcDNA3-neo eukaryotic expression vector, and pcDNA3/MyoD was formed. The pcDNA3/MyoD, digested with restriction enzymes, was found to contain the MyoD cDNA sequence by agarose gel electrophoresis analysis. The extracted and purified PEMMBC2 beta 5 contained the correct nucleotide sequence for the full length of MyoD cDNA fragment. The MyoD cDNA fragment had been inserted into the eukaryotic expression plasmid pcDNA3-neo, which formed the pcDNA3/MyoD. The pcDNA3/MyoD, a eukaryotic expression plasmid, for MyoD is constructed successfully.

  2. Structural and dynamic characterization of eukaryotic gene regulatory protein domains in solution

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    Lee, Andrew Loyd [Univ. of California, Berkeley, CA (United States). Dept. of Chemistry

    1996-05-01

    Solution NMR was primarily used to characterize structure and dynamics in two different eukaryotic protein systems: the δ-Al-ε activation domain from c-jun and the Drosophila RNA-binding protein Sex-lethal. The second system is the Drosophila Sex-lethal (Sxl) protein, an RNA-binding protein which is the ``master switch`` in sex determination. Sxl contains two adjacent RNA-binding domains (RBDs) of the RNP consensus-type. The NMR spectrum of the second RBD (Sxl-RBD2) was assigned using multidimensional heteronuclear NMR, and an intermediate-resolution family of structures was calculated from primarily NOE distance restraints. The overall fold was determined to be similar to other RBDs: a βαβ-βαβ pattern of secondary structure, with the two helices packed against a 4-stranded anti-parallel β-sheet. In addition 15N T1, T2, and 15N/1H NOE relaxation measurements were carried out to characterize the backbone dynamics of Sxl-RBD2 in solution. RNA corresponding to the polypyrimidine tract of transformer pre-mRNA was generated and titrated into 3 different Sxl-RBD protein constructs. Combining Sxl-RBD1+2 (bht RBDs) with this RNA formed a specific, high affinity protein/RNA complex that is amenable to further NMR characterization. The backbone 1H, 13C, and 15N resonances of Sxl-RBD1+2 were assigned using a triple-resonance approach, and 15N relaxation experiments were carried out to characterize the backbone dynamics of this complex. The changes in chemical shift in Sxl-RBD1+2 upon binding RNA are observed using Sxl-RBD2 as a substitute for unbound Sxl-RBD1+2. This allowed the binding interface to be qualitatively mapped for the second domain.

  3. Silencing or knocking out eukaryotic gene expression by oligodeoxynucleotide decoys.

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    Cutroneo, Kenneth R; Ehrlich, H

    2006-01-01

    The elucidation of molecular and signaling pathways in eukaryotic cells is often achieved by targeting regulatory element(s) found in the promoter or the enhancer region of eukaryotic gene(s) using a double-stranded (ds) oligodeoxynucleotide (ODN) containing a specific cis-element. Our laboratory is focusing on dsODN decoys containing the TGF-beta element as a novel nonsteroidal antifibrotic for achieving normal wound healing. In the model systems discussed, there is either a specific gene possessing a specific cis-element or a cluster of genes with one gene containing the consensus cis-element. The rest of the genes in the cluster contain the cis-elements homologous to this consensus element, which allows for dsODN decoy regulation of a gene cluster at one time.

  4. Chromatin—a global buffer for eukaryotic gene control

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    Yuri M. Moshkin

    2015-09-01

    Full Text Available Most of eukaryotic DNA is embedded into nucleosome arrays formed by DNA wrapped around a core histone octamer. Nucleosome is a fundamental repeating unit of chromatin guarding access to the genetic information. Here, I will discuss two facets of nucleosome in eukaryotic gene control. On the one hand, nucleosome acts as a regulatory unit, which controls gene switches through a set of post-translational modifications occurring on histone tails. On the other hand, global configuration of nucleosome arrays with respect to nucleosome positioning, spacing and turnover acts as a tuning parameter for all genomic functions. A “histone code” hypothesis extents the Jacob-Monod model for eukaryotic gene control; however, when considering factors capable of reconfiguring entire nucleosome array, such as ATP-dependent chromatin remodelers, this model becomes limited. Global changes in nucleosome arrays will be sensed by every gene, yet the transcriptional responses might be specific and appear as gene targeted events. What determines such specificity is unclear, but it’s likely to depend on initial gene settings, such as availability of transcription factors, and on configuration of new nucleosome array state.

  5. Horizontal gene transfer in eukaryotic plant pathogens.

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    Soanes, Darren; Richards, Thomas A

    2014-01-01

    Gene transfer has been identified as a prevalent and pervasive phenomenon and an important source of genomic innovation in bacteria. The role of gene transfer in microbial eukaryotes seems to be of a reduced magnitude but in some cases can drive important evolutionary innovations, such as new functions that underpin the colonization of different niches. The aim of this review is to summarize published cases that support the hypothesis that horizontal gene transfer (HGT) has played a role in the evolution of phytopathogenic traits in fungi and oomycetes. Our survey of the literature identifies 46 proposed cases of transfer of genes that have a putative or experimentally demonstrable phytopathogenic function. When considering the life-cycle steps through which a pathogen must progress, the majority of the HGTs identified are associated with invading, degrading, and manipulating the host. Taken together, these data suggest HGT has played a role in shaping how fungi and oomycetes colonize plant hosts.

  6. Patterns of prokaryotic lateral gene transfers affecting parasitic microbial eukaryotes

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    Alsmark, Cecilia; Foster, Peter G; Sicheritz-Pontén, Thomas

    2013-01-01

    BACKGROUND: The influence of lateral gene transfer on gene origins and biology in eukaryotes is poorly understood compared with those of prokaryotes. A number of independent investigations focusing on specific genes, individual genomes, or specific functional categories from various eukaryotes have...... indicated that lateral gene transfer does indeed affect eukaryotic genomes. However, the lack of common methodology and criteria in these studies makes it difficult to assess the general importance and influence of lateral gene transfer on eukaryotic genome evolution. RESULTS: We used a phylogenomic...... approach to systematically investigate lateral gene transfer affecting the proteomes of thirteen, mainly parasitic, microbial eukaryotes, representing four of the six eukaryotic super-groups. All of the genomes investigated have been significantly affected by prokaryote-to-eukaryote lateral gene transfers...

  7. Horizontal gene transfer in eukaryotes: The weak-link model

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    Huang, Jinling

    2013-01-01

    The significance of horizontal gene transfer (HGT) in eukaryotic evolution remains controversial. Although many eukaryotic genes are of bacterial origin, they are often interpreted as being derived from mitochondria or plastids. Because of their fixed gene pool and gene loss, however, mitochondria and plastids alone cannot adequately explain the presence of all, or even the majority, of bacterial genes in eukaryotes. Available data indicate that no insurmountable barrier to HGT exists, even in complex multicellular eukaryotes. In addition, the discovery of both recent and ancient HGT events in all major eukaryotic groups suggests that HGT has been a regular occurrence throughout the history of eukaryotic evolution. A model of HGT is proposed that suggests both unicellular and early developmental stages as likely entry points for foreign genes into multicellular eukaryotes. PMID:24037739

  8. Integrated databases and computer systems for studying eukaryotic gene expression.

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    Kolchanov, N A; Ponomarenko, M P; Frolov, A S; Ananko, E A; Kolpakov, F A; Ignatieva, E V; Podkolodnaya, O A; Goryachkovskaya, T N; Stepanenko, I L; Merkulova, T I; Babenko, V V; Ponomarenko, Y V; Kochetov, A V; Podkolodny, N L; Vorobiev, D V; Lavryushev, S V; Grigorovich, D A; Kondrakhin, Y V; Milanesi, L; Wingender, E; Solovyev, V; Overton, G C

    1999-01-01

    The goal of the work was to develop a WWW-oriented computer system providing a maximal integration of informational and software resources on the regulation of gene expression and navigation through them. Rapid growth of the variety and volume of information accumulated in the databases on regulation of gene expression necessarily requires the development of computer systems for automated discovery of the knowledge that can be further used for analysis of regulatory genomic sequences. The GeneExpress system developed includes the following major informational and software modules: (1) Transcription Regulation (TRRD) module, which contains the databases on transcription regulatory regions of eukaryotic genes and TRRD Viewer for data visualization; (2) Site Activity Prediction (ACTIVITY), the module for analysis of functional site activity and its prediction; (3) Site Recognition module, which comprises (a) B-DNA-VIDEO system for detecting the conformational and physicochemical properties of DNA sites significant for their recognition, (b) Consensus and Weight Matrices (ConsFrec) and (c) Transcription Factor Binding Sites Recognition (TFBSR) systems for detecting conservative contextual regions of functional sites and their recognition; (4) Gene Networks (GeneNet), which contains an object-oriented database accumulating the data on gene networks and signal transduction pathways, and the Java-based Viewer for exploration and visualization of the GeneNet information; (5) mRNA Translation (Leader mRNA), designed to analyze structural and contextual properties of mRNA 5'-untranslated regions (5'-UTRs) and predict their translation efficiency; (6) other program modules designed to study the structure-function organization of regulatory genomic sequences and regulatory proteins. GeneExpress is available at http://wwwmgs.bionet.nsc. ru/systems/GeneExpress/ and the links to the mirror site(s) can be found at http://wwwmgs.bionet.nsc.ru/mgs/links/mirrors.html+ ++.

  9. Endosymbiotic gene transfer from prokaryotic pangenomes: Inherited chimerism in eukaryotes.

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    Ku, Chuan; Nelson-Sathi, Shijulal; Roettger, Mayo; Garg, Sriram; Hazkani-Covo, Einat; Martin, William F

    2015-08-18

    Endosymbiotic theory in eukaryotic-cell evolution rests upon a foundation of three cornerstone partners--the plastid (a cyanobacterium), the mitochondrion (a proteobacterium), and its host (an archaeon)--and carries a corollary that, over time, the majority of genes once present in the organelle genomes were relinquished to the chromosomes of the host (endosymbiotic gene transfer). However, notwithstanding eukaryote-specific gene inventions, single-gene phylogenies have never traced eukaryotic genes to three single prokaryotic sources, an issue that hinges crucially upon factors influencing phylogenetic inference. In the age of genomes, single-gene trees, once used to test the predictions of endosymbiotic theory, now spawn new theories that stand to eventually replace endosymbiotic theory with descriptive, gene tree-based variants featuring supernumerary symbionts: prokaryotic partners distinct from the cornerstone trio and whose existence is inferred solely from single-gene trees. We reason that the endosymbiotic ancestors of mitochondria and chloroplasts brought into the eukaryotic--and plant and algal--lineage a genome-sized sample of genes from the proteobacterial and cyanobacterial pangenomes of their respective day and that, even if molecular phylogeny were artifact-free, sampling prokaryotic pangenomes through endosymbiotic gene transfer would lead to inherited chimerism. Recombination in prokaryotes (transduction, conjugation, transformation) differs from recombination in eukaryotes (sex). Prokaryotic recombination leads to pangenomes, and eukaryotic recombination leads to vertical inheritance. Viewed from the perspective of endosymbiotic theory, the critical transition at the eukaryote origin that allowed escape from Muller's ratchet--the origin of eukaryotic recombination, or sex--might have required surprisingly little evolutionary innovation.

  10. Conservation and implications of eukaryote transcriptional regulatory regions across multiple species

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    Deng Minghua

    2008-12-01

    Full Text Available Abstract Background Increasing evidence shows that whole genomes of eukaryotes are almost entirely transcribed into both protein coding genes and an enormous number of non-protein-coding RNAs (ncRNAs. Therefore, revealing the underlying regulatory mechanisms of transcripts becomes imperative. However, for a complete understanding of transcriptional regulatory mechanisms, we need to identify the regions in which they are found. We will call these transcriptional regulation regions, or TRRs, which can be considered functional regions containing a cluster of regulatory elements that cooperatively recruit transcriptional factors for binding and then regulating the expression of transcripts. Results We constructed a hierarchical stochastic language (HSL model for the identification of core TRRs in yeast based on regulatory cooperation among TRR elements. The HSL model trained based on yeast achieved comparable accuracy in predicting TRRs in other species, e.g., fruit fly, human, and rice, thus demonstrating the conservation of TRRs across species. The HSL model was also used to identify the TRRs of genes, such as p53 or OsALYL1, as well as microRNAs. In addition, the ENCODE regions were examined by HSL, and TRRs were found to pervasively locate in the genomes. Conclusion Our findings indicate that 1 the HSL model can be used to accurately predict core TRRs of transcripts across species and 2 identified core TRRs by HSL are proper candidates for the further scrutiny of specific regulatory elements and mechanisms. Meanwhile, the regulatory activity taking place in the abundant numbers of ncRNAs might account for the ubiquitous presence of TRRs across the genome. In addition, we also found that the TRRs of protein coding genes and ncRNAs are similar in structure, with the latter being more conserved than the former.

  11. Massive expansion of the calpain gene family in unicellular eukaryotes

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    Zhao Sen

    2012-09-01

    Full Text Available Abstract Background Calpains are Ca2+-dependent cysteine proteases that participate in a range of crucial cellular processes. Dysfunction of these enzymes may cause, for instance, life-threatening diseases in humans, the loss of sex determination in nematodes and embryo lethality in plants. Although the calpain family is well characterized in animal and plant model organisms, there is a great lack of knowledge about these genes in unicellular eukaryote species (i.e. protists. Here, we study the distribution and evolution of calpain genes in a wide range of eukaryote genomes from major branches in the tree of life. Results Our investigations reveal 24 types of protein domains that are combined with the calpain-specific catalytic domain CysPc. In total we identify 41 different calpain domain architectures, 28 of these domain combinations have not been previously described. Based on our phylogenetic inferences, we propose that at least four calpain variants were established in the early evolution of eukaryotes, most likely before the radiation of all the major supergroups of eukaryotes. Many domains associated with eukaryotic calpain genes can be found among eubacteria or archaebacteria but never in combination with the CysPc domain. Conclusions The analyses presented here show that ancient modules present in prokaryotes, and a few de novo eukaryote domains, have been assembled into many novel domain combinations along the evolutionary history of eukaryotes. Some of the new calpain genes show a narrow distribution in a few branches in the tree of life, likely representing lineage-specific innovations. Hence, the functionally important classical calpain genes found among humans and vertebrates make up only a tiny fraction of the calpain family. In fact, a massive expansion of the calpain family occurred by domain shuffling among unicellular eukaryotes and contributed to a wealth of functionally different genes.

  12. An Evolutionary Network of Genes Present in the Eukaryote Common Ancestor Polls Genomes on Eukaryotic and Mitochondrial Origin

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    Thiergart, Thorsten; Landan, Giddy; Schenk, Marc; Dagan, Tal; Martin, William F.

    2012-01-01

    To test the predictions of competing and mutually exclusive hypotheses for the origin of eukaryotes, we identified from a sample of 27 sequenced eukaryotic and 994 sequenced prokaryotic genomes 571 genes that were present in the eukaryote common ancestor and that have homologues among eubacterial and archaebacterial genomes. Maximum-likelihood trees identified the prokaryotic genomes that most frequently contained genes branching as the sister to the eukaryotic nuclear homologues. Among the archaebacteria, euryarchaeote genomes most frequently harbored the sister to the eukaryotic nuclear gene, whereas among eubacteria, the α-proteobacteria were most frequently represented within the sister group. Only 3 genes out of 571 gave a 3-domain tree. Homologues from α-proteobacterial genomes that branched as the sister to nuclear genes were found more frequently in genomes of facultatively anaerobic members of the rhiozobiales and rhodospirilliales than in obligate intracellular ricketttsial parasites. Following α-proteobacteria, the most frequent eubacterial sister lineages were γ-proteobacteria, δ-proteobacteria, and firmicutes, which were also the prokaryote genomes least frequently found as monophyletic groups in our trees. Although all 22 higher prokaryotic taxa sampled (crenarchaeotes, γ-proteobacteria, spirochaetes, chlamydias, etc.) harbor genes that branch as the sister to homologues present in the eukaryotic common ancestor, that is not evidence of 22 different prokaryotic cells participating at eukaryote origins because prokaryotic “lineages” have laterally acquired genes for more than 1.5 billion years since eukaryote origins. The data underscore the archaebacterial (host) nature of the eukaryotic informational genes and the eubacterial (mitochondrial) nature of eukaryotic energy metabolism. The network linking genes of the eukaryote ancestor to contemporary homologues distributed across prokaryotic genomes elucidates eukaryote gene origins in a

  13. Distinct gene number-genome size relationships for eukaryotes and non-eukaryotes: gene content estimation for dinoflagellate genomes.

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    Yubo Hou

    Full Text Available The ability to predict gene content is highly desirable for characterization of not-yet sequenced genomes like those of dinoflagellates. Using data from completely sequenced and annotated genomes from phylogenetically diverse lineages, we investigated the relationship between gene content and genome size using regression analyses. Distinct relationships between log(10-transformed protein-coding gene number (Y' versus log(10-transformed genome size (X', genome size in kbp were found for eukaryotes and non-eukaryotes. Eukaryotes best fit a logarithmic model, Y' = ln(-46.200+22.678X', whereas non-eukaryotes a linear model, Y' = 0.045+0.977X', both with high significance (p0.91. Total gene number shows similar trends in both groups to their respective protein coding regressions. The distinct correlations reflect lower and decreasing gene-coding percentages as genome size increases in eukaryotes (82%-1% compared to higher and relatively stable percentages in prokaryotes and viruses (97%-47%. The eukaryotic regression models project that the smallest dinoflagellate genome (3x10(6 kbp contains 38,188 protein-coding (40,086 total genes and the largest (245x10(6 kbp 87,688 protein-coding (92,013 total genes, corresponding to 1.8% and 0.05% gene-coding percentages. These estimates do not likely represent extraordinarily high functional diversity of the encoded proteome but rather highly redundant genomes as evidenced by high gene copy numbers documented for various dinoflagellate species.

  14. Noise minimization in eukaryotic gene expression

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    Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

    2004-01-15

    All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

  15. Gene name ambiguity of eukaryotic nomenclatures.

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    Chen, Lifeng; Liu, Hongfang; Friedman, Carol

    2005-01-15

    With more and more scientific literature published online, the effective management and reuse of this knowledge has become problematic. Natural language processing (NLP) may be a potential solution by extracting, structuring and organizing biomedical information in online literature in a timely manner. One essential task is to recognize and identify genomic entities in text. 'Recognition' can be accomplished using pattern matching and machine learning. But for 'identification' these techniques are not adequate. In order to identify genomic entities, NLP needs a comprehensive resource that specifies and classifies genomic entities as they occur in text and that associates them with normalized terms and also unique identifiers so that the extracted entities are well defined. Online organism databases are an excellent resource to create such a lexical resource. However, gene name ambiguity is a serious problem because it affects the appropriate identification of gene entities. In this paper, we explore the extent of the problem and suggest ways to address it. We obtained gene information from 21 organisms and quantified naming ambiguities within species, across species, with English words and with medical terms. When the case (of letters) was retained, official symbols displayed negligible intra-species ambiguity (0.02%) and modest ambiguities with general English words (0.57%) and medical terms (1.01%). In contrast, the across-species ambiguity was high (14.20%). The inclusion of gene synonyms increased intra-species ambiguity substantially and full names contributed greatly to gene-medical-term ambiguity. A comprehensive lexical resource that covers gene information for the 21 organisms was then created and used to identify gene names by using a straightforward string matching program to process 45,000 abstracts associated with the mouse model organism while ignoring case and gene names that were also English words. We found that 85.1% of correctly retrieved mouse

  16. Automatic generation of gene finders for eukaryotic species

    DEFF Research Database (Denmark)

    Terkelsen, Kasper Munch; Krogh, A.

    2006-01-01

    Background The number of sequenced eukaryotic genomes is rapidly increasing. This means that over time it will be hard to keep supplying customised gene finders for each genome. This calls for procedures to automatically generate species-specific gene finders and to re-train them as the quantity...... length distributions. The performance of each individual gene predictor on each individual genome is comparable to the best of the manually optimised species-specific gene finders. It is shown that species-specific gene finders are superior to gene finders trained on other species....

  17. Eukaryote-to-eukaryote gene transfer gives rise to genome mosaicism in euglenids

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    Weber Andreas PM

    2011-04-01

    Full Text Available Abstract Background Euglenophytes are a group of photosynthetic flagellates possessing a plastid derived from a green algal endosymbiont, which was incorporated into an ancestral host cell via secondary endosymbiosis. However, the impact of endosymbiosis on the euglenophyte nuclear genome is not fully understood due to its complex nature as a 'hybrid' of a non-photosynthetic host cell and a secondary endosymbiont. Results We analyzed an EST dataset of the model euglenophyte Euglena gracilis using a gene mining program designed to detect laterally transferred genes. We found E. gracilis genes showing affinity not only with green algae, from which the secondary plastid in euglenophytes evolved, but also red algae and/or secondary algae containing red algal-derived plastids. Phylogenetic analyses of these 'red lineage' genes suggest that E. gracilis acquired at least 14 genes via eukaryote-to-eukaryote lateral gene transfer from algal sources other than the green algal endosymbiont that gave rise to its current plastid. We constructed an EST library of the aplastidic euglenid Peranema trichophorum, which is a eukaryovorous relative of euglenophytes, and also identified 'red lineage' genes in its genome. Conclusions Our data show genome mosaicism in E. gracilis and P. trichophorum. One possible explanation for the presence of these genes in these organisms is that some or all of them were independently acquired by lateral gene transfer and contributed to the successful integration and functioning of the green algal endosymbiont as a secondary plastid. Alternative hypotheses include the presence of a phagocytosed alga as the single source of those genes, or a cryptic tertiary endosymbiont harboring secondary plastid of red algal origin, which the eukaryovorous ancestor of euglenophytes had acquired prior to the secondary endosymbiosis of a green alga.

  18. Horizontal gene acquisitions by eukaryotes as drivers of adaptive evolution.

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    Schönknecht, Gerald; Weber, Andreas P M; Lercher, Martin J

    2014-01-01

    In contrast to vertical gene transfer from parent to offspring, horizontal (or lateral) gene transfer moves genetic information between different species. Bacteria and archaea often adapt through horizontal gene transfer. Recent analyses indicate that eukaryotic genomes, too, have acquired numerous genes via horizontal transfer from prokaryotes and other lineages. Based on this we raise the hypothesis that horizontally acquired genes may have contributed more to adaptive evolution of eukaryotes than previously assumed. Current candidate sets of horizontally acquired eukaryotic genes may just be the tip of an iceberg. We have recently shown that adaptation of the thermoacidophilic red alga Galdieria sulphuraria to its hot, acid, toxic-metal laden, volcanic environment was facilitated by the acquisition of numerous genes from extremophile bacteria and archaea. Other recently published examples of horizontal acquisitions involved in adaptation include ice-binding proteins in marine algae, enzymes for carotenoid biosynthesis in aphids, and genes involved in fungal metabolism. Editor's suggested further reading in BioEssays Jumping the fine LINE between species: Horizontal transfer of transposable elements in animals catalyses genome evolution Abstract. © 2014 WILEY Periodicals, Inc.

  19. Gene regulatory mechanisms in infected fish

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

    2011-01-01

    This talk will highlight the regulatory mechanisms of gene expression especially the programmed form of mRNA decay which is known as RNA interference (RNAi) and how this and other mechanisms contribute to the regulation of genes involved in immunity. In the RNAi mechanism small double stranded RNA...... molecules produced by the eukaryotic cell is used to program the RNA Induced Silencing Complex (RISC) for cleavage of specific mRNA transcripts and/or translational repression in the cytoplasm or even chromatin methylation in the nucleus. All processes leading to silencing of the target gene. MicroRNAs (or...... miRNAs) are one class of such small RNAs which are expressed from the genome. The RISC system allows for non-perfect base pairing of miRNAs to their target genes why one small RNA can in theory silence large groups of genes at the same time. It is therefore anticipated that they are able to depress...

  20. Evolution of filamentous plant pathogens: gene exchange across eukaryotic kingdoms.

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    Richards, Thomas A; Dacks, Joel B; Jenkinson, Joanna M; Thornton, Christopher R; Talbot, Nicholas J

    2006-09-19

    Filamentous fungi and oomycetes are eukaryotic microorganisms that grow by producing networks of thread-like hyphae, which secrete enzymes to break down complex nutrients, such as wood and plant material, and recover the resulting simple sugars and amino acids by osmotrophy. These organisms are extremely similar in both appearance and lifestyle and include some of the most economically important plant pathogens . However, the morphological similarity of fungi and oomycetes is misleading because they represent some of the most distantly related eukaryote evolutionary groupings, and their shared osmotrophic growth habit is interpreted as being the result of convergent evolution . The fungi branch with the animals, whereas the oomycetes branch with photosynthetic algae as part of the Chromalveolata . In this report, we provide strong phylogenetic evidence that multiple horizontal gene transfers (HGT) have occurred from filamentous ascomycete fungi to the distantly related oomycetes. We also present evidence that a subset of the associated gene families was initially the product of prokaryote-to-fungi HGT. The predicted functions of the gene products associated with fungi-to-oomycete HGT suggest that this process has played a significant role in the evolution of the osmotrophic, filamentous lifestyle on two separate branches of the eukaryote tree.

  1. Therapeutic gene editing: delivery and regulatory perspectives.

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    Shim, Gayong; Kim, Dongyoon; Park, Gyu Thae; Jin, Hyerim; Suh, Soo-Kyung; Oh, Yu-Kyoung

    2017-06-01

    Gene-editing technology is an emerging therapeutic modality for manipulating the eukaryotic genome by using target-sequence-specific engineered nucleases. Because of the exceptional advantages that gene-editing technology offers in facilitating the accurate correction of sequences in a genome, gene editing-based therapy is being aggressively developed as a next-generation therapeutic approach to treat a wide range of diseases. However, strategies for precise engineering and delivery of gene-editing nucleases, including zinc finger nucleases, transcription activator-like effector nuclease, and CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats-associated nuclease Cas9), present major obstacles to the development of gene-editing therapies, as with other gene-targeting therapeutics. Currently, viral and non-viral vectors are being studied for the delivery of these nucleases into cells in the form of DNA, mRNA, or proteins. Clinical trials are already ongoing, and in vivo studies are actively investigating the applicability of CRISPR/Cas9 techniques. However, the concept of correcting the genome poses major concerns from a regulatory perspective, especially in terms of safety. This review addresses current research trends and delivery strategies for gene editing-based therapeutics in non-clinical and clinical settings and considers the associated regulatory issues.

  2. Evolution of glutamate dehydrogenase genes: evidence for lateral gene transfer within and between prokaryotes and eukaryotes

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    Roger Andrew J

    2003-06-01

    Full Text Available Abstract Background Lateral gene transfer can introduce genes with novel functions into genomes or replace genes with functionally similar orthologs or paralogs. Here we present a study of the occurrence of the latter gene replacement phenomenon in the four gene families encoding different classes of glutamate dehydrogenase (GDH, to evaluate and compare the patterns and rates of lateral gene transfer (LGT in prokaryotes and eukaryotes. Results We extend the taxon sampling of gdh genes with nine new eukaryotic sequences and examine the phylogenetic distribution pattern of the various GDH classes in combination with maximum likelihood phylogenetic analyses. The distribution pattern analyses indicate that LGT has played a significant role in the evolution of the four gdh gene families. Indeed, a number of gene transfer events are identified by phylogenetic analyses, including numerous prokaryotic intra-domain transfers, some prokaryotic inter-domain transfers and several inter-domain transfers between prokaryotes and microbial eukaryotes (protists. Conclusion LGT has apparently affected eukaryotes and prokaryotes to a similar extent within the gdh gene families. In the absence of indications that the evolution of the gdh gene families is radically different from other families, these results suggest that gene transfer might be an important evolutionary mechanism in microbial eukaryote genome evolution.

  3. Phylogenetic analysis of ferlin genes reveals ancient eukaryotic origins

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    Lek Monkol

    2010-07-01

    Full Text Available Abstract Background The ferlin gene family possesses a rare and identifying feature consisting of multiple tandem C2 domains and a C-terminal transmembrane domain. Much currently remains unknown about the fundamental function of this gene family, however, mutations in its two most well-characterised members, dysferlin and otoferlin, have been implicated in human disease. The availability of genome sequences from a wide range of species makes it possible to explore the evolution of the ferlin family, providing contextual insight into characteristic features that define the ferlin gene family in its present form in humans. Results Ferlin genes were detected from all species of representative phyla, with two ferlin subgroups partitioned within the ferlin phylogenetic tree based on the presence or absence of a DysF domain. Invertebrates generally possessed two ferlin genes (one with DysF and one without, with six ferlin genes in most vertebrates (three DysF, three non-DysF. Expansion of the ferlin gene family is evident between the divergence of lamprey (jawless vertebrates and shark (cartilaginous fish. Common to almost all ferlins is an N-terminal C2-FerI-C2 sandwich, a FerB motif, and two C-terminal C2 domains (C2E and C2F adjacent to the transmembrane domain. Preservation of these structural elements throughout eukaryotic evolution suggests a fundamental role of these motifs for ferlin function. In contrast, DysF, C2DE, and FerA are optional, giving rise to subtle differences in domain topologies of ferlin genes. Despite conservation of multiple C2 domains in all ferlins, the C-terminal C2 domains (C2E and C2F displayed higher sequence conservation and greater conservation of putative calcium binding residues across paralogs and orthologs. Interestingly, the two most studied non-mammalian ferlins (Fer-1 and Misfire in model organisms C. elegans and D. melanogaster, present as outgroups in the phylogenetic analysis, with results suggesting

  4. Analysis of gene order conservation in eukaryotes identifies transcriptionally and functionally linked genes.

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    Marcela Dávila López

    Full Text Available The order of genes in eukaryotes is not entirely random. Studies of gene order conservation are important to understand genome evolution and to reveal mechanisms why certain neighboring genes are more difficult to separate during evolution. Here, genome-wide gene order information was compiled for 64 species, representing a wide variety of eukaryotic phyla. This information is presented in a browser where gene order may be displayed and compared between species. Factors related to non-random gene order in eukaryotes were examined by considering pairs of neighboring genes. The evolutionary conservation of gene pairs was studied with respect to relative transcriptional direction, intergenic distance and functional relationship as inferred by gene ontology. The results show that among gene pairs that are conserved the divergently and co-directionally transcribed genes are much more common than those that are convergently transcribed. Furthermore, highly conserved pairs, in particular those of fungi, are characterized by a short intergenic distance. Finally, gene pairs of metazoa and fungi that are evolutionary conserved and that are divergently transcribed are much more likely to be related by function as compared to poorly conserved gene pairs. One example is the ribosomal protein gene pair L13/S16, which is unusual as it occurs both in fungi and alveolates. A specific functional relationship between these two proteins is also suggested by the fact that they are part of the same operon in both eubacteria and archaea. In conclusion, factors associated with non-random gene order in eukaryotes include relative gene orientation, intergenic distance and functional relationships. It seems likely that certain pairs of genes are conserved because the genes involved have a transcriptional and/or functional relationship. The results also indicate that studies of gene order conservation aid in identifying genes that are related in terms of transcriptional

  5. Horizontal gene transfer of a Chlamydial tRNA-guanine transglycosylase gene to eukaryotic microbes.

    Science.gov (United States)

    Manna, Sam; Harman, Ashley

    2016-01-01

    tRNA-guanine transglycosylases are found in all domains of life and mediate the base exchange of guanine with queuine in the anticodon loop of tRNAs. They can also regulate virulence in bacteria such as Shigella flexneri, which has prompted the development of drugs that inhibit the function of these enzymes. Here we report a group of tRNA-guanine transglycosylases in eukaryotic microbes (algae and protozoa) which are more similar to their bacterial counterparts than previously characterized eukaryotic tRNA-guanine transglycosylases. We provide evidence demonstrating that the genes encoding these enzymes were acquired by these eukaryotic lineages via horizontal gene transfer from the Chlamydiae group of bacteria. Given that the S. flexneri tRNA-guanine transglycosylase can be targeted by drugs, we propose that the bacterial-like tRNA-guanine transglycosylases could potentially be targeted in a similar fashion in pathogenic amoebae that possess these enzymes such as Acanthamoeba castellanii. This work also presents ancient prokaryote-to-eukaryote horizontal gene transfer events as an untapped resource of potential drug target identification in pathogenic eukaryotes. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Comparative genomics of Eukaryotes

    NARCIS (Netherlands)

    Noort, Vera van

    2007-01-01

    This thesis focuses on developing comparative genomics methods in eukaryotes, with an emphasis on applications for gene function prediction and regulatory element detection. In the past, methods have been developed to predict functional associations between gene pairs in prokaryotes. The challenge

  7. Automated Eukaryotic Gene Structure Annotation Using EVidenceModeler and the Program to Assemble Spliced Alignments

    Energy Technology Data Exchange (ETDEWEB)

    Haas, B J; Salzberg, S L; Zhu, W; Pertea, M; Allen, J E; Orvis, J; White, O; Buell, C R; Wortman, J R

    2007-12-10

    EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation.

  8. Horizontal transfer of a eukaryotic plastid-targeted protein gene to cyanobacteria

    Directory of Open Access Journals (Sweden)

    Keeling Patrick J

    2007-06-01

    Full Text Available Abstract Background Horizontal or lateral transfer of genetic material between distantly related prokaryotes has been shown to play a major role in the evolution of bacterial and archaeal genomes, but exchange of genes between prokaryotes and eukaryotes is not as well understood. In particular, gene flow from eukaryotes to prokaryotes is rarely documented with strong support, which is unusual since prokaryotic genomes appear to readily accept foreign genes. Results Here, we show that abundant marine cyanobacteria in the related genera Synechococcus and Prochlorococcus acquired a key Calvin cycle/glycolytic enzyme from a eukaryote. Two non-homologous forms of fructose bisphosphate aldolase (FBA are characteristic of eukaryotes and prokaryotes respectively. However, a eukaryotic gene has been inserted immediately upstream of the ancestral prokaryotic gene in several strains (ecotypes of Synechococcus and Prochlorococcus. In one lineage this new gene has replaced the ancestral gene altogether. The eukaryotic gene is most closely related to the plastid-targeted FBA from red algae. This eukaryotic-type FBA once replaced the plastid/cyanobacterial type in photosynthetic eukaryotes, hinting at a possible functional advantage in Calvin cycle reactions. The strains that now possess this eukaryotic FBA are scattered across the tree of Synechococcus and Prochlorococcus, perhaps because the gene has been transferred multiple times among cyanobacteria, or more likely because it has been selectively retained only in certain lineages. Conclusion A gene for plastid-targeted FBA has been transferred from red algae to cyanobacteria, where it has inserted itself beside its non-homologous, functional analogue. Its current distribution in Prochlorococcus and Synechococcus is punctate, suggesting a complex history since its introduction to this group.

  9. Gradient descent optimization in gene regulatory pathways.

    Science.gov (United States)

    Das, Mouli; Mukhopadhyay, Subhasis; De, Rajat K

    2010-09-03

    Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. Elucidating the architecture and dynamics of large scale gene regulatory networks is an important goal in systems biology. The knowledge of the gene regulatory networks further gives insights about gene regulatory pathways. This information leads to many potential applications in medicine and molecular biology, examples of which are identification of metabolic pathways, complex genetic diseases, drug discovery and toxicology analysis. High-throughput technologies allow studying various aspects of gene regulatory networks on a genome-wide scale and we will discuss recent advances as well as limitations and future challenges for gene network modeling. Novel approaches are needed to both infer the causal genes and generate hypothesis on the underlying regulatory mechanisms. In the present article, we introduce a new method for identifying a set of optimal gene regulatory pathways by using structural equations as a tool for modeling gene regulatory networks. The method, first of all, generates data on reaction flows in a pathway. A set of constraints is formulated incorporating weighting coefficients. Finally the gene regulatory pathways are obtained through optimization of an objective function with respect to these weighting coefficients. The effectiveness of the present method is successfully tested on ten gene regulatory networks existing in the literature. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. The results compare favorably with earlier experimental results. The validated pathways point to a combination of previously documented and novel findings. We show that our method can correctly identify the causal genes and effectively output experimentally verified pathways. The present method has been successful in deriving the optimal regulatory pathways for all the regulatory networks considered. The biological

  10. Horizontal transfers of transposable elements in eukaryotes: The flying genes.

    Science.gov (United States)

    Panaud, Olivier

    2016-01-01

    Transposable elements (TEs) are the major components of eukaryotic genomes. Their propensity to densely populate and in some cases invade the genomes of plants and animals is in contradiction with the fact that transposition is strictly controlled by several molecular pathways acting at either transcriptional or post-transcriptional levels. Horizontal transfers, defined as the transmission of genetic material between sexually isolated species, have long been considered as rare phenomena. Here, we show that the horizontal transfers of transposable elements (HTTs) are very frequent in ecosystems. The exact mechanisms of such transfers are not well understood, but species involved in close biotic interactions, like parasitism, show a propensity to exchange genetic material horizontally. We propose that HTTs allow TEs to escape the silencing machinery of their host genome and may therefore be an important mechanism for their survival and their dissemination in eukaryotes. Copyright © 2016 Académie des sciences. Published by Elsevier SAS. All rights reserved.

  11. Helicobacter pylori evolution: lineage- specific adaptations in homologs of eukaryotic Sel1-like genes.

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    Masako Ogura

    2007-08-01

    Full Text Available Geographic partitioning is postulated to foster divergence of Helicobacter pylori populations as an adaptive response to local differences in predominant host physiology. H. pylori's ability to establish persistent infection despite host inflammatory responses likely involves active management of host defenses using bacterial proteins that may themselves be targets for adaptive evolution. Sequenced H. pylori genomes encode a family of eight or nine secreted proteins containing repeat motifs that are characteristic of the eukaryotic Sel1 regulatory protein, whereas the related Campylobacter and Wolinella genomes each contain only one or two such "Sel1-like repeat" (SLR genes ("slr genes". Signatures of positive selection (ratio of nonsynonymous to synonymous mutations, dN/dS = omega > 1 were evident in the evolutionary history of H. pylori slr gene family expansion. Sequence analysis of six of these slr genes (hp0160, hp0211, hp0235, hp0519, hp0628, and hp1117 from representative East Asian, European, and African H. pylori strains revealed that all but hp0628 had undergone positive selection, with different amino acids often selected in different regions. Most striking was a divergence of Japanese and Korean alleles of hp0519, with Japanese alleles having undergone particularly strong positive selection (omegaJ > 25, whereas alleles of other genes from these populations were intermingled. Homology-based structural modeling localized most residues under positive selection to SLR protein surfaces. Rapid evolution of certain slr genes in specific H. pylori lineages suggests a model of adaptive change driven by selection for fine-tuning of host responses, and facilitated by geographic isolation. Characterization of such local adaptations should help elucidate how H. pylori manages persistent infection, and potentially lead to interventions tailored to diverse human populations.

  12. The transferome of metabolic genes explored: analysis of the horizontal transfer of enzyme encoding genes in unicellular eukaryotes.

    Science.gov (United States)

    Whitaker, John W; McConkey, Glenn A; Westhead, David R

    2009-01-01

    Metabolic networks are responsible for many essential cellular processes, and exhibit a high level of evolutionary conservation from bacteria to eukaryotes. If genes encoding metabolic enzymes are horizontally transferred and are advantageous, they are likely to become fixed. Horizontal gene transfer (HGT) has played a key role in prokaryotic evolution and its importance in eukaryotes is increasingly evident. High levels of endosymbiotic gene transfer (EGT) accompanied the establishment of plastids and mitochondria, and more recent events have allowed further acquisition of bacterial genes. Here, we present the first comprehensive multi-species analysis of E/HGT of genes encoding metabolic enzymes from bacteria to unicellular eukaryotes. The phylogenetic trees of 2,257 metabolic enzymes were used to make E/HGT assertions in ten groups of unicellular eukaryotes, revealing the sources and metabolic processes of the transferred genes. Analyses revealed a preference for enzymes encoded by genes gained through horizontal and endosymbiotic transfers to be connected in the metabolic network. Enrichment in particular functional classes was particularly revealing: alongside plastid related processes and carbohydrate metabolism, this highlighted a number of pathways in eukaryotic parasites that are rich in enzymes encoded by transferred genes, and potentially key to pathogenicity. The plant parasites Phytophthora were discovered to have a potential pathway for lipopolysaccharide biosynthesis of E/HGT origin not seen before in eukaryotes outside the Plantae. The number of enzymes encoded by genes gained through E/HGT has been established, providing insight into functional gain during the evolution of unicellular eukaryotes. In eukaryotic parasites, genes encoding enzymes that have been gained through horizontal transfer may be attractive drug targets if they are part of processes not present in the host, or are significantly diverged from equivalent host enzymes.

  13. Making connections: Insulators organize eukaryotic chromosomes into independent cis-regulatory networks

    Science.gov (United States)

    Chetverina, Darya; Aoki, Tsutomu; Erokhin, Maksim; Georgiev, Pavel; Schedl, Paul

    2015-01-01

    Summary Insulators play a central role in subdividing the chromosome into a series of discrete topologically independent domains and in ensuring that enhancers and silencers contact their appropriate target genes. In this review we first discuss the general characteristics of insulator elements and their associated protein factors. A growing collection of insulator proteins have been identified including a family of proteins whose expression is developmental regulator. We next consider several unexpected discoveries that require us to completely rethink both how insulators function (and how they can best be assayed). These discoveries also require a reevaluation of how insulators might restrict or orchestrate (by preventing or promoting) interactions between regulatory elements and their target genes. We conclude by connecting these new insights into the mechanisms of insulator action to dynamic changes in the 3-dimensional topology of the chromatin fiber and the generation of specific patterns of gene activity during development and differentiation. PMID:24277632

  14. Lateral gene transfer between prokaryotes and multicellular eukaryotes: ongoing and significant?

    NARCIS (Netherlands)

    Ros, V.I.D.; Hurst, G.D.D.

    2009-01-01

    The expansion of genome sequencing projects has produced accumulating evidence for lateral transfer of genes between prokaryotic and eukaryotic genomes. However, it remains controversial whether these genes are of functional importance in their recipient host. Nikoh and Nakabachi, in a recent paper

  15. Algal endosymbionts as vectors of horizontal gene transfer in photosynthetic eukaryotes

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    Huan eQiu

    2013-09-01

    Full Text Available Photosynthesis in eukaryotes occurs in the plastid, an organelle that is derived from a single cyanobacterial primary endosymbiosis in the common ancestor of the supergroup Plantae (or Archaeplastida that includes green, red, and glaucophyte algae and plants. However a variety of other phytoplankton such as the chlorophyll c-containing diatoms, dinoflagellates, and haptophytes contain a red alga-derived plastid that traces its origin to secondary or tertiary (eukaryote engulfs eukaryote endosymbiosis. The hypothesis of Plantae monophyly has only recently been substantiated, however the extent and role of endosymbiotic and horizontal gene transfer (EGT and HGT in algal genome evolution still remain to be fully understood. What is becoming clear from analysis of complete genome data is that algal gene complements can no longer be considered essentially eukaryotic in provenance; i.e., with the expected addition of several hundred cyanobacterial genes derived from EGT and a similar number derived from the mitochondrial ancestor. For example, we now know that foreign cells such as Chlamydiae and other prokaryotes have made significant contributions to plastid functions in Plantae. Perhaps more surprising is the recent finding of extensive bacterium-derived HGT in the nuclear genome of the unicellular red alga Porphyridium purpureum that does not relate to plastid functions. These non-endosymbiont gene transfers not only shaped the evolutionary history of Plantae but also were propagated via secondary endosymbiosis to a multitude of other phytoplankton. Here we discuss the idea that Plantae (in particular red algae are one of the major players in eukaryote genome evolution by virtue of their ability to act as sinks and sources of foreign genes through HGT and endosymbiosis, respectively. This hypothesis recognizes the often under-appreciated Rhodophyta as major sources of genetic novelty among photosynthetic eukaryotes.

  16. A tree of life based on ninety-eight expressed genes conserved across diverse eukaryotic species.

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    Pawan Kumar Jayaswal

    Full Text Available Rapid advances in DNA sequencing technologies have resulted in the accumulation of large data sets in the public domain, facilitating comparative studies to provide novel insights into the evolution of life. Phylogenetic studies across the eukaryotic taxa have been reported but on the basis of a limited number of genes. Here we present a genome-wide analysis across different plant, fungal, protist, and animal species, with reference to the 36,002 expressed genes of the rice genome. Our analysis revealed 9831 genes unique to rice and 98 genes conserved across all 49 eukaryotic species analysed. The 98 genes conserved across diverse eukaryotes mostly exhibited binding and catalytic activities and shared common sequence motifs; and hence appeared to have a common origin. The 98 conserved genes belonged to 22 functional gene families including 26S protease, actin, ADP-ribosylation factor, ATP synthase, casein kinase, DEAD-box protein, DnaK, elongation factor 2, glyceraldehyde 3-phosphate, phosphatase 2A, ras-related protein, Ser/Thr protein phosphatase family protein, tubulin, ubiquitin and others. The consensus Bayesian eukaryotic tree of life developed in this study demonstrated widely separated clades of plants, fungi, and animals. Musa acuminata provided an evolutionary link between monocotyledons and dicotyledons, and Salpingoeca rosetta provided an evolutionary link between fungi and animals, which indicating that protozoan species are close relatives of fungi and animals. The divergence times for 1176 species pairs were estimated accurately by integrating fossil information with synonymous substitution rates in the comprehensive set of 98 genes. The present study provides valuable insight into the evolution of eukaryotes.

  17. Prokaryotic genes in eukaryotic genome sequences: when to infer horizontal gene transfer and when to suspect an actual microbe.

    Science.gov (United States)

    Artamonova, Irena I; Lappi, Tanya; Zudina, Liudmila; Mushegian, Arcady R

    2015-07-01

    Assessment of phylogenetic positions of predicted gene and protein sequences is a routine step in any genome project, useful for validating the species' taxonomic position and for evaluating hypotheses about genome evolution and function. Several recent eukaryotic genome projects have reported multiple gene sequences that were much more similar to homologues in bacteria than to any eukaryotic sequence. In the spirit of the times, horizontal gene transfer from bacteria to eukaryotes has been invoked in some of these cases. Here, we show, using comparative sequence analysis, that some of those bacteria-like genes indeed appear likely to have been horizontally transferred from bacteria to eukaryotes. In other cases, however, the evidence strongly indicates that the eukaryotic DNA sequenced in the genome project contains a sample of non-integrated DNA from the actual bacteria, possibly providing a window into the host microbiome. Recent literature suggests also that common reagents, kits and laboratory equipment may be systematically contaminated with bacterial DNA, which appears to be sampled by metagenome projects non-specifically. We review several bioinformatic criteria that help to distinguish putative horizontal gene transfers from the admixture of genes from autonomously replicating bacteria in their hosts' genome databases or from the reagent contamination. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

  18. Widespread Horizontal Gene Transfer from Circular Single-stranded DNA Viruses to Eukaryotic Genomes

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    Xie Jiatao

    2011-09-01

    Full Text Available Abstract Background In addition to vertical transmission, organisms can also acquire genes from other distantly related species or from their extra-chromosomal elements (plasmids and viruses via horizontal gene transfer (HGT. It has been suggested that phages represent substantial forces in prokaryotic evolution. In eukaryotes, retroviruses, which can integrate into host genome as an obligate step in their replication strategy, comprise approximately 8% of the human genome. Unlike retroviruses, few members of other virus families are known to transfer genes to host genomes. Results Here we performed a systematic search for sequences related to circular single-stranded DNA (ssDNA viruses in publicly available eukaryotic genome databases followed by comprehensive phylogenetic analysis. We conclude that the replication initiation protein (Rep-related sequences of geminiviruses, nanoviruses and circoviruses have been frequently transferred to a broad range of eukaryotic species, including plants, fungi, animals and protists. Some of the transferred viral genes were conserved and expressed, suggesting that these genes have been coopted to assume cellular functions in the host genomes. We also identified geminivirus-like and parvovirus-like transposable elements in genomes of fungi and lower animals, respectively, and thereby provide direct evidence that eukaryotic transposons could derive from ssDNA viruses. Conclusions Our discovery extends the host range of circular ssDNA viruses and sheds light on the origin and evolution of these viruses. It also suggests that ssDNA viruses act as an unforeseen source of genetic innovation in their hosts.

  19. Recurrent horizontal transfer of bacterial toxin genes to eukaryotes.

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    Moran, Yehu; Fredman, David; Szczesny, Pawel; Grynberg, Marcin; Technau, Ulrich

    2012-09-01

    In this work, we report likely recurrent horizontal (lateral) gene transfer events of genes encoding pore-forming toxins of the aerolysin family between species belonging to different kingdoms of life. Clustering based on pairwise similarity and phylogenetic analysis revealed several distinct aerolysin sequence groups, each containing proteins from multiple kingdoms of life. These results strongly support at least six independent transfer events between distantly related phyla in the evolutionary history of one protein family and discount selective retention of ancestral genes as a plausible explanation for this patchy phylogenetic distribution. We discuss the possible roles of these proteins and show evidence for a convergent new function in two extant species. We hypothesize that certain gene families are more likely to be maintained following horizontal gene transfer from commensal or pathogenic organism to its host if they 1) can function alone; and 2) are immediately beneficial for the ecology of the organism, as in the case of pore-forming toxins which can be utilized in multicellular organisms for defense and predation.

  20. A study of bacterial gene regulatory mechanisms

    DEFF Research Database (Denmark)

    Hansen, Sabine

    the different regulatory mechanisms affect system dynamics. We have designed a synthetic gene regulatory network (GRN) in bacterial cells that enables us to study the dynamics of GRNs. The results presented in this PhD thesis show that model equations based on the established mechanisms of action of each...... of a particular type of regulatory mechanism. The synthetic system presented in this thesis is, to our knowledge, the first of its kind to allow a direct comparison of the dynamic behaviors of gene regulatory networks that employ different mechanisms of regulation. In addition to studying the dynamic behavior...... of GRNs this thesis also provided the first evidence of the sensor histidine kinase VC1831 being an additional player in the Vibrio cholerae quorum sensing (QS) GRN. Bacteria use a process of cell-cell communication called QS which enable the bacterial cells to collectively control their gene expression...

  1. Gene transfer from bacteria and archaea facilitated evolution of an extremophilic eukaryote.

    Science.gov (United States)

    Schönknecht, Gerald; Chen, Wei-Hua; Ternes, Chad M; Barbier, Guillaume G; Shrestha, Roshan P; Stanke, Mario; Bräutigam, Andrea; Baker, Brett J; Banfield, Jillian F; Garavito, R Michael; Carr, Kevin; Wilkerson, Curtis; Rensing, Stefan A; Gagneul, David; Dickenson, Nicholas E; Oesterhelt, Christine; Lercher, Martin J; Weber, Andreas P M

    2013-03-08

    Some microbial eukaryotes, such as the extremophilic red alga Galdieria sulphuraria, live in hot, toxic metal-rich, acidic environments. To elucidate the underlying molecular mechanisms of adaptation, we sequenced the 13.7-megabase genome of G. sulphuraria. This alga shows an enormous metabolic flexibility, growing either photoautotrophically or heterotrophically on more than 50 carbon sources. Environmental adaptation seems to have been facilitated by horizontal gene transfer from various bacteria and archaea, often followed by gene family expansion. At least 5% of protein-coding genes of G. sulphuraria were probably acquired horizontally. These proteins are involved in ecologically important processes ranging from heavy-metal detoxification to glycerol uptake and metabolism. Thus, our findings show that a pan-domain gene pool has facilitated environmental adaptation in this unicellular eukaryote.

  2. Multiple Origins of Eukaryotic cox15 Suggest Horizontal Gene Transfer from Bacteria to Jakobid Mitochondrial DNA.

    Science.gov (United States)

    He, Ding; Fu, Cheng-Jie; Baldauf, Sandra L

    2016-01-01

    The most gene-rich and bacterial-like mitochondrial genomes known are those of Jakobida (Excavata). Of these, the most extreme example to date is the Andalucia godoyi mitochondrial DNA (mtDNA), including a cox15 gene encoding the respiratory enzyme heme A synthase (HAS), which is nuclear-encoded in nearly all other mitochondriate eukaryotes. Thus cox15 in eukaryotes appears to be a classic example of mitochondrion-to-nucleus (endosymbiotic) gene transfer, with A. godoyi uniquely retaining the ancestral state. However, our analyses reveal two highly distinct HAS types (encoded by cox15-1 and cox15-2 genes) and identify A. godoyi mitochondrial cox15-encoded HAS as type-1 and all other eukaryotic cox15-encoded HAS as type-2. Molecular phylogeny places the two HAS types in widely separated clades with eukaryotic type-2 HAS clustering with the bulk of α-proteobacteria (>670 sequences), whereas A. godoyi type-1 HAS clusters with an eclectic set of bacteria and archaea including two α-proteobacteria missing from the type-2 clade. This wide phylogenetic separation of the two HAS types is reinforced by unique features of their predicted protein structures. Meanwhile, RNA-sequencing and genomic analyses fail to detect either cox15 type in the nuclear genome of any jakobid including A. godoyi. This suggests that not only is cox15-1 a relatively recent acquisition unique to the Andalucia lineage but also the jakobid last common ancestor probably lacked both cox15 types. These results indicate that uptake of foreign genes by mtDNA is more taxonomically widespread than previously thought. They also caution against the assumption that all α-proteobacterial-like features of eukaryotes are ancient remnants of endosymbiosis. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  3. Distribution Associated with Stochastic Processes of Gene Expression in a Single Eukaryotic Cell

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    Kuznetsov Vladimir A

    2001-01-01

    Full Text Available The ability to simultaneously measure mRNA abundance for large number of genes has revolutionized biological research by allowing statistical analysis of global gene-expression data. Large-scale gene-expression data sets have been analyzed in order to identify the probability distributions of gene expression levels (or transcript copy numbers in eukaryotic cells. Determining such function(s may provide a theoretical basis for accurately counting all expressed genes in a given cell and for understanding gene expression control. Using the gene-expression libraries derived from yeast cells and from different human cell tissues we found that all observed gene expression levels data appear to follow a Pareto-like skewed frequency distribution. We produced a the skewed probability function, called the Binomial Differential distribution, that accounts for many rarely transcribed genes in a single cell. We also developed a novel method for estimating and removing major experimental errors and redundancies from the Serial Analysis Gene Expression (SAGE data sets. We successfully applied this method to the yeast transcriptome. A "basal" random transcription mechanism for all protein-coding genes in every eukaryotic cell type is predicted.

  4. Modeling gene regulatory network motifs using Statecharts.

    Science.gov (United States)

    Fioravanti, Fabio; Helmer-Citterich, Manuela; Nardelli, Enrico

    2012-03-28

    Gene regulatory networks are widely used by biologists to describe the interactions among genes, proteins and other components at the intra-cellular level. Recently, a great effort has been devoted to give gene regulatory networks a formal semantics based on existing computational frameworks.For this purpose, we consider Statecharts, which are a modular, hierarchical and executable formal model widely used to represent software systems. We use Statecharts for modeling small and recurring patterns of interactions in gene regulatory networks, called motifs. We present an improved method for modeling gene regulatory network motifs using Statecharts and we describe the successful modeling of several motifs, including those which could not be modeled or whose models could not be distinguished using the method of a previous proposal.We model motifs in an easy and intuitive way by taking advantage of the visual features of Statecharts. Our modeling approach is able to simulate some interesting temporal properties of gene regulatory network motifs: the delay in the activation and the deactivation of the "output" gene in the coherent type-1 feedforward loop, the pulse in the incoherent type-1 feedforward loop, the bistability nature of double positive and double negative feedback loops, the oscillatory behavior of the negative feedback loop, and the "lock-in" effect of positive autoregulation. We present a Statecharts-based approach for the modeling of gene regulatory network motifs in biological systems. The basic motifs used to build more complex networks (that is, simple regulation, reciprocal regulation, feedback loop, feedforward loop, and autoregulation) can be faithfully described and their temporal dynamics can be analyzed.

  5. Modular, rule-based modeling for the design of eukaryotic synthetic gene circuits.

    Science.gov (United States)

    Marchisio, Mario Andrea; Colaiacovo, Moreno; Whitehead, Ellis; Stelling, Jörg

    2013-05-27

    The modular design of synthetic gene circuits via composable parts (DNA segments) and pools of signal carriers (molecules such as RNA polymerases and ribosomes) has been successfully applied to bacterial systems. However, eukaryotic cells are becoming a preferential host for new synthetic biology applications. Therefore, an accurate description of the intricate network of reactions that take place inside eukaryotic parts and pools is necessary. Rule-based modeling approaches are increasingly used to obtain compact representations of reaction networks in biological systems. However, this approach is intrinsically non-modular and not suitable per se for the description of composable genetic modules. In contrast, the Model Description Language (MDL) adopted by the modeling tool ProMoT is highly modular and it enables a faithful representation of biological parts and pools. We developed a computational framework for the design of complex (eukaryotic) gene circuits by generating dynamic models of parts and pools via the joint usage of the BioNetGen rule-based modeling approach and MDL. The framework converts the specification of a part (or pool) structure into rules that serve as inputs for BioNetGen to calculate the part's species and reactions. The BioNetGen output is translated into an MDL file that gives a complete description of all the reactions that take place inside the part (or pool) together with a proper interface to connect it to other modules in the circuit. In proof-of-principle applications to eukaryotic Boolean circuits with more than ten genes and more than one thousand reactions, our framework yielded proper representations of the circuits' truth tables. For the model-based design of increasingly complex gene circuits, it is critical to achieve exact and systematic representations of the biological processes with minimal effort. Our computational framework provides such a detailed and intuitive way to design new and complex synthetic gene circuits.

  6. Evolution of evolvability in gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Anton Crombach

    Full Text Available Gene regulatory networks are perhaps the most important organizational level in the cell where signals from the cell state and the outside environment are integrated in terms of activation and inhibition of genes. For the last decade, the study of such networks has been fueled by large-scale experiments and renewed attention from the theoretical field. Different models have been proposed to, for instance, investigate expression dynamics, explain the network topology we observe in bacteria and yeast, and for the analysis of evolvability and robustness of such networks. Yet how these gene regulatory networks evolve and become evolvable remains an open question. An individual-oriented evolutionary model is used to shed light on this matter. Each individual has a genome from which its gene regulatory network is derived. Mutations, such as gene duplications and deletions, alter the genome, while the resulting network determines the gene expression pattern and hence fitness. With this protocol we let a population of individuals evolve under Darwinian selection in an environment that changes through time. Our work demonstrates that long-term evolution of complex gene regulatory networks in a changing environment can lead to a striking increase in the efficiency of generating beneficial mutations. We show that the population evolves towards genotype-phenotype mappings that allow for an orchestrated network-wide change in the gene expression pattern, requiring only a few specific gene indels. The genes involved are hubs of the networks, or directly influencing the hubs. Moreover, throughout the evolutionary trajectory the networks maintain their mutational robustness. In other words, evolution in an alternating environment leads to a network that is sensitive to a small class of beneficial mutations, while the majority of mutations remain neutral: an example of evolution of evolvability.

  7. Gene-regulatory interactions in embryonic stem cells represent cell-type specific gene regulatory programs.

    Science.gov (United States)

    Ha, Misook; Hong, Soondo

    2017-10-13

    Pluripotency, the ability of embryonic stem cells to differentiate into specialized cell types, is determined by ESC-specific gene regulators such as transcription factors and chromatin modification factors. It is not well understood how ESCs are poised for differentiation, however, and methods are needed for prognosis of the molecular changes in the differentiation of ESCs into specific organs. We describe a new approach to infer cell-type specific gene regulatory programs based on gene regulatory interactions in ESCs. Our method infers the molecular logic of gene regulatory mechanisms by mapping the position-specific combinatory patterns of numerous regulators in ESCs into cell-type specific gene regulations. We validate the proposed approach by recapitulating the RNA-seq and microarray data of neuronal progenitor cells, adult liver cells, and ESCs from the integrated patterns of diverse gene regulators in ESCs. We find that the collective functions of diverse gene regulators in ESCs represent distinct gene regulatory programs in specialized cell types. Our new approach expands our understanding of the differential gene regulatory information in developments encoded in regulatory networks of ESCs. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Multiple, non-allelic, intein-coding sequences in eukaryotic RNA polymerase genes

    Directory of Open Access Journals (Sweden)

    Butler Margaret I

    2006-10-01

    Full Text Available Abstract Background Inteins are self-splicing protein elements. They are translated as inserts within host proteins that excise themselves and ligate the flanking portions of the host protein (exteins with a peptide bond. They are encoded as in-frame insertions within the genes for the host proteins. Inteins are found in all three domains of life and in viruses, but have a very sporadic distribution. Only a small number of intein coding sequences have been identified in eukaryotic nuclear genes, and all of these are from ascomycete or basidiomycete fungi. Results We identified seven intein coding sequences within nuclear genes coding for the second largest subunits of RNA polymerase. These sequences were found in diverse eukaryotes: one is in the second largest subunit of RNA polymerase I (RPA2 from the ascomycete fungus Phaeosphaeria nodorum, one is in the RNA polymerase III (RPC2 of the slime mould Dictyostelium discoideum and four intein coding sequences are in RNA polymerase II genes (RPB2, one each from the green alga Chlamydomonas reinhardtii, the zygomycete fungus Spiromyces aspiralis and the chytrid fungi Batrachochytrium dendrobatidis and Coelomomyces stegomyiae. The remaining intein coding sequence is in a viral relic embedded within the genome of the oomycete Phytophthora ramorum. The Chlamydomonas and Dictyostelium inteins are the first nuclear-encoded inteins found outside of the fungi. These new inteins represent a unique dataset: they are found in homologous proteins that form a paralogous group. Although these paralogues diverged early in eukaryotic evolution, their sequences can be aligned over most of their length. The inteins are inserted at multiple distinct sites, each of which corresponds to a highly conserved region of RNA polymerase. This dataset supports earlier work suggesting that inteins preferentially occur in highly conserved regions of their host proteins. Conclusion The identification of these new inteins

  9. Snapshot of the eukaryotic gene expression in muskoxen rumen--a metatranscriptomic approach.

    Directory of Open Access Journals (Sweden)

    Meng Qi

    Full Text Available BACKGROUND: Herbivores rely on digestive tract lignocellulolytic microorganisms, including bacteria, fungi and protozoa, to derive energy and carbon from plant cell wall polysaccharides. Culture independent metagenomic studies have been used to reveal the genetic content of the bacterial species within gut microbiomes. However, the nature of the genes encoded by eukaryotic protozoa and fungi within these environments has not been explored using metagenomic or metatranscriptomic approaches. METHODOLOGY/PRINCIPAL FINDINGS: In this study, a metatranscriptomic approach was used to investigate the functional diversity of the eukaryotic microorganisms within the rumen of muskoxen (Ovibos moschatus, with a focus on plant cell wall degrading enzymes. Polyadenylated RNA (mRNA was sequenced on the Illumina Genome Analyzer II system and 2.8 gigabases of sequences were obtained and 59129 contigs assembled. Plant cell wall degrading enzyme modules including glycoside hydrolases, carbohydrate esterases and polysaccharide lyases were identified from over 2500 contigs. These included a number of glycoside hydrolase family 6 (GH6, GH48 and swollenin modules, which have rarely been described in previous gut metagenomic studies. CONCLUSIONS/SIGNIFICANCE: The muskoxen rumen metatranscriptome demonstrates a much higher percentage of cellulase enzyme discovery and an 8.7x higher rate of total carbohydrate active enzyme discovery per gigabase of sequence than previous rumen metagenomes. This study provides a snapshot of eukaryotic gene expression in the muskoxen rumen, and identifies a number of candidate genes coding for potentially valuable lignocellulolytic enzymes.

  10. WebAUGUSTUS—a web service for training AUGUSTUS and predicting genes in eukaryotes

    Science.gov (United States)

    Hoff, Katharina J.; Stanke, Mario

    2013-01-01

    The prediction of protein coding genes is an important step in the annotation of newly sequenced and assembled genomes. AUGUSTUS is one of the most accurate tools for eukaryotic gene prediction. Here, we present WebAUGUSTUS, a web interface for training AUGUSTUS and predicting genes with AUGUSTUS. Depending on the needs of the user, WebAUGUSTUS generates training gene structures automatically. Besides a genome file, either a file with expressed sequence tags or a file with protein sequences is required for this step. Alternatively, it is possible to submit an externally generated training gene structure file and a genome file. The web service optimizes AUGUSTUS parameters and predicts genes with those parameters. WebAUGUSTUS is available at http://bioinf.uni-greifswald.de/webaugustus. PMID:23700307

  11. WebAUGUSTUS--a web service for training AUGUSTUS and predicting genes in eukaryotes.

    Science.gov (United States)

    Hoff, Katharina J; Stanke, Mario

    2013-07-01

    The prediction of protein coding genes is an important step in the annotation of newly sequenced and assembled genomes. AUGUSTUS is one of the most accurate tools for eukaryotic gene prediction. Here, we present WebAUGUSTUS, a web interface for training AUGUSTUS and predicting genes with AUGUSTUS. Depending on the needs of the user, WebAUGUSTUS generates training gene structures automatically. Besides a genome file, either a file with expressed sequence tags or a file with protein sequences is required for this step. Alternatively, it is possible to submit an externally generated training gene structure file and a genome file. The web service optimizes AUGUSTUS parameters and predicts genes with those parameters. WebAUGUSTUS is available at http://bioinf.uni-greifswald.de/webaugustus.

  12. Toxoplasma gondii gene expression is under the control of regulatory pathways acting through chromatin structure

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    Bougdour A.

    2008-09-01

    Full Text Available The activity state of a gene is determined by a complex regulatory network of co-acting factors affecting the structure of the chromatin into which the gene is embedded. While significant changes of the transcriptome occur during cell differentiation in apicomplexan parasites, basic mechanisms controlling gene expression are still unknown. Recent studies support and expand the concept of the chromatin environment being key factor for the control of transcriptional activity in these lower eukaryotes organisms. Here, we review recent advances in the field of epigenetic gene regulation in Toxoplasma gondii, the model apicomplexan.

  13. UTRdb and UTRsite: a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs

    Science.gov (United States)

    Mignone, Flavio; Grillo, Giorgio; Licciulli, Flavio; Iacono, Michele; Liuni, Sabino; Kersey, Paul J.; Duarte, Jorge; Saccone, Cecilia; Pesole, Graziano

    2005-01-01

    The 5′ and 3′ untranslated regions of eukaryotic mRNAs play crucial roles in the post-transcriptional regulation of gene expression through the modulation of nucleo-cytoplasmic mRNA transport, translation efficiency, subcellular localization and message stability. UTRdb is a curated database of 5′ and 3′ untranslated sequences of eukaryotic mRNAs, derived from several sources of primary data. Experimentally validated functional motifs are annotated (and also collated as the UTRsite database) and cross-links to genomic and protein data are provided. The integration of UTRdb with genomic and protein data has allowed the implementation of a powerful retrieval resource for the selection and extraction of UTR subsets based on their genomic coordinates and/or features of the protein encoded by the relevant mRNA (e.g. GO term, PFAM domain, etc.). All internet resources implemented for retrieval and functional analysis of 5′ and 3′ untranslated regions of eukaryotic mRNAs are accessible at http://www.ba.itb.cnr.it/UTR/. PMID:15608165

  14. Unravelling cis-regulatory elements in the genome of the smallest photosynthetic eukaryote: phylogenetic footprinting in Ostreococcus.

    Science.gov (United States)

    Piganeau, Gwenael; Vandepoele, Klaas; Gourbière, Sébastien; Van de Peer, Yves; Moreau, Hervé

    2009-09-01

    We used a phylogenetic footprinting approach, adapted to high levels of divergence, to estimate the level of constraint in intergenic regions of the extremely gene dense Ostreococcus algae genomes (Chlorophyta, Prasinophyceae). We first benchmarked our method against the Saccharomyces sensu stricto genome data and found that the proportion of conserved non-coding sites was consistent with those obtained with methods using calibration by the neutral substitution rate. We then applied our method to the complete genomes of Ostreococcus tauri and O. lucimarinus, which are the most divergent species from the same genus sequenced so far. We found that 77% of intergenic regions in Ostreococcus still contain some phylogenetic footprints, as compared to 88% for Saccharomyces, corresponding to an average rate of constraint on intergenic region of 17% and 30%, respectively. A comparison with some known functional cis-regulatory elements enabled us to investigate whether some transcriptional regulatory pathways were conserved throughout the green lineage. Strikingly, the size of the phylogenetic footprints depends on gene orientation of neighboring genes, and appears to be genus-specific. In Ostreococcus, 5' intergenic regions contain four times more conserved sites than 3' intergenic regions, whereas in yeast a higher frequency of constrained sites in intergenic regions between genes on the same DNA strand suggests a higher frequency of bidirectional regulatory elements. The phylogenetic footprinting approach can be used despite high levels of divergence in the ultrasmall Ostreococcus algae, to decipher structure of constrained regulatory motifs, and identify putative regulatory pathways conserved within the green lineage.

  15. Differential gene expression in Giardia lamblia under oxidative stress: significance in eukaryotic evolution.

    Science.gov (United States)

    Raj, Dibyendu; Ghosh, Esha; Mukherjee, Avik K; Nozaki, Tomoyoshi; Ganguly, Sandipan

    2014-02-10

    Giardia lamblia is a unicellular, early branching eukaryote causing giardiasis, one of the most common human enteric diseases. Giardia, a microaerophilic protozoan parasite has to build up mechanisms to protect themselves against oxidative stress within the human gut (oxygen concentration 60 μM) to establish its pathogenesis. G. lamblia is devoid of the conventional mechanisms of the oxidative stress management system, including superoxide dismutase, catalase, peroxidase, and glutathione cycling, which are present in most eukaryotes. NADH oxidase is a major component of the electron transport chain of G. lamblia, which in concurrence with disulfide reductase, protects oxygen-labile proteins such as pyruvate: ferredoxin oxidoreductase against oxidative stress by sustaining a reduced intracellular environment. It also contains the arginine dihydrolase pathway, which occurs in a number of anaerobic prokaryotes, includes substrate level phosphorylation and adequately active to make a major contribution to ATP production. To study differential gene expression under three types of oxidative stress, a Giardia genomic DNA array was constructed and hybridized with labeled cDNA of cells with or without stress. The transcriptomic data has been analyzed and further validated using real time PCR. We identified that out of 9216 genes represented on the array, more than 200 genes encoded proteins with functions in metabolism, oxidative stress management, signaling, reproduction and cell division, programmed cell death and cytoskeleton. We recognized genes modulated by at least ≥ 2 fold at a significant time point in response to oxidative stress. The study has highlighted the genes that are differentially expressed during the three experimental conditions which regulate the stress management pathway differently to achieve redox homeostasis. Identification of some unique genes in oxidative stress regulation may help in new drug designing for this common enteric parasite prone to

  16. Inter-species differences of co-expression of neighboring genes in eukaryotic genomes

    Directory of Open Access Journals (Sweden)

    Inaoka Hidenori

    2004-01-01

    Full Text Available Abstract Background There is increasing evidence that gene order within the eukaryotic genome is not random. In yeast and worm, adjacent or neighboring genes tend to be co-expressed. Clustering of co-expressed genes has been found in humans, worm and fruit flies. However, in mice and rats, an effect of chromosomal distance (CD on co-expression has not been investigated yet. Also, no cross-species comparison has been made so far. We analyzed the effect of CD as well as normalized distance (ND using expression data in six eukaryotic species: yeast, fruit fly, worm, rat, mouse and human. Results We analyzed 24 sets of expression data from the six species. Highly co-expressed pairs were sorted into bins of equal sized intervals of CD, and a co-expression rate (CoER in each bin was calculated. In all datasets, a higher CoER was obtained in a short CD range than a long distance range. These results show that across all studied species, there was a consistent effect of CD on co-expression. However, the results using the ND show more diversity. Intra- and inter-species comparisons of CoER reveal that there are significant differences in the co-expression rates of neighboring genes among the species. A pair-wise BLAST analysis finds 8 – 30 % of the highly co-expressed pairs are duplic ated genes. Conclusion We confirmed that in the six eukaryotic species, there was a consistent tendency that neighboring genes are likely to be co-expressed. Results of pair-wised BLAST indicate a significant effect of non-duplicated pairs on co-expression. A comparison of CD and ND suggests the dominant effect of CD.

  17. Evolutionary relationship of archaebacteria, eubacteria, and eukaryotes inferred from phylogenetic trees of duplicated genes.

    Science.gov (United States)

    Iwabe, N; Kuma, K; Hasegawa, M; Osawa, S; Miyata, T

    1989-01-01

    All extant organisms are though to be classified into three primary kingdoms, eubacteria, eukaryotes, and archaebacteria. The molecular evolutionary studies on the origin and evolution of archaebacteria to date have been carried out by inferring a molecular phylogenetic tree of the primary kingdoms based on comparison of a single molecule from a variety of extant species. From such comparison, it was not possible to derive the exact evolutionary relationship among the primary kingdoms, because the root of the tree could not be determined uniquely. To overcome this difficulty, we compared a pair of duplicated genes, elongation factors Tu and G, and the alpha and beta subunits of ATPase, which are thought to have diverged by gene duplication before divergence of the primary kingdoms. Using each protein pair, we inferred a composite phylogenetic tree with two clusters corresponding to different proteins, from which the evolutionary relationship of the primary kingdoms is determined uniquely. The inferred composite trees reveal that archaebacteria are more closely related to eukaryotes than to eubacteria for all the cases. By bootstrap resamplings, this relationship is reproduced with probabilities of 0.96, 0.79, 1.0, and 1.0 for elongation factors Tu and G and for ATPase subunits alpha and beta, respectively. There are also several lines of evidence for the close sequence similarity between archaebacteria and eukaryotes. Thus we propose that this tree topology represents the general evolutionary relationship among the three primary kingdoms. PMID:2531898

  18. Phylogenetic analysis of the core histone doublet and DNA topo II genes of Marseilleviridae: evidence of proto-eukaryotic provenance.

    Science.gov (United States)

    Erives, Albert J

    2017-11-28

    While the genomes of eukaryotes and Archaea both encode the histone-fold domain, only eukaryotes encode the core histone paralogs H2A, H2B, H3, and H4. With DNA, these core histones assemble into the nucleosomal octamer underlying eukaryotic chromatin. Importantly, core histones for H2A and H3 are maintained as neofunctionalized paralogs adapted for general bulk chromatin (canonical H2 and H3) or specialized chromatin (H2A.Z enriched at gene promoters and cenH3s enriched at centromeres). In this context, the identification of core histone-like "doublets" in the cytoplasmic replication factories of the Marseilleviridae (MV) is a novel finding with possible relevance to understanding the origin of eukaryotic chromatin. Here, we analyze and compare the core histone doublet genes from all known MV genomes as well as other MV genes relevant to the origin of the eukaryotic replisome. Using different phylogenetic approaches, we show that MV histone domains encode obligate H2B-H2A and H4-H3 dimers of possible proto-eukaryotic origin. MV core histone moieties form sister clades to each of the four eukaryotic clades of canonical and variant core histones. This suggests that MV core histone moieties diverged prior to eukaryotic neofunctionalizations associated with paired linear chromosomes and variant histone octamer assembly. We also show that MV genomes encode a proto-eukaryotic DNA topoisomerase II enzyme that forms a sister clade to eukaryotes. This is a relevant finding given that DNA topo II influences histone deposition and chromatin compaction and is the second most abundant nuclear protein after histones. The combined domain architecture and phylogenomic analyses presented here suggest that a primitive origin for MV histone genes is a more parsimonious explanation than horizontal gene transfers + gene fusions + sufficient divergence to eliminate relatedness to eukaryotic neofunctionalizations within the H2A and H3 clades without loss of relatedness to each of

  19. Mutational robustness of gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Aalt D J van Dijk

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

  20. Patterns of Transcript Abundance of Eukaryotic Biogeochemically-Relevant Genes in the Amazon River Plume.

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    Brian L Zielinski

    Full Text Available The Amazon River has the largest discharge of all rivers on Earth, and its complex plume system fuels a wide array of biogeochemical processes, across a large area of the western tropical North Atlantic. The plume thus stimulates microbial processes affecting carbon sequestration and nutrient cycles at a global scale. Chromosomal gene expression patterns of the 2.0 to 156 μm size-fraction eukaryotic microbial community were investigated in the Amazon River Plume, generating a robust dataset (more than 100 million mRNA sequences that depicts the metabolic capabilities and interactions among the eukaryotic microbes. Combining classical oceanographic field measurements with metatranscriptomics yielded characterization of the hydrographic conditions simultaneous with a quantification of transcriptional activity and identity of the community. We highlight the patterns of eukaryotic gene expression for 31 biogeochemically significant gene targets hypothesized to be valuable within forecasting models. An advantage to this targeted approach is that the database of reference sequences used to identify the target genes was selectively constructed and highly curated optimizing taxonomic coverage, throughput, and the accuracy of annotations. A coastal diatom bloom highly expressed nitrate transporters and carbonic anhydrase presumably to support high growth rates and enhance uptake of low levels of dissolved nitrate and CO2. Diatom-diazotroph association (DDA: diatoms with nitrogen fixing symbionts blooms were common when surface salinity was mesohaline and dissolved nitrate concentrations were below detection, and hence did not show evidence of nitrate utilization, suggesting they relied on ammonium transporters to aquire recently fixed nitrogen. These DDA blooms in the outer plume had rapid turnover of the photosystem D1 protein presumably caused by photodegradation under increased light penetration in clearer waters, and increased expression of silicon

  1. Gene Regulatory Network Evolution Through Augmenting Topologies

    OpenAIRE

    Cussat-Blanc, Sylvain; Harrington, Kyle; Pollack, Jordan

    2015-01-01

    Artificial gene regulatory networks (GRNs) are biologically inspired dynamical systems used to control various kinds of agents, from the cells in developmental models to embodied robot swarms. Most recent work uses a genetic algorithm (GA) or an evolution strategy in order to optimize the network for a specific task. However, the empirical performances of these algorithms are unsatisfactory. This paper presents an algorithm that primarily exploits a network distance metric, which allows genet...

  2. Gene Regulatory Network Evolution Through Augmenting Topologies

    OpenAIRE

    Cussat-Blanc, Sylvain; Harrington, Kyle; Pollack, Jordan

    2015-01-01

    International audience; Artificial gene regulatory networks (GRNs) are biologically inspired dynamical systems used to control various kinds of agents, from the cells in developmental models to embodied robot swarms. Most recent work uses a genetic algorithm (GA) or an evolution strategy in order to optimize the network for a specific task. However, the empirical performances of these algorithms are unsatisfactory. This paper presents an algorithm that primarily exploits a network distance me...

  3. Glyceraldehyde-3-phosphate dehydrogenase gene diversity in eubacteria and eukaryotes: evidence for intra- and inter-kingdom gene transfer.

    Science.gov (United States)

    Figge, R M; Schubert, M; Brinkmann, H; Cerff, R

    1999-04-01

    Cyanobacteria contain up to three highly divergent glyceraldehyde-3-phosphate dehydrogenase (GAPDH) genes: gap1, gap2, and gap3. Genes gap1 and gap2 are closely related at the sequence level to the nuclear genes encoding cytosolic and chloroplast GAPDH of higher plants and have recently been shown to play distinct key roles in catabolic and anabolic carbon flow, respectively, of the unicellular cyanobacterium Synechocystis sp. PCC6803. In the present study, sequences of 10 GAPDH genes distributed across the cyanobacteria Prochloron didemni, Gloeobacter violaceus PCC7421, and Synechococcus PCC7942 and the alpha-proteobacterium Paracoccus denitrificans and the beta-proteobacterium Ralstonia solanacearum were determined. Prochloron didemni possesses homologs to the gap2 and gap3 genes from Anabaena, Gloeobacter harbors gap1 and gap2 homologs, and Synechococcus possesses gap1, gap2, and gap3. Paracoccus harbors two highly divergent gap genes that are related to gap3, and Ralstonia possesses a homolog of the gap1 gene. Phylogenetic analyses of these sequences in the context of other eubacterial and eukaryotic GAPDH genes reveal that divergence across eubacterial gap1, and gap2, and gap3 genes is greater than that between eubacterial gap1 and eukaroytic glycolytic GapC or between eubacterial gap2 and eukaryotic Calvin cycle GapAB. These data strongly support previous analyses which suggested that eukaryotes acquired their nuclear genes for GapC and GapAB via endosymbiotic gene transfer from the antecedents of mitochondria and chloroplasts, and extend the known range of sequence diversity of the antecedent eubacterial genes. Analyses of available GAPDH sequences from other eubacterial sources indicate that the glycosomal gap gene from trypanosomes (cytosolic in Euglena) and the gap gene from the spirochete Treponema pallidum are each other's closest relatives. This specific relationship can therefore not reflect organismal evolution but must be the result of an

  4. Lateral transfer of tetrahymanol-synthesizing genes has allowed multiple diverse eukaryote lineages to independently adapt to environments without oxygen

    Directory of Open Access Journals (Sweden)

    Takishita Kiyotaka

    2012-02-01

    Full Text Available Abstract Sterols are key components of eukaryotic cellular membranes that are synthesized by multi-enzyme pathways that require molecular oxygen. Because prokaryotes fundamentally lack sterols, it is unclear how the vast diversity of bacterivorous eukaryotes that inhabit hypoxic environments obtain, or synthesize, sterols. Here we show that tetrahymanol, a triterpenoid that does not require molecular oxygen for its biosynthesis, likely functions as a surrogate of sterol in eukaryotes inhabiting oxygen-poor environments. Genes encoding the tetrahymanol synthesizing enzyme squalene-tetrahymanol cyclase were found from several phylogenetically diverged eukaryotes that live in oxygen-poor environments and appear to have been laterally transferred among such eukaryotes. Reviewers This article was reviewed by Eric Bapteste and Eugene Koonin.

  5. Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks.

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    Vipin Narang

    Full Text Available Human gene regulatory networks (GRN can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs. Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data accompanying this manuscript.

  6. Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks.

    Science.gov (United States)

    Narang, Vipin; Ramli, Muhamad Azfar; Singhal, Amit; Kumar, Pavanish; de Libero, Gennaro; Poidinger, Michael; Monterola, Christopher

    2015-01-01

    Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs). Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data) accompanying this manuscript.

  7. Preferential duplication of intermodular hub genes: an evolutionary signature in eukaryotes genome networks.

    Directory of Open Access Journals (Sweden)

    Ricardo M Ferreira

    Full Text Available Whole genome protein-protein association networks are not random and their topological properties stem from genome evolution mechanisms. In fact, more connected, but less clustered proteins are related to genes that, in general, present more paralogs as compared to other genes, indicating frequent previous gene duplication episodes. On the other hand, genes related to conserved biological functions present few or no paralogs and yield proteins that are highly connected and clustered. These general network characteristics must have an evolutionary explanation. Considering data from STRING database, we present here experimental evidence that, more than not being scale free, protein degree distributions of organisms present an increased probability for high degree nodes. Furthermore, based on this experimental evidence, we propose a simulation model for genome evolution, where genes in a network are either acquired de novo using a preferential attachment rule, or duplicated with a probability that linearly grows with gene degree and decreases with its clustering coefficient. For the first time a model yields results that simultaneously describe different topological distributions. Also, this model correctly predicts that, to produce protein-protein association networks with number of links and number of nodes in the observed range for Eukaryotes, it is necessary 90% of gene duplication and 10% of de novo gene acquisition. This scenario implies a universal mechanism for genome evolution.

  8. Characterization of the icmH and icmF genes required for Legionella pneumophila intracellular growth, genes that are present in many bacteria associated with eukaryotic cells.

    Science.gov (United States)

    Zusman, Tal; Feldman, Michal; Halperin, Einat; Segal, Gil

    2004-06-01

    Legionella pneumophila, the causative agent of Legionnaires' disease, replicates intracellularly within a specialized phagosome of mammalian and protozoan host cells, and the Icm/Dot type IV secretion system has been shown to be essential for this process. Unlike all the other known Icm/Dot proteins, the IcmF protein, which was described before, and the IcmH protein, which is characterized here, have homologous proteins in many bacteria (such as Yersinia pestis, Salmonella enterica, Rhizobium leguminosarum, and Vibrio cholerae), all of which associate with eukaryotic cells. Here, we have characterized the L. pneumophila icmH and icmF genes and found that both genes are present in 16 different Legionella species examined. The icmH and icmF genes were found to be absolutely required for intracellular multiplication in Acanthamoeba castellanii and partially required for intracellular growth in HL-60-derived human macrophages, for immediate cytotoxicity, and for salt sensitivity. Mutagenesis of the predicted ATP/GTP binding site of IcmF revealed that the site is partially required for intracellular growth in A. castellanii. Analysis of the regulatory region of the icmH and icmF genes, which were found to be cotranscribed, revealed that it contains at least two regulatory elements. In addition, an icmH::lacZ fusion was shown to be activated during stationary phase in a LetA- and RelA-dependent manner. Our results indicate that although the icmH and icmF genes probably have a different evolutionary origin than the rest of the icm/dot genes, they are part of the icm/dot system and are required for L. pneumophila pathogenesis.

  9. Markov State Models of gene regulatory networks.

    Science.gov (United States)

    Chu, Brian K; Tse, Margaret J; Sato, Royce R; Read, Elizabeth L

    2017-02-06

    Gene regulatory networks with dynamics characterized by multiple stable states underlie cell fate-decisions. Quantitative models that can link molecular-level knowledge of gene regulation to a global understanding of network dynamics have the potential to guide cell-reprogramming strategies. Networks are often modeled by the stochastic Chemical Master Equation, but methods for systematic identification of key properties of the global dynamics are currently lacking. The method identifies the number, phenotypes, and lifetimes of long-lived states for a set of common gene regulatory network models. Application of transition path theory to the constructed Markov State Model decomposes global dynamics into a set of dominant transition paths and associated relative probabilities for stochastic state-switching. In this proof-of-concept study, we found that the Markov State Model provides a general framework for analyzing and visualizing stochastic multistability and state-transitions in gene networks. Our results suggest that this framework-adopted from the field of atomistic Molecular Dynamics-can be a useful tool for quantitative Systems Biology at the network scale.

  10. Patterns of exon-intron architecture variation of genes in eukaryotic genomes

    Directory of Open Access Journals (Sweden)

    Chen Jian-Qun

    2009-01-01

    Full Text Available Abstract Background The origin and importance of exon-intron architecture comprises one of the remaining mysteries of gene evolution. Several studies have investigated the variations of intron length, GC content, ordinal position in a gene and divergence. However, there is little study about the structural variation of exons and introns. Results We investigated the length, GC content, ordinal position and divergence in both exons and introns of 13 eukaryotic genomes, representing plant and animal. Our analyses revealed that three basic patterns of exon-intron variation were present in nearly all analyzed genomes (P Conclusion Although the factors contributing to these patterns have not been identified, our results provide three important clues: common factor(s exist and may shape both exons and introns; the ordinal reduction patterns may reflect a time-orderly evolution; and the larger first and last exons may be splicing-required. These clues provide a framework for elucidating mechanisms involved in the organization of eukaryotic genomes and particularly in building exon-intron structures.

  11. Gene Editing: Regulatory and Translation to Clinic.

    Science.gov (United States)

    Ando, Dale; Meyer, Kathleen

    2017-10-01

    The clinical application and regulatory strategy of genome editing for ex vivo cell therapy is derived from the intersection of two fields of study: viral vector gene therapy trials; and clinical trials with ex vivo purification and engraftment of CD34+ hematopoietic stem cells, T cells, and tumor cell vaccines. This article covers the regulatory and translational preclinical activities needed for a genome editing clinical trial modifying hematopoietic stem cells and the genesis of this current strategy based on previous clinical trials using genome-edited T cells. The SB-728 zinc finger nuclease platform is discussed because this is the most clinically advanced genome editing technology. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. From gene expression to gene regulatory networks in Arabidopsis thaliana.

    Science.gov (United States)

    Needham, Chris J; Manfield, Iain W; Bulpitt, Andrew J; Gilmartin, Philip M; Westhead, David R

    2009-09-03

    The elucidation of networks from a compendium of gene expression data is one of the goals of systems biology and can be a valuable source of new hypotheses for experimental researchers. For Arabidopsis, there exist several thousand microarrays which form a valuable resource from which to learn. A novel Bayesian network-based algorithm to infer gene regulatory networks from gene expression data is introduced and applied to learn parts of the transcriptomic network in Arabidopsis thaliana from a large number (thousands) of separate microarray experiments. Starting from an initial set of genes of interest, a network is grown by iterative addition to the model of the gene, from another defined set of genes, which gives the 'best' learned network structure. The gene set for iterative growth can be as large as the entire genome. A number of networks are inferred and analysed; these show (i) an agreement with the current literature on the circadian clock network, (ii) the ability to model other networks, and (iii) that the learned network hypotheses can suggest new roles for poorly characterized genes, through addition of relevant genes from an unconstrained list of over 15,000 possible genes. To demonstrate the latter point, the method is used to suggest that particular GATA transcription factors are regulators of photosynthetic genes. Additionally, the performance in recovering a known network from different amounts of synthetically generated data is evaluated. Our results show that plausible regulatory networks can be learned from such gene expression data alone. This work demonstrates that network hypotheses can be generated from existing gene expression data for use by experimental biologists.

  13. Analysis of regulatory networks constructed based on gene ...

    Indian Academy of Sciences (India)

    Gene coexpression patterns can reveal gene collections with functional consistency. This study systematically constructs regulatory networks for pituitary tumours by integrating gene coexpression, transcriptional and posttranscriptional regulation. Through network analysis, we elaborate the incidence mechanism of pituitary ...

  14. Analysis of regulatory networks constructed based on gene ...

    Indian Academy of Sciences (India)

    2013-12-09

    Dec 9, 2013 ... Abstract. Gene coexpression patterns can reveal gene collections with functional consistency. This study systematically constructs regulatory networks for pituitary tumours by integrating gene coexpression, transcriptional and posttranscriptional regulation. Through network analysis, we elaborate the ...

  15. 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...

  16. CRISPR-Mediated Base Editing Enables Efficient Disruption of Eukaryotic Genes through Induction of STOP Codons.

    Science.gov (United States)

    Billon, Pierre; Bryant, Eric E; Joseph, Sarah A; Nambiar, Tarun S; Hayward, Samuel B; Rothstein, Rodney; Ciccia, Alberto

    2017-09-21

    Standard CRISPR-mediated gene disruption strategies rely on Cas9-induced DNA double-strand breaks (DSBs). Here, we show that CRISPR-dependent base editing efficiently inactivates genes by precisely converting four codons (CAA, CAG, CGA, and TGG) into STOP codons without DSB formation. To facilitate gene inactivation by induction of STOP codons (iSTOP), we provide access to a database of over 3.4 million single guide RNAs (sgRNAs) for iSTOP (sgSTOPs) targeting 97%-99% of genes in eight eukaryotic species, and we describe a restriction fragment length polymorphism (RFLP) assay that allows the rapid detection of iSTOP-mediated editing in cell populations and clones. To simplify the selection of sgSTOPs, our resource includes annotations for off-target propensity, percentage of isoforms targeted, prediction of nonsense-mediated decay, and restriction enzymes for RFLP analysis. Additionally, our database includes sgSTOPs that could be employed to precisely model over 32,000 cancer-associated nonsense mutations. Altogether, this work provides a comprehensive resource for DSB-free gene disruption by iSTOP. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Clustering context-specific gene regulatory networks.

    Science.gov (United States)

    Ramesh, Archana; Trevino, Robert; VON Hoff, Daniel D; Kim, Seungchan

    2010-01-01

    Gene regulatory networks (GRNs) learned from high throughput genomic data are often hard to visualize due to the large number of nodes and edges involved, rendering them difficult to appreciate. This becomes an important issue when modular structures are inherent in the inferred networks, such as in the recently proposed context-specific GRNs.(12) In this study, we investigate the application of graph clustering techniques to discern modularity in such highly complex graphs, focusing on context-specific GRNs. Identified modules are then associated with a subset of samples and the key pathways enriched in the module. Specifically, we study the use of Markov clustering and spectral clustering on cancer datasets to yield evidence on the possible association amongst different tumor types. Two sets of gene expression profiling data were analyzed to reveal context-specificity as well as modularity in genomic regulations.

  18. Discovery of PPi-type Phosphoenolpyruvate Carboxykinase Genes in Eukaryotes and Bacteria*

    Science.gov (United States)

    Chiba, Yoko; Kamikawa, Ryoma; Nakada-Tsukui, Kumiko; Saito-Nakano, Yumiko; Nozaki, Tomoyoshi

    2015-01-01

    Phosphoenolpyruvate carboxykinase (PEPCK) is one of the pivotal enzymes that regulates the carbon flow of the central metabolism by fixing CO2 to phosphoenolpyruvate (PEP) to produce oxaloacetate or vice versa. Whereas ATP- and GTP-type PEPCKs have been well studied, and their protein identities are established, inorganic pyrophosphate (PPi)-type PEPCK (PPi-PEPCK) is poorly characterized. Despite extensive enzymological studies, its protein identity and encoding gene remain unknown. In this study, PPi-PEPCK has been identified for the first time from a eukaryotic human parasite, Entamoeba histolytica, by conventional purification and mass spectrometric identification of the native enzyme, followed by demonstration of its enzymatic activity. A homolog of the amebic PPi-PEPCK from an anaerobic bacterium Propionibacterium freudenreichii subsp. shermanii also exhibited PPi-PEPCK activity. The primary structure of PPi-PEPCK has no similarity to the functional homologs ATP/GTP-PEPCKs and PEP carboxylase, strongly suggesting that PPi-PEPCK arose independently from the other functional homologues and very likely has unique catalytic sites. PPi-PEPCK homologs were found in a variety of bacteria and some eukaryotes but not in archaea. The molecular identification of this long forgotten enzyme shows us the diversity and functional redundancy of enzymes involved in the central metabolism and can help us to understand the central metabolism more deeply. PMID:26269598

  19. Discovery of PPi-type Phosphoenolpyruvate Carboxykinase Genes in Eukaryotes and Bacteria.

    Science.gov (United States)

    Chiba, Yoko; Kamikawa, Ryoma; Nakada-Tsukui, Kumiko; Saito-Nakano, Yumiko; Nozaki, Tomoyoshi

    2015-09-25

    Phosphoenolpyruvate carboxykinase (PEPCK) is one of the pivotal enzymes that regulates the carbon flow of the central metabolism by fixing CO2 to phosphoenolpyruvate (PEP) to produce oxaloacetate or vice versa. Whereas ATP- and GTP-type PEPCKs have been well studied, and their protein identities are established, inorganic pyrophosphate (PPi)-type PEPCK (PPi-PEPCK) is poorly characterized. Despite extensive enzymological studies, its protein identity and encoding gene remain unknown. In this study, PPi-PEPCK has been identified for the first time from a eukaryotic human parasite, Entamoeba histolytica, by conventional purification and mass spectrometric identification of the native enzyme, followed by demonstration of its enzymatic activity. A homolog of the amebic PPi-PEPCK from an anaerobic bacterium Propionibacterium freudenreichii subsp. shermanii also exhibited PPi-PEPCK activity. The primary structure of PPi-PEPCK has no similarity to the functional homologs ATP/GTP-PEPCKs and PEP carboxylase, strongly suggesting that PPi-PEPCK arose independently from the other functional homologues and very likely has unique catalytic sites. PPi-PEPCK homologs were found in a variety of bacteria and some eukaryotes but not in archaea. The molecular identification of this long forgotten enzyme shows us the diversity and functional redundancy of enzymes involved in the central metabolism and can help us to understand the central metabolism more deeply. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  20. Metatranscriptomics reveals the diversity of genes expressed by eukaryotes in forest soils.

    Directory of Open Access Journals (Sweden)

    Coralie Damon

    Full Text Available Eukaryotic organisms play essential roles in the biology and fertility of soils. For example the micro and mesofauna contribute to the fragmentation and homogenization of plant organic matter, while its hydrolysis is primarily performed by the fungi. To get a global picture of the activities carried out by soil eukaryotes we sequenced 2×10,000 cDNAs synthesized from polyadenylated mRNA directly extracted from soils sampled in beech (Fagus sylvatica and spruce (Picea abies forests. Taxonomic affiliation of both cDNAs and 18S rRNA sequences showed a dominance of sequences from fungi (up to 60% and metazoans while protists represented less than 12% of the 18S rRNA sequences. Sixty percent of cDNA sequences from beech forest soil and 52% from spruce forest soil had no homologs in the GenBank/EMBL/DDJB protein database. A Gene Ontology term was attributed to 39% and 31.5% of the spruce and beech soil sequences respectively. Altogether 2076 sequences were putative homologs to different enzyme classes participating to 129 KEGG pathways among which several were implicated in the utilisation of soil nutrients such as nitrogen (ammonium, amino acids, oligopeptides, sugars, phosphates and sulfate. Specific annotation of plant cell wall degrading enzymes identified enzymes active on major polymers (cellulose, hemicelluloses, pectin, lignin and glycoside hydrolases represented 0.5% (beech soil-0.8% (spruce soil of the cDNAs. Other sequences coding enzymes active on organic matter (extracellular proteases, lipases, a phytase, P450 monooxygenases were identified, thus underlining the biotechnological potential of eukaryotic metatranscriptomes. The phylogenetic affiliation of 12 full-length carbohydrate active enzymes showed that most of them were distantly related to sequences from known fungi. For example, a putative GH45 endocellulase was closely associated to molluscan sequences, while a GH7 cellobiohydrolase was closest to crustacean sequences, thus

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

    Indian Academy of Sciences (India)

    2015-09-28

    Sep 28, 2015 ... [Patel N and Wang JTL 2015 Semi-supervised prediction of gene regulatory networks using machine learning algorithms. J. Biosci. 40 731–740]. DOI 10.1007/s12038-015-9558-9. 1. Introduction. 1.1 Background. Using gene expression data to infer gene regulatory net- works (GRNs) is a key approach to ...

  2. Diffusion driven oscillations in gene regulatory networks.

    Science.gov (United States)

    Macnamara, Cicely K; Chaplain, Mark Aj

    2016-10-21

    Gene regulatory networks (GRNs) play an important role in maintaining cellular function by correctly timing key processes such as cell division and apoptosis. GRNs are known to contain similar structural components, which describe how genes and proteins within a network interact - typically by feedback. In many GRNs, proteins bind to gene-sites in the nucleus thereby altering the transcription rate. If the binding reduces the transcription rate there is a negative feedback leading to oscillatory behaviour in mRNA and protein levels, both spatially (e.g. by observing fluorescently labelled molecules in single cells) and temporally (e.g. by observing protein/mRNA levels over time). Mathematical modelling of GRNs has focussed on such oscillatory behaviour. Recent computational modelling has demonstrated that spatial movement of the molecules is a vital component of GRNs, while it has been proved rigorously that the diffusion coefficient of the protein/mRNA acts as a bifurcation parameter and gives rise to a Hopf-bifurcation. In this paper we consider the spatial aspect further by considering the specific location of gene and protein production, showing that there is an optimum range for the distance between an mRNA gene-site and a protein production site in order to achieve oscillations. We first present a model of a well-known GRN, the Hes1 system, and then extend the approach to examine spatio-temporal models of synthetic GRNs e.g. n-gene repressilator and activator-repressor systems. By incorporating the idea of production sites into such models we show that the spatial component is vital to fully understand GRN dynamics. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Eukaryote-to-eukaryote gene transfer events revealed by the genome sequence of the wine yeast Saccharomyces cerevisiae EC1118.

    Science.gov (United States)

    Novo, Maite; Bigey, Frédéric; Beyne, Emmanuelle; Galeote, Virginie; Gavory, Frédérick; Mallet, Sandrine; Cambon, Brigitte; Legras, Jean-Luc; Wincker, Patrick; Casaregola, Serge; Dequin, Sylvie

    2009-09-22

    Saccharomyces cerevisiae has been used for millennia in winemaking, but little is known about the selective forces acting on the wine yeast genome. We sequenced the complete genome of the diploid commercial wine yeast EC1118, resulting in an assembly of 31 scaffolds covering 97% of the S288c reference genome. The wine yeast differed strikingly from the other S. cerevisiae isolates in possessing 3 unique large regions, 2 of which were subtelomeric, the other being inserted within an EC1118 chromosome. These regions encompass 34 genes involved in key wine fermentation functions. Phylogeny and synteny analyses showed that 1 of these regions originated from a species closely related to the Saccharomyces genus, whereas the 2 other regions were of non-Saccharomyces origin. We identified Zygosaccharomyces bailii, a major contaminant of wine fermentations, as the donor species for 1 of these 2 regions. Although natural hybridization between Saccharomyces strains has been described, this report provides evidence that gene transfer may occur between Saccharomyces and non-Saccharomyces species. We show that the regions identified are frequent and differentially distributed among S. cerevisiae clades, being found almost exclusively in wine strains, suggesting acquisition through recent transfer events. Overall, these data show that the wine yeast genome is subject to constant remodeling through the contribution of exogenous genes. Our results suggest that these processes are favored by ecologic proximity and are involved in the molecular adaptation of wine yeasts to conditions of high sugar, low nitrogen, and high ethanol concentrations.

  4. Evidence that the intra-amoebal Legionella drancourtii acquired a sterol reductase gene from eukaryotes

    Directory of Open Access Journals (Sweden)

    Fournier Pierre-Edouard

    2009-03-01

    Full Text Available Abstract Background Free-living amoebae serve as a natural reservoir for some bacteria that have evolved into «amoeba-resistant» bacteria. Among these, some are strictly intra-amoebal, such as Candidatus "Protochlamydia amoebophila" (Candidatus "P. amoebophila", whose genomic sequence is available. We sequenced the genome of Legionella drancourtii (L. drancourtii, another recently described intra-amoebal bacterium. By comparing these two genomes with those of their closely related species, we were able to study the genetic characteristics specific to their amoebal lifestyle. Findings We identified a sterol delta-7 reductase-encoding gene common to these two bacteria and absent in their relatives. This gene encodes an enzyme which catalyses the last step of cholesterol biosynthesis in eukaryotes, and is probably functional within L. drancourtii since it is transcribed. The phylogenetic analysis of this protein suggests that it was acquired horizontally by a few bacteria from viridiplantae. This gene was also found in the Acanthamoeba polyphaga Mimivirus genome, a virus that grows in amoebae and possesses the largest viral genome known to date. Conclusion L. drancourtii acquired a sterol delta-7 reductase-encoding gene of viridiplantae origin. The most parsimonious hypothesis is that this gene was initially acquired by a Chlamydiales ancestor parasite of plants. Subsequently, its descendents transmitted this gene in amoebae to other intra-amoebal microorganisms, including L. drancourtii and Coxiella burnetii. The role of the sterol delta-7 reductase in prokaryotes is as yet unknown but we speculate that it is involved in host cholesterol parasitism.

  5. A eukaryotic nicotinate-inducible gene cluster: convergent evolution in fungi and bacteria

    Science.gov (United States)

    Ámon, Judit; Fernández-Martín, Rafael; Bokor, Eszter; Cultrone, Antonietta; Kelly, Joan M.; Flipphi, Michel; Scazzocchio, Claudio

    2017-01-01

    Nicotinate degradation has hitherto been elucidated only in bacteria. In the ascomycete Aspergillus nidulans, six loci, hxnS/AN9178 encoding the molybdenum cofactor-containing nicotinate hydroxylase, AN11197 encoding a Cys2/His2 zinc finger regulator HxnR, together with AN11196/hxnZ, AN11188/hxnY, AN11189/hxnP and AN9177/hxnT, are clustered and stringently co-induced by a nicotinate derivative and subject to nitrogen metabolite repression mediated by the GATA factor AreA. These genes are strictly co-regulated by HxnR. Within the hxnR gene, constitutive mutations map in two discrete regions. Aspergillus nidulans is capable of using nicotinate and its oxidation products 6-hydroxynicotinic acid and 2,5-dihydroxypyridine as sole nitrogen sources in an HxnR-dependent way. HxnS is highly similar to HxA, the canonical xanthine dehydrogenase (XDH), and has originated by gene duplication, preceding the origin of the Pezizomycotina. This cluster is conserved with some variations throughout the Aspergillaceae. Our results imply that a fungal pathway has arisen independently from bacterial ones. Significantly, the neo-functionalization of XDH into nicotinate hydroxylase has occurred independently from analogous events in bacteria. This work describes for the first time a gene cluster involved in nicotinate catabolism in a eukaryote and has relevance for the formation and evolution of co-regulated primary metabolic gene clusters and the microbial degradation of N-heterocyclic compounds. PMID:29212709

  6. AS3MT-mediated tolerance to arsenic evolved by multiple independent horizontal gene transfers from bacteria to eukaryotes

    DEFF Research Database (Denmark)

    Palmgren, Michael Broberg; Engström, Karin; Hallström, Björn M

    2017-01-01

    the evolutionary origin of AS3MT and assessed the ability of different genotypes to produce methylated arsenic metabolites. Phylogenetic analysis suggests that multiple, independent horizontal gene transfers between different bacteria, and from bacteria to eukaryotes, increased tolerance to environmental arsenic...

  7. Regulatory Factor X (RFX)-mediated transcriptional rewiring of ciliary genes in animals.

    Science.gov (United States)

    Piasecki, Brian P; Burghoorn, Jan; Swoboda, Peter

    2010-07-20

    Cilia were present in the last eukaryotic common ancestor (LECA) and were retained by most organisms spanning all extant eukaryotic lineages, including organisms in the Unikonta (Amoebozoa, fungi, choanoflagellates, and animals), Archaeplastida, Excavata, Chromalveolata, and Rhizaria. In certain animals, including humans, ciliary gene regulation is mediated by Regulatory Factor X (RFX) transcription factors (TFs). RFX TFs bind X-box promoter motifs and thereby positively regulate >50 ciliary genes. Though RFX-mediated ciliary gene regulation has been studied in several bilaterian animals, little is known about the evolutionary conservation of ciliary gene regulation. Here, we explore the evolutionary relationships between RFX TFs and cilia. By sampling the genome sequences of >120 eukaryotic organisms, we show that RFX TFs are exclusively found in unikont organisms (whether ciliated or not), but are completely absent from the genome sequences of all nonunikont organisms (again, whether ciliated or not). Sampling the promoter sequences of 12 highly conserved ciliary genes from 23 diverse unikont and nonunikont organisms further revealed that phylogenetic footprints of X-box promoter motif sequences are found exclusively in ciliary genes of certain animals. Thus, there is no correlation between cilia/ciliary genes and the presence or absence of RFX TFs and X-box promoter motifs in nonanimal unikont and in nonunikont organisms. These data suggest that RFX TFs originated early in the unikont lineage, distinctly after cilia evolved. The evolutionary model that best explains these observations indicates that the transcriptional rewiring of many ciliary genes by RFX TFs occurred early in the animal lineage.

  8. Regulatory states in the developmental control of gene expression.

    Science.gov (United States)

    Peter, Isabelle S

    2017-09-01

    A growing body of evidence shows that gene expression in multicellular organisms is controlled by the combinatorial function of multiple transcription factors. This indicates that not the individual transcription factors or signaling molecules, but the combination of expressed regulatory molecules, the regulatory state, should be viewed as the functional unit in gene regulation. Here, I discuss the concept of the regulatory state and its proposed role in the genome-wide control of gene expression. Recent analyses of regulatory gene expression in sea urchin embryos have been instrumental for solving the genomic control of cell fate specification in this system. Some of the approaches that were used to determine the expression of regulatory states during sea urchin embryogenesis are reviewed. Significant developmental changes in regulatory state expression leading to the distinct specification of cell fates are regulated by gene regulatory network circuits. How these regulatory state transitions are encoded in the genome is illuminated using the sea urchin endoderm-mesoderms cell fate decision circuit as an example. These observations highlight the importance of considering developmental gene regulation, and the function of individual transcription factors, in the context of regulatory states. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  9. A Regulatory Network Analysis of Orphan Genes in Arabidopsis Thaliana

    Science.gov (United States)

    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.

  10. Expression of conjoined genes: another mechanism for gene regulation in eukaryotes.

    Directory of Open Access Journals (Sweden)

    Tulika Prakash

    Full Text Available From the ENCODE project, it is realized that almost every base of the entire human genome is transcribed. One class of transcripts resulting from this arises from the conjoined gene, which is formed by combining the exons of two or more distinct (parent genes lying on the same strand of a chromosome. Only a very limited number of such genes are known, and the definition and terminologies used for them are highly variable in the public databases. In this work, we have computationally identified and manually curated 751 conjoined genes (CGs in the human genome that are supported by at least one mRNA or EST sequence available in the NCBI database. 353 representative CGs, of which 291 (82% could be confirmed, were subjected to experimental validation using RT-PCR and sequencing methods. We speculate that these genes are arising out of novel functional requirements and are not merely artifacts of transcription, since more than 70% of them are conserved in other vertebrate genomes. The unique splicing patterns exhibited by CGs reveal their possible roles in protein evolution or gene regulation. Novel CGs, for which no transcript is available, could be identified in 80% of randomly selected potential CG forming regions, indicating that their formation is a routine process. Formation of CGs is not only limited to human, as we have also identified 270 CGs in mouse and 227 in drosophila using our approach. Additionally, we propose a novel mechanism for the formation of CGs. Finally, we developed a database, ConjoinG, which contains detailed information about all the CGs (800 in total identified in the human genome. In summary, our findings reveal new insights about the functionality of CGs in terms of another possible mechanism for gene regulation and genomic evolution and the mechanism leading to their formation.

  11. The frequency of eubacterium-to-eukaryote lateral gene transfers shows significant cross-taxa variation within amoebozoa.

    Science.gov (United States)

    Watkins, Russell F; Gray, Michael W

    2006-12-01

    Single-celled bacterivorous eukaryotes offer excellent test cases for evaluation of the frequency of prey-to-predator lateral gene transfer (LGT). Here we use analysis of expressed sequence tag (EST) data sets to quantify the extent of LGT from eubacteria to two amoebae, Acanthamoeba castellanii and Hartmannella vermiformis. Stringent screening for LGT proceeded in several steps intended to enrich for authentic events while at the same time minimizing the incidence of false positives due to factors such as limitations in database coverage and ancient paralogy. The results were compared with data obtained when the same methodology was applied to EST libraries from a number of other eukaryotic taxa. Significant differences in the extent of apparent eubacterium-to-eukaryote LGT were found between taxa. Our results indicate that there may be substantial inter-taxon variation in the number of LGT events that become fixed even between amoebozoan species that have similar feeding modalities.

  12. FFPred 2.0: improved homology-independent prediction of gene ontology terms for eukaryotic protein sequences.

    Directory of Open Access Journals (Sweden)

    Federico Minneci

    Full Text Available To understand fully cell behaviour, biologists are making progress towards cataloguing the functional elements in the human genome and characterising their roles across a variety of tissues and conditions. Yet, functional information - either experimentally validated or computationally inferred by similarity - remains completely missing for approximately 30% of human proteins. FFPred was initially developed to bridge this gap by targeting sequences with distant or no homologues of known function and by exploiting clear patterns of intrinsic disorder associated with particular molecular activities and biological processes. Here, we present an updated and improved version, which builds on larger datasets of protein sequences and annotations, and uses updated component feature predictors as well as revised training procedures. FFPred 2.0 includes support vector regression models for the prediction of 442 Gene Ontology (GO terms, which largely expand the coverage of the ontology and of the biological process category in particular. The GO term list mainly revolves around macromolecular interactions and their role in regulatory, signalling, developmental and metabolic processes. Benchmarking experiments on newly annotated proteins show that FFPred 2.0 provides more accurate functional assignments than its predecessor and the ProtFun server do; also, its assignments can complement information obtained using BLAST-based transfer of annotations, improving especially prediction in the biological process category. Furthermore, FFPred 2.0 can be used to annotate proteins belonging to several eukaryotic organisms with a limited decrease in prediction quality. We illustrate all these points through the use of both precision-recall plots and of the COGIC scores, which we recently proposed as an alternative numerical evaluation measure of function prediction accuracy.

  13. Mutual information and the fidelity of response of gene regulatory models

    Science.gov (United States)

    Tabbaa, Omar P.; Jayaprakash, C.

    2014-08-01

    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.

  14. Evolution of PAS domains and PAS-containing genes in eukaryotes.

    Science.gov (United States)

    Mei, Qiming; Dvornyk, Volodymyr

    2014-08-01

    The PAS domains are signal modules, which are widely distributed in proteins across all kingdoms of life. They are common in photoreceptors and transcriptional regulators of eukaryotic circadian clocks q(bHLH-PAS proteins and PER in animals; PHY and ZTL in plants; and WC-1, 2, and VVD in fungi) and possess mainly protein-protein interaction and light-sensing functions. We conducted several evolutionary analyses of the PAS superfamily. Although the whole superfamily evolved primarily under strong purifying selection (average ω ranges from 0.0030 to 0.1164), some lineages apparently experienced strong episodic positive selection at some periods of the evolution. Although the PAS domains from different proteins vary in sequence and length, but they maintain a fairly conserved 3D structure, which is determined by only eight residues. The WC-1 and WC- 2, bHLH-PAS, and P er genes probably originated in the Neoproterozoic Era (1000-542 Mya), plant P hy and ZTL evolved in the Paleozoic (541-252 Mya), which might be a result of adaptation to the major climate and global light regime changes having occurred in those eras.

  15. Isolation of a novel ras gene from Trichomonas vaginalis: a possible evolutionary ancestor of the Ras and Rap genes of higher eukaryotes.

    Science.gov (United States)

    Xu, Ming-Yan; Liu, Ju-Li; Zhang, Ren-Li; Fu, Yu-cai

    2007-04-01

    The Ras subfamily proteins are small, monomeric GTP-binding proteins with vital roles in regulating eukaryotic signal transduction pathways. Gene duplication and divergence have been postulated as the mechanism by which such family members have evolved their specific functions. A cDNA clone of TvRsp was isolated and sequenced from a cDNA expression library of the primitive eukaryote Trichomonas vaginalis. The genomic DNA corresponding to the cDNA sequence was amplified by PCR and sequenced. Sequence analysis suggested that TvRsp was an intronless gene. This gene encoded a protein of 181 amino acids and contained the 5 conserved G domains that designated it as a Ras or Rap subfamily member. However, the deduced amino acid sequence shared only 34%-37% overall identity with other Ras subfamily members of different species, and the presence of motifs characteristic of both the Ras and Rap families of GTPase confused the familial classification of this gene. Phylogenetic analysis showed its origins at the divergence point of the Ras/Rap families and suggested that TvRsp was a possible evolutionary ancestral gene of the ras/rap genes of higher eukaryotes. This information was of importance not only from the perspective of understanding the evolution and diversity of eukaryotic signal transduction pathways but also in providing a framework by which to understand protein processing in the growth and differentiation of single-celled microorganisms.

  16. Identification of context-specific gene regulatory networks with GEMULA--Gene Expression Modeling Using LAsso

    NARCIS (Netherlands)

    Geeven, G.; van Kesteren, R.E.; Smit, A.B.; de Gunst, M.C.M.

    2012-01-01

    Motivation: Gene regulatory networks, in which edges between nodes describe interactions between transcriptional regulators and their target genes, determine the coordinated spatiotemporal expression of genes. Especially in higher organisms, context-specific combinatorial regulation by transcription

  17. Dynamic integration of splicing within gene regulatory pathways

    National Research Council Canada - National Science Library

    Braunschweig, Ulrich; Gueroussov, Serge; Plocik, Alex M; Graveley, Brenton R; Blencowe, Benjamin J

    2013-01-01

    .... In addition to generating vast repertoires of RNAs and proteins, splicing has a profound impact on other gene regulatory layers, including mRNA transcription, turnover, transport, and translation...

  18. Robustness and accuracy in sea urchin developmental gene regulatory networks

    Directory of Open Access Journals (Sweden)

    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.

  19. Robustness and Accuracy in Sea Urchin Developmental Gene Regulatory Networks.

    Science.gov (United States)

    Ben-Tabou de-Leon, Smadar

    2016-01-01

    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.

  20. Evolving chromosomes and gene regulatory networks

    Indian Academy of Sciences (India)

    Aswin

    Many processes change genomes. Koonin and Wolf. 2008. Page 5 .. including horizontal gene transfer. Koonin and Wolf. 2008. Page 6. Horizontal gene transfer. Drastic modification of genetic material. Rapid exploration of ne niches and phenot pes. Page 7. Horizontal gene transfer regulates. New selective forces for gene ...

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

    Science.gov (United States)

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

    2017-11-02

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

  2. Functional and evolutionary analysis of alternatively spliced genes is consistent with an early eukaryotic origin of alternative splicing

    DEFF Research Database (Denmark)

    Irimia, Manuel; Rukov, Jakob Lewin; Penny, David

    2007-01-01

    , and may therefore predate multicellularity, is still unknown. To better understand the origin and evolution of alternative splicing and its usage in diverse organisms, we studied alternative splicing in 12 eukaryotic species, comparing rates of alternative splicing across genes of different functional...... classes, cellular locations, intron/exon structures and evolutionary origins. RESULTS: For each species, we find that genes from most functional categories are alternatively spliced. Ancient genes (shared between animals, fungi and plants) show high levels of alternative splicing. Genes with products...... expressed in the nucleus or plasma membrane are generally more alternatively spliced while those expressed in extracellular location show less alternative splicing. We find a clear correspondence between incidence of alternative splicing and intron number per gene both within and between genomes. In general...

  3. A scalable algorithm for structure identification of complex gene regulatory network from temporal expression data.

    Science.gov (United States)

    Gui, Shupeng; Rice, Andrew P; Chen, Rui; Wu, Liang; Liu, Ji; Miao, Hongyu

    2017-01-31

    Gene regulatory interactions are of fundamental importance to various biological functions and processes. However, only a few previous computational studies have claimed success in revealing genome-wide regulatory landscapes from temporal gene expression data, especially for complex eukaryotes like human. Moreover, recent work suggests that these methods still suffer from the curse of dimensionality if a network size increases to 100 or higher. Here we present a novel scalable algorithm for identifying genome-wide gene regulatory network (GRN) structures, and we have verified the algorithm performances by extensive simulation studies based on the DREAM challenge benchmark data. The highlight of our method is that its superior performance does not degenerate even for a network size on the order of 10(4), and is thus readily applicable to large-scale complex networks. Such a breakthrough is achieved by considering both prior biological knowledge and multiple topological properties (i.e., sparsity and hub gene structure) of complex networks in the regularized formulation. We also validate and illustrate the application of our algorithm in practice using the time-course gene expression data from a study on human respiratory epithelial cells in response to influenza A virus (IAV) infection, as well as the CHIP-seq data from ENCODE on transcription factor (TF) and target gene interactions. An interesting finding, owing to the proposed algorithm, is that the biggest hub structures (e.g., top ten) in the GRN all center at some transcription factors in the context of epithelial cell infection by IAV. The proposed algorithm is the first scalable method for large complex network structure identification. The GRN structure identified by our algorithm could reveal possible biological links and help researchers to choose which gene functions to investigate in a biological event. The algorithm described in this article is implemented in MATLAB (Ⓡ) , and the source code is

  4. 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.

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

    NARCIS (Netherlands)

    Westenberg, Michel A.; Hijum, Sacha A.F.T. van; Lulko, Andrzej T.; Kuipers, Oscar P.; Roerdink, Jos 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,

  6. Phylogenetic analysis of eukaryotic NEET proteins uncovers a link between a key gene duplication event and the evolution of vertebrates

    Science.gov (United States)

    Inupakutika, Madhuri A.; Sengupta, Soham; Nechushtai, Rachel; Jennings, Patricia A.; Onuchic, Jose' N.; Azad, Rajeev K.; Padilla, Pamela; Mittler, Ron

    2017-02-01

    NEET proteins belong to a unique family of iron-sulfur proteins in which the 2Fe-2S cluster is coordinated by a CDGSH domain that is followed by the “NEET” motif. They are involved in the regulation of iron and reactive oxygen metabolism, and have been associated with the progression of diabetes, cancer, aging and neurodegenerative diseases. Despite their important biological functions, the evolution and diversification of eukaryotic NEET proteins are largely unknown. Here we used the three members of the human NEET protein family (CISD1, mitoNEET; CISD2, NAF-1 or Miner 1; and CISD3, Miner2) as our guides to conduct a phylogenetic analysis of eukaryotic NEET proteins and their evolution. Our findings identified the slime mold Dictyostelium discoideum’s CISD proteins as the closest to the ancient archetype of eukaryotic NEET proteins. We further identified CISD3 homologs in fungi that were previously reported not to contain any NEET proteins, and revealed that plants lack homolog(s) of CISD3. Furthermore, our study suggests that the mammalian NEET proteins, mitoNEET (CISD1) and NAF-1 (CISD2), emerged via gene duplication around the origin of vertebrates. Our findings provide new insights into the classification and expansion of the NEET protein family, as well as offer clues to the diverged functions of the human mitoNEET and NAF-1 proteins.

  7. Construction and expression of eukaryotic expression vectors of full-length, amino-terminus and carboxyl-terminus Raf gene

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    Zhuomin WANG

    2008-06-01

    Full Text Available Background and objective Raf is a key molecule in the Ras-Raf-MEK-ERK signal transduction pathway and is highly activated in different human carcinomas. However, its biological functions and regulation mechanisms are still unclear. The aims of this study were to construct eukaryotic expression vectors with Raf full encoding region, truncated amino-terminus and carboxyl-terminus, respectively. Methods Eukaryotic expression vectors of pCMV-Tag2b-Raf-1, pCMV-Tag2b-N-Raf and pCMV-Tag2b-C-Raf were constructed by gene recombination technique and confirmed by restriction enzyme analysis and DNA sequencing. Furthermore, the expression of these fusion proteins was detected by western blot in transient transfected 293T cells. Results The sequences and open reading frames of these three vectors were completely consistent with experimental design. All target proteins can be detected in 293T cells. Conclusion Eukaryotic expression vectors of pCMV-Tag2b-Raf-1, pCMV-Tag2b-N-Raf and pCMV-Tag2b-C-Raf were successfully constructed and can be expressed in 293T cells.

  8. 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.

  9. The Eukaryotic Promoter Database, EPD: new entry types and links to gene expression data.

    Science.gov (United States)

    Praz, Viviane; Périer, Rouaïda; Bonnard, Claude; Bucher, Philipp

    2002-01-01

    The Eukaryotic Promoter Database (EPD) is an annotated, non-redundant collection of eukaryotic Pol II promoters, for which the transcription start site has been determined experimentally. Access to promoter sequences is provided by pointers to positions in nucleotide sequence entries. The annotation part of an entry includes a description of the initiation site mapping data, exhaustive cross-references to the EMBL nucleotide sequence database, SWISS-PROT, TRANSFAC and other databases, as well as bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. World Wide Web-based interfaces have been developed which enable the user to view EPD entries in different formats, to select and extract promoter sequences according to a variety of criteria, and to navigate to related databases exploiting different cross-references. The EPD web site also features yearly updated base frequency matrices for major eukaryotic promoter elements. EPD can be accessed at http://www.epd.isb-sib.ch.

  10. Stochastic modeling and numerical simulation of gene regulatory networks with protein bursting.

    Science.gov (United States)

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

    2017-05-21

    Gene expression is inherently stochastic. Advanced single-cell microscopy techniques together with mathematical models for single gene expression led to important insights in elucidating the sources of intrinsic noise in prokaryotic and eukaryotic cells. In addition to the finite size effects due to low copy numbers, translational bursting is a dominant source of stochasticity in cell scenarios involving few short lived mRNA transcripts with high translational efficiency (as is typically the case for prokaryotes), causing protein synthesis to occur in random bursts. In the context of gene regulation cascades, the Chemical Master Equation (CME) governing gene expression has in general no closed form solution, and the accurate stochastic simulation of the dynamics of complex gene regulatory networks is a major computational challenge. The CME associated to a single gene self regulatory motif has been previously approximated by a one dimensional time dependent partial integral differential equation (PIDE). However, to the best of our knowledge, multidimensional versions for such PIDE have not been developed yet. Here we propose a multidimensional PIDE model for regulatory networks involving multiple genes with self and cross regulations (in which genes can be regulated by different transcription factors) derived as the continuous counterpart of a CME with jump process. The model offers a reliable description of systems with translational bursting. In order to provide an efficient numerical solution, we develop a semilagrangian method to discretize the differential part of the PIDE, combined with a composed trapezoidal quadrature formula to approximate the integral term. We apply the model and numerical method to study sustained stochastic oscillations and the development of competence, a particular case of transient differentiation attained by certain bacterial cells under stress conditions. We found that the resulting probability distributions are distinguishable

  11. Gene regulatory networks elucidating huanglongbing disease mechanisms.

    Directory of Open Access Journals (Sweden)

    Federico Martinelli

    Full Text Available Next-generation sequencing was exploited to gain deeper insight into the response to infection by Candidatus liberibacter asiaticus (CaLas, especially the immune disregulation and metabolic dysfunction caused by source-sink disruption. Previous fruit transcriptome data were compared with additional RNA-Seq data in three tissues: immature fruit, and young and mature leaves. Four categories of orchard trees were studied: symptomatic, asymptomatic, apparently healthy, and healthy. Principal component analysis found distinct expression patterns between immature and mature fruits and leaf samples for all four categories of trees. A predicted protein - protein interaction network identified HLB-regulated genes for sugar transporters playing key roles in the overall plant responses. Gene set and pathway enrichment analyses highlight the role of sucrose and starch metabolism in disease symptom development in all tissues. HLB-regulated genes (glucose-phosphate-transporter, invertase, starch-related genes would likely determine the source-sink relationship disruption. In infected leaves, transcriptomic changes were observed for light reactions genes (downregulation, sucrose metabolism (upregulation, and starch biosynthesis (upregulation. In parallel, symptomatic fruits over-expressed genes involved in photosynthesis, sucrose and raffinose metabolism, and downregulated starch biosynthesis. We visualized gene networks between tissues inducing a source-sink shift. CaLas alters the hormone crosstalk, resulting in weak and ineffective tissue-specific plant immune responses necessary for bacterial clearance. Accordingly, expression of WRKYs (including WRKY70 was higher in fruits than in leaves. Systemic acquired responses were inadequately activated in young leaves, generally considered the sites where most new infections occur.

  12. Approaches to modeling gene regulatory networks: a gentle introduction.

    Science.gov (United States)

    Schlitt, Thomas

    2013-01-01

    This chapter is split into two main sections; first, I will present an introduction to gene networks. Second, I will discuss various approaches to gene network modeling which will include some examples for using different data sources. Computational modeling has been used for many different biological systems and many approaches have been developed addressing the different needs posed by the different application fields. The modeling approaches presented here are not limited to gene regulatory networks and occasionally I will present other examples. The material covered here is an update based on several previous publications by Thomas Schlitt and Alvis Brazma (FEBS Lett 579(8),1859-1866, 2005; Philos Trans R Soc Lond B Biol Sci 361(1467), 483-494, 2006; BMC Bioinformatics 8(suppl 6), S9, 2007) that formed the foundation for a lecture on gene regulatory networks at the In Silico Systems Biology workshop series at the European Bioinformatics Institute in Hinxton.

  13. A gene regulatory network armature for T-lymphocyte specification

    Energy Technology Data Exchange (ETDEWEB)

    Fung, Elizabeth-sharon [Los Alamos National Laboratory

    2008-01-01

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

  14. The human SUMF1 gene, required for posttranslational sulfatase modification, defines a new gene family which is conserved from pro- to eukaryotes.

    Science.gov (United States)

    Landgrebe, Jobst; Dierks, Thomas; Schmidt, Bernhard; von Figura, Kurt

    2003-10-16

    Recently, the human C(alpha)-formylglycine (FGly)-generating enzyme (FGE), whose deficiency causes the autosomal-recessively transmitted lysosomal storage disease multiple sulfatase deficiency (MSD), has been identified. In sulfatases, FGE posttranslationally converts a cysteine residue to FGly, which is part of the catalytic site and is essential for sulfatase activity. FGE is encoded by the sulfatase modifying factor 1 (SUMF1) gene, which defines a new gene family comprising orthologs from prokaryotes to higher eukaryotes. The genomes of E. coli, S. cerevisiae and C. elegans lack SUMF1, indicating a phylogenetic gap and the existence of an alternative FGly-generating system. The genomes of vertebrates including mouse, man and pufferfish contain a sulfatase modifying factor 2 (SUMF2) gene encoding an FGE paralog of unknown function. SUMF2 evolved from a single exon SUMF1 gene as found in diptera prior to divergent intron acquisition. In several prokaryotic genomes, the SUMF1 gene is cotranscribed with genes encoding sulfatases which require FGly modification. The FGE protein contains a single domain that is made up of three highly conserved subdomains spaced by nonconserved sequences of variable lengths. The similarity among the eukaryotic FGE orthologs varies between 72% and 100% for the three subdomains and is highest for the C-terminal subdomain, which is a hotspot for mutations in MSD patients.

  15. Global Regulatory Differences for Gene- and Cell-Based Therapies

    DEFF Research Database (Denmark)

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

    2017-01-01

    Gene- and cell-based therapies (GCTs) offer potential new treatment options for unmet medical needs. However, the use of conventional regulatory requirements for medicinal products to approve GCTs may impede patient access and therapeutic innovation. Furthermore, requirements differ between juris...

  16. SELANSI: a toolbox for Simulation of Stochastic Gene Regulatory Networks.

    Science.gov (United States)

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

    2017-10-11

    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 (CME) with a partial integral differential equation (PIDE) 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.

  17. Regulatory gene mutations affecting apolipoprotein gene expression: functions and regulatory behavior of known genes may guide future pharmacogenomic approaches to therapy.

    Science.gov (United States)

    Zannis, Vassilis I; Liu, Tong; Zanni, Markella; Kan, Horng-Yuan; Kardassis, Dimitris

    2003-04-01

    A pharmacogenomic approach to therapy requires systematic knowledge of the regulatory regions of the genes, as well as basic understanding of transcriptional regulatory mechanisms of genes. Using the apolipoprotein (apo) A-I/CIII gene cluster as a model system, we have identified by in vitro and in vivo studies the regulatory elements and the factors which control its transcription. Studies in transgenic mice established that the hepatocyte nuclear factor (HNF-4) binding site of the apoCIII enhancer, which controls transcription of both genes, is required for the intestinal expression of apoA-I and apoCIII genes, and enhances synergistically their hepatic transcription in vivo. The three Sp1 sites of the enhancer are also required for the intestinal expression of apoA-land apoCIII genes in vivo, and for the enhancement of the hepatic transcription. The regulation of the apoE/apoCI/apoCIV/apoCII cluster is also cited. It is expected that identification of the regulatory regions of genes will be soon accelerated by the sequencing of several mammalian genomes. The functional analyses of the regulatory domains of genes involved in lipid homeostasis, combined with cross-species sequence comparisons in the near future, may identify natural regulatory gene polymorphisms in the general population that will permit rational pharmacogenomic approaches for treatment of dyslipidemias.

  18. Deduced products of C4-dicarboxylate transport regulatory genes of Rhizobium leguminosarum are homologous to nitrogen regulatory gene products.

    OpenAIRE

    Ronson, C W; Astwood, P M; Nixon, B T; Ausubel, F M

    1987-01-01

    We have sequenced two genes dctB and dctD required for the activation of the C4-dicarboxylate transport structural gene dctA in free-living Rhizobium leguminosarum. The hydropathic profile of the dctB gene product (DctB) suggested that its N-terminal region may be located in the periplasm and its C-terminal region in the cytoplasm. The C-terminal region of DctB was strongly conserved with similar regions of the products of several regulatory genes that may act as environmental sensors, includ...

  19. Implicit methods for qualitative modeling of gene regulatory networks.

    Science.gov (United States)

    Garg, Abhishek; Mohanram, Kartik; De Micheli, Giovanni; Xenarios, Ioannis

    2012-01-01

    Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

  20. 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.

  1. Analysis of gene regulatory networks in the mammalian circadian rhythm.

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    Jun Yan

    2008-10-01

    Full Text Available Circadian rhythm is fundamental in regulating a wide range of cellular, metabolic, physiological, and behavioral activities in mammals. Although a small number of key circadian genes have been identified through extensive molecular and genetic studies in the past, the existence of other key circadian genes and how they drive the genomewide circadian oscillation of gene expression in different tissues still remains unknown. Here we try to address these questions by integrating all available circadian microarray data in mammals. We identified 41 common circadian genes that showed circadian oscillation in a wide range of mouse tissues with a remarkable consistency of circadian phases across tissues. Comparisons across mouse, rat, rhesus macaque, and human showed that the circadian phases of known key circadian genes were delayed for 4-5 hours in rat compared to mouse and 8-12 hours in macaque and human compared to mouse. A systematic gene regulatory network for the mouse circadian rhythm was constructed after incorporating promoter analysis and transcription factor knockout or mutant microarray data. We observed the significant association of cis-regulatory elements: EBOX, DBOX, RRE, and HSE with the different phases of circadian oscillating genes. The analysis of the network structure revealed the paths through which light, food, and heat can entrain the circadian clock and identified that NR3C1 and FKBP/HSP90 complexes are central to the control of circadian genes through diverse environmental signals. Our study improves our understanding of the structure, design principle, and evolution of gene regulatory networks involved in the mammalian circadian rhythm.

  2. Gene Regulatory Network Reconstruction Using Conditional Mutual Information

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    Xiaodong Wang

    2008-06-01

    Full Text Available The inference of gene regulatory network from expression data is an important area of research that provides insight to the inner workings of a biological system. The relevance-network-based approaches provide a simple and easily-scalable solution to the understanding of interaction between genes. Up until now, most works based on relevance network focus on the discovery of direct regulation using correlation coefficient or mutual information. However, some of the more complicated interactions such as interactive regulation and coregulation are not easily detected. In this work, we propose a relevance network model for gene regulatory network inference which employs both mutual information and conditional mutual information to determine the interactions between genes. For this purpose, we propose a conditional mutual information estimator based on adaptive partitioning which allows us to condition on both discrete and continuous random variables. We provide experimental results that demonstrate that the proposed regulatory network inference algorithm can provide better performance when the target network contains coregulated and interactively regulated genes.

  3. Heart morphogenesis gene regulatory networks revealed by temporal expression analysis.

    Science.gov (United States)

    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.

  4. Gap Gene Regulatory Dynamics Evolve along a Genotype Network

    Science.gov (United States)

    Crombach, Anton; Wotton, Karl R.; Jiménez-Guri, Eva; Jaeger, Johannes

    2016-01-01

    Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as “system drift.” System drift is illustrated by the gap gene network—involved in segmental patterning—in dipteran insects. In the classic model organism Drosophila melanogaster and the nonmodel scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them with an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of “genotype networks” and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability). PMID:26796549

  5. 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.

  6. Discovery of Novel Human Gene Regulatory Modules from Gene Co-expression and Promoter Motif Analysis.

    Science.gov (United States)

    Ma, Shisong; Snyder, Michael; Dinesh-Kumar, Savithramma P

    2017-07-17

    Deciphering gene regulatory networks requires identification of gene expression modules. We describe a novel bottom-up approach to identify gene modules regulated by cis-regulatory motifs from a human gene co-expression network. Target genes of a cis-regulatory motif were identified from the network via the motif's enrichment or biased distribution towards transcription start sites in the promoters of co-expressed genes. A gene sub-network containing the target genes was extracted and used to derive gene modules. The analysis revealed known and novel gene modules regulated by the NF-Y motif. The binding of NF-Y proteins to these modules' gene promoters were verified using ENCODE ChIP-Seq data. The analyses also identified 8,048 Sp1 motif target genes, interestingly many of which were not detected by ENCODE ChIP-Seq. These target genes assemble into house-keeping, tissues-specific developmental, and immune response modules. Integration of Sp1 modules with genomic and epigenomic data indicates epigenetic control of Sp1 targets' expression in a cell/tissue specific manner. Finally, known and novel target genes and modules regulated by the YY1, RFX1, IRF1, and 34 other motifs were also identified. The study described here provides a valuable resource to understand transcriptional regulation of various human developmental, disease, or immunity pathways.

  7. Gene co-regulation is highly conserved in the evolution of eukaryotes and prokaryotes.

    NARCIS (Netherlands)

    Snel, B.; Noort, V. van; Huynen, M.A.

    2004-01-01

    Differences between species have been suggested to largely reside in the network of connections among the genes. Nevertheless, the rate at which these connections evolve has not been properly quantified. Here, we measure the extent to which co-regulation between pairs of genes is conserved over

  8. Singular Perturbation Analysis and Gene Regulatory Networks with Delay

    Science.gov (United States)

    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.

  9. Regulatory feedback loops bridge the human gene regulatory network and regulate carcinogenesis.

    Science.gov (United States)

    Chen, Yun-Ru; Huang, Hsuan-Cheng; Lin, Chen-Ching

    2017-11-29

    The development of disease involves a systematic disturbance inside cells and is associated with changes in the interactions or regulations among genes forming biological networks. The bridges inside a network are critical in shortening the distances between nodes. We observed that, inside the human gene regulatory network, one strongly connected core bridged the whole network. Other regulations outside the core formed a weakly connected component surrounding the core like a peripheral structure. Furthermore, the regulatory feedback loops (FBLs) inside the core compose an interface-like structure between the core and periphery. We then denoted the regulatory FBLs as the interface core. Notably, both the cancer-associated and essential biomolecules and regulations were significantly overrepresented in the interface core. These results implied that the interface core is not only critical for the network structure but central in cellular systems. Furthermore, the enrichment of the cancer-associated and essential regulations in the interface core might be attributed to its bridgeness in the network. More importantly, we identified one regulatory FBL between HNF4A and NR2F2 that possesses the highest bridgeness in the interface core. Further investigation suggested that the disturbance of the HNF4A-NR2F2 FBL might protect tumor cells from apoptotic processes. Our results emphasize the relevance of the regulatory network properties to cellular systems and might reveal a critical role of the interface core in cancer. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  10. Eukaryotic genomes may exhibit up to 10 generic classes of gene promoters

    Directory of Open Access Journals (Sweden)

    Gagniuc Paul

    2012-09-01

    Full Text Available Abstract Background The main function of gene promoters appears to be the integration of different gene products in their biological pathways in order to maintain homeostasis. Generally, promoters have been classified in two major classes, namely TATA and CpG. Nevertheless, many genes using the same combinatorial formation of transcription factors have different gene expression patterns. Accordingly, we tried to ask ourselves some fundamental questions: Why certain genes have an overall predisposition for higher gene expression levels than others? What causes such a predisposition? Is there a structural relationship of these sequences in different tissues? Is there a strong phylogenetic relationship between promoters of closely related species? Results In order to gain valuable insights into different promoter regions, we obtained a series of image-based patterns which allowed us to identify 10 generic classes of promoters. A comprehensive analysis was undertaken for promoter sequences from Arabidopsis thaliana, Drosophila melanogaster, Homo sapiens and Oryza sativa, and a more extensive analysis of tissue-specific promoters in humans. We observed a clear preference for these species to use certain classes of promoters for specific biological processes. Moreover, in humans, we found that different tissues use distinct classes of promoters, reflecting an emerging promoter network. Depending on the tissue type, comparisons made between these classes of promoters reveal a complementarity between their patterns whereas some other classes of promoters have been observed to occur in competition. Furthermore, we also noticed the existence of some transitional states between these classes of promoters that may explain certain evolutionary mechanisms, which suggest a possible predisposition for specific levels of gene expression and perhaps for a different number of factors responsible for triggering gene expression. Our conclusions are based on

  11. Roles of lignin biosynthesis and regulatory genes in plant development

    Science.gov (United States)

    Yoon, Jinmi; Choi, Heebak

    2015-01-01

    Abstract Lignin is an important factor affecting agricultural traits, biofuel production, and the pulping industry. Most lignin biosynthesis genes and their regulatory genes are expressed mainly in the vascular bundles of stems and leaves, preferentially in tissues undergoing lignification. Other genes are poorly expressed during normal stages of development, but are strongly induced by abiotic or biotic stresses. Some are expressed in non‐lignifying tissues such as the shoot apical meristem. Alterations in lignin levels affect plant development. Suppression of lignin biosynthesis genes causes abnormal phenotypes such as collapsed xylem, bending stems, and growth retardation. The loss of expression by genes that function early in the lignin biosynthesis pathway results in more severe developmental phenotypes when compared with plants that have mutations in later genes. Defective lignin deposition is also associated with phenotypes of seed shattering or brittle culm. MYB and NAC transcriptional factors function as switches, and some homeobox proteins negatively control lignin biosynthesis genes. Ectopic deposition caused by overexpression of lignin biosynthesis genes or master switch genes induces curly leaf formation and dwarfism. PMID:26297385

  12. Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources

    Directory of Open Access Journals (Sweden)

    Morgenstern Burkhard

    2006-02-01

    Full Text Available Abstract Background In order to improve gene prediction, extrinsic evidence on the gene structure can be collected from various sources of information such as genome-genome comparisons and EST and protein alignments. However, such evidence is often incomplete and usually uncertain. The extrinsic evidence is usually not sufficient to recover the complete gene structure of all genes completely and the available evidence is often unreliable. Therefore extrinsic evidence is most valuable when it is balanced with sequence-intrinsic evidence. Results We present a fairly general method for integration of external information. Our method is based on the evaluation of hints to potentially protein-coding regions by means of a Generalized Hidden Markov Model (GHMM that takes both intrinsic and extrinsic information into account. We used this method to extend the ab initio gene prediction program AUGUSTUS to a versatile tool that we call AUGUSTUS+. In this study, we focus on hints derived from matches to an EST or protein database, but our approach can be used to include arbitrary user-defined hints. Our method is only moderately effected by the length of a database match. Further, it exploits the information that can be derived from the absence of such matches. As a special case, AUGUSTUS+ can predict genes under user-defined constraints, e.g. if the positions of certain exons are known. With hints from EST and protein databases, our new approach was able to predict 89% of the exons in human chromosome 22 correctly. Conclusion Sensitive probabilistic modeling of extrinsic evidence such as sequence database matches can increase gene prediction accuracy. When a match of a sequence interval to an EST or protein sequence is used it should be treated as compound information rather than as information about individual positions.

  13. 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.

  14. An Arabidopsis gene regulatory network for secondary cell wall synthesis.

    Science.gov (United States)

    Taylor-Teeples, M; Lin, L; de Lucas, M; Turco, G; Toal, T W; Gaudinier, A; Young, N F; Trabucco, G M; Veling, M T; Lamothe, R; Handakumbura, P P; Xiong, G; Wang, C; Corwin, J; Tsoukalas, A; Zhang, L; Ware, D; Pauly, M; Kliebenstein, D J; Dehesh, K; Tagkopoulos, I; Breton, G; Pruneda-Paz, J L; Ahnert, S E; Kay, S A; Hazen, S P; Brady, S M

    2015-01-29

    The plant cell wall is an important factor for determining cell shape, function and response to the environment. Secondary cell walls, such as those found in xylem, are composed of cellulose, hemicelluloses and lignin and account for the bulk of plant biomass. The coordination between transcriptional regulation of synthesis for each polymer is complex and vital to cell function. A regulatory hierarchy of developmental switches has been proposed, although the full complement of regulators remains unknown. Here we present a protein-DNA network between Arabidopsis thaliana transcription factors and secondary cell wall metabolic genes with gene expression regulated by a series of feed-forward loops. This model allowed us to develop and validate new hypotheses about secondary wall gene regulation under abiotic stress. Distinct stresses are able to perturb targeted genes to potentially promote functional adaptation. These interactions will serve as a foundation for understanding the regulation of a complex, integral plant component.

  15. Plastid 16S rRNA gene diversity among eukaryotic picophytoplankton sorted by flow cytometry from the South Pacific Ocean.

    Directory of Open Access Journals (Sweden)

    Xiao Li Shi

    Full Text Available The genetic diversity of photosynthetic picoeukaryotes was investigated in the South East Pacific Ocean. Genetic libraries of the plastid 16S rRNA gene were constructed on picoeukaryote populations sorted by flow cytometry, using two different primer sets, OXY107F/OXY1313R commonly used to amplify oxygenic organisms, and PLA491F/OXY1313R, biased towards plastids of marine algae. Surprisingly, the two sets revealed quite different photosynthetic picoeukaryote diversity patterns, which were moreover different from what we previously reported using the 18S rRNA nuclear gene as a marker. The first 16S primer set revealed many sequences related to Pelagophyceae and Dictyochophyceae, the second 16S primer set was heavily biased toward Prymnesiophyceae, while 18S sequences were dominated by Prasinophyceae, Chrysophyceae and Haptophyta. Primer mismatches with major algal lineages is probably one reason behind this discrepancy. However, other reasons, such as DNA accessibility or gene copy numbers, may be also critical. Based on plastid 16S rRNA gene sequences, the structure of photosynthetic picoeukaryotes varied along the BIOSOPE transect vertically and horizontally. In oligotrophic regions, Pelagophyceae, Chrysophyceae, and Prymnesiophyceae dominated. Pelagophyceae were prevalent at the DCM depth and Chrysophyceae at the surface. In mesotrophic regions Pelagophyceae were still important but Chlorophyta contribution increased. Phylogenetic analysis revealed a new clade of Prasinophyceae (clade 16S-IX, which seems to be restricted to hyper-oligotrophic stations. Our data suggest that a single gene marker, even as widely used as 18S rRNA, provides a biased view of eukaryotic communities and that the use of several markers is necessary to obtain a complete image.

  16. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    Science.gov (United States)

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Wei, Ze-Gang; Chen, Luonan

    2016-08-01

    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  17. Riboswitches: discovery of drugs that target bacterial gene-regulatory RNAs

    Science.gov (United States)

    Deigan, Katherine E.; Ferré-D’Amaré, Adrian R.

    2011-01-01

    Conspectus Riboswitches, which were discovered in the first years of the XXI century, are gene-regulatory mRNA domains that respond to the intracellular concentration of a variety of metabolites and second messengers. They control essential genes in many pathogenic bacteria, and represent a new class of biomolecular target for the development of antibiotics and chemical-biological tools. Five mechanisms of gene regulation are known for riboswitches. Most bacterial riboswitches modulate transcription termination or translation initiation in response to ligand binding. All known examples of eukaryotic riboswitches and some bacterial riboswitches control gene expression by alternative splicing. The glmS riboswitch, widespread in Gram-positive bacteria, is a catalytic RNA activated by ligand binding. Its self-cleavage destabilizes the mRNA of which it is part. Finally, one example of trans-acting riboswitch is known. Three-dimensional (3D) structures have been determined of representatives of thirteen structurally distinct riboswitch classes, providing atomic-level insight into their mechanisms of ligand recognition. While cellular and viral RNAs in general have attracted interest as potential drug targets, riboswitches show special promise due to the diversity and sophistication of small molecule recognition strategies on display in their ligand binding pockets. Moreover, uniquely among known structured RNA domains, riboswitches evolved to recognize small molecule ligands. Structural and biochemical advances in the study of riboswitches provide an impetus for the development of methods for the discovery of novel riboswitch activators and inhibitors. Recent rational drug design efforts focused on select riboswitch classes have yielded a small number of candidate antibiotic compounds, including one active in a mouse model of Staphylococcus aureus infection. The development of high-throughput methods suitable for riboswitch-specific drug discovery is ongoing. A fragment

  18. Gene Ontology consistent protein function prediction: the FALCON algorithm applied to six eukaryotic genomes

    NARCIS (Netherlands)

    Kourmpetis, Y.A.I.; Dijk, van A.D.J.; Braak, ter C.J.F.

    2013-01-01

    Gene Ontology (GO) is a hierarchical vocabulary for the description of biological functions and locations, often employed by computational methods for protein function prediction. Due to the structure of GO, function predictions can be self- contradictory. For example, a protein may be predicted to

  19. Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks.

    Science.gov (United States)

    Kalender Atak, Zeynep; Imrichova, Hana; Svetlichnyy, Dmitry; Hulselmans, Gert; Christiaens, Valerie; Reumers, Joke; Ceulemans, Hugo; Aerts, Stein

    2017-08-30

    The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying "personal" gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genomes of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers. μ-cisTarget is available from http://mucistarget.aertslab.org .

  20. Using GeneReg to construct time delay gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Qian Ziliang

    2010-05-01

    Full Text Available Abstract Background Understanding gene expression and regulation is essential for understanding biological mechanisms. Because gene expression profiling has been widely used in basic biological research, especially in transcription regulation studies, we have developed GeneReg, an easy-to-use R package, to construct gene regulatory networks from time course gene expression profiling data; More importantly, this package can provide information about time delays between expression change in a regulator and that of its target genes. Findings The R package GeneReg is based on time delay linear regression, which can generate a model of the expression levels of regulators at a given time point against the expression levels of their target genes at a later time point. There are two parameters in the model, time delay and regulation coefficient. Time delay is the time lag during which expression change of the regulator is transmitted to change in target gene expression. Regulation coefficient expresses the regulation effect: a positive regulation coefficient indicates activation and negative indicates repression. GeneReg was implemented on a real Saccharomyces cerevisiae cell cycle dataset; more than thirty percent of the modeled regulations, based entirely on gene expression files, were found to be consistent with previous discoveries from known databases. Conclusions GeneReg is an easy-to-use, simple, fast R package for gene regulatory network construction from short time course gene expression data. It may be applied to study time-related biological processes such as cell cycle, cell differentiation, or causal inference.

  1. Stability of functions in Boolean models of gene regulatory networks

    Science.gov (United States)

    Rämö, Pauli; Kesseli, Juha; Yli-Harja, Olli

    2005-09-01

    Boolean networks are used to model large nonlinear systems such as gene regulatory networks. We will present results that can be used to understand how the choice of functions affects the network dynamics. The so called bias-map and its fixed points depict much of the function's dynamical role in the network. We define the concept of stabilizing functions and show that many Post and canalizing functions are also stabilizing functions. Boolean networks constructed using the same type of stabilizing functions are always stable regardless of the average in-degree of network functions. We derive the number of all stabilizing functions and find it to be much larger than the number of Post and canalizing functions. We also discuss the implementation of functions and apply the presented results to biological data that give an approximation of the distribution of regulatory functions in eucaryotic cells. We find that the obtained theoretical results on the number of active genes are biologically plausible. Finally, based on the presented results, we discuss why canalizing and Post regulatory functions seem to be common in cells.

  2. Resolution of gene regulatory conflicts caused by combinations of antibiotics.

    Science.gov (United States)

    Bollenbach, Tobias; Kishony, Roy

    2011-05-20

    Regulatory conflicts occur when two signals that individually trigger opposite cellular responses are present simultaneously. Here, we investigate regulatory conflicts in the bacterial response to antibiotic combinations. We use an Escherichia coli promoter-GFP library to study the transcriptional response of many promoters to either additive or antagonistic drug pairs at fine two-dimensional (2D) resolution of drug concentration. Surprisingly, we find that this data set can be characterized as a linear sum of only two principal components. Component one, accounting for over 70% of the response, represents the response to growth inhibition by the drugs. Component two describes how regulatory conflicts are resolved. For the additive drug pair, conflicts are resolved by linearly interpolating the single drug responses, while for the antagonistic drug pair, the growth-limiting drug dominates the response. Importantly, for a given drug pair, the same conflict resolution strategy applies to almost all genes. These results provide a recipe for predicting gene expression responses to antibiotic combinations. Copyright © 2011 Elsevier Inc. All rights reserved.

  3. Regulatory Oversight of Cell and Gene Therapy Products in Canada.

    Science.gov (United States)

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

    2015-01-01

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

  4. AGRIS: Arabidopsis gene regulatory information server, an information resource of Arabidopsis cis-regulatory elements and transcription factors.

    Science.gov (United States)

    Davuluri, Ramana V; Sun, Hao; Palaniswamy, Saranyan K; Matthews, Nicole; Molina, Carlos; Kurtz, Mike; Grotewold, Erich

    2003-06-23

    The gene regulatory information is hardwired in the promoter regions formed by cis-regulatory elements that bind specific transcription factors (TFs). Hence, establishing the architecture of plant promoters is fundamental to understanding gene expression. The determination of the regulatory circuits controlled by each TF and the identification of the cis-regulatory sequences for all genes have been identified as two of the goals of the Multinational Coordinated Arabidopsis thaliana Functional Genomics Project by the Multinational Arabidopsis Steering Committee (June 2002). AGRIS is an information resource of Arabidopsis promoter sequences, transcription factors and their target genes. AGRIS currently contains two databases, AtTFDB (Arabidopsis thaliana transcription factor database) and AtcisDB (Arabidopsis thaliana cis-regulatory database). AtTFDB contains information on approximately 1,400 transcription factors identified through motif searches and grouped into 34 families. AtTFDB links the sequence of the transcription factors with available mutants and, when known, with the possible genes they may regulate. AtcisDB consists of the 5' regulatory sequences of all 29,388 annotated genes with a description of the corresponding cis-regulatory elements. Users can search the databases for (i) promoter sequences, (ii) a transcription factor, (iii) a direct target genes for a specific transcription factor, or (vi) a regulatory network that consists of transcription factors and their target genes. AGRIS provides the necessary software tools on Arabidopsis transcription factors and their putative binding sites on all genes to initiate the identification of transcriptional regulatory networks in the model dicotyledoneous plant Arabidopsis thaliana. AGRIS can be accessed from http://arabidopsis.med.ohio-state.edu.

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

    Directory of Open Access Journals (Sweden)

    Frank eEmmert-Streib

    2014-02-01

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

  6. Topological effects of data incompleteness of gene regulatory networks

    CERN Document Server

    Sanz, J; Borge-Holthoefer, J; Moreno, Y

    2012-01-01

    The topological analysis of biological networks has been a prolific topic in network science during the last decade. A persistent problem with this approach is the inherent uncertainty and noisy nature of the data. One of the cases in which this situation is more marked is that of transcriptional regulatory networks (TRNs) in bacteria. The datasets are incomplete because regulatory pathways associated to a relevant fraction of bacterial genes remain unknown. Furthermore, direction, strengths and signs of the links are sometimes unknown or simply overlooked. Finally, the experimental approaches to infer the regulations are highly heterogeneous, in a way that induces the appearance of systematic experimental-topological correlations. And yet, the quality of the available data increases constantly. In this work we capitalize on these advances to point out the influence of data (in)completeness and quality on some classical results on topological analysis of TRNs, specially regarding modularity at different level...

  7. Construction of a recombinant eukaryotic human ZHX1 gene expression plasmid and the role of ZHX1 in hepatocellular carcinoma.

    Science.gov (United States)

    Wang, Jianping; Liu, Dejie; Liang, Xiaohong; Gao, Lifen; Yue, Xuetian; Yang, Yang; Ma, Chunhong; Liu, Jun

    2013-11-01

    The zinc-fingers and homeoboxes protein 1 (ZHX1) consists of 873 amino acid residues, is localized in the cell nucleus and appears to act as a transcriptional repressor. Previous studies have shown that ZHX1 interacts with nuclear factor Y subunit α (NF-YA), DNA methyltransferases (DNMT) 3B and ZHX2, all of which are involved in tumorigenesis. However, the exact role of ZHX1 in tumorigenesis remains unknown. The aim of the current study was to construct a recombinant eukaryotic expression plasmid containing the human ZHX1 (hZHX1) gene and to investigate the biological activities of ZHX1 in hepatocellular carcinoma (HCC). Reverse transcription-polymerase chain reaction (RT‑PCR) was used to amplify the N- and C-terminal fragments (ZHX1‑N and ZHX1‑C, respectively) of the hZHX1 gene. The two PCR fragments were cloned into the pEASY-T1 vector and subcloned into the pcDNA3 plasmid to generate a recombinant pcDNA3‑ZHX1 plasmid. Following identification by enzyme digestion and DNA sequencing, the recombinant pcDNA3‑ZHX1 plasmid was transfected into SMMC-7721 cells. The level of ZHX1 expression was detected by RT-PCR and western blot analysis. Cell growth curve assays were used to evaluate the effect of ZHX1 on cell proliferation. Moreover, the differential expression of ZHX1 between cancer and adjacent cirrhotic liver tissue was investigated by quantitative PCR (qPCR). Enzyme digestion and DNA sequencing confirmed the successful construction of the recombinant plasmid, pcDNA3‑ZHX1. qPCR and western blot analysis demonstrated that ZHX1 was efficiently expressed in SMMC-7721 cells and overexpression of ZHX1 may inhibit the proliferation of SMMC-7721 cells. In addition, reduced ZHX1 expression is widespread among cancer tissues from HCC patients. In conclusion, a recombinant eukaryotic expression plasmid, pcDNA3‑ZHX1, was successfully constructed. In addition, the current results indicate that a low expression of ZHX1 may be responsible for hepatocarcinogenesis.

  8. Applications of Recombinant Dna Technology in Gastrointestinal Medicine and Hepatology: Basic Paradigms of Molecular Cell Biology. Part B: Eukaryotic Gene Transcription and Post-Transcripional Rna Processing

    Directory of Open Access Journals (Sweden)

    Gary E Wild

    2000-01-01

    Full Text Available The transcription of DNA into RNA is the primary level at which gene expression is controlled in eukaryotic cells. Eukaryotic gene transcription  involves several different RNA polymerases that interact with a host of transcription factors to initiate transcription. Genes that encode proteins are transcribed into messenger RNA (mRNA by RNA polymerase II. Ribosomal RNAs (rRNAs and transfer RNAs (tRNAs are transcribed by RNA polymerase I and III, respectively.  The production of each mRNA in human cells involves complex interactions of proteins (ie, trans-acting factors with specific sequences on the DNA (ie, cis-acting elements. Cis-acting elements are short base sequences adjacent to or within a particular gene. While the regulation of transcription is a pivotal step in the control of gene expression, a variety of molecular events, collectively known as ’RNA processing’  add an additional level of control of gene expression in eukaryotic cells.

  9. A provisional gene regulatory atlas for mouse heart development.

    Science.gov (United States)

    Chen, Hailin; VanBuren, Vincent

    2014-01-01

    Congenital Heart Disease (CHD) is one of the most common birth defects. Elucidating the molecular mechanisms underlying normal cardiac development is an important step towards early identification of abnormalities during the developmental program and towards the creation of early intervention strategies. We developed a novel computational strategy for leveraging high-content data sets, including a large selection of microarray data associated with mouse cardiac development, mouse genome sequence, ChIP-seq data of selected mouse transcription factors and Y2H data of mouse protein-protein interactions, to infer the active transcriptional regulatory network of mouse cardiac development. We identified phase-specific expression activity for 765 overlapping gene co-expression modules that were defined for obtained cardiac lineage microarray data. For each co-expression module, we identified the phase of cardiac development where gene expression for that module was higher than other phases. Co-expression modules were found to be consistent with biological pathway knowledge in Wikipathways, and met expectations for enrichment of pathways involved in heart lineage development. Over 359,000 transcription factor-target relationships were inferred by analyzing the promoter sequences within each gene module for overrepresentation against the JASPAR database of Transcription Factor Binding Site (TFBS) motifs. The provisional regulatory network will provide a framework of studying the genetic basis of CHD.

  10. A provisional gene regulatory atlas for mouse heart development.

    Directory of Open Access Journals (Sweden)

    Hailin Chen

    Full Text Available Congenital Heart Disease (CHD is one of the most common birth defects. Elucidating the molecular mechanisms underlying normal cardiac development is an important step towards early identification of abnormalities during the developmental program and towards the creation of early intervention strategies. We developed a novel computational strategy for leveraging high-content data sets, including a large selection of microarray data associated with mouse cardiac development, mouse genome sequence, ChIP-seq data of selected mouse transcription factors and Y2H data of mouse protein-protein interactions, to infer the active transcriptional regulatory network of mouse cardiac development. We identified phase-specific expression activity for 765 overlapping gene co-expression modules that were defined for obtained cardiac lineage microarray data. For each co-expression module, we identified the phase of cardiac development where gene expression for that module was higher than other phases. Co-expression modules were found to be consistent with biological pathway knowledge in Wikipathways, and met expectations for enrichment of pathways involved in heart lineage development. Over 359,000 transcription factor-target relationships were inferred by analyzing the promoter sequences within each gene module for overrepresentation against the JASPAR database of Transcription Factor Binding Site (TFBS motifs. The provisional regulatory network will provide a framework of studying the genetic basis of CHD.

  11. 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.

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

    Science.gov (United States)

    Xiao, Fei; Gao, Lin; Ye, Yusen; Hu, Yuxuan; He, Ruijie

    2016-01-01

    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.

  13. Evolutionary and Topological Properties of Genes and Community Structures in Human Gene Regulatory Networks.

    Science.gov (United States)

    Szedlak, Anthony; Smith, Nicholas; Liu, Li; Paternostro, Giovanni; Piermarocchi, Carlo

    2016-06-01

    The diverse, specialized genes present in today's lifeforms evolved from a common core of ancient, elementary genes. However, these genes did not evolve individually: gene expression is controlled by a complex network of interactions, and alterations in one gene may drive reciprocal changes in its proteins' binding partners. Like many complex networks, these gene regulatory networks (GRNs) are composed of communities, or clusters of genes with relatively high connectivity. A deep understanding of the relationship between the evolutionary history of single genes and the topological properties of the underlying GRN is integral to evolutionary genetics. Here, we show that the topological properties of an acute myeloid leukemia GRN and a general human GRN are strongly coupled with its genes' evolutionary properties. Slowly evolving ("cold"), old genes tend to interact with each other, as do rapidly evolving ("hot"), young genes. This naturally causes genes to segregate into community structures with relatively homogeneous evolutionary histories. We argue that gene duplication placed old, cold genes and communities at the center of the networks, and young, hot genes and communities at the periphery. We demonstrate this with single-node centrality measures and two new measures of efficiency, the set efficiency and the interset efficiency. We conclude that these methods for studying the relationships between a GRN's community structures and its genes' evolutionary properties provide new perspectives for understanding evolutionary genetics.

  14. Reverse Engineering of Gene Regulatory Networks: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Hache Hendrik

    2009-01-01

    Full Text Available Reverse engineering of gene regulatory networks has been an intensively studied topic in bioinformatics since it constitutes an intermediate step from explorative to causative gene expression analysis. Many methods have been proposed through recent years leading to a wide range of mathematical approaches. In practice, different mathematical approaches will generate different resulting network structures, thus, it is very important for users to assess the performance of these algorithms. We have conducted a comparative study with six different reverse engineering methods, including relevance networks, neural networks, and Bayesian networks. Our approach consists of the generation of defined benchmark data, the analysis of these data with the different methods, and the assessment of algorithmic performances by statistical analyses. Performance was judged by network size and noise levels. The results of the comparative study highlight the neural network approach as best performing method among those under study.

  15. Manipulating the regulatory genes for teicoplanin production in Actinoplanes teichomyceticus.

    Science.gov (United States)

    Horbal, Lilia; Zaburannyy, Nestor; Ostash, Bohdan; Shulga, Sergiy; Fedorenko, Victor

    2012-05-01

    Actinoplanes teichomyceticus produces the lipoglycopeptide antibiotic teicoplanin, which is considered a last line of defense against multidrug resistant Gram-positive cocci. Different strategies have been employed to generate industrial producers of teicoplanin, however they do not include manipulations of teicoplanin biosynthetic genes due to a poorly developed genetic "toolkit" for this strain. Through this work, we extend the choice of vectors that can be conjugally transferred and maintained in A. teichomyceticus. Antibiotic producing properties and stability of the transconjugants have been examined. As an illustration of the utility of pSG5-based vector pKC1139, we improved teicoplanin production by the wild type strain via manipulations of two regulatory genes from the teicoplanin biosynthetic cluster, tcp28 and tcp29.

  16. Optimal Constrained Stationary Intervention in Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Golnaz Vahedi

    2008-05-01

    Full Text Available A key objective of gene network modeling is to develop intervention strategies to alter regulatory dynamics in such a way as to reduce the likelihood of undesirable phenotypes. Optimal stationary intervention policies have been developed for gene regulation in the framework of probabilistic Boolean networks in a number of settings. To mitigate the possibility of detrimental side effects, for instance, in the treatment of cancer, it may be desirable to limit the expected number of treatments beneath some bound. This paper formulates a general constraint approach for optimal therapeutic intervention by suitably adapting the reward function and then applies this formulation to bound the expected number of treatments. A mutated mammalian cell cycle is considered as a case study.

  17. 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.

  18. Neurogenic gene regulatory pathways in the sea urchin embryo.

    Science.gov (United States)

    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.

  19. Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression

    Science.gov (United States)

    MacNeil, Lesley T.; Walhout, Albertha J.M.

    2011-01-01

    In any given cell, thousands of genes are expressed and work in concert to ensure the cell's function, fitness, and survival. Each gene, in turn, must be expressed at the proper time and in the proper amounts to ensure the appropriate functional outcome. The regulation and expression of some genes are highly robust; their expression is controlled by invariable expression programs. For instance, developmental gene expression is extremely similar in a given cell type from one individual to another. The expression of other genes is more variable: Their levels are noisy and are different from cell to cell and from individual to individual. This can be highly beneficial in physiological responses to outside cues and stresses. Recent advances have enabled the analysis of differential gene expression at a systems level. Gene regulatory networks (GRNs) involving interactions between large numbers of genes and their regulators have been mapped onto graphic diagrams that are used to visualize the regulatory relationships. The further characterization of GRNs has already uncovered global principles of gene regulation. Together with synthetic network biology, such studies are starting to provide insights into the transcriptional mechanisms that cause robust versus stochastic gene expression and their relationships to phenotypic robustness and variability. Here, we discuss GRNs and their topological properties in relation to transcriptional and phenotypic outputs in development and organismal physiology. PMID:21324878

  20. Cross-Tissue Regulatory Gene Networks in Coronary Artery Disease.

    Science.gov (United States)

    Talukdar, Husain A; Foroughi Asl, Hassan; Jain, Rajeev K; Ermel, Raili; Ruusalepp, Arno; Franzén, Oscar; Kidd, Brian A; Readhead, Ben; Giannarelli, Chiara; Kovacic, Jason C; Ivert, Torbjörn; Dudley, Joel T; Civelek, Mete; Lusis, Aldons J; Schadt, Eric E; Skogsberg, Josefin; Michoel, Tom; Björkegren, Johan L M

    2016-03-23

    Inferring molecular networks can reveal how genetic perturbations interact with environmental factors to cause common complex diseases. We analyzed genetic and gene expression data from seven tissues relevant to coronary artery disease (CAD) and identified regulatory gene networks (RGNs) and their key drivers. By integrating data from genome-wide association studies, we identified 30 CAD-causal RGNs interconnected in vascular and metabolic tissues, and we validated them with corresponding data from the Hybrid Mouse Diversity Panel. As proof of concept, by targeting the key drivers AIP, DRAP1, POLR2I, and PQBP1 in a cross-species-validated, arterial-wall RGN involving RNA-processing genes, we re-identified this RGN in THP-1 foam cells and independent data from CAD macrophages and carotid lesions. This characterization of the molecular landscape in CAD will help better define the regulation of CAD candidate genes identified by genome-wide association studies and is a first step toward achieving the goals of precision medicine. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  1. 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.

  2. Regulatory genes and their roles for improvement of antibiotic biosynthesis in Streptomyces.

    Science.gov (United States)

    Lu, Fengjuan; Hou, Yanyan; Zhang, Heming; Chu, Yiwen; Xia, Haiyang; Tian, Yongqiang

    2017-08-01

    The numerous secondary metabolites in Streptomyces spp. are crucial for various applications. For example, cephamycin C is used as an antibiotic, and avermectin is used as an insecticide. Specifically, antibiotic yield is closely related to many factors, such as the external environment, nutrition (including nitrogen and carbon sources), biosynthetic efficiency and the regulatory mechanisms in producing strains. There are various types of regulatory genes that work in different ways, such as pleiotropic (or global) regulatory genes, cluster-situated regulators, which are also called pathway-specific regulatory genes, and many other regulators. The study of regulatory genes that influence antibiotic biosynthesis in Streptomyces spp. not only provides a theoretical basis for antibiotic biosynthesis in Streptomyces but also helps to increase the yield of antibiotics via molecular manipulation of these regulatory genes. Currently, more and more emphasis is being placed on the regulatory genes of antibiotic biosynthetic gene clusters in Streptomyces spp., and many studies on these genes have been performed to improve the yield of antibiotics in Streptomyces. This paper lists many antibiotic biosynthesis regulatory genes in Streptomyces spp. and focuses on frequently investigated regulatory genes that are involved in pathway-specific regulation and pleiotropic regulation and their applications in genetic engineering.

  3. 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

  4. Toward microRNA-mediated gene regulatory networks in plants.

    Science.gov (United States)

    Meng, Yijun; Shao, Chaogang; Chen, Ming

    2011-11-01

    Current achievements in plant microRNA (miRNA) research area are inspiring. Molecular cloning and functional elucidation have greatly advanced our understanding of this small RNA species. As one of the ultimate goals, many research efforts devoted to draw a comprehensive view of miRNA-mediated gene regulatory networks in plants. Numerous bioinformatics tools competent for network analysis have been available. However, the most important point for network construction is to obtain reliable analytical results based on sufficient experimental data. Here, we introduced a general workflow to retrieve and analyze the desired data sets that serve as the cornerstones for network construction. For the upstream analyses of miRNA genes, the sequence feature of miRNA promoters should be characterized. And, regulatory relationships between transcription factors (TFs) and miRNA genes need to be investigated. For the downstream part, we emphasized that the high-throughput degradome sequencing data were especially useful for genuine miRNA-target pair identification. Functional characterization of the miRNA targets is essential to provide deep biological insights into certain miRNA-mediated pathways. For miRNAs themselves, studies on their organ- or tissue-specific expression patterns and the mechanism of self-regulation were discussed. Besides, exhaustive literature mining is required to further support or improve the established networks. It is desired that the introduced framework for miRNA-mediated network construction is timely and useful and could inspire more research efforts in the miRNA research area.

  5. Indeterminacy of reverse engineering of Gene Regulatory Networks: the curse of gene elasticity.

    Directory of Open Access Journals (Sweden)

    Arun Krishnan

    Full Text Available BACKGROUND: Gene Regulatory Networks (GRNs have become a major focus of interest in recent years. A number of reverse engineering approaches have been developed to help uncover the regulatory networks giving rise to the observed gene expression profiles. However, this is an overspecified problem due to the fact that more than one genotype (network wiring can give rise to the same phenotype. We refer to this phenomenon as "gene elasticity." In this work, we study the effect of this particular problem on the pure, data-driven inference of gene regulatory networks. METHODOLOGY: We simulated a four-gene network in order to produce "data" (protein levels that we use in lieu of real experimental data. We then optimized the network connections between the four genes with a view to obtain the original network that gave rise to the data. We did this for two different cases: one in which only the network connections were optimized and the other in which both the network connections as well as the kinetic parameters (given as reaction probabilities in our case were estimated. We observed that multiple genotypes gave rise to very similar protein levels. Statistical experimentation indicates that it is impossible to differentiate between the different networks on the basis of both equilibrium as well as dynamic data. CONCLUSIONS: We show explicitly that reverse engineering of GRNs from pure expression data is an indeterminate problem. Our results suggest the unsuitability of an inferential, purely data-driven approach for the reverse engineering transcriptional networks in the case of gene regulatory networks displaying a certain level of complexity.

  6. Reverse engineering highlights potential principles of large gene regulatory network design and learning.

    Science.gov (United States)

    Carré, Clément; Mas, André; Krouk, Gabriel

    2017-01-01

    Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge of systems biology, with potential impacts ranging from medicine to agronomy. There are several techniques used presently to experimentally assay transcription factors to target relationships, defining important information about real gene regulatory networks connections. These techniques include classical ChIP-seq, yeast one-hybrid, or more recently, DAP-seq or target technologies. These techniques are usually used to validate algorithm predictions. Here, we developed a reverse engineering approach based on mathematical and computer simulation to evaluate the impact that this prior knowledge on gene regulatory networks may have on training machine learning algorithms. First, we developed a gene regulatory networks-simulating engine called FRANK (Fast Randomizing Algorithm for Network Knowledge) that is able to simulate large gene regulatory networks (containing 10(4) genes) with characteristics of gene regulatory networks observed in vivo. FRANK also generates stable or oscillatory gene expression directly produced by the simulated gene regulatory networks. The development of FRANK leads to important general conclusions concerning the design of large and stable gene regulatory networks harboring scale free properties (built ex nihilo). In combination with supervised (accepting prior knowledge) support vector machine algorithm we (i) address biologically oriented questions concerning our capacity to accurately reconstruct gene regulatory networks and in particular we demonstrate that prior-knowledge structure is crucial for accurate learning, and (ii) draw conclusions to inform experimental design to performed learning able to solve gene regulatory networks in the future. By demonstrating that our predictions concerning the influence of the prior-knowledge structure on support vector machine learning capacity holds true on real data (Escherichia coli K14 network

  7. Small RNAs with 5'-polyphosphate termini associate with a Piwi-related protein and regulate gene expression in the single-celled eukaryote Entamoeba histolytica.

    Science.gov (United States)

    Zhang, Hanbang; Ehrenkaufer, Gretchen M; Pompey, Justine M; Hackney, Jason A; Singh, Upinder

    2008-11-01

    Small interfering RNAs regulate gene expression in diverse biological processes, including heterochromatin formation and DNA elimination, developmental regulation, and cell differentiation. In the single-celled eukaryote Entamoeba histolytica, we have identified a population of small RNAs of 27 nt size that (i) have 5'-polyphosphate termini, (ii) map antisense to genes, and (iii) associate with an E. histolytica Piwi-related protein. Whole genome microarray expression analysis revealed that essentially all genes to which antisense small RNAs map were not expressed under trophozoite conditions, the parasite stage from which the small RNAs were cloned. However, a number of these genes were expressed in other E. histolytica strains with an inverse correlation between small RNA and gene expression level, suggesting that these small RNAs mediate silencing of the cognate gene. Overall, our results demonstrate that E. histolytica has an abundant 27 nt small RNA population, with features similar to secondary siRNAs from C. elegans, and which appear to regulate gene expression. These data indicate that a silencing pathway mediated by 5'-polyphosphate siRNAs extends to single-celled eukaryotic organisms.

  8. Small RNAs with 5′-Polyphosphate Termini Associate with a Piwi-Related Protein and Regulate Gene Expression in the Single-Celled Eukaryote Entamoeba histolytica

    Science.gov (United States)

    Zhang, Hanbang; Ehrenkaufer, Gretchen M.; Pompey, Justine M.; Hackney, Jason A.; Singh, Upinder

    2008-01-01

    Small interfering RNAs regulate gene expression in diverse biological processes, including heterochromatin formation and DNA elimination, developmental regulation, and cell differentiation. In the single-celled eukaryote Entamoeba histolytica, we have identified a population of small RNAs of 27 nt size that (i) have 5′-polyphosphate termini, (ii) map antisense to genes, and (iii) associate with an E. histolytica Piwi-related protein. Whole genome microarray expression analysis revealed that essentially all genes to which antisense small RNAs map were not expressed under trophozoite conditions, the parasite stage from which the small RNAs were cloned. However, a number of these genes were expressed in other E. histolytica strains with an inverse correlation between small RNA and gene expression level, suggesting that these small RNAs mediate silencing of the cognate gene. Overall, our results demonstrate that E. histolytica has an abundant 27 nt small RNA population, with features similar to secondary siRNAs from C. elegans, and which appear to regulate gene expression. These data indicate that a silencing pathway mediated by 5′-polyphosphate siRNAs extends to single-celled eukaryotic organisms. PMID:19043551

  9. Small RNAs with 5'-polyphosphate termini associate with a Piwi-related protein and regulate gene expression in the single-celled eukaryote Entamoeba histolytica.

    Directory of Open Access Journals (Sweden)

    Hanbang Zhang

    2008-11-01

    Full Text Available Small interfering RNAs regulate gene expression in diverse biological processes, including heterochromatin formation and DNA elimination, developmental regulation, and cell differentiation. In the single-celled eukaryote Entamoeba histolytica, we have identified a population of small RNAs of 27 nt size that (i have 5'-polyphosphate termini, (ii map antisense to genes, and (iii associate with an E. histolytica Piwi-related protein. Whole genome microarray expression analysis revealed that essentially all genes to which antisense small RNAs map were not expressed under trophozoite conditions, the parasite stage from which the small RNAs were cloned. However, a number of these genes were expressed in other E. histolytica strains with an inverse correlation between small RNA and gene expression level, suggesting that these small RNAs mediate silencing of the cognate gene. Overall, our results demonstrate that E. histolytica has an abundant 27 nt small RNA population, with features similar to secondary siRNAs from C. elegans, and which appear to regulate gene expression. These data indicate that a silencing pathway mediated by 5'-polyphosphate siRNAs extends to single-celled eukaryotic organisms.

  10. Gene-Regulatory Activity of α-Tocopherol

    Directory of Open Access Journals (Sweden)

    John K. Lodge

    2010-03-01

    Full Text Available Vitamin E is an essential vitamin and a lipid soluble antioxidant, at least, under in vitro conditions. The antioxidant properties of vitamin E are exerted through its phenolic hydroxyl group, which donates hydrogen to peroxyl radicals, resulting in the formation of stable lipid species. Beside an antioxidant role, important cell signalling properties of vitamin E have been described. By using gene chip technology we have identified α-tocopherol sensitive molecular targets in vivo including christmas factor (involved in the blood coagulation and 5α-steroid reductase type 1 (catalyzes the conversion of testosterone to 5α-dihydrotestosterone being upregulated and γ-glutamyl-cysteinyl synthetase (the rate limiting enzyme in GSH synthesis being downregulated due to a-tocopherol deficiency. α-Tocopherol regulates signal transduction cascades not only at the mRNA but also at the miRNA level since miRNA 122a (involved in lipid metabolism and miRNA 125b (involved in inflammation are downregulated by α-tocopherol. Genetic polymorphisms may determine the biological and gene-regulatory activity of a-tocopherol. In this context we have recently shown that genes encoding for proteins involved in peripheral α-tocopherol transport and degradation are significantly affected by the apoE genotype.

  11. Complex Dynamic Behavior in Simple Gene Regulatory Networks

    Science.gov (United States)

    Santillán Zerón, Moisés

    2007-02-01

    Knowing the complete genome of a given species is just a piece of the puzzle. To fully unveil the systems behavior of an organism, an organ, or even a single cell, we need to understand the underlying gene regulatory dynamics. Given the complexity of the whole system, the ultimate goal is unattainable for the moment. But perhaps, by analyzing the most simple genetic systems, we may be able to develop the mathematical techniques and procedures required to tackle more complex genetic networks in the near future. In the present work, the techniques for developing mathematical models of simple bacterial gene networks, like the tryptophan and lactose operons are introduced. Despite all of the underlying assumptions, such models can provide valuable information regarding gene regulation dynamics. Here, we pay special attention to robustness as an emergent property. These notes are organized as follows. In the first section, the long historical relation between mathematics, physics, and biology is briefly reviewed. Recently, the multidisciplinary work in biology has received great attention in the form of systems biology. The main concepts of this novel science are discussed in the second section. A very slim introduction to the essential concepts of molecular biology is given in the third section. In the fourth section, a brief introduction to chemical kinetics is presented. Finally, in the fifth section, a mathematical model for the lactose operon is developed and analyzed..

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

    Directory of Open Access Journals (Sweden)

    Alina Sîrbu

    2015-05-01

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

  13. Stochastic S-system modeling of gene regulatory network.

    Science.gov (United States)

    Chowdhury, Ahsan Raja; Chetty, Madhu; Evans, Rob

    2015-10-01

    Microarray gene expression data can provide insights into biological processes at a system-wide level and is commonly used for reverse engineering gene regulatory networks (GRN). Due to the amalgamation of noise from different sources, microarray expression profiles become inherently noisy leading to significant impact on the GRN reconstruction process. Microarray replicates (both biological and technical), generated to increase the reliability of data obtained under noisy conditions, have limited influence in enhancing the accuracy of reconstruction . Therefore, instead of the conventional GRN modeling approaches which are deterministic, stochastic techniques are becoming increasingly necessary for inferring GRN from noisy microarray data. In this paper, we propose a new stochastic GRN model by investigating incorporation of various standard noise measurements in the deterministic S-system model. Experimental evaluations performed for varying sizes of synthetic network, representing different stochastic processes, demonstrate the effect of noise on the accuracy of genetic network modeling and the significance of stochastic modeling for GRN reconstruction . The proposed stochastic model is subsequently applied to infer the regulations among genes in two real life networks: (1) the well-studied IRMA network, a real-life in-vivo synthetic network constructed within the Saccharomyces cerevisiae yeast, and (2) the SOS DNA repair network in Escherichia coli.

  14. Gene Regulatory Network for Tapetum Development in Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Dan-Dan Li

    2017-09-01

    Full Text Available In flowering plants, male gametophyte development occurs in the anther. Tapetum, the innermost of the four anther somatic layers, surrounds the developing reproductive cells to provide materials for pollen development. A genetic pathway of DYT1-TDF1-AMS-MS188 in regulating tapetum development has been proven. Here we used laser microdissection and pressure catapulting to capture and analyze the transcriptome data for the Arabidopsis tapetum at two stages. With a comprehensive analysis by the microarray data of dyt1, tdf1, ams, and ms188 mutants, we identified possible downstream genes for each transcription factor. These transcription factors regulate many biological processes in addition to activating the expression of the other transcription factor. Briefly, DYT1 may also regulate early tapetum development via E3 ubiquitin ligases and many other transcription factors. TDF1 is likely involved in redox and cell degradation. AMS probably regulates lipid transfer proteins, which are involved in pollen wall formation, and other E3 ubiquitin ligases, functioning in degradating proteins produced in previous processes. MS188 is responsible for most cell wall-related genes, functioning both in tapetum cell wall degradation and pollen wall formation. These results propose a more complex gene regulatory network for tapetum development and function.

  15. Algebraic model checking for Boolean gene regulatory networks.

    Science.gov (United States)

    Tran, Quoc-Nam

    2011-01-01

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

  16. Analysis of deterministic cyclic gene regulatory network models with delays

    CERN Document Server

    Ahsen, Mehmet Eren; Niculescu, Silviu-Iulian

    2015-01-01

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

  17. Modeling gene regulatory networks: A network simplification algorithm

    Science.gov (United States)

    Ferreira, Luiz Henrique O.; de Castro, Maria Clicia S.; da Silva, Fabricio A. B.

    2016-12-01

    Boolean networks have been used for some time to model Gene Regulatory Networks (GRNs), which describe cell functions. Those models can help biologists to make predictions, prognosis and even specialized treatment when some disturb on the GRN lead to a sick condition. However, the amount of information related to a GRN can be huge, making the task of inferring its boolean network representation quite a challenge. The method shown here takes into account information about the interactome to build a network, where each node represents a protein, and uses the entropy of each node as a key to reduce the size of the network, allowing the further inferring process to focus only on the main protein hubs, the ones with most potential to interfere in overall network behavior.

  18. Comparative genomic analysis reveals a diverse repertoire of genes involved in prokaryote-eukaryote interactions within the Pseudovibrio genus.

    Directory of Open Access Journals (Sweden)

    Stefano eRomano

    2016-03-01

    Full Text Available Strains of the Pseudovibrio genus have been detected worldwide, mainly as part of bacterial communities associated with marine invertebrates, particularly sponges. This recurrent association has been considered as an indication of a symbiotic relationship between these microbes and their host. Until recently, the availability of only two genomes, belonging to closely related strains, has limited the knowledge on the genomic and physiological features of the genus to a single phylogenetic lineage.Here we present 10 newly sequenced genomes of Pseudovibrio strains isolated from marine sponges from the west coast of Ireland, and including the other two publicly available genomes we performed an extensive comparative genomic analysis. Homogeneity was apparent in terms of both the orthologous genes and the metabolic features shared amongst the 12 strains. At the genomic level, a key physiological difference observed amongst the isolates was the presence only in strain P. axinellae AD2 of genes encoding proteins involved in assimilatory nitrate reduction, which was then proved experimentally. We then focused on studying those systems known to be involved in the interactions with eukaryotic and prokaryotic cells. This analysis revealed that the genus harbors a large diversity of toxin-like proteins, secretion systems and their potential effectors. Their distribution in the genus was not always consistent with the phylogenetic relationship of the strains. Finally, our analyses identified new genomic islands encoding potential toxin-immunity systems, previously unknown in the genus.Our analyses shed new light on the Pseudovibrio genus, indicating a large diversity of both metabolic features and systems for interacting with the host. The diversity in both distribution and abundance of these systems amongst the strains underlines how metabolically and phylogenetically similar bacteria may use different strategies to interact with the host and find a niche

  19. Unraveling gene regulatory networks from time-resolved gene expression data -- a measures comparison study

    Directory of Open Access Journals (Sweden)

    Koseska Aneta

    2011-07-01

    Full Text Available Abstract Background Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications. Results Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in

  20. Gene regulatory network models for floral organ determination.

    Science.gov (United States)

    Azpeitia, Eugenio; Davila-Velderrain, José; Villarreal, Carlos; Alvarez-Buylla, Elena R

    2014-01-01

    Understanding how genotypes map unto phenotypes implies an integrative understanding of the processes regulating cell differentiation and morphogenesis, which comprise development. Such a task requires the use of theoretical and computational approaches to integrate and follow the concerted action of multiple genetic and nongenetic components that hold highly nonlinear interactions. Gene regulatory network (GRN) models have been proposed to approach such task. GRN models have become very useful to understand how such types of interactions restrict the multi-gene expression patterns that characterize different cell-fates. More recently, such temporal single-cell models have been extended to recover the temporal and spatial components of morphogenesis. Since the complete genomic GRN is still unknown and intractable for any organism, and some clear developmental modules have been identified, we focus here on the analysis of well-curated and experimentally grounded small GRN modules. One of the first experimentally grounded GRN that was proposed and validated corresponds to the regulatory module involved in floral organ determination. In this chapter we use this GRN as an example of the methodologies involved in: (1) formalizing and integrating molecular genetic data into the logical functions (Boolean functions) that rule gene interactions and dynamics in a Boolean GRN; (2) the algorithms and computational approaches used to recover the steady-states that correspond to each cell type, as well as the set of initial GRN configurations that lead to each one of such states (i.e., basins of attraction); (3) the approaches used to validate a GRN model using wild type and mutant or overexpression data, or to test the robustness of the GRN being proposed; (4) some of the methods that have been used to incorporate random fluctuations in the GRN Boolean functions and enable stochastic GRN models to address the temporal sequence with which gene configurations and cell fates are

  1. Eukaryotic transcription factors

    DEFF Research Database (Denmark)

    Staby, Lasse; O'Shea, Charlotte; Willemoës, Martin

    2017-01-01

    Gene-specific transcription factors (TFs) are key regulatory components of signaling pathways, controlling, for example, cell growth, development, and stress responses. Their biological functions are determined by their molecular structures, as exemplified by their structured DNA-binding domains...

  2. Using SCOPE to identify potential regulatory motifs in coregulated genes.

    Science.gov (United States)

    Martyanov, Viktor; Gross, Robert H

    2011-05-31

    SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data. In this article, we utilize a web version of SCOPE to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs and has been used in other studies. The three algorithms that comprise SCOPE are BEAM, which finds non-degenerate motifs (ACCGGT), PRISM, which finds degenerate motifs (ASCGWT), and SPACER, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from

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

    Science.gov (United States)

    Guo, Liyuan; Wang, Jing

    2017-11-11

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

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

    Directory of Open Access Journals (Sweden)

    David A Garfield

    2013-10-01

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

  5. Regulatory component analysis: a semi-blind extraction approach to infer gene regulatory networks with imperfect biological knowledge.

    Science.gov (United States)

    Wang, Chen; Xuan, Jianhua; Shih, Ie-Ming; Clarke, Robert; Wang, Yue

    2012-08-01

    With the advent of high-throughput biotechnology capable of monitoring genomic signals, it becomes increasingly promising to understand molecular cellular mechanisms through systems biology approaches. One of the active research topics in systems biology is to infer gene transcriptional regulatory networks using various genomic data; this inference problem can be formulated as a linear model with latent signals associated with some regulatory proteins called transcription factors (TFs). As common statistical assumptions may not hold for genomic signals, typical latent variable algorithms such as independent component analysis (ICA) are incapable to reveal underlying true regulatory signals. Liao et al. [1] proposed to perform inference using an approach named network component analysis (NCA), the optimization of which is achieved by a least-squares fitting approach with biological knowledge constraints. However, the incompleteness of biological knowledge and its inconsistency with gene expression data are not considered in the original NCA solution, which could greatly affect the inference accuracy. To overcome these limitations, we propose a linear extraction scheme, namely regulatory component analysis (RCA), to infer underlying regulatory signals even with partial biological knowledge. Numerical simulations show a significant improvement of our proposed RCA over NCA, not only when signal-to-noise-ratio (SNR) is low, but also when the given biological knowledge is incomplete and inconsistent to gene expression data. Furthermore, real biological experiments on E. coli are performed for regulatory network inference in comparison with several typical linear latent variable methods, which again demonstrates the effectiveness and improved performance of the proposed algorithm.

  6. Automated large-scale control of gene regulatory networks.

    Science.gov (United States)

    Tan, Mehmet; Alhajj, Reda; Polat, Faruk

    2010-04-01

    Controlling gene regulatory networks (GRNs) is an important and hard problem. As it is the case in all control problems, the curse of dimensionality is the main issue in real applications. It is possible that hundreds of genes may regulate one biological activity in an organism; this implies a huge state space, even in the case of Boolean models. This is also evident in the literature that shows that only models of small portions of the genome could be used in control applications. In this paper, we empower our framework for controlling GRNs by eliminating the need for expert knowledge to specify some crucial threshold that is necessary for producing effective results. Our framework is characterized by applying the factored Markov decision problem (FMDP) method to the control problem of GRNs. The FMDP is a suitable framework for large state spaces as it represents the probability distribution of state transitions using compact models so that more space and time efficient algorithms could be devised for solving control problems. We successfully mapped the GRN control problem to an FMDP and propose a model reduction algorithm that helps find approximate solutions for large networks by using existing FMDP solvers. The test results reported in this paper demonstrate the efficiency and effectiveness of the proposed approach.

  7. An algebra-based method for inferring gene regulatory networks.

    Science.gov (United States)

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

    2014-03-26

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

  8. Applications of Recombinant DNA Technology in Gastrointestinal Medicine and Hepatology: Basic Paradigms of Molecular Cell Biology. Part A: Eukaryotic Gene Structure and DNA Replication

    Directory of Open Access Journals (Sweden)

    Gary E Wild

    2000-01-01

    Full Text Available Progress in the basic sciences of cell and molecular biology has provided an exciting dimension that has translated into clinically relevant information in every medical subspecialty. Importantly, the application of recombinant DNA technology has played a major role in unravelling the intricacies related to the molecular pathophysiology of disease. This series of review articles constitutes a framework for the integration of the database of new information into the core knowledge base of concepts related to the pathogenesis of gastrointestinal disorders and liver disease. The goal of this series of three articles is to review the basic principles of eukaryotic gene expression. The first article examines the role of DNA in directing the flow of genetic information in eukaryotic cells.

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

    Directory of Open Access Journals (Sweden)

    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

  10. Regulatory elements of Caenorhabditis elegans ribosomal protein genes

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    Sleumer Monica C

    2012-08-01

    Full Text Available Abstract Background Ribosomal protein genes (RPGs are essential, tightly regulated, and highly expressed during embryonic development and cell growth. Even though their protein sequences are strongly conserved, their mechanism of regulation is not conserved across yeast, Drosophila, and vertebrates. A recent investigation of genomic sequences conserved across both nematode species and associated with different gene groups indicated the existence of several elements in the upstream regions of C. elegans RPGs, providing a new insight regarding the regulation of these genes in C. elegans. Results In this study, we performed an in-depth examination of C. elegans RPG regulation and found nine highly conserved motifs in the upstream regions of C. elegans RPGs using the motif discovery algorithm DME. Four motifs were partially similar to transcription factor binding sites from C. elegans, Drosophila, yeast, and human. One pair of these motifs was found to co-occur in the upstream regions of 250 transcripts including 22 RPGs. The distance between the two motifs displayed a complex frequency pattern that was related to their relative orientation. We tested the impact of three of these motifs on the expression of rpl-2 using a series of reporter gene constructs and showed that all three motifs are necessary to maintain the high natural expression level of this gene. One of the motifs was similar to the binding site of an orthologue of POP-1, and we showed that RNAi knockdown of pop-1 impacts the expression of rpl-2. We further determined the transcription start site of rpl-2 by 5’ RACE and found that the motifs lie 40–90 bases upstream of the start site. We also found evidence that a noncoding RNA, contained within the outron of rpl-2, is co-transcribed with rpl-2 and cleaved during trans-splicing. Conclusions Our results indicate that C. elegans RPGs are regulated by a complex novel series of regulatory elements that is evolutionarily distinct from

  11. Posttranscriptional mechanisms in controlling eukaryotic circadian rhythms.

    Science.gov (United States)

    Zhang, Lin; Weng, Wenya; Guo, Jinhu

    2011-05-20

    The circadian clock is essential in almost all living organisms to synchronise biochemical, metabolic, physiological and behavioural cycles to daily changing environmental factors. In a highly conserved fashion, the circadian clock is primarily controlled by multiple positive and negative molecular circuitries that control gene expression. More recently, research in Neurospora and other eukaryotes has uncovered the involvement of additional regulatory components that operate at the posttranslational level to fine tune the circadian system. Though it remains poorly understood, a growing body of evidence has shown that posttranscriptional regulation controls the expression of both circadian oscillator and output gene transcripts at a number of different steps. This regulation is crucial for driving and maintaining robust circadian rhythms. Here we review recent advances in circadian rhythm research at the RNA level. Copyright © 2011 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  12. Intervention in gene regulatory networks with maximal phenotype alteration.

    Science.gov (United States)

    Yousefi, Mohammadmahdi R; Dougherty, Edward R

    2013-07-15

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

  13. Design and experimental application of a novel non-degenerate universal primer set that amplifies prokaryotic 16S rRNA genes with a low possibility to amplify eukaryotic rRNA genes.

    Science.gov (United States)

    Mori, Hiroshi; Maruyama, Fumito; Kato, Hiromi; Toyoda, Atsushi; Dozono, Ayumi; Ohtsubo, Yoshiyuki; Nagata, Yuji; Fujiyama, Asao; Tsuda, Masataka; Kurokawa, Ken

    2014-01-01

    The deep sequencing of 16S rRNA genes amplified by universal primers has revolutionized our understanding of microbial communities by allowing the characterization of the diversity of the uncultured majority. However, some universal primers also amplify eukaryotic rRNA genes, leading to a decrease in the efficiency of sequencing of prokaryotic 16S rRNA genes with possible mischaracterization of the diversity in the microbial community. In this study, we compared 16S rRNA gene sequences from genome-sequenced strains and identified candidates for non-degenerate universal primers that could be used for the amplification of prokaryotic 16S rRNA genes. The 50 identified candidates were investigated to calculate their coverage for prokaryotic and eukaryotic rRNA genes, including those from uncultured taxa and eukaryotic organelles, and a novel universal primer set, 342F-806R, covering many prokaryotic, but not eukaryotic, rRNA genes was identified. This primer set was validated by the amplification of 16S rRNA genes from a soil metagenomic sample and subsequent pyrosequencing using the Roche 454 platform. The same sample was also used for pyrosequencing of the amplicons by employing a commonly used primer set, 338F-533R, and for shotgun metagenomic sequencing using the Illumina platform. Our comparison of the taxonomic compositions inferred by the three sequencing experiments indicated that the non-degenerate 342F-806R primer set can characterize the taxonomic composition of the microbial community without substantial bias, and is highly expected to be applicable to the analysis of a wide variety of microbial communities.

  14. Identifying key genes in glaucoma based on a benchmarked dataset and the gene regulatory network.

    Science.gov (United States)

    Chen, Xi; Wang, Qiao-Ling; Zhang, Meng-Hui

    2017-10-01

    The current study aimed to identify key genes in glaucoma based on a benchmarked dataset and gene regulatory network (GRN). Local and global noise was added to the gene expression dataset to produce a benchmarked dataset. Differentially-expressed genes (DEGs) between patients with glaucoma and normal controls were identified utilizing the Linear Models for Microarray Data (Limma) package based on benchmarked dataset. A total of 5 GRN inference methods, including Zscore, GeneNet, context likelihood of relatedness (CLR) algorithm, Partial Correlation coefficient with Information Theory (PCIT) and GEne Network Inference with Ensemble of Trees (Genie3) were evaluated using receiver operating characteristic (ROC) and precision and recall (PR) curves. The interference method with the best performance was selected to construct the GRN. Subsequently, topological centrality (degree, closeness and betweenness) was conducted to identify key genes in the GRN of glaucoma. Finally, the key genes were validated by performing reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A total of 176 DEGs were detected from the benchmarked dataset. The ROC and PR curves of the 5 methods were analyzed and it was determined that Genie3 had a clear advantage over the other methods; thus, Genie3 was used to construct the GRN. Following topological centrality analysis, 14 key genes for glaucoma were identified, including IL6, EPHA2 and GSTT1 and 5 of these 14 key genes were validated by RT-qPCR. Therefore, the current study identified 14 key genes in glaucoma, which may be potential biomarkers to use in the diagnosis of glaucoma and aid in identifying the molecular mechanism of this disease.

  15. An extended phylogenetic analysis reveals ancient origin of "non-green" phosphoribulokinase genes from two lineages of "green" secondary photosynthetic eukaryotes: Euglenophyta and Chlorarachniophyta

    Directory of Open Access Journals (Sweden)

    Sekimoto Hiroyuki

    2011-09-01

    Full Text Available Abstract Background Euglenophyta and Chlorarachniophyta are groups of photosynthetic eukaryotes harboring secondary plastids of distinct green algal origins. Although previous phylogenetic analyses of genes encoding Calvin cycle enzymes demonstrated the presence of genes apparently not derived from green algal endosymbionts in the nuclear genomes of Euglena gracilis (Euglenophyta and Bigelowiella natans (Chlorarachniophyta, the origins of these "non-green" genes in "green" secondary phototrophs were unclear due to the limited taxon sampling. Results Here, we sequenced five new phosphoribulokinase (PRK genes (from one euglenophyte, two chlorarachniophytes, and two glaucophytes and performed an extended phylogenetic analysis of the genes based on a phylum-wide taxon sampling from various photosynthetic eukaryotes. Our phylogenetic analyses demonstrated that the PRK sequences form two genera of Euglenophyta formed a robust monophyletic group within a large clade including stramenopiles, haptophytes and a cryptophyte, and three genera of Chlorarachniophyta were placed within the red algal clade. These "non-green" affiliations were supported by the taxon-specific insertion/deletion sequences in the PRK alignment, especially between euglenophytes and stramenopiles. In addition, phylogenetic analysis of another Calvin cycle enzyme, plastid-targeted sedoheptulose-bisphosphatase (SBP, showed that the SBP sequences from two genera of Chlorarachniophyta were positioned within a red algal clade. Conclusions Our results suggest that PRK genes may have been transferred from a "stramenopile" ancestor to Euglenophyta and from a "red algal" ancestor to Chlorarachniophyta before radiation of extant taxa of these two "green" secondary phototrophs. The presence of two of key Calvin cycle enzymes, PRK and SBP, of red algal origins in Chlorarachniophyta indicate that the contribution of "non-green" algae to the plastid proteome in the "green" secondary phototrophs is

  16. Production and characterization of novel recombinant adeno-associated virus replicative-form genomes: a eukaryotic source of DNA for gene transfer.

    Directory of Open Access Journals (Sweden)

    Lina Li

    Full Text Available Conventional non-viral gene transfer uses bacterial plasmid DNA containing antibiotic resistance genes, cis-acting bacterial sequence elements, and prokaryotic methylation patterns that may adversely affect transgene expression and vector stability in vivo. Here, we describe novel replicative forms of a eukaryotic vector DNA that consist solely of an expression cassette flanked by adeno-associated virus (AAV inverted terminal repeats. Extensive structural analyses revealed that this AAV-derived vector DNA consists of linear, duplex molecules with covalently closed ends (termed closed-ended, linear duplex, or "CELiD", DNA. CELiD vectors, produced in Sf9 insect cells, require AAV rep gene expression for amplification. Amounts of CELiD DNA produced from insect cell lines stably transfected with an ITR-flanked transgene exceeded 60 mg per 5 × 10(9 Sf9 cells, and 1-15 mg from a comparable number of parental Sf9 cells in which the transgene was introduced via recombinant baculovirus infection. In mice, systemically delivered CELiD DNA resulted in long-term, stable transgene expression in the liver. CELiD vectors represent a novel eukaryotic alternative to bacterial plasmid DNA.

  17. Regulatory Divergence between Parental Alleles Determines Gene Expression Patterns in Hybrids

    Science.gov (United States)

    Combes, Marie-Christine; Hueber, Yann; Dereeper, Alexis; Rialle, Stéphanie; Herrera, Juan-Carlos; Lashermes, Philippe

    2015-01-01

    Both hybridization and allopolyploidization generate novel phenotypes by conciliating divergent genomes and regulatory networks in the same cellular context. To understand the rewiring of gene expression in hybrids, the total expression of 21,025 genes and the allele-specific expression of over 11,000 genes were quantified in interspecific hybrids and their parental species, Coffea canephora and Coffea eugenioides using RNA-seq technology. Between parental species, cis- and trans-regulatory divergences affected around 32% and 35% of analyzed genes, respectively, with nearly 17% of them showing both. The relative importance of trans-regulatory divergences between both species could be related to their low genetic divergence and perennial habit. In hybrids, among divergently expressed genes between parental species and hybrids, 77% was expressed like one parent (expression level dominance), including 65% like C. eugenioides. Gene expression was shown to result from the expression of both alleles affected by intertwined parental trans-regulatory factors. A strong impact of C. eugenioides trans-regulatory factors on the upregulation of C. canephora alleles was revealed. The gene expression patterns appeared determined by complex combinations of cis- and trans-regulatory divergences. In particular, the observed biased expression level dominance seemed to be derived from the asymmetric effects of trans-regulatory parental factors on regulation of alleles. More generally, this study illustrates the effects of divergent trans-regulatory parental factors on the gene expression pattern in hybrids. The characteristics of the transcriptional response to hybridization appear to be determined by the compatibility of gene regulatory networks and therefore depend on genetic divergences between the parental species and their evolutionary history. PMID:25819221

  18. Reconstructing context-specific gene regulatory network and identifying modules and network rewiring through data integration.

    Science.gov (United States)

    Ma, Tianle; Zhang, Aidong

    2017-07-15

    Reconstructing context-specific transcriptional regulatory network is crucial for deciphering principles of regulatory mechanisms underlying various conditions. Recently studies that reconstructed transcriptional networks have focused on individual organisms or cell types and relied on data repositories of context-free regulatory relationships. Here we present a comprehensive framework to systematically derive putative regulator-target pairs in any given context by integrating context-specific transcriptional profiling and public data repositories of gene regulatory networks. Moreover, our framework can identify core regulatory modules and signature genes underlying global regulatory circuitry, and detect network rewiring and core rewired modules in different contexts by considering gene modules and edge (gene interaction) modules collaboratively. We applied our methods to analyzing Autism RNA-seq experiment data and produced biologically meaningful results. In particular, all 11 hub genes in a predicted rewired autistic regulatory subnetwork have been linked to autism based on literature review. The predicted rewired autistic regulatory network may shed some new insight into disease mechanism. Published by Elsevier Inc.

  19. 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

  20. Modular reorganization of the global network of gene regulatory interactions during perinatal human brain development.

    Science.gov (United States)

    Monzón-Sandoval, Jimena; Castillo-Morales, Atahualpa; Urrutia, Araxi O; Gutierrez, Humberto

    2016-05-12

    During early development of the nervous system, gene expression patterns are known to vary widely depending on the specific developmental trajectories of different structures. Observable changes in gene expression profiles throughout development are determined by an underlying network of precise regulatory interactions between individual genes. Elucidating the organizing principles that shape this gene regulatory network is one of the central goals of developmental biology. Whether the developmental programme is the result of a dynamic driven by a fixed architecture of regulatory interactions, or alternatively, the result of waves of regulatory reorganization is not known. Here we contrast these two alternative models by examining existing expression data derived from the developing human brain in prenatal and postnatal stages. We reveal a sharp change in gene expression profiles at birth across brain areas. This sharp division between foetal and postnatal profiles is not the result of pronounced changes in level of expression of existing gene networks. Instead we demonstrate that the perinatal transition is marked by the widespread regulatory rearrangement within and across existing gene clusters, leading to the emergence of new functional groups. This rearrangement is itself organized into discrete blocks of genes, each targeted by a distinct set of transcriptional regulators and associated to specific biological functions. Our results provide evidence of an acute modular reorganization of the regulatory architecture of the brain transcriptome occurring at birth, reflecting the reassembly of new functional associations required for the normal transition from prenatal to postnatal brain development.

  1. 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.

  2. Clinical characteristics and prognosis of acute myeloid leukemia associated with DNA-methylation regulatory gene mutations.

    Science.gov (United States)

    Ryotokuji, Takeshi; Yamaguchi, Hiroki; Ueki, Toshimitsu; Usuki, Kensuke; Kurosawa, Saiko; Kobayashi, Yutaka; Kawata, Eri; Tajika, Kenji; Gomi, Seiji; Kanda, Junya; Kobayashi, Anna; Omori, Ikuko; Marumo, Atsushi; Fujiwara, Yusuke; Yui, Shunsuke; Terada, Kazuki; Fukunaga, Keiko; Hirakawa, Tsuneaki; Arai, Kunihito; Kitano, Tomoaki; Kosaka, Fumiko; Tamai, Hayato; Nakayama, Kazutaka; Wakita, Satoshi; Fukuda, Takahiro; Inokuchi, Koiti

    2016-09-01

    In recent years, it has been reported that the frequency of DNA-methylation regulatory gene mutations - mutations of the genes that regulate gene expression through DNA methylation - is high in acute myeloid leukemia. The objective of the present study was to elucidate the clinical characteristics and prognosis of acute myeloid leukemia with associated DNA-methylation regulatory gene mutation. We studied 308 patients with acute myeloid leukemia. DNA-methylation regulatory gene mutations were observed in 135 of the 308 cases (43.8%). Acute myeloid leukemia associated with a DNA-methylation regulatory gene mutation was more frequent in older patients (Pgene mutation was an unfavorable prognostic factor for overall survival in the whole cohort (P=0.0018), in patients aged ≤70 years, in patients with intermediate cytogenetic risk, and in FLT3-ITD-negative patients (P=0.0409). Among the patients with DNA-methylation regulatory gene mutations, 26.7% were found to have two or more such mutations and prognosis worsened with increasing number of mutations. In multivariate analysis DNA-methylation regulatory gene mutation was an independent unfavorable prognostic factor for overall survival (P=0.0424). However, patients with a DNA-methylation regulatory gene mutation who underwent allogeneic stem cell transplantation in first remission had a significantly better prognosis than those who did not undergo such transplantation (P=0.0254). Our study establishes that DNA-methylation regulatory gene mutation is an important unfavorable prognostic factor in acute myeloid leukemia. Copyright© Ferrata Storti Foundation.

  3. New Regulatory Gene That Contributes to Control of Bacteroides thetaiotaomicron Starch Utilization Genes

    Science.gov (United States)

    Cho, Kyu Hong; Cho, Diedre; Wang, Gui-Rong; Salyers, Abigail A.

    2001-01-01

    Bacteroides thetaiotaomicron uses starch as a source of carbon and energy. Early steps in the pathway of starch utilization, such as starch binding and starch hydrolysis, are encoded by sus genes, which have been characterized previously. The sus structural genes are expressed only if cells are grown in medium containing maltose or higher oligomers of glucose. Regulation of the sus structural genes is mediated by SusR, an activator that is encoded by a gene located next to the sus structural genes. A strain with a disruption in susR cannot grow on starch but can still grow on maltose and maltotriose. A search for transposon-generated mutants that could not grow on maltose and maltotriose unexpectedly located a gene, designated malR, which regulates expression of an α-glucosidase not controlled by SusR. Although a disruption in susR did not affect expression of the malR controlled gene, a disruption in malR reduced expression of the sus structural genes. Thus, MalR appears to participate with SusR in regulation of the sus genes. Results of transcriptional fusion assays and reverse transcription-PCR experiments showed that malR is expressed constitutively. Moreover, multiple copies of malR provided on a plasmid (5 to 10 copies per cell) more than doubled the amount of α-glucosidase activity in cell extracts. Our results demonstrate that the starch utilization system of B. thetaiotaomicron is controlled on at least two levels by the regulatory proteins SusR and MalR. PMID:11717279

  4. Isolation and characterization of strong gene regulatory sequences from apple, Malus x domestica

    NARCIS (Netherlands)

    Schaart, J.G.; Tinnenbroek, I.E.M.; Krens, F.A.

    2011-01-01

    For the strong expression of genes in plant tissue, the availability of specific gene regulatory sequences is desired. We cloned promoter and terminator sequences of an apple (Malus x domestica) ribulose biphosphate carboxylase small subunit gene (MdRbcS), which is known for its high expression and

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

    Science.gov (United States)

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

    2011-01-01

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

  6. Gene therapeutics and DNA vaccines; quality and regulatory aspects

    NARCIS (Netherlands)

    Schalk JAC; Hegger I; Jongen PMJM; LGM

    2001-01-01

    Transfer of genes to cells and the subsequent expression of these genes can alleviate the symptoms of a disease (gene therapy), or prevent infectious diseases (DNA vaccination). Gene therapy and DNA vaccination are based on relatively new technologies. The first gene therapeutics are expected to

  7. A provisional regulatory gene network for specification of endomesoderm in the sea urchin embryo

    Science.gov (United States)

    Davidson, Eric H.; Rast, Jonathan P.; Oliveri, Paola; Ransick, Andrew; Calestani, Cristina; Yuh, Chiou-Hwa; Minokawa, Takuya; Amore, Gabriele; Hinman, Veronica; Arenas-Mena, Cesar; hide

    2002-01-01

    We present the current form of a provisional DNA sequence-based regulatory gene network that explains in outline how endomesodermal specification in the sea urchin embryo is controlled. The model of the network is in a continuous process of revision and growth as new genes are added and new experimental results become available; see http://www.its.caltech.edu/mirsky/endomeso.htm (End-mes Gene Network Update) for the latest version. The network contains over 40 genes at present, many newly uncovered in the course of this work, and most encoding DNA-binding transcriptional regulatory factors. The architecture of the network was approached initially by construction of a logic model that integrated the extensive experimental evidence now available on endomesoderm specification. The internal linkages between genes in the network have been determined functionally, by measurement of the effects of regulatory perturbations on the expression of all relevant genes in the network. Five kinds of perturbation have been applied: (1) use of morpholino antisense oligonucleotides targeted to many of the key regulatory genes in the network; (2) transformation of other regulatory factors into dominant repressors by construction of Engrailed repressor domain fusions; (3) ectopic expression of given regulatory factors, from genetic expression constructs and from injected mRNAs; (4) blockade of the beta-catenin/Tcf pathway by introduction of mRNA encoding the intracellular domain of cadherin; and (5) blockade of the Notch signaling pathway by introduction of mRNA encoding the extracellular domain of the Notch receptor. The network model predicts the cis-regulatory inputs that link each gene into the network. Therefore, its architecture is testable by cis-regulatory analysis. Strongylocentrotus purpuratus and Lytechinus variegatus genomic BAC recombinants that include a large number of the genes in the network have been sequenced and annotated. Tests of the cis-regulatory predictions of

  8. Gene regulatory networks in plants: learning causality from time and perturbation.

    Science.gov (United States)

    Krouk, Gabriel; Lingeman, Jesse; Colon, Amy Marshall; Coruzzi, Gloria; Shasha, Dennis

    2013-06-27

    The goal of systems biology is to generate models for predicting how a system will react under untested conditions or in response to genetic perturbations. This paper discusses experimental and analytical approaches to deriving causal relationships in gene regulatory networks.

  9. MicroRNAs and gene regulatory networks: managing the impact of noise in biological systems.

    Science.gov (United States)

    Herranz, Héctor; Cohen, Stephen M

    2010-07-01

    Biological systems are continuously challenged by an environment that is variable. Yet, a key feature of developmental and physiological processes is their remarkable stability. This review considers how microRNAs contribute to gene regulatory networks that confer robustness.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-01-05

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

  11. Reverse engineering and analysis of genome-wide gene regulatory networks from gene expression profiles using high-performance computing.

    Science.gov (United States)

    Belcastro, Vincenzo; Gregoretti, Francesco; Siciliano, Velia; Santoro, Michele; D'Angelo, Giovanni; Oliva, Gennaro; di Bernardo, Diego

    2012-01-01

    Regulation of gene expression is a carefully regulated phenomenon in the cell. “Reverse-engineering” algorithms try to reconstruct the regulatory interactions among genes from genome-scale measurements of gene expression profiles (microarrays). Mammalian cells express tens of thousands of genes; hence, hundreds of gene expression profiles are necessary in order to have acceptable statistical evidence of interactions between genes. As the number of profiles to be analyzed increases, so do computational costs and memory requirements. In this work, we designed and developed a parallel computing algorithm to reverse-engineer genome-scale gene regulatory networks from thousands of gene expression profiles. The algorithm is based on computing pairwise Mutual Information between each gene-pair. We successfully tested it to reverse engineer the Mus Musculus (mouse) gene regulatory network in liver from gene expression profiles collected from a public repository. A parallel hierarchical clustering algorithm was implemented to discover “communities” within the gene network. Network communities are enriched for genes involved in the same biological functions. The inferred network was used to identify two mitochondrial proteins.

  12. Codon usage of HIV regulatory genes is not determined by nucleotide composition.

    Science.gov (United States)

    Phakaratsakul, Supinya; Sirihongthong, Thanyaporn; Boonarkart, Chompunuch; Suptawiwat, Ornpreya; Auewarakul, Prasert

    2018-02-01

    Codon usage bias can be a result of either mutational bias or selection for translational efficiency and/or accuracy. Previous data has suggested that nucleotide composition constraint was the main determinant of HIV codon usage, and that nucleotide composition and codon usage were different between the regulatory genes, tat and rev, and other viral genes. It is not clear whether translational selection contributed to the codon usage difference and how nucleotide composition and translational selection interact to determine HIV codon usage. In this study, a model of codon bias due to GC composition with modification for the A-rich third codon position was used to calculate predicted HIV codon frequencies based on its nucleotide composition. The predicted codon usage of each gene was compared with the actual codon frequency. The predicted codon usage based on GC composition matched well with the actual codon frequencies for the structural genes (gag, pol and env). However, the codon usage of the regulatory genes (tat and rev) could not be predicted. Codon usage of the regulatory genes was also relatively unbiased showing the highest effective number of codons (ENC). Moreover, the codon adaptation index (CAI) of the regulatory genes showed better adaptation to human codons when compared to other HIV genes. Therefore, the early expressed genes responsible for regulation of the replication cycle, tat and rev, were more similar to humans in terms of codon usage and GC content than other HIV genes. This may help these genes to be expressed efficiently during the early stages of infection.

  13. A novel parametric approach to mine gene regulatory relationship from microarray datasets

    Directory of Open Access Journals (Sweden)

    Zhu Yunping

    2010-12-01

    Full Text Available Abstract Background Microarray has been widely used to measure the gene expression level on the genome scale in the current decade. Many algorithms have been developed to reconstruct gene regulatory networks based on microarray data. Unfortunately, most of these models and algorithms focus on global properties of the expression of genes in regulatory networks. And few of them are able to offer intuitive parameters. We wonder whether some simple but basic characteristics of microarray datasets can be found to identify the potential gene regulatory relationship. Results Based on expression correlation, expression level variation and vectors derived from microarray expression levels, we first introduced several novel parameters to measure the characters of regulating gene pairs. Subsequently, we used the naïve Bayesian network to integrate these features as well as the functional co-annotation between transcription factors and their target genes. Then, based on the character of time-delay from the expression profile, we were able to predict the existence and direction of the regulatory relationship respectively. Conclusions Several novel parameters have been proposed and integrated to identify the regulatory relationship. This new model is proved to be of higher efficacy than that of individual features. It is believed that our parametric approach can serve as a fast approach for regulatory relationship mining.

  14. Reconstructing gene-regulatory networks from time series, knock-out data, and prior knowledge

    Directory of Open Access Journals (Sweden)

    Timmer Jens

    2007-02-01

    Full Text Available Abstract Background Cellular processes are controlled by gene-regulatory networks. Several computational methods are currently used to learn the structure of gene-regulatory networks from data. This study focusses on time series gene expression and gene knock-out data in order to identify the underlying network structure. We compare the performance of different network reconstruction methods using synthetic data generated from an ensemble of reference networks. Data requirements as well as optimal experiments for the reconstruction of gene-regulatory networks are investigated. Additionally, the impact of prior knowledge on network reconstruction as well as the effect of unobserved cellular processes is studied. Results We identify linear Gaussian dynamic Bayesian networks and variable selection based on F-statistics as suitable methods for the reconstruction of gene-regulatory networks from time series data. Commonly used discrete dynamic Bayesian networks perform inferior and this result can be attributed to the inevitable information loss by discretization of expression data. It is shown that short time series generated under transcription factor knock-out are optimal experiments in order to reveal the structure of gene regulatory networks. Relative to the level of observational noise, we give estimates for the required amount of gene expression data in order to accurately reconstruct gene-regulatory networks. The benefit of using of prior knowledge within a Bayesian learning framework is found to be limited to conditions of small gene expression data size. Unobserved processes, like protein-protein interactions, induce dependencies between gene expression levels similar to direct transcriptional regulation. We show that these dependencies cannot be distinguished from transcription factor mediated gene regulation on the basis of gene expression data alone. Conclusion Currently available data size and data quality make the reconstruction of

  15. Arabinogalactan proteins have deep roots in eukaryotes: identification of genes and epitopes in brown algae and their role in Fucus serratus embryo development.

    Science.gov (United States)

    Hervé, Cécile; Siméon, Amandine; Jam, Murielle; Cassin, Andrew; Johnson, Kim L; Salmeán, Armando A; Willats, William G T; Doblin, Monika S; Bacic, Antony; Kloareg, Bernard

    2016-03-01

    Arabinogalactan proteins (AGPs) are highly glycosylated, hydroxyproline-rich proteins found at the cell surface of plants, where they play key roles in developmental processes. Brown algae are marine, multicellular, photosynthetic eukaryotes. They belong to the phylum Stramenopiles, which is unrelated to land plants and green algae (Chloroplastida). Brown algae share common evolutionary features with other multicellular organisms, including a carbohydrate-rich cell wall. They differ markedly from plants in their cell wall composition, and AGPs have not been reported in brown algae. Here we investigated the presence of chimeric AGP-like core proteins in this lineage. We report that the genome sequence of the brown algal model Ectocarpus siliculosus encodes AGP protein backbone motifs, in a gene context that differs considerably from what is known in land plants. We showed the occurrence of AGP glycan epitopes in a range of brown algal cell wall extracts. We demonstrated that these chimeric AGP-like core proteins are developmentally regulated in embryos of the order Fucales and showed that AGP loss of function seriously impairs the course of early embryogenesis. Our findings shine a new light on the role of AGPs in cell wall sensing and raise questions about the origin and evolution of AGPs in eukaryotes. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

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

    Directory of Open Access Journals (Sweden)

    Yi Kan Wang

    Full Text Available 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.

  17. CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

    Directory of Open Access Journals (Sweden)

    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

  18. CoryneRegNet 4.0 - A reference database for corynebacterial gene regulatory networks.

    Science.gov (United States)

    Baumbach, Jan

    2007-11-06

    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. Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user) can be analyzed in the context of known transcriptional regulatory networks to predict putative

  19. Intronic microRNAs support their host genes by mediating synergistic and antagonistic regulatory effects

    Directory of Open Access Journals (Sweden)

    Krumsiek Jan

    2010-04-01

    Full Text Available Abstract Background MicroRNA-mediated control of gene expression via translational inhibition has substantial impact on cellular regulatory mechanisms. About 37% of mammalian microRNAs appear to be located within introns of protein coding genes, linking their expression to the promoter-driven regulation of the host gene. In our study we investigate this linkage towards a relationship beyond transcriptional co-regulation. Results Using measures based on both annotation and experimental data, we show that intronic microRNAs tend to support their host genes by regulation of target gene expression with significantly correlated expression patterns. We used expression data of three differentiating cell types and compared gene expression profiles of host and target genes. Many microRNA target genes show expression patterns significantly correlated with the expressions of the microRNA host genes. By calculating functional similarities between host and predicted microRNA target genes based on GO annotations, we confirm that many microRNAs link host and target gene activity in an either synergistic or antagonistic manner. Conclusions These two regulatory effects may result from fine tuning of target gene expression functionally related to the host or knock-down of remaining opponent target gene expression. This finding allows to extend the common practice of mapping large scale gene expression data to protein associated genes with functionality of co-expressed intronic microRNAs.

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

    Directory of Open Access Journals (Sweden)

    Jennifer Ferguson

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

  1. Potential gene regulatory role for cyclin D3 in muscle cells

    Indian Academy of Sciences (India)

    2015-06-27

    Jun 27, 2015 ... In the present study, we investigated the mechanistic role of cyclin D3 in muscle gene regulation. We initially ... Our results have implications for a regulatory role for cyclin D3 in muscle-specific gene activation. [Athar F and Parnaik VK 2015 .... Statistical significance was calculated using the Student's t-test.

  2. 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.

  3. Is There any Alternative to Canonical DNA Barcoding of Multicellular Eukaryotic Species? A Case for the Tubulin Gene Family.

    Science.gov (United States)

    Breviario, Diego

    2017-04-13

    Modern taxonomy is largely relying on DNA barcoding, a nucleotide sequence-based approach that provides automated species identification using short orthologous DNA regions, mainly of organellar origin when applied to multicellular Eukaryotic species. Target DNA loci have been selected that contain a minimal amount of nucleotide sequence variation within species while diverging among species. This strategy is quite effective for the identification of vertebrates and other animal lineages but poses a problem in plants where different combinations of two or three loci are constantly used. Even so, species discrimination in such plant categories as ornamentals and herbals remain problematic as well as the confident identification of subspecies, ecotypes, and closely related or recently evolved species. All these limitations may be successfully solved by the application of a different strategy, based on the use of a multi-locus, ubiquitous, nuclear marker, that is tubulin. In fact, the tubulin-based polymorphism method can release specific genomic profiles to any plant species independently from its taxonomic group. This offers the rare possibility of an effective yet generic genomic fingerprint. In a more general context, the issue is raised about the possibility that approaches alternative to systematic DNA sequencing may still provide useful and simple solutions.

  4. Why eukaryotic cells use introns to enhance gene expression: Splicing reduces transcription-associated mutagenesis by inhibiting topoisomerase I cutting activity

    Directory of Open Access Journals (Sweden)

    Yang Yu-Fei

    2011-05-01

    Full Text Available Abstract Background The costs and benefits of spliceosomal introns in eukaryotes have not been established. One recognized effect of intron splicing is its known enhancement of gene expression. However, the mechanism regulating such splicing-mediated expression enhancement has not been defined. Previous studies have shown that intron splicing is a time-consuming process, indicating that splicing may not reduce the time required for transcription and processing of spliced pre-mRNA molecules; rather, it might facilitate the later rounds of transcription. Because the densities of active RNA polymerase II on most genes are less than one molecule per gene, direct interactions between the splicing apparatus and transcriptional complexes (from the later rounds of transcription are infrequent, and thus unlikely to account for splicing-mediated gene expression enhancement. Presentation of the hypothesis The serine/arginine-rich protein SF2/ASF can inhibit the DNA topoisomerase I activity that removes negative supercoiling of DNA generated by transcription. Consequently, splicing could make genes more receptive to RNA polymerase II during the later rounds of transcription, and thus affect the frequency of gene transcription. Compared with the transcriptional enhancement mediated by strong promoters, intron-containing genes experience a lower frequency of cut-and-paste processes. The cleavage and religation activity of DNA strands by DNA topoisomerase I was recently shown to account for transcription-associated mutagenesis. Therefore, intron-mediated enhancement of gene expression could reduce transcription-associated genome instability. Testing the hypothesis Experimentally test whether transcription-associated mutagenesis is lower in intron-containing genes than in intronless genes. Use bioinformatic analysis to check whether exons flanking lost introns have higher frequencies of short deletions. Implications of the hypothesis The mechanism of intron

  5. GPMiner: an integrated system for mining combinatorial cis-regulatory elements in mammalian gene group.

    Science.gov (United States)

    Lee, Tzong-Yi; Chang, Wen-Chi; Hsu, Justin Bo-Kai; Chang, Tzu-Hao; Shien, Dray-Ming

    2012-01-01

    Sequence features in promoter regions are involved in regulating gene transcription initiation. Although numerous computational methods have been developed for predicting transcriptional start sites (TSSs) or transcription factor (TF) binding sites (TFBSs), they lack annotations for do not consider some important regulatory features such as CpG islands, tandem repeats, the TATA box, CCAAT box, GC box, over-represented oligonucleotides, DNA stability, and GC content. Additionally, the combinatorial interaction of TFs regulates the gene group that is associated with same expression pattern. To investigate gene transcriptional regulation, an integrated system that annotates regulatory features in a promoter sequence and detects co-regulation of TFs in a group of genes is needed. This work identifies TSSs and regulatory features in a promoter sequence, and recognizes co-occurrence of cis-regulatory elements in co-expressed genes using a novel system. Three well-known TSS prediction tools are incorporated with orthologous conserved features, such as CpG islands, nucleotide composition, over-represented hexamer nucleotides, and DNA stability, to construct the novel Gene Promoter Miner (GPMiner) using a support vector machine (SVM). According to five-fold cross-validation results, the predictive sensitivity and specificity are both roughly 80%. The proposed system allows users to input a group of gene names/symbols, enabling the co-occurrence of TFBSs to be determined. Additionally, an input sequence can also be analyzed for homogeneity of experimental mammalian promoter sequences, and conserved regulatory features between homologous promoters can be observed through cross-species analysis. After identifying promoter regions, regulatory features are visualized graphically to facilitate gene promoter observations. The GPMiner, which has a user-friendly input/output interface, has numerous benefits in analyzing human and mouse promoters. The proposed system is freely

  6. Structure–system correlation identifies a gene regulatory Mediator submodule

    Science.gov (United States)

    Larivière, Laurent; Seizl, Martin; van Wageningen, Sake; Röther, Susanne; van de Pasch, Loes; Feldmann, Heidi; Sträßer, Katja; Hahn, Steve; Holstege, Frank C.P.; Cramer, Patrick

    2008-01-01

    A combination of crystallography, biochemistry, and gene expression analysis identifies the coactivator subcomplex Med8C/18/20 as a functionally distinct submodule of the Mediator head module. Med8C forms a conserved α-helix that tethers Med18/20 to the Mediator. Deletion of Med8C in vivo results in dissociation of Med18/20 from Mediator and in loss of transcription activity of extracts. Deletion of med8C, med18, or med20 causes similar changes in the yeast transcriptome, establishing Med8C/18/20 as a predominantly positive, gene-specific submodule required for low transcription levels of nonactivated genes, including conjugation genes. The presented structure-based system perturbation is superior to gene deletion analysis of gene regulation. PMID:18381891

  7. Analysis of Gene Regulatory Networks in the Mammalian Circadian Rhythm

    OpenAIRE

    Jun Yan; Haifang Wang; Yuting Liu; Chunxuan Shao

    2008-01-01

    Circadian rhythm is fundamental in regulating a wide range of cellular, metabolic, physiological, and behavioral activities in mammals. Although a small number of key circadian genes have been identified through extensive molecular and genetic studies in the past, the existence of other key circadian genes and how they drive the genomewide circadian oscillation of gene expression in different tissues still remains unknown. Here we try to address these questions by integrating all available ci...

  8. Organizational structure and the periphery of the gene regulatory network in B-cell lymphoma.

    Science.gov (United States)

    de Matos Simoes, Ricardo; Tripathi, Shailesh; Emmert-Streib, Frank

    2012-05-14

    The physical periphery of a biological cell is mainly described by signaling pathways which are triggered by transmembrane proteins and receptors that are sentinels to control the whole gene regulatory network of a cell. However, our current knowledge about the gene regulatory mechanisms that are governed by extracellular signals is severely limited. The purpose of this paper is three fold. First, we infer a gene regulatory network from a large-scale B-cell lymphoma expression data set using the C3NET algorithm. Second, we provide a functional and structural analysis of the largest connected component of this network, revealing that this network component corresponds to the peripheral region of a cell. Third, we analyze the hierarchical organization of network components of the whole inferred B-cell gene regulatory network by introducing a new approach which exploits the variability within the data as well as the inferential characteristics of C3NET. As a result, we find a functional bisection of the network corresponding to different cellular components. Overall, our study allows to highlight the peripheral gene regulatory network of B-cells and shows that it is centered around hub transmembrane proteins located at the physical periphery of the cell. In addition, we identify a variety of novel pathological transmembrane proteins such as ion channel complexes and signaling receptors in B-cell lymphoma.

  9. CMIP: a software package capable of reconstructing genome-wide regulatory networks using gene expression data.

    Science.gov (United States)

    Zheng, Guangyong; Xu, Yaochen; Zhang, Xiujun; Liu, Zhi-Ping; Wang, Zhuo; Chen, Luonan; Zhu, Xin-Guang

    2016-12-23

    A gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes. Currently, most of network inference methods are computationally intensive, which are usually effective for small-scale tasks (e.g., networks with a few hundred genes), but are difficult to construct GRNs at genome-scale. Here, we present a software package for gene regulatory network reconstruction at a genomic level, in which gene interaction is measured by the conditional mutual information measurement using a parallel computing framework (so the package is named CMIP). The package is a greatly improved implementation of our previous PCA-CMI algorithm. In CMIP, we provide not only an automatic threshold determination method but also an effective parallel computing framework for network inference. Performance tests on benchmark datasets show that the accuracy of CMIP is comparable to most current network inference methods. Moreover, running tests on synthetic datasets demonstrate that CMIP can handle large datasets especially genome-wide datasets within an acceptable time period. In addition, successful application on a real genomic dataset confirms its practical applicability of the package. This new software package provides a powerful tool for genomic network reconstruction to biological community. The software can be accessed at http://www.picb.ac.cn/CMIP/ .

  10. CTCF-mediated chromatin loops enclose inducible gene regulatory domains

    NARCIS (Netherlands)

    Oti, M.O.; Falck, J.; Huynen, M.A.; Zhou, Huiqing

    2016-01-01

    BACKGROUND: The CCTC-binding factor (CTCF) protein is involved in genome organization, including mediating three-dimensional chromatin interactions. Human patient lymphocytes with mutations in a single copy of the CTCF gene have reduced expression of enhancer-associated genes involved in response to

  11. Using shRNA experiments to validate gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Catharina Olsen

    2015-06-01

    In this Data in Brief we detail the contents and quality controls for the gene expression data (available from NCBI Gene Expression Omnibus repository with accession number GSE53091 associated with our study published in Genomics (Olsen et al. 2014. We also provide R code to access the data and reproduce the analysis presented in this article.

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

    Directory of Open Access Journals (Sweden)

    Xiaodong Cai

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

  13. Diverse Cis-Regulatory Mechanisms Contribute to Expression Evolution of Tandem Gene Duplicates.

    Science.gov (United States)

    Baudouin-Gonzalez, Luís; Santos, Marília A; Tempesta, Camille; Sucena, Élio; Roch, Fernando; Tanaka, Kohtaro

    2017-12-01

    Pairs of duplicated genes generally display a combination of conserved expression patterns inherited from their unduplicated ancestor and newly acquired domains. However, how the cis-regulatory architecture of duplicated loci evolves to produce these expression patterns is poorly understood. We have directly examined the gene-regulatory evolution of two tandem duplicates, the Drosophila Ly6 genes CG9336 and CG9338, which arose at the base of the drosophilids between 40 and 60 Ma. Comparing the expression patterns of the two paralogs in four Drosophila species with that of the unduplicated ortholog in the tephritid Ceratitis capitata, we show that they diverged from each other as well as from the unduplicated ortholog. Moreover, the expression divergence appears to have occurred close to the duplication event and also more recently in a lineage-specific manner. The comparison of the tissue-specific cis-regulatory modules (CRMs) controlling the paralog expression in the four Drosophila species indicates that diverse cis-regulatory mechanisms, including the novel tissue-specific enhancers, differential inactivation, and enhancer sharing, contributed to the expression evolution. Our analysis also reveals a surprisingly variable cis-regulatory architecture, in which the CRMs driving conserved expression domains change in number, location, and specificity. Altogether, this study provides a detailed historical account that uncovers a highly dynamic picture of how the paralog expression patterns and their underlying cis-regulatory landscape evolve. We argue that our findings will encourage studying cis-regulatory evolution at the whole-locus level to understand how interactions between enhancers and other regulatory levels shape the evolution of gene expression. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  14. Cis-regulatory elements of the mouse Krt1.12 gene.

    Science.gov (United States)

    Wang, I-Jong; Carlson, Eric C; Liu, Chia-Yang; Kao, Candace W C; Hu, Fung-Rong; Kao, Winston W Y

    2002-04-07

    Keratin 12 is a cornea epithelial cell-specific intermediate filament component. To better understand the regulatory mechanism of its expression, the cis-regulatory elements located between the transcription start site and 600 bp upstream of the Krt1.12 gene were determined. The promoter activity of reporter gene constructs containing 0.6, 0.4, and 0.2 kb of DNA 5' upstream of Krt1.12 coupled to the lac Z gene were determined in rabbit corneas using Gene Gun technology. DNA foot printing and EMSA (electrophoresis mobility shift assay) were employed to identify putative cis-regulatory elements of the Krt1.12 gene using bovine corneal epithelial cell nuclear extracts. Enzyme activity assays and histochemical analysis of beta-galactosidase from the 0.6, 0.4, and 0.2 kb K12 promoter constructs indicated that the DNA elements between -0.2 and -0.6 kb 5' of the Krt1.12 gene contain cis-regulatory elements for its corneal epithelial cell-specific expression. Foot printing and EMSA showed that the sequences between -181 to -111 and -256 to -193 upstream of the Krt1.12 gene reacted to nuclear proteins isolated from bovine corneal epithelial cells. A Genbank search revealed that these two regions were potential binding sites for many transcription factors such as AP1, c/EBP, and KLF6. Immunofluorescent staining indicated the presence of c-jun and c/EBP transcription factors in the nuclei of corneal epithelial cells. The data is consistent with the notion that the -182 to -111 and -256 to -193 fragments 5' of the Krt1.12 gene may serve as corneal epithelial cell-specific cis-regulatory elements, and the coordinated interactions of various transcription factors are required for cornea-specific expression of Krt1.12 gene.

  15. Increasing galactose consumption by Saccharomyces cerevisiae through metabolic engineering of the GAL gene regulatory network

    DEFF Research Database (Denmark)

    Østergaard, Simon; Olsson, Lisbeth; Johnston, M.

    2000-01-01

    Increasing the flux through central carbon metabolism is difficult because of rigidity in regulatory structures, at both the genetic and the enzymatic levels. Here we describe metabolic engineering of a regulatory network to obtain a balanced increase in the activity of all the enzymes...... in the pathway, and ultimately, increasing metabolic flux through the pathway of interest, By manipulating the GAL gene regulatory network of Saccharomyces cerevisiae, which is a tightly regulated system, we produced prototroph mutant strains, which increased the flux through the galactose utilization pathway...

  16. Cis- and Trans-regulatory Effects on Gene Expression in a Natural Population of Drosophila melanogaster.

    Science.gov (United States)

    Osada, Naoki; Miyagi, Ryutaro; Takahashi, Aya

    2017-08-01

    Cis- and trans-regulatory mutations are important contributors to transcriptome evolution. Quantifying their relative contributions to intraspecific variation in gene expression is essential for understanding the population genetic processes that underlie evolutionary changes in gene expression. Here, we have examined this issue by quantifying genome-wide, allele-specific expression (ASE) variation using a crossing scheme that produces F1 hybrids between 18 different Drosophila melanogaster strains sampled from the Drosophila Genetic Reference Panel and a reference strain from another population. Head and body samples from F1 adult females were subjected to RNA sequencing and the subsequent ASE quantification. Cis- and trans-regulatory effects on expression variation were estimated from these data. A higher proportion of genes showed significant cis-regulatory variation (∼28%) than those that showed significant trans-regulatory variation (∼9%). The sizes of cis-regulatory effects on expression variation were 1.98 and 1.88 times larger than trans-regulatory effects in heads and bodies, respectively. A generalized linear model analysis revealed that both cis- and trans-regulated expression variation was strongly associated with nonsynonymous nucleotide diversity and tissue specificity. Interestingly, trans-regulated variation showed a negative correlation with local recombination rate. Also, our analysis on proximal transposable element (TE) insertions suggested that they affect transcription levels of ovary-expressed genes more pronouncedly than genes not expressed in the ovary, possibly due to defense mechanisms against TE mobility in the germline. Collectively, our detailed quantification of ASE variations from a natural population has revealed a number of new relationships between genomic factors and the effects of cis- and trans-regulatory factors on expression variation. Copyright © 2017 by the Genetics Society of America.

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

    Science.gov (United States)

    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.

  18. Transcription regulatory networks analysis using CAGE

    KAUST Repository

    Tegnér, Jesper N.

    2009-10-01

    Mapping out cellular networks in general and transcriptional networks in particular has proved to be a bottle-neck hampering our understanding of biological processes. Integrative approaches fusing computational and experimental technologies for decoding transcriptional networks at a high level of resolution is therefore of uttermost importance. Yet, this is challenging since the control of gene expression in eukaryotes is a complex multi-level process influenced by several epigenetic factors and the fine interplay between regulatory proteins and the promoter structure governing the combinatorial regulation of gene expression. In this chapter we review how the CAGE data can be integrated with other measurements such as expression, physical interactions and computational prediction of regulatory motifs, which together can provide a genome-wide picture of eukaryotic transcriptional regulatory networks at a new level of resolution. © 2010 by Pan Stanford Publishing Pte. Ltd. All rights reserved.

  19. Large-scale gene expression study in the ophiuroid Amphiura filiformis provides insights into evolution of gene regulatory networks

    Directory of Open Access Journals (Sweden)

    David Viktor Dylus

    2016-01-01

    Full Text Available Abstract Background The evolutionary mechanisms involved in shaping complex gene regulatory networks (GRN that encode for morphologically similar structures in distantly related animals remain elusive. In this context, echinoderm larval skeletons found in brittle stars and sea urchins provide an ideal system. Here, we characterize for the first time the development of the larval skeleton in the ophiuroid Amphiura filiformis and compare it systematically with its counterpart in sea urchin. Results We show that ophiuroids and euechinoids, that split at least 480 Million years ago (Mya, have remarkable similarities in tempo and mode of skeletal development. Despite morphological and ontological similarities, our high-resolution study of the dynamics of genetic regulatory states in A. filiformis highlights numerous differences in the architecture of their underlying GRNs. Importantly, the A.filiformis pplx, the closest gene to the sea urchin double negative gate (DNG repressor pmar1, fails to drive the skeletogenic program in sea urchin, showing important evolutionary differences in protein function. hesC, the second repressor of the DNG, is co-expressed with most of the genes that are repressed in sea urchin, indicating the absence of direct repression of tbr, ets1/2, and delta in A. filiformis. Furthermore, the absence of expression in later stages of brittle star skeleton development of key regulatory genes, such as foxb and dri, shows significantly different regulatory states. Conclusion Our data fill up an important gap in the picture of larval mesoderm in echinoderms and allows us to explore the evolutionary implications relative to the recently established phylogeny of echinoderm classes. In light of recent studies on other echinoderms, our data highlight a high evolutionary plasticity of the same nodes throughout evolution of echinoderm skeletogenesis. Finally, gene duplication, protein function diversification, and cis-regulatory element

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Bringas Ricardo

    2008-01-01

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

  2. F-MAP: A Bayesian approach to infer the gene regulatory network using external hints.

    Science.gov (United States)

    Shahdoust, Maryam; Pezeshk, Hamid; Mahjub, Hossein; Sadeghi, Mehdi

    2017-01-01

    The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches.

  3. Gene regulatory network identification from the yeast cell cycle based on a neuro-fuzzy system.

    Science.gov (United States)

    Wang, B H; Lim, J W; Lim, J S

    2016-08-30

    Many studies exist for reconstructing gene regulatory networks (GRNs). In this paper, we propose a method based on an advanced neuro-fuzzy system, for gene regulatory network reconstruction from microarray time-series data. This approach uses a neural network with a weighted fuzzy function to model the relationships between genes. Fuzzy rules, which determine the regulators of genes, are very simplified through this method. Additionally, a regulator selection procedure is proposed, which extracts the exact dynamic relationship between genes, using the information obtained from the weighted fuzzy function. Time-series related features are extracted from the original data to employ the characteristics of temporal data that are useful for accurate GRN reconstruction. The microarray dataset of the yeast cell cycle was used for our study. We measured the mean squared prediction error for the efficiency of the proposed approach and evaluated the accuracy in terms of precision, sensitivity, and F-score. The proposed method outperformed the other existing approaches.

  4. A regulatory gene (ECO-orf4) required for ECO-0501 biosynthesis in Amycolatopsis orientalis.

    Science.gov (United States)

    Shen, Yang; Huang, He; Zhu, Li; Luo, Minyu; Chen, Daijie

    2014-02-01

    ECO-0501 is a novel linear polyene antibiotic, which was discovered from Amycolatopsis orientalis. Recent study of ECO-0501 biosynthesis pathway revealed the presence of regulatory gene: ECO-orf4. The A. orientalis ECO-orf4 gene from the ECO-0501 biosynthesis cluster was analyzed, and its deduced protein (ECO-orf4) was found to have amino acid sequence homology with large ATP-binding regulators of the LuxR (LAL) family regulators. Database comparison revealed two hypothetical domains, a LuxR-type helix-turn-helix (HTH) DNA binding motif near the C-terminal and an N-terminal nucleotide triphosphate (NTP) binding motif included. Deletion of the corresponding gene (ECO-orf4) resulted in complete loss of ECO-0501 production. Complementation by one copy of intact ECO-orf4 restored the polyene biosynthesis demonstrating that ECO-orf4 is required for ECO-0501 biosynthesis. The results of overexpression ECO-orf4 on ECO-0501 production indicated that it is a positive regulatory gene. Gene expression analysis by reverse transcription PCR of the ECO-0501 gene cluster showed that the transcription of ECO-orf4 correlates with that of genes involved in polyketide biosynthesis. These results demonstrated that ECO-orf4 is a pathway-specific positive regulatory gene that is essential for ECO-0501 biosynthesis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Hase, Takeshi; Ghosh, Samik; Yamanaka, Ryota; Kitano, Hiroaki

    2013-01-01

    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.

  7. Molecular characterization of a maize regulatory gene. Progress report, July 1989--March 1990

    Energy Technology Data Exchange (ETDEWEB)

    Wessler, S.

    1990-12-31

    This progress report contains information concerning the characterization of the Maize regulatory gene. The findings of this research program have immediate significance. Firstly, it provides support for the notion that R proteins, produced by the regulatory gene, are functionally equivalent. Secondly, the success of these experiments provides a simple transient assay for either natural or constructed R protein mutations. The relative ease of this assay coupled with overnight results are important prerequisites to the proposed experiments involving a structure-function analysis of the R protein.

  8. 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...

  9. Sensor-coupled fractal gene regulatory networks for locomotion control of a modular snake robot

    DEFF Research Database (Denmark)

    Zahadat, Payam; Christensen, David Johan; Katebi, Serajeddin

    2013-01-01

    In this paper we study fractal gene regulatory network (FGRN) controllers based on sensory information. The FGRN controllers are evolved to control a snake robot consisting of seven simulated ATRON modules. Each module contains three tilt sensors which represent the direction of gravity in the co......In this paper we study fractal gene regulatory network (FGRN) controllers based on sensory information. The FGRN controllers are evolved to control a snake robot consisting of seven simulated ATRON modules. Each module contains three tilt sensors which represent the direction of gravity...

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

    Directory of Open Access Journals (Sweden)

    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.

  11. The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity.

    Directory of Open Access Journals (Sweden)

    Slavé Petrovski

    2015-09-01

    Full Text Available Noncoding sequence contains pathogenic mutations. Yet, compared with mutations in protein-coding sequence, pathogenic regulatory mutations are notoriously difficult to recognize. Most fundamentally, we are not yet adept at recognizing the sequence stretches in the human genome that are most important in regulating the expression of genes. For this reason, it is difficult to apply to the regulatory regions the same kinds of analytical paradigms that are being successfully applied to identify mutations among protein-coding regions that influence risk. To determine whether dosage sensitive genes have distinct patterns among their noncoding sequence, we present two primary approaches that focus solely on a gene's proximal noncoding regulatory sequence. The first approach is a regulatory sequence analogue of the recently introduced residual variation intolerance score (RVIS, termed noncoding RVIS, or ncRVIS. The ncRVIS compares observed and predicted levels of standing variation in the regulatory sequence of human genes. The second approach, termed ncGERP, reflects the phylogenetic conservation of a gene's regulatory sequence using GERP++. We assess how well these two approaches correlate with four gene lists that use different ways to identify genes known or likely to cause disease through changes in expression: 1 genes that are known to cause disease through haploinsufficiency, 2 genes curated as dosage sensitive in ClinGen's Genome Dosage Map, 3 genes judged likely to be under purifying selection for mutations that change expression levels because they are statistically depleted of loss-of-function variants in the general population, and 4 genes judged unlikely to cause disease based on the presence of copy number variants in the general population. We find that both noncoding scores are highly predictive of dosage sensitivity using any of these criteria. In a similar way to ncGERP, we assess two ensemble-based predictors of regional noncoding

  12. CpLEA5, the Late Embryogenesis Abundant Protein Gene from Chimonanthus praecox, Possesses Low Temperature and Osmotic Resistances in Prokaryote and Eukaryotes

    Directory of Open Access Journals (Sweden)

    Yiling Liu

    2015-11-01

    Full Text Available Plants synthesize and accumulate a series of stress-resistance proteins to protect normal physiological activities under adverse conditions. Chimonanthus praecox which blooms in freezing weather accumulates late embryogenesis abundant proteins (LEAs in flowers, but C. praecox LEAs are little reported. Here, we report a group of five LEA genes of C. praecox (CpLEA5, KT727031. Prokaryotic-expressed CpLEA5 was employed in Escherichia coli to investigate bioactivities and membrane permeability at low-temperature. In comparison with the vacant strains, CpLEA5-containing strains survived in a 20% higher rate; and the degree of cell membrane damage in CpLEA5-containing strains was 55% of that of the vacant strains according to a conductivity test, revealing the low-temperature resistance of CpLEA5 in bacteria. CpLEA5 was also expressed in Pichia pastoris. Interestingly, besides low-temperature resistance, CpLEA5 conferred high resistance to salt and alkali in CpLEA5 overexpressing yeast. The CpLEA5 gene was transferred into Arabidopsis thaliana to also demonstrate CpLEA5 actions in plants. As expected, the transgenic lines were more resistant against low-temperature and drought while compared with the wild type. Taken together, CpLEA5-conferred resistances to several conditions in prokaryote and eukaryotes could have great value as a genetic technology to enhance osmotic stress and low-temperature tolerance.

  13. Rapid evolution of regulatory element libraries for tunable transcriptional and translational control of gene expression

    Directory of Open Access Journals (Sweden)

    Erqing Jin

    2017-12-01

    Full Text Available Engineering cell factories for producing biofuels and pharmaceuticals has spurred great interests to develop rapid and efficient synthetic biology tools customized for modular pathway engineering. Along the way, combinatorial gene expression control through modification of regulatory element offered tremendous opportunity for fine-tuning gene expression and generating digital-like genetic circuits. In this report, we present an efficient evolutionary approach to build a range of regulatory control elements. The reported method allows for rapid construction of promoter, 5′UTR, terminator and trans-activating RNA libraries. Synthetic overlapping oligos with high portion of degenerate nucleotides flanking the regulatory element could be efficiently assembled to a vector expressing fluorescence reporter. This approach combines high mutation rate of the synthetic DNA with the high assembly efficiency of Gibson Mix. Our constructed library demonstrates broad range of transcriptional or translational gene expression dynamics. Specifically, both the promoter library and 5′UTR library exhibits gene expression dynamics spanning across three order of magnitude. The terminator library and trans-activating RNA library displays relatively narrowed gene expression pattern. The reported study provides a versatile toolbox for rapidly constructing a large family of prokaryotic regulatory elements. These libraries also facilitate the implementation of combinatorial pathway engineering principles and the engineering of more efficient microbial cell factory for various biomanufacturing applications.

  14. Evolutionary Analysis of the B56 Gene Family of PP2A Regulatory Subunits

    Directory of Open Access Journals (Sweden)

    Lauren M. Sommer

    2015-05-01

    Full Text Available Protein phosphatase 2A (PP2A is an abundant serine/threonine phosphatase that functions as a tumor suppressor in numerous cell-cell signaling pathways, including Wnt, myc, and ras. The B56 subunit of PP2A regulates its activity, and is encoded by five genes in humans. B56 proteins share a central core domain, but have divergent amino- and carboxy-termini, which are thought to provide isoform specificity. We performed phylogenetic analyses to better understand the evolution of the B56 gene family. We found that B56 was present as a single gene in eukaryotes prior to the divergence of animals, fungi, protists, and plants, and that B56 gene duplication prior to the divergence of protostomes and deuterostomes led to the origin of two B56 subfamilies, B56αβε and B56γδ. Further duplications led to three B56αβε genes and two B56γδ in vertebrates. Several nonvertebrate B56 gene names are based on distinct vertebrate isoform names, and would best be renamed. B56 subfamily genes lack significant divergence within primitive chordates, but each became distinct in complex vertebrates. Two vertebrate lineages have undergone B56 gene loss, Xenopus and Aves. In Xenopus, B56δ function may be compensated for by an alternatively spliced transcript, B56δ/γ, encoding a B56δ-like amino-terminal region and a B56γ core.

  15. Genetic polymorphism in FOXP3 gene: imbalance in regulatory T ...

    Indian Academy of Sciences (India)

    2013-04-02

    Apr 2, 2013 ... Genetic polymorphism in FOXP3 gene. The −924 (rs2232365) SNP is significantly associated with unexplained recurrent spontaneous abortion in the. Chinese Han population, highlighting the important role of. FOXP3 in successful pregnancy (Wu et al. 2012). But no associations were found between this ...

  16. Genetic polymorphism in FOXP3 gene: imbalance in regulatory T ...

    Indian Academy of Sciences (India)

    Dysfunction of FOXP3 gene product could result in lack of Treg cells and subsequently chronically activated CD4+ T cells which express increased levels of several activation markers and cytokines, resulting in some autoimmune diseases. In contrast, high Treg levels have been reported in peripheral blood, lymph nodes, ...

  17. Molecular evolution constraints in the floral organ specification gene regulatory network module across 18 angiosperm genomes.

    Science.gov (United States)

    Davila-Velderrain, Jose; Servin-Marquez, Andres; Alvarez-Buylla, Elena R

    2014-03-01

    The gene regulatory network of floral organ cell fate specification of Arabidopsis thaliana is a robust developmental regulatory module. Although such finding was proposed to explain the overall conservation of floral organ types and organization among angiosperms, it has not been confirmed that the network components are conserved at the molecular level among flowering plants. Using the genomic data that have accumulated, we address the conservation of the genes involved in this network and the forces that have shaped its evolution during the divergence of angiosperms. We recovered the network gene homologs for 18 species of flowering plants spanning nine families. We found that all the genes are highly conserved with no evidence of positive selection. We studied the sequence conservation features of the genes in the context of their known biological function and the strength of the purifying selection acting upon them in relation to their placement within the network. Our results suggest an association between protein length and sequence conservation, evolutionary rates, and functional category. On the other hand, we found no significant correlation between the strength of purifying selection and gene placement. Our results confirm that the studied robust developmental regulatory module has been subjected to strong functional constraints. However, unlike previous studies, our results do not support the notion that network topology plays a major role in constraining evolutionary rates. We speculate that the dynamical functional role of genes within the network and not just its connectivity could play an important role in constraining evolution.

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

    Science.gov (United States)

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

    2014-12-01

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

  19. Applying gene regulatory network logic to the evolution of social behavior

    OpenAIRE

    Baran, Nicole M.; Patrick T McGrath; Streelman, J Todd

    2017-01-01

    Animal behavior is ultimately the product of gene regulatory networks (GRNs) for brain development and neural networks for brain function. The GRN approach has advanced the fields of genomics and development, and we identify organizational similarities between networks of genes that build the brain and networks of neurons that encode brain function. In this perspective, we engage the analogy between developmental networks and neural networks, exploring the advantages of using GRN logic to stu...

  20. Inferring Gene Regulatory Networks in the Arabidopsis Root Using a Dynamic Bayesian Network Approach.

    Science.gov (United States)

    de Luis Balaguer, Maria Angels; Sozzani, Rosangela

    2017-01-01

    Gene regulatory network (GRN) models have been shown to predict and represent interactions among sets of genes. Here, we first show the basic steps to implement a simple but computationally efficient algorithm to infer GRNs based on dynamic Bayesian networks (DBNs), and we then explain how to approximate DBN-based GRN models with continuous models. In addition, we show a MATLAB implementation of the key steps of this method, which we use to infer an Arabidopsis root GRN.

  1. 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

    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...... 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......IP-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...

  2. The interferon regulatory factor 5 gene confers susceptibility to rheumatoid arthritis and influences its erosive phenotype

    NARCIS (Netherlands)

    Dawidowicz, K.; Allanore, Y.; Guedj, M.; Pierlot, C.; Bombardieri, S.; Balsa, A.; Westhovens, R.; Barrera, P.; Alves, H.; Teixeira, V.H.; Petit-Teixeira, E.; Putte, L.B.A. van de; Riel, P.L.C.M. van; Prum, B.; Bardin, T.; Meyer, O.; Cornelis, F.; Dieude, P.

    2011-01-01

    BACKGROUND: Increased expression of type I IFN genes, also referred to as an IFN signature, has been detected in various autoimmune diseases including rheumatoid arthritis (RA). Interferon regulatory factors, such as IRF5, coordinate type I IFN expression. Multiple IRF5 variants were suggested as

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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...

  5. Identifying genes and regulatory pathways associated with the scleractinian coral calcification process.

    Science.gov (United States)

    Gutner-Hoch, Eldad; Waldman Ben-Asher, Hiba; Yam, Ruth; Shemesh, Aldo; Levy, Oren

    2017-01-01

    Reef building corals precipitate calcium carbonate as an exo-skeleton and provide substratum for prosperous marine life. Biomineralization of the coral's skeleton is a developmental process that occurs concurrently with other proliferation processes that control the animal extension and growth. The development of the animal body is regulated by large gene regulatory networks, which control the expression of gene sets that progressively generate developmental patterns in the animal body. In this study we have explored the gene expression profile and signaling pathways followed by the calcification process of a basal metazoan, the Red Sea scleractinian (stony) coral, Stylophora pistillata . When treated by seawater with high calcium concentrations (addition of 100 gm/L, added as CaCl 2 .2H 2 O), the coral increases its calcification rates and associated genes were up-regulated as a result, which were then identified. Gene expression was compared between corals treated with elevated and normal calcium concentrations. Calcification rate measurements and gene expression analysis by microarray RNA transcriptional profiling at two time-points (midday and night-time) revealed several genes common within mammalian gene regulatory networks. This study indicates that core genes of the Wnt and TGF-β/BMP signaling pathways may also play roles in development, growth, and biomineralization in early-diverging organisms such as corals.

  6. Identifying genes and regulatory pathways associated with the scleractinian coral calcification process

    Directory of Open Access Journals (Sweden)

    Eldad Gutner-Hoch

    2017-07-01

    Full Text Available Reef building corals precipitate calcium carbonate as an exo-skeleton and provide substratum for prosperous marine life. Biomineralization of the coral’s skeleton is a developmental process that occurs concurrently with other proliferation processes that control the animal extension and growth. The development of the animal body is regulated by large gene regulatory networks, which control the expression of gene sets that progressively generate developmental patterns in the animal body. In this study we have explored the gene expression profile and signaling pathways followed by the calcification process of a basal metazoan, the Red Sea scleractinian (stony coral, Stylophora pistillata. When treated by seawater with high calcium concentrations (addition of 100 gm/L, added as CaCl2.2H2O, the coral increases its calcification rates and associated genes were up-regulated as a result, which were then identified. Gene expression was compared between corals treated with elevated and normal calcium concentrations. Calcification rate measurements and gene expression analysis by microarray RNA transcriptional profiling at two time-points (midday and night-time revealed several genes common within mammalian gene regulatory networks. This study indicates that core genes of the Wnt and TGF-β/BMP signaling pathways may also play roles in development, growth, and biomineralization in early-diverging organisms such as corals.

  7. In vivo SPECT reporter gene imaging of regulatory T cells.

    Directory of Open Access Journals (Sweden)

    Ehsan Sharif-Paghaleh

    Full Text Available Regulatory T cells (Tregs were identified several years ago and are key in controlling autoimmune diseases and limiting immune responses to foreign antigens, including alloantigens. In vivo imaging techniques including intravital microscopy as well as whole body imaging using bioluminescence probes have contributed to the understanding of in vivo Treg function, their mechanisms of action and target cells. Imaging of the human sodium/iodide symporter via Single Photon Emission Computed Tomography (SPECT has been used to image various cell types in vivo. It has several advantages over the aforementioned imaging techniques including high sensitivity, it allows non-invasive whole body studies of viable cell migration and localisation of cells over time and lastly it may offer the possibility to be translated to the clinic. This study addresses whether SPECT/CT imaging can be used to visualise the migratory pattern of Tregs in vivo. Treg lines derived from CD4(+CD25(+FoxP3(+ cells were retrovirally transduced with a construct encoding for the human Sodium Iodide Symporter (NIS and the fluorescent protein mCherry and stimulated with autologous DCs. NIS expressing self-specific Tregs were specifically radiolabelled in vitro with Technetium-99m pertechnetate ((99mTcO(4(- and exposure of these cells to radioactivity did not affect cell viability, phenotype or function. In addition adoptively transferred Treg-NIS cells were imaged in vivo in C57BL/6 (BL/6 mice by SPECT/CT using (99mTcO(4(-. After 24 hours NIS expressing Tregs were observed in the spleen and their localisation was further confirmed by organ biodistribution studies and flow cytometry analysis. The data presented here suggests that SPECT/CT imaging can be utilised in preclinical imaging studies of adoptively transferred Tregs without affecting Treg function and viability thereby allowing longitudinal studies within disease models.

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

    Directory of Open Access Journals (Sweden)

    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

  9. Cis- and trans-regulatory mechanisms of gene expression in the ASJ sensory neuron of Caenorhabditis elegans

    NARCIS (Netherlands)

    M. González-Barrios (María); J.C. Fierro-González (Juan Carlos); E. Krpelanova (Eva); J.A. Mora-Lorca (José Antonio); J. Rafael Pedrajas (José); X. Peñate (Xenia); S. Chavez (Sebastián); P. Swoboda (Peter); G. Jansen (Gert); A. Miranda-Vizuet (Antonio)

    2015-01-01

    textabstractThe identity of a given cell type is determined by the expression of a set of genes sharing common cis-regulatory motifs and being regulated by shared transcription factors. Here, we identify cis and trans regulatory elements that drive gene expression in the bilateral sensory neuron

  10. MicroRNAs: The Mega Regulators in Eukaryotic Genomes

    Directory of Open Access Journals (Sweden)

    Iftekhar Ahmed Baloch

    2013-09-01

    Full Text Available MicroRNAs (miRNAs are endogenous, small, noncoding RNAs of 18-25 nucleotide (nt in length that negatively regulate their complementary messenger RNAs (mRNAs at the transcriptional and posttranscriptional level in many eukaryotic organisms. By affecting the gene regulation, miRNAs are likely to be concerned with most biological processes. Majority of the miRNA genes are found in intergenic regions or in anti-sense orientation to genes and have their own miRNA gene promoter and regulatory units. In contrast to their name and size, the miRNAs perform mega functions in eukaryotic organisms. They perform important functions in plants and animals during growth, organogenesis, transgene suppression, signaling pathway, environmental stresses, disease development and defense against the invading viruses. miRNAs are evolutionarily conserved from species to species within the same kingdom. However, there is a controversy among scientists about their conservation from animals to plants. Their conserved nature becomes an important logical tool for homologous discovery of miRNAs in other species. This review is aimed at describing some basic concepts regarding biogenesis and functions of miRNAs.

  11. Positive selection for unpreferred codon usage in eukaryotic genomes

    Directory of Open Access Journals (Sweden)

    Galagan James E

    2007-07-01

    Full Text Available Abstract Background Natural selection has traditionally been understood as a force responsible for pushing genes to states of higher translational efficiency, whereas lower translational efficiency has been explained by neutral mutation and genetic drift. We looked for evidence of directional selection resulting in increased unpreferred codon usage (and presumably reduced translational efficiency in three divergent clusters of eukaryotic genomes using a simple optimal-codon-based metric (Kp/Ku. Results Here we show that for some genes natural selection is indeed responsible for causing accelerated unpreferred codon substitution, and document the scope of this selection. In Cryptococcus and to a lesser extent Drosophila, we find many genes showing a statistically significant signal of selection for unpreferred codon usage in one or more lineages. We did not find evidence for this type of selection in Saccharomyces. The signal of positive selection observed from unpreferred synonymous codon substitutions is coincident in Cryptococcus and Drosophila with the distribution of upstream open reading frames (uORFs, another genic feature known to reduce translational efficiency. Functional enrichment analysis of genes exhibiting low Kp/Ku ratios reveals that genes in regulatory roles are particularly subject to this type of selection. Conclusion Through genome-wide scans, we find recent selection for unpreferred codon usage at approximately 1% of genetic loci in a Cryptococcus and several genes in Drosophila. Unpreferred codons can impede translation efficiency, and we find that genes with translation-impeding uORFs are enriched for this selection signal. We find that regulatory genes are particularly likely to be subject to selection for unpreferred codon usage. Given that expression noise can propagate through regulatory cascades, and that low translational efficiency can reduce expression noise, this finding supports the hypothesis that translational

  12. 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

    2018-02-17

    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

  13. Reliable transfer of transcriptional gene regulatory networks between taxonomically related organisms

    Directory of Open Access Journals (Sweden)

    Tauch Andreas

    2009-01-01

    Full Text Available Abstract Background Transcriptional regulation of gene activity is essential for any living organism. Transcription factors therefore recognize specific binding sites within the DNA to regulate the expression of particular target genes. The genome-scale reconstruction of the emerging regulatory networks is important for biotechnology and human medicine but cost-intensive, time-consuming, and impossible to perform for any species separately. By using bioinformatics methods one can partially transfer networks from well-studied model organisms to closely related species. However, the prediction quality is limited by the low level of evolutionary conservation of the transcription factor binding sites, even within organisms of the same genus. Results Here we present an integrated bioinformatics workflow that assures the reliability of transferred gene regulatory networks. Our approach combines three methods that can be applied on a large-scale: re-assessment of annotated binding sites, subsequent binding site prediction, and homology detection. A gene regulatory interaction is considered to be conserved if (1 the transcription factor, (2 the adjusted binding site, and (3 the target gene are conserved. The power of the approach is demonstrated by transferring gene regulations from the model organism Corynebacterium glutamicum to the human pathogens C. diphtheriae, C. jeikeium, and the biotechnologically relevant C. efficiens. For these three organisms we identified reliable transcriptional regulations for ~40% of the common transcription factors, compared to ~5% for which knowledge was available before. Conclusion Our results suggest that trustworthy genome-scale transfer of gene regulatory networks between organisms is feasible in general but still limited by the level of evolutionary conservation.

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

    Science.gov (United States)

    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

  15. Comparison of five major trichome regulatory genes in Brassica villosa with orthologues within the Brassicaceae.

    Directory of Open Access Journals (Sweden)

    Naghabushana K Nayidu

    Full Text Available 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.

  16. Construction of eukaryotic expression vectors encoding CFP-10 and ESAT-6 genes and their potential in lymphocyte proliferation.

    Science.gov (United States)

    Torabi, Azam; Tahmoorespour, Mojtaba; Vahedi, Fatemeh; Mosavari, Nader; Nassiri, Mohammadreza

    2013-10-01

    Mycobacterium (M.) bovis is the agent of bovine tuberculosis (TB) in a range of animal species, including humans. Recent advances in immunology and the molecular biology of Mycobacterium have allowed identification of a large number of antigens with the potential for the development of a new TB vaccine. The ESAT-6 and CFP-10 proteins of M. bovis are important structural and functional proteins known to be important immunogens. In the current study, the DNAs encoding these genes were utilized in the construction of pcDNA 3.1+/ESAT-6 and pcDNA3.1+/CFP-10 plasmids. After intramuscular injection of BALB/c mice with these plasmids, ESAT-6 and CFP-10 mRNA expression was assessed by RT-PCR. Mice were inoculated and boosted with the plasmids to evaluate their effects on lymphocyte proliferation. Our results indicate the plasmids are expressed at the RNA level and can induce lymphocyte proliferation. Further study is needed to characterize the effect of these antigens on the immune system and determine whether they are effective vaccine candidates against M. bovis.

  17. 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

  18. A gene regulatory network for root epidermis cell differentiation in Arabidopsis.

    Directory of Open Access Journals (Sweden)

    Angela Bruex

    2012-01-01

    Full Text Available The root epidermis of Arabidopsis provides an exceptional model for studying the molecular basis of cell fate and differentiation. To obtain a systems-level view of root epidermal cell differentiation, we used a genome-wide transcriptome approach to define and organize a large set of genes into a transcriptional regulatory network. Using cell fate mutants that produce only one of the two epidermal cell types, together with fluorescence-activated cell-sorting to preferentially analyze the root epidermis transcriptome, we identified 1,582 genes differentially expressed in the root-hair or non-hair cell types, including a set of 208 "core" root epidermal genes. The organization of the core genes into a network was accomplished by using 17 distinct root epidermis mutants and 2 hormone treatments to perturb the system and assess the effects on each gene's transcript accumulation. In addition, temporal gene expression information from a developmental time series dataset and predicted gene associations derived from a Bayesian modeling approach were used to aid the positioning of genes within the network. Further, a detailed functional analysis of likely bHLH regulatory genes within the network, including MYC1, bHLH54, bHLH66, and bHLH82, showed that three distinct subfamilies of bHLH proteins participate in root epidermis development in a stage-specific manner. The integration of genetic, genomic, and computational analyses provides a new view of the composition, architecture, and logic of the root epidermal transcriptional network, and it demonstrates the utility of a comprehensive systems approach for dissecting a complex regulatory network.

  19. A Gene Regulatory Network for Root Epidermis Cell Differentiation in Arabidopsis

    Science.gov (United States)

    Bruex, Angela; Kainkaryam, Raghunandan M.; Wieckowski, Yana; Kang, Yeon Hee; Bernhardt, Christine; Xia, Yang; Zheng, Xiaohua; Wang, Jean Y.; Lee, Myeong Min; Benfey, Philip; Woolf, Peter J.; Schiefelbein, John

    2012-01-01

    The root epidermis of Arabidopsis provides an exceptional model for studying the molecular basis of cell fate and differentiation. To obtain a systems-level view of root epidermal cell differentiation, we used a genome-wide transcriptome approach to define and organize a large set of genes into a transcriptional regulatory network. Using cell fate mutants that produce only one of the two epidermal cell types, together with fluorescence-activated cell-sorting to preferentially analyze the root epidermis transcriptome, we identified 1,582 genes differentially expressed in the root-hair or non-hair cell types, including a set of 208 “core” root epidermal genes. The organization of the core genes into a network was accomplished by using 17 distinct root epidermis mutants and 2 hormone treatments to perturb the system and assess the effects on each gene's transcript accumulation. In addition, temporal gene expression information from a developmental time series dataset and predicted gene associations derived from a Bayesian modeling approach were used to aid the positioning of genes within the network. Further, a detailed functional analysis of likely bHLH regulatory genes within the network, including MYC1, bHLH54, bHLH66, and bHLH82, showed that three distinct subfamilies of bHLH proteins participate in root epidermis development in a stage-specific manner. The integration of genetic, genomic, and computational analyses provides a new view of the composition, architecture, and logic of the root epidermal transcriptional network, and it demonstrates the utility of a comprehensive systems approach for dissecting a complex regulatory network. PMID:22253603

  20. Improved reconstruction of in silico gene regulatory networks by integrating knockout and perturbation data.

    Directory of Open Access Journals (Sweden)

    Kevin Y Yip

    Full Text Available We performed computational reconstruction of the in silico gene regulatory networks in the DREAM3 Challenges. Our task was to learn the networks from two types of data, namely gene expression profiles in deletion strains (the 'deletion data' and time series trajectories of gene expression after some initial perturbation (the 'perturbation data'. In the course of developing the prediction method, we observed that the two types of data contained different and complementary information about the underlying network. In particular, deletion data allow for the detection of direct regulatory activities with strong responses upon the deletion of the regulator while perturbation data provide richer information for the identification of weaker and more complex types of regulation. We applied different techniques to learn the regulation from the two types of data. For deletion data, we learned a noise model to distinguish real signals from random fluctuations using an iterative method. For perturbation data, we used differential equations to model the change of expression levels of a gene along the trajectories due to the regulation of other genes. We tried different models, and combined their predictions. The final predictions were obtained by merging the results from the two types of data. A comparison with the actual regulatory networks suggests that our approach is effective for networks with a range of different sizes. The success of the approach demonstrates the importance of integrating heterogeneous data in network reconstruction.

  1. iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections

    Science.gov (United States)

    Imrichová, Hana; Van de Sande, Bram; Standaert, Laura; Christiaens, Valerie; Hulselmans, Gert; Herten, Koen; Naval Sanchez, Marina; Potier, Delphine; Svetlichnyy, Dmitry; Kalender Atak, Zeynep; Fiers, Mark; Marine, Jean-Christophe; Aerts, Stein

    2014-01-01

    Identifying master regulators of biological processes and mapping their downstream gene networks are key challenges in systems biology. We developed a computational method, called iRegulon, to reverse-engineer the transcriptional regulatory network underlying a co-expressed gene set using cis-regulatory sequence analysis. iRegulon implements a genome-wide ranking-and-recovery approach to detect enriched transcription factor motifs and their optimal sets of direct targets. We increase the accuracy of network inference by using very large motif collections of up to ten thousand position weight matrices collected from various species, and linking these to candidate human TFs via a motif2TF procedure. We validate iRegulon on gene sets derived from ENCODE ChIP-seq data with increasing levels of noise, and we compare iRegulon with existing motif discovery methods. Next, we use iRegulon on more challenging types of gene lists, including microRNA target sets, protein-protein interaction networks, and genetic perturbation data. In particular, we over-activate p53 in breast cancer cells, followed by RNA-seq and ChIP-seq, and could identify an extensive up-regulated network controlled directly by p53. Similarly we map a repressive network with no indication of direct p53 regulation but rather an indirect effect via E2F and NFY. Finally, we generalize our computational framework to include regulatory tracks such as ChIP-seq data and show how motif and track discovery can be combined to map functional regulatory interactions among co-expressed genes. iRegulon is available as a Cytoscape plugin from http://iregulon.aertslab.org. PMID:25058159

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

    Science.gov (United States)

    Behdani, Elham; Bakhtiarizadeh, Mohammad Reza

    2017-10-01

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

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

    DEFF Research Database (Denmark)

    Fang, Xin; Sastry, Anand; Mih, Nathan

    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...... 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...

  4. Preservation of Gene Duplication Increases the Regulatory Spectrum of Ribosomal Protein Genes and Enhances Growth under Stress

    Directory of Open Access Journals (Sweden)

    Julie Parenteau

    2015-12-01

    Full Text Available In baker’s yeast, the majority of ribosomal protein genes (RPGs are duplicated, and it was recently proposed that such duplications are preserved via the functional specialization of the duplicated genes. However, the origin and nature of duplicated RPGs’ (dRPGs functional specificity remain unclear. In this study, we show that differences in dRPG functions are generated by variations in the modality of gene expression and, to a lesser extent, by protein sequence. Analysis of the sequence and expression patterns of non-intron-containing RPGs indicates that each dRPG is controlled by specific regulatory sequences modulating its expression levels in response to changing growth conditions. Homogenization of dRPG sequences reduces cell tolerance to growth under stress without changing the number of expressed genes. Together, the data reveal a model where duplicated genes provide a means for modulating the expression of ribosomal proteins in response to stress.

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

    Directory of Open Access Journals (Sweden)

    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

  6. Genes associated with the cis-regulatory functions of intragenic LINE-1 elements.

    Science.gov (United States)

    Wanichnopparat, Wachiraporn; Suwanwongse, Kulachanya; Pin-On, Piyapat; Aporntewan, Chatchawit; Mutirangura, Apiwat

    2013-03-27

    Thousands of intragenic long interspersed element 1 sequences (LINE-1 elements or L1s) reside within genes. These intragenic L1 sequences are conserved and regulate the expression of their host genes. When L1 methylation is decreased, either through chemical induction or in cancer, the intragenic L1 transcription is increased. The resulting L1 mRNAs form RISC complexes with pre-mRNA to degrade the complementary mRNA. In this study, we screened for genes that are involved in intragenic L1 regulation networks. Genes containing L1s were obtained from L1Base (http://l1base.molgen.mpg.de). The expression profiles of 205 genes in 516 gene knockdown experiments were obtained from the Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo). The expression levels of the genes with and without L1s were compared using Pearson's chi-squared test. After a permutation based statistical analysis and a multiple hypothesis testing, 73 genes were found to induce significant regulatory changes (upregulation and/or downregulation) in genes with L1s. In detail, 5 genes were found to induce both the upregulation and downregulation of genes with L1s, whereas 27 and 37 genes induced the downregulation and upregulation, respectively, of genes with L1s. These regulations sometimes differed depending on the cell type and the orientation of the intragenic L1s. Moreover, the siRNA-regulating genes containing L1s possess a variety of molecular functions, are responsible for many cellular phenotypes and are associated with a number of diseases. Cells use intragenic L1s as cis-regulatory elements within gene bodies to modulate gene expression. There may be several mechanisms by which L1s mediate gene expression. Intragenic L1s may be involved in the regulation of several biological processes, including DNA damage and repair, inflammation, immune function, embryogenesis, cell differentiation, cellular response to external stimuli and hormonal responses. Furthermore, in addition to cancer

  7. Identification of C4 photosynthesis metabolism and regulatory-associated genes in Eleocharis vivipara by SSH.

    Science.gov (United States)

    Chen, Taiyu; Ye, Rongjian; Fan, Xiaolei; Li, Xianghua; Lin, Yongjun

    2011-09-01

    This is the first effort to investigate the candidate genes involved in kranz developmental regulation and C(4) metabolic fluxes in Eleocharis vivipara, which is a leafless freshwater amphibious plant and possesses a distinct culms anatomy structure and photosynthetic pattern in contrasting environments. A terrestrial specific SSH library was constructed to investigate the genes involved in kranz anatomy developmental regulation and C(4) metabolic fluxes. A total of 73 ESTs and 56 unigenes in 384 clones were identified by array hybridization and sequencing. In total, 50 unigenes had homologous genes in the databases of rice and Arabidopsis. The real-time quantitative PCR results showed that most of the genes were accumulated in terrestrial culms and ABA-induced culms. The C(4) marker genes were stably accumulated during the culms development process in terrestrial culms. With respect to C(3) culms, C(4) photosynthesis metabolism consumed much more transporters and translocators related to ion metabolism, organic acids and carbohydrate metabolism, phosphate metabolism, amino acids metabolism, and lipids metabolism. Additionally, ten regulatory genes including five transcription factors, four receptor-like proteins, and one BURP protein were identified. These regulatory genes, which co-accumulated with the culms developmental stages, may play important roles in culms structure developmental regulation, bundle sheath chloroplast maturation, and environmental response. These results shed new light on the C(4) metabolic fluxes, environmental response, and anatomy structure developmental regulation in E. vivipara.

  8. Improvement of lentiviral transfer vectors using cis-acting regulatory elements for increased gene expression.

    Science.gov (United States)

    Real, Gonçalo; Monteiro, Francisca; Burger, Christa; Alves, Paula M

    2011-09-01

    Lentiviral vectors are an important tool for gene delivery in vivo and in vitro. The success of gene transfer approaches relies on high and stable levels of gene expression. To this end, several molecular strategies have been employed to manipulate these vectors towards improving gene expression in the targeted animal cells. Low gene expression can be accepted due to the weak transcription from the majority of available mammalian promoters; however, this obstacle can be in part overcome by the insertion of cis-acting elements that enhance gene expression in various expression contexts. In this work, we created different lentiviral vectors in which several posttranscriptional regulatory elements, namely the Woodchuck hepatitis posttranscriptional regulatory element (WPRE) and different specialized poly(A) termination sequences (BGH and SV40) were used to develop vectors leading to improved transgene expression. These vectors combine the advantages of restriction enzyme/ligation-independent cloning eliminating the instability and recombinogenic problems occurring from traditional cloning methods in lentiviral expression vectors and were tested by expressing GFP and the firefly Luciferase reporter gene from different cellular promoters in different cell lines. We show that the promoter activity varies between cell lines and is affected by the lentiviral genomic context. Moreover, we show that the combination of the WPRE element with the BGH poly(A) signal significantly enhances transgene expression. The vectors herein created can be easily modified and adapted without the need for extensive recloning making them a valuable tool for viral vector development.

  9. Gene-gene interaction in regulatory T-cell function in atopy and asthma development in childhood.

    Science.gov (United States)

    Bottema, Renske W B; Kerkhof, Marjan; Reijmerink, Naomi E; Thijs, Carel; Smit, Henriette A; van Schayck, Constant P; Brunekreef, Bert; van Oosterhout, Antoon J; Postma, Dirkje S; Koppelman, Gerard H

    2010-08-01

    Regulatory T-cell dysfunction is associated with development of the complex genetic conditions atopy and asthma. Therefore, we hypothesized that single nucleotide polymorphisms in genes involved in the development and function of regulatory T cells are associated with atopy and asthma development. To evaluate main effects and gene-gene interactions of haplotype tagging single nucleotide polymorphisms of genes involved in regulatory T-cell function-IL6, IL6R, IL10, heme-oxygenase 1 (HMOX1), IL2, Toll-like receptor 2 (TLR2), TGFB1, TGF-beta receptor (TGFBR)-1, TGFBR2, IL2RA, and forkhead box protein 3 (FOXP3)-in relation to atopy and asthma. Single-locus and multilocus associations with total IgE (3rd vs 1st tertile); specific IgE to egg, milk, and indoor allergens; and asthma were evaluated by chi(2) tests and the multifactor dimensionality-reduction method in 3 birth cohorts (Allergenic study). Multiple statistically significant multilocus associations existed. IL2RA rs4749926 and TLR2 rs4696480 associated with IgE in both age groups tested (1-2 and 6-8 years). TGFBR2 polymorphisms associated with total and specific IgE in both age groups and with asthma. TGFBR2 rs9831477 associated with specific IgE for milk at age 1 to 2 years and indoor allergens at age 6 to 8 years. For milk-specific IgE, interaction between TGFBR2 and FOXP3 polymorphisms was confirmed by logistic regression and consistent in 2 birth cohorts and when stratified for sex, supplying internal replications. Genes involved in the development and function of regulatory T cells, specifically IL2RA, TLR2, TGFBR2, and FOXP3, associate with atopy and asthma by gene-gene interaction. Modeling of multiple gene-gene interactions is important to unravel further the genetic susceptibility to atopy and asthma. Copyright 2010 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

  10. Transcriptional and post-transcriptional control of the plant circadian gene regulatory network.

    Science.gov (United States)

    Hernando, C Esteban; Romanowski, Andrés; Yanovsky, Marcelo J

    2017-01-01

    The circadian clock drives rhythms in multiple physiological processes allowing plants to anticipate and adjust to periodic changes in environmental conditions. These physiological rhythms are associated with robust oscillations in the expression of thousands of genes linked to the control of photosynthesis, cell elongation, biotic and abiotic stress responses, developmental processes such as flowering, and the clock itself. Given its pervasive effects on plant physiology, it is not surprising that circadian clock genes have played an important role in the domestication of crop plants and in the improvement of crop productivity. Therefore, identifying the principles governing the dynamics of the circadian gene regulatory network in plants could strongly contribute to further speed up crop improvement. Here we provide an historical as well as a current description of our knowledge of the molecular mechanisms underlying circadian rhythms in plants. This work focuses on the transcriptional and post-transcriptional regulatory layers that control the very core of the circadian clock, and some of its complex interactions with signaling pathways that help synchronize plant growth and development to daily and seasonal changes in the environment. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Inferring a transcriptional regulatory network from gene expression data using nonlinear manifold embedding.

    Directory of Open Access Journals (Sweden)

    Hossein Zare

    Full Text Available Transcriptional networks consist of multiple regulatory layers corresponding to the activity of global regulators, specialized repressors and activators as well as proteins and enzymes shaping the DNA template. Such intrinsic complexity makes uncovering connections difficult and it calls for corresponding methodologies, which are adapted to the available data. Here we present a new computational method that predicts interactions between transcription factors and target genes using compendia of microarray gene expression data and documented interactions between genes and transcription factors. The proposed method, called Kernel Embedding of Regulatory Networks (KEREN, is based on the concept of gene-regulon association, and captures hidden geometric patterns of the network via manifold embedding. We applied KEREN to reconstruct transcription regulatory interactions on a genome-wide scale in the model bacteria Escherichia coli (E. coli. Application of the method not only yielded accurate predictions of verifiable interactions, which outperformed on certain metrics comparable methodologies, but also demonstrated the utility of a geometric approach in the analysis of high-dimensional biological data. We also described possible applications of kernel embedding techniques to other function and network discovery algorithms.

  12. Inferring a transcriptional regulatory network from gene expression data using nonlinear manifold embedding.

    Science.gov (United States)

    Zare, Hossein; Kaveh, Mostafa; Khodursky, Arkady

    2011-01-01

    Transcriptional networks consist of multiple regulatory layers corresponding to the activity of global regulators, specialized repressors and activators as well as proteins and enzymes shaping the DNA template. Such intrinsic complexity makes uncovering connections difficult and it calls for corresponding methodologies, which are adapted to the available data. Here we present a new computational method that predicts interactions between transcription factors and target genes using compendia of microarray gene expression data and documented interactions between genes and transcription factors. The proposed method, called Kernel Embedding of Regulatory Networks (KEREN), is based on the concept of gene-regulon association, and captures hidden geometric patterns of the network via manifold embedding. We applied KEREN to reconstruct transcription regulatory interactions on a genome-wide scale in the model bacteria Escherichia coli (E. coli). Application of the method not only yielded accurate predictions of verifiable interactions, which outperformed on certain metrics comparable methodologies, but also demonstrated the utility of a geometric approach in the analysis of high-dimensional biological data. We also described possible applications of kernel embedding techniques to other function and network discovery algorithms.

  13. A Catalog of Regulatory Sequences for Trait Gene for the Genome Editing of Wheat.

    Science.gov (United States)

    Makai, Szabolcs; Tamás, László; Juhász, Angéla

    2016-01-01

    Wheat has been cultivated for 10000 years and ever since the origin of hexaploid wheat it has been exempt from natural selection. Instead, it was under the constant selective pressure of human agriculture from harvest to sowing during every year, producing a vast array of varieties. Wheat has been adopted globally, accumulating variation for genes involved in yield traits, environmental adaptation and resistance. However, one small but important part of the wheat genome has hardly changed: the regulatory regions of both the x- and y-type high molecular weight glutenin subunit (HMW-GS) genes, which are alone responsible for approximately 12% of the grain protein content. The phylogeny of the HMW-GS regulatory regions of the Triticeae demonstrates that a genetic bottleneck may have led to its decreased diversity during domestication and the subsequent cultivation. It has also highlighted the fact that the wild relatives of wheat may offer an unexploited genetic resource for the regulatory region of these genes. Significant research efforts have been made in the public sector and by international agencies, using wild crosses to exploit the available genetic variation, and as a result synthetic hexaploids are now being utilized by a number of breeding companies. However, a newly emerging tool of genome editing provides significantly improved efficiency in exploiting the natural variation in HMW-GS genes and incorporating this into elite cultivars and breeding lines. Recent advancement in the understanding of the regulation of these genes underlines the needs for an overview of the regulatory elements for genome editing purposes.

  14. Functional data analysis for identifying nonlinear models of gene regulatory networks.

    Science.gov (United States)

    Summer, Georg; Perkins, Theodore J

    2010-12-02

    A key problem in systems biology is estimating dynamical models of gene regulatory networks. Traditionally, this has been done using regression or other ad-hoc methods when the model is linear. More detailed, realistic modeling studies usually employ nonlinear dynamical models, which lead to computationally difficult parameter estimation problems. Functional data analysis methods, however, offer a means to simplify fitting by transforming the problem from one of matching modeled and observed dynamics to one of matching modeled and observed time derivatives-a regression problem, albeit a nonlinear one. We formulate a functional data analysis approach for estimating the parameters of nonlinear dynamical models and evaluate this approach on data from two real systems, the gap gene system of Drosophila melanogaster and the synthetic IRMA network, which was created expressly as a test case for genetic network inference. We also evaluate the approach on simulated data sets generated by the GeneNetWeaver program, the basis for the annual DREAM reverse engineering challenge. We assess the accuracy with which the correct regulatory relationships within the networks are extracted, and consider alternative methods of regularization for the purpose of overfitting avoidance. We also show that the computational efficiency of the functional data analysis approach, and the decomposability of the resulting regression problem, allow us to explicitly enumerate and evaluate all possible regulator combinations for every gene. This gives deeper insight into the the relevance of different regulators or regulator combinations, and lets one check for alternative regulatory explanations. Functional data analysis is a powerful approach for estimating detailed nonlinear models of gene expression dynamics, allowing efficient and accurate estimation of regulatory architecture.

  15. Cis-Regulatory Control of the Nuclear Receptor Coup-TF Gene in the Sea Urchin Paracentrotus lividus Embryo

    OpenAIRE

    Lamprini G Kalampoki; Flytzanis, Constantin N.

    2014-01-01

    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 plute...

  16. Abundant raw material for cis-regulatory evolution in humans

    Science.gov (United States)

    Rockman, Matthew V.; Wray, Gregory A.

    2002-01-01

    Changes in gene expression and regulation--due in particular to the evolution of cis-regulatory DNA sequences--may underlie many evolutionary changes in phenotypes, yet little is known about the distribution of such variation in populations. We present in this study the first survey of experimentally validated functional cis-regulatory polymorphism. These data are derived from more than 140 polymorphisms involved in the regulation of 107 genes in Homo sapiens, the eukaryote species with the most available data. We find that functional cis-regulatory variation is widespread in the human genome and that the consequent variation in gene expression is twofold or greater for 63% of the genes surveyed. Transcription factor-DNA interactions are highly polymorphic, and regulatory interactions have been gained and lost within human populations. On average, humans are heterozygous at more functional cis-regulatory sites (>16,000) than at amino acid positions (human phenotypic variation.

  17. A Consensus Network of Gene Regulatory Factors in the Human Frontal Lobe

    Science.gov (United States)

    Berto, Stefano; Perdomo-Sabogal, Alvaro; Gerighausen, Daniel; Qin, Jing; Nowick, Katja

    2016-01-01

    Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID) or autism spectrum disorders (ASD). Because many of these genes are gene regulatory factors (GRFs) we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies. PMID:27014338

  18. A consensus network of gene regulatory factors in the human frontal lobe

    Directory of Open Access Journals (Sweden)

    Stefano eBerto

    2016-03-01

    Full Text Available Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID or autism spectrum disorders (ASD. Because many of these genes are gene regulatory factors (GRFs we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies.

  19. Reverse Engineering Sparse Gene Regulatory Networks Using Cubature Kalman Filter and Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Amina Noor

    2013-01-01

    Full Text Available This paper proposes a novel algorithm for inferring gene regulatory networks which makes use of cubature Kalman filter (CKF and Kalman filter (KF techniques in conjunction with compressed sensing methods. The gene network is described using a state-space model. A nonlinear model for the evolution of gene expression is considered, while the gene expression data is assumed to follow a linear Gaussian model. The hidden states are estimated using CKF. The system parameters are modeled as a Gauss-Markov process and are estimated using compressed sensing-based KF. These parameters provide insight into the regulatory relations among the genes. The Cramér-Rao lower bound of the parameter estimates is calculated for the system model and used as a benchmark to assess the estimation accuracy. The proposed algorithm is evaluated rigorously using synthetic data in different scenarios which include different number of genes and varying number of sample points. In addition, the algorithm is tested on the DREAM4 in silico data sets as well as the in vivo data sets from IRMA network. The proposed algorithm shows superior performance in terms of accuracy, robustness, and scalability.

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

    Directory of Open Access Journals (Sweden)

    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.

  1. Adaptive NetworkProfiler for Identifying Cancer Characteristic-Specific Gene Regulatory Networks.

    Science.gov (United States)

    Park, Heewon; Shimamura, Teppei; Imoto, Seiya; Miyano, Satoru

    2017-10-20

    There is currently much discussion about sample (patient)-specific gene regulatory network identification, since the efficiently constructed sample-specific gene networks lead to effective personalized cancer therapy. Although statistical approaches have been proposed for inferring gene regulatory networks, the methods cannot reveal sample-specific characteristics because the existing methods, such as an L1-type regularization, provide averaged results for all samples. Thus, we cannot reveal sample-specific characteristics in transcriptional regulatory networks. To settle on this issue, the NetworkProfiler was proposed based on the kernel-based L1-type regularization. The NetworkProfiler imposes a weight on each sample based on the Gaussian kernal function for controlling effect of samples on modeling a target sample, where the amount of weight depends on similarity of cancer characteristics between samples. The method, however, cannot perform gene regulatory network identification well for a target sample in a sparse region (i.e., for a target sample, there are only a few samples having a similar characteristic of the target sample, where the characteristic is considered as a modulator in sample-specific gene network construction), since a constant bandwidth in the Gaussian kernel function cannot effectively group samples for modeling a target sample in sparse region. The cancer characteristics, such as an anti-cancer drug sensitivity, are usually nonuniformly distributed, and thus modeling for samples in a sparse region is also a crucial issue. We propose a novel kernel-based L1-type regularization method based on a modified k-nearest neighbor (KNN)-Gaussian kernel function, called an adaptive NetworkProfiler. By using the modified KNN-Gaussian kernel function, our method provides robust results against the distribution of modulators, and properly groups samples according to a cancer characteristic for sample-specific analysis. Furthermore, we propose a sample

  2. Identification of critical regulatory genes in cancer signaling network using controllability analysis

    Science.gov (United States)

    Ravindran, Vandana; Sunitha, V.; Bagler, Ganesh

    2017-05-01

    Cancer is characterized by a complex web of regulatory mechanisms which makes it difficult to identify features that are central to its control. Molecular integrative models of cancer, generated with the help of data from experimental assays, facilitate use of control theory to probe for ways of controlling the state of such a complex dynamic network. We modeled the human cancer signaling network as a directed graph and analyzed it for its controllability, identification of driver nodes and their characterization. We identified the driver nodes using the maximum matching algorithm and classified them as backbone, peripheral and ordinary based on their role in regulatory interactions and control of the network. We found that the backbone driver nodes were key to driving the regulatory network into cancer phenotype (via mutations) as well as for steering into healthy phenotype (as drug targets). This implies that while backbone genes could lead to cancer by virtue of mutations, they are also therapeutic targets of cancer. Further, based on their impact on the size of the set of driver nodes, genes were characterized as indispensable, dispensable and neutral. Indispensable nodes within backbone of the network emerged as central to regulatory mechanisms of control of cancer. In addition to probing the cancer signaling network from the perspective of control, our findings suggest that indispensable backbone driver nodes could be potentially leveraged as therapeutic targets. This study also illustrates the application of structural controllability for studying the mechanisms underlying the regulation of complex diseases.

  3. 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

  4. Finding Robust Adaptation Gene Regulatory Networks Using Multi-Objective Genetic Algorithm.

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    Ren, Hai-Peng; Huang, Xiao-Na; Hao, Jia-Xuan

    2016-01-01

    Robust adaptation plays a key role in gene regulatory networks, and it is thought to be an important attribute for the organic or cells to survive in fluctuating conditions. In this paper, a simplified three-node enzyme network is modeled by the Michaelis-Menten rate equations for all possible topologies, and a family of topologies and the corresponding parameter sets of the network with satisfactory adaptation are obtained using the multi-objective genetic algorithm. The proposed approach improves the computation efficiency significantly as compared to the time consuming exhaustive searching method. This approach provides a systemic way for searching the feasible topologies and the corresponding parameter sets to make the gene regulatory networks have robust adaptation. The proposed methodology, owing to its universality and simplicity, can be used to address more complex issues in biological networks.

  5. Information theory in systems biology. Part I: Gene regulatory and metabolic networks.

    Science.gov (United States)

    Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-03-01

    "A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Computational discovery and in vivo validation of hnf4 as a regulatory gene in planarian regeneration.

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    Lobo, Daniel; Morokuma, Junji; Levin, Michael

    2016-09-01

    Automated computational methods can infer dynamic regulatory network models directly from temporal and spatial experimental data, such as genetic perturbations and their resultant morphologies. Recently, a computational method was able to reverse-engineer the first mechanistic model of planarian regeneration that can recapitulate the main anterior-posterior patterning experiments published in the literature. Validating this comprehensive regulatory model via novel experiments that had not yet been performed would add in our understanding of the remarkable regeneration capacity of planarian worms and demonstrate the power of this automated methodology. Using the Michigan Molecular Interactions and STRING databases and the MoCha software tool, we characterized as hnf4 an unknown regulatory gene predicted to exist by the reverse-engineered dynamic model of planarian regeneration. Then, we used the dynamic model to predict the morphological outcomes under different single and multiple knock-downs (RNA interference) of hnf4 and its predicted gene pathway interactors β-catenin and hh Interestingly, the model predicted that RNAi of hnf4 would rescue the abnormal regenerated phenotype (tailless) of RNAi of hh in amputated trunk fragments. Finally, we validated these predictions in vivo by performing the same surgical and genetic experiments with planarian worms, obtaining the same phenotypic outcomes predicted by the reverse-engineered model. These results suggest that hnf4 is a regulatory gene in planarian regeneration, validate the computational predictions of the reverse-engineered dynamic model, and demonstrate the automated methodology for the discovery of novel genes, pathways and experimental phenotypes. michael.levin@tufts.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

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    Daniel Meier

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

  8. Augmenting microarray data with literature-based knowledge to enhance gene regulatory network inference.

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    Guocai Chen

    2014-06-01

    Full Text Available Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions. The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a

  9. Echinochrome A Increases Mitochondrial Mass and Function by Modulating Mitochondrial Biogenesis Regulatory Genes

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    Seung Hun Jeong

    2014-08-01

    Full Text Available Echinochrome A (Ech A is a natural pigment from sea urchins that has been reported to have antioxidant properties and a cardio protective effect against ischemia reperfusion injury. In this study, we ascertained whether Ech A enhances the mitochondrial biogenesis and oxidative phosphorylation in rat cardio myoblast H9c2 cells. To study the effects of Ech A on mitochondrial biogenesis, we measured mitochondrial mass, level of oxidative phosphorylation, and mitochondrial biogenesis regulatory gene expression. Ech A treatment did not induce cytotoxicity. However, Ech A treatment enhanced oxygen consumption rate and mitochondrial ATP level. Likewise, Ech A treatment increased mitochondrial contents in H9c2 cells. Furthermore, Ech A treatment up-regulated biogenesis of regulatory transcription genes, including proliferator-activated receptor gamma co-activator (PGC-1α, estrogen-related receptor (ERR-α, peroxisome proliferator-activator receptor (PPAR-γ, and nuclear respiratory factor (NRF-1 and such mitochondrial transcription regulatory genes as mitochondrial transcriptional factor A (TFAM, mitochondrial transcription factor B2 (TFB2M, mitochondrial DNA direct polymerase (POLMRT, single strand binding protein (SSBP and Tu translation elongation factor (TUFM. In conclusion, these data suggest that Ech A is a potentiated marine drug which enhances mitochondrial biogenesis.

  10. Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation.

    Science.gov (United States)

    Simandi, Zoltan; Horvath, Attila; Nagy, Peter; Nagy, Laszlo

    2016-06-21

    Embryonic development is a multistep process involving activation and repression of many genes. Enhancer elements in the genome are known to contribute to tissue and cell-type specific regulation of gene expression during the cellular differentiation. Thus, their identification and further investigation is important in order to understand how cell fate is determined. Integration of gene expression data (e.g., microarray or RNA-seq) and results of chromatin immunoprecipitation (ChIP)-based genome-wide studies (ChIP-seq) allows large-scale identification of these regulatory regions. However, functional validation of cell-type specific enhancers requires further in vitro and in vivo experimental procedures. Here we describe how active enhancers can be identified and validated experimentally. This protocol provides a step-by-step workflow that includes: 1) identification of regulatory regions by ChIP-seq data analysis, 2) cloning and experimental validation of putative regulatory potential of the identified genomic sequences in a reporter assay, and 3) determination of enhancer activity in vivo by measuring enhancer RNA transcript level. The presented protocol is detailed enough to help anyone to set up this workflow in the lab. Importantly, the protocol can be easily adapted to and used in any cellular model system.

  11. Autophagy in unicellular eukaryotes

    NARCIS (Netherlands)

    Kiel, J.A.K.W.

    2010-01-01

    Cells need a constant supply of precursors to enable the production of macromolecules to sustain growth and survival. Unlike metazoans, unicellular eukaryotes depend exclusively on the extracellular medium for this supply. When environmental nutrients become depleted, existing cytoplasmic components

  12. 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

  13. Applying gene regulatory network logic to the evolution of social behavior.

    Science.gov (United States)

    Baran, Nicole M; McGrath, Patrick T; Streelman, J Todd

    2017-06-06

    Animal behavior is ultimately the product of gene regulatory networks (GRNs) for brain development and neural networks for brain function. The GRN approach has advanced the fields of genomics and development, and we identify organizational similarities between networks of genes that build the brain and networks of neurons that encode brain function. In this perspective, we engage the analogy between developmental networks and neural networks, exploring the advantages of using GRN logic to study behavior. Applying the GRN approach to the brain and behavior provides a quantitative and manipulative framework for discovery. We illustrate features of this framework using the example of social behavior and the neural circuitry of aggression.

  14. NetDiff - Bayesian model selection for differential gene regulatory network inference.

    Science.gov (United States)

    Thorne, Thomas

    2016-12-16

    Differential networks allow us to better understand the changes in cellular processes that are exhibited in conditions of interest, identifying variations in gene regulation or protein interaction between, for example, cases and controls, or in response to external stimuli. Here we present a novel methodology for the inference of differential gene regulatory networks from gene expression microarray data. Specifically we apply a Bayesian model selection approach to compare models of conserved and varying network structure, and use Gaussian graphical models to represent the network structures. We apply a variational inference approach to the learning of Gaussian graphical models of gene regulatory networks, that enables us to perform Bayesian model selection that is significantly more computationally efficient than Markov Chain Monte Carlo approaches. Our method is demonstrated to be more robust than independent analysis of data from multiple conditions when applied to synthetic network data, generating fewer false positive predictions of differential edges. We demonstrate the utility of our approach on real world gene expression microarray data by applying it to existing data from amyotrophic lateral sclerosis cases with and without mutations in C9orf72, and controls, where we are able to identify differential network interactions for further investigation.

  15. Two Lamprey Hedgehog Genes Share Non-Coding Regulatory Sequences and Expression Patterns with Gnathostome Hedgehogs

    Science.gov (United States)

    Ekker, Marc; Hadzhiev, Yavor; Müller, Ferenc; Casane, Didier; Magdelenat, Ghislaine; Rétaux, Sylvie

    2010-01-01

    Hedgehog (Hh) genes play major roles in animal development and studies of their evolution, expression and function point to major differences among chordates. Here we focused on Hh genes in lampreys in order to characterize the evolution of Hh signalling at the emergence of vertebrates. Screening of a cosmid library of the river lamprey Lampetra fluviatilis and searching the preliminary genome assembly of the sea lamprey Petromyzon marinus indicate that lampreys have two Hh genes, named Hha and Hhb. Phylogenetic analyses suggest that Hha and Hhb are lamprey-specific paralogs closely related to Sonic/Indian Hh genes. Expression analysis indicates that Hha and Hhb are expressed in a Sonic Hh-like pattern. The two transcripts are expressed in largely overlapping but not identical domains in the lamprey embryonic brain, including a newly-described expression domain in the nasohypophyseal placode. Global alignments of genomic sequences and local alignment with known gnathostome regulatory motifs show that lamprey Hhs share conserved non-coding elements (CNE) with gnathostome Hhs albeit with sequences that have significantly diverged and dispersed. Functional assays using zebrafish embryos demonstrate gnathostome-like midline enhancer activity for CNEs contained in intron2. We conclude that lamprey Hh genes are gnathostome Shh-like in terms of expression and regulation. In addition, they show some lamprey-specific features, including duplication and structural (but not functional) changes in the intronic/regulatory sequences. PMID:20967201

  16. Inferring gene regulatory networks by singular value decomposition and gravitation field algorithm.

    Science.gov (United States)

    Zheng, Ming; Wu, Jia-nan; Huang, Yan-xin; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

    2012-01-01

    Reconstruction of gene regulatory networks (GRNs) is of utmost interest and has become a challenge computational problem in system biology. However, every existing inference algorithm from gene expression profiles has its own advantages and disadvantages. In particular, the effectiveness and efficiency of every previous algorithm is not high enough. In this work, we proposed a novel inference algorithm from gene expression data based on differential equation model. In this algorithm, two methods were included for inferring GRNs. Before reconstructing GRNs, singular value decomposition method was used to decompose gene expression data, determine the algorithm solution space, and get all candidate solutions of GRNs. In these generated family of candidate solutions, gravitation field algorithm was modified to infer GRNs, used to optimize the criteria of differential equation model, and search the best network structure result. The proposed algorithm is validated on both the simulated scale-free network and real benchmark gene regulatory network in networks database. Both the Bayesian method and the traditional differential equation model were also used to infer GRNs, and the results were used to compare with the proposed algorithm in our work. And genetic algorithm and simulated annealing were also used to evaluate gravitation field algorithm. The cross-validation results confirmed the effectiveness of our algorithm, which outperforms significantly other previous algorithms.

  17. PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space.

    Science.gov (United States)

    Ma, Chihua; Luciani, Timothy; Terebus, Anna; Liang, Jie; Marai, G Elisabeta

    2017-02-15

    Visualizing the complex probability landscape of stochastic gene regulatory networks can further biologists' understanding of phenotypic behavior associated with specific genes. We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based visual analysis tool for the systematic exploration of probability distributions over simulation time and state space in such networks. PRODIGEN was designed in collaboration with bioinformaticians who research stochastic gene networks. The analysis tool combines in a novel way existing, expanded, and new visual encodings to capture the time-varying characteristics of probability distributions: spaghetti plots over one dimensional projection, heatmaps of distributions over 2D projections, enhanced with overlaid time curves to display temporal changes, and novel individual glyphs of state information corresponding to particular peaks. We demonstrate the effectiveness of the tool through two case studies on the computed probabilistic landscape of a gene regulatory network and of a toggle-switch network. Domain expert feedback indicates that our visual approach can help biologists: 1) visualize probabilities of stable states, 2) explore the temporal probability distributions, and 3) discover small peaks in the probability landscape that have potential relation to specific diseases.

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

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    Tuqyah Abdullah Al Qazlan

    2015-01-01

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

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

    Science.gov (United States)

    Al Qazlan, Tuqyah Abdullah; Kara-Mohamed, Chafia

    2015-01-01

    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. PMID:25879048

  20. Single master regulatory gene coordinates the evolution and development of butterfly color and iridescence.

    Science.gov (United States)

    Zhang, Linlin; Mazo-Vargas, Anyi; Reed, Robert D

    2017-10-03

    The optix gene has been implicated in butterfly wing pattern adaptation by genetic association, mapping, and expression studies. The actual developmental function of this gene has remained unclear, however. Here we used CRISPR/Cas9 genome editing to show that optix plays a fundamental role in nymphalid butterfly wing pattern development, where it is required for determination of all chromatic coloration. optix knockouts in four species show complete replacement of color pigments with melanins, with corresponding changes in pigment-related gene expression, resulting in black and gray butterflies. We also show that optix simultaneously acts as a switch gene for blue structural iridescence in some butterflies, demonstrating simple regulatory coordination of structural and pigmentary coloration. Remarkably, these optix knockouts phenocopy the recurring "black and blue" wing pattern archetype that has arisen on many independent occasions in butterflies. Here we demonstrate a simple genetic basis for structural coloration, and show that optix plays a deeply conserved role in butterfly wing pattern development.

  1. Regulatory role of SGT1 in early R gene-mediated plant defenses.

    Science.gov (United States)

    Austin, Mark J; Muskett, Paul; Kahn, Katherine; Feys, Bart J; Jones, Jonathan D G; Parker, Jane E

    2002-03-15

    Animal SGT1 is a component of Skp1-Cullin-F-box protein (SCF) ubiquitin ligases that target regulatory proteins for degradation. Mutations in one (SGT1b) of two highly homologous Arabidopsis SGT1 genes disable early plant defenses conferred by multiple resistance (R) genes. Loss of SGT1b function in resistance is not compensated for by SGT1a. R genes differ in their requirements for SGT1b and a second resistance signaling gene, RAR1, that was previously implicated as an SGT1 interactor. Moreover, SGT1b and RAR1 contribute additively to RPP5-mediated pathogen recognition. These data imply both operationally distinct and cooperative functions of SGT1 and RAR1 in plant disease resistance.

  2. Structural disorder in eukaryotes.

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    Rita Pancsa

    Full Text Available Based on early bioinformatic studies on a handful of species, the frequency of structural disorder of proteins is generally thought to be much higher in eukaryotes than in prokaryotes. To refine this view, we present here a comparative prediction study and analysis of 194 fully described eukaryotic proteomes and 87 reference prokaryotes for structural disorder. We found that structural disorder does distinguish eukaryotes from prokaryotes, but its frequency spans a very wide range in the two superkingdoms that largely overlap. The number of disordered binding regions and different Pfam domain types also contribute to distinguish eukaryotes from prokaryotes. Unexpectedly, the highest levels--and highest variability--of predicted disorder is found in protists, i.e. single-celled eukaryotes, often surpassing more complex eukaryote organisms, plants and animals. This trend contrasts with that of the number of domain types, which increases rather monotonously toward more complex organisms. The level of structural disorder appears to be strongly correlated with lifestyle, because some obligate intracellular parasites and endosymbionts have the lowest levels, whereas host-changing parasites have the highest level of predicted disorder. We conclude that protists have been the evolutionary hot-bed of experimentation with structural disorder, in a period when structural disorder was actively invented and the major functional classes of disordered proteins established.

  3. The Genome of Naegleria gruberi Illuminates Early Eukaryotic Versatility

    Energy Technology Data Exchange (ETDEWEB)

    Fritz-Laylin, Lillian K.; Prochnik, Simon E.; Ginger, Michael L.; Dacks, Joel; Carpenter, Meredith L.; Field, Mark C.; Kuo, Alan; Paredez, Alex; Chapman, Jarrod; Pham, Jonathan; Shu, Shengqiang; Neupane, Rochak; Cipriano, Michael; Mancuso, Joel; Tu, Hank; Salamov, Asaf; Lindquist, Erika; Shapiro, Harris; Lucas, Susan; Grigoriev, Igor V.; Cande, W. Zacheus; Fulton, Chandler; Rokhsar, Daniel S.; Dawson, Scott C.

    2010-03-01

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

  4. 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

  5. Metatranscriptomic insights on gene expression and regulatory controls in Candidatus Accumulibacter phosphatis

    Science.gov (United States)

    Oyserman, Ben O; Noguera, Daniel R; del Rio, Tijana Glavina; Tringe, Susannah G; McMahon, Katherine D

    2016-01-01

    Previous studies on enhanced biological phosphorus removal (EBPR) have focused on reconstructing genomic blueprints for the model polyphosphate-accumulating organism Candidatus Accumulibacter phosphatis. Here, a time series metatranscriptome generated from enrichment cultures of Accumulibacter was used to gain insight into anerobic/aerobic metabolism and regulatory mechanisms within an EBPR cycle. Co-expressed gene clusters were identified displaying ecologically relevant trends consistent with batch cycle phases. Transcripts displaying increased abundance during anerobic acetate contact were functionally enriched in energy production and conversion, including upregulation of both cytoplasmic and membrane-bound hydrogenases demonstrating the importance of transcriptional regulation to manage energy and electron flux during anerobic acetate contact. We hypothesized and demonstrated hydrogen production after anerobic acetate contact, a previously unknown strategy for Accumulibacter to maintain redox balance. Genes involved in anerobic glycine utilization were identified and phosphorus release after anerobic glycine contact demonstrated, suggesting that Accumulibacter routes diverse carbon sources to acetyl-CoA formation via previously unrecognized pathways. A comparative genomics analysis of sequences upstream of co-expressed genes identified two statistically significant putative regulatory motifs. One palindromic motif was identified upstream of genes involved in PHA synthesis and acetate activation and is hypothesized to be a phaR binding site, hence representing a hypothetical PHA modulon. A second motif was identified ~35 base pairs (bp) upstream of a large and diverse array of genes and hence may represent a sigma factor binding site. This analysis provides a basis and framework for further investigations into Accumulibacter metabolism and the reconstruction of regulatory networks in uncultured organisms. PMID:26555245

  6. A perturbation model of the gene regulatory network for oral and aboral ectoderm specification in the sea urchin embryo

    Science.gov (United States)

    Su, Yi-Hsien; Li, Enhu; Geiss, Gary K.; Longabaugh, William J. R.; Krämer, Alexander; Davidson, Eric H.

    2009-01-01

    The current gene regulatory network (GRN) for the sea urchin embryo pertains to pregastrular specification functions in the endomesodermal territories. Here we extend gene regulatory network analysis to the adjacent oral and aboral ectoderm territories over the same period. A large fraction of the regulatory genes predicted by the sea urchin genome project and shown in ancillary studies to be expressed in either oral or aboral ectoderm by 24h are included, though universally expressed and pan-ectodermal regulatory genes are in general not. The loci of expression of these genes have been determined by whole mount in situ hybridization. We have carried out a global perturbation analysis in which expression of each gene was interrupted by introduction of morpholino antisense oligonucleotide, and the effects on all other genes were measured quantitatively, both by QPCR and by a new instrumental technology (NanoString Technologies nCounter Analysis System). At its current stage the network model, built in BioTapestry, includes 22 genes encoding transcription factors, 4 genes encoding known signaling ligands, and 3 genes that are yet unknown but are predicted to perform specific roles. Evidence emerged from the analysis pointing to distinctive subcircuit features observed earlier in other parts of the GRN, including a double negative transcriptional regulatory gate, and dynamic state lockdowns by feedback interactions. While much of the regulatory apparatus is downstream of Nodal signaling, as expected from previous observations, there are also cohorts of independently activated oral and aboral ectoderm regulatory genes, and we predict yet unidentified signaling interactions between oral and aboral territories. PMID:19268450

  7. Developmental gene regulatory network evolution: insights from comparative studies in echinoderms.

    Science.gov (United States)

    Hinman, Veronica F; Cheatle Jarvela, Alys M

    2014-03-01

    One of the central concerns of Evolutionary Developmental biology is to understand how the specification of cell types can change during evolution. In the last decade, developmental biology has progressed toward a systems level understanding of cell specification processes. In particular, the focus has been on determining the regulatory interactions of the repertoire of genes that make up gene regulatory networks (GRNs). Echinoderms provide an extraordinary model system for determining how GRNs evolve. This review highlights the comparative GRN analyses arising from the echinoderm system. This work shows that certain types of GRN subcircuits or motifs, i.e., those involving positive feedback, tend to be conserved and may provide a constraint on development. This conservation may be due to a required arrangement of transcription factor binding sites in cis regulatory modules. The review will also discuss ways in which novelty may arise, in particular through the co-option of regulatory genes and subcircuits. The development of the sea urchin larval skeleton, a novel feature that arose in echinoderms, has provided a model for study of co-option mechanisms. Finally, the types of GRNs that can permit the great diversity in the patterns of ciliary bands and their associated neurons found among these taxa are discussed. The availability of genomic resources is rapidly expanding for echinoderms, including genome sequences not only for multiple species of sea urchins but also a species of sea star, sea cucumber, and brittle star. This will enable echinoderms to become a particularly powerful system for understanding how developmental GRNs evolve. Copyright © 2014 Wiley Periodicals, Inc.

  8. Predicting miRNA Targets by Integrating Gene Regulatory Knowledge with Expression Profiles.

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    Weijia Zhang

    Full Text Available microRNAs (miRNAs play crucial roles in post-transcriptional gene regulation of both plants and mammals, and dysfunctions of miRNAs are often associated with tumorigenesis and development through the effects on their target messenger RNAs (mRNAs. Identifying miRNA functions is critical for understanding cancer mechanisms and determining the efficacy of drugs. Computational methods analyzing high-throughput data offer great assistance in understanding the diverse and complex relationships between miRNAs and mRNAs. However, most of the existing methods do not fully utilise the available knowledge in biology to reduce the uncertainty in the modeling process. Therefore it is desirable to develop a method that can seamlessly integrate existing biological knowledge and high-throughput data into the process of discovering miRNA regulation mechanisms.In this article we present an integrative framework, CIDER (Causal miRNA target Discovery with Expression profile and Regulatory knowledge, to predict miRNA targets. CIDER is able to utilise a variety of gene regulation knowledge, including transcriptional and post-transcriptional knowledge, and to exploit gene expression data for the discovery of miRNA-mRNA regulatory relationships. The benefits of our framework is demonstrated by both simulation study and the analysis of the epithelial-to-mesenchymal transition (EMT and the breast cancer (BRCA datasets. Our results reveal that even a limited amount of either Transcription Factor (TF-miRNA or miRNA-mRNA regulatory knowledge improves the performance of miRNA target prediction, and the combination of the two types of knowledge enhances the improvement further. Another useful property of the framework is that its performance increases monotonically with the increase of regulatory knowledge.

  9. Evolution of gene regulatory network architectures: examples of subcircuit conservation and plasticity between classes of echinoderms.

    Science.gov (United States)

    Hinman, Veronica F; Yankura, Kristen A; McCauley, Brenna S

    2009-04-01

    Developmental gene regulatory networks (GRNs) explain how regulatory states are established in particular cells during development and how these states then determine the final form of the embryo. Evolutionary changes to the sequence of the genome will direct reorganization of GRN architectures, which in turn will lead to the alteration of developmental programs. A comparison of GRN architectures must consequently reveal the molecular basis for the evolution of developmental programs among different organisms. This review highlights some of the important findings that have emerged from the most extensive direct comparison of GRN architectures to date. Comparison of the orthologous GRNs for endomesodermal specification in the sea urchin and sea star, provides examples of several discrete, functional GRN subcircuits and shows that they are subject to diverse selective pressures. This demonstrates that different regulatory linkages may be more or less amenable to evolutionary change. One of the more surprising findings from this comparison is that GRN-level functions may be maintained while the factors performing the functions have changed, suggesting that GRNs have a high capacity for compensatory changes involving transcription factor binding to cis regulatory modules.

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

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    Katherine M. Buckley

    2017-10-01

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

  11. Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors.

    Science.gov (United States)

    Kemmeren, Patrick; Sameith, Katrin; van de Pasch, Loes A L; Benschop, Joris J; Lenstra, Tineke L; Margaritis, Thanasis; O'Duibhir, Eoghan; Apweiler, Eva; van Wageningen, Sake; Ko, Cheuk W; van Heesch, Sebastiaan; Kashani, Mehdi M; Ampatziadis-Michailidis, Giannis; Brok, Mariel O; Brabers, Nathalie A C H; Miles, Anthony J; Bouwmeester, Diane; van Hooff, Sander R; van Bakel, Harm; Sluiters, Erik; Bakker, Linda V; Snel, Berend; Lijnzaad, Philip; van Leenen, Dik; Groot Koerkamp, Marian J A; Holstege, Frank C P

    2014-04-24

    To understand regulatory systems, it would be useful to uniformly determine how different components contribute to the expression of all other genes. We therefore monitored mRNA expression genome-wide, for individual deletions of one-quarter of yeast genes, focusing on (putative) regulators. The resulting genetic perturbation signatures reflect many different properties. These include the architecture of protein complexes and pathways, identification of expression changes compatible with viability, and the varying responsiveness to genetic perturbation. The data are assembled into a genetic perturbation network that shows different connectivities for different classes of regulators. Four feed-forward loop (FFL) types are overrepresented, including incoherent type 2 FFLs that likely represent feedback. Systematic transcription factor classification shows a surprisingly high abundance of gene-specific repressors, suggesting that yeast chromatin is not as generally restrictive to transcription as is often assumed. The data set is useful for studying individual genes and for discovering properties of an entire regulatory system. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. 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.

  13. A stele-enriched gene regulatory network in the Arabidopsis root.

    Science.gov (United States)

    Brady, Siobhan M; Zhang, Lifang; Megraw, Molly; Martinez, Natalia J; Jiang, Eric; Yi, Charles S; Liu, Weilin; Zeng, Anna; Taylor-Teeples, Mallorie; Kim, Dahae; Ahnert, Sebastian; Ohler, Uwe; Ware, Doreen; Walhout, Albertha J M; Benfey, Philip N

    2011-01-18

    Tightly controlled gene expression is a hallmark of multicellular development and is accomplished by transcription factors (TFs) and microRNAs (miRNAs). Although many studies have focused on identifying downstream targets of these molecules, less is known about the factors that regulate their differential expression. We used data from high spatial resolution gene expression experiments and yeast one-hybrid (Y1H) and two-hybrid (Y2H) assays to delineate a subset of interactions occurring within a gene regulatory network (GRN) that determines tissue-specific TF and miRNA expression in plants. We find that upstream TFs are expressed in more diverse cell types than their targets and that promoters that are bound by a relatively large number of TFs correspond to key developmental regulators. The regulatory consequence of many TFs for their target was experimentally determined using genetic analysis. Remarkably, molecular phenotypes were identified for 65% of the TFs, but morphological phenotypes were associated with only 16%. This indicates that the GRN is robust, and that gene expression changes may be canalized or buffered.

  14. Regulatory T Cells and Immune Tolerance to Coagulation Factor IX in the Context of Intramuscular AAV1 Gene Transfer

    OpenAIRE

    Kelly, Meagan; Bharadwaj, Arpita S.; Tacke, Frank; Chao, Hengjun

    2009-01-01

    Regulatory T cells play a major role in induction and maintenance of immune tolerance and immunological homeostasis. A variety of strategies have been attempted to induce regulatory T cells for control of unwanted, adverse immunity in autoimmune diseases, transplantation as well as gene transfer. We recently reported efficient induction of immune tolerance to coagulation factor IX (FIX) following intramuscular AAV1 gene transfer. In the current study, we performed a systematic and comprehensi...

  15. 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.

  16. Dynamic and distinct histone modifications modulate the expression of key adipogenesis regulatory genes.

    Science.gov (United States)

    Zhang, Qiongyi; Ramlee, Muhammad Khairul; Brunmeir, Reinhard; Villanueva, Claudio J; Halperin, Daniel; Xu, Feng

    2012-12-01

    Histone modifications and their modifying enzymes are fundamentally involved in the epigenetic regulation of adipogenesis. This study aimed to define the roles of various histone modifications and their "division of labor" in fat cell differentiation. To achieve these goals, we examined the distribution patterns of eight core histone modifications at five key adipogenic regulatory genes, Pref-1, C/EBPβ, C/EBPα, PPARγ2 and aP2, during the adipogenesis of C3H 10T1/2 mouse mesenchymal stem cells (MSCs) and 3T3-L1 preadipocytes. We found that the examined histone modifications are globally stable throughout adipogenesis but show distinct and highly dynamic distribution patterns at specific genes. For example, the Pref-1 gene has lower levels of active chromatin markers and significantly higher H3 K27 tri-methylation in MSCs compared with committed preadipocytes; the C/EBPβ gene is enriched in active chromatin markers at its 3'-UTR; the C/EBPα gene is predominantly marked by H3 K27 tri-methylation in adipogenic precursor cells, and this repressive marker decreases dramatically upon induction; the PPARγ2 and aP2 genes show increased histone acetylation on both H3 and H4 tails during adipogenesis. Further functional studies revealed that the decreased level of H3 K27 tri-methylation leads to de-repression of Pref-1 gene, while the increased level of histone acetylation activates the transcription of PPARγ2 and aP2 genes. Moreover, the active histone modification-marked 3'-UTR of C/EBPβ gene was demonstrated as a strong enhancer element by luciferase assay. Our results indicate that histone modifications are gene-specific at adipogenic regulator genes, and they play distinct roles in regulating the transcriptional network during adipogenesis.

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

    Science.gov (United States)

    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.

  18. Regulatory regions of SERPINC1 gene: identification of the first mutation associated with antithrombin deficiency.

    Science.gov (United States)

    de la Morena-Barrio, María Eugenia; Antón, Ana Isabel; Martínez-Martínez, Irene; Padilla, José; Miñano, Antonia; Navarro-Fernández, José; Águila, Sonia; López, María Fernanda; Fontcuberta, Jordi; Vicente, Vicente; Corral, Javier

    2012-03-01

    Antithrombin is the main endogenous anticoagulant. Impaired function or deficiency of this molecule significantly increases the risk of thrombosis. We studied the genetic variability of SERPINC1 , the gene encoding antithrombin, to identify mutations affecting regulatory regions with functional effect on its levels. We sequenced 15,375 bp of this gene, including the potential promoter region, in three groups of subjects: five healthy subjects with antithrombin levels in the lowest (75%) and highest (115%) ranges of our population, 14 patients with venous thrombosis and a moderate antithrombin deficiency as the single thrombophilic defect, and two families with type I antithrombin deficiency who had neither mutations affecting exons or flanking regions, nor gross gene deletions. Our study confirmed the low genetic variability of SERPINC1 , particularly in the coding region, and its minor influence in the heterogeneity of antithrombin levels. Interestingly, in one family, we identified a g.2143 C>G transversion, located 170 bp upstream from the translation initiation codon. This mutation affected one of the four regions located in the minimal promoter that have potential regulatory activity according to previous DNase footprinting protection assays. Genotype-phenotype analysis in the affected family and reporter analysis in different hepatic cell lines demonstrated that this mutation significantly impaired, although it did not abolish, the downstream transcription. Therefore, this is the first mutation affecting a regulatory region of the SERPINC1 gene associated with antithrombin deficiency. Our results strongly sustain the inclusion of the promoter region of SERPINC1 in the molecular analysis of patients with antithrombin deficiency.

  19. RNA sequencing identifies gene regulatory networks controlling extracellular matrix synthesis in intervertebral disk tissues.

    Science.gov (United States)

    Riester, Scott M; Lin, Yang; Wang, Wei; Cong, Lin; Mohamed Ali, Abdel-Moneim; Peck, Sun H; Smith, Lachlan J; Currier, Bradford L; Clark, Michelle; Huddleston, Paul; Krauss, William; Yaszemski, Michael J; Morrey, Mark E; Abdel, Matthew P; Bydon, Mohamad; Qu, Wenchun; Larson, Annalise N; van Wijnen, Andre J; Nassr, Ahmad

    2017-12-11

    Degenerative disk disease of the spine is a major cause of back pain and disability. Optimization of regenerative medical therapies for degenerative disk disease requires a deep mechanistic understanding of the factors controlling the structural integrity of spinal tissues. In this investigation, we sought to identify candidate regulatory genes controlling extracellular matrix synthesis in spinal tissues. To achieve this goal we performed high throughput next generation RNA sequencing on 39 annulus fibrosus and 21 nucleus pulposus human tissue samples. Specimens were collected from patients undergoing surgical discectomy for the treatment of degenerative disk disease. Our studies identified associations between extracellular matrix genes, growth factors, and other important regulatory molecules. The fibrous matrix characteristic of annulus fibrosus was associated with expression of the growth factors platelet derived growth factor beta (PDGFB), vascular endothelial growth factor C (VEGFC), and fibroblast growth factor 9 (FGF9). Additionally we observed high expression of multiple signaling proteins involved in the NOTCH and WNT signaling cascades. Nucleus pulposus extracellular matrix related genes were associated with the expression of numerous diffusible growth factors largely associated with the transforming growth signaling cascade, including transforming factor alpha (TGFA), inhibin alpha (INHA), inhibin beta A (INHBA), bone morphogenetic proteins (BMP2, BMP6), and others. this investigation provides important data on extracellular matrix gene regulatory networks in disk tissues. This information can be used to optimize pharmacologic, stem cell, and tissue engineering strategies for regeneration of the intervertebral disk and the treatment of back pain. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

  20. 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

  1. Gene Regulatory Enhancers with Evolutionarily Conserved Activity Are More Pleiotropic than Those with Species-Specific Activity.

    Science.gov (United States)

    Fish, Alexandra; Chen, Ling; Capra, John A

    2017-10-01

    Studies of regulatory activity and gene expression have revealed an intriguing dichotomy: There is substantial turnover in the regulatory activity of orthologous sequences between species; however, the expression level of orthologous genes is largely conserved. Understanding how distal regulatory elements, for example, enhancers, evolve and function is critical, as alterations in gene expression levels can drive the development of both complex disease and functional divergence between species. In this study, we investigated determinants of the conservation of regulatory enhancer activity for orthologous sequences across mammalian evolution. Using liver enhancers identified from genome-wide histone modification profiles in ten diverse mammalian species, we compared orthologous sequences that exhibited regulatory activity in all species (conserved-activity enhancers) to shared sequences active only in a single species (species-specific-activity enhancers). Conserved-activity enhancers have greater regulatory potential than species-specific-activity enhancers, as quantified by both the density and diversity of transcription factor binding motifs. Consistent with their greater regulatory potential, conserved-activity enhancers have greater regulatory activity in humans than species-specific-activity enhancers: They are active across more cellular contexts, and they regulate more genes than species-specific-activity enhancers. Furthermore, the genes regulated by conserved-activity enhancers are expressed in more tissues and are less tolerant of loss-of-function mutations than those targeted by species-specific-activity enhancers. These consistent results across various stages of gene regulation demonstrate that conserved-activity enhancers are more pleiotropic than their species-specific-activity counterparts. This suggests that pleiotropy is associated with the conservation of regulatory across mammalian evolution. © The Author 2017. Published by Oxford University

  2. Comparative genomics and evolution of eukaryotic phospholipidbiosynthesis

    Energy Technology Data Exchange (ETDEWEB)

    Lykidis, Athanasios

    2006-12-01

    Phospholipid biosynthetic enzymes produce diverse molecular structures and are often present in multiple forms encoded by different genes. This work utilizes comparative genomics and phylogenetics for exploring the distribution, structure and evolution of phospholipid biosynthetic genes and pathways in 26 eukaryotic genomes. Although the basic structure of the pathways was formed early in eukaryotic evolution, the emerging picture indicates that individual enzyme families followed unique evolutionary courses. For example, choline and ethanolamine kinases and cytidylyltransferases emerged in ancestral eukaryotes, whereas, multiple forms of the corresponding phosphatidyltransferases evolved mainly in a lineage specific manner. Furthermore, several unicellular eukaryotes maintain bacterial-type enzymes and reactions for the synthesis of phosphatidylglycerol and cardiolipin. Also, base-exchange phosphatidylserine synthases are widespread and ancestral enzymes. The multiplicity of phospholipid biosynthetic enzymes has been largely generated by gene expansion in a lineage specific manner. Thus, these observations suggest that phospholipid biosynthesis has been an actively evolving system. Finally, comparative genomic analysis indicates the existence of novel phosphatidyltransferases and provides a candidate for the uncharacterized eukaryotic phosphatidylglycerol phosphate phosphatase.

  3. Self-regulatory gene: An exact solution for the gene gate model

    Science.gov (United States)

    Vandecan, Yves; Blossey, Ralf

    2013-04-01

    The stochastic dynamics of gene expression is often described by highly abstract models involving only the key molecular actors DNA, RNA, and protein, neglecting all further details of the transcription and translation processes. One example of such models is the “gene gate model,” which contains a minimal set of actors and kinetic parameters, which allows us to describe the regulation of a gene by both repression and activation. Based on this approach, we formulate a master equation for the case of a single gene regulated by its own product—a transcription factor—and solve it exactly. The obtained gene product distributions display features of mono- and bimodality, depending on the choice of parameters. We discuss our model in the perspective of other models in the literature.

  4. Inferring gene regulatory networks by integrating ChIP-seq/chip and transcriptome data via LASSO-type regularization methods.

    Science.gov (United States)

    Qin, Jing; Hu, Yaohua; Xu, Feng; Yalamanchili, Hari Krishna; Wang, Junwen

    2014-06-01

    Inferring gene regulatory networks from gene expression data at whole genome level is still an arduous challenge, especially in higher organisms where the number of genes is large but the number of experimental samples is small. It is reported that the accuracy of current methods at genome scale significantly drops from Escherichia coli to Saccharomyces cerevisiae due to the increase in number of genes. This limits the applicability of current methods to more complex genomes, like human and mouse. Least absolute shrinkage and selection operator (LASSO) is widely used for gene regulatory network inference from gene expression profiles. However, the accuracy of LASSO on large genomes is not satisfactory. In this study, we apply two extended models of LASSO, L0 and L1/2 regularization models to infer gene regulatory network from both high-throughput gene expression data and transcription factor binding data in mouse embryonic stem cells (mESCs). We find that both the L0 and L1/2 regularization models significantly outperform LASSO in network inference. Incorporating interactions between transcription factors and their targets remarkably improved the prediction accuracy. Current study demonstrates the efficiency and applicability of these two models for gene regulatory network inference from integrative omics data in large genomes. The applications of the two models will facilitate biologists to study the gene regulation of higher model organisms in a genome-wide scale. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. Omics approaches to study gene regulatory networks for development in echinoderms.

    Science.gov (United States)

    Lowe, Elijah K; Cuomo, Claudia; Arnone, Maria I

    2017-09-01

    Gene regulatory networks (GRNs) describe the interactions for a developmental process at a given time and space. Historically, perturbation experiments represent one of the key methods for analyzing and reconstructing a GRN, and the GRN governing early development in the sea urchin embryo stands as one of the more deeply dissected so far. As technology progresses, so do the methods used to address different biological questions. Next-generation sequencing (NGS) has become a standard experimental technique for genome and transcriptome sequencing and studies of protein-DNA interactions and DNA accessibility. While several efforts have been made toward the integration of different omics approaches for the study of the regulatory genome in many animals, in a few cases, these are applied with the purpose of reconstructing and experimentally testing developmental GRNs. Here, we review emerging approaches integrating multiple NGS technologies for the prediction and validation of gene interactions within echinoderm GRNs. These approaches can be applied to both 'model' and 'non-model' organisms. Although a number of issues still need to be addressed, advances in NGS applications, such as assay for transposase-accessible chromatin sequencing, combined with the availability of embryos belonging to different species, all separated by various evolutionary distances and accessible to experimental regulatory biology, place echinoderms in an unprecedented position for the reconstruction and evolutionary comparison of developmental GRNs. We conclude that sequencing technologies and integrated omics approaches allow the examination of GRNs on a genome-wide scale only if biological perturbation and cis-regulatory analyses are experimentally accessible, as in the case of echinoderm embryos. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  6. Sequence tolerance of the phage lambda PRM promoter: implications for evolution of gene regulatory circuitry.

    Science.gov (United States)

    Michalowski, Christine B; Short, Megan D; Little, John W

    2004-12-01

    Much of the gene regulatory circuitry of phage lambda centers on a complex region called the O(R) region. This approximately 100-bp region is densely packed with regulatory sites, including two promoters and three repressor-binding sites. The dense packing of this region is likely to impose severe constraints on its ability to change during evolution, raising the question of how the specific arrangement of sites and their exact sequences could evolve to their present form. Here we ask whether the sequence of a cis-acting site can be widely varied while retaining its function; if it can, evolution could proceed by a larger number of paths. To help address this question, we developed a lambda cloning vector that allowed us to clone fragments spanning the O(R) region. By using this vector, we carried out intensive mutagenesis of the P(RM) promoter, which drives expression of CI repressor and is activated by CI itself. We made a pool of fragments in which 8 of the 12 positions in the -35 and -10 regions were randomized and cloned this pool into the vector, making a pool of P(RM) variant phage. About 10% of the P(RM) variants were able to lysogenize, suggesting that the lambda regulatory circuitry is compatible with a wide range of P(RM) sequences. Analysis of several of these phages indicated a range of behaviors in prophage induction. Several isolates had induction properties similar to those of the wild type, and their promoters resembled the wild type in their responses to CI. We term this property of different sequences allowing roughly equivalent function "sequence tolerance " and discuss its role in the evolution of gene regulatory circuitry.

  7. Regulatory T cells and immune tolerance to coagulation factor IX in the context of intramuscular AAV1 gene transfer.

    Science.gov (United States)

    Kelly, Meagan; Bharadwaj, Arpita S; Tacke, Frank; Chao, Hengjun

    2010-02-01

    Regulatory T cells play a major role in induction and maintenance of immune tolerance and immunological homeostasis. A variety of strategies have been attempted to induce regulatory T cells for control of unwanted, adverse immunity in autoimmune diseases, transplantation as well as gene transfer. We recently reported efficient induction of immune tolerance to coagulation factor IX (FIX) following intramuscular AAV1 gene transfer. In the current study, we performed a systematic and comprehensive examination of the role and function of regulatory T cells in induction and maintenance of FIX tolerance in the context of intramuscular AAV1 gene transfer. We observed no significant upregulation of regulatory T cells in the FIX-tolerant mice. In addition, adoptive transfer of splenocytes from FIX-tolerant mice did not suppress anti-hFIX immunity in recipient mice. Both in vitro and in vivo depletion of regulatory T cells failed to reverse FIX tolerance. These observations revealed that regulatory T cells do not play a significant role in the maintenance/protection of the established FIX tolerance. Our results provide critical insight into the role and function of regulatory T cells in induction and maintenance/protection of immune tolerance in gene transfer, complementing the current paradigm of immune tolerance mechanism.

  8. Transfer of DNA from Bacteria to Eukaryotes

    Directory of Open Access Journals (Sweden)

    Benoît Lacroix

    2016-07-01

    Full Text Available Historically, the members of the Agrobacterium genus have been considered the only bacterial species naturally able to transfer and integrate DNA into the genomes of their eukaryotic hosts. Yet, increasing evidence suggests that this ability to genetically transform eukaryotic host cells might be more widespread in the bacterial world. Indeed, analyses of accumulating genomic data reveal cases of horizontal gene transfer from bacteria to eukaryotes and suggest that it represents a significant force in adaptive evolution of eukaryotic species. Specifically, recent reports indicate that bacteria other than Agrobacterium, such as Bartonella henselae (a zoonotic pathogen, Rhizobium etli (a plant-symbiotic bacterium related to Agrobacterium, or even Escherichia coli, have the ability to genetically transform their host cells under laboratory conditions. This DNA transfer relies on type IV secretion systems (T4SSs, the molecular machines that transport macromolecules during conjugative plasmid transfer and also during transport of proteins and/or DNA to the eukaryotic recipient cells. In this review article, we explore the extent of possible transfer of genetic information from bacteria to eukaryotic cells as well as the evolutionary implications and potential applications of this transfer.

  9. Shaping skeletal growth by modular regulatory elements in the Bmp5 gene.

    Directory of Open Access Journals (Sweden)

    Catherine Guenther

    2008-12-01

    Full Text Available Cartilage and bone are formed into a remarkable range of shapes and sizes that underlie many anatomical adaptations to different lifestyles in vertebrates. Although the morphological blueprints for individual cartilage and bony structures must somehow be encoded in the genome, we currently know little about the detailed genomic mechanisms that direct precise growth patterns for particular bones. We have carried out large-scale enhancer surveys to identify the regulatory architecture controlling developmental expression of the mouse Bmp5 gene, which encodes a secreted signaling molecule required for normal morphology of specific skeletal features. Although Bmp5 is expressed in many skeletal precursors, different enhancers control expression in individual bones. Remarkably, we show here that different enhancers also exist for highly restricted spatial subdomains along the surface of individual skeletal structures, including ribs and nasal cartilages. Transgenic, null, and regulatory mutations confirm that these anatomy-specific sequences are sufficient to trigger local changes in skeletal morphology and are required for establishing normal growth rates on separate bone surfaces. Our findings suggest that individual bones are composite structures whose detailed growth patterns are built from many smaller lineage and gene expression domains. Individual enhancers in BMP genes provide a genomic mechanism for controlling precise growth domains in particular cartilages and bones, making it possible to separately regulate skeletal anatomy at highly specific locations in the body.

  10. Bivalent Chromatin Marks Developmental Regulatory Genes in the Mouse Embryonic Germline In Vivo

    Directory of Open Access Journals (Sweden)

    Michael Sachs

    2013-06-01

    Full Text Available Developmental regulatory genes have both activating (H3K4me3 and repressive (H3K27me3 histone modifications in embryonic stem cells (ESCs. This bivalent configuration is thought to maintain lineage commitment programs in a poised state. However, establishing physiological relevance has been complicated by the high number of cells required for chromatin immunoprecipitation (ChIP. We developed a low-cell-number chromatin immunoprecipitation (low-cell ChIP protocol to investigate the chromatin of mouse primordial germ cells (PGCs. Genome-wide analysis of embryonic day 11.5 (E11.5 PGCs revealed H3K4me3/H3K27me3 bivalent domains highly enriched at developmental regulatory genes in a manner remarkably similar to ESCs. Developmental regulators remain bivalent and transcriptionally silent through the initiation of sexual differentiation at E13.5. We also identified >2,500 “orphan” bivalent domains that are distal to known genes and expressed in a tissue-specific manner but silent in PGCs. Our results demonstrate the existence of bivalent domains in the germline and raise the possibility that the somatic program is continuously maintained as bivalent, potentially imparting transgenerational epigenetic inheritance.

  11. Understanding Epistatic Interactions between Genes Targeted by Non-coding Regulatory Elements in Complex Diseases

    Directory of Open Access Journals (Sweden)

    Min Kyung Sung

    2014-12-01

    Full Text Available Genome-wide association studies have proven the highly polygenic architecture of complex diseases or traits; therefore, single-locus-based methods are usually unable to detect all involved loci, especially when individual loci exert small effects. Moreover, the majority of associated single-nucleotide polymorphisms resides in non-coding regions, making it difficult to understand their phenotypic contribution. In this work, we studied epistatic interactions associated with three common diseases using Korea Association Resource (KARE data: type 2 diabetes mellitus (DM, hypertension (HT, and coronary artery disease (CAD. We showed that epistatic single-nucleotide polymorphisms (SNPs were enriched in enhancers, as well as in DNase I footprints (the Encyclopedia of DNA Elements [ENCODE] Project Consortium 2012, which suggested that the disruption of the regulatory regions where transcription factors bind may be involved in the disease mechanism. Accordingly, to identify the genes affected by the SNPs, we employed whole-genome multiple-cell-type enhancer data which discovered using DNase I profiles and Cap Analysis Gene Expression (CAGE. Assigned genes were significantly enriched in known disease associated gene sets, which were explored based on the literature, suggesting that this approach is useful for detecting relevant affected genes. In our knowledge-based epistatic network, the three diseases share many associated genes and are also closely related with each other through many epistatic interactions. These findings elucidate the genetic basis of the close relationship between DM, HT, and CAD.

  12. Modeling the cis-regulatory modules of genes expressed in developmental stages of Drosophila melanogaster.

    Science.gov (United States)

    López, Yosvany; Vandenbon, Alexis; Nose, Akinao; Nakai, Kenta

    2017-01-01

    Because transcription is the first step in the regulation of gene expression, understanding how transcription factors bind to their DNA binding motifs has become absolutely necessary. It has been shown that the promoters of genes with similar expression profiles share common structural patterns. This paper presents an extensive study of the regulatory regions of genes expressed in 24 developmental stages of Drosophila melanogaster. It proposes the use of a combination of structural features, such as positioning of individual motifs relative to the transcription start site, orientation, pairwise distance between motifs, and presence of motifs anywhere in the promoter for predicting gene expression from structural features of promoter sequences. RNA-sequencing data was utilized to create and validate the 24 models. When genes with high-scoring promoters were compared to those identified by RNA-seq samples, 19 (79.2%) statistically significant models, a number that exceeds previous studies, were obtained. Each model yielded a set of highly informative features, which were used to search for genes with similar biological functions.

  13. A novel regulatory element between the human FGA and FGG genes.

    Science.gov (United States)

    Fish, Richard J; Neerman-Arbez, Marguerite

    2012-09-01

    High circulating fibrinogen levels correlate with cardiovascular disease (CVD) risk. Fibrinogen levels vary between people and also change in response to physiological and environmental stimuli. A modest proportion of the variation in fibrinogen levels can be explained by genotype, inferring that variation in genomic sequences that regulate the fibrinogen genes ( FGA , FGB and FGG ) may affect hepatic fibrinogen production and perhaps CVD risk. We previously identified a conserved liver enhancer in the fibrinogen gene cluster (CNC12), between FGB and FGA . Genome-wide Chromatin immunoprecipitation-sequencing (ChIP-seq) demonstrated that transcription factors which bind fibrinogen gene promoters also interact with CNC12, as well as two potential fibrinogen enhancers (PFE), between FGA and FGG . Here we show that one of the PFE sequences has potent hepatocyte enhancer activity. Using a luciferase reporter gene system, we found that PFE2 enhances minimal promoter- and FGA promoter-driven gene expression in hepatoma cells, regardless of its orientation with respect to the promoters. A region within PFE2 bears a short series of conserved nucleotides which maintain enhancer activity without flanking sequence. We also demonstrate that PFE2 is a liver enhancer in vivo, driving enhanced green fluorescent protein expression in transgenic zebrafish larval livers. Our study shows that combining public domain ChIP-seq data with in vitro and in vivo functional tests can identify novel fibrinogen gene cluster regulatory sequences. Variation in such elements could affect fibrinogen production and influence CVD risk.

  14. Novel insights into the regulatory roles of gene hshB in Xanthomonas oryzae pv. oryzicola.

    Science.gov (United States)

    Song, Zhiwei; Zhao, Yancun; Qian, Guoliang; Odhiambo, Benard Omondi; Liu, Fengquan

    Xanthomonas oryzae pv. oryzicola causes leaf streak disease of rice. The gene hshB is a newly identified virulence-associated gene that is co-regulated by diffusible signal factor signaling and global regulator Clp in X. oryzae pv. oryzicola. Our previous study showed that mutation of hshB remarkably impaired the virulence, extracellular protease activity, extracellular polysaccharide production and resistance to oxidative stress of X. oryzae pv. oryzicola. In this study, the regulatory role of hshB in X. oryzae pv .oryzicola was expanded. Results showed that hshB was also required for cell swimming motility. Transcriptome analysis showed that 305 genes were significantly differentially expressed after deletion of hshB in X. oryzae pv. oryzicola. Further analysis of transcriptome data indicated that the differentially expressed genes focused on two aspects: namely, cell motility and cell signal transduction. This finding strongly identified the closely related function of hshB to cell motility and signal transduction. In addition, the mutation of hshB of X. oryzae pv. oryzicola enhanced biofilm formation. Collectively, the study showed novel functions of gene hshB in cell motility and biofilm formation by transcriptome analysis, thus expanding our understanding of the roles of gene hshB in the pathogenic X. oryzae pv. oryzicola. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  15. Refining ensembles of predicted gene regulatory networks based on characteristic interaction sets.

    Directory of Open Access Journals (Sweden)

    Lukas Windhager

    Full Text Available Different ensemble voting approaches have been successfully applied for reverse-engineering of gene regulatory networks. They are based on the assumption that a good approximation of true network structure can be derived by considering the frequencies of individual interactions in a large number of predicted networks. Such approximations are typically superior in terms of prediction quality and robustness as compared to considering a single best scoring network only. Nevertheless, ensemble approaches only work well if the predicted gene regulatory networks are sufficiently similar to each other. If the topologies of predicted networks are considerably different, an ensemble of all networks obscures interesting individual characteristics. Instead, networks should be grouped according to local topological similarities and ensemble voting performed for each group separately. We argue that the presence of sets of co-occurring interactions is a suitable indicator for grouping predicted networks. A stepwise bottom-up procedure is proposed, where first mutual dependencies between pairs of interactions are derived from predicted networks. Pairs of co-occurring interactions are subsequently extended to derive characteristic interaction sets that distinguish groups of networks. Finally, ensemble voting is applied separately to the resulting topologically similar groups of networks to create distinct group-ensembles. Ensembles of topologically similar networks constitute distinct hypotheses about the reference network structure. Such group-ensembles are easier to interpret as their characteristic topology becomes clear and dependencies between interactions are known. The availability of distinct hypotheses facilitates the design of further experiments to distinguish between plausible network structures. The proposed procedure is a reasonable refinement step for non-deterministic reverse-engineering applications that produce a large number of candidate

  16. Sox10 controls migration of B16F10 melanoma cells through multiple regulatory target genes.

    Directory of Open Access Journals (Sweden)

    Ikjoo Seong

    Full Text Available It is believed that the inherent differentiation program of melanocytes during embryogenesis predisposes melanoma cells to high frequency of metastasis. Sox10, a transcription factor expressed in neural crest stem cells and a subset of progeny lineages, plays a key role in the development of melanocytes. We show that B16F10 melanoma cells transfected with siRNAs specific for Sox10 display reduced migratory activity which in turn indicated that a subset of transcriptional regulatory target genes of Sox10 is likely to be involved in migration and metastasis of melanoma cells. We carried out a microarray-based gene expression profiling using a Sox10-specific siRNA to identify relevant regulatory targets and found that multiple genes including melanocortin-1 receptor (Mc1r partake in the regulation of migration. We provide evidences that the effect of Sox10 on migration is mediated in large part by Mitf, a transcription factor downstream to Sox10. Among the mouse melanoma cell lines examined, however, only B16F10 showed robust down-regulation of Sox10 and inhibition of cell migration indicating that further dissection of dosage effects and/or cell line-specific regulatory networks is necessary. The involvement of Mc1r in migration was studied in detail in vivo using a murine metastasis model. Specifically, B16F10 melanoma cells treated with a specific siRNA showed reduced tendency in metastasizing to and colonizing the lung after being injected in the tail vein. These data reveal a cadre of novel regulators and mediators involved in migration and metastasis of melanoma cells that represents potential targets of therapeutic intervention.

  17. Refining Ensembles of Predicted Gene Regulatory Networks Based on Characteristic Interaction Sets

    Science.gov (United States)

    Windhager, Lukas; Zierer, Jonas; Küffner, Robert

    2014-01-01

    Different ensemble voting approaches have been successfully applied for reverse-engineering of gene regulatory networks. They are based on the assumption that a good approximation of true network structure can be derived by considering the frequencies of individual interactions in a large number of predicted networks. Such approximations are typically superior in terms of prediction quality and robustness as compared to considering a single best scoring network only. Nevertheless, ensemble approaches only work well if the predicted gene regulatory networks are sufficiently similar to each other. If the topologies of predicted networks are considerably different, an ensemble of all networks obscures interesting individual characteristics. Instead, networks should be grouped according to local topological similarities and ensemble voting performed for each group separately. We argue that the presence of sets of co-occurring interactions is a suitable indicator for grouping predicted networks. A stepwise bottom-up procedure is proposed, where first mutual dependencies between pairs of interactions are derived from predicted networks. Pairs of co-occurring interactions are subsequently extended to derive characteristic interaction sets that distinguish groups of networks. Finally, ensemble voting is applied separately to the resulting topologically similar groups of networks to create distinct group-ensembles. Ensembles of topologically similar networks constitute distinct hypotheses about the reference network structure. Such group-ensembles are easier to interpret as their characteristic topology becomes clear and dependencies between interactions are known. The availability of distinct hypotheses facilitates the design of further experiments to distinguish between plausible network structures. The proposed procedure is a reasonable refinement step for non-deterministic reverse-engineering applications that produce a large number of candidate predictions for a gene

  18. PreCisIon: PREdiction of CIS-regulatory elements improved by gene's positION.

    Science.gov (United States)

    Elati, Mohamed; Nicolle, Rémy; Junier, Ivan; Fernández, David; Fekih, Rim; Font, Julio; Képès, François

    2013-02-01

    Conventional approaches to predict transcriptional regulatory interactions usually rely on the definition of a shared motif sequence on the target genes of a transcription factor (TF). These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices, which may match large numbers of sites and produce an unreliable list of target genes. To improve the prediction of binding sites, we propose to additionally use the unrelated knowledge of the genome layout. Indeed, it has been shown that co-regulated genes tend to be either neighbors or periodically spaced along the whole chromosome. This study demonstrates that respective gene positioning carries significant information. This novel type of information is combined with traditional sequence information by a machine learning algorithm called PreCisIon. To optimize this combination, PreCisIon builds a strong gene target classifier by adaptively combining weak classifiers based on either local binding sequence or global gene position. This strategy generically paves the way to the optimized incorporation of any future advances in gene target prediction based on local sequence, genome layout or on novel criteria. With the current state of the art, PreCisIon consistently improves methods based on sequence information only. This is shown by implementing a cross-validation analysis of the 20 major TFs from two phylogenetically remote model organisms. For Bacillus subtilis and Escherichia coli, respectively, PreCisIon achieves on average an area under the receiver operating characteristic curve of 70 and 60%, a sensitivity of 80 and 70% and a specificity of 60 and 56%. The newly predicted gene targets are demonstrated to be functionally consistent with previously known targets, as assessed by analysis of Gene Ontology enrichment or of the relevant literature and databases.

  19. Small RNA-Controlled Gene Regulatory Networks in Pseudomonas putida

    DEFF Research Database (Denmark)

    Bojanovic, Klara

    . 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...... such as sRNAs and riboswitches. Further, the sRNAome during the growth of bacteria was investigatedand compared to the strain without Hfq protein. Hfq has a big impact on sRNAs and gene expression in P. putida, hence many Hfq-associated sRNAs and mRNAs were found. Together, the results reported here...

  20. 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 results show good performance compared to previous results achieved using learning methods. Furthermore, some experiments are performed to investigate evolvability of the achieved solutions in the case of module failure and it is shown that the system is capable of come up with new effective solutions....

  1. Extreme Learning Machines for reverse engineering of gene regulatory networks from expression time series.

    Science.gov (United States)

    Rubiolo, M; Milone, D H; Stegmayer, G

    2017-11-22

    The reconstruction of gene regulatory networks (GRNs) from genes profiles has a growing interest in bioinformatics for understanding the complex regulatory mechanisms in cellular systems. GRNs explicitly represent the cause-effect of regulation among a group of genes and its reconstruction is today a challenging computational problem. Several methods were proposed, but most of them require different input sources to provide an acceptable prediction. Thus, it is a great challenge to reconstruct a GRN only from temporal gene-expression data. Extreme Learning Machine (ELM) is a new supervised neural model that has gained interest in the last years because of its higher learning rate and better performance than existing supervised models in terms of predictive power. This work proposes a novel approach for GRNs reconstruction in which ELMs are used for modeling the relationships between gene expression time series. Artificial datasets generated with the well-known benchmark tool used in DREAM competitions were used. Real datasets were used for validation of this novel proposal with well-known GRNs underlying the time series. The impact of increasing the size of GRNs was analyzed in detail for the compared methods. The results obtained confirm the superiority of the ELM approach against very recent state-of-the-art methods in the same experimental conditions. The webdemo can be found at http://sinc.unl.edu.ar/web-demo/elm-grnnminer/. The source code is available at: https://sourceforge.net/projects/sourcesinc/files/elm-grnnminer. mrubiolo@santafe-conicet.gov.ar. Supplementary materials are available at Bioinformatics online.

  2. Enriching regulatory networks by bootstrap learning using optimised GO-based gene similarity and gene links mined from PubMed abstracts

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C.; Sanfilippo, Antonio P.; McDermott, Jason E.; Baddeley, Robert L.; Riensche, Roderick M.; Jensen, Russell S.; Verhagen, Marc; Pustejovsky, James

    2011-02-18

    Transcriptional regulatory networks are being determined using “reverse engineering” methods that infer connections based on correlations in gene state. Corroboration of such networks through independent means such as evidence from the biomedical literature is desirable. Here, we explore a novel approach, a bootstrapping version of our previous Cross-Ontological Analytic method (XOA) that can be used for semi-automated annotation and verification of inferred regulatory connections, as well as for discovery of additional functional relationships between the genes. First, we use our annotation and network expansion method on a biological network learned entirely from the literature. We show how new relevant links between genes can be iteratively derived using a gene similarity measure based on the Gene Ontology that is optimized on the input network at each iteration. Second, we apply our method to annotation, verification, and expansion of a set of regulatory connections found by the Context Likelihood of Relatedness algorithm.

  3. Characterization of the proneural gene regulatory network during mouse telencephalon development

    Directory of Open Access Journals (Sweden)

    Parker Joel S

    2008-03-01

    Full Text Available Abstract Background The proneural proteins Mash1 and Ngn2 are key cell autonomous regulators of neurogenesis in the mammalian central nervous system, yet little is known about the molecular pathways regulated by these transcription factors. Results Here we identify the downstream effectors of proneural genes in the telencephalon using a genomic approach to analyze the transcriptome of mice that are either lacking or overexpressing proneural genes. Novel targets of Ngn2 and/or Mash1 were identified, such as members of the Notch and Wnt pathways, and proteins involved in adhesion and signal transduction. Next, we searched the non-coding sequence surrounding the predicted proneural downstream effector genes for evolutionarily conserved transcription factor binding sites associated with newly defined consensus binding sites for Ngn2 and Mash1. This allowed us to identify potential novel co-factors and co-regulators for proneural proteins, including Creb, Tcf/Lef, Pou-domain containing transcription factors, Sox9, and Mef2a. Finally, a gene regulatory network was delineated using a novel Bayesian-based algorithm that can incorporate information from diverse datasets. Conclusion Together, these data shed light on the molecular pathways regulated by proneural genes and demonstrate that the integration of experimentation with bioinformatics can guide both hypothesis testing and hypothesis generation.

  4. Foundations for modeling the dynamics of gene regulatory networks: a multilevel-perspective review.

    Science.gov (United States)

    Sanchez-Osorio, Ismael; Ramos, Fernando; Mayorga, Pedro; Dantan, Edgar

    2014-02-01

    A promising alternative for unraveling the principles under which the dynamic interactions among genes lead to cellular phenotypes relies on mathematical and computational models at different levels of abstraction, from the molecular level of protein-DNA interactions to the system level of functional relationships among genes. This review article presents, under a bottom-up perspective, a hierarchy of approaches to modeling gene regulatory network dynamics, from microscopic descriptions at the single-molecule level in the spatial context of an individual cell to macroscopic models providing phenomenological descriptions at the population-average level. The reviewed modeling approaches include Molecular Dynamics, Particle-Based Brownian Dynamics, the Master Equation approach, Ordinary Differential Equations, and the Boolean logic abstraction. Each of these frameworks is motivated by a particular biological context and the nature of the insight being pursued. The setting of gene network dynamic models from such frameworks involves assumptions and mathematical artifacts often ignored by the non-specialist. This article aims at providing an entry point for biologists new to the field and computer scientists not acquainted with some recent biophysically-inspired models of gene regulation. The connections promoting intuition between different abstraction levels and the role that approximations play in the modeling process are highlighted throughout the paper.

  5. Heterologous expression of the pneumococcal serotype 14 polysaccharide in Lactococcus lactis requires lactococcal epsABC regulatory genes

    NARCIS (Netherlands)

    Nierop Groot, M.N.; Godefrooij, J.; Kleerebezem, M.

    2008-01-01

    The pneumococcal serotype 14 polysaccharide was produced in Lactococcus lactis by coexpressing pneumococcal polysaccharide type 14-specific genes (cpsFGHIJKL(14)) with the lactococcal regulatory and priming glucosyltransferase-encoding genes specific for B40 polysaccharide (epsABCD(B40)). The

  6. Organ-specific activity of the 5' regulatory region of the glutamine synthetase gene in developing mice

    NARCIS (Netherlands)

    Lie-Venema, H.; de Boer, P. A.; Moorman, A. F.; Lamers, W. H.

    1997-01-01

    Glutamine synthetase (GS) converts ammonia and glutamate into glutamine. We assessed the activity of the 5' regulatory region of the GS gene in developing transgenic mice carrying the chloramphenicol acetyltransferase (CAT) gene under the control of 3150 bp of the upstream sequence of the rat GS

  7. Exploring the roles of basal transcription factor 3 in eukaryotic growth and development.

    Science.gov (United States)

    Jamil, Muhammad; Wang, Wenyi; Xu, Mengyun; Tu, Jumin

    2015-01-01

    Basal transcription factor 3 (BTF3) has been reported to play a significant part in the transcriptional regulation linking with eukaryotes growth and development. Alteration in the BTF3 gene expression patterns or variation in their activities adds to the explanation of different signaling pathways and regulatory networks. Moreover, BTF3s often respond to numerous stresses, and subsequently they are involved in regulation of various mechanisms. BTF3 proteins also function through protein-protein contact, which can assist us to identify the multifaceted processes of signaling and transcriptional regulation controlled by BTF3 proteins. In this review, we discuss current advances made in starting to explore the roles of BTF3 transcription factors in eukaryotes especially in plant growth and development.

  8. Two different negative regulatory elements control the transcription of T-cell activation gene 3 in activated mast cells.

    OpenAIRE

    C. K. Oh; Neurath, M; Cho, J.J.; Semere, T; Metcalfe, D D

    1997-01-01

    T-cell activation gene 3 (TCA3) encodes a beta-chemokine that is transcriptionally regulated in mast cells; the gene has a functional NF-kappaB element at positions -194 to -185. The 5'-flanking region of this gene is also known to have a negative regulatory region between -2057 and -1342. To characterize the negative regulatory elements (NREs), this region was sequenced and then digested by HindIII enzyme into two fragments, NRE-1 (-2057 to -1493) and NRE-2 (-1492 to -1342). Both NRE-1 and N...

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

    Directory of Open Access Journals (Sweden)

    Alexandra Saudemont

    2010-12-01

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

  10. Constructing a Knowledge Base for Gene Regulatory Dynamics by Formal Concept Analysis Methods

    CERN Document Server

    Wollbold, Johannes; Ganter, Bernhard

    2008-01-01

    Our aim is to build a set of rules, such that reasoning over temporal dependencies within gene regulatory networks is possible. The underlying transitions may be obtained by discretizing observed time series, or they are generated based on existing knowledge, e.g. by Boolean networks or their nondeterministic generalization. We use the mathematical discipline of formal concept analysis (FCA), which has been applied successfully in domains as knowledge representation, data mining or software engineering. By the attribute exploration algorithm, an expert or a supporting computer program is enabled to decide about the validity of a minimal set of implications and thus to construct a sound and complete knowledge base. From this all valid implications are derivable that relate to the selected properties of a set of genes. We present results of our method for the initiation of sporulation in Bacillus subtilis. However the formal structures are exhibited in a most general manner. Therefore the approach may be adapte...

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

    Science.gov (United States)

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

    2012-05-01

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

  12. T-Box Genes and Developmental Gene Regulatory Networks in Ascidians.

    Science.gov (United States)

    Di Gregorio, A

    2017-01-01

    Ascidians are invertebrate chordates with a biphasic life cycle characterized by a dual body plan that displays simplified versions of chordate structures, such as a premetamorphic 40-cell notochord topped by a dorsal nerve cord and postmetamorphic pharyngeal slits. These relatively simple chordates are characterized by rapid development, compact genomes and ease of transgenesis, and thus provide the opportunity to rapidly characterize the genomic organization, developmental function, and transcriptional regulation of evolutionarily conserved gene families. This review summarizes the current knowledge on members of the T-box family of transcription factors in Ciona and other ascidians. In both chordate and nonchordate animals, these genes control a variety of morphogenetic processes, and their mutations are responsible for malformations and developmental defects in organisms ranging from flies to humans. In ascidians, T-box transcription factors are required for the formation and specialization of essential structures, including notochord, muscle, heart, and differentiated neurons. In recent years, the experimental advantages offered by ascidian embryos have allowed the rapid accumulation of a wealth of information on the molecular mechanisms that regulate the expression of T-box genes. These studies have also elucidated the strategies employed by these transcription factors to orchestrate the appropriate spatial and temporal deployment of the numerous target genes that they control. © 2017 Elsevier Inc. All rights reserved.

  13. Inferring gene regulatory relationships with a high-dimensional robust approach.

    Science.gov (United States)

    Zang, Yangguang; Zhao, Qing; Zhang, Qingzhao; Li, Yang; Zhang, Sanguo; Ma, Shuangge

    2017-07-01

    Gene expression (GE) levels have important biological and clinical implications. They are regulated by copy number alterations (CNAs). Modeling the regulatory relationships between GEs and CNAs facilitates understanding disease biology and can also have values in translational medicine. The expression level of a gene can be regulated by its cis-acting as well as trans-acting CNAs, and the set of trans-acting CNAs is usually not known, which poses a high-dimensional selection and estimation problem. Most of the existing studies share a common limitation in that they cannot accommodate long-tailed distributions or contamination of GE data. In this study, we develop a high-dimensional robust regression approach to infer the regulatory relationships between GEs and CNAs. A high-dimensional regression model is used to accommodate the effects of both cis-acting and trans-acting CNAs. A density power divergence loss function is used to accommodate long-tailed GE distributions and contamination. Penalization is adopted for regularized estimation and selection of relevant CNAs. The proposed approach is effectively realized using a coordinate descent algorithm. Simulation shows that it has competitive performance compared to the nonrobust benchmark and the robust LAD (least absolute deviation) approach. We analyze TCGA (The Cancer Genome Atlas) data on cutaneous melanoma and study GE-CNA regulations in the RAP (regulation of apoptosis) pathway, which further demonstrates the satisfactory performance of the proposed approach. © 2017 WILEY PERIODICALS, INC.

  14. Footprinting the 'essential regulatory region' of the retinoblastoma gene promoter in intact human cells.

    Science.gov (United States)

    Temple, Mark D; Murray, Vincent

    2005-03-01

    The retinoblastoma tumour suppressor protein is a key cell cycle regulator. Protein-DNA interactions at the retinoblastoma (RB1) promoter, including the 'essential regulatory region', were investigated using novel DNA-targeted nitrogen mustards in intact human cells. The footprinting experiments were carried out in two different environments: in intact HeLa and K562 cells where the access of DNA-targeted probes to chromatin is affected by cellular protein-DNA interactions associated with gene regulation; and in purified DNA where their access is unencumbered by protein-DNA interactions. Using the ligation-mediated PCR (LMPCR) technique, the sites of damage were determined at base pair resolution on DNA sequencing gels. Our results demonstrate that, in intact cells, footprints were observed at the E2F, ATF and RBF1/Sp1 DNA binding motifs in the RB1 promoter. In addition, a novel footprint was observed at a previously unidentified cycle homology region (CHR) and at four uncharacterised protein-DNA binding sites. In further experiments, nitrogen mustard-treated cells were FACS sorted into G1, S and G2/M phases of the cell cycle prior to LMPCR analysis. Expression of the RB1 gene is cell cycle-regulated and footprinting studies of the promoter in FACS-sorted cells indicated that transcription factor binding at the GC box, CHR binding motif and the 'essential regulatory region' are cell cycle dependent.

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

    Science.gov (United States)

    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.

  16. Negative feedback and transcriptional overshooting in a regulatory network for horizontal gene transfer.

    Directory of Open Access Journals (Sweden)

    Raul Fernandez-Lopez

    2014-02-01

    Full Text Available Horizontal gene transfer (HGT is a major force driving bacterial evolution. Because of their ability to cross inter-species barriers, bacterial plasmids are essential agents for HGT. This ability, however, poses specific requisites on plasmid physiology, in particular the need to overcome a multilevel selection process with opposing demands. We analyzed the transcriptional network of plasmid R388, one of the most promiscuous plasmids in Proteobacteria. Transcriptional analysis by fluorescence expression profiling and quantitative PCR revealed a regulatory network controlled by six transcriptional repressors. The regulatory network relied on strong promoters, which were tightly repressed in negative feedback loops. Computational simulations and theoretical analysis indicated that this architecture would show a transcriptional burst after plasmid conjugation, linking the magnitude of the feedback gain with the intensity of the transcriptional burst. Experimental analysis showed that transcriptional overshooting occurred when the plasmid invaded a new population of susceptible cells. We propose that transcriptional overshooting allows genome rebooting after horizontal gene transfer, and might have an adaptive role in overcoming the opposing demands of multilevel selection.

  17. Cloning and characterization of nif structural and regulatory genes in the purple sulfur bacterium, Halorhodospira halophila.

    Science.gov (United States)

    Tsuihiji, Hisayoshi; Yamazaki, Yoichi; Kamikubo, Hironari; Imamoto, Yasushi; Kataoka, Mikio

    2006-03-01

    Halorhodospira halophila is a halophilic photosynthetic bacterium classified as a purple sulfur bacterium. We found that H. halophila generates hydrogen gas during photoautotrophic growth as a byproduct of a nitrogenase reaction. In order to consider the applied possibilities of this photobiological hydrogen generation, we cloned and characterized the structural and regulatory genes encoding the nitrogenase, nifH, nifD and nifA, from H. halophila. This is the first description of the nif genes for a purple sulfur bacterium. The amino-acid sequences of NifH and NifD indicated that these proteins are an Fe protein and a part of a MoFe protein, respectively. The important residues are conserved completely. The sequence upstream from the nifH region and sequence similarities of nifH and nifD with those of the other organisms suggest that the regulatory system might be a NifL-NifA system; however, H. halophila lacks nifL. The amino-acid sequence of H. halophila NifA is closer to that of the NifA of the NifL-NifA system than to that of NifA without NifL. H. halophila NifA does not conserve either the residue that interacts with NifL or the important residues involved in NifL-independent regulation. These results suggest the existence of yet another regulatory system, and that the development of functional systems and their molecular counterparts are not necessarily correlated throughout evolution. All of these Nif proteins of H. halophila possess an excess of acidic residues, which acts as a salt-resistant mechanism.

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

    Directory of Open Access Journals (Sweden)

    Elena Vasilyevna Chetina

    2012-01-01

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

  19. Deciphering ascorbic acid regulatory pathways in ripening tomato fruit using a weighted gene correlation network analysis approach.

    Science.gov (United States)

    Gao, Chao; Ju, Zheng; Li, Shan; Zuo, Jinhua; Fu, Daqi; Tian, Huiqin; Luo, Yunbo; Zhu, Benzhong

    2013-11-01

    Genotype is generally determined by the co-expression of diverse genes and multiple regulatory pathways in plants. Gene co-expression analysis combining with physiological trait data provides very important information about the gene function and regulatory mechanism. L-Ascorbic acid (AsA), which is an essential nutrient component for human health and plant metabolism, plays key roles in diverse biological processes such as cell cycle, cell expansion, stress resistance, hormone synthesis, and signaling. Here, we applied a weighted gene correlation network analysis approach based on gene expression values and AsA content data in ripening tomato (Solanum lycopersicum L.) fruit with different AsA content levels, which leads to identification of AsA relevant modules and vital genes in AsA regulatory pathways. Twenty-four modules were compartmentalized according to gene expression profiling. Among these modules, one negatively related module containing genes involved in redox processes and one positively related module enriched with genes involved in AsA biosynthetic and recycling pathways were further analyzed. The present work herein indicates that redox pathways as well as hormone-signal pathways are closely correlated with AsA accumulation in ripening tomato fruit, and allowed us to prioritize candidate genes for follow-up studies to dissect this interplay at the biochemical and molecular level. © 2013 Institute of Botany, Chinese Academy of Sciences.

  20. Expression profiles and associations of muscle regulatory factor (MRF) genes with growth traits in Tibetan chickens.

    Science.gov (United States)

    Zhang, R; Li, R; Zhi, L; Xu, Y; Lin, Y; Chen, L

    2017-10-25

    1. Muscle regulatory factors (MRFs), including Myf5, Myf6 (MRF4/herculin), MyoD and MyoG (myogenin), play pivotal roles in muscle growth and development. Therefore, they are considered as candidate genes for meat production traits in livestock and poultry. 2. The objective of this study was to investigate the expression profiles of these genes in skeletal muscles (breast muscle and thigh muscle) at 5 developmental stages (0, 81, 119, 154 and 210 d old) of Tibetan chickens. Relationships between expressions of these genes and growth and carcass traits in these chickens were also estimated. 3. The expression profiles showed that in the breast muscle of both genders the mRNA levels of MRF genes were highest on the day of hatching, then declined significantly from d 0 to d 81, and fluctuated in a certain range from d 81 to d 210. However, the expression of Myf5, Myf6 and MyoG reached peaks in the thigh muscle in 118-d-old females and for MyoD in 154-d-old females, whereas the mRNA amounts of MRF genes in the male thigh muscle were in a narrow range from d 0 to d 210. 4. Correlation analysis suggested that gender had an influence on the relationships of MRF gene expression with growth traits. The RNA levels of MyoD, Myf5 genes in male breast muscle were positively related with several growth traits of Tibetan chickens (P growth and development of Tibetan chickens, as well as selective breeding and resource exploration.

  1. Precambrian Skeletonized Microbial Eukaryotes

    Science.gov (United States)

    Lipps, Jere H.

    2017-04-01

    Skeletal heterotrophic eukaryotes are mostly absent from the Precambrian, although algal eukaryotes appear about 2.2 billion years ago. Tintinnids, radiolaria and foraminifera have molecular origins well back into the Precambrian yet no representatives of these groups are known with certainty in that time. These data infer times of the last common ancestors, not the appearance of true representatives of these groups which may well have diversified or not been preserved since those splits. Previous reports of these groups in the Precambrian are misinterpretations of other objects in the fossil record. Reported tintinnids at 1600 mya from China are metamorphic shards or mineral artifacts, the many specimens from 635-715 mya in Mongolia may be eukaryotes but they are not tintinnids, and the putative tintinnids at 580 mya in the Doushantou formation of China are diagenetic alterations of well-known acritarchs. The oldest supposed foraminiferan is Titanotheca from 550 to 565 mya rocks in South America and Africa is based on the occurrence of rutile in the tests and in a few modern agglutinated foraminifera, as well as the agglutinated tests. Neither of these nor the morphology are characteristic of foraminifera; hence these fossils remain as indeterminate microfossils. Platysolenites, an agglutinated tube identical to the modern foraminiferan Bathysiphon, occurs in the latest Neoproterozoic in Russia, Canada, and the USA (California). Some of the larger fossils occurring in typical Ediacaran (late Neoproterozoic) assemblages may be xenophyophorids (very large foraminifera), but the comparison is disputed and flawed. Radiolaria, on occasion, have been reported in the Precambrian, but the earliest known clearly identifiable ones are in the Cambrian. The only certain Precambrian heterotrophic skeletal eukaryotes (thecamoebians) occur in fresh-water rocks at about 750 mya. Skeletonized radiolaria and foraminifera appear sparsely in the Cambrian and radiate in the Ordovician

  2. 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

  3. Association analysis of PRKAG3 gene variants with carcass and ...

    African Journals Online (AJOL)

    The bovine PRKAG3 gene encodes a muscle-specific isoform of the regulatory gamma-subunit of adenosine monophosphate activated protein kinase (AMPK), which plays a key role in regulating energy homeostasis in eukaryotes. It is well known that mutations in the PRKAG3 gene affect high glycogen content in the ...

  4. Use of H19 Gene Regulatory Sequences in DNA-Based Therapy for Pancreatic Cancer

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    V. Scaiewicz

    2010-01-01

    Full Text Available Pancreatic cancer is the eighth most common cause of death from cancer in the world, for which palliative treatments are not effective and frequently accompanied by severe side effects. We propose a DNA-based therapy for pancreatic cancer using a nonviral vector, expressing the diphtheria toxin A chain under the control of the H19 gene regulatory sequences. The H19 gene is an oncofetal RNA expressed during embryo development and in several types of cancer. We tested the expression of H19 gene in patients, and found that 65% of human pancreatic tumors analyzed showed moderated to strong expression of the gene. In vitro experiments showed that the vector was effective in reducing Luciferase protein activity on pancreatic carcinoma cell lines. In vivo experiment results revealed tumor growth arrest in different animal models for pancreatic cancer. Differences in tumor size between control and treated groups reached a 75% in the heterotopic model (P=.037 and 50% in the orthotopic model (P=.007. In addition, no visible metastases were found in the treated group of the orthotopic model. These results indicate that the treatment with the vector DTA-H19 might be a viable new therapeutic option for patients with unresectable pancreatic cancer.

  5. A case study for effects of operational taxonomic units from intracellular endoparasites and ciliates on the eukaryotic phylogeny: phylogenetic position of the haptophyta in analyses of multiple slowly evolving genes.

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    Hisayoshi Nozaki

    Full Text Available Recent multigene phylogenetic analyses have contributed much to our understanding of eukaryotic phylogeny. However, the phylogenetic positions of various lineages within the eukaryotes have remained unresolved or in conflict between different phylogenetic studies. These phylogenetic ambiguities might have resulted from mixtures or integration from various factors including limited taxon sampling, missing data in the alignment, saturations of rapidly evolving genes, mixed analyses of short- and long-branched operational taxonomic units (OTUs, intracellular endoparasite and ciliate OTUs with unusual substitution etc. In order to evaluate the effects from intracellular endoparasite and ciliate OTUs co-analyzed on the eukaryotic phylogeny and simplify the results, we here used two different sets of data matrices of multiple slowly evolving genes with small amounts of missing data and examined the phylogenetic position of the secondary photosynthetic chromalveolates Haptophyta, one of the most abundant groups of oceanic phytoplankton and significant primary producers. In both sets, a robust sister relationship between Haptophyta and SAR (stramenopiles, alveolates, rhizarians, or SA [stramenopiles and alveolates] was resolved when intracellular endoparasite/ciliate OTUs were excluded, but not in their presence. Based on comparisons of character optimizations on a fixed tree (with a clade composed of haptophytes and SAR or SA, disruption of the monophyly between haptophytes and SAR (or SA in the presence of intracellular endoparasite/ciliate OTUs can be considered to be a result of multiple evolutionary reversals of character positions that supported the synapomorphy of the haptophyte and SAR (or SA clade in the absence of intracellular endoparasite/ciliate OTUs.

  6. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Science.gov (United States)

    Sayyed-Ahmad, Abdallah; Tuncay, Kagan; Ortoleva, Peter J

    2007-01-01

    Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the construction of the network of

  7. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Directory of Open Access Journals (Sweden)

    Tuncay Kagan

    2007-01-01

    Full Text Available Abstract Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the

  8. Identification of an evolutionarily conserved regulatory element of the zebrafish col2a1a gene

    Science.gov (United States)

    Dale, Rodney M.; Topczewski, Jacek

    2011-01-01

    Zebrafish (Danio rerio) is an excellent model organism for the study of vertebrate development including skeletogenesis. Studies of mammalian cartilage formation were greatly advanced through the use of a cartilage specific regulatory element of the Collagen type II alpha 1 (Col2a1) gene. In an effort to isolate such an element in zebrafish, we compared the expression of two col2a1 homologues and found that expression of col2a1b, a previously uncharacterized zebrafish homologue, only partially overlaps with col2a1a. We focused our analysis on col2a1a, as it is expressed in both the stacked chondrocytes and the perichondrium. By comparing the genomic sequence surrounding the predicted transcriptional start site of col2a1a among several species of teleosts we identified a small highly conserved sequence (R2) located 1.7 kb upstream of the presumptive transcriptional initiation site. Interestingly, neither the sequence nor location of this element is conserved between teleost and mammalian Col2a1. We generated transient and stable transgenic lines with just the R2 element or the entire 1.7 kb fragment 5’ of the transcriptional initiation site. The identified regulatory elements enable the tracking of cellular development in various tissues by driving robust reporter expression in craniofacial cartilage, ear, notochord, floor plate, hypochord and fins in a pattern similar to the expression of endogenous col2a1a. Using a reporter gene driven by the R2 regulatory element, we analyzed the morphogenesis of the notochord sheath cells as they withdraw from the stack of initially uniform cells and encase the inflating vacuolated notochord cells. Finally, we show that like endogenous col2a1a, craniofacial expression of these reporter constructs depends on Sox9a transcription factor activity. At the same time, notochord expression is maintained after Sox9a knockdown, suggesting that other factors can activate expression through the identified regulatory element in this tissue

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

    Science.gov (United States)

    Zainudin, Suhaila; Arif, Shereena M.

    2017-01-01

    Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5. PMID:28250767

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Faridah Hani Mohamed Salleh

    2017-01-01

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

  12. An improved Bayesian network method for reconstructing gene regulatory network based on candidate auto selection.

    Science.gov (United States)

    Xing, Linlin; Guo, Maozu; Liu, Xiaoyan; Wang, Chunyu; Wang, Lei; Zhang, Yin

    2017-11-17

    The reconstruction of gene regulatory network (GRN) from gene expression data can discover regulatory relationships among genes and gain deep insights into the complicated regulation mechanism of life. However, it is still a great challenge in systems biology and bioinformatics. During the past years, numerous computational approaches have been developed for this goal, and Bayesian network (BN) methods draw most of attention among these methods because of its inherent probability characteristics. However, Bayesian network methods are time consuming and cannot handle large-scale networks due to their high computational complexity, while the mutual information-based methods are highly effective but directionless and have a high false-positive rate. To solve these problems, we propose a Candidate Auto Selection algorithm (CAS) based on mutual information and breakpoint detection to restrict the search space in order to accelerate the learning process of Bayesian network. First, the proposed CAS algorithm automatically selects the neighbor candidates of each node before searching the best structure of GRN. Then based on CAS algorithm, we propose a globally optimal greedy search method (CAS + G), which focuses on finding the highest rated network structure, and a local learning method (CAS + L), which focuses on faster learning the structure with little loss of quality. Results show that the proposed CAS algorithm can effectively reduce the search space of Bayesian networks through identifying the neighbor candidates of each node. In our experiments, the CAS + G method outperforms the state-of-the-art method on simulation data for inferring GRNs, and the CAS + L method is significantly faster than the state-of-the-art method with little loss of accuracy. Hence, the CAS based methods effectively decrease the computational complexity of Bayesian network and are more suitable for GRN inference.

  13. Multiple herbicide resistance in Lolium multiflorum and identification of conserved regulatory elements of herbicide resistance genes

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    Khalid Mahmood

    2016-08-01

    Full Text Available Herbicide resistance is a ubiquitous challenge to herbicide sustainability and a looming threat to control weeds in crops. Recently four genes were found constituently over-expressed in herbicide resistant individuals of Lolium rigidum, a close relative of L. multiflorum. These include two cytochrome P450s, one nitronate monooxygenase and one glycosyl-transferase. Higher expressions of these four herbicide metabolism related (HMR genes were also observed after herbicides exposure in the gene expression databases, indicating them a reliable marker. In order to get an overview of herbicidal resistance status of Lolium multiflorum L, 19 field populations were collected. Among these populations, four populations were found to be resistant to acetolactate synthase (ALS inhibitors while three exhibited resistance to acetyl-CoA carboxylase (ACCase inhibitors in our initial screening and dose response study. The genotyping showed the presence of mutations Trp-574-Leu and Ile-2041-Asn in ALS and ACCase, respectively and qPCR experiments revealed the enhanced expression of HMR genes in individuals of certain resistant populations. Moreover, co-expression networks and promoter analyses of HMR genes in O.sativa and A.thaliana resulted in the identification of a cis-regulatory motif and zinc finger transcription factors. The identified transcription factors were highly expressed similar to HMR genes in response to xenobiotics whereas the identified motif known to play a vital role in coping with environmental stresses and maintaining genome stability. Overall, our findings provide an important step forward towards a better understanding of metabolism-based herbicide resistance that can be utilized to devise novel strategies of weed management.

  14. Mitochondrion-related organelles in eukaryotic protists.

    Science.gov (United States)

    Shiflett, April M; Johnson, Patricia J

    2010-01-01

    The discovery of mitochondrion-type genes in organisms thought to lack mitochondria led to the demonstration that hydrogenosomes share a common ancestry with mitochondria, as well as the discovery of mitosomes in multiple eukaryotic lineages. No examples of examined eukaryotes lacking a mitochondrion-related organelle exist, implying that the endosymbiont that gave rise to the mitochondrion was present in the first eukaryote. These organelles, known as hydrogenosomes, mitosomes, or mitochondrion-like organelles, are typically reduced, both structurally and biochemically, relative to classical mitochondria. However, despite their diversification and adaptation to different niches, all appear to play a role in Fe-S cluster assembly, as observed for mitochondria. Although evidence supports the use of common protein targeting mechanisms in the biogenesis of these diverse organelles, divergent features are also apparent. This review examines the metabolism and biogenesis of these organelles in divergent unicellular microbes, with a focus on parasitic protists.

  15. Atypical mitochondrial inheritance patterns in eukaryotes.

    Science.gov (United States)

    Breton, Sophie; Stewart, Donald T

    2015-10-01

    Mitochondrial DNA (mtDNA) is predominantly maternally inherited in eukaryotes. Diverse molecular mechanisms underlying the phenomenon of strict maternal inheritance (SMI) of mtDNA have been described, but the evolutionary forces responsible for its predominance in eukaryotes remain to be elucidated. Exceptions to SMI have been reported in diverse eukaryotic taxa, leading to the prediction that several distinct molecular mechanisms controlling mtDNA transmission are present among the eukaryotes. We propose that these mechanisms will be better understood by studying the deviations from the predominating pattern of SMI. This minireview summarizes studies on eukaryote species with unusual or rare mitochondrial inheritance patterns, i.e., other than the predominant SMI pattern, such as maternal inheritance of stable heteroplasmy, paternal leakage of mtDNA, biparental and strictly paternal inheritance, and doubly uniparental inheritance of mtDNA. The potential genes and mechanisms involved in controlling mitochondrial inheritance in these organisms are discussed. The linkage between mitochondrial inheritance and sex determination is also discussed, given that the atypical systems of mtDNA inheritance examined in this minireview are frequently found in organisms with uncommon sexual systems such as gynodioecy, monoecy, or andromonoecy. The potential of deviations from SMI for facilitating a better understanding of a number of fundamental questions in biology, such as the evolution of mtDNA inheritance, the coevolution of nuclear and mitochondrial genomes, and, perhaps, the role of mitochondria in sex determination, is considerable.

  16. Phylogenetic and regulatory region analysis of Wnt5 genes reveals conservation of a regulatory module with putative implication in pancreas development

    Directory of Open Access Journals (Sweden)

    Arhondakis Stilianos

    2010-08-01

    Full Text Available Abstract Background Wnt5 genes belong to the large Wnt family, encoding proteins implicated into several tumorigenic and developmental processes. Phylogenetic analyses showed that Wnt5 gene has been duplicated at the divergence time of gnathostomata from agnatha. Interestingly, experimental data for some species indicated that only one of the two Wnt5 paralogs participates in the development of the endocrine pancreas. The purpose of this paper is to reexamine the phylogenetic history of the Wnt5 developmental regulators and investigate the functional shift between paralogs through comparative genomics. Results In this study, the phylogeny of Wnt5 genes was investigated in species belonging to protostomia and deuterostomia. Furthermore, an in silico regulatory region analysis of Wnt5 paralogs was conducted, limited to those species with insulin producing cells and pancreas, covering the evolutionary distance from agnatha to gnathostomata. Our results confirmed the Wnt5 gene duplication and additionally revealed that this duplication event included also the upstream region. Moreover, within this latter region, a conserved module was detected to which a complex of transcription factors, known to be implicated in embryonic pancreas formation, bind. Conclusions Results and observations presented in this study, allow us to conclude that during evolution, the Wnt5 gene has been duplicated in early vertebrates, and that some paralogs conserved a module within their regulatory region, functionally related to embryonic development of pancreas. Interestingly, our results allowed advancing a possible explanation on why the Wnt5 orthologs do not share the same function during pancreas development. As a final remark, we suggest that an in silico comparative analysis of regulatory regions, especially when associated to published experimental data, represents a powerful approach for explaining shift of roles among paralogs. Reviewers This article was reviewed

  17. Phylogenetic and regulatory region analysis of Wnt5 genes reveals conservation of a regulatory module with putative implication in pancreas development.

    Science.gov (United States)

    Kapasa, Maria; Arhondakis, Stilianos; Kossida, Sophia

    2010-08-04

    Wnt5 genes belong to the large Wnt family, encoding proteins implicated into several tumorigenic and developmental processes. Phylogenetic analyses showed that Wnt5 gene has been duplicated at the divergence time of gnathostomata from agnatha. Interestingly, experimental data for some species indicated that only one of the two Wnt5 paralogs participates in the development of the endocrine pancreas. The purpose of this paper is to reexamine the phylogenetic history of the Wnt5 developmental regulators and investigate the functional shift between paralogs through comparative genomics. In this study, the phylogeny of Wnt5 genes was investigated in species belonging to protostomia and deuterostomia. Furthermore, an in silico regulatory region analysis of Wnt5 paralogs was conducted, limited to those species with insulin producing cells and pancreas, covering the evolutionary distance from agnatha to gnathostomata. Our results confirmed the Wnt5 gene duplication and additionally revealed that this duplication event included also the upstream region. Moreover, within this latter region, a conserved module was detected to which a complex of transcription factors, known to be implicated in embryonic pancreas formation, bind. Results and observations presented in this study, allow us to conclude that during evolution, the Wnt5 gene has been duplicated in early vertebrates, and that some paralogs conserved a module within their regulatory region, functionally related to embryonic development of pancreas. Interestingly, our results allowed advancing a possible explanation on why the Wnt5 orthologs do not share the same function during pancreas development. As a final remark, we suggest that an in silico comparative analysis of regulatory regions, especially when associated to published experimental data, represents a powerful approach for explaining shift of roles among paralogs.

  18. The COG database: an updated version includes eukaryotes

    Directory of Open Access Journals (Sweden)

    Sverdlov Alexander V

    2003-09-01

    Full Text Available Abstract Background The availability of multiple, essentially complete genome sequences of prokaryotes and eukaryotes spurred both the demand and the opportunity for the construction of an evolutionary classification of genes from these genomes. Such a classification system based on orthologous relationships between genes appears to be a natural framework for comparative genomics and should facilitate both functional annotation of genomes and large-scale evolutionary studies. Results We describe here a major update of the previously developed system for delineation of Clusters of Orthologous Groups of proteins (COGs from the sequenced genomes of prokaryotes and unicellular eukaryotes and the construction of clusters of predicted orthologs for 7 eukaryotic genomes, which we named KOGs after eukaryotic orthologous groups. The COG collection currently consists of 138,458 proteins, which form 4873 COGs and comprise 75% of the 185,505 (predicted proteins encoded in 66 genomes of unicellular organisms. The eukaryotic orthologous groups (KOGs include proteins from 7 eukaryotic genomes: three animals (the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster and Homo sapiens, one plant, Arabidopsis thaliana, two fungi (Saccharomyces cerevisiae and Schizosaccharomyces pombe, and the intracellular microsporidian parasite Encephalitozoon cuniculi. The current KOG set consists of 4852 clusters of orthologs, which include 59,838 proteins, or ~54% of the analyzed eukaryotic 110,655 gene products. Compared to the coverage of the prokaryotic genomes with COGs, a considerably smaller fraction of eukaryotic genes could be included into the KOGs; addition of new eukaryotic genomes is expected to result in substantial increase in the coverage of eukaryotic genomes with KOGs. Examination of the phyletic patterns of KOGs reveals a conserved core represented in all analyzed species and consisting of ~20% of the KOG set. This conserved portion of the

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

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

    2013-04-26

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

  20. Recurrent neural network-based modeling of gene regulatory network using elephant swarm water search algorithm.

    Science.gov (United States)

    Mandal, Sudip; Saha, Goutam; Pal, Rajat Kumar

    2017-08-01

    Correct inference of genetic regulations inside a cell from the biological database like time series microarray data is one of the greatest challenges in post genomic era for biologists and researchers. Recurrent Neural Network (RNN) is one of the most popular and simple approach to model the dynamics as well as to infer correct dependencies among genes. Inspired by the behavior of social elephants, we propose a new metaheuristic namely Elephant Swarm Water Search Algorithm (ESWSA) to infer Gene Regulatory Network (GRN). This algorithm is mainly based on the water search strategy of intelligent and social elephants during drought, utilizing the different types of communication techniques. Initially, the algorithm is tested against benchmark small and medium scale artificial genetic networks without and with presence of different noise levels and the efficiency was observed in term of parametric error, minimum fitness value, execution time, accuracy of prediction of true regulation, etc. Next, the proposed algorithm is tested against the real time gene expression data of Escherichia Coli SOS Network and results were also compared with others state of the art optimization methods. The experimental results suggest that ESWSA is very efficient for GRN inference problem and performs better than other methods in many ways.

  1. DNA Methylation of Regulatory Regions of Imprinted Genes at Birth and Its Relation to Infant Temperament

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    Bernard F. Fuemmeler

    2016-01-01

    Full Text Available BACKGROUND DNA methylation of the differentially methylated regions (DMRs of imprinted genes is relevant to neurodevelopment. METHODS DNA methylation status of the DMRs of nine imprinted genes in umbilical cord blood leukocytes was analyzed in relation to infant behaviors and temperament (n = 158. RESULTS MEG3 DMR levels were positively associated with internalizing ( β = 0.15, P = 0.044 and surgency ( β = 0.19, P = 0.018 behaviors, after adjusting for birth weight, gender, gestational age at birth, maternal age at delivery, race/ethnicity, education level, smoking status, parity, and a history of anxiety or depression. Higher methylation levels at the intergenic MEG3-IG methylation regions were associated with surgency ( β = 0.28, P = 0.0003 and PEG3 was positively related to externalizing ( β = 0.20, P = 0.01 and negative affectivity ( β = 0.18, P = 0.02. CONCLUSION While the small sample size limits inference, these pilot data support gene-specific associations between epigenetic differences in regulatory regions of imprinted domains at birth and later infant temperament.

  2. Evolution of gene regulatory networks by fluctuating selection and intrinsic constraints.

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    Masaki E Tsuda

    Full Text Available Various characteristics of complex gene regulatory networks (GRNs have been discovered during the last decade, e.g., redundancy, exponential indegree distributions, scale-free outdegree distributions, mutational robustness, and evolvability. Although progress has been made in this field, it is not well understood whether these characteristics are the direct products of selection or those of other evolutionary forces such as mutational biases and biophysical constraints. To elucidate the causal factors that promoted the evolution of complex GRNs, we examined the effect of fluctuating environmental selection and some intrinsic constraining factors on GRN evolution by using an individual-based model. We found that the evolution of complex GRNs is remarkably promoted by fixation of beneficial gene duplications under unpredictably fluctuating environmental conditions and that some internal factors inherent in organisms, such as mutational bias, gene expression costs, and constraints on expression dynamics, are also important for the evolution of GRNs. The results indicate that various biological properties observed in GRNs could evolve as a result of not only adaptation to unpredictable environmental changes but also non-adaptive processes owing to the properties of the organisms themselves. Our study emphasizes that evolutionary models considering such intrinsic constraining factors should be used as null models to analyze the effect of selection on GRN evolution.

  3. Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method.

    Science.gov (United States)

    Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui

    2017-10-06

    Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli, and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.

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

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    Michael Hadjiargyrou

    2018-01-01

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

  5. The Construction of Regulatory Network for Insulin-Mediated Genes by Integrating Methods Based on Transcription Factor Binding Motifs and Gene Expression Variations

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    Hyeim Jung

    2015-09-01

    Full Text Available Type 2 diabetes mellitus is a complex metabolic disorder associated with multiple genetic, developmental and environmental factors. The recent advances in gene expression microarray technologies as well as network-based analysis methodologies provide groundbreaking opportunities to study type 2 diabetes mellitus. In the present study, we used previously published gene expression microarray datasets of human skeletal muscle samples collected from 20 insulin sensitive individuals before and after insulin treatment in order to construct insulin-mediated regulatory network. Based on a motif discovery method implemented by iRegulon, a Cytoscape app, we identified 25 candidate regulons, motifs of which were enriched among the promoters of 478 up-regulated genes and 82 down-regulated genes. We then looked for a hierarchical network of the candidate regulators, in such a way that the conditional combination of their expression changes may explain those of their target genes. Using Genomica, a software tool for regulatory network construction, we obtained a hierarchical network of eight regulons that were used to map insulin downstream signaling network. Taken together, the results illustrate the benefits of combining completely different methods such as motif-based regulatory factor discovery and expression level-based construction of regulatory network of their target genes in understanding insulin induced biological processes and signaling pathways.

  6. The Construction of Regulatory Network for Insulin-Mediated Genes by Integrating Methods Based on Transcription Factor Binding Motifs and Gene Expression Variations.

    Science.gov (United States)

    Jung, Hyeim; Han, Seonggyun; Kim, Sangsoo

    2015-09-01

    Type 2 diabetes mellitus is a complex metabolic disorder associated with multiple genetic, developmental and environmental factors. The recent advances in gene expression microarray technologies as well as network-based analysis methodologies provide groundbreaking opportunities to study type 2 diabetes mellitus. In the present study, we used previously published gene expression microarray datasets of human skeletal muscle samples collected from 20 insulin sensitive individuals before and after insulin treatment in order to construct insulin-mediated regulatory network. Based on a motif discovery method implemented by iRegulon, a Cytoscape app, we identified 25 candidate regulons, motifs of which were enriched among the promoters of 478 up-regulated genes and 82 down-regulated genes. We then looked for a hierarchical network of the candidate regulators, in such a way that the conditional combination of their expression changes may explain those of their target genes. Using Genomica, a software tool for regulatory network construction, we obtained a hierarchical network of eight regulons that were used to map insulin downstream signaling network. Taken together, the results illustrate the benefits of combining completely different methods such as motif-based regulatory factor discovery and expression level-based construction of regulatory network of their target genes in understanding insulin induced biological processes and signaling pathways.

  7. Uncovering Gene Regulatory Networks from Time-Series Microarray Data with Variational Bayesian Structural Expectation Maximization

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    Huang Yufei

    2007-01-01

    Full Text Available We investigate in this paper reverse engineering of gene regulatory networks from time-series microarray data. We apply dynamic Bayesian networks (DBNs for modeling cell cycle regulations. In developing a network inference algorithm, we focus on soft solutions that can provide a posteriori probability (APP of network topology. In particular, we propose a variational Bayesian structural expectation maximization algorithm that can learn the posterior distribution of the network model parameters and topology jointly. We also show how the obtained APPs of the network topology can be used in a Bayesian data integration strategy to integrate two different microarray data sets. The proposed VBSEM algorithm has been tested on yeast cell cycle data sets. To evaluate the confidence of the inferred networks, we apply a moving block bootstrap method. The inferred network is validated by comparing it to the KEGG pathway map.

  8. Morphogenesis in sea urchin embryos: linking cellular events to gene regulatory network states

    Science.gov (United States)

    Lyons, Deidre; Kaltenbach, Stacy; McClay, David R.

    2013-01-01

    Gastrulation in the sea urchin begins with ingression of the primary mesenchyme cells (PMCs) at the vegetal pole of the embryo. After entering the blastocoel the PMCs migrate, form a syncitium, and synthesize the skeleton of the embryo. Several hours after the PMCs ingress the vegetal plate buckles to initiate invagination of the archenteron. That morphogenetic process occurs in several steps. The non-skeletogenic cells produce the initial inbending of the vegetal plate. Endoderm cells then rearrange and extend the length of the gut across the blastocoel to a target near the animal pole. Finally, cells that will form part of the midgut and hindgut are added to complete gastrulation. Later, the stomodeum invaginates from the oral ectoderm and fuses with the foregut to complete the archenteron. In advance of, and during these morphogenetic events an increasingly complex gene regulatory network controls the specification and the cell biological events that conduct the gastrulation movements. PMID:23801438

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

    Science.gov (United States)

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

    2017-12-14

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

  10. The architecture of gene regulatory variation across multiple human tissues: the MuTHER study.

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    Alexandra C Nica

    2011-02-01

    Full Text Available While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role of cis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL, skin, and fat. The samples (156 LCL, 160 skin, 166 fat were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes. In addition, we apply factor analysis (FA to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes. The unique study design (Matched Co-Twin Analysis--MCTA permits immediate replication of eQTLs using co-twins (93%-98% and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%-20% have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits.

  11. Gene regulatory networks in neural cell fate acquisition from genome-wide chromatin association of Geminin and Zic1

    Science.gov (United States)

    Sankar, Savita; Yellajoshyula, Dhananjay; Zhang, Bo; Teets, Bryan; Rockweiler, Nicole; Kroll, Kristen L.

    2016-01-01

    Neural cell fate acquisition is mediated by transcription factors expressed in nascent neuroectoderm, including Geminin and members of the Zic transcription factor family. However, regulatory networks through which this occurs are not well defined. Here, we identified Geminin-associated chromatin locations in embryonic stem cells and Geminin- and Zic1-associated locations during neural fate acquisition at a genome-wide level. We determined how Geminin deficiency affected histone acetylation at gene promoters during this process. We integrated these data to demonstrate that Geminin associates with and promotes histone acetylation at neurodevelopmental genes, while Geminin and Zic1 bind a shared gene subset. Geminin- and Zic1-associated genes exhibit embryonic nervous system-enriched expression and encode other regulators of neural development. Both Geminin and Zic1-associated peaks are enriched for Zic1 consensus binding motifs, while Zic1-bound peaks are also enriched for Sox3 motifs, suggesting co-regulatory potential. Accordingly, we found that Geminin and Zic1 could cooperatively activate the expression of several shared targets encoding transcription factors that control neurogenesis, neural plate patterning, and neuronal differentiation. We used these data to construct gene regulatory networks underlying neural fate acquisition. Establishment of this molecular program in nascent neuroectoderm directly links early neural cell fate acquisition with regulatory control of later neurodevelopment. PMID:27881878

  12. Role of transcription regulatory sequence in regulation of gene expression and replication of porcine reproductive and respiratory syndrome virus.

    Science.gov (United States)

    Wang, Chengbao; Meng, Han; Gao, Yujin; Gao, Hui; Guo, Kangkang; Almazan, Fernando; Sola, Isabel; Enjuanes, Luis; Zhang, Yanming; Abrahamyan, Levon

    2017-08-10

    In order to gain insight into the role of the transcription regulatory sequences (TRSs) in the regulation of gene expression and replication of porcine reproductive and respiratory syndrome virus (PRRSV), the enhanced green fluorescent protein (EGFP) gene, under the control of the different structural gene TRSs, was inserted between the N gene and 3'-UTR of the PRRSV genome and EGFP expression was analyzed for each TRS. TRSs of all the studied structural genes of PRRSV positively modulated EGFP expression at different levels. Among the TRSs analyzed, those of GP2, GP5, M, and N genes highly enhanced EGFP expression without altering replication of PRRSV. These data indicated that structural gene TRSs could be an extremely useful tool for foreign gene expression using PRRSV as a vector.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2017-12-15

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

  15. A regulatory gene network related to the porcine umami taste receptor (TAS1R1/TAS1R3).

    Science.gov (United States)

    Kim, J M; Ren, D; Reverter, A; Roura, E

    2016-02-01

    Taste perception plays an important role in the mediation of food choices in mammals. The first porcine taste receptor genes identified, sequenced and characterized, TAS1R1 and TAS1R3, were related to the dimeric receptor for umami taste. However, little is known about their regulatory network. The objective of this study was to unfold the genetic network involved in porcine umami taste perception. We performed a meta-analysis of 20 gene expression studies spanning 480 porcine microarray chips and screened 328 taste-related genes by selective mining steps among the available 12,320 genes. A porcine umami taste-specific regulatory network was constructed based on the normalized coexpression data of the 328 genes across 27 tissues. From the network, we revealed the 'taste module' and identified a coexpression cluster for the umami taste according to the first connector with the TAS1R1/TAS1R3 genes. Our findings identify several taste-related regulatory genes and extend previous genetic background of porcine umami taste. © 2015 Stichting International Foundation for Animal Genetics.

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

    Directory of Open Access Journals (Sweden)

    Manoj Kulkarni

    2017-12-01

    gold-standard reference genome sequence and advent of genome editing technologies, are expected to aid in deciphering of the functional roles of genes and regulatory networks underlying adaptive phenological traits, and utilizing the outcomes of such studies in developing drought tolerant cultivars.

  17. Origins and evolution of viruses of eukaryotes: The ultimate modularity

    Energy Technology Data Exchange (ETDEWEB)

    Koonin, Eugene V., E-mail: koonin@ncbi.nlm.nih.gov [National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894 (United States); Dolja, Valerian V., E-mail: doljav@science.oregonstate.edu [Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331 (United States); Krupovic, Mart, E-mail: krupovic@pasteur.fr [Institut Pasteur, Unité Biologie Moléculaire du Gène chez les Extrêmophiles, Department of Microbiology, Paris 75015 (France)

    2015-05-15

    Viruses and other selfish genetic elements are dominant entities in the biosphere, with respect to both physical abundance and genetic diversity. Various selfish elements parasitize on all cellular life forms. The relative abundances of different classes of viruses are dramatically different between prokaryotes and eukaryotes. In prokaryotes, the great majority of viruses possess double-stranded (ds) DNA genomes, with a substantial minority of single-stranded (ss) DNA viruses and only limited presence of RNA viruses. In contrast, in eukaryotes, RNA viruses account for the majority of the virome diversity although ssDNA and dsDNA viruses are common as well. Phylogenomic analysis yields tangible clues for the origins of major classes of eukaryotic viruses and in particular their likely roots in prokaryotes. Specifically, the ancestral genome of positive-strand RNA viruses of eukaryotes might have been assembled de novo from genes derived from prokaryotic retroelements and bacteria although a primordial origin of this class of viruses cannot be ruled out. Different groups of double-stranded RNA viruses derive either from dsRNA bacteriophages or from positive-strand RNA viruses. The eukaryotic ssDNA viruses apparently evolved via a fusion of genes from prokaryotic rolling circle-replicating plasmids and positive-strand RNA viruses. Different families of eukaryotic dsDNA viruses appear to have originated from specific groups of bacteriophages on at least two independent occasions. Polintons, the largest known eukaryotic transposons, predicted to also form virus particles, most likely, were the evolutionary intermediates between bacterial tectiviruses and several groups of eukaryotic dsDNA viruses including the proposed order “Megavirales” that unites diverse families of large and giant viruses. Strikingly, evolution of all classes of eukaryotic viruses appears to have involved fusion between structural and replicative gene modules derived from different sources

  18. A gene regulatory network model for floral transition of the shoot apex in maize and its dynamic modeling.

    Science.gov (United States)

    Dong, Zhanshan; Danilevskaya, Olga; Abadie, Tabare; Messina, Carlos; Coles, Nathan; Cooper, Mark

    2012-01-01

    The transition from the vegetative to reproductive development is a critical event in the plant life cycle. The accurate prediction of flowering time in elite germplasm is important for decisions in maize breeding programs and best agronomic practices. The understanding of the genetic control of flowering time in maize has significantly advanced in the past decade. Through comparative genomics, mutant analysis, genetic analysis and QTL cloning, and transgenic approaches, more than 30 flowering time candidate genes in maize have been revealed and the relationships among these genes have been partially uncovered. Based on the knowledge of the flowering time candidate genes, a conceptual gene regulatory network model for the genetic control of flowering time in maize is proposed. To demonstrate the potential of the proposed gene regulatory network model, a first attempt was made to develop a dynamic gene network model to predict flowering time of maize genotypes varying for specific genes. The dynamic gene network model is composed of four genes and was built on the basis of gene expression dynamics of the two late flowering id1 and dlf1 mutants, the early flowering landrace Gaspe Flint and the temperate inbred B73. The model was evaluated against the phenotypic data of the id1 dlf1 double mutant and the ZMM4 overexpressed transgenic lines. The model provides a working example that leverages knowledge from model organisms for the utilization of maize genomic information to predict a whole plant trait phenotype, flowering time, of maize genotypes.

  19. Human sterol regulatory element-binding protein 1a contributes significantly to hepatic lipogenic gene expression.

    Science.gov (United States)

    Bitter, Andreas; Nüssler, Andreas K; Thasler, Wolfgang E; Klein, Kathrin; Zanger, Ulrich M; Schwab, Matthias; Burk, Oliver

    2015-01-01

    Sterol regulatory element-binding protein (SREBP) 1, the master regulator of lipogenesis, was shown to be associated with non-alcoholic fatty liver disease, which is attributed to its major isoform SREBP1c. Based on studies in mice, the minor isoform SREBP1a is regarded as negligible for hepatic lipogenesis. This study aims to elucidate the expression and functional role of SREBP1a in human liver. mRNA expression of both isoforms was quantified in cohorts of human livers and primary human hepatocytes. Hepatocytes were treated with PF-429242 to inhibit the proteolytic activation of SREBP precursor protein. SREBP1a-specifc and pan-SREBP1 knock-down were performed by transfection of respective siRNAs. Lipogenic SREBP-target gene expression was analyzed by real-time RT-PCR. In human liver, SREBP1a accounts for up to half of the total SREBP1 pool. Treatment with PF-429242 indicated SREBP-dependent auto-regulation of SREBP1a, which however was much weaker than of SREBP1c. SREBP1a-specifc knock-down also reduced significantly the expression of SREBP1c and of SREBP-target genes. Regarding most SREBP-target genes, simultaneous knock-down of both isoforms resulted in effects of only similar extent as SREBP1a-specific knock-down. We here showed that SREBP1a is significantly contributing to the human hepatic SREBP1 pool and has a share in human hepatic lipogenic gene expression. © 2015 S. Karger AG, Basel.

  20. Human Sterol Regulatory Element-Binding Protein 1a Contributes Significantly to Hepatic Lipogenic Gene Expression

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    Andreas Bitter

    2015-01-01

    Full Text Available Background/Aims: Sterol regulatory element-binding protein (SREBP 1, the master regulator of lipogenesis, was shown to be associated with non-alcoholic fatty liver disease, which is attributed to its major isoform SREBP1c. Based on studies in mice, the minor isoform SREBP1a is regarded as negligible for hepatic lipogenesis. This study aims to elucidate the expression and functional role of SREBP1a in human liver. Methods: mRNA expression of both isoforms was quantified in cohorts of human livers and primary human hepatocytes. Hepatocytes were treated with PF-429242 to inhibit the proteolytic activation of SREBP precursor protein. SREBP1a-specifc and pan-SREBP1 knock-down were performed by transfection of respective siRNAs. Lipogenic SREBP-target gene expression was analyzed by real-time RT-PCR. Results: In human liver, SREBP1a accounts for up to half of the total SREBP1 pool. Treatment with PF-429242 indicated SREBP-dependent auto-regulation of SREBP1a, which however was much weaker than of SREBP1c. SREBP1a-specifc knock-down also reduced significantly the expression of SREBP1c and of SREBP-target genes. Regarding most SREBP-target genes, simultaneous knock-down of both isoforms resulted in effects of only similar extent as SREBP1a-specific knock-down. Conclusion: We here showed that SREBP1a is significantly contributing to the human hepatic SREBP1 pool and has a share in human hepatic lipogenic gene expression.

  1. Molecular Data are Transforming Hypotheses on the Origin and Diversification of Eukaryotes.

    Science.gov (United States)

    Tekle, Yonas I; Parfrey, Laura Wegener; Katz, Laura A

    2009-06-01

    The explosion of molecular data has transformed hypotheses on both the origin of eukaryotes and the structure of the eukaryotic tree of life. Early ideas about the evolution of eukaryotes arose through analyses of morphology by light microscopy and later electron microscopy. Though such studies have proven powerful at resolving more recent events, theories on origins and diversification of eukaryotic life have been substantially revised in light of analyses of molecular data including gene and, increasingly, whole genome sequences. By combining these approaches, progress has been made in elucidating both the origin and diversification of eukaryotes. Yet many aspects of the evolution of eukaryotic life remain to be illuminated.

  2. A Gene Regulatory Network Cooperatively Controlled by Pdx1 and Sox9 Governs Lineage Allocation of Foregut Progenitor Cells

    DEFF Research Database (Denmark)

    Shih, Hung Ping; Seymour, Philip A; Patel, Nisha A

    2015-01-01

    The generation of pancreas, liver, and intestine from a common pool of progenitors in the foregut endoderm requires the establishment of organ boundaries. How dorsal foregut progenitors activate pancreatic genes and evade the intestinal lineage choice remains unclear. Here, we identify Pdx1 and Sox......9 as cooperative inducers of a gene regulatory network that distinguishes the pancreatic from the intestinal lineage. Genetic studies demonstrate dual and cooperative functions for Pdx1 and Sox9 in pancreatic lineage induction and repression of the intestinal lineage choice. Pdx1 and Sox9 bind...... to regulatory sequences near pancreatic and intestinal differentiation genes and jointly regulate their expression, revealing direct cooperative roles for Pdx1 and Sox9 in gene activation and repression. Our study identifies Pdx1 and Sox9 as important regulators of a transcription factor network that initiates...

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

    Science.gov (United States)

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

    2017-05-01

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

  4. 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

  5. Steroidogenic acute regulatory protein (StAR) gene expression construct: Development, nanodelivery and effect on reproduction in air-breathing catfish, Clarias batrachus.

    Science.gov (United States)

    Rathor, Pravesh Kumar; Bhat, Irfan Ahmad; Rather, Mohd Ashraf; Gireesh-Babu, Pathakota; Kumar, Kundan; Purayil, Suresh Babu Padinhate; Sharma, Rupam

    2017-11-01

    Steroidogenic acute regulatory protein (StAR) is responsible for the relocation of cholesterol across mitochondrial membrane in vertebrates and is, therefore, a key factor in regulating the rate and timing of steroidogenesis. In the present study, we developed chitosan nanoparticle (CNP) conjugated StAR gene construct (CNP-pcDNA4-StAR) in a eukaryotic expression vector, pcDNA4/HisMax A. CNPs of 135.4nm diameter, 26.7mV zeta potential and 0.381 polydispersity index were used for conjugation. The loading efficiency (LE) of pcDNA4-StAR construct with CNPs was found to be 86%. After the 24h of intramuscular injection, the CNP-pcDNA4-StAR plasmid could be detected from testis, brain, kidney and muscle tissues of Clarias batrachus. The transcript levels of important reproductive genes viz. cyp11a1, cyp17a1, 3β-hsd, 17β-hsd and cyp19a1 in CNP-pcDNA4-StAR treated group were initially low up to 24h, but significantly increased subsequently up to 120h. In naked pcDNA4-StAR treated group, the mRNA level of 3β-hsd, 17β-hsd and cyp19a1 increased initially up to 24h, while cyp11a1 and cyp17a1 increased up to 48h and then started declining. Similar results were obtained for 11-Ketotestosterone and 17β-estradiol. The results indicate relatively long lasting effects of nano-conjugated construct compared to the construct alone. Furthermore, the histopathology of gonads and liver authenticates its possible role in the gonadal development in fish without any adverse effect. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Functional conservation between rodents and chicken of regulatory sequences driving skeletal muscle gene expression in transgenic chickens

    Directory of Open Access Journals (Sweden)

    Taylor Lorna

    2010-02-01

    Full Text Available Abstract Background Regulatory elements that control expression of specific genes during development have been shown in many cases to contain functionally-conserved modules that can be transferred between species and direct gene expression in a comparable developmental pattern. An example of such a module has been identified at the rat myosin light chain (MLC 1/3 locus, which has been well characterised in transgenic mouse studies. This locus contains two promoters encoding two alternatively spliced isoforms of alkali myosin light chain. These promoters are differentially regulated during development through the activity of two enhancer elements. The MLC3 promoter alone has been shown to confer expression of a reporter gene in skeletal and cardiac muscle in transgenic mice and the addition of the downstream MLC enhancer increased expression levels in skeletal muscle. We asked whether this regulatory module, sufficient for striated muscle gene expression in the mouse, would drive expression in similar domains in the chicken. Results We have observed that a conserved downstream MLC enhancer is present in the chicken MLC locus. We found that the rat MLC1/3 regulatory elements were transcriptionally active in chick skeletal muscle primary cultures. We observed that a single copy lentiviral insert containing this regulatory cassette was able to drive expression of a lacZ reporter gene in the fast-fibres of skeletal muscle in chicken in three independent transgenic chicken lines in a pattern similar to the endogenous MLC locus. Reporter gene expression in cardiac muscle tissues was not observed for any of these lines. Conclusions From these results we conclude that skeletal expression from this regulatory module is conserved in a genomic context between rodents and chickens. This transgenic module will be useful in future investigations of muscle development in avian species.

  7. Modeling the zebrafish segmentation clock's gene regulatory network constrained by expression data suggests evolutionary transitions between oscillating and nonoscillating transcription.

    Science.gov (United States)

    Schwendinger-Schreck, Jamie; Kang, Yuan; Holley, Scott A

    2014-06-01

    During segmentation of vertebrate embryos, somites form in accordance with a periodic pattern established by the segmentation clock. In the zebrafish (Danio rerio), the segmentation clock includes six hairy/enhancer of split-related (her/hes) genes, five of which oscillate due to negative autofeedback. The nonoscillating gene hes6 forms the hub of a network of 10 Her/Hes protein dimers, which includes 7 DNA-binding dimers and 4 weak or non-DNA-binding dimers. The balance of dimer species is critical for segmentation clock function, and loss-of-function studies suggest that the her genes have both unique and redundant functions within the clock. However, the precise regulatory interactions underlying the negative feedback loop are unknown. Here, we combine quantitative experimental data, in silico modeling, and a global optimization algorithm to identify a gene regulatory network (GRN) designed to fit measured transcriptional responses to gene knockdown. Surprisingly, we find that hes6, the clock gene that does not oscillate, responds to negative feedback. Consistent with prior in silico analyses, we find that variation in transcription, translation, and degradation rates can mediate the gain and loss of oscillatory behavior for genes regulated by negative feedback. Extending our study, we found that transcription of the nonoscillating Fgf pathway gene sef responds to her/hes perturbation similarly to oscillating her genes. These observations suggest a more extensive underlying regulatory similarity between the zebrafish segmentation clock and the mouse and chick segmentation clocks, which exhibit oscillations of her/hes genes as well as numerous other Notch, Fgf, and Wnt pathway genes. Copyright © 2014 by the Genetics Society of America.

  8. Endosymbiotic theories for eukaryote origin.

    Science.gov (United States)

    Martin, William F; Garg, Sriram; Zimorski, Verena

    2015-09-26

    For over 100 years, endosymbiotic theories have figured in thoughts about the differences between prokaryotic and eukaryotic cells. More than 20 different versions of endosymbiotic theory have been presented in the literature to explain the origin of eukaryotes and their mitochondria. Very few of those models account for eukaryotic anaerobes. The role of energy and the energetic constraints that prokaryotic cell organization placed on evolutionary innovation in cell history has recently come to bear on endosymbiotic theory. Only cells that possessed mitochondria had the bioenergetic means to attain eukaryotic cell complexity, which is why there are no true intermediates in the prokaryote-to-eukaryote transition. Current versions of endosymbiotic theory have it that the host was an archaeon (an archaebacterium), not a eukaryote. Hence the evolutionary history and biology of archaea increasingly comes to bear on eukaryotic origins, more than ever before. Here, we have compiled a survey of endosymbiotic theories for the origin of eukaryotes and mitochondria, and for the origin of the eukaryotic nucleus, summarizing the essentials of each and contrasting some of their predictions to the observations. A new aspect of endosymbiosis in eukaryote evolution comes into focus from these considerations: the host for the origin of plastids was a facultative anaerobe. © 2015 The Authors.

  9. Endosymbiotic theories for eukaryote origin

    Science.gov (United States)

    Martin, William F.; Garg, Sriram; Zimorski, Verena

    2015-01-01

    For over 100 years, endosymbiotic theories have figured in thoughts about the differences between prokaryotic and eukaryotic cells. More than 20 different versions of endosymbiotic theory have been presented in the literature to explain the origin of eukaryotes and their mitochondria. Very few of those models account for eukaryotic anaerobes. The role of energy and the energetic constraints that prokaryotic cell organization placed on evolutionary innovation in cell history has recently come to bear on endosymbiotic theory. Only cells that possessed mitochondria had the bioenergetic means to attain eukaryotic cell complexity, which is why there are no true intermediates in the prokaryote-to-eukaryote transition. Current versions of endosymbiotic theory have it that the host was an archaeon (an archaebacterium), not a eukaryote. Hence the evolutionary history and biology of archaea increasingly comes to bear on eukaryotic origins, more than ever before. Here, we have compiled a survey of endosymbiotic theories for the origin of eukaryotes and mitochondria, and for the origin of the eukaryotic nucleus, summarizing the essentials of each and contrasting some of their predictions to the observations. A new aspect of endosymbiosis in eukaryote evolution comes into focus from these considerations: the host for the origin of plastids was a facultative anaerobe. PMID:26323761

  10. Global characterization of interferon regulatory factor (IRF genes in vertebrates: Glimpse of the diversification in evolution

    Directory of Open Access Journals (Sweden)

    Xu Zhen

    2010-05-01

    Full Text Available Abstract Background Interferon regulatory factors (IRFs, which can be identified based on a unique helix-turn-helix DNA-binding domain (DBD are a large family of transcription factors involved in host immune response, haemotopoietic differentiation and immunomodulation. Despite the identification of ten IRF family members in mammals, and some recent effort to identify these members in fish, relatively little is known in the composition of these members in other classes of vertebrates, and the evolution and probably the origin of the IRF family have not been investigated in vertebrates. Results Genome data mining has been performed to identify any possible IRF family members in human, mouse, dog, chicken, anole lizard, frog, and some teleost fish, mainly zebrafish and stickleback, and also in non-vertebrate deuterostomes including the hemichordate, cephalochordate, urochordate and echinoderm. In vertebrates, all ten IRF family members, i.e. IRF-1 to IRF-10 were identified, with two genes of IRF-4 and IRF-6 identified in fish and frog, respectively, except that in zebrafish exist three IRF-4 genes. Surprisingly, an additional member in the IRF family, IRF-11 was found in teleost fish. A range of two to ten IRF-like genes were detected in the non-vertebrate deuterostomes, and they had little similarity to those IRF family members in vertebrates as revealed in genomic structure and in phylogenetic analysis. However, the ten IRF family members, IRF-1 to IRF-10 showed certain degrees of conservation in terms of genomic structure and gene synteny. In particular, IRF-1, IRF-2, IRF-6, IRF-8 are quite conserved in their genomic structure in all vertebrates, and to a less degree, some IRF family members, such as IRF-5 and IRF-9 are comparable in the structure. Synteny analysis revealed that the gene loci for the ten IRF family members in vertebrates were also quite conservative, but in zebrafish conserved genes were distributed in a much longer distance in

  11. PRMT1 mediated methylation of TAF15 is required for its positive gene regulatory function

    Energy Technology Data Exchange (ETDEWEB)

    Jobert, Laure; Argentini, Manuela [Institut de Genetique et de Biologie Moleculaire et Cellulaire (IGBMC), CNRS UMR 7104, INSERM U 596, Universite Louis Pasteur de Strasbourg, BP 10142 - 67404 Illkirch Cedex, CU de Strasbourg (France); Tora, Laszlo, E-mail: laszlo@igbmc.u-strasbg.fr [Institut de Genetique et de Biologie Moleculaire et Cellulaire (IGBMC), CNRS UMR 7104, INSERM U 596, Universite Louis Pasteur de Strasbourg, BP 10142 - 67404 Illkirch Cedex, CU de Strasbourg (France)

    2009-04-15

    TAF15 (formerly TAF{sub II}68) is a nuclear RNA-binding protein that is associated with a distinct population of TFIID and RNA polymerase II complexes. TAF15 harbours an N-terminal activation domain, an RNA recognition motif (RRM) and many Arg-Gly-Gly (RGG) repeats at its C-terminal end. The N-terminus of TAF15 serves as an essential transforming domain in the fusion oncoprotein created by chromosomal translocation in certain human chondrosarcomas. Post-transcriptional modifications (PTMs) of proteins are known to regulate their activity, however, nothing is known on how PTMs affect TAF15 function. Here we demonstrate that endogenous human TAF15 is methylated in vivo at its numerous RGG repeats. Furthermore, we identify protein arginine N-methyltransferase 1 (PRMT1) as a TAF15 interactor and the major PRMT responsible for its methylation. In addition, the RGG repeat-containing C-terminus of TAF15 is responsible for the shuttling between the nucleus and the cytoplasm and the methylation of RGG repeats affects the subcellular localization of TAF15. The methylation of TAF15 by PRMT1 is required for the ability of TAF15 to positively regulate the expression of the studied endogenous TAF15-target genes. Our findings demonstrate that arginine methylation of TAF15 by PRMT1 is a crucial event determining its proper localization and gene regulatory function.

  12. Structure and function of eukaryotic chromosomes

    Energy Technology Data Exchange (ETDEWEB)

    Hennig, W.

    1987-01-01

    Contents: Introduction; Polytene Chromosomel Giant Chromosomes in Ciliates; The sp-I Genes in the Balbiani Rings of Chironomus Salivary Glands; The White Locus of Drosophila Melanogaster; The Genetic and Molecular Organization of the Dense Cluster of Functionally Related Vital Genes in the DOPA Decarboxylase Region of the Drosophila melanogaster Genome; Heat Shock Puffs and Response to Environmental Stress; The Y Chromosomal Lampbrush Loops of Drosophila; Contributions of Electron Microscopic Spreading Preparations (''Miller Spreads'') to the Analysis of Chromosome Structure; Replication of DNA in Eukaryotic Chromosomes; Gene Amplification in Dipteran Chromosomes; The Significance of Plant Transposable Elements in Biologically Relevant Processes; Arrangement of Chromosomes in Interphase Cell Nuclei; Heterochromatin and the Phenomenon of Chromosome Banding; Multiple Nonhistone Protein-DNA Complexes in Chromatin Regulate the Cell- and Stage-Specific Activity of an Eukaryotic Gene; Genetics of Sex Determination in Eukaryotes; Application of Basic Chromosome Research in Biotechnology and Medicine. This book presents an overview of various aspects of chromosome research.

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

    Science.gov (United States)

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

    2015-01-01

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

  14. 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.

  15. Arabidopsis CPR5 is a senescence-regulatory gene with pleiotropic functions as predicted by the evolutionary theory of senescence

    NARCIS (Netherlands)

    Jing, Hai-Chun; Anderson, Lisa; Sturre, Marcel J. G.; Hille, Jacques; Dijkwel, Paul P.

    2007-01-01

    Arabidopsis CPR5 is a senescence-regulatory gene with pleiotropic functions as predicted by the evolutionary theory of senescence Hai-Chun Jing1,2, Lisa Anderson3, Marcel J.G. Sturre1, Jacques Hille1 and Paul P. Dijkwel1,* 1Molecular Biology of Plants, Groningen Biomolecular Sciences and

  16. Human Retrotransposon Insertion Polymorphisms Are Associated with Health and Disease via Gene Regulatory Phenotypes

    Directory of Open Access Journals (Sweden)

    Lu Wang

    2017-08-01

    Full Text Available The human genome hosts several active families of transposable elements (TEs, including the Alu, LINE-1, and SVA retrotransposons that are mobilized via reverse transcription of RNA intermediates. We evaluated how insertion polymorphisms generated by human retrotransposon activity may be related to common health and disease phenotypes that have been previously interrogated through genome-wide association studies (GWAS. To address this question, we performed a genome-wide screen for retrotransposon polymorphism disease associations that are linked to TE induced gene regulatory changes. Our screen first identified polymorphic retrotransposon insertions found in linkage disequilibrium (LD with single nucleotide polymorphisms that were previously associated with common complex diseases by GWAS. We further narrowed this set of candidate disease associated retrotransposon polymorphisms by identifying insertions that are located within tissue-specific enhancer elements. We then performed expression quantitative trait loci analysis on the remaining set of candidates in order to identify polymorphic retrotransposon insertions that are associated with gene expression changes in B-cells of the human immune system. This progressive and stringent screen yielded a list of six retrotransposon insertions as the strongest candidates for TE polymorphisms that lead to disease via enhancer-mediated changes in gene regulation. For example, we found an SVA insertion within a cell-type specific enhancer located in the second intron of the B4GALT1 gene. B4GALT1 encodes a glycosyltransferase that functions in the glycosylation of the Immunoglobulin G (IgG antibody in such a way as to convert its activity from pro- to anti-inflammatory. The disruption of the B4GALT1 enhancer by the SVA insertion is associated with down-regulation of the gene in B-cells, which would serve to keep the IgG molecule in a pro-inflammatory state. Consistent with this idea, the B4GALT1 enhancer

  17. A Novel Cellular Senescence Gene, SENEX, Is Involved in Peripheral Regulatory T Cells Accumulation in Aged Urinary Bladder Cancer

    Science.gov (United States)

    Chen, Tianping; Wang, Huiping; Zhang, Zhiqiang; Li, Qing; Yan, Kaili; Tao, Qianshan; Ye, Qianling; Xiong, Shudao; Wang, Yiping; Zhai, Zhimin

    2014-01-01

    Regulatory T cells (Tregs) play an essential role in sustaining self-tolerance and immune homeostasis. Despite many studies on the correlation between Tregs accumulation and age, or malignancies, the related mechanism hasn’t been well explored. To find out the mechanism of Tregs accumulation in aged urinary bladder cancer, we examined the novel cellular senesence gene SENEX and relevant apoptosis gene mRNA expression in sorted CD4+CD25hi Tregs from aged UBC donors, evaluated serum cytokine profiles related to tumor immunopathology, and further explored the relationship between SENEX expression, apoptosis gene expression and cytokine secretion. After having silenced down SENEX gene expression with RNA interference, we also evaluated the cellular apoptosis of Tregs sorted from aged UBC patients in response to H2O2-mediated stress. Our data indicated that upregulated SENEX mRNA expression in Tregs of aged UBC patients was correlated with pro-apoptotic gene expression and cytokine concentration. Silencing SENEX gene expression increased cellular apoptosis and pro-apoptotic gene expression of Tregs, in response to H2O2-mediated stress. Upregulated SENEX mRNA expression together with decreased pro-apoptotic gene expression and disturbances in cytokines synthesis may contribute to the Tregs proliferation and promote tumorigenesis and metastasis. Overall, upregulation of cellular senescence gene SENEX, was associated to regulatory T cells accumulation in aged urinary bladder cancer. Our study provides a new insight into understanding of peripheral Tregs accumulation in aged malignancies. PMID:24505313

  18. Radiation and the regulatory landscape of neo2-Darwinism.

    Science.gov (United States)

    Rollo, C David

    2006-05-11

    Several recently revealed features of eukaryotic genomes were not predicted by earlier evolutionary paradigms, including the relatively small number of genes, the very large amounts of non-functional code and its quarantine in heterochromatin, the remarkable conservation of many functionally important genes across relatively enormous phylogenetic distances, and the prevalence of extra-genomic information associated with chromatin structure and histone proteins. All of these emphasize a paramount role for regulatory evolution, which is further reinforced by recent perspectives highlighting even higher-order regulation governing epigenetics and development (EVO-DEVO). Modern neo2-Darwinism, with its emphasis on regulatory mechanisms and regulatory evolution provides new vision for understanding radiation biology, particularly because free radicals and redox states are central to many regulatory mechanisms and free radicals generated by radiation mimic and amplify endogenous signalling. This paper explores some of these aspects and their implications for low-dose radiation biology.

  19. A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Xiangyun Xiao

    Full Text Available The reconstruction of gene regulatory networks (GRNs from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM, experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.

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

    Directory of Open Access Journals (Sweden)

    Ellen L Goode

    Ful